We test the effectiveness of self-help peer groups as a commitment device for precautionary savings, through two randomized field experiments among 2,687 microentrepreneurs in Chile. The first experiment finds that self-help peer groups are a powerful tool to increase savings (the number of deposits grows 3.5-fold and the average savings balance almost doubles). Conversely, a substantially higher interest rate has no effect on most participants. A second experiment tests an alternative delivery mechanism and shows that effects of a similar size can be achieved by holding people accountable through feedback text messages, without any meetings or peer pressure.
Poverty is often characterized not only by low and unstable income, but also by heavy debt burdens. We find that reducing barriers to saving through access to free savings accounts decreases participants' short-term debt by about 20%. In addition, participants who experience an economic shock have less need to reduce consumption, and subjective well-being improves significantly. Precautionary savings and credit therefore act as substitutes in providing self-insurance, and participants prefer borrowing less when a free formal savings account is available. Take-up patterns suggest that requests by others for participants to share their resources may be a key obstacle to saving.
Reducing tax evasion is a key challenge for governments around the world, particularly in developing countries. This paper presents a methodology to generate information to optimize audit strategies. Randomly selected taxpayers receive a deterrence message. Comparing their subsequent tax payments to a control group allows estimating what types of taxpayers are more likely to respond to an increase in perceived audit probability. This information can be used to target audits toward taxpayers that respond particularly strongly, and to construct risk indicators to predict taxpayers’ responses. We show results from an application in Chile and describe lessons learned during the implementation.
Recent years have seen a large expansion in the use of rigorous impact evaluation techniques. Increasingly, public administrations are collaborating with academic economists and other quantitative social scientists to apply such rigorous methods to the study of public finance. These developments allow for more reliable measurements of the effects of different policy options on the behavioral responses of citizens, firm owners, or public officials. They can help decision makers in tax administrations, public procurement offices, and other public agencies design programs informed by well-founded evidence. This article provides an introductory overview of the most frequently used impact evaluation methods. It is aimed at facilitating communication and collaboration between practitioners and academics by introducing key vocabulary and concepts used in rigorous impact evaluation methods, starting with randomized controlled trials and comparing them with other methods ranging from simple pre–post analysis to difference-in-differences, matching estimations, and regression discontinuity designs.
We document that U.S. employment polarization in the 1980-2008 period is largely generated by women. Female employment shares increase both at the bottom and at the top of the skill distribution, generating the typical U-shape polarization graph, while male employment shares decrease in a more similar fashion along the whole skill distribution. We show that a canonical model of skill-biased technological change augmented with a gender dimension, an endogenous market/home labor choice and a multi-sector environment accounts well for gender and overall employment polarization. The model also accounts for the absence of employment polarization during the 1960- 1980 period and broadly reproduces the different evolution of employment shares across decades during the 1980-2008 period. The faster growth of skill-biased technological change since the 1980s accounts for most of the employment polarization generated by the model.
Ein internationales Forscherteam unter der Leitung von Stefano Battiston, Professor am Institut für Banking und Finance, hat einen neuartigen netzwerkbasierten «Klima-Stresstest» entwickelt, mit dem sich die Klimarisiken von Anlageportfolios in Abhängigkeit von politischen Szenarien beurteilen lassen.
We measure the "new" gains from trade reaped by Canada as a result of the Canada-US Free Trade Agreement (CUSFTA). We think of the "new" gains from trade of a country as all welfare effects pertaining to changes in the set of firms serving that country as emphasized in the so-called "new" trade literature. To this end, we first develop an exact decomposition of the gains from trade which separates "traditional" and "new" gains. We then apply this decomposition using Canadian and US micro data and and that the "new" welfare effects of CUSFTA on Canada were negative.
