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XTIVREG28: Stata module to perform extended IV/2SLS, GMM and AC/HAC, LIML and k-class regression for panel data models (version 8)
TLDR
xtivreg2 as mentioned in this paper is a wrapper for ivreg28, which can be installed on Stata versions 9+ and can be used to estimate fixed-effects and first-difference panel data models with possibly endogenous regressors.Abstract:
xtivreg28 implements IV/GMM estimation of the fixed-effects and first-differences panel data models with possibly endogenous regressors. It is essentially a wrapper for ivreg28, which must be installed for xtivreg28 to run. Users of Stata versions 9+ should use xtivreg2. xtivreg28 supports all the estimation and reporting options of ivreg28; see help ivreg28 for full descriptions and examples. In particular, all the statistics available with ivreg28 (heteroskedastic, cluster- and autocorrelation-robust covariance matrix and standard errors, overidentification and orthogonality tests, first-stage and weak/underidentification statistics, etc.) are also supported by xtivreg2 and will be reported with any degrees-of-freedom adjustments required for a panel data estimation.read more
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Law and Innovation: Evidence from State Trade Secrets Laws
TL;DR: In this paper, the effect of state enactment of the Uniform Trade Secrets Act (UTSA) on R&D among U.S. businesses between 1979 and 1998 was studied.
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Democracy, Dictatorship and Protection of Property Rights
TL;DR: In this article, the authors investigate how political regimes influence property rights and conclude that democracy is likely endogenous to property rights protection, even when controlling for endogeneity and country-specific characteristics.
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Reference Pricing, Competition, and Pharmaceutical Expenditures: Theory and Evidence from a Natural Experiment
TL;DR: This paper studied the impact of regulation on competition between brand-names and generics and pharmaceutical expenditures using a unique policy experiment in Norway, where reference pricing (RP) replaced price cap regulation in 2003 for a sub-sample of off-patent products.
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Does Wealth Inequality Matter for Growth? The Effect of Billionaire Wealth, Income Distribution, and Poverty
Sutirtha Bagchi,Jan Svejnar +1 more
TL;DR: The authors derived a global measure of wealth inequality from Forbes magazine's listing of billionaires and compared its effect on growth to the effects of income inequality and poverty, finding that wealth inequality reduces economic growth, but when controlling for the fact that some billionaires acquired wealth through political connections, the effect of politically connected wealth inequality is negative, while politically unconnected wealth inequality, income inequality, and initial poverty have no significant effect.
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Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases
Ben Michael Brumpton,Ben Michael Brumpton,Eleanor Sanderson,Fernando Pires Hartwig,Fernando Pires Hartwig,Sean Harrison,Gunnhild Åberge Vie,Yoonsu Cho,Laura D Howe,Amanda Hughes,Dorret I. Boomsma,Alexandra Havdahl,Alexandra Havdahl,John L. Hopper,Michael C. Neale,Michel G. Nivard,Nancy L. Pedersen,Chandra A. Reynolds,Elliot M. Tucker-Drob,Andrew D. Grotzinger,Laurence J. Howe,Tim T Morris,Shuai Li,Shuai Li,Wei-Min Chen,Johan Håkon Bjørngaard,Kristian Hveem,Cristen J. Willer,David M. Evans,David M. Evans,Jaakko Kaprio,George Davey Smith,Bjørn Olav Åsvold,Gibran Hemani,Neil M Davies +34 more
TL;DR: Differences between population-based and within-family based MR estimates are found, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.
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