Nonparametric instrumental variable (NPIV) estimation is a cutting‐edge methodological framework employed to uncover causal relationships in the presence of endogenous regressors, without imposing ...

Building upon recent developments in spatial econometric models that address the misspecification of spatial weight matrices through adaptive LASSO techniques, my research aims to enhance the ...

Assessing causal treatment effect on a time-to-event outcome is of key interest in many scientific investigations. Instrumental variable (IV) is a useful tool to mitigate the impact of endogenous ...

In this work we propose a functional concurrent regression model to estimate labor supply elasticities over the years 1988 through 2014 using Current Population Survey data. Assuming, as is common, ...

Abstract: Treatment effect estimation from observational data is a fundamental problem in causal inference, and its critical challenge is to address the confounding bias arising from the confounders.

ABSTRACT: Economic modeling that yields practical value must cater for effects caused by exogenous variables. AutoRegressive eXogenous approach (ARX) has been widely used in regional economic studies.

Sequential causal effect estimation has recently attracted increasing attention from research and industry. While the existing models have achieved many successes, there are still many limitations.

This paper extends the usual Instrumental Variables estimator of the parameters of a linear regression involving stochastic regressors to the case where these parameters are subject to exact linear ...