On the estimation of Okun’s coefficient in some countries in Latin America: a comparison between OLS and GME estimators
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We explore Okun’s coefficient in several Latin American countries for the period from 1995 to 2017 and compare the results obtained using ordinary least squares (OLS) and generalised maximum entropy (GME) estimators. There are several advantages in considering the GME estimator over traditional regression approaches. First, it can estimate the parameters of an equation without imposing constraints on the probability distribution of the errors. Second, empirical and simulation studies available in the literature showed that GME worked well for ill-posed problems (e.g. when a model estimate is performed using a small sample of data). Among the main findings, we confirm the inverted relationship between changes in the unemployment rate and real gross domestic product growth in the explored countries except for Perù. Okun’s coefficient and the associated confidence intervals obtained by applying GME were very close to those obtained from OLS. Therefore, we did not observe a gain when using the GME estimator rather than the classic OLS approach.
KeywordsGeneralised maximum entropy Gross domestic product Latin America countries Ordinary least squares Okun’s coefficient Unemployment rate
JEL ClassificationC50 E24 N16
I would like to thank two reviewers for their constructive suggestions that helped to improve the presentation and quality of the article. I dedicate this article to my daughter Gloria, who was born in 2018. The opinions expressed herein are those of the author and do not necessarily reflect those of the institution of affiliation.
This research has not received funding.
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Conflict of interest
The authors declare that they have no conflict of interest.
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