We quantify the importance of endogenous peer effects in group lending programs by estimating a static game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich data set from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The benchmark model suggests that the probability of a member making a full repayment would be 11 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity.

Group lending has been widely adopted in the past thirty years by many microfinance institutions as a means to mitigate information asymmetries when delivering credit to the poor. This paper proposes an empirical method to address the potential omitted-variable problem resulting from unobserved group types when modeling the repayment behavior of group members. We estimate the model using a rich dataset from a group-lending program in India. The estimation results support our model specification and show the advantages of relying on a type-varying method when analyzing the probability of default of group members. In particular, our model helps to better understand the factors driving repayment behavior, which may differ across group types, and shows a higher predictive power than standard single-agent choice models.

The substantial differences in agricultural productivity between Asia and Africa can be largely explained by differences in use of modern inputs. The evidence suggests that better access to infrastructure (such as roads and irrigation) and agricultural services has given Asian farmers significantly better access to modern inputs, while Sub-Saharan African farmers without such an access are not able to fully exploit the benefits of modern agricultural inputs. This brief discusses the relationship between agricultural service provision and modern input use by farmers in Nigeria, with a focus on the differences among states and local government areas (LGA).

From 2006 to mid-2008 the international prices of agricultural commodities increased considerably, by a factor larger than two. This upward trend in agricultural prices captured the world's attention as a new food crisis was emerging. Several explanations for these movements in prices, ranging from demand-driven forces to supply shocks, have been provided by analysts, researchers, and development institutions. This paper is an attempt to empirically validate these explanations using time series econometrics and data at monthly frequency. We focus on the international price of corn, wheat, rice, and soybeans. First, we identify variables associated with the factors mentioned as causing the increase in these agricultural commodities prices. Second, we use time series analysis to try to quantitatively validate those explanations. The empirical work presented here includes first difference models and rolling Granger causality tests. Overall, our empirical analysis mainly provides evidence that financial activity in futures markets and proxies for speculation can help explain the observed change in food prices; any other explanation is not well supported by our time series analysis.

We provide a systematic analysis of the properties of individual returns to wealth using twelve years of population data from Norway’s administrative tax records. We document a number of novel results. First, during our sample period individuals earn markedly different average returns on their financial assets (a standard deviation of 14%) and on their net worth (a standard deviation of 8%). Second, heterogeneity in returns does not arise merely from differences in the allocation of wealth between safe and risky assets: returns are heterogeneous even within asset classes. Third, returns are positively correlated with wealth: moving from the 10th to the 90th percentile of the financial wealth distribution increases the return by 3 percentage points - and by 17 percentage points when the same exercise is performed for the return to net worth. Fourth, wealth returns exhibit substantial persistence over time. We argue that while this persistence partly reflects stable differences in risk exposure and assets scale, it also reflects persistent heterogeneity in sophistication and financial information, as well as entrepreneurial talent. Finally, wealth returns are (mildly) correlated across generations. We discuss the implications of these findings for several strands of the wealth inequality debate.

This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.