ABSTRACT: Purpose: The purpose of this study is to examine the effect of factor inputs, namely gross fixed capital formation, human capital investment, and population growth, on industrial sector ...
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.
Nobel laureate Lars Peter Hansen, the David Rockefeller Distinguished Service Professor in Economics and Statistics at the University of Chicago, shared the Sveriges Riksbank Prize in Economic ...
Endogeneity presents a significant challenge in conducting causal inference in observational settings. Researchers in social sciences, statistics, and related fields have developed various ...
ABSTRACT: This study assesses the effects of migrant remittances on inclusive growth in Africa. We applied the ordinary least squares method on a sample of 48 countries in Africa with daily data from ...
How to Set Temporary Environment Variables in Linux (+Video Tutorial) Your email has been sent In Jack Wallen's tutorial for developers, he show how easy it is to set temporary environment variables ...
The R package 'HD_Variable_Selection_under_endogeneity' implements the coding procedure for the research project titled: "Variable Selection and Goodness-of-fit Testing in High-Dimensional Linear ...
This paper uses a nationally representative and large-scale dataset from China to empirically examine the relationship between exercise participation and happiness. To address the problem of reverse ...
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