Enhanced Routines for Instrumental Variables/Generalized Method of Moments Estimation and Testing

Abstract

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Does Board Gender Diversity Influence Financial Performance? Evidence from Spain

“…Because of the recent publication of these legislations and the fact that only a few countries have imposed them, the results of this paper have strong economic and public policy implications, especially for the stakeholders, directors, and law makers (mainly market regulators and governments). Second, by using the test of endogeneity proposed by Baum et al (2007), we empirically analyze the existence of endogeneity in the relationship between gender diversity and firm performance. Third, to date, this is the third research work that studies the impact of the number of female corporate board memberships in the Spanish capital market, since most previous empirical evidences on this issue have been based on the US market.…”

“…The objective of dividing our statistical method into two steps is to address the concern of potential endogeneity and causality associated with the relations between the number of women in the boardroom and financial performance. In addition, to assume from a theoretical view that the relationship between gender diversity and financial performance is endogenously determined, we empirically test this by using the GMM distance test of endogeneity proposed by Baum et al (2007).…”

“…Since, from a theoretical point of view, there are arguments to justify a possible endogeneity and causality of the relationship between gender diversity and firm performance (Campbell and Mínguez-Vera 2008;Srinidhi et al 2011), we applied the endogeneity test proposed by Baum et al (2007) to empirically test its existence. As shown in Table 6, the results for this test are statistically significant, and we therefore accept the null hypothesis, which corroborates the presence of endogeneity.…”

U.S. hospital efficiency and adoption of health information technology

“…However, some of the instrumental variables used in the past [30,46,47] were found to be unsatisfactory. 6 We applied the IVREG2 routine in Stata/SE 11.1 to our cost equation [51,52] to test the validity of our instruments and found that our model did not pass overidentification and weak identification tests.…”

Controlling Episodic Air Pollution with a Seasonal Gas Tax: The Case of Cache Valley, Utah

“…(1)] was unnecessary, we note that in our PM 2.5 regression model moving average processes eliminate a potential repetitive seasonal component in the dependent variable (Maddala and Kim 1998). In the IV PM 2.5 regression equation, we use a HAC weighting matrix to correct for autocorrelation, the main source of which is seasonality (Baum et al 2007). 15 A 4-month interval was necessary in order to obtain a large enough subsample for econometric estimation.…”