scholarly journals A Generalized Heckman Model With Varying Sample Selection Bias and Dispersion Parameters

2023 ◽  
Author(s):  
Fernando de Souza Bastos ◽  
Wagner Barreto-Souza ◽  
Marc G. Genton
Keyword(s):  
Selection Bias ◽  
Sample Selection ◽  
Sample Selection Bias ◽  
Dispersion Parameters ◽  
Heckman Model

scholarly journals University Choice and Students` Migration: An Application of the Heckman Model

2010 ◽  
Vol 25 (2) ◽  
pp. 65-79
Author(s):  
Park Min Soo ◽  
Koo Chan Dong ◽  
Oh Jeung Il
Keyword(s):  
High School Students ◽  
Selection Bias ◽  
Higher Education Policy ◽  
Sample Selection ◽  
Small Towns ◽  
Sample Selection Bias ◽  
Economic Policies ◽  
School Students ◽  
Heckman Model ◽  
Migration Equation

This study attempts to elucidate the migration patterns of Korean high school students choosing a university. Estimating a migration equation without considering sample-selection bias would yield incorrect results. Thus, this study used the Heckman model. We found that the sample selection bias would be serious in the case of students living in Seoul. We also found that students living in small towns had a 13.1 percent higher probability of migrating than those residing in Seoul, and an 8.2 percent higher probability than those living in other big cities. The differences in the migration probabilities can be interpreted as a preference for metropolitan areas. A simple policy that provides physical and financial resources to the universities would not be successful. A higher-education policy is likely to be effective only when it is implemented in coordination with the cultural and economic policies of the region.

Foreign Direct Investment and Export Decisions of Vietnamese Enterprises

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Pham The Anh
Keyword(s):  
Foreign Direct Investment ◽  
Selection Bias ◽  
Direct Investment ◽  
Positive Impact ◽  
Sample Selection ◽  
Sample Selection Bias ◽  
Heckman Model ◽  
Insignificant Effect ◽  
Export Decisions ◽  
The Impact

This research quantifies the impact of foreign direct investment (FDI) on the export  decisions of Vietnamese  enterprises. To control the problem of sample selection bias, this study employs the Heckman model (1979) estimated for two equations on export participation and rate. Unlike previous researches, which mainly rely on one single proxy of FDI, this research adopts sensititivy analysis through the estimation of a model with two representative variables for FDI. It is indicated that FDI has a positive impact on the export decisions of Vietnamese enterprises. Nonetheless, FDI has an insignificant effect on the export rate of Vietnamese enterprises.

scholarly journals Heterogeneous Causal Effects and Sample Selection Bias

2015 ◽  
Vol 2 ◽  
pp. 351-369 ◽  
Author(s):  
Richard Breen ◽  
Seungsoo Choi ◽  
Anders Holm
Keyword(s):  
Selection Bias ◽  
Sample Selection ◽  
Causal Effects ◽  
Sample Selection Bias

Face Hallucination Based On Sample Selection Bias Correction

2012 ◽  
Vol 4 (5) ◽  
pp. 91-98
Author(s):  
Tao Lu ◽  
Ruimin Hu ◽  
Zhen Han ◽  
Junjun Jiang ◽  
Jun Chang
Keyword(s):  
Selection Bias ◽  
Bias Correction ◽  
Sample Selection ◽  
Sample Selection Bias ◽  
Face Hallucination

Diagnosing Sample-Selection Bias in Historical Heights: A Reply to Komlos and A’Hearn

2019 ◽  
Vol 79 (4) ◽  
pp. 1154-1175 ◽  
Author(s):  
Howard Bodenhorn ◽  
Timothy W. Guinnane ◽  
Thomas A. Mroz
Keyword(s):  
Economic Growth ◽  
Nineteenth Century ◽  
Selection Bias ◽  
Economic History ◽  
Sample Selection ◽  
Sample Selection Bias ◽  
Conditional Mean

Our 2017 article in this Journal stresses the pitfalls of using choice-based samples in economic history. A prominent example is the literature addressing the so-called antebellum puzzle. Heights researchers claim that Americans grew shorter in the first half of the nineteenth century, a period of robust economic growth. We argue that this result relies on choice-based samples. Without knowing the process that led to inclusion in the sample, researchers cannot properly estimate conditional mean heights. We proposed a diagnostic that can detect, but not correct for, selection bias. Komlos and A’Hearn’s interpretation of our analysis confuses diagnosis with cure. We dispute their view that selection bias has been appreciated in the heights literature.

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