Is Digital Credit Filling a Hole or Digging a Hole? Evidence from MalawiBrailovskaya, Valentina; Dupas, Pascaline; Robinson, Jonathan
doi: 10.1093/ej/uead083pmid: N/A
Digital credit has expanded rapidly in Africa, with opaque loan terms amidst low consumer financial literacy. Rich data from Malawi shows substantial demand for a digital loan with a base interest rate of 10% over 15 days, yet most borrowers are not aware of loan terms, repay late and incur substantial late fees. Regression discontinuity analyses show no evidence that access to small digital loans harms consumers’ perceived well-being. A short, randomised, phone-based financial literacy intervention improved knowledge, but did not increase timely loan repayment and modestly increased loan demand, ultimately increasing the likelihood of ever defaulting.
The Boss is Watching: How Monitoring Decisions Hurt Black WorkersCavounidis, Costas; Lang, Kevin; Weinstein, Russell
doi: 10.1093/ej/uead079pmid: N/A
African Americans face shorter employment durations than similar Whites. We hypothesise that employers discriminate in acquiring or acting on ability-relevant information. In our model, monitoring Black, but not White, workers is self-sustaining. New Black hires were more likely fired by previous employers after monitoring. This reduces firms’ beliefs about ability, incentivising discriminatory monitoring. We confirm our predictions that layoffs are initially higher for Black than non-Black workers, but that they converge with seniority and decline more with the Armed Forces Qualification Test for Black workers. Two additional predictions, lower lifetime incomes and longer unemployment durations for Black workers, have known empirical support.
Data-Driven Envelopment with Privacy-Policy TyingCondorelli, Daniele; Padilla, Jorge
doi: 10.1093/ej/uead090pmid: N/A
We present a theory of monopoly protection by means of entry in adjacent markets that have a common customer base (i.e., envelopment). A firm dominant in its market enters a data-rich secondary market and engages in predatory pricing and privacy-policy tying. We define the latter as conditioning service provision to the subscription of a privacy policy that allows bundling of user data across all sources. Acquiring data from the secondary market confers an advantage in the data-intensive primary market that shields the dominant firm from entry, thus harming consumers. We discuss potential remedies, including data unbundling and portability.
Negative Tail Events, Emotions and Risk TakingCorgnet, Brice; Cornand, Camille; Hanaki, Nobuyuki
doi: 10.1093/ej/uead080pmid: N/A
We design a novel experiment to assess investors’ behavioural and physiological reactions to negative tail events. Investors who observed, without suffering from, tail events decreased their bids, whereas investors suffering tail losses increased them. However, the increase in bids after tail losses was not observed for those who exhibited no emotional arousal. This suggests that emotions are key in explaining prospect theory prediction of risk seeking in the loss domain.
Unexpected Supply Effects of Quantitative Easing and TighteningD’Amico, Stefania; Seida, Tim
doi: 10.1093/ej/uead071pmid: N/A
To analyse the evolution of the effects of quantitative easing and tightening across consecutive announcements, we focus on their unexpected component. Treasury yield sensitivities to quantitative tightening supply surprises are on average larger than sensitivities to quantitative easing surprises, implying that supply effects did not diminish during periods of market calm amid economic expansion. Yield sensitivities to later quantitative easing and tightening surprises do not fall monotonically, and thus supply shocks seemed to remain powerful. Finally, yield sensitivities are amplified by the amount of interest rate uncertainty prevailing before announcements, implying that turning points in the balance sheet policy tended to elicit larger reactions.
Unemployment and DevelopmentFeng, Ying; Lagakos, David; Rauch, James E
doi: 10.1093/ej/uead076pmid: N/A
We draw on household survey data from countries of all income levels and document that average unemployment rates increase with gross domestic product per capita. This is accounted for almost entirely by low—rather than high—educated workers. We interpret these facts in a model with frictional labour markets, a traditional self-employment sector, skill-biased productivity differences across countries, and unemployment benefits that become more generous with development. A calibrated version of the model does well in explaining the cross-country patterns that we document. Counterfactual exercises point to skill-biased productivity differences as the most important factor in explaining the cross-country unemployment patterns.
Child Penalties in PoliticsFiva, Jon H; King, Max-Emil M
doi: 10.1093/ej/uead084pmid: N/A
Women tend to experience a substantial decline in their labour income after their first child is born, while men do not. Do such ‘child penalties’ also exist in the political arena? Using comprehensive administrative data from Norway, we find that women are less likely than men to secure elected office after their first child is born. The effects already manifest from the nomination stage, where mothers receive less favourable rankings on party lists relative to comparable fathers. This paper broadens our understanding of a fundamental social issue in political representation and demonstrates how motherhood even affects positively selected women.
Parental Investments and Intra-household Inequality in Child Human Capital: Evidence from a Survey ExperimentGiannola, Michele
doi: 10.1093/ej/uead086pmid: N/A
Intra-household inequality explains 40% of child human capital variation in the developing world. I study how parents’ investment contributes to this inequality. To mitigate the identification problem posed by observational data, I design a survey experiment with parents in India that allows me to identify beliefs about the human capital production function, preferences for inequality in outcomes and the role of resources. I find that investments are driven by efficiency considerations: as parents perceive investment and ability as complements, they invest more in higher-achieving children and more so when constrained. Simulations indicate that interventions have intra-household distributional impacts through parental responses.
Unintended Consequences of Central Bank Lending in Financial Crisesvan der Kwaak, Christiaan
doi: 10.1093/ej/uead078pmid: N/A
I investigate the macroeconomic impact of central bank funding becoming a more attractive funding source to financial intermediaries in times of crisis. I show that the requirement to pledge collateral has a contractionary effect on private credit, everything else equal, and thereby reduces the expansionary effect that such lending otherwise has. I use an estimated New Keynesian model with financial frictions to show that the collateral effect explains the limited growth of Italian banks’ private credit in response to the European Central Bank’s three-year longer-term refinancing operations. Finally, I explore whether changes in lending policy can offset the cumulative negative effects from the collateral effect.
Corrupted by Algorithms? How AI-generated and Human-written Advice Shape (Dis)honestyLeib, Margarita; Köbis, Nils; Rilke, Rainer Michael; Hagens, Marloes; Irlenbusch, Bernd
doi: 10.1093/ej/uead056pmid: N/A
Artificial intelligence increasingly becomes an indispensable advisor. New ethical concerns arise if artificial intelligence persuades people to behave dishonestly. In an experiment, we study how artificial intelligence advice (generated by a natural language processing algorithm) affects (dis)honesty, compare it to equivalent human advice and test whether transparency about the advice source matters. We find that dishonesty-promoting advice increases dishonesty, whereas honesty-promoting advice does not increase honesty. This is the case for both artificial intelligence and human advice. Algorithmic transparency, a commonly proposed policy to mitigate artificial intelligence risks, does not affect behaviour. The findings mark the first steps towards managing artificial intelligence advice responsibly.