Testing Exogeneity in the Bivariate Probit Model: A Monte Carlo Study

By C. Monfardini, Rosalba Radice. 2008

250 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/45e98d2f33f18b1e12672df3c053ce78a7ab55b6

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In Economics and Econometrics

In Management Science and Operations Research

Citations in the corpus

Training and Innovation (2009, background): “This again can be seen as evidence that omitted variables are only weakly correlated or uncorrelated with training and innovation (Monfardini and Radice 2008).”
Out of Sight, Out of Mind: Migration, Entrepreneurship and Social Capital (2012, methodology): “m = nW q( ) + q( ) By combining these two equations and using (28) and (24), we obtain:”
Firms’ exporting and importing activities: is there a two-way relationship? (2012, unknown): “…of past importing, while the hypothesis of exogeneity of the lagged import dummy is supported by the absence of statistically significant correlation between the error terms of the two equations (see Monfardini and Radice (2008) for a discussion on testing exogeneity in bivariate probit models).”
Monitoring Managers: Does it Matter? (2013, unknown): “Based on Monte Carlo evidence, Monfardini and Radice (2008) conclude that this test performs well even when the distribution of the errors is specified incorrectly.”
Estimation of a semiparametric recursive bivariate probit model in the presence of endogeneity (2011, background): “When the exclusion restriction does not hold, the estimates areworse than those in Figure 2, case inwhich the availability of an instrument helps to obtain better estimated coefficients; Monfardini & Radice (2008) found the same result in a similar context.”
Return migrants: The rise of new entrepreneurs in rural China (2010, unknown): “Although no exclusion restrictions are theoretically needed to achieve identification of the model parameters (Wilde, 2000), Monfardini and Radice (2008) advocate the use of instruments to help in obtaining results more robust to distributional misspecification.”
Fringe benefits and job satisfaction (2010, methodology): “Estimation of the recursive bivariate probit model explained above and the following endogeneity testing follows from Monfardini and Radice (2008). The authors”