Can Bureaucrats Really Be Paid Like Ceos? Substitution Between Incentives and Resources Among School Administrators in China

Renfu Luo; Grant Miller; Scott Rozelle; Sean Sylvia; Marcos Vera-Hernández

doi:10.1093/jeea/jvy047

Can Bureaucrats Really Be Paid Like Ceos? Substitution Between Incentives and Resources Among School Administrators in China

Luo, Renfu; Miller, Grant; Rozelle, Scott; Sylvia, Sean; Vera-Hernández, Marcos 2020-02-01 00:00:00 Unlike performance incentives for private sector managers, little is known about performance incentives for managers in public sector bureaucracies. Through a randomized trial in rural China, we study performance incentives rewarding school administrators for reducing student anemia— as well as complementarity between incentives and orthogonally assigned discretionary resources. Large (but not small) incentives and unrestricted grants both reduced anemia, but incentives were more cost-effective. Although unrestricted grants and small incentives do not interact, grants fully crowd-out the effect of larger incentives. Our ﬁndings suggest that performance incentives can be effective in bureaucratic environments, but they are not complementary to discretionary resources. (JEL:O15, I12, H40, M52) The editor in charge of this paper was M. Daniele Paserman. Acknowledgments: Soledad Giardili and Ravi Somani provided excellent research assistance. We are grateful to Dana Andersen, Antonio Cabrales, Syngjoo Choi, Adeline Delavande, Katherine Donato, Will Dow, Eric French, Vivian Hoffmann, Rob Jensen, Victor Lavy, Hamish Low, Aprajit Mahajan, David Perez- ´ Castrillo, Ian Preston, Carol Propper, Imran Rasul, Pedro Rey-Biel, and Alessandro Tarozzi for helpful comments. We are also grateful to the National Institutes of Health (Grant Number: R01 HL106023), the Economic and Social Research Council via the ESRC-funded Centre for the Microeconomic Analysis of Public Policy (grant reference ES/H021221/1) at the Institute for Fiscal Studies, as well as the Global Under-Development Action Fund the Walter H. Shorenstein Asia-Paciﬁc Research Center at Stanford University for ﬁnancial support. Miller is a Research Associate at NBER. Marcos Vera-Hernandez ´ is a Research Fellow at the Institute for Fiscal Studies. E-mail: [email protected] (Luo); [email protected] (Miller); [email protected] (Rozelle); sean [email protected] (Sylvia); [email protected] (Vera-Hernandez) ´ Journal of the European Economic Association 2020 18(1):165–201 DOI: 10.1093/jeea/jvy047 The Author(s) 2019. Published by Oxford University Press on behalf of European Economic Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 166 Journal of the European Economic Association 1. Introduction The provision of public services in many developing countries is low in quality (Banerjee, Deaton, and Duﬂo 2004; World Bank 2004; Das, Hammer, and Leonard 2008; Berendes et al. 2011). Although the underlying reasons are complex and incompletely understood, the culprit is not simply lack of resources, inadequate training, or deﬁciencies in provider knowledge. Supply-side incentives are also often poorly aligned with social objectives. Absenteeism in many parts of the world is pervasive (Chaudhury and Hammer 2004; Kremer et al. 2005; Banerjee and Duﬂo 2006; Chaudhury et al. 2006;Lewis 2006), and providers often fail to do in practice what is within their knowledge and means (Das and Hammer 2004;Alcazar ´ et al. 2006; Chaudhury et al. 2006; Das and Hammer 2007; Leonard and Masatu 2010;Das et al. 2012; Sylvia et al. 2015). To better align provider incentives with social objectives, performance pay has become increasingly common in public sector service delivery (Oxman and Fretheim 2008; Eichler and Levine 2009; Miller and Babiarz 2014). Drawing on the logic of performance pay in human resource management (Lazear 1995; Hall and Liebman 1998; Lazear 2000), this approach provides direct ﬁnancial rewards for achieving prespeciﬁed performance targets. Despite its growing prominence, however, there is remarkably little empirical evidence on basic mechanism design considerations in the use of performance pay to improve public service delivery (Miller and Babiarz 2014). This paper contributes to the literature on performance pay in developing countries—and in particular, its design—through a large-scale experiment studying the interaction of performance incentives and unconditional block grants, both of varying sizes, for public sector administrators. Speciﬁcally, we provide primary school administrators (lead principals who are the managers and executive decision-makers in schools—hereafter “administrators”) with randomly assigned budget transfers (large and small) and randomly assigned ﬁnancial incentives (large and small) for improving the health of their students. Our health focus is anemia, a leading child health problem in rural China. Our study yields four key ﬁndings. First, we ﬁnd that larger incentives for anemia reduction were effective when administrators had fewer resources at their disposal for implementing the program. Incentives that provided substantial additional income to administrators (mean realized payouts of about 2 months of annual salary) reduced anemia among students who were anemic at baseline by 13.8 percentage points (or 38%). Second, in contrast, small incentives (one tenth the size of the larger incentives) were ineffective in reducing anemia—and were signiﬁcantly less effective than large incentives. Third, even absent explicit incentives, unrestricted budget transfers to school administrators led to sizeable reductions in anemia, suggesting other motives among administrators to allocate resources toward student nutrition. However, the 1. Previous studies have shown anemia rates among primary school aged students in poor regions of western China to be around 30% on average (Luo et al. 2011; Miller et al. 2012). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 167 resource cost of reducing anemia through larger school budgets was approximately twice as great (per case of anemia averted) as combining larger performance incentives with smaller budgets—implying that school administrators with explicit ﬁnancial incentives used smaller budgets with greater productive efﬁciency. Finally, we ﬁnd that explicit ﬁnancial incentives and unrestricted grants can be strong substitutes—and whether or not they are depends critically on incentive size. Speciﬁcally, we ﬁnd that large incentives and grants are pronounced substitutes. The effect is particularly strong: unrestricted resource transfers (of sizes chosen by government planners in practice) crowd-out the effect of large incentives. Importantly, we ﬁnd this pattern of results not only with student nutritional outcomes, but also with intermediate measures of resource allocation and effort (e.g., the provision of better nutrition and effort to persuade parents to improve their children’s diets at home). Substitution therefore reﬂects reductions in administrator effort with larger budgets (and not simply decreasing marginal returns to inputs in the biological production of child nutrition). Our ﬁndings contribute to existing literature on performance incentives in several ways. First, previous studies on the role of performance pay in the public sector have generally focused on front-line workers rather than public sector managers (or “bureaucrats”—an exception is Rasul and Rogger 2018). However, the scope of behavioral responses among managers is potentially much broader, possibly with greater potential for improving public sector service delivery. Speciﬁcally, rather than simply increasing effort, the actions of managers can have greater inﬂuence on productive and allocative efﬁciency because of the resources under over which they have decision-making authority (Holmstrom and Ricart i Costa 1986; Athey and Roberts 2001; Bandiera, Barankay, and Rasul 2007; Burgess et al. 2010). Second, existing studies of performance pay for managers generally examine the private sector, but insights from this literature cannot be easily extrapolated to 2. One concern in this context may be multitasking–in particular, whether or not incentives to reduce anemia led schools to focus on anemia reduction at the expense of teaching. In a separate analysis of multitasking effects, we ﬁnd no evidence that these incentives led to a reduction in student test scores on standardized Math and Chinese exams designed by the research team based on the national curriculum and designed to have good psychometric properties. However, we do ﬁnd some evidence of multitasking on margins of teaching where the costs to administrators and teachers of diverting effort are lower (i.e., tasks that would likely be the ﬁrst source of diverted effort). For example, in “secondary subjects” (subjects other than math or Chinese, which are not a focus of high school entrance exams and hence given less weight in the curriculum) we ﬁnd evidence of diverted effort when children were taught these subjects by a homeroom teacher (who was often given responsibilities related to the anemia program). 3. Several recent studies have examined performance pay provided as personal income to front line workers in the health and education sectors, including Lavy (2002, 2009), Glewwe et al. (2010), Muralidharan and Sundararaman (2011), Duﬂo et al. (2012), Ashraf et al. (2014), and Behrman et al. (2015). Other recent studies have focused on incentives to institutions paid as budget revenue. These include Bloom et al. (2006), Basinga et al. (2011), Gertler and Vermeersch (2012), Olken, Onishi, and Wong (2014), and Yip et al. (2014). Behrman et al. (2015) also study incentives for school administrators, but bundled with incentives to students and teachers. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 168 Journal of the European Economic Association bureaucracies. Career concerns can be particularly strong in bureaucracies—and they may overpower or interact with incentives created by performance pay (Gibbons and Murphy 1992). Moreover, civil servants may be considerably more prosocially or intrinsically motivated (Francois 2000; Francois and Vlassopoulos 2008; Tonin and Vlassopoulos 2015)—and performance pay may dampen the effects of these motivations (see Fehr and Falk 2002; Gneezy, Meier, and Rey-Biel 2011; Kamenica 2012 for reviews). Finally, public sector production processes tend to be both more complex (due to multiple objectives and multiple agents—Dixit (2002)) and more heterogeneous (due to a primary goal being to expand access, which necessitates operation in a wider range of contexts than private sector organizations that have more scope to select the markets in which they operate). Performance pay may therefore be ineffective if rewards are not well-aligned with effective inputs across the range of contexts within which an organization operates. Third, we contribute to existing literature by studying three mechanism design considerations of performance pay. One is that we reward outputs directly. In contrast to rewarding inputs, performance incentives for outputs strengthens incentives for managers to draw on local information and contextual knowledge to improve both allocative and productive efﬁciency—or to “innovate.” Our study is one of the ﬁrst focused on health to reward health outputs—and we do indeed ﬁnd evidence of managerial innovation (school administrators successfully work with parents to improve diets at home). Another is that we directly study differential behavioral responses to performance incentives of varying sizes. Existing literature on this issue is split: a number of studies outside of organizational settings report large responses to very modest rewards (as well as highly elastic demand at prices close to zero), whereas others suggest small responses—or even reductions in effort (e.g. when intrinsic motivation is crowded-out). Our results are more closely aligned with the latter. Finally, we provide ﬁrst evidence on how incentives interact with the amount of resources under contracted agents’ control. A common focus is on the relative effects of 4. On performance pay for corporate executives and private sector managers in developed countries, see Jensen and Murphy (1990), Hall and Liebman (1998), Murphy (1999), Hall and Murphy (2003), and Oyer and Schaefer (2005). Bandiera et al. (2007) and Bloom et al. (2013) study these virtues of performance pay for private sector managers in developing countries. Burgess et al. (2010) study a team- based incentive scheme in the context of a government agency in the United Kingdom; although the scheme was not explicitly targeted to managers, the authors ﬁnd that the team-based incentive induced managers to reallocate more efﬁcient workers to incentivized tasks. 5. The two exceptions of which we are aware are Singh (2015) and Miller et al. (2012). Though not studying the health impacts of incentives tied to health outcomes, Leonard (2003) studies traditional healers’ use of outcome-contingent contracts in Cameroun. In the education sector, performance pay rewarding good test scores is more common (Lavy 2009; Muralidharan and Sundararaman 2011; Behrman et al. 2015). 6. Kremer and Miguel (2007), Thornton (2008), Banerjee et al. (2010), Cohen and Dupas (2010), Karlan, List, and Shaﬁr (2011), Duﬂo, Kremer, and Robinson (2011). 7. See Gneezy, Meier, and Rey-Biel (2011) for several examples. 8. We also note at least two key differences with this previous literature: one is that receiving incentive payments in our study required sustained behavior change (reducing iron deﬁciency anemia requires several Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 169 incentive and resource-based approaches (see Lavy 2002; Hanushek 2006); however, these two approaches are often implemented simultaneously and are likely to interact in important ways. Theoretically, incentives and resources available to managers can be complements or substitutes. We study this issue both theoretically and empirically, ﬁnd evidence of strong substitution when incentives and budgets are large. The rest of this paper is organized as follows. Section 2 presents a conceptual framework for understanding school administrators’ behavioral responses to output- based performance incentives. Section 3 provides background on school-based nutrition programs as well as the causes and consequences of anemia. Section 4 describes our experimental design, data collection, and methods. Section 5 reports our results, and Section 6 concludes. 2. Conceptual Framework In this section, we propose a simple model of the school administrator decision problem that we study. Speciﬁcally, we consider the inﬂuence of both output-based performance incentives and discretionary resources on organizational effort—as well as how they interact (i.e., if they are substitutes or complements). We model the school administrator (bureaucrat) as choosing effort e to reduce anemia in the school. Additionally, the school administrator also decides on the allocation of resources—in particular, how to divide the school budget G between anemia reduction A and other school functions G A. The health production function f(e, A) combines the school administrator’s effort e and the funds allocated to reducing anemia A in determining student health H. The school administrator’s maximization problem is therefore max w C H v .e/ C S .G A/ (1) e;A subj: toW w D tH C m; (2) H D f .e; A/ ; (3) G A (4) Total take-home pay w includes both base pay m and a reward or bonus for improving student health, tH, which is the product of t, the marginal bonus, and H, the net gain in student health (in our case, the net reduction in the number of students with 0 00 anemia). Disutility of effort, v(e), is also strictly increasing but convex: v > 0, v 0. The parameter , which is non-negative, allows the school administrator to be altruistic, deriving direct utility from student health (prosociality and public service motivation months of dietary chance), and another is that because all school administrators receive information about anemia, the presence of incentives may not alter its salience as much (Benhassine et al. 2015). 9. See Rogger (2014)and Nath (2015) for other models of bureaucratic behavior with choices of effort. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 170 Journal of the European Economic Association are often considered important among public sector workers—e.g., see Besley and Ghatak 2007;DalBo, ´ Finan, and Rossi 2013). The school administrator also derives utility from school functions unrelated to health, S(G A), which is also assumed 0 0 to be increasing (S > 0) and concave (S 0). We make standard assumptions that the health production function, f(e, A), is increasing in both arguments and concave (f > 0, f < 0, f > 0, f < 0, f f f 0) and the intuitive assumption that e ee A AA ee AA eA f 0, or that the marginal productivity of one input is nondecreasing in the level of eA the other input. Assuming an interior solution, the solution to (1)–(4) is equivalent to the solution to max . C t / f .e; A/ v .e/ C S .G A/ : (5) e;A The ﬁrst order conditions are U . C t / f .e; A/ v .e/ D 0; (6) e e U . C t / f .e; A/ S .G A/ D 0: (7) A A The ﬁrst order condition (6) implies that the optimal level of effort equates the marginal beneﬁt of increasing effort (the increase in health, f (e, A), multiplied by t C , reﬂecting both the increase in take-home pay and the altruistic increase in direct utility) with its marginal cost. Equivalently, the ﬁrst order condition (7) implies that resources G are invested in activities unrelated to nutrition up to the point that its marginal beneﬁt, S (G A), equals the marginal beneﬁt of investing in nutrition-related activities, ( C t)f (e, A). The second order conditions required for a maximum are U . C t / f .e; A/ v <0; (8) ee ee U . C t / f .e; A/ C S <0; (9) AA AA jH j U U U >0; where U . C t / f : (10) ee AA eA eA eA 2.1. Comparative Statics We analyze how the school administrator’s choice of effort and resources dedicated to nutrition changes both with incentives t and discretionary resources G—both separately and in combination (as we study empirically through our experiment). First, we consider each effect separately; the corresponding ﬁrst order comparative statics (see the Online Appendix B for these and other derivations and proofs) are de f . C t / f C S C . C t / f f e AA A eA D >0; (11) dt jH j f . C t / f C v C . C t / f f dA A ee e eA D >0; (12) dt jH j Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 171 de . C t / f S eA D >0; (13) dG jH j 00 00 . C t / f v S dA ee D >0: (14) dG jH j Intuitively, an increase in the incentive rate t leads to an increase in both effort and the amount of resources dedicated to nutrition (11–12). Notably, these increases are greater when f is larger. Naturally, the larger that f is, the larger is the marginal eA eA productivity of either e or A when the other input increases, accentuating the effect of increasing the incentive rate. An increase in discretionary resources also raises both effort and resources devoted to nutrition (13–14). Note in (13) that if the marginal productivity of effort were independent of the level of A—that is, if f D 0, then changes in discretionary eA resources would not inﬂuence effort. This is not a general property, but rather a result of our simplifying assumption that v(e) and S(G A) are additive in the utility function, so e and A only interact through the production function. An important result is also that 0 < dA/dG < 1. This means that an increase in G translates into a positive but smaller increase in A, implying that the full increase in G is not entirely allocated to A, but rather a share is invested in non-nutritional activities. This is clear from (7): if G and A increased by the same amount, then the term S (G A) would not change—and hence could not be equal to ( C t)f (e, A). From ﬁrst order conditions (11–14), it then follows that dH de dA D f C f >0; (15) e A dt dt dt dH de dA D f C f >0: (16) e A dG dG dG To understand the conditions under which incentives and resources are complements or substitutes, we must compute the cross-partial derivatives of e, A, and H with respect to t and G. Note that because the ﬁrst order comparative statics (11–14) depend on the second derivatives of v(e),S(G A), and f(e, A), the cross- partial derivatives will necessarily depend on the third order derivatives of v(e), S(G A), and f(e, A). In order to gain insight, we make the simplifying assumption that the third order derivatives of the production function are null (i.e., that the production 000 000 10 function is quadratic) while leaving v and S unrestricted. Using the chain rule on H D f(e, A), the cross-partial derivative of H with respect to t and G is dH de de dA dA de dA de dA D f C f C f C ee AA Ae dt dG dG dt dG dt dG dt dt dG de dA C f C f ; (17) e A dt dG dt dG 10. Note that the third order derivatives of the production function include f , f , f , and f ;the eee AAA eeA eAA solution would be very cumbersome if we did not assume that these are zero. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 172 Journal of the European Economic Association which could be positive (implying that t and G are complements) or negative (implying that they are substitutes) because the ﬁrst term in brackets is negative, the second term is positive (and its size crucially depends on f ), and the third and fourth could be eA positive or negative (as shown in Online Appendix B, which provides expressions for de=dt dG and dA=d t d G). Because the sign of dH=d t d G cannot be determined a priori, we discuss in what follows how its sign depends on the sign and size of key 000 000 derivatives: S , v , f . eA A key determinant of dH=d t d G is f , how much the productivity of effort eA increases when A increases. A larger f favors complementarity between t and G eA (dH=d t d G > 0). Intuitively, larger values of G imply larger values of A, leading to effort being more productive (f > 0), and hence a larger response to the incentive. eA Mathematically, f multiplies the second term in (17), which is positive, and also eA enters into the formulae for de/dtdG and dA/dtdG. 000 0 The third derivative of v(e), v , deﬁnes whether the marginal cost of effort, v ,is 000 000 convex (v > 0) or concave (v < 0). A convex (concave) marginal cost of effort favor substitution (complementarity). To understand the intuition, assume that the marginal 000 ˛ cost of effort is concave, that is, v < 0 (i.e., v(e) D e ,2 <˛ < 3), and consider the following approximation: h l de.GDG ;t / de.GDG ;t / de dt dt h l ;G >G : (18) h l dt dG G G h l Note that de=dG > 0, so effort is greater for G than for G . Moreover, the concavity of the marginal cost of effort implies that, at higher levels of effort, the marginal cost of effort increases at a lower rate. Hence, the marginal cost of effort increases at a h l lower rate at G than at G . Hence, the response of effort to an increase in incentives, h l de(G, t)/dt, that is, the terms in the numerator of (18), might be larger for G than G because the increase in the marginal cost of effort will be smaller. A similar argument can be made to explain why S > 0 is conducive to complementarity. Ultimately, both e and A are inputs in the health production function, but v(e) is increasing in e whereas S(G A) is decreasing in A. This explains why if 000 000 12 v < 0 favors complementarity, S > 0 also does. The ﬂexibility of the model means that our predictions depend on three key parameters. Having discussed the effect of each of them individually, Table 1 summarizes the necessary and sufﬁcient conditions that the model provides. 000 000 11. Note that if S < 0, the term S f , which is part of de/dtdG (see the Online Appendix), can partially eA offset this effect. 12. Note that if one assumed a simple power function such as S(G A) D (G A) , the condition that 00 000 S < 0, would also imply necessarily that S > 0. However, this would not be the case for other functional forms, such as a cubic polynomial. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 173 TABLE 1. Summary of necessary and sufﬁcient conditions implied by the model. dH 000 000 S 0, and v 0, and f D 0 imply that <0 eA dtdG dH 000 000 S > 0, or v < 0, or f > 0 are necessary conditions for >0 eA dtdG 3. Background 3.1. School-Based Nutrition Programs School-based interventions are believed to be among the most cost-effective approaches for delivering health and nutrition services to children in developing countries (Bundy and Guyatt 1996; Jukes, Drake, and Bundy 2008; Orazem, Glewwe, and Patrinos 2008). Because schools are natural points of contact with school-aged children, they may provide a platform from which health and nutrition interventions can be delivered at relatively low cost (Bundy and Guyatt 1996; Bundy et al. 2006; Jukes, Drake, and Bundy 2008). Because of this, school-based health, nutrition and feeding programs are a ubiquitously central function of schools, particularly in developing countries. In China, schools have the legal responsibility to promote the health of their students (Education Law of the Peoples Republic of China, 1995). Although school administrators are evaluated as part of the cadre evaluation system (ganbu kaohe zhidu)—a system for evaluating public ofﬁcials and servants in China (Whiting 2004)—measures of child health are not typically included as criteria for evaluation. 3.2. The Causes and Consequences of Anemia Our study examines school-based programs to reduce anemia. Anemia is estimated to affect nearly one quarter of all school-aged children worldwide (World Health Organization 2001). Although there are many causes of anemia (including a variety of genetic disorders and infections as well as nutritional deﬁciencies), iron deﬁciency accounts for about 50% of cases globally (Balarajan et al. 2011; Pasricha et al. 2013) —and 85%–95% of cases in China (Du et al. 2000). The consequences of iron deﬁciency—with or without anemia—can be substantial, particularly for children at critical stages of development. A large literature links iron deﬁciency to fatigue and reduced work capacity among adolescents and adults, impaired cognition and cognitive development among children, and reduced immune response for all age groups (Thomas et al. 2006; World Health Organization 2001;Yip 2001; Balarajan et al. 2011). School-aged children with anemia (the focus of our study) 13. There is some debate in the public health literature on the proportion of the anemia burden attributable to iron deﬁciency (Balarajan et al. 2011). Intestinal worms are unlikely to be a major cause of anemia in our study areas as the prevalence of hookworm (the parasite most commonly associated with anemia) is low (Xu et al. 1995). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 174 Journal of the European Economic Association have also been shown to have inferior educational outcomes (grades, attendance, and school attainment—Taras 2005; Nokes, van den Bosch, and Bundy 1998). 3.3. Biomedical Strategies for Reducing Anemia Increasing iron consumption can effectively prevent iron deﬁciency anemia. Worldwide, fortifying staple foods with iron has historically been an effective approach to addressing micronutrient deﬁciencies (Allen et al. 2006). Fortiﬁcation is an attractive strategy because it requires little behavior change and because it can be implemented on a large scale. However, fortiﬁcation of staple foods may be ineffective in areas like Northwest China in which households grow and consume their own food (Allen et al. 2006). An alternative approach is to increase the consumption of naturally iron-rich foods and those that promote iron absorption during digestion. Animal sources (including red meats, ﬁsh, and poultry) provide heme iron, which is more easily absorbed during digestion; plant sources (including green, leafy vegetables) provide nonheme iron, which is less readily absorbed—but can be promoted by consumption of vitamin C (and inhibited by consumption of milk and other calcium-rich products). Finally, a third approach is the delivery of micronutrient supplements (e.g., vitamins) containing iron. To be effective, however, regular consumption over several few months is necessary—and so inadequate compliance may render supplementation ineffective (Bobonis et al. 2006; Bhutta et al. 2013; Pasricha et al. 2013; Martorell et al. 2015). 4. The Experiment 4.1. Sampling To draw our study sample, we began with all 36 counties ofﬁcially designated by the Chinese government as “poverty counties” in ﬁve regions (prefectures) in western China (Haidong in Qinghai Province, Dingxi, Tianshui, and Longnan in Gansu Province, and Ankang in Shaanxi Province—see Figure 1). In August 2011, we conducted a canvass survey in each county to construct a list of all rural primary schools and the number of students enrolled in each. Restricting our sampling frame to primary schools with 150–300 students total, we randomly selected 170 of 1410 14. Previous trials addressing iron deﬁciency and anemia have suffered from low levels of compliance or attempted to preempt compliance problems. Bobonis et al. (2006), for example, instructed preschool teachers to provide children with iron therapy for 30 days following health camps but found that only around 18 days were actually administered. The WISE study in Indonesia (Thomas et al. 2006)hired facilitators to regularly visit participants and remind them to take their supplements. 15. A lower bound of 150 students was chosen to ensure that the number of samples students per school was enough to meet power requirements. 300 was chosen as the upper bound to keep the project within Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 175 FIGURE 1. Study regions. eligible schools for inclusion in our study (and limited our selection to one school per township ). Our sample size was based on power calculations conducted using data from primary schools in the same region of China (Miller et al. 2012). Within study schools, we randomly sampled 50 fourth and ﬁfth grade students from each school. In China, fourth and ﬁfth grade students are typically 10–11 years old, and we chose these grades to select students whom we considered sufﬁciently old to provide meaningful survey responses—but also sufﬁciently young to be generally prepubescent (given the independent effect of menarche on hemoglobin concentration). budget. These bounds are on reported school sizes; actual numbers of students are often signiﬁcantly less than reported. Note that 39.9% of rural primary schools in the sampling frame (all rural primary schools in project counties) were reported to be within this range. 16. Local administration of schools is generally done at the school district level, which is below the township. Contamination due to two school administrators meeting at events organized at higher levels, for example, was thus unlikely. 17. Using data from Miller et al. (2012), we performed Monte Carlo simulations to conduct power calculations for students who were anemic at the time of that study’s baseline survey. The intraclass correlation was estimated adjusting for covariates (baseline hemoglobin concentration, the number of students in each school, whether schools had a kitchen, student–teacher ratio, distance to the furthest village served by the school, percent boarding students, and county dummies), which we also speciﬁed as covariates in the current study’s preanalysis plan. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 176 Journal of the European Economic Association We also conducted physical exams and collected data from students from other grades at baseline to obfuscate our focus on fourth and ﬁfth graders. 4.2. Data Collection We conducted our baseline survey in September 2011 and our follow-up survey in May 2012 (at the beginning and end of the 2011–2012 academic year), collecting detailed information on students, households, school administrators, and schools. Student Surveys. We interviewed all sampled students at their school, collecting information on student background, health behaviors related to anemia, school activities, and general health. To collect information on school and home feeding practices, students were also given standard food frequency questionnaires to record information about food consumption at school and at home over the past week. We also measured student blood hemoglobin (Hb) concentration at the time of the student survey. Nurses from the Medical School of Xi’an Jiaotong University accompanied study enumerators, collecting ﬁnger-prick blood samples to analyze on- site (at schools) using HemoCue Hb 201C assessment systems. Household Surveys. For each sampled student, we also collected information on students’ households using forms completed by parents. Speciﬁcally, these surveys collected information about interactions between parents and the school, household income and assets, health-related expenditures, expenditures on food and information on other household members, focusing on household characteristics that students would be unlikely to know themselves. School Administrator Surveys. We interviewed school administrators (bureaucrats) at three different points in time: before and after school administrators were told about the incentive contract and block grant to which they were assigned and again at endline. At baseline, school administrators provided information about their background, job history, salary, and compensation as well as perceptions of professional responsibilities and anemia knowledge. Using scales adapted from Grant (2008), we also measured the intrinsic and prosocial motivation of administrators. Following their participation in the training session on anemia (conducted 3 weeks after the baseline survey) 18. Information on food consumption was collected using a seven-day recall “food frequency questionnaires” (FFQs) completed by students as part of the endline survey. These questionnaires asked children the number of times they had eaten each of 33 food items in the past seven days, separately for school and home. Food frequency questionnaires (FFQs) have long been used in nutrition research and have been recommended for use in large surveys of children given low cost and low respondent burden (McPherson et al. 2000; Magarey et al. 2011). FFQ responses by children about their own consumption has been shown to be more accurate than the responses of their parents (Burrows et al. 2013). 19. For budgetary reasons, household surveys were given to students to take home and return. As a result, household forms are missing for approximately 20% of students. All possible information on students and households was collected with the student survey, which was administered by enumerators. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 177 300 Schools Group A: No Group B: Small Group C: Large Other Experimental Administrator Anemia Reduction Anemia Reduction Groups Incentive Incentive (40 Schools) Incentive (65 Schools) (130 Schools) (65 Schools) A1. Small Block B1. Small Block C1. Small Block Grant Grant Grant (32 Schools) (20 Schools) (33 Schools) A2. Large Block B2. Large Block C2. Large Block Grant Grant Grant (33 Schools) (20 Schools) (32 Schools) FIGURE 2. Experimental design. administrators were given a second short survey to measure their understanding of the training material. School Surveys. Finally, we collected basic information from schools (about enrollment, stafﬁng, facilities, ﬁnances, and meal provision) and teachers (about teacher characteristics, communication with parents, and teaching practices). 4.3. Experimental Design We designed our study as a cluster-randomized trial using a 3 2 crosscutting design (Figure 2). After conducting our baseline survey, we provided all school administrators with information about anemia (which included presentations and a video presentation by a Chinese nutrition specialist, see script in Online Appendix C), and schools were randomly assigned one of six experimental cells (see Figure 3 for the study timeline). The ﬁrst three paths of Figure 2 show randomly-assigned incentive groups: a group without incentives (group A), a “small” incentive group (group B), and a “large” incentive group (group C). Across these arms are two orthogonally assigned block grant groups: a “small” block grant group (group 1) and a “large” block grant group (group 2). The reference group in our six-cell design is the default policy (education about anemia coupled with a modest resource transfer and no incentives, group A1). 20. Thus, all schools in the experiment received a small or large grant. This was done to ensure that all schools had access to resources that could be devoted to anemia reduction. In a previous study, we ﬁnd that educating school administrators on anemia (including the same information as in the current study) alone, Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 178 Journal of the European Economic Association Anemia Training, Grant Notification, Incentive Contract Baseline Endline Signing and Post Survey Survey Training Survey School Administrators Contacted School Administrators Contacted to Confirm First Grant and to Confirm Second Grant and Supplement Installment Supplement Installment Delivery of First Grant Delivery of Second Grant Installment and Installment and Supplements (if ordered) Supplements (if ordered) September May October November December January February March April 2011 2012 FIGURE 3. Data collection and intervention timeline. To improve power, we used a stratiﬁed randomization procedure. Speciﬁcally, using joint quintiles of the baseline distribution of school-level hemoglobin concentration and combined standardized math and Chinese exam scores—yielding 25 strata, we randomized cell assignment within each stratum. Stratiﬁcation improves power by ensuring balance on these covariates between experimental groups. Our analysis takes this randomization procedure into account, conditioning on stratum ﬁxed effects (Bruhn and McKenzie 2009). Incentives for Anemia Reduction. In the large incentive arm (65 schools, group C in Figure 2), we offered school administrators ﬁnancial incentives to be paid as private income according to the net reduction in number of students identiﬁed as anemic between the beginning and end of the school year. The speciﬁc structure of the large incentive contract was 125 RMB N N if N N >0 b e b e P D ; 0 otherwise where N is the number of students found to be anemic at baseline and N is the number b e of who were anemic at the time of the endline survey. Based on an earlier study (Miller without incentives or grants, had no detectable impact on anemia rates (Miller et al. 2012). Our reference group also mimics how a recent Chinese school nutrition program (costing 16 billion yuan per year) was designed. Under the program, local education bureaus and schools receive 3 yuan per day per student (4 yuan for boarding students) to provide nutritious meals. How exactly the program is implemented and monitored varies widely across localities. 21. We measured anemia using a sample of 50 fourth and ﬁfth graders and calculated the implied number of anemic children in the school using the prevalence rate in our sample. Although administrators could possibly discern which students were tested at baseline (although testing was done before contract assignment), they were later told explicitly that another sample of students would be drawn at the end of the school year. Moreover, unreported analyses show that teachers were unable to correctly name or identify anemic students at endline. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 179 et al. 2012), the contract increment (125 yuan (RMB), or about $19.40 ) per student reduction was chosen to provide roughly two months of a school administrator’s annual salary for a feasible reduction in anemia given previous studies (a reduction of about 50%). Actual payouts for school administrators with the large incentive and small block were ultimately 3,303 yuan (or about $516)—approximately two month’s base pay for school administrators in this region. We did not reveal the identity of students who were anemic at baseline to administrators (and when we asked teachers to identify students who were anemic at endline, they were unable to do so). The small incentive arm (40 schools, group B in Figure 2) was identical to the large incentive arm except that the magnitude of the incremental incentive was ten times smaller (12.5 RMB, or about $1.95 per student reduction in anemia between baseline and follow-up in our sample). This magnitude of this incentive provides roughly 0.2 additional months of annual salary for the same feasible reduction in anemia given previous studies. At the time that school administrators signed incentive contracts, they were told the (implied) number of anemic students in their schools (the identity of anemic children was not revealed). Contracts were written using ofﬁcial letterhead of the Chinese Academy of Sciences (a government agency) and counter-signed by the deputy director of the implementing research center (school administrators signed two copies of the contract, one of which they kept). Note that all interventions were implemented in partnership with local education bureaus, signifying to school administrators that the project was sanctioned by local governments. Block Grants. The small block grant (group 1 in Figure 2) was 0.3 RMB ($0.05) per student per day (85 schools), which we calculated to be adequate for school administrators to purchase vitamins for each student to take daily. The large block grant (group 2 in Figure 2) was 0.7 RMB ($0.11) per student per day (85 schools). In total, small block grant schools received 7,452 yuan ($1164) on average and large block grant schools received 17,388 yuan ($2717). These grants were given to schools in two installments, once at the beginning of the program and another approximately half way 22. We use a conversion rate of $1 D 6.4 RMB, the approximate exchange rate at the time of the baseline survey (September 2011). 23. There are presumably superior contract structures, but optimal contract design requires substantial information not available to us, including information about the cost of provider effort, the productivity of provider effort, and the utility functions of both providers and the contracting “principal” (Laffont and Tirole 1993; Salanie´ 2005). Simple, easily understandable contracts may also appear more transparent to school administrators and promote credibility. 24. We did reveal the identity of students who were severely anemic (with hemoglobin concentration below 80 g/L) as these students required immediate medical attention. There were 3 such students found at baseline. 25. Note that administrators in all study cells were provided the same information about the number of anemic children in their respective schools. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 180 Journal of the European Economic Association No Incentive Small Large No Incentive Small Large Incentive Incentive Incentive Incentive Small Block Grant Large Block Grant Iron Supplements/ Foodstuff Fortified Soy, Flour Communication/ Non−nutrition Transfers to Households FIGURE 4. Reported use of block grants by category. Figure shows mean values of reported use of block grants by experimental group from the endline survey. Expenditure amounts are per student. through the school year. Although funds were given in the context of the nutrition program roll-out, administrators were explicitly told that they were free to allocate these at their discretion to other school functions beneﬁtting students—whether this be for educational goods, health speciﬁc goods, or general school supplies. Indeed, Figure 4 shows that administrators used a substantial share of their grants for activities unrelated to nutrition. Health Education. Because knowledge about anemia in our study areas was poor, prior to revealing treatment assignment, we provided health education about nutrition 26. After explaining block grant assignment to administrators, we asked them to complete a nonbinding budget plan for how they intended to use the block grant. Our study team emphasized that this plan was nonbinding, but this plan would be used to coordinate orders for iron supplements to be delivered to schools. This was necessary because the market for supplements in rural areas is limited. Administrators were free to change their supplement orders at any time. Administrators had no reason to believe that second installments were conditional on performance—they were given an explicit time frame and told an explicit amount for the second installment. 27. Note that although these transfers were not large compared to total school expenditures, they do represent a signiﬁcant increase in budgetary autonomy for school administrators as the bulk of school expenditures are earmarked for speciﬁed uses at higher levels of administration. Although administrators often have discretion over small expenditures, larger expenses require approval from upper levels. Reported Expenditure from Grant (yuan per student) 0 10 20 30 40 Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 181 and anemia to all school administrators in our study (see Online Appendix C). Our health education materials were based on published, peer-reviewed studies and speciﬁcally included information about: (1) the prevalence and causes of anemia, (2) the consequences of anemia (including its effect on cognitive development and academic performance), and (3) efﬁcacious nutritional approaches to reduce anemia (increasing dietary intake of iron-rich foods, nutritional supplementation with iron fortiﬁed soy and ﬂour or with supplements, etc.). 4.4. Balance and Attrition Summary statistics and tests for balance across study arms are shown in Table 2. Panel A shows student level characteristics (N D 2051), panel B shows characteristics of schools (N D 167), and panel C shows characteristics of school administrators (N D 167). The ﬁrst two columns of the table give the mean and standard deviation of each variable in the comparison (small block grant, no incentive) group. Columns (3)– (7) show coefﬁcients on treatment variables and interactions estimated using equation (19), controlling only for randomization strata ﬁxed effects. The ﬁnal column shows the p-value from a test that the coefﬁcients are jointly zero for each characteristic. Only 4 of the 75 tests are signiﬁcant at the 10% level, and a test for joint equality is rejected at the 10% level for only one characteristic (the number of times meat was consumed in the past week). Joint tests for all 15 characteristics reveal no signiﬁcant differences. The overall attrition rate between baseline and endline surveys was 6.2% in our sample of children anemic at baseline (5% for the full sample). Deﬁning attrition as a missing hemoglobin measurement at endline for students with a baseline measurement, Online Appendix Table A.2 shows that there were no meaningful differences in attrition across treatment groups (columns (1) and (2)). Analyzing the correlates of a missing household survey at endline conditional on a child not dropping out, Online Appendix Table A.2 also shows that neither the treatment indicators nor other covariates are signiﬁcantly correlated with a missing household survey form. 28. This table shows summary statistics and tests balance for our main analysis sample of students initially anemic at baseline. Summary statistics and balance tests for the full sample are given in Online Appendix Table A.1. 29. Although 170 schools were included in the study, no students were found to be anemic in 3 schools at baseline. No schools refused participation in the study. The baseline anemia rate (deﬁned as Hb < 120 g/L) in the full sample was 24%. Online Appendix Table A.11 shows transitions in and out of anemia status in the comparison (small grant only) group. 30. These tests were conducted by regressing treatment status on all 15 baseline covariates and testing that the coefﬁcients were jointly zero. The smallest p-value from these F-tests was 0.29. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 182 Journal of the European Economic Association TABLE 2. Descriptive statistics and balance check. No incentive, small grant group Coefﬁcient (standard error) on (Small- (Large Joint Test Small Large incentive) incentive) p-value: all Mean SD incentive incentive Large grant (large grant) (large grant) coefﬁcients D 0 Observations (1) (2) (3) (4) (5) (6) (7) (8) (9) Panel A: Child characteristics (1) Hemoglobin 118.446 7.541 0.965 1.525 0.653 2.868 1.479 0.420 2051 concentration (g/L) (1.326) (1.163) (1.438) (1.959) (1.761) (2) Age (years) 10.514 1.153 0.046 0.077 0.113 0.002 0.070 0.914 2051 (0.166) (0.125) (0.134) (0.242) (0.189) (3) 5th Grade (0/1) 0.468 – 0.055 0.002 0.003 0.106 0.016 0.177 2051 (0.032) (0.029) (0.031) (0.050) (0.042) (4) Female (0/1) 0.530 – 0.003 0.021 0.009 0.001 0.044 0.945 2051 (0.044) (0.035) (0.039) (0.060) (0.052) (5) Times consumed 3.922 4.145 0.534 1.293 0.352 0.039 0.909 0.091 2051 meat in past week (incl. chicken, pork, beef, lamb) (0.618) (0.453) (0.709) (0.888) (0.790) Panel B: School characteristics (6) Number of students 203.733 55.788 2.424 7.060 1.925 21.948 9.631 0.725 167 (16.959) (14.194) (15.304) (25.245) (20.780) (7) Has kitchen (0/1) 0.067 – 0.135 0.068 0.054 0.071 0.052 0.732 167 (0.099) (0.077) (0.085) (0.161) (0.120) (8) Student–teacher 16.192 4.356 2.859 1.190 0.019 1.804 0.866 0.185 167 ratio (1.377) (1.216) (1.182) (1.928) (1.678) (9) Time to furthest 61.167 37.570 12.294 2.256 4.020 7.468 4.605 0.918 167 village served (min) (13.474) (11.962) (12.520) (21.139) (17.681) Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 183 TABLE 2. Continued No incentive, small Coefﬁcient (standard error) on grant group Mean SD Small Large Large grant (Small- (Large Joint Test Observations incentive incentive incentive) incentive) p-value: all (large grant) (large grant) coefﬁcients D 0 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Percent boarding 4.277 9.493 2.228 0.756 1.310 0.757 1.804 0.985 167 students (%) (3.976) (2.899) (3.400) (6.204) (5.107) Panel C: School administrator characteristics (11) Male (0/1) 0.967 – 0.015 0.028 0.038 0.014 0.070 0.606 167 (0.051) (0.032) (0.034) (0.053) (0.046) (12) Age (years) 39.567 7.398 1.550 1.299 1.599 4.730 0.090 0.383 167 (2.112) (1.837) (1.882) (3.022) (2.601) (13) Higher education 0.900 – 0.018 0.007 0.107 0.032 0.007 0.558 167 degree (0/1) (0.092) (0.081) (0.093) (0.136) (0.126) (14) Experience (years) 8.333 6.227 0.194 1.124 0.898 2.761 0.165 0.137 167 (1.531) (1.786) (1.630) (2.210) (2.577) (15) Monthly base 1855.067 706.106 57.049 110.575 36.880 312.491 35.944 0.602 167 salary (yuan) (196.310) (178.286) (182.302) (305.716) (247.052) Notes: Table uses sample of children testing anemic at baseline. Children are considered anemic if they have an altitude-adjusted hemoglobin concentration below 120 g/L (per WHO guidelines). The ﬁrst and second columns show the mean and standard deviation in the comparison (small grant, no incentives) group. Columns (3) through (7) show coefﬁcients and standard errors from a regression of each characteristic on indicators for incentive and large grant treatment group indicators and there interactions, controlling for randomization strata. Column (8) shows the p-value from a test that coefﬁcients are jointly zero. All tests account for clustering at the school level. Signiﬁcant at 10%; signiﬁcant at 5%; signiﬁcant at 1%. Source: Baseline survey. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 184 Journal of the European Economic Association 4.5. Empirical Strategy Given random assignment of schools to treatment cells shown in Figure 2, comparisons of outcome variable means across treatment groups provide unbiased estimates of the effect of each experimental treatment. However, to increase power (and to account for our stratiﬁed randomization procedure), we condition our estimates on a set of covariates used in power calculations. With few exceptions, all of the analyses presented (including outcome variables, regression speciﬁcations, and hypotheses tested) were prespeciﬁed in a preanalysis plan written and ﬁled before endline data were available for analysis. In reporting results in what follows, we explicitly note analyses that deviate from the preanalysis plan. As speciﬁed in advance, we use ordinary least-squares (OLS) regression to estimate the effect of cell assignment on child-level outcomes with the following speciﬁcation: Y D ˛ C ˇ SI C ˇ LI C ˇ LG C ˇ .S I / .LG / i;j 1 j 2 j 3 j 4 j j C ˇ .LI / .LG / C X C " ; (19) 5 j j i;j i;j where Y is the outcome for child i in school j; SI is a dummy that equals 1 if the i, j j administrator in school j was assigned to receive a small incentive contract and 0 otherwise; LI is equal to 1 if the administrator in school j was assigned to receive a large anemia reduction incentive contract; LG is equal to 1 if the school received a large block grant; X is a vector of child controls (age, class-year, and gender, and i, j baseline value of the outcome variable), school controls (number of students, student- teacher ratio, whether the school has a kitchen, proportion of boarding students, and distance to the farthest village in the school’s catchment area); and dummy variables for counties and randomization strata. We adjusted our standard errors for clustering at the school level using Liang–Zeger clustered standard errors. In addition to estimating effects on our two primary outcomes (hemoglobin concentration and a dichotomous indicator for anemia status), we use the same speciﬁcation to estimate effects on secondary outcomes to examine the behavioral mechanisms underlying changes in primary outcomes. For these secondary outcomes, we focus our analysis on summary indices constructed using groups of closely-related outcome variables (as we speciﬁed in advance). To construct these indices, we used the GLS weighting procedure described by Anderson (2008). For each individual, we constructed a variable s N as the weighted average of k normalized outcome variables ij in group (y ). The weight placed on each outcome variable is the sum of its row ij k entries in the inverted covariance matrix for group j such that 1 1 X X d d 0 0 s N D 1 1 1 y ; ij ij j j 31. This analysis plan was ﬁled with the Abdul Latif Jameel Poverty Action Lab at http://www. povertyactionlab.org/Hypothesis-Registry. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 185 where 1 is a column vector of 1 s, is the inverted covariance matrix, and y is j ij a column vector of all outcomes for individual i in group j. In addition to reducing the number of tests required, this weighting procedure can improve efﬁciency by placing less weight on outcomes that are highly correlated and more weight on those less correlated. The summary index variable can also be created for individuals with a subset of missing outcomes (these outcomes simply receive less weight in the construction of the index). Although we emphasize these indices in our discussion, we also report estimates for each individual index component in Online Appendix Tables A.5–A.8. A note on correcting for multiple comparisons is also warranted. For our primary estimates, we test eight null hypotheses: ﬁve for treatment main effects and their interactions (shown in equation (19)) and three additional ones—that the small and large incentives have the same average effect (ˇ D ˇ ), that the large incentive and the 1 2 large block grant have the same average effect (ˇ D ˇ ), and that the average effect 2 3 of the large incentive in presence of a large grant is zero (ˇ C ˇ D 0). We therefore 2 5 adjust our p-values to control the family wise error rate (FWER), or the probability of at least one Type I error. Speciﬁcally, we use the free step-down resampling method of Westfall and Young (1993). This procedure accounts for the dependency of the data, and is therefore more powerful than procedures that do not (e.g. a Bonferroni correction ). For secondary outcomes, we adjust our p-values according to the total number of tests within a family of outcomes (the number of outcomes in the family times ﬁve—the number of treatment coefﬁcients in each regression). 5. Results: Childhood Anemia and Underlying Behavioral Responses In this section, we ﬁrst present results obtained by estimating equation (19) for anemia status and hemoglobin concentration, and in Section 5.2, we then investigate the underlying behavioral responses that may have produced them. Following our preanalysis plan, we emphasize estimates from our sub-sample of children who were anemic at baseline. In the Online Appendix Tables we report results for the full sample of children receiving hemoglobin tests (Online Appendix Tables A.3, A.4, A.6, and A.8). 5.1. Childhood Anemia The ﬁrst ﬁve rows of Table 3 report estimates for each treatment and their interactions (and the seventh row reports comparison group means for the no incentive, small grant group at endline). For each estimate, we report the regression coefﬁcient, the standard 32. We did not prespecify the last of these (whether or not the joint effect of the large grant and large incentive is negative), but we did prespecify whether or not incentives and large grants are complements or substitutes (ˇ D 0, ˇ D 0). 4 5 Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 186 Journal of the European Economic Association TABLE 3. Impacts of school administrator anemia reduction incentives and block grant size on student hemoglobin concentration and anemia prevalence. Anemic at endline Hemoglobin (Hb < 120 g/L) concentration (g/L) Dependent variable (1) (2) Panel A: Impacts relative to comparison (no incentive, small grant) group (1) ˇ : small incentive 0.012 0.387 (0.040) (1.101) [0.771] [0.726] f0.972gf0.792g (2) ˇ : large incentive 0.138 2.567 (0.039) (1.044) [0.001] [0.015] f0.064gf0.285g (3) ˇ : large grant 0.145 4.205 (0.038) (1.123) [<0.001] [<0.001] f0.047gf0.045g (4) ˇ : (small incentive) (large grant) 0.042 1.445 (0.056) (1.541) [0.453] [0.350] f0.888gf0.664g (5) ˇ : (large incentive) (large grant) 0.196 4.580 (0.058) (1.586) [<0.001] [0.004] f0.072gf0.173g (6) Observations 1923 1923 (7) Mean in no incentive, small grant group 0.364 129.901 Panel B: p-values of Additional Comparisons (8) ˇ –ˇ : effect of large incentive versus effect of [0.002] [0.014] 1 2 small incentive given small grant f0.089gf0.285g (9) ˇ –ˇ : effect of large incentive given small [0.854] [0.169] 2 3 f0.972gf0.597g grant versus effect of increasing grant amount (10) ˇ C ˇ : effect of large incentive given large [0.141] [0.080] 2 5 grant f0.650gf0.511g Notes: Table uses sample of children testing anemic at baseline. Children are considered anemic if they have an altitude-adjusted hemoglobin concentration below 120 g/L (per WHO guidelines). Rows (1)–(5) in panel A show estimated coefﬁcients for treatment group indicators and interactions obtained by estimating equation (19) (controlling for baseline hemoglobin concentration, student age, student grade, student sex, number of students in the school, whether the school has a canteen, student teacher ratio, distance to the furthest village served, percent of boarding students, whether the school has implemented the “Free Lunch” policy, county dummy variables, and dummy variables for randomization strata). Standard errors are shown in parentheses, unadjusted p-values are shown in square brackets and p-values adjusted for multiple inference are shown in curly brackets. Adjusted p-values were constructed using the free step-down resampling method of Westfall and Young (1993) with 10,000 iterations. Panel B shows unadjusted and adjusted p values from tests of linear combinations of coefﬁcients in panel A. Signiﬁcant at 10%; signiﬁcant at 5%; signiﬁcant at 1% based on adjusted p values. error and corresponding p-value, and the p-value adjusted for multiple hypotheses testing. RESULT 1. (Large Incentives). First, we ﬁnd that the large incentive signiﬁcantly reduced the probability of anemia at endline in schools receiving a small grant. Speciﬁcally, the large incentive was associated with a 14 percentage point reduction 33. Table 3 reports results for students found to be anemic at baseline as pre-speciﬁed. Appendix Table 3 shows main results for the full sample. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 187 in anemia (Table 3, row 2, column (1); unadjusted p-value D 0.001, adjusted p-value D 0.064), implying a 37.9% reduction relative to the comparison group (small grant, no incentive schools) at endline. The corresponding increase in hemoglobin was about 2.6 g/L (Table 3, row 2, column (2); unadjusted p-value D 0.015, adjusted p-value D 0.285). These empirical ﬁndings agree with our model’s prediction derived in equations (11) and (12). Because our incentives rewarded anemia reduction (and not hemoglobin levels per se) and anemia status reﬂects shifts in the distribution of altitude adjusted hemoglobin concentrations across the 120 g/L threshold, Figure 5a plots the distribution of endline hemoglobin concentrations (adjusted for covariates included in equation (19)) by study arm among children who were anemic at baseline. The distribution for the large incentive group is shifted to the right of the control group distribution (Kolmogorov– Smirov test p-value D 0.02). This relative shift in mass is greater in the left tail of the distribution, implying that the large incentive reduced the share of children falling below the anemia threshold. RESULT 2. (Small Incentives). Second, in contrast, the small incentive had no detectable effect on the probability of anemia at endline (Table 3, row 1, column (1)). Comparing the estimates for small and large incentives (ˇ D ˇ in equation (19)), 1 2 we also reject the null hypothesis that the two estimates are equal (Table 3,row 8, column (1); adjusted p-value D 0.089). Taken together, the estimates for the small and large incentives suggest that the price effect of incentives is meaningful independent of information conveyed by the presence of an incentive contract (Gneezy and Rustichini 2000). Figure 5a shows that the shift in the hemoglobin distribution for the small incentive arm relative to the control group arm is smaller—particularly in the left tail of the distribution. An important question in the literature on ﬁnancial incentives is whether or not they crowd-out intrinsic or prosocial motivation (Deci and Ryan 1985; Gneezy and Rustichini 2000; Fehr and Falk 2002; Francois and Vlassopoulos 2008; Gneezy, Meier, and Rey-Biel 2011; Kamenica 2012). We ﬁnd that the effects of the small incentive on anemia was signiﬁcantly more positive amongst school administrators who score higher at baseline on a prosociality scale (adapted from Grant 2008) (Online Appendix Table A.10, row 1, columns (1)–(3); adjusted p-value D 0.038). We also ﬁnd a similar effect for intrinsic motivation (also adapted from Grant 2008), but the difference in effects is not statistically signiﬁcant (Online Appendix Table A.10, row 4, columns (1)–(3); adjusted p-value D 0.570). However, the effect of the large incentive is not heterogeneous by prosocial or intrinsic motivation (the coefﬁcients are close to zero and not statistically signiﬁcant), implying that if monetary incentives are large, crowding- out of prosocial motivation may be overcome by extrinsic motivation provided by incentives. RESULT 3. (Large Block Grants). Third, in the absence of any explicit incentive, the large block grant alone reduced the probability of student anemia at endline (an unambiguous prediction of our model, as equations (13), (14), and (16) show). Speciﬁcally, Table 3 (column (1), row 3) shows that the large block grant was associated Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 188 Journal of the European Economic Association FIGURE 5. Distributions of hemoglobin concentration. (a) and (b) plot the distributions of student level hemoglobin concentrations (in g/L) at endline across incentive treatment groups separately by small and large block grant groups. Endline Hb concentrations are adjusted for prespeciﬁed baseline control variables. Kolmogrov–Smirnov p values for small anemia incentive versus no incentive are in 0.93 panel (a) and 0.12 in panel (b). For large anemia versus no incentive these are in 0.02 panel (a) and 0.24 in panel (b). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 189 with a 14.5 percentage point reduction in anemia (adjusted p-value D 0.047), implying a 39.8% reduction relative to the comparison group at endline. This reduction is very similar to the effect of the large incentive (0.145 vs. 0.138), but the average increase in hemoglobin concentration is larger (4.205 vs. 2.567), although not statistically so (Table 3, row 9, column (2); adjusted p-value D 0.597). RESULT 4. (Interactions between Incentives and Grants). Whether or not incentives and unrestricted grants are complements or substitutes is an empirical issue. The model in Section 2 makes clear that both complements or substitutes are possible depending on cross partial derivatives of the hemoglobin production function as well as the curvature of the marginal cost of effort and the marginal utility that the school administrator obtains from non-nutritional activities. We do not ﬁnd evidence of complementarity— and notably, incentives and block grants can be strong substitutes if the incentives are sufﬁciently large. Table 3 shows that the interaction between the large incentive and the large block grant (ˇ in equation (19); Table 3, column (1), row 5) is positive and statistically signiﬁcant (adjusted p-value D 0.072). Moreover, the magnitude of substitution implies that the large incentive and the large block grant fully crowd each other out: the marginal effect of the large incentive given the large block grant in column (1) (ˇ C ˇ D 0.058) is not statistically different from zero (adjusted p-value D 0.65) for the probability of anemia. Although this point estimate is positive, we are not able to rule out a negative effect of the large incentive given a large block grant on anemia as predicted by equation (15) of the model in Section 2. Adding coefﬁcients, the estimated total effect of the large incentive and large grant on anemia is 0.087 (adjusted p-value: 0.177). Given decreasing marginal returns to inputs in the reduction of anemia, a natural question arising from these results is if substitution between incentives and resources is due to (i) the biological relationship between inputs and anemia (i.e., although more inputs are used, there is no effect on anemia because of biological constraints) or (ii) conscious decisions by administrators. Our results for input use in Section 5.2 are consistent with the latter interpretation (we ﬁnd direct evidence of substitution in input use). (We also note that efﬁcacy trials of iron supplementation suggest that much larger reductions in anemia are biologically possible (Gera et al. 2007).) Given that we ﬁnd similar results for input use in the full sample (Online Appendix Table A.4), differences in the effects of incentives and resources on anemia rates between the sample of children anemic at baseline (Table 3) and the full sample (Online Appendix Table A.3) are likely explained by decreasing marginal returns to inputs in the reduction of anemia rather than diminishing marginal returns to effort on the part of administrators. 34. Likewise, ˇ C ˇ , the marginal effect of increasing the grant amount given large incentives is 3 5 insigniﬁcant (ˇ C ˇ D 0.051, adjusted p-value 0.742). 3 5 Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 190 Journal of the European Economic Association 5.2. Behavioral Responses Underlying Changes in Anemia We next examine the underlying behavioral responses to our interventions that may have produced the changes in anemia described in Section 5.1. To do so, we focus on actions taken by administrators and subsequent responses among students and their parents—speciﬁcally, student consumption of iron-rich foods, direct iron supplementation, communication between parents and schools about anemia and its nutritional basis. For each family of outcome variables, we examine indices as described in Section 4.5. Behavioral Responses Underlying Result 1: Large Incentives. We ﬁrst consider the behavioral responses underlying Result 1—that in the presence of the small block grant, the large incentive signiﬁcantly reduced the probability of student anemia. The results in Table 4 suggest that the large incentive led administrators to increase vitamin supplementation and the provision of iron-rich foods (column (1), row 2; adjusted p-value 0.105). This increase in iron-rich foods seems driven largely by home consumption (row 2, column (5), adjusted p-value 0.090). An interesting issue is if the increase is vitamin supplementation and provision of iron-rich foods occurred because school administrators with large incentives spent the block grant differently—or instead because they exerted more effort. As Figure 4 shows, reported use of block grants for different types of nutrition interventions (vitamins, food, fortiﬁcation), and other uses is similar for incentive and nonincentives schools receiving a small grant, suggesting that greater anemia reduction due to incentives is driven by effort rather than differential allocation of the block grant. In exploring how administrators were able to increase child consumption of iron rich foods at home, we examine contact with parents. Row 2, column (8) of Table 4 reports a positive (but insigniﬁcant) increase in contact. However, Online Appendix Table A.7 shows that estimates for several components of this index appear meaningful and important, albeit insigniﬁcant at conventional levels using adjusted p-values (largely because of the large number of hypotheses being tested (11 5 D 55). These results are suggestive that the large incentive led administrators to engage more regularly with households—speciﬁcally about nutrition and anemia—which in turn appears to have improved children’s diets at home. 35. Subindices for supplements and food (including separate indices for food at home and school) were not explicitly speciﬁed in the preanalysis plan. Online Appendix Table A.9 reproduces Table 4, including additional tests of linear combinations of coefﬁcients estimated using equation (19). These additional tests were not prespeciﬁed. 36. Speciﬁcally, the number of individual meetings between administrators and households over the past semester increased by 0.52 (column (2), row 2)—an increase of 59%; whether or not schools contacted parents about nutrition in the past semester rose by 12 percentage points (column (3), row 2)—an increase of 29%; and whether or not schools contacted parents about feeding children iron-rich foods rich in the past semester rose by 10 percentage points (column (4), row 2)—an increase of 47%. Note that the number of school-wide parent meetings and number of individual meetings with parents were not prespeciﬁed to be part of this index. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 191 TABLE 4. Child and household reported receipt of supplements and iron-rich food. Index: supplements Subindex: Subindex: food Sub-index: food Index: Subindex: information Subindex: information Dependent variable and food supplements Subindex: food at school at home information to students to households (1) (2) (3) (4) (5) (6) (7) (8) (1) ˇ : small incentive 0.059 0.138 0.033 0.08 0.072 0.027 0.062 0.045 (0.047) (0.084) (0.044) (0.055) (0.061) (0.075) (0.126) (0.084) [0.21] [0.104] [0.452] [0.151] [0.243] [0.724] [0.623] [0.594] f0.331gf0.234gf0.56gf0.555gf0.403gf0.935gf0.911gf0.690g (2) ˇ : large incentive 0.114 0.158 0.073 0.039 0.187 0.070 0.111 0.130 (0.045) (0.080) (0.038) (0.048) (0.064) (0.072) (0.101) (0.084) [0.011] [0.052] [0.057] [0.427] [0.004] [0.332] [0.272] [0.124] f0.105gf0.234gf0.339gf0.601gf0.090gf0.800gf0.796gf0.430g (3) ˇ : large grant 0.190 0.241 0.138 0.133 0.189 0.162 0.136 0.233 (0.041) (0.072) (0.047) (0.06) (0.075) (0.076) (0.107) (0.113) [<0.001] [0.001] [0.004] [0.029] [0.013] [0.034] [0.207] [0.041] f0.004gf0.051gf0.092gf0.27gf0.126gf0.326gf0.768gf0.352g (4) ˇ : (small incentive) 0.200 0.269 0.114 0.105 0.150 0.037 0.190 0.314 (0.068) (0.116) (0.072) (0.09) (0.105) (0.123) (0.178) (0.148) (large grant) [0.004] [0.021] [0.116] [0.243] [0.157] [0.766] [0.288] [0.036] f0.071gf0.186gf0.36gf0.601gf0.403gf0.935gf0.796gf0.352g (5) ˇ : (large incentive) 0.248 0.289 0.212 0.209 0.292 0.117 0.039 0.356 (0.064) (0.106) (0.067) (0.079) (0.110) (0.108) (0.151) (0.146) (large grant) [<0.001] [0.007] [0.002] [0.009] [0.009] [0.282] [0.797] [0.016] f0.016gf0.124gf0.074gf0.16gf0.122gf0.800gf0.911gf0.271g (6) Observations 1932 1932 1928 1920 1927 1932 1928 1548 (7) Mean in no incentive, 0.031 0.055 0.039 0.033 0.053 0.040 0.017 0.082 small grant group Notes: Table uses sample of children testing anemic at baseline. Children are considered anemic if they have an altitude-adjusted hemoglobin concentration below 120 g/L (per WHO guidelines). Rows (1)–(5) show estimated coefﬁcients for treatment group indicators and interactions obtained by estimating equation (12) (controlling for the baseline value of the dependent variable, student age, student grade, student sex, number of students in the school, whether the school has a canteen, student teacher ratio, distance to the furthest village served, percent of boarding students, whether the school has implemented the “Free Lunch” policy, county dummy variables, and dummy variables for randomization strata). The dependent variable in each regression is a summary index constructed using the GLS weighting procedure in Anderson (2008). Estimates for the individual components of each index are shown in Online Appendix Tables A.5 and A.6. Standard errors are shown in parentheses, unadjusted p values are shown in square brackets and p values adjusted for multiple inference are shown in curly brackets. Adjusted p values were constructed using the free step-down resampling method of Westfall and Young (1993) with 10,000 iterations. Signiﬁcant at 10%; signiﬁcantat5%; signiﬁcant at 1% based on adjusted p-values. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 192 Journal of the European Economic Association The ﬁnding that administrators responded to large incentives by engaging with households is important for at least two related reasons. First, it demonstrates innovation and the use of local knowledge in response to performance incentives that reward outputs (health outcomes) as opposed to those that rigidly reward the use of prespeciﬁed inputs (such as vitamin consumption at school), as most performance incentives in the health sector do (Miller and Singer Babiarz 2014). Second, for outcomes jointly produced with beneﬁciary households (like good child nutrition), it demonstrates the potential of performance incentives that reward outputs to minimize offsetting compensatory behavior among beneﬁciaries (e.g. a common ﬁnding among studies of school lunch programs, ) (Jacoby 2002; Leonard 2003; Kazianga et al. 2009; Das et al. 2013). Behavioral Responses Underlying Result 2: Small Incentives. Second, we study the behavioral responses underlying Result 2—that the small incentive did not reduce anemia prevalence. Table 4 (column (1)) shows that administrators with small incentives did not signiﬁcantly increase the provision of supplements or food (row 1, columns (1)–(3)), nor did they increase their contact with households (column (8)) (Online Appendix Table A.7, row 1 also shows that none of the individual components of this index are statistically signiﬁcant (even using unadjusted p-values). Behavioral Responses Underlying Result 3: Large Block Grants. Third, we examine behavioral responses to large block grants, which reduced the prevalence of student anemia. The large block grant signiﬁcantly increased the provision of supplements and food (Table 4, row 3, column (1); adjusted p-value 0.004). This increase appears due to increases in both iron supplements (column (2), adjusted p-value 0.051) and iron-rich food (column (3), adjusted p-value 0.092). Interestingly, the large block grant may have also increased school contact with parents—suggesting that administrators worked through households to reduce anemia without any explicit incentives to do so. Although the estimate for the index in Table 4 is not statistically signiﬁcant (row 3, column (8)), some estimates for index components are larger than those for incentives. This may reﬂect intrinsic or prosocial motivation— or a sense of obligation or organizational mission (Ashraf, Bandiera, and Jack 2014). Furthermore, although the large block grant increased communication with households, the impact of block grants on food consumption at home is insigniﬁcant. We speculate that this could reﬂect less effort (relative to administrators with incentives) devoted to mitigating compensatory behavior by households in response to greater food provision at school (which seems to have increased, although not signiﬁcantly, with large grants). 37. We speculate that the bureaucratic environment is one reason that administrators chose to work through households. Administrators may have viewed this strategy as a way to reduce anemia (and increase rewards) while avoiding the risk of career harm due to possible adverse events. This career harm may also be more severe under incentives if incentives altered perceptions of administrators’ motivation for reducing anemia (analogous to how incentives may crowd-out effort if they alter the motives for prosocial tasks perceived by others—Benabou ´ and Tirole (2006)). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 193 Behavioral Responses Underlying Result 4: Substitution between Large Incentives and Large Block Grants. Finally, with the combination of large incentives and large block grants, we ﬁnd direct evidence of crowding-out of inputs consistent with our anemia estimates in Table 3. Speciﬁcally, Table 4 shows that for vitamin supplementation and consumption of iron-rich foods (both at school and at home), estimates for the interaction between the large incentive and large block grant are negative, implying substitution (row 5). The interaction between the small incentive and large grant is also negative, but smaller in magnitude and only marginally signiﬁcant. Overall, there is no evidence that resources and incentives are complements—and that at sufﬁciently high levels, they are substitutes. 5.3. Comparative Cost-Effectiveness Finally, we examine the comparative cost-effectiveness of each of our intervention combinations. In doing so, we consider both the subsample of children anemic at baseline and our full sample of children, and we present both “programmatic” cost-effectiveness (direct monetary program costs to the implementing organization) and social cost-effectiveness calculations. We calculate total social costs as the sum of: (a) programmatic costs; (b) the cost of public funds; and (c) costs incurred by households in responding to the interventions. From social costs we exclude incentive payments (apart from their contribution the cost of public funds), considering these payments to be transfers (Kremer, Miguel, and Thornton 2009). Incentive payments may also not be considered a cost, but rather simply another way of allocating salary expenditures (Muralidharan and Sundararaman 2011). Note that although we only consider comparative cost-effectiveness in reducing anemia prevalence (the primary outcome of the study), it is possible that the treatments, particularly the block grant, do produce other beneﬁts not considered here. Moreover, if the sole purpose of transfers to schools is to reduce anemia, there may be more cost-effective options than unrestricted block grants. Our goal is not to conduct a full cost-beneﬁt analysis, but rather to compare strategies for reducing anemia. Although we ﬁnd no intervention effects on standardized exam scores, even these (together with anemia measures) may fail to fully capture intervention beneﬁts. Table 5 presents these results. The key ﬁnding that we highlight is that although large block grants were as effective in reducing student anemia as large incentives, they were more expensive. First, considering full social costs and using the full sample, the relative cost per case of anemia averted was 1,453 yuan (about $227) in the large incentive/small block grant group—but 44% larger in the large block grant group 38. Given our experimental design, we are unable to rule out the possibility of complementarity at lower levels of resources. 39. See table notes for further details about these calculations. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 194 Journal of the European Economic Association TABLE 5. Comparative cost effectiveness calculations. Incremental amount relative to comparison (small block grant, no incentives) group Small block Small block Large block Large block Large block grant, small grant, large grant, no grant, small grant, large incentives incentives incentives incentives incentives Panel A: Costs Programmatic costs (1) Block grant 0.0 0.0 48.0 48.0 48.0 (2) Incentive payments 1.1 15.7 0.0 1.4 17.5 Cost of public funds (3) Cost of public funds 0.3 4.7 14.4 14.8 19.7 Costs to households (4) Full sample 45.5 60.7 90.8 38.3 62.7 (5) Anemic sample 34.6 95.0 147.5 26.6 49.4 Total costs (6) Programmatic 1.1 15.7 48.0 49.4 65.5 (7) Social—full sample 45.8 65.4 153.2 101.1 130.3 (8) Social—anemic 34.9 99.7 209.9 89.5 117.0 sample Panel B: Anemia reduction (percentage point reduction) (9) Full sample 0.028 0.045 0.073 0.074 0.032 (10) Anemic sample 0.012 0.138 0.145 0.199 0.087 Panel C: Cost effectiveness (cost of averting one anemia case) Full sample (11) Programmatic N.S. 349.6 657.5 668.1 2047.4 (12) Social N.S. 1452.7 2098.6 1366.1 4072.4 Anemic sample (13) Programmatic N.S. 114.0 331.0 248.4 753.1 (14) Social N.S. 722.5 1447.3 449.6 1345.1 Notes: All costs in renminbi per child (exchange rate as of September 2012 was 6.3 USD/RMB). Costs of the information intervention and anemia testing are excluded as these are constant across treatments. The cost of the information intervention was 1,020 yuan per school and the cost of anemia testing was 6.7 yuan per child. Additional administrative costs are assumed to be negligible as administration of block grants could be built into the administration of other school ﬁnances, administrative costs of rewards into administration of existing school administrator evaluation policies and policies, and monitoring of anemia into existing policies stipulating annual checkups for school children. In the absence of good estimates for China (and other developing countries), the cost of public funds is assumed to be 0.3 based on estimates for the United States (Ballard, Shoven, and Whalley, 1985). Social costs include costs incurred by households and exclude incentive payments (except the deadweight loss to taxation) considering them a transfer. Costs to households include costs of purchasing additional food and additional time spent attending parent meetings. Estimates for additional food costs are based on estimates for impact on meat, vegetable, and fruit consumption at home reported in Online Appendix Tables A.5 and A.6. Reported increases in times foods were consumed in the past week are assumed to be constant across all 24 weeks of the program. Serving sizes are assumed to be half of the recommended daily consumption (25 g of meat, 150 g of vegetables, and 100 g of fruit). Food prices are based on prices in local markets as reported by the school accountant at baseline. Time spent in parent meetings is based on estimates in Online Appendix Tables A.7 and A.8. One meeting is assumed to have an opportunity cost of 60 yuan (approximately half of local daily wages). Anemia reduction estimates in panel B are calculated from estimates in Table 2 and Online Appendix Table A.3. Effects not signiﬁcant (N.S.) for the small block grant, no incentives intervention. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 195 (2,099 yuan, or about $328). Second, the cost-effectiveness of these two interventions relative to each other is similar when we restrict our calculations to children anemic at baseline (as we do in Sections 4 and 5, following our preanalysis plan). Speciﬁcally, the large incentive/small block grant intervention is approximately 50% more cost effective than large block grant intervention without incentives (723 yuan, or $113, per case of anemia averted vs. 1,447 yuan, or $226). Finally, considering calculating only programmatic costs and using children anemic at baseline, the cost-effectiveness of the large incentive/small block grant intervention is roughly one third of that of the large block grant (114 yuan, or about $18 vs. 331 yuan, or about $52). 6. Conclusion This paper provides new evidence on how public sector managers respond to the provision of performance incentives. To the best of our knowledge, it is the ﬁrst study to analyze how behavioral responses to performance pay interact with exogenously assigned levels of resources—a critical issue in the design of incentive systems under stringent resource constraints (as is common in many developing countries). We report four key ﬁndings. First, when school administrators have fewer budgetary resources available to them, large performance incentives (with realized payments equivalent to a couple of months of annual salary) lead to substantial improvement in service delivery. This seems driven by greater effort rather than changes in budgetary resource allocation. In particular, we ﬁnd evidence that school administrators were able to innovate, working through their students’ parents to alter nutritional practices at home. Second, smaller incentives (one tenth the size of the larger ones) were ineffective on average and had negative effects on prosocially motivated administrators. Third, even absent explicit performance incentives, increasing school administrators’ budgets led to important improvements in performance (but was considerably less cost-effective than using performance incentives), implying the presence of other motives—potentially including intrinsic ones—in our context. Fourth, we ﬁnd that performance incentives and unrestricted grants are substitutes in the production of health when incentives are large. The degree of substitution is substantial: at the policy-relevant levels that we study, increasing the size of unrestricted block grants completely crowds out the effect of incentives (and vice versa). This is an important result for resource-poor environments in which both budgetary resources and performance incentives are used simultaneously as policy levers for improving the quality of public service delivery. There are of course limitations to this study. One is that, as with all empirical studies, our results are not generalizable to settings beyond our study context. However, 40. These estimates exclude administrative costs of the incentive scheme (assuming these would be rolled into existing policies as noted in the notes to Table 5). When the costs incurred for anemia testing (6.7 RMB per child in a sample of 50 children per school annually) are included in costs of the incentive scheme, the large incentive/small block grant remains more socially cost-effective than the large block grant at 1,848 yuan per case averted. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 196 Journal of the European Economic Association school-based nutrition programs like the one we study are nearly ubiquitous in low- and middle-income countries (Del Rosso and Marek 1996;Muk ˜ oma and Flisher 2004; Bundy et al. 2006; Orazem et al. 2008). Because a large share of children attend school in most countries, school-based programs are widely considered to be among the most cost-effective means of delivering child health interventions (Orazem et al. 2008). We believe that our study provides behavioral insights relevant in a variety of settings in which managers have budgetary discretion—and increasingly also face high powered incentives. Another is that our study estimates short-run intervention effects. Longer- run effects may differ, particularly as administrators learn more about the relationships among their effort, various inputs, and anemia reduction. Finally, although we ﬁnd that incentives for school administrators to reduce student anemia were effective, we also note features that may make our setting conducive to the use of performance incentives. One is that the rewarded outcome (anemia reduction) can be measured objectively and reliably. Relative to other settings, frontline workers (teachers in our setting) in China may also be relatively responsive to instruction from administrators, which might alleviate problems of moral hazard in teams that could be more prevalent elsewhere. 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M. Jukes, L. Drake, D. Bundy (2007)
School Health, Nutrition and Education for All: Levelling The Playing Field
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ChaudhuryNazmul, HammerJeffrey S. (2004). “Ghost Doctors: Absenteeism in Rural Bangladeshi Health Facilities.”The World Bank Economic Review, 18, 423–441.
ChaudhuryNazmul, HammerJeffrey S. (2004). “Ghost Doctors: Absenteeism in Rural Bangladeshi Health Facilities.”The World Bank Economic Review, 18, 423–441., ChaudhuryNazmul, HammerJeffrey S. (2004). “Ghost Doctors: Absenteeism in Rural Bangladeshi Health Facilities.”The World Bank Economic Review, 18, 423–441.
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GneezyUri, RustichiniAldo (2000). “Pay Enough or Don’t Pay at All.”Quarterly Journal of Economics, 115, 791–810.
GneezyUri, RustichiniAldo (2000). “Pay Enough or Don’t Pay at All.”Quarterly Journal of Economics, 115, 791–810., GneezyUri, RustichiniAldo (2000). “Pay Enough or Don’t Pay at All.”Quarterly Journal of Economics, 115, 791–810.

Publisher: Oxford University Press
Copyright: © The Author(s) 2019. Published by Oxford University Press on behalf of European Economic Association.
ISSN: 1542-4766
eISSN: 1542-4774
DOI: 10.1093/jeea/jvy047
Publisher site: See Article on Publisher Site

Abstract

Unlike performance incentives for private sector managers, little is known about performance incentives for managers in public sector bureaucracies. Through a randomized trial in rural China, we study performance incentives rewarding school administrators for reducing student anemia— as well as complementarity between incentives and orthogonally assigned discretionary resources. Large (but not small) incentives and unrestricted grants both reduced anemia, but incentives were more cost-effective. Although unrestricted grants and small incentives do not interact, grants fully crowd-out the effect of larger incentives. Our ﬁndings suggest that performance incentives can be effective in bureaucratic environments, but they are not complementary to discretionary resources. (JEL:O15, I12, H40, M52) The editor in charge of this paper was M. Daniele Paserman. Acknowledgments: Soledad Giardili and Ravi Somani provided excellent research assistance. We are grateful to Dana Andersen, Antonio Cabrales, Syngjoo Choi, Adeline Delavande, Katherine Donato, Will Dow, Eric French, Vivian Hoffmann, Rob Jensen, Victor Lavy, Hamish Low, Aprajit Mahajan, David Perez- ´ Castrillo, Ian Preston, Carol Propper, Imran Rasul, Pedro Rey-Biel, and Alessandro Tarozzi for helpful comments. We are also grateful to the National Institutes of Health (Grant Number: R01 HL106023), the Economic and Social Research Council via the ESRC-funded Centre for the Microeconomic Analysis of Public Policy (grant reference ES/H021221/1) at the Institute for Fiscal Studies, as well as the Global Under-Development Action Fund the Walter H. Shorenstein Asia-Paciﬁc Research Center at Stanford University for ﬁnancial support. Miller is a Research Associate at NBER. Marcos Vera-Hernandez ´ is a Research Fellow at the Institute for Fiscal Studies. E-mail: [email protected] (Luo); [email protected] (Miller); [email protected] (Rozelle); sean [email protected] (Sylvia); [email protected] (Vera-Hernandez) ´ Journal of the European Economic Association 2020 18(1):165–201 DOI: 10.1093/jeea/jvy047 The Author(s) 2019. Published by Oxford University Press on behalf of European Economic Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 166 Journal of the European Economic Association 1. Introduction The provision of public services in many developing countries is low in quality (Banerjee, Deaton, and Duﬂo 2004; World Bank 2004; Das, Hammer, and Leonard 2008; Berendes et al. 2011). Although the underlying reasons are complex and incompletely understood, the culprit is not simply lack of resources, inadequate training, or deﬁciencies in provider knowledge. Supply-side incentives are also often poorly aligned with social objectives. Absenteeism in many parts of the world is pervasive (Chaudhury and Hammer 2004; Kremer et al. 2005; Banerjee and Duﬂo 2006; Chaudhury et al. 2006;Lewis 2006), and providers often fail to do in practice what is within their knowledge and means (Das and Hammer 2004;Alcazar ´ et al. 2006; Chaudhury et al. 2006; Das and Hammer 2007; Leonard and Masatu 2010;Das et al. 2012; Sylvia et al. 2015). To better align provider incentives with social objectives, performance pay has become increasingly common in public sector service delivery (Oxman and Fretheim 2008; Eichler and Levine 2009; Miller and Babiarz 2014). Drawing on the logic of performance pay in human resource management (Lazear 1995; Hall and Liebman 1998; Lazear 2000), this approach provides direct ﬁnancial rewards for achieving prespeciﬁed performance targets. Despite its growing prominence, however, there is remarkably little empirical evidence on basic mechanism design considerations in the use of performance pay to improve public service delivery (Miller and Babiarz 2014). This paper contributes to the literature on performance pay in developing countries—and in particular, its design—through a large-scale experiment studying the interaction of performance incentives and unconditional block grants, both of varying sizes, for public sector administrators. Speciﬁcally, we provide primary school administrators (lead principals who are the managers and executive decision-makers in schools—hereafter “administrators”) with randomly assigned budget transfers (large and small) and randomly assigned ﬁnancial incentives (large and small) for improving the health of their students. Our health focus is anemia, a leading child health problem in rural China. Our study yields four key ﬁndings. First, we ﬁnd that larger incentives for anemia reduction were effective when administrators had fewer resources at their disposal for implementing the program. Incentives that provided substantial additional income to administrators (mean realized payouts of about 2 months of annual salary) reduced anemia among students who were anemic at baseline by 13.8 percentage points (or 38%). Second, in contrast, small incentives (one tenth the size of the larger incentives) were ineffective in reducing anemia—and were signiﬁcantly less effective than large incentives. Third, even absent explicit incentives, unrestricted budget transfers to school administrators led to sizeable reductions in anemia, suggesting other motives among administrators to allocate resources toward student nutrition. However, the 1. Previous studies have shown anemia rates among primary school aged students in poor regions of western China to be around 30% on average (Luo et al. 2011; Miller et al. 2012). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 167 resource cost of reducing anemia through larger school budgets was approximately twice as great (per case of anemia averted) as combining larger performance incentives with smaller budgets—implying that school administrators with explicit ﬁnancial incentives used smaller budgets with greater productive efﬁciency. Finally, we ﬁnd that explicit ﬁnancial incentives and unrestricted grants can be strong substitutes—and whether or not they are depends critically on incentive size. Speciﬁcally, we ﬁnd that large incentives and grants are pronounced substitutes. The effect is particularly strong: unrestricted resource transfers (of sizes chosen by government planners in practice) crowd-out the effect of large incentives. Importantly, we ﬁnd this pattern of results not only with student nutritional outcomes, but also with intermediate measures of resource allocation and effort (e.g., the provision of better nutrition and effort to persuade parents to improve their children’s diets at home). Substitution therefore reﬂects reductions in administrator effort with larger budgets (and not simply decreasing marginal returns to inputs in the biological production of child nutrition). Our ﬁndings contribute to existing literature on performance incentives in several ways. First, previous studies on the role of performance pay in the public sector have generally focused on front-line workers rather than public sector managers (or “bureaucrats”—an exception is Rasul and Rogger 2018). However, the scope of behavioral responses among managers is potentially much broader, possibly with greater potential for improving public sector service delivery. Speciﬁcally, rather than simply increasing effort, the actions of managers can have greater inﬂuence on productive and allocative efﬁciency because of the resources under over which they have decision-making authority (Holmstrom and Ricart i Costa 1986; Athey and Roberts 2001; Bandiera, Barankay, and Rasul 2007; Burgess et al. 2010). Second, existing studies of performance pay for managers generally examine the private sector, but insights from this literature cannot be easily extrapolated to 2. One concern in this context may be multitasking–in particular, whether or not incentives to reduce anemia led schools to focus on anemia reduction at the expense of teaching. In a separate analysis of multitasking effects, we ﬁnd no evidence that these incentives led to a reduction in student test scores on standardized Math and Chinese exams designed by the research team based on the national curriculum and designed to have good psychometric properties. However, we do ﬁnd some evidence of multitasking on margins of teaching where the costs to administrators and teachers of diverting effort are lower (i.e., tasks that would likely be the ﬁrst source of diverted effort). For example, in “secondary subjects” (subjects other than math or Chinese, which are not a focus of high school entrance exams and hence given less weight in the curriculum) we ﬁnd evidence of diverted effort when children were taught these subjects by a homeroom teacher (who was often given responsibilities related to the anemia program). 3. Several recent studies have examined performance pay provided as personal income to front line workers in the health and education sectors, including Lavy (2002, 2009), Glewwe et al. (2010), Muralidharan and Sundararaman (2011), Duﬂo et al. (2012), Ashraf et al. (2014), and Behrman et al. (2015). Other recent studies have focused on incentives to institutions paid as budget revenue. These include Bloom et al. (2006), Basinga et al. (2011), Gertler and Vermeersch (2012), Olken, Onishi, and Wong (2014), and Yip et al. (2014). Behrman et al. (2015) also study incentives for school administrators, but bundled with incentives to students and teachers. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 168 Journal of the European Economic Association bureaucracies. Career concerns can be particularly strong in bureaucracies—and they may overpower or interact with incentives created by performance pay (Gibbons and Murphy 1992). Moreover, civil servants may be considerably more prosocially or intrinsically motivated (Francois 2000; Francois and Vlassopoulos 2008; Tonin and Vlassopoulos 2015)—and performance pay may dampen the effects of these motivations (see Fehr and Falk 2002; Gneezy, Meier, and Rey-Biel 2011; Kamenica 2012 for reviews). Finally, public sector production processes tend to be both more complex (due to multiple objectives and multiple agents—Dixit (2002)) and more heterogeneous (due to a primary goal being to expand access, which necessitates operation in a wider range of contexts than private sector organizations that have more scope to select the markets in which they operate). Performance pay may therefore be ineffective if rewards are not well-aligned with effective inputs across the range of contexts within which an organization operates. Third, we contribute to existing literature by studying three mechanism design considerations of performance pay. One is that we reward outputs directly. In contrast to rewarding inputs, performance incentives for outputs strengthens incentives for managers to draw on local information and contextual knowledge to improve both allocative and productive efﬁciency—or to “innovate.” Our study is one of the ﬁrst focused on health to reward health outputs—and we do indeed ﬁnd evidence of managerial innovation (school administrators successfully work with parents to improve diets at home). Another is that we directly study differential behavioral responses to performance incentives of varying sizes. Existing literature on this issue is split: a number of studies outside of organizational settings report large responses to very modest rewards (as well as highly elastic demand at prices close to zero), whereas others suggest small responses—or even reductions in effort (e.g. when intrinsic motivation is crowded-out). Our results are more closely aligned with the latter. Finally, we provide ﬁrst evidence on how incentives interact with the amount of resources under contracted agents’ control. A common focus is on the relative effects of 4. On performance pay for corporate executives and private sector managers in developed countries, see Jensen and Murphy (1990), Hall and Liebman (1998), Murphy (1999), Hall and Murphy (2003), and Oyer and Schaefer (2005). Bandiera et al. (2007) and Bloom et al. (2013) study these virtues of performance pay for private sector managers in developing countries. Burgess et al. (2010) study a team- based incentive scheme in the context of a government agency in the United Kingdom; although the scheme was not explicitly targeted to managers, the authors ﬁnd that the team-based incentive induced managers to reallocate more efﬁcient workers to incentivized tasks. 5. The two exceptions of which we are aware are Singh (2015) and Miller et al. (2012). Though not studying the health impacts of incentives tied to health outcomes, Leonard (2003) studies traditional healers’ use of outcome-contingent contracts in Cameroun. In the education sector, performance pay rewarding good test scores is more common (Lavy 2009; Muralidharan and Sundararaman 2011; Behrman et al. 2015). 6. Kremer and Miguel (2007), Thornton (2008), Banerjee et al. (2010), Cohen and Dupas (2010), Karlan, List, and Shaﬁr (2011), Duﬂo, Kremer, and Robinson (2011). 7. See Gneezy, Meier, and Rey-Biel (2011) for several examples. 8. We also note at least two key differences with this previous literature: one is that receiving incentive payments in our study required sustained behavior change (reducing iron deﬁciency anemia requires several Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 169 incentive and resource-based approaches (see Lavy 2002; Hanushek 2006); however, these two approaches are often implemented simultaneously and are likely to interact in important ways. Theoretically, incentives and resources available to managers can be complements or substitutes. We study this issue both theoretically and empirically, ﬁnd evidence of strong substitution when incentives and budgets are large. The rest of this paper is organized as follows. Section 2 presents a conceptual framework for understanding school administrators’ behavioral responses to output- based performance incentives. Section 3 provides background on school-based nutrition programs as well as the causes and consequences of anemia. Section 4 describes our experimental design, data collection, and methods. Section 5 reports our results, and Section 6 concludes. 2. Conceptual Framework In this section, we propose a simple model of the school administrator decision problem that we study. Speciﬁcally, we consider the inﬂuence of both output-based performance incentives and discretionary resources on organizational effort—as well as how they interact (i.e., if they are substitutes or complements). We model the school administrator (bureaucrat) as choosing effort e to reduce anemia in the school. Additionally, the school administrator also decides on the allocation of resources—in particular, how to divide the school budget G between anemia reduction A and other school functions G A. The health production function f(e, A) combines the school administrator’s effort e and the funds allocated to reducing anemia A in determining student health H. The school administrator’s maximization problem is therefore max w C H v .e/ C S .G A/ (1) e;A subj: toW w D tH C m; (2) H D f .e; A/ ; (3) G A (4) Total take-home pay w includes both base pay m and a reward or bonus for improving student health, tH, which is the product of t, the marginal bonus, and H, the net gain in student health (in our case, the net reduction in the number of students with 0 00 anemia). Disutility of effort, v(e), is also strictly increasing but convex: v > 0, v 0. The parameter , which is non-negative, allows the school administrator to be altruistic, deriving direct utility from student health (prosociality and public service motivation months of dietary chance), and another is that because all school administrators receive information about anemia, the presence of incentives may not alter its salience as much (Benhassine et al. 2015). 9. See Rogger (2014)and Nath (2015) for other models of bureaucratic behavior with choices of effort. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 170 Journal of the European Economic Association are often considered important among public sector workers—e.g., see Besley and Ghatak 2007;DalBo, ´ Finan, and Rossi 2013). The school administrator also derives utility from school functions unrelated to health, S(G A), which is also assumed 0 0 to be increasing (S > 0) and concave (S 0). We make standard assumptions that the health production function, f(e, A), is increasing in both arguments and concave (f > 0, f < 0, f > 0, f < 0, f f f 0) and the intuitive assumption that e ee A AA ee AA eA f 0, or that the marginal productivity of one input is nondecreasing in the level of eA the other input. Assuming an interior solution, the solution to (1)–(4) is equivalent to the solution to max . C t / f .e; A/ v .e/ C S .G A/ : (5) e;A The ﬁrst order conditions are U . C t / f .e; A/ v .e/ D 0; (6) e e U . C t / f .e; A/ S .G A/ D 0: (7) A A The ﬁrst order condition (6) implies that the optimal level of effort equates the marginal beneﬁt of increasing effort (the increase in health, f (e, A), multiplied by t C , reﬂecting both the increase in take-home pay and the altruistic increase in direct utility) with its marginal cost. Equivalently, the ﬁrst order condition (7) implies that resources G are invested in activities unrelated to nutrition up to the point that its marginal beneﬁt, S (G A), equals the marginal beneﬁt of investing in nutrition-related activities, ( C t)f (e, A). The second order conditions required for a maximum are U . C t / f .e; A/ v <0; (8) ee ee U . C t / f .e; A/ C S <0; (9) AA AA jH j U U U >0; where U . C t / f : (10) ee AA eA eA eA 2.1. Comparative Statics We analyze how the school administrator’s choice of effort and resources dedicated to nutrition changes both with incentives t and discretionary resources G—both separately and in combination (as we study empirically through our experiment). First, we consider each effect separately; the corresponding ﬁrst order comparative statics (see the Online Appendix B for these and other derivations and proofs) are de f . C t / f C S C . C t / f f e AA A eA D >0; (11) dt jH j f . C t / f C v C . C t / f f dA A ee e eA D >0; (12) dt jH j Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 171 de . C t / f S eA D >0; (13) dG jH j 00 00 . C t / f v S dA ee D >0: (14) dG jH j Intuitively, an increase in the incentive rate t leads to an increase in both effort and the amount of resources dedicated to nutrition (11–12). Notably, these increases are greater when f is larger. Naturally, the larger that f is, the larger is the marginal eA eA productivity of either e or A when the other input increases, accentuating the effect of increasing the incentive rate. An increase in discretionary resources also raises both effort and resources devoted to nutrition (13–14). Note in (13) that if the marginal productivity of effort were independent of the level of A—that is, if f D 0, then changes in discretionary eA resources would not inﬂuence effort. This is not a general property, but rather a result of our simplifying assumption that v(e) and S(G A) are additive in the utility function, so e and A only interact through the production function. An important result is also that 0 < dA/dG < 1. This means that an increase in G translates into a positive but smaller increase in A, implying that the full increase in G is not entirely allocated to A, but rather a share is invested in non-nutritional activities. This is clear from (7): if G and A increased by the same amount, then the term S (G A) would not change—and hence could not be equal to ( C t)f (e, A). From ﬁrst order conditions (11–14), it then follows that dH de dA D f C f >0; (15) e A dt dt dt dH de dA D f C f >0: (16) e A dG dG dG To understand the conditions under which incentives and resources are complements or substitutes, we must compute the cross-partial derivatives of e, A, and H with respect to t and G. Note that because the ﬁrst order comparative statics (11–14) depend on the second derivatives of v(e),S(G A), and f(e, A), the cross- partial derivatives will necessarily depend on the third order derivatives of v(e), S(G A), and f(e, A). In order to gain insight, we make the simplifying assumption that the third order derivatives of the production function are null (i.e., that the production 000 000 10 function is quadratic) while leaving v and S unrestricted. Using the chain rule on H D f(e, A), the cross-partial derivative of H with respect to t and G is dH de de dA dA de dA de dA D f C f C f C ee AA Ae dt dG dG dt dG dt dG dt dt dG de dA C f C f ; (17) e A dt dG dt dG 10. Note that the third order derivatives of the production function include f , f , f , and f ;the eee AAA eeA eAA solution would be very cumbersome if we did not assume that these are zero. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 172 Journal of the European Economic Association which could be positive (implying that t and G are complements) or negative (implying that they are substitutes) because the ﬁrst term in brackets is negative, the second term is positive (and its size crucially depends on f ), and the third and fourth could be eA positive or negative (as shown in Online Appendix B, which provides expressions for de=dt dG and dA=d t d G). Because the sign of dH=d t d G cannot be determined a priori, we discuss in what follows how its sign depends on the sign and size of key 000 000 derivatives: S , v , f . eA A key determinant of dH=d t d G is f , how much the productivity of effort eA increases when A increases. A larger f favors complementarity between t and G eA (dH=d t d G > 0). Intuitively, larger values of G imply larger values of A, leading to effort being more productive (f > 0), and hence a larger response to the incentive. eA Mathematically, f multiplies the second term in (17), which is positive, and also eA enters into the formulae for de/dtdG and dA/dtdG. 000 0 The third derivative of v(e), v , deﬁnes whether the marginal cost of effort, v ,is 000 000 convex (v > 0) or concave (v < 0). A convex (concave) marginal cost of effort favor substitution (complementarity). To understand the intuition, assume that the marginal 000 ˛ cost of effort is concave, that is, v < 0 (i.e., v(e) D e ,2 <˛ < 3), and consider the following approximation: h l de.GDG ;t / de.GDG ;t / de dt dt h l ;G >G : (18) h l dt dG G G h l Note that de=dG > 0, so effort is greater for G than for G . Moreover, the concavity of the marginal cost of effort implies that, at higher levels of effort, the marginal cost of effort increases at a lower rate. Hence, the marginal cost of effort increases at a h l lower rate at G than at G . Hence, the response of effort to an increase in incentives, h l de(G, t)/dt, that is, the terms in the numerator of (18), might be larger for G than G because the increase in the marginal cost of effort will be smaller. A similar argument can be made to explain why S > 0 is conducive to complementarity. Ultimately, both e and A are inputs in the health production function, but v(e) is increasing in e whereas S(G A) is decreasing in A. This explains why if 000 000 12 v < 0 favors complementarity, S > 0 also does. The ﬂexibility of the model means that our predictions depend on three key parameters. Having discussed the effect of each of them individually, Table 1 summarizes the necessary and sufﬁcient conditions that the model provides. 000 000 11. Note that if S < 0, the term S f , which is part of de/dtdG (see the Online Appendix), can partially eA offset this effect. 12. Note that if one assumed a simple power function such as S(G A) D (G A) , the condition that 00 000 S < 0, would also imply necessarily that S > 0. However, this would not be the case for other functional forms, such as a cubic polynomial. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 173 TABLE 1. Summary of necessary and sufﬁcient conditions implied by the model. dH 000 000 S 0, and v 0, and f D 0 imply that <0 eA dtdG dH 000 000 S > 0, or v < 0, or f > 0 are necessary conditions for >0 eA dtdG 3. Background 3.1. School-Based Nutrition Programs School-based interventions are believed to be among the most cost-effective approaches for delivering health and nutrition services to children in developing countries (Bundy and Guyatt 1996; Jukes, Drake, and Bundy 2008; Orazem, Glewwe, and Patrinos 2008). Because schools are natural points of contact with school-aged children, they may provide a platform from which health and nutrition interventions can be delivered at relatively low cost (Bundy and Guyatt 1996; Bundy et al. 2006; Jukes, Drake, and Bundy 2008). Because of this, school-based health, nutrition and feeding programs are a ubiquitously central function of schools, particularly in developing countries. In China, schools have the legal responsibility to promote the health of their students (Education Law of the Peoples Republic of China, 1995). Although school administrators are evaluated as part of the cadre evaluation system (ganbu kaohe zhidu)—a system for evaluating public ofﬁcials and servants in China (Whiting 2004)—measures of child health are not typically included as criteria for evaluation. 3.2. The Causes and Consequences of Anemia Our study examines school-based programs to reduce anemia. Anemia is estimated to affect nearly one quarter of all school-aged children worldwide (World Health Organization 2001). Although there are many causes of anemia (including a variety of genetic disorders and infections as well as nutritional deﬁciencies), iron deﬁciency accounts for about 50% of cases globally (Balarajan et al. 2011; Pasricha et al. 2013) —and 85%–95% of cases in China (Du et al. 2000). The consequences of iron deﬁciency—with or without anemia—can be substantial, particularly for children at critical stages of development. A large literature links iron deﬁciency to fatigue and reduced work capacity among adolescents and adults, impaired cognition and cognitive development among children, and reduced immune response for all age groups (Thomas et al. 2006; World Health Organization 2001;Yip 2001; Balarajan et al. 2011). School-aged children with anemia (the focus of our study) 13. There is some debate in the public health literature on the proportion of the anemia burden attributable to iron deﬁciency (Balarajan et al. 2011). Intestinal worms are unlikely to be a major cause of anemia in our study areas as the prevalence of hookworm (the parasite most commonly associated with anemia) is low (Xu et al. 1995). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 174 Journal of the European Economic Association have also been shown to have inferior educational outcomes (grades, attendance, and school attainment—Taras 2005; Nokes, van den Bosch, and Bundy 1998). 3.3. Biomedical Strategies for Reducing Anemia Increasing iron consumption can effectively prevent iron deﬁciency anemia. Worldwide, fortifying staple foods with iron has historically been an effective approach to addressing micronutrient deﬁciencies (Allen et al. 2006). Fortiﬁcation is an attractive strategy because it requires little behavior change and because it can be implemented on a large scale. However, fortiﬁcation of staple foods may be ineffective in areas like Northwest China in which households grow and consume their own food (Allen et al. 2006). An alternative approach is to increase the consumption of naturally iron-rich foods and those that promote iron absorption during digestion. Animal sources (including red meats, ﬁsh, and poultry) provide heme iron, which is more easily absorbed during digestion; plant sources (including green, leafy vegetables) provide nonheme iron, which is less readily absorbed—but can be promoted by consumption of vitamin C (and inhibited by consumption of milk and other calcium-rich products). Finally, a third approach is the delivery of micronutrient supplements (e.g., vitamins) containing iron. To be effective, however, regular consumption over several few months is necessary—and so inadequate compliance may render supplementation ineffective (Bobonis et al. 2006; Bhutta et al. 2013; Pasricha et al. 2013; Martorell et al. 2015). 4. The Experiment 4.1. Sampling To draw our study sample, we began with all 36 counties ofﬁcially designated by the Chinese government as “poverty counties” in ﬁve regions (prefectures) in western China (Haidong in Qinghai Province, Dingxi, Tianshui, and Longnan in Gansu Province, and Ankang in Shaanxi Province—see Figure 1). In August 2011, we conducted a canvass survey in each county to construct a list of all rural primary schools and the number of students enrolled in each. Restricting our sampling frame to primary schools with 150–300 students total, we randomly selected 170 of 1410 14. Previous trials addressing iron deﬁciency and anemia have suffered from low levels of compliance or attempted to preempt compliance problems. Bobonis et al. (2006), for example, instructed preschool teachers to provide children with iron therapy for 30 days following health camps but found that only around 18 days were actually administered. The WISE study in Indonesia (Thomas et al. 2006)hired facilitators to regularly visit participants and remind them to take their supplements. 15. A lower bound of 150 students was chosen to ensure that the number of samples students per school was enough to meet power requirements. 300 was chosen as the upper bound to keep the project within Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 175 FIGURE 1. Study regions. eligible schools for inclusion in our study (and limited our selection to one school per township ). Our sample size was based on power calculations conducted using data from primary schools in the same region of China (Miller et al. 2012). Within study schools, we randomly sampled 50 fourth and ﬁfth grade students from each school. In China, fourth and ﬁfth grade students are typically 10–11 years old, and we chose these grades to select students whom we considered sufﬁciently old to provide meaningful survey responses—but also sufﬁciently young to be generally prepubescent (given the independent effect of menarche on hemoglobin concentration). budget. These bounds are on reported school sizes; actual numbers of students are often signiﬁcantly less than reported. Note that 39.9% of rural primary schools in the sampling frame (all rural primary schools in project counties) were reported to be within this range. 16. Local administration of schools is generally done at the school district level, which is below the township. Contamination due to two school administrators meeting at events organized at higher levels, for example, was thus unlikely. 17. Using data from Miller et al. (2012), we performed Monte Carlo simulations to conduct power calculations for students who were anemic at the time of that study’s baseline survey. The intraclass correlation was estimated adjusting for covariates (baseline hemoglobin concentration, the number of students in each school, whether schools had a kitchen, student–teacher ratio, distance to the furthest village served by the school, percent boarding students, and county dummies), which we also speciﬁed as covariates in the current study’s preanalysis plan. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 176 Journal of the European Economic Association We also conducted physical exams and collected data from students from other grades at baseline to obfuscate our focus on fourth and ﬁfth graders. 4.2. Data Collection We conducted our baseline survey in September 2011 and our follow-up survey in May 2012 (at the beginning and end of the 2011–2012 academic year), collecting detailed information on students, households, school administrators, and schools. Student Surveys. We interviewed all sampled students at their school, collecting information on student background, health behaviors related to anemia, school activities, and general health. To collect information on school and home feeding practices, students were also given standard food frequency questionnaires to record information about food consumption at school and at home over the past week. We also measured student blood hemoglobin (Hb) concentration at the time of the student survey. Nurses from the Medical School of Xi’an Jiaotong University accompanied study enumerators, collecting ﬁnger-prick blood samples to analyze on- site (at schools) using HemoCue Hb 201C assessment systems. Household Surveys. For each sampled student, we also collected information on students’ households using forms completed by parents. Speciﬁcally, these surveys collected information about interactions between parents and the school, household income and assets, health-related expenditures, expenditures on food and information on other household members, focusing on household characteristics that students would be unlikely to know themselves. School Administrator Surveys. We interviewed school administrators (bureaucrats) at three different points in time: before and after school administrators were told about the incentive contract and block grant to which they were assigned and again at endline. At baseline, school administrators provided information about their background, job history, salary, and compensation as well as perceptions of professional responsibilities and anemia knowledge. Using scales adapted from Grant (2008), we also measured the intrinsic and prosocial motivation of administrators. Following their participation in the training session on anemia (conducted 3 weeks after the baseline survey) 18. Information on food consumption was collected using a seven-day recall “food frequency questionnaires” (FFQs) completed by students as part of the endline survey. These questionnaires asked children the number of times they had eaten each of 33 food items in the past seven days, separately for school and home. Food frequency questionnaires (FFQs) have long been used in nutrition research and have been recommended for use in large surveys of children given low cost and low respondent burden (McPherson et al. 2000; Magarey et al. 2011). FFQ responses by children about their own consumption has been shown to be more accurate than the responses of their parents (Burrows et al. 2013). 19. For budgetary reasons, household surveys were given to students to take home and return. As a result, household forms are missing for approximately 20% of students. All possible information on students and households was collected with the student survey, which was administered by enumerators. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 177 300 Schools Group A: No Group B: Small Group C: Large Other Experimental Administrator Anemia Reduction Anemia Reduction Groups Incentive Incentive (40 Schools) Incentive (65 Schools) (130 Schools) (65 Schools) A1. Small Block B1. Small Block C1. Small Block Grant Grant Grant (32 Schools) (20 Schools) (33 Schools) A2. Large Block B2. Large Block C2. Large Block Grant Grant Grant (33 Schools) (20 Schools) (32 Schools) FIGURE 2. Experimental design. administrators were given a second short survey to measure their understanding of the training material. School Surveys. Finally, we collected basic information from schools (about enrollment, stafﬁng, facilities, ﬁnances, and meal provision) and teachers (about teacher characteristics, communication with parents, and teaching practices). 4.3. Experimental Design We designed our study as a cluster-randomized trial using a 3 2 crosscutting design (Figure 2). After conducting our baseline survey, we provided all school administrators with information about anemia (which included presentations and a video presentation by a Chinese nutrition specialist, see script in Online Appendix C), and schools were randomly assigned one of six experimental cells (see Figure 3 for the study timeline). The ﬁrst three paths of Figure 2 show randomly-assigned incentive groups: a group without incentives (group A), a “small” incentive group (group B), and a “large” incentive group (group C). Across these arms are two orthogonally assigned block grant groups: a “small” block grant group (group 1) and a “large” block grant group (group 2). The reference group in our six-cell design is the default policy (education about anemia coupled with a modest resource transfer and no incentives, group A1). 20. Thus, all schools in the experiment received a small or large grant. This was done to ensure that all schools had access to resources that could be devoted to anemia reduction. In a previous study, we ﬁnd that educating school administrators on anemia (including the same information as in the current study) alone, Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 178 Journal of the European Economic Association Anemia Training, Grant Notification, Incentive Contract Baseline Endline Signing and Post Survey Survey Training Survey School Administrators Contacted School Administrators Contacted to Confirm First Grant and to Confirm Second Grant and Supplement Installment Supplement Installment Delivery of First Grant Delivery of Second Grant Installment and Installment and Supplements (if ordered) Supplements (if ordered) September May October November December January February March April 2011 2012 FIGURE 3. Data collection and intervention timeline. To improve power, we used a stratiﬁed randomization procedure. Speciﬁcally, using joint quintiles of the baseline distribution of school-level hemoglobin concentration and combined standardized math and Chinese exam scores—yielding 25 strata, we randomized cell assignment within each stratum. Stratiﬁcation improves power by ensuring balance on these covariates between experimental groups. Our analysis takes this randomization procedure into account, conditioning on stratum ﬁxed effects (Bruhn and McKenzie 2009). Incentives for Anemia Reduction. In the large incentive arm (65 schools, group C in Figure 2), we offered school administrators ﬁnancial incentives to be paid as private income according to the net reduction in number of students identiﬁed as anemic between the beginning and end of the school year. The speciﬁc structure of the large incentive contract was 125 RMB N N if N N >0 b e b e P D ; 0 otherwise where N is the number of students found to be anemic at baseline and N is the number b e of who were anemic at the time of the endline survey. Based on an earlier study (Miller without incentives or grants, had no detectable impact on anemia rates (Miller et al. 2012). Our reference group also mimics how a recent Chinese school nutrition program (costing 16 billion yuan per year) was designed. Under the program, local education bureaus and schools receive 3 yuan per day per student (4 yuan for boarding students) to provide nutritious meals. How exactly the program is implemented and monitored varies widely across localities. 21. We measured anemia using a sample of 50 fourth and ﬁfth graders and calculated the implied number of anemic children in the school using the prevalence rate in our sample. Although administrators could possibly discern which students were tested at baseline (although testing was done before contract assignment), they were later told explicitly that another sample of students would be drawn at the end of the school year. Moreover, unreported analyses show that teachers were unable to correctly name or identify anemic students at endline. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 179 et al. 2012), the contract increment (125 yuan (RMB), or about $19.40 ) per student reduction was chosen to provide roughly two months of a school administrator’s annual salary for a feasible reduction in anemia given previous studies (a reduction of about 50%). Actual payouts for school administrators with the large incentive and small block were ultimately 3,303 yuan (or about $516)—approximately two month’s base pay for school administrators in this region. We did not reveal the identity of students who were anemic at baseline to administrators (and when we asked teachers to identify students who were anemic at endline, they were unable to do so). The small incentive arm (40 schools, group B in Figure 2) was identical to the large incentive arm except that the magnitude of the incremental incentive was ten times smaller (12.5 RMB, or about $1.95 per student reduction in anemia between baseline and follow-up in our sample). This magnitude of this incentive provides roughly 0.2 additional months of annual salary for the same feasible reduction in anemia given previous studies. At the time that school administrators signed incentive contracts, they were told the (implied) number of anemic students in their schools (the identity of anemic children was not revealed). Contracts were written using ofﬁcial letterhead of the Chinese Academy of Sciences (a government agency) and counter-signed by the deputy director of the implementing research center (school administrators signed two copies of the contract, one of which they kept). Note that all interventions were implemented in partnership with local education bureaus, signifying to school administrators that the project was sanctioned by local governments. Block Grants. The small block grant (group 1 in Figure 2) was 0.3 RMB ($0.05) per student per day (85 schools), which we calculated to be adequate for school administrators to purchase vitamins for each student to take daily. The large block grant (group 2 in Figure 2) was 0.7 RMB ($0.11) per student per day (85 schools). In total, small block grant schools received 7,452 yuan ($1164) on average and large block grant schools received 17,388 yuan ($2717). These grants were given to schools in two installments, once at the beginning of the program and another approximately half way 22. We use a conversion rate of $1 D 6.4 RMB, the approximate exchange rate at the time of the baseline survey (September 2011). 23. There are presumably superior contract structures, but optimal contract design requires substantial information not available to us, including information about the cost of provider effort, the productivity of provider effort, and the utility functions of both providers and the contracting “principal” (Laffont and Tirole 1993; Salanie´ 2005). Simple, easily understandable contracts may also appear more transparent to school administrators and promote credibility. 24. We did reveal the identity of students who were severely anemic (with hemoglobin concentration below 80 g/L) as these students required immediate medical attention. There were 3 such students found at baseline. 25. Note that administrators in all study cells were provided the same information about the number of anemic children in their respective schools. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 180 Journal of the European Economic Association No Incentive Small Large No Incentive Small Large Incentive Incentive Incentive Incentive Small Block Grant Large Block Grant Iron Supplements/ Foodstuff Fortified Soy, Flour Communication/ Non−nutrition Transfers to Households FIGURE 4. Reported use of block grants by category. Figure shows mean values of reported use of block grants by experimental group from the endline survey. Expenditure amounts are per student. through the school year. Although funds were given in the context of the nutrition program roll-out, administrators were explicitly told that they were free to allocate these at their discretion to other school functions beneﬁtting students—whether this be for educational goods, health speciﬁc goods, or general school supplies. Indeed, Figure 4 shows that administrators used a substantial share of their grants for activities unrelated to nutrition. Health Education. Because knowledge about anemia in our study areas was poor, prior to revealing treatment assignment, we provided health education about nutrition 26. After explaining block grant assignment to administrators, we asked them to complete a nonbinding budget plan for how they intended to use the block grant. Our study team emphasized that this plan was nonbinding, but this plan would be used to coordinate orders for iron supplements to be delivered to schools. This was necessary because the market for supplements in rural areas is limited. Administrators were free to change their supplement orders at any time. Administrators had no reason to believe that second installments were conditional on performance—they were given an explicit time frame and told an explicit amount for the second installment. 27. Note that although these transfers were not large compared to total school expenditures, they do represent a signiﬁcant increase in budgetary autonomy for school administrators as the bulk of school expenditures are earmarked for speciﬁed uses at higher levels of administration. Although administrators often have discretion over small expenditures, larger expenses require approval from upper levels. Reported Expenditure from Grant (yuan per student) 0 10 20 30 40 Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 181 and anemia to all school administrators in our study (see Online Appendix C). Our health education materials were based on published, peer-reviewed studies and speciﬁcally included information about: (1) the prevalence and causes of anemia, (2) the consequences of anemia (including its effect on cognitive development and academic performance), and (3) efﬁcacious nutritional approaches to reduce anemia (increasing dietary intake of iron-rich foods, nutritional supplementation with iron fortiﬁed soy and ﬂour or with supplements, etc.). 4.4. Balance and Attrition Summary statistics and tests for balance across study arms are shown in Table 2. Panel A shows student level characteristics (N D 2051), panel B shows characteristics of schools (N D 167), and panel C shows characteristics of school administrators (N D 167). The ﬁrst two columns of the table give the mean and standard deviation of each variable in the comparison (small block grant, no incentive) group. Columns (3)– (7) show coefﬁcients on treatment variables and interactions estimated using equation (19), controlling only for randomization strata ﬁxed effects. The ﬁnal column shows the p-value from a test that the coefﬁcients are jointly zero for each characteristic. Only 4 of the 75 tests are signiﬁcant at the 10% level, and a test for joint equality is rejected at the 10% level for only one characteristic (the number of times meat was consumed in the past week). Joint tests for all 15 characteristics reveal no signiﬁcant differences. The overall attrition rate between baseline and endline surveys was 6.2% in our sample of children anemic at baseline (5% for the full sample). Deﬁning attrition as a missing hemoglobin measurement at endline for students with a baseline measurement, Online Appendix Table A.2 shows that there were no meaningful differences in attrition across treatment groups (columns (1) and (2)). Analyzing the correlates of a missing household survey at endline conditional on a child not dropping out, Online Appendix Table A.2 also shows that neither the treatment indicators nor other covariates are signiﬁcantly correlated with a missing household survey form. 28. This table shows summary statistics and tests balance for our main analysis sample of students initially anemic at baseline. Summary statistics and balance tests for the full sample are given in Online Appendix Table A.1. 29. Although 170 schools were included in the study, no students were found to be anemic in 3 schools at baseline. No schools refused participation in the study. The baseline anemia rate (deﬁned as Hb < 120 g/L) in the full sample was 24%. Online Appendix Table A.11 shows transitions in and out of anemia status in the comparison (small grant only) group. 30. These tests were conducted by regressing treatment status on all 15 baseline covariates and testing that the coefﬁcients were jointly zero. The smallest p-value from these F-tests was 0.29. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 182 Journal of the European Economic Association TABLE 2. Descriptive statistics and balance check. No incentive, small grant group Coefﬁcient (standard error) on (Small- (Large Joint Test Small Large incentive) incentive) p-value: all Mean SD incentive incentive Large grant (large grant) (large grant) coefﬁcients D 0 Observations (1) (2) (3) (4) (5) (6) (7) (8) (9) Panel A: Child characteristics (1) Hemoglobin 118.446 7.541 0.965 1.525 0.653 2.868 1.479 0.420 2051 concentration (g/L) (1.326) (1.163) (1.438) (1.959) (1.761) (2) Age (years) 10.514 1.153 0.046 0.077 0.113 0.002 0.070 0.914 2051 (0.166) (0.125) (0.134) (0.242) (0.189) (3) 5th Grade (0/1) 0.468 – 0.055 0.002 0.003 0.106 0.016 0.177 2051 (0.032) (0.029) (0.031) (0.050) (0.042) (4) Female (0/1) 0.530 – 0.003 0.021 0.009 0.001 0.044 0.945 2051 (0.044) (0.035) (0.039) (0.060) (0.052) (5) Times consumed 3.922 4.145 0.534 1.293 0.352 0.039 0.909 0.091 2051 meat in past week (incl. chicken, pork, beef, lamb) (0.618) (0.453) (0.709) (0.888) (0.790) Panel B: School characteristics (6) Number of students 203.733 55.788 2.424 7.060 1.925 21.948 9.631 0.725 167 (16.959) (14.194) (15.304) (25.245) (20.780) (7) Has kitchen (0/1) 0.067 – 0.135 0.068 0.054 0.071 0.052 0.732 167 (0.099) (0.077) (0.085) (0.161) (0.120) (8) Student–teacher 16.192 4.356 2.859 1.190 0.019 1.804 0.866 0.185 167 ratio (1.377) (1.216) (1.182) (1.928) (1.678) (9) Time to furthest 61.167 37.570 12.294 2.256 4.020 7.468 4.605 0.918 167 village served (min) (13.474) (11.962) (12.520) (21.139) (17.681) Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 183 TABLE 2. Continued No incentive, small Coefﬁcient (standard error) on grant group Mean SD Small Large Large grant (Small- (Large Joint Test Observations incentive incentive incentive) incentive) p-value: all (large grant) (large grant) coefﬁcients D 0 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Percent boarding 4.277 9.493 2.228 0.756 1.310 0.757 1.804 0.985 167 students (%) (3.976) (2.899) (3.400) (6.204) (5.107) Panel C: School administrator characteristics (11) Male (0/1) 0.967 – 0.015 0.028 0.038 0.014 0.070 0.606 167 (0.051) (0.032) (0.034) (0.053) (0.046) (12) Age (years) 39.567 7.398 1.550 1.299 1.599 4.730 0.090 0.383 167 (2.112) (1.837) (1.882) (3.022) (2.601) (13) Higher education 0.900 – 0.018 0.007 0.107 0.032 0.007 0.558 167 degree (0/1) (0.092) (0.081) (0.093) (0.136) (0.126) (14) Experience (years) 8.333 6.227 0.194 1.124 0.898 2.761 0.165 0.137 167 (1.531) (1.786) (1.630) (2.210) (2.577) (15) Monthly base 1855.067 706.106 57.049 110.575 36.880 312.491 35.944 0.602 167 salary (yuan) (196.310) (178.286) (182.302) (305.716) (247.052) Notes: Table uses sample of children testing anemic at baseline. Children are considered anemic if they have an altitude-adjusted hemoglobin concentration below 120 g/L (per WHO guidelines). The ﬁrst and second columns show the mean and standard deviation in the comparison (small grant, no incentives) group. Columns (3) through (7) show coefﬁcients and standard errors from a regression of each characteristic on indicators for incentive and large grant treatment group indicators and there interactions, controlling for randomization strata. Column (8) shows the p-value from a test that coefﬁcients are jointly zero. All tests account for clustering at the school level. Signiﬁcant at 10%; signiﬁcant at 5%; signiﬁcant at 1%. Source: Baseline survey. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 184 Journal of the European Economic Association 4.5. Empirical Strategy Given random assignment of schools to treatment cells shown in Figure 2, comparisons of outcome variable means across treatment groups provide unbiased estimates of the effect of each experimental treatment. However, to increase power (and to account for our stratiﬁed randomization procedure), we condition our estimates on a set of covariates used in power calculations. With few exceptions, all of the analyses presented (including outcome variables, regression speciﬁcations, and hypotheses tested) were prespeciﬁed in a preanalysis plan written and ﬁled before endline data were available for analysis. In reporting results in what follows, we explicitly note analyses that deviate from the preanalysis plan. As speciﬁed in advance, we use ordinary least-squares (OLS) regression to estimate the effect of cell assignment on child-level outcomes with the following speciﬁcation: Y D ˛ C ˇ SI C ˇ LI C ˇ LG C ˇ .S I / .LG / i;j 1 j 2 j 3 j 4 j j C ˇ .LI / .LG / C X C " ; (19) 5 j j i;j i;j where Y is the outcome for child i in school j; SI is a dummy that equals 1 if the i, j j administrator in school j was assigned to receive a small incentive contract and 0 otherwise; LI is equal to 1 if the administrator in school j was assigned to receive a large anemia reduction incentive contract; LG is equal to 1 if the school received a large block grant; X is a vector of child controls (age, class-year, and gender, and i, j baseline value of the outcome variable), school controls (number of students, student- teacher ratio, whether the school has a kitchen, proportion of boarding students, and distance to the farthest village in the school’s catchment area); and dummy variables for counties and randomization strata. We adjusted our standard errors for clustering at the school level using Liang–Zeger clustered standard errors. In addition to estimating effects on our two primary outcomes (hemoglobin concentration and a dichotomous indicator for anemia status), we use the same speciﬁcation to estimate effects on secondary outcomes to examine the behavioral mechanisms underlying changes in primary outcomes. For these secondary outcomes, we focus our analysis on summary indices constructed using groups of closely-related outcome variables (as we speciﬁed in advance). To construct these indices, we used the GLS weighting procedure described by Anderson (2008). For each individual, we constructed a variable s N as the weighted average of k normalized outcome variables ij in group (y ). The weight placed on each outcome variable is the sum of its row ij k entries in the inverted covariance matrix for group j such that 1 1 X X d d 0 0 s N D 1 1 1 y ; ij ij j j 31. This analysis plan was ﬁled with the Abdul Latif Jameel Poverty Action Lab at http://www. povertyactionlab.org/Hypothesis-Registry. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 185 where 1 is a column vector of 1 s, is the inverted covariance matrix, and y is j ij a column vector of all outcomes for individual i in group j. In addition to reducing the number of tests required, this weighting procedure can improve efﬁciency by placing less weight on outcomes that are highly correlated and more weight on those less correlated. The summary index variable can also be created for individuals with a subset of missing outcomes (these outcomes simply receive less weight in the construction of the index). Although we emphasize these indices in our discussion, we also report estimates for each individual index component in Online Appendix Tables A.5–A.8. A note on correcting for multiple comparisons is also warranted. For our primary estimates, we test eight null hypotheses: ﬁve for treatment main effects and their interactions (shown in equation (19)) and three additional ones—that the small and large incentives have the same average effect (ˇ D ˇ ), that the large incentive and the 1 2 large block grant have the same average effect (ˇ D ˇ ), and that the average effect 2 3 of the large incentive in presence of a large grant is zero (ˇ C ˇ D 0). We therefore 2 5 adjust our p-values to control the family wise error rate (FWER), or the probability of at least one Type I error. Speciﬁcally, we use the free step-down resampling method of Westfall and Young (1993). This procedure accounts for the dependency of the data, and is therefore more powerful than procedures that do not (e.g. a Bonferroni correction ). For secondary outcomes, we adjust our p-values according to the total number of tests within a family of outcomes (the number of outcomes in the family times ﬁve—the number of treatment coefﬁcients in each regression). 5. Results: Childhood Anemia and Underlying Behavioral Responses In this section, we ﬁrst present results obtained by estimating equation (19) for anemia status and hemoglobin concentration, and in Section 5.2, we then investigate the underlying behavioral responses that may have produced them. Following our preanalysis plan, we emphasize estimates from our sub-sample of children who were anemic at baseline. In the Online Appendix Tables we report results for the full sample of children receiving hemoglobin tests (Online Appendix Tables A.3, A.4, A.6, and A.8). 5.1. Childhood Anemia The ﬁrst ﬁve rows of Table 3 report estimates for each treatment and their interactions (and the seventh row reports comparison group means for the no incentive, small grant group at endline). For each estimate, we report the regression coefﬁcient, the standard 32. We did not prespecify the last of these (whether or not the joint effect of the large grant and large incentive is negative), but we did prespecify whether or not incentives and large grants are complements or substitutes (ˇ D 0, ˇ D 0). 4 5 Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 186 Journal of the European Economic Association TABLE 3. Impacts of school administrator anemia reduction incentives and block grant size on student hemoglobin concentration and anemia prevalence. Anemic at endline Hemoglobin (Hb < 120 g/L) concentration (g/L) Dependent variable (1) (2) Panel A: Impacts relative to comparison (no incentive, small grant) group (1) ˇ : small incentive 0.012 0.387 (0.040) (1.101) [0.771] [0.726] f0.972gf0.792g (2) ˇ : large incentive 0.138 2.567 (0.039) (1.044) [0.001] [0.015] f0.064gf0.285g (3) ˇ : large grant 0.145 4.205 (0.038) (1.123) [<0.001] [<0.001] f0.047gf0.045g (4) ˇ : (small incentive) (large grant) 0.042 1.445 (0.056) (1.541) [0.453] [0.350] f0.888gf0.664g (5) ˇ : (large incentive) (large grant) 0.196 4.580 (0.058) (1.586) [<0.001] [0.004] f0.072gf0.173g (6) Observations 1923 1923 (7) Mean in no incentive, small grant group 0.364 129.901 Panel B: p-values of Additional Comparisons (8) ˇ –ˇ : effect of large incentive versus effect of [0.002] [0.014] 1 2 small incentive given small grant f0.089gf0.285g (9) ˇ –ˇ : effect of large incentive given small [0.854] [0.169] 2 3 f0.972gf0.597g grant versus effect of increasing grant amount (10) ˇ C ˇ : effect of large incentive given large [0.141] [0.080] 2 5 grant f0.650gf0.511g Notes: Table uses sample of children testing anemic at baseline. Children are considered anemic if they have an altitude-adjusted hemoglobin concentration below 120 g/L (per WHO guidelines). Rows (1)–(5) in panel A show estimated coefﬁcients for treatment group indicators and interactions obtained by estimating equation (19) (controlling for baseline hemoglobin concentration, student age, student grade, student sex, number of students in the school, whether the school has a canteen, student teacher ratio, distance to the furthest village served, percent of boarding students, whether the school has implemented the “Free Lunch” policy, county dummy variables, and dummy variables for randomization strata). Standard errors are shown in parentheses, unadjusted p-values are shown in square brackets and p-values adjusted for multiple inference are shown in curly brackets. Adjusted p-values were constructed using the free step-down resampling method of Westfall and Young (1993) with 10,000 iterations. Panel B shows unadjusted and adjusted p values from tests of linear combinations of coefﬁcients in panel A. Signiﬁcant at 10%; signiﬁcant at 5%; signiﬁcant at 1% based on adjusted p values. error and corresponding p-value, and the p-value adjusted for multiple hypotheses testing. RESULT 1. (Large Incentives). First, we ﬁnd that the large incentive signiﬁcantly reduced the probability of anemia at endline in schools receiving a small grant. Speciﬁcally, the large incentive was associated with a 14 percentage point reduction 33. Table 3 reports results for students found to be anemic at baseline as pre-speciﬁed. Appendix Table 3 shows main results for the full sample. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 187 in anemia (Table 3, row 2, column (1); unadjusted p-value D 0.001, adjusted p-value D 0.064), implying a 37.9% reduction relative to the comparison group (small grant, no incentive schools) at endline. The corresponding increase in hemoglobin was about 2.6 g/L (Table 3, row 2, column (2); unadjusted p-value D 0.015, adjusted p-value D 0.285). These empirical ﬁndings agree with our model’s prediction derived in equations (11) and (12). Because our incentives rewarded anemia reduction (and not hemoglobin levels per se) and anemia status reﬂects shifts in the distribution of altitude adjusted hemoglobin concentrations across the 120 g/L threshold, Figure 5a plots the distribution of endline hemoglobin concentrations (adjusted for covariates included in equation (19)) by study arm among children who were anemic at baseline. The distribution for the large incentive group is shifted to the right of the control group distribution (Kolmogorov– Smirov test p-value D 0.02). This relative shift in mass is greater in the left tail of the distribution, implying that the large incentive reduced the share of children falling below the anemia threshold. RESULT 2. (Small Incentives). Second, in contrast, the small incentive had no detectable effect on the probability of anemia at endline (Table 3, row 1, column (1)). Comparing the estimates for small and large incentives (ˇ D ˇ in equation (19)), 1 2 we also reject the null hypothesis that the two estimates are equal (Table 3,row 8, column (1); adjusted p-value D 0.089). Taken together, the estimates for the small and large incentives suggest that the price effect of incentives is meaningful independent of information conveyed by the presence of an incentive contract (Gneezy and Rustichini 2000). Figure 5a shows that the shift in the hemoglobin distribution for the small incentive arm relative to the control group arm is smaller—particularly in the left tail of the distribution. An important question in the literature on ﬁnancial incentives is whether or not they crowd-out intrinsic or prosocial motivation (Deci and Ryan 1985; Gneezy and Rustichini 2000; Fehr and Falk 2002; Francois and Vlassopoulos 2008; Gneezy, Meier, and Rey-Biel 2011; Kamenica 2012). We ﬁnd that the effects of the small incentive on anemia was signiﬁcantly more positive amongst school administrators who score higher at baseline on a prosociality scale (adapted from Grant 2008) (Online Appendix Table A.10, row 1, columns (1)–(3); adjusted p-value D 0.038). We also ﬁnd a similar effect for intrinsic motivation (also adapted from Grant 2008), but the difference in effects is not statistically signiﬁcant (Online Appendix Table A.10, row 4, columns (1)–(3); adjusted p-value D 0.570). However, the effect of the large incentive is not heterogeneous by prosocial or intrinsic motivation (the coefﬁcients are close to zero and not statistically signiﬁcant), implying that if monetary incentives are large, crowding- out of prosocial motivation may be overcome by extrinsic motivation provided by incentives. RESULT 3. (Large Block Grants). Third, in the absence of any explicit incentive, the large block grant alone reduced the probability of student anemia at endline (an unambiguous prediction of our model, as equations (13), (14), and (16) show). Speciﬁcally, Table 3 (column (1), row 3) shows that the large block grant was associated Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 188 Journal of the European Economic Association FIGURE 5. Distributions of hemoglobin concentration. (a) and (b) plot the distributions of student level hemoglobin concentrations (in g/L) at endline across incentive treatment groups separately by small and large block grant groups. Endline Hb concentrations are adjusted for prespeciﬁed baseline control variables. Kolmogrov–Smirnov p values for small anemia incentive versus no incentive are in 0.93 panel (a) and 0.12 in panel (b). For large anemia versus no incentive these are in 0.02 panel (a) and 0.24 in panel (b). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 189 with a 14.5 percentage point reduction in anemia (adjusted p-value D 0.047), implying a 39.8% reduction relative to the comparison group at endline. This reduction is very similar to the effect of the large incentive (0.145 vs. 0.138), but the average increase in hemoglobin concentration is larger (4.205 vs. 2.567), although not statistically so (Table 3, row 9, column (2); adjusted p-value D 0.597). RESULT 4. (Interactions between Incentives and Grants). Whether or not incentives and unrestricted grants are complements or substitutes is an empirical issue. The model in Section 2 makes clear that both complements or substitutes are possible depending on cross partial derivatives of the hemoglobin production function as well as the curvature of the marginal cost of effort and the marginal utility that the school administrator obtains from non-nutritional activities. We do not ﬁnd evidence of complementarity— and notably, incentives and block grants can be strong substitutes if the incentives are sufﬁciently large. Table 3 shows that the interaction between the large incentive and the large block grant (ˇ in equation (19); Table 3, column (1), row 5) is positive and statistically signiﬁcant (adjusted p-value D 0.072). Moreover, the magnitude of substitution implies that the large incentive and the large block grant fully crowd each other out: the marginal effect of the large incentive given the large block grant in column (1) (ˇ C ˇ D 0.058) is not statistically different from zero (adjusted p-value D 0.65) for the probability of anemia. Although this point estimate is positive, we are not able to rule out a negative effect of the large incentive given a large block grant on anemia as predicted by equation (15) of the model in Section 2. Adding coefﬁcients, the estimated total effect of the large incentive and large grant on anemia is 0.087 (adjusted p-value: 0.177). Given decreasing marginal returns to inputs in the reduction of anemia, a natural question arising from these results is if substitution between incentives and resources is due to (i) the biological relationship between inputs and anemia (i.e., although more inputs are used, there is no effect on anemia because of biological constraints) or (ii) conscious decisions by administrators. Our results for input use in Section 5.2 are consistent with the latter interpretation (we ﬁnd direct evidence of substitution in input use). (We also note that efﬁcacy trials of iron supplementation suggest that much larger reductions in anemia are biologically possible (Gera et al. 2007).) Given that we ﬁnd similar results for input use in the full sample (Online Appendix Table A.4), differences in the effects of incentives and resources on anemia rates between the sample of children anemic at baseline (Table 3) and the full sample (Online Appendix Table A.3) are likely explained by decreasing marginal returns to inputs in the reduction of anemia rather than diminishing marginal returns to effort on the part of administrators. 34. Likewise, ˇ C ˇ , the marginal effect of increasing the grant amount given large incentives is 3 5 insigniﬁcant (ˇ C ˇ D 0.051, adjusted p-value 0.742). 3 5 Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 190 Journal of the European Economic Association 5.2. Behavioral Responses Underlying Changes in Anemia We next examine the underlying behavioral responses to our interventions that may have produced the changes in anemia described in Section 5.1. To do so, we focus on actions taken by administrators and subsequent responses among students and their parents—speciﬁcally, student consumption of iron-rich foods, direct iron supplementation, communication between parents and schools about anemia and its nutritional basis. For each family of outcome variables, we examine indices as described in Section 4.5. Behavioral Responses Underlying Result 1: Large Incentives. We ﬁrst consider the behavioral responses underlying Result 1—that in the presence of the small block grant, the large incentive signiﬁcantly reduced the probability of student anemia. The results in Table 4 suggest that the large incentive led administrators to increase vitamin supplementation and the provision of iron-rich foods (column (1), row 2; adjusted p-value 0.105). This increase in iron-rich foods seems driven largely by home consumption (row 2, column (5), adjusted p-value 0.090). An interesting issue is if the increase is vitamin supplementation and provision of iron-rich foods occurred because school administrators with large incentives spent the block grant differently—or instead because they exerted more effort. As Figure 4 shows, reported use of block grants for different types of nutrition interventions (vitamins, food, fortiﬁcation), and other uses is similar for incentive and nonincentives schools receiving a small grant, suggesting that greater anemia reduction due to incentives is driven by effort rather than differential allocation of the block grant. In exploring how administrators were able to increase child consumption of iron rich foods at home, we examine contact with parents. Row 2, column (8) of Table 4 reports a positive (but insigniﬁcant) increase in contact. However, Online Appendix Table A.7 shows that estimates for several components of this index appear meaningful and important, albeit insigniﬁcant at conventional levels using adjusted p-values (largely because of the large number of hypotheses being tested (11 5 D 55). These results are suggestive that the large incentive led administrators to engage more regularly with households—speciﬁcally about nutrition and anemia—which in turn appears to have improved children’s diets at home. 35. Subindices for supplements and food (including separate indices for food at home and school) were not explicitly speciﬁed in the preanalysis plan. Online Appendix Table A.9 reproduces Table 4, including additional tests of linear combinations of coefﬁcients estimated using equation (19). These additional tests were not prespeciﬁed. 36. Speciﬁcally, the number of individual meetings between administrators and households over the past semester increased by 0.52 (column (2), row 2)—an increase of 59%; whether or not schools contacted parents about nutrition in the past semester rose by 12 percentage points (column (3), row 2)—an increase of 29%; and whether or not schools contacted parents about feeding children iron-rich foods rich in the past semester rose by 10 percentage points (column (4), row 2)—an increase of 47%. Note that the number of school-wide parent meetings and number of individual meetings with parents were not prespeciﬁed to be part of this index. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 191 TABLE 4. Child and household reported receipt of supplements and iron-rich food. Index: supplements Subindex: Subindex: food Sub-index: food Index: Subindex: information Subindex: information Dependent variable and food supplements Subindex: food at school at home information to students to households (1) (2) (3) (4) (5) (6) (7) (8) (1) ˇ : small incentive 0.059 0.138 0.033 0.08 0.072 0.027 0.062 0.045 (0.047) (0.084) (0.044) (0.055) (0.061) (0.075) (0.126) (0.084) [0.21] [0.104] [0.452] [0.151] [0.243] [0.724] [0.623] [0.594] f0.331gf0.234gf0.56gf0.555gf0.403gf0.935gf0.911gf0.690g (2) ˇ : large incentive 0.114 0.158 0.073 0.039 0.187 0.070 0.111 0.130 (0.045) (0.080) (0.038) (0.048) (0.064) (0.072) (0.101) (0.084) [0.011] [0.052] [0.057] [0.427] [0.004] [0.332] [0.272] [0.124] f0.105gf0.234gf0.339gf0.601gf0.090gf0.800gf0.796gf0.430g (3) ˇ : large grant 0.190 0.241 0.138 0.133 0.189 0.162 0.136 0.233 (0.041) (0.072) (0.047) (0.06) (0.075) (0.076) (0.107) (0.113) [<0.001] [0.001] [0.004] [0.029] [0.013] [0.034] [0.207] [0.041] f0.004gf0.051gf0.092gf0.27gf0.126gf0.326gf0.768gf0.352g (4) ˇ : (small incentive) 0.200 0.269 0.114 0.105 0.150 0.037 0.190 0.314 (0.068) (0.116) (0.072) (0.09) (0.105) (0.123) (0.178) (0.148) (large grant) [0.004] [0.021] [0.116] [0.243] [0.157] [0.766] [0.288] [0.036] f0.071gf0.186gf0.36gf0.601gf0.403gf0.935gf0.796gf0.352g (5) ˇ : (large incentive) 0.248 0.289 0.212 0.209 0.292 0.117 0.039 0.356 (0.064) (0.106) (0.067) (0.079) (0.110) (0.108) (0.151) (0.146) (large grant) [<0.001] [0.007] [0.002] [0.009] [0.009] [0.282] [0.797] [0.016] f0.016gf0.124gf0.074gf0.16gf0.122gf0.800gf0.911gf0.271g (6) Observations 1932 1932 1928 1920 1927 1932 1928 1548 (7) Mean in no incentive, 0.031 0.055 0.039 0.033 0.053 0.040 0.017 0.082 small grant group Notes: Table uses sample of children testing anemic at baseline. Children are considered anemic if they have an altitude-adjusted hemoglobin concentration below 120 g/L (per WHO guidelines). Rows (1)–(5) show estimated coefﬁcients for treatment group indicators and interactions obtained by estimating equation (12) (controlling for the baseline value of the dependent variable, student age, student grade, student sex, number of students in the school, whether the school has a canteen, student teacher ratio, distance to the furthest village served, percent of boarding students, whether the school has implemented the “Free Lunch” policy, county dummy variables, and dummy variables for randomization strata). The dependent variable in each regression is a summary index constructed using the GLS weighting procedure in Anderson (2008). Estimates for the individual components of each index are shown in Online Appendix Tables A.5 and A.6. Standard errors are shown in parentheses, unadjusted p values are shown in square brackets and p values adjusted for multiple inference are shown in curly brackets. Adjusted p values were constructed using the free step-down resampling method of Westfall and Young (1993) with 10,000 iterations. Signiﬁcant at 10%; signiﬁcantat5%; signiﬁcant at 1% based on adjusted p-values. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 192 Journal of the European Economic Association The ﬁnding that administrators responded to large incentives by engaging with households is important for at least two related reasons. First, it demonstrates innovation and the use of local knowledge in response to performance incentives that reward outputs (health outcomes) as opposed to those that rigidly reward the use of prespeciﬁed inputs (such as vitamin consumption at school), as most performance incentives in the health sector do (Miller and Singer Babiarz 2014). Second, for outcomes jointly produced with beneﬁciary households (like good child nutrition), it demonstrates the potential of performance incentives that reward outputs to minimize offsetting compensatory behavior among beneﬁciaries (e.g. a common ﬁnding among studies of school lunch programs, ) (Jacoby 2002; Leonard 2003; Kazianga et al. 2009; Das et al. 2013). Behavioral Responses Underlying Result 2: Small Incentives. Second, we study the behavioral responses underlying Result 2—that the small incentive did not reduce anemia prevalence. Table 4 (column (1)) shows that administrators with small incentives did not signiﬁcantly increase the provision of supplements or food (row 1, columns (1)–(3)), nor did they increase their contact with households (column (8)) (Online Appendix Table A.7, row 1 also shows that none of the individual components of this index are statistically signiﬁcant (even using unadjusted p-values). Behavioral Responses Underlying Result 3: Large Block Grants. Third, we examine behavioral responses to large block grants, which reduced the prevalence of student anemia. The large block grant signiﬁcantly increased the provision of supplements and food (Table 4, row 3, column (1); adjusted p-value 0.004). This increase appears due to increases in both iron supplements (column (2), adjusted p-value 0.051) and iron-rich food (column (3), adjusted p-value 0.092). Interestingly, the large block grant may have also increased school contact with parents—suggesting that administrators worked through households to reduce anemia without any explicit incentives to do so. Although the estimate for the index in Table 4 is not statistically signiﬁcant (row 3, column (8)), some estimates for index components are larger than those for incentives. This may reﬂect intrinsic or prosocial motivation— or a sense of obligation or organizational mission (Ashraf, Bandiera, and Jack 2014). Furthermore, although the large block grant increased communication with households, the impact of block grants on food consumption at home is insigniﬁcant. We speculate that this could reﬂect less effort (relative to administrators with incentives) devoted to mitigating compensatory behavior by households in response to greater food provision at school (which seems to have increased, although not signiﬁcantly, with large grants). 37. We speculate that the bureaucratic environment is one reason that administrators chose to work through households. Administrators may have viewed this strategy as a way to reduce anemia (and increase rewards) while avoiding the risk of career harm due to possible adverse events. This career harm may also be more severe under incentives if incentives altered perceptions of administrators’ motivation for reducing anemia (analogous to how incentives may crowd-out effort if they alter the motives for prosocial tasks perceived by others—Benabou ´ and Tirole (2006)). Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 193 Behavioral Responses Underlying Result 4: Substitution between Large Incentives and Large Block Grants. Finally, with the combination of large incentives and large block grants, we ﬁnd direct evidence of crowding-out of inputs consistent with our anemia estimates in Table 3. Speciﬁcally, Table 4 shows that for vitamin supplementation and consumption of iron-rich foods (both at school and at home), estimates for the interaction between the large incentive and large block grant are negative, implying substitution (row 5). The interaction between the small incentive and large grant is also negative, but smaller in magnitude and only marginally signiﬁcant. Overall, there is no evidence that resources and incentives are complements—and that at sufﬁciently high levels, they are substitutes. 5.3. Comparative Cost-Effectiveness Finally, we examine the comparative cost-effectiveness of each of our intervention combinations. In doing so, we consider both the subsample of children anemic at baseline and our full sample of children, and we present both “programmatic” cost-effectiveness (direct monetary program costs to the implementing organization) and social cost-effectiveness calculations. We calculate total social costs as the sum of: (a) programmatic costs; (b) the cost of public funds; and (c) costs incurred by households in responding to the interventions. From social costs we exclude incentive payments (apart from their contribution the cost of public funds), considering these payments to be transfers (Kremer, Miguel, and Thornton 2009). Incentive payments may also not be considered a cost, but rather simply another way of allocating salary expenditures (Muralidharan and Sundararaman 2011). Note that although we only consider comparative cost-effectiveness in reducing anemia prevalence (the primary outcome of the study), it is possible that the treatments, particularly the block grant, do produce other beneﬁts not considered here. Moreover, if the sole purpose of transfers to schools is to reduce anemia, there may be more cost-effective options than unrestricted block grants. Our goal is not to conduct a full cost-beneﬁt analysis, but rather to compare strategies for reducing anemia. Although we ﬁnd no intervention effects on standardized exam scores, even these (together with anemia measures) may fail to fully capture intervention beneﬁts. Table 5 presents these results. The key ﬁnding that we highlight is that although large block grants were as effective in reducing student anemia as large incentives, they were more expensive. First, considering full social costs and using the full sample, the relative cost per case of anemia averted was 1,453 yuan (about $227) in the large incentive/small block grant group—but 44% larger in the large block grant group 38. Given our experimental design, we are unable to rule out the possibility of complementarity at lower levels of resources. 39. See table notes for further details about these calculations. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 194 Journal of the European Economic Association TABLE 5. Comparative cost effectiveness calculations. Incremental amount relative to comparison (small block grant, no incentives) group Small block Small block Large block Large block Large block grant, small grant, large grant, no grant, small grant, large incentives incentives incentives incentives incentives Panel A: Costs Programmatic costs (1) Block grant 0.0 0.0 48.0 48.0 48.0 (2) Incentive payments 1.1 15.7 0.0 1.4 17.5 Cost of public funds (3) Cost of public funds 0.3 4.7 14.4 14.8 19.7 Costs to households (4) Full sample 45.5 60.7 90.8 38.3 62.7 (5) Anemic sample 34.6 95.0 147.5 26.6 49.4 Total costs (6) Programmatic 1.1 15.7 48.0 49.4 65.5 (7) Social—full sample 45.8 65.4 153.2 101.1 130.3 (8) Social—anemic 34.9 99.7 209.9 89.5 117.0 sample Panel B: Anemia reduction (percentage point reduction) (9) Full sample 0.028 0.045 0.073 0.074 0.032 (10) Anemic sample 0.012 0.138 0.145 0.199 0.087 Panel C: Cost effectiveness (cost of averting one anemia case) Full sample (11) Programmatic N.S. 349.6 657.5 668.1 2047.4 (12) Social N.S. 1452.7 2098.6 1366.1 4072.4 Anemic sample (13) Programmatic N.S. 114.0 331.0 248.4 753.1 (14) Social N.S. 722.5 1447.3 449.6 1345.1 Notes: All costs in renminbi per child (exchange rate as of September 2012 was 6.3 USD/RMB). Costs of the information intervention and anemia testing are excluded as these are constant across treatments. The cost of the information intervention was 1,020 yuan per school and the cost of anemia testing was 6.7 yuan per child. Additional administrative costs are assumed to be negligible as administration of block grants could be built into the administration of other school ﬁnances, administrative costs of rewards into administration of existing school administrator evaluation policies and policies, and monitoring of anemia into existing policies stipulating annual checkups for school children. In the absence of good estimates for China (and other developing countries), the cost of public funds is assumed to be 0.3 based on estimates for the United States (Ballard, Shoven, and Whalley, 1985). Social costs include costs incurred by households and exclude incentive payments (except the deadweight loss to taxation) considering them a transfer. Costs to households include costs of purchasing additional food and additional time spent attending parent meetings. Estimates for additional food costs are based on estimates for impact on meat, vegetable, and fruit consumption at home reported in Online Appendix Tables A.5 and A.6. Reported increases in times foods were consumed in the past week are assumed to be constant across all 24 weeks of the program. Serving sizes are assumed to be half of the recommended daily consumption (25 g of meat, 150 g of vegetables, and 100 g of fruit). Food prices are based on prices in local markets as reported by the school accountant at baseline. Time spent in parent meetings is based on estimates in Online Appendix Tables A.7 and A.8. One meeting is assumed to have an opportunity cost of 60 yuan (approximately half of local daily wages). Anemia reduction estimates in panel B are calculated from estimates in Table 2 and Online Appendix Table A.3. Effects not signiﬁcant (N.S.) for the small block grant, no incentives intervention. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 Luo et al. Can Bureaucrats Really be Paid Like CEOs? 195 (2,099 yuan, or about $328). Second, the cost-effectiveness of these two interventions relative to each other is similar when we restrict our calculations to children anemic at baseline (as we do in Sections 4 and 5, following our preanalysis plan). Speciﬁcally, the large incentive/small block grant intervention is approximately 50% more cost effective than large block grant intervention without incentives (723 yuan, or $113, per case of anemia averted vs. 1,447 yuan, or $226). Finally, considering calculating only programmatic costs and using children anemic at baseline, the cost-effectiveness of the large incentive/small block grant intervention is roughly one third of that of the large block grant (114 yuan, or about $18 vs. 331 yuan, or about $52). 6. Conclusion This paper provides new evidence on how public sector managers respond to the provision of performance incentives. To the best of our knowledge, it is the ﬁrst study to analyze how behavioral responses to performance pay interact with exogenously assigned levels of resources—a critical issue in the design of incentive systems under stringent resource constraints (as is common in many developing countries). We report four key ﬁndings. First, when school administrators have fewer budgetary resources available to them, large performance incentives (with realized payments equivalent to a couple of months of annual salary) lead to substantial improvement in service delivery. This seems driven by greater effort rather than changes in budgetary resource allocation. In particular, we ﬁnd evidence that school administrators were able to innovate, working through their students’ parents to alter nutritional practices at home. Second, smaller incentives (one tenth the size of the larger ones) were ineffective on average and had negative effects on prosocially motivated administrators. Third, even absent explicit performance incentives, increasing school administrators’ budgets led to important improvements in performance (but was considerably less cost-effective than using performance incentives), implying the presence of other motives—potentially including intrinsic ones—in our context. Fourth, we ﬁnd that performance incentives and unrestricted grants are substitutes in the production of health when incentives are large. The degree of substitution is substantial: at the policy-relevant levels that we study, increasing the size of unrestricted block grants completely crowds out the effect of incentives (and vice versa). This is an important result for resource-poor environments in which both budgetary resources and performance incentives are used simultaneously as policy levers for improving the quality of public service delivery. There are of course limitations to this study. One is that, as with all empirical studies, our results are not generalizable to settings beyond our study context. However, 40. These estimates exclude administrative costs of the incentive scheme (assuming these would be rolled into existing policies as noted in the notes to Table 5). When the costs incurred for anemia testing (6.7 RMB per child in a sample of 50 children per school annually) are included in costs of the incentive scheme, the large incentive/small block grant remains more socially cost-effective than the large block grant at 1,848 yuan per case averted. Downloaded from https://academic.oup.com/jeea/article/18/1/165/5290364 by DeepDyve user on 18 July 2022 196 Journal of the European Economic Association school-based nutrition programs like the one we study are nearly ubiquitous in low- and middle-income countries (Del Rosso and Marek 1996;Muk ˜ oma and Flisher 2004; Bundy et al. 2006; Orazem et al. 2008). Because a large share of children attend school in most countries, school-based programs are widely considered to be among the most cost-effective means of delivering child health interventions (Orazem et al. 2008). We believe that our study provides behavioral insights relevant in a variety of settings in which managers have budgetary discretion—and increasingly also face high powered incentives. Another is that our study estimates short-run intervention effects. Longer- run effects may differ, particularly as administrators learn more about the relationships among their effort, various inputs, and anemia reduction. Finally, although we ﬁnd that incentives for school administrators to reduce student anemia were effective, we also note features that may make our setting conducive to the use of performance incentives. One is that the rewarded outcome (anemia reduction) can be measured objectively and reliably. Relative to other settings, frontline workers (teachers in our setting) in China may also be relatively responsive to instruction from administrators, which might alleviate problems of moral hazard in teams that could be more prevalent elsewhere. 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Can Bureaucrats Really Be Paid Like Ceos? Substitution Between Incentives and Resources Among School Administrators in China

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Can Bureaucrats Really Be Paid Like Ceos? Substitution Between Incentives and Resources Among School Administrators in China

Can Bureaucrats Really Be Paid Like Ceos? Substitution Between Incentives and Resources Among School Administrators in China

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