On the finite-sample properties of conditional empirical likelihood estimators

We provide Monte Carlo evidence on the finite-sample behavior of the conditional empirical likelihood (CEL) estimator of Kitamura, Tripathi, and Ahn and the conditional Euclidean empirical likelihood (CEEL) estimator of Antoine, Bonnal, and Renault in the context of a heteroscedastic linear model with an endogenous regressor. We compare these estimators with three heteroscedasticity-consistent instrument-based estimators and the Donald, Imbens, and Newey estimator in terms of various performance measures. Our results suggest that the CEL and CEEL with fixed bandwidths may suffer from the no-moment problem, similarly to the unconditional generalized empirical likelihood estimators studied by Guggenberger. We also study the CEL and CEEL estimators with automatic bandwidths selected through cross-validation. We do not find evidence that these suffer from the no-moment problem. When the instruments are weak, we find CEL and CEEL to have finite-sample properties—in terms of mean squared error and coverage probability of confidence intervals—poorer than the heteroscedasticity-consistent Fuller (HFUL) estimator. In the strong instruments case, the CEL and CEEL estimators with automatic bandwidths tend to outperform HFUL in terms of mean squared error, while the reverse holds in terms of the coverage probability, although the differences in numerical performance are rather small.     

Rural Residence as a Determinant of Attitudes Toward US Immigration Policy

Between 1990 and 2000, the foreign-born population in the United States increased by 57 per cent, compared to a 13 per cent increase in the native-born population. This growth has fueled considerable media attention and has fomented some anti-immigrant sentiments. Although a number of authors have charted changes in support for restrictionist immigration policies, few have examined their determinants. In this paper, we focus on region of residence and use data from a 2004 telephone survey of a nationally representative sample of 1888 adults to test the hypothesis that rural Americans are more likely to support restrictive immigration policies than individuals in urban and suburban communities. In a series of regression analyses, this hypothesis is confirmed; rural residents hold the most restrictionist views. Additional analyses indicate that this effect of rural residence on policy attitudes is mediated by attitudes toward multiculturalism, the perceived traits of immigrants, and perceptions about the costs of immigration. Ultimately, the analyses indicate that the perceived cost of immigration is the single strongest predictor of support for restrictive immigration policies, and that it best accounts for rural residents'more restrictionist views.