Spurious Regressions and Panel IV Estimation: Revisiting the Causes of Conflict

2021 ◽  
Author(s):  
Christopher B. Barrett ◽  
Paul Christian ◽  
Cornell SC Johnson College of Busin Submitter
Keyword(s):  
Iv Estimation

IV estimation without distributional assumptions

2020 ◽  
Vol 62 (3) ◽  
pp. 688-696
Author(s):  
Theis Lange ◽  
Aksel K. G. Jensen
Keyword(s):  
Iv Estimation ◽  
Distributional Assumptions

scholarly journals Retrospectives: Who Invented Instrumental Variable Regression?

2003 ◽  
Vol 17 (3) ◽  
pp. 177-194 ◽  
Author(s):  
James H Stock ◽  
Francesco Trebbi
Keyword(s):  
Instrumental Variables ◽  
Vegetable Oils ◽  
Instrumental Variable ◽  
Historical Evidence ◽  
Iv Estimation ◽  
Instrumental Variable Regression ◽  
Sewall Wright ◽  
Father And Son

The instrumental variables estimator first appeared explicitly in Appendix B of The Tariff on Animal and Vegetable Oils by Philip G. Wright (1928). It has been suggested that this appendix was written by Philip's son Sewall Wright, then already an important genetic statistician. To find out who wrote Appendix B, we use stylometric statistics to compare it to other texts known to have been written solely by the father and son. The sharp results are consistent with contextual and historical evidence on the authorship of Appendix B and on the origination of the idea of IV estimation.

Matching and semi-parametric IV estimation, a distance-based measure of migration, and the wages of young men

2011 ◽  
Vol 161 (2) ◽  
pp. 208-227 ◽  
Author(s):  
John C. Ham ◽  
Xianghong Li ◽  
Patricia B. Reagan
Keyword(s):  
Young Men ◽  
Iv Estimation

Economic Crisis, Natural Resources, and Irregular Leader Removal in Autocracies

2019 ◽  
Vol 63 (3) ◽  
pp. 726-741
Author(s):  
Suthan Krishnarajan
Keyword(s):  
Natural Resources ◽  
Economic Crisis ◽  
Direct Effect ◽  
Natural Resource ◽  
Instrumental Variable ◽  
Iv Estimation ◽  
International Credit ◽  
Leader Survival ◽  
The 1960S ◽  
The Relationship

AbstractWhy do autocratic leaders escape revolution, coups, and assassination during times of economic crisis? I argue that the spike in natural resource revenues since the 1960s has increased autocratic crisis resilience. The availability of this alternative revenue stream provides autocratic leaders with a constant inflow of money, increases their ability to repress dissent, and improves their access to international credit. Extending the analysis back to 1875, I show that the relationship between economic crisis and irregular leader removal in autocracies is strong and robust before the 1960s, but disappears in more recent periods. Interaction analyses confirm that the effects of economic crisis are moderated by natural resource income. These findings are robust to an array of alternative specifications, including analyses that address endogeneity concerns via instrumental variable (IV) estimation. A more particular examination of the theoretical mechanisms also supports the argument. These findings challenge widely held beliefs in the literature of a strong, direct effect of economic crisis on autocratic leader survival; they explain why economic crisis seems to destabilize some autocrats, but not others.

Intergenerational Income Elasticities, Instrumental Variable Estimation, and Bracketing Strategies

2020 ◽  
Vol 50 (1) ◽  
pp. 1-46
Author(s):  
Pablo A. Mitnik
Keyword(s):  
Instrumental Variable ◽  
Income Elasticity ◽  
Geometric Mean ◽  
Panel Study ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Point Estimate ◽  
Set Estimation ◽  
Iv Estimation ◽  
Short Run

The fact that the intergenerational income elasticity (IGE)—the workhorse measure of economic mobility—is defined in terms of the geometric mean of children’s income generates serious methodological problems. This has led to a call to replace it with the IGE of the expectation, which requires developing the methodological knowledge necessary to estimate the latter with short-run measures of income. This article contributes to this aim. The author advances a “bracketing strategy” for the set estimation of the IGE of the expectation that is equivalent to that used to set estimate (rather than point estimate) the conventional IGE with estimates obtained with the ordinary least squares and instrumental variable (IV) estimators. The proposed bracketing strategy couples estimates generated with the Poisson pseudo–maximum likelihood estimator and a generalized method of moments IV estimator of the Poisson or exponential regression model. The author develops a generalized error-in-variables model for the IV estimation of the IGE of the expectation and compares it with the corresponding model underlying the IV estimation of the conventional IGE. By considering both bracketing strategies from the perspective of the partial-identification approach to inference, the author specifies how to construct confidence intervals for the IGEs, in particular when the upper bound is estimated more than once with different sets of instruments. Finally, using data from the Panel Study of Income Dynamics, the author shows that the bracketing strategies work as expected and assesses the information they generate and how this information varies across instruments and short-run measures of parental income. Three computer programs made available as companions to the article make the set estimation of IGEs, and statistical inference, very simple endeavors.

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