In this paper, we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We approximate the unknown functional coefficients by some basis...

We utilize county-level data to explore growth determination in the U.S. and possible heterogeneity in growth determination across individual states. The data includes over 3,000 cross-sectional observations and 39 demographic control variables. We use a consistent two stage least squares...

This paper studies semiparametric versions of the classical sample selection model (Heckman (1976, 1979)) without exclusion restrictions. We extend the analysis in Honor'e and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that...

This paper studies heterogeneity in the fiscal reaction function for European Union members by resorting to the unconditional quantile regression estimation. Based on annual observations spanning from 2005 to 2018, the results point to significant asymmetries concerning the fiscal response...

One of the greatest concerns over globalisation is its impact on the environment. This paper contributes to this debate by analysing the consequences of becoming an exporter on a firm's energy consumption. We show both theoretically and empirically that for low fuel intensity firms exporting...

Many commonly used treatment effects estimators rely on the unconfoundedness assumption ("selection on observables") which is fundamentally non-testable. When evaluating the effects of labor market policies, researchers need to observe variables that affect both treatment participation and labor...

Nonparametric regression with spatial, or spatio-temporal, data is considered. The conditional mean of a dependent variable, given explanatory ones, is a nonparametric function, while the conditional covariance reflects spatial correlation. Conditional heteroscedasticity is also allowed, as well...

It is well known that the class of strong (Generalized) AutoRegressive Conditional Heteroskedasticity (or GARCH) processes is not closed under contemporaneous aggregation. This paper provides the dynamics followed by the aggregate process when the individual persistence parameters are drawn from...

Many commonly used treatment effects estimators rely on the unconfoundedness assumption (“selection on observables") which is fundamentally non-testable. When evaluating the effects of labor market policies, researchers need to observe variables that affect both treatment participation and...