Knowledge that Transforms

In a natural experiment among former colonies between 1970 and 1999, weak institutions reflected in high settler mortality and French legal origin often increase the likelihood and intensity of local currency and real crises (i.e., those resulting in a drop in real output) amid six global crises. The effects of institutions on crises are often mediated through macroeconomic policies, but they are often not primary channels. Persistent institutions (i.e., those reflected in the legal origins and settler mortality) predict the occurrence and intensity of crises better than time-varying institutions do.

Recent evidence from Bound, Brown, and Mathiowetz (2001) and Black, Sanders, and Taylor (2003) suggests that reporting errors in survey data routinely violate all of the classical measurement error assumptions. The econometrics literature has not considered the consequences of fully arbitrary measurement error for identification of regression coefficients. This paper highlights the severity of the identification problem given the presence of even infrequent arbitrary errors in a binary regressor. In the empirical component, health insurance misclassification rates of less than 1.3% generate double-digit percentage point ranges of uncertainty about the variable's true marginal effect on the use of health services.

Why do people frequently cooperate in defiance of their immediate incentives? One explanation is that individuals are conditionally cooperative. As an explanation of behavior in one-shot settings, such preferences require individuals to be able to discern their opponents' preferences. Using data from a television game show, we provide evidence about how individuals implement conditionally cooperative preferences. We show that contestants forgo large sums of money to be cooperative; they cooperate at heightened levels when their opponents are predictably cooperative; and they fare worse when their observable characteristics predict less cooperation because opponents avoid cooperating with them.

Consumption commitments—goods like housing for which adjustment is costly—change the relationship between risk and consumption. Commitment provides a motive to reduce consumption when possible future losses are too small to warrant adjustment but not when losses are large enough that adjustment would be worthwhile. This implies conditions under which mean-preserving increases in risk can increase housing consumption. Our empirical evidence exploits the interaction of these conditions with a novel proxy for unemployment risk: couples sharing an occupation. Consistent with our model, same-occupation couples consume more housing only when adjustment costs are high and potential losses are sufficiently large.

We use data on vote outcomes from a universal voucher initiative to examine whether white households with children in public schools will use vouchers to leave predominantly nonwhite schools, thereby contributing to more racially and ethnically segregated schools. We find that white households are more likely to support vouchers when their children attend schools with larger concentrations of nonwhite schoolchildren, an effect that is absent for nonwhite households and households without children. This result may be driven less by race or ethnicity and more by other characteristics, such as student performance, that are correlated with race or ethnicity.

Marriage allows couples to diversify labor income risks and dynamically coordinate labor supply decisions in response to shocks. This paper argues that these risk-sharing benefits of marriage are countercyclical; husbands' and wives' income changes are more positively correlated when the economy is growing rapidly. As a result, while individuals face more idiosyncratic income risk in bad times than in good, households do not. I exploit variation in the cross-sectional covariance of husbands' and wives' incomes to infer the covariance of past income changes. Couples with marriages spanning periods of greater economic expansion have more positively correlated incomes in the cross-section.

If pricing is state dependent, firms are more likely to adjust whenever aggregate and idiosyncratic shocks reinforce each other and trigger desired price changes in the same direction. Using measures of technology shocks derived from production function estimates for four-digit U.S. manufacturing industries, I find that sectoral inflation rates are more sensitive to negative, as opposed to positive, technology disturbances in periods of higher economy-wide inflation, commodity price increases, and expansionary monetary policy shocks. I argue, using a state-dependent sticky price model that matches salient features of the U.S. microprice data, that these results suggest that pricing is state-dependent in U.S. manufacturing.

This paper develops a framework to study empirically the relationship between trade policy and individual income risk and to evaluate the associated welfare consequences. The analysis proceeds in three steps. First, longitudinal data on workers are used to estimate time-varying individual income risk parameters in various manufacturing sectors. Second, the estimated income risk parameters and data on trade barriers are used to analyze the relationship between trade policy and income risk. Finally, a simple dynamic incomplete-market model is used to assess the corresponding welfare costs. In the implementation of this methodology using Mexican data, we find that trade policy changes have a significant short-run effect on income risk. Further, while the tariff level has an insignificant mean effect, it nevertheless changes the degree to which macroeconomic shocks affect income risk.

Until the end of 1977, the U.S. consumer price index (CPI) for rents tended to omit rent increases when units had a change of tenants or were vacant, biasing inflation estimates downward. Beginning in 1978, the Bureau of Labor Statistics (BLS) implemented a series of methodological changes that reduced this nonresponse bias, but substantial bias remained until 1985. We set up a model of nonresponse bias, parameterize it, and test it using BLS microdata. From 1940 to 1985, the official BLS CPI for urban wage earners and clerical workers (CPI-W) price index for tenant rents rose 3.6% annually; we argue that it should have risen 5.0% annually.

We test for customer discrimination with data from more than 800 retail stores employing over 70,000 individuals matched to census data on the demographics of each store's community. While our tests detect some increase in sales when the workforce more closely resembles potential customers, the effects we find are modest in magnitude. Customer discrimination is neither strong nor pervasive. We find little payoff to matching employee demographics to those of potential customers except when the customers do not speak English.