Knowledge that Transforms

Research has focused on why and when firms access external technology markets. Less is known about the reliability of patents attached to licensed technologies during litigation. Unreliable patents expose a firm to loss of downstream revenues. We address this by constructing a data set of patent litigation in the pharmaceutical industry and exploit a change in patent law that exogenously increased the probability of litigation. We find that licensed patents are more likely to fall during litigation. This effect is isolated to firms with fewer intellectual property capabilities and less patenting experience, suggesting that benefits from external technology are not shared equally.

Governments have used vouchers to spend billions of dollars on private education; much of this has gone to religiously affiliated schools. We explore the possibility that vouchers could alter the financial outcomes of religious organizations that are operating schools and thus have an impact on the spiritual, moral, and social fabric of communities. Using a data set of Catholic parish finances from Milwaukee, we show that vouchers are a dominant source of funding for many churches. Vouchers appear to offer financial stability for congregations as voucher expansion prevents church closures and mergers. However, voucher expansion causes significant declines in church donations and church revenue from noneducational sources.

Survey nonresponse has risen in recent years, which has increased the share of imputed and underreported values found on commonly used data sets. While this trend has been well documented for earnings, the growth in nonresponse to government transfers questions has received far less attention. We demonstrate analytically that the underreporting and imputation of transfer benefits can lead to program impact estimates that are substantially overstated when using instrumental variables methods to correct for endogeneity or measurement error in benefit amounts. We document the importance of failing to account for these issues using two empirical examples.

This paper shows that since votes of members of the Federal Open Market Committee have been included in press statements, stock prices increase after the announcement when votes are unanimous but fall when dissent (which typically is due to preference for higher interest rates) occurs. This pattern started prior to the 2007–2008 financial crisis. The differences in stock market reaction between unanimity and dissent remain, even controlling for the stance of monetary policy and consecutive dissent. Statement semantics also do not seem to explain the documented effect. We find no differences between unanimity and dissent with respect to impact on market risk and Treasury securities.

We propose to use economic theories to construct shrinkage estimators that perform well when the theories' empirical implications are approximately correct but perform no worse than unrestricted estimators when the theories' implications do not hold. We implement this construction in various settings, including labor demand and wage inequality, and estimation of consumer demand. We provide asymptotic and finite sample characterizations of the behavior of the proposed estimators. Our approach is an alternative to the use of theory as something to be tested or to be imposed on estimates. Our approach complements uses of theory for identification and extrapolation.

This paper develops a criterion to assess equalization of opportunity that is consistent with theoretical views of equality of opportunity. We characterize inequality of opportunity as a situation where some groups in society enjoy an illegitimate advantage. In this context, equalization of opportunity requires that the extent of the illegitimate advantage enjoyed by the privileged groups falls. Robustness requires that this judgment be supported by the broadest class of individual preferences. We formalize this criterion in a decision-theoretic framework and derive an empirical condition for equalization of opportunity based on observed opportunity distributions. The criterion is used to assess the effectiveness of child care at equalizing opportunity among children, using quantile treatment effects estimates of a major child care reform in Norway. Overall, we find strong evidence supporting equalization of opportunity.

We evaluate the impact on youth crime of a welfare reform that tightened activation requirements for social assistance clients. The evaluation strategy exploits administrative individual data in combination with geographically differentiated implementation of the reform. We find that the reform reduced crime among teenage boys from economically disadvantaged families. Stronger reform effects on weekday versus weekend crime, reduced school dropout, and favorable long-run outcomes in terms of crime and educational attainment point to both incapacitation and human capital accumulation as key mechanisms. Despite lowered social assistance take-up, we uncover no indication that loss of income support pushed youth into crime.

In volume 94 of this REVIEW, Adams, Blackburn, and Cotti (ABC), using Fatal Accident Reporting System data from 1998 to 2006, find that a 10% increase in the minimum wage is associated with a 7% to 11% increase in alcohol-related fatal traffic accidents involving teen drivers. We find this result does not hold when the analysis period is expanded to include 1991 through 2013. In addition, auxiliary analyses provide no support for income-driven increases in alcohol consumption, the primary mechanism posited by ABC. Together, our results suggest that minimum wage increases are not a silent killer.

A new regression-based approach for the estimation of the tail index of heavy-tailed distributions with several important properties is introduced. First, it provides a bias reduction when compared to available regression-based methods; second, it is resilient to the choice of the tail length used for the estimation of the tail index; third, when the effect of the slowly varying function at infinity of the Pareto distribution vanishes slowly, it continues to perform satisfactorily; and fourth, it performs well under dependence of unknown form. An approach to compute the asymptotic variance under time dependence and conditional heteroskcedasticity is also provided.

This paper estimates the elasticity of substitution between capital and skill in manufacturing using immigration-induced variation in skill mix across U.S. counties between 1860 and 1930. We find that capital initially complemented both high- and low-skill labor (determined by literacy) and, unlike today, was more complementary with low-skill labor. Around 1890, capital increased its relative complementarity with high-skill labor. Simulations calibrated to our estimates imply the level of capital-skill complementarity after 1890 allowed the manufacturing sector to absorb the large wave of Eastern and Southern European immigrants with only a modest decline in less-skilled relative wages. This would not have been possible under the older production technology.