Are Drone Strikes Effective in Afghanistan and Pakistan? On the Dynamics of Violence between the United States and the Taliban

Strikes by unmanned aerial vehicles, or drones, have been the primary weapon used by the United States to combat the Taliban and Al-Qaeda in Afghanistan and Pakistan. This paper examines the dynamics of violence involving drone strikes and the Taliban/Al-Qaeda in Afghanistan and Pakistan from January 2007 to December 2010. We find that drone strikes do not have any significant impact on terrorist violence in Afghanistan but that drone strikes do have a significant impact on Taliban/Al-Qaeda violence in Pakistan. We find that our results are robust to examining different time periods and lag structures. We also examine the impact of successful and unsuccessful drone strikes (which did or did not succeed in targeted killing of a militant leader) on terrorist attacks by the Taliban. We find strong negative impacts of unsuccessful drone strikes on Taliban violence in Pakistan, showing the deterrent effects are quite strong, while the incapacitation effects appear to be weak or non-existent.time series models, conflict

On the Sensitivity of Return to Schooling Estimates to Estimation Methods, Model Specification, and Influential Outliers If Identification Is Weak

We provide a comparison of return to schooling estimates based on an influential study by Angrist and Krueger (1991) using two stage least squares (TSLS), limited information maximum likelihood (LIML), jackknife (JIVE), and split sample instrumental variables (SSIV) estimation. We find that the estimated return to education is quite sensitive to the age controls used in the models as well as the estimation method used. In particular, we provide evidence that JIVE coefficients' standard errors are inflated by a group of extreme years of education observations, for which identification is especially weak. We propose to use Cook's Distance in order to identify influential outliers having substantial influence on first-stage JIVE coefficients and fitted values.Cook's Distance, heteroskedasticity, outliers, return to education, specification, weak instruments

Direct evidence on risk attitudes and migration

Geographic mobility is important for the functioning of labor markets because it brings labor resources to where they can be most efficiently used. It has long been hypothesized that individuals' migration propensities depend on their attitudes towards risk, but the empirical evidence, to the extent that it exists, has been indirect. In this paper, we use newly available data from the German Socio-Economic Panel to measure directly the relationship between migration propensities and attitudes towards risk. We find that individuals who are more willing to take risks are more likely to migrate between labor markets in Germany. This result is robust to stratifying by age, sex, education, national origin, and a variety of other demographic characteristics, as well as to the level of aggregation used to define geographic mobility. The effect is substantial relative to the unconditional migration propensity and compared to the conventional determinants of migration. We also find that being more willing to take risks is more important for the extensive than for the intensive margin of migratio

The Cure Can Be Worse than the Disease: A Cautionary Tale Regarding Instrumental Variables

In this paper we draw attention to two problems associated with the use of instrumental variables (IV) whose importance for empirical work has not been fully appreciated. First, using potential instruments that explain little of the variation in the: endogenous explanatory variables can lead to large inconsistencies of the IV estimates even If only a weal

The Persistence of Self-Employment Across Borders: New Evidence on Legal Immigrants to the United States

Using recently-available data from the New Immigrant Survey, we find that previous self-employment experience in an immigrant's country of origin is an important determinant of their self-employment status in the U.S., increasing the probability of being self-employed by about 7 percent. Our results improve on the previous literature by measuring home-country self-employment directly rather than relying on proxy measures. We find little evidence to suggest that home-country selfemployment has a significant effect on U.S. wages in either paid employment or self employment.Self-employment, entrepreneurship, New Immigrant Survey

Natives, the Foreign-Born and High School Equivalents: New Evidence on the Returns to the GED

In this paper we explore the labor market returns to the General Education Development exam, or GED. Using new data from the Current Population Survey, we examine how the return to the GED varies between U.S. natives and the foreign-born. We find that foreignborn men who hold a GED but received all of their formal schooling outside of the U.S. earn significantly more than either foreign-schooled dropouts or individuals with a foreign high school diploma. For foreign-born men with some U.S. schooling, earning a GED brings higher wages than a traditional U.S. high school diploma, although this difference is not statistically significantly different from zero. These patterns stand in contrast to those for U.S. natives, among whom GED recipients earn less than high school graduates but significantly more than dropouts. The effects for natives appear to become larger over the life cycle and do not seem to be due to cohort effects. While it is difficult to attach a purely causal interpretation to our findings, they do indicate that the GED may be more valuable in the labor market than some previous research suggests

On the sensitivity of return to schooling estimates to estimation methods, model specification, and influential outliers if identification is weak

We provide a comparison of return to schooling estimates based on an influential study by Angrist and Krueger (1991) using two stage least squares (TSLS), limited information maximum likelihood (LIML), jackknife (JIVE), and split sample instrumental variables (SSIV) estimation. We find that the estimated return to education is quite sensitive to the age controls used in the models as well as the estimation method used. In particular, we provide evidence that JIVE coefficients' standard errors are inflated by a group of extreme years of education observations, for which identification is especially weak. We propose to use Cook's Distance in order to identify influential outliers having substantial influence on first-stage JIVE coefficients and fitted values