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| Format: | Artículo científico |
| Sprache: | en |
| Veröffentlicht: |
Universidade de São Paulo
2019
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| Online-Zugang: | https://www.redalyc.org/articulo.oa?id=553861448012 https://www.redalyc.org/journal/5538/553861448012/ https://www.redalyc.org/journal/5538/553861448012/html/ https://www.redalyc.org/journal/5538/553861448012/553861448012.epub https://www.redalyc.org/journal/5538/553861448012/movil |
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Inhaltsangabe:
- Estimating Poisson pseudo-maximum-likelihood rather than log-linear model of a log-transformed dependent variable Victor Motta Administración y Contabilidad Health economics Applied microeconometrics Poisson pseudo maximum likelihood estimator Purpose–The purpose of this study is to account for a recent non-mainstream econometric approach usingmicrodata and how it can inform research in business administration. More specifically, the paper draws fromthe applied microeconometric literature stances in favor offitting Poisson regression with robust standarderrors rather than the OLS linear regression of a log-transformed dependent variable. In addition, the authorspoint to the appropriate Stata coding and take into account the possibility of failing to check for the existenceof the estimates–convergency issues–as well as being sensitive to numerical problems.Design/methodology/approach–The author details the main issues with the log-linear model,drawing from the applied econometric literature in favor of estimating multiplicative models for non-countdata. Then, he provides the Stata commands and illustrates the differences in the coefficient and standarderrors between both OLS and Poisson models using the health expenditure dataset from the RAND HealthInsurance Experiment (RHIE).Findings–The results indicate that the use of Poisson pseudo maximum likelihood estimators yield betterresults that the log-linear model, as well as other alternative models, such as Tobit and two-part models.Originality/value–The originality of this study lies in demonstrating an alternative microeconometrictechnique to deal with positive skewness of dependent variables. 2019 artículo científico 2531-0488 https://www.redalyc.org/articulo.oa?id=553861448012 https://www.redalyc.org/journal/5538/553861448012/ https://www.redalyc.org/journal/5538/553861448012/html/ https://www.redalyc.org/journal/5538/553861448012/553861448012.epub https://www.redalyc.org/journal/5538/553861448012/movil en http://www.redalyc.org/revista.oa?id=5538 RAUSP Management Journal application/pdf Universidade de São Paulo RAUSP Management Journal (Brasil) Num.4 Vol.54