Estimating dynamic Panel data. A practical approach to perform long panels

• Main Authors: Romilio Labra, Celia Torrecillas
• Format: Article
• Language: English
• Published: Universidad Nacional de Colombia
• Series: Revista Colombiana de Estadística
• Subjects: Dynamic Panels; Endogenous Models; Overidentification; Panel Data; Stata; xtabond2
• Online Access: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512018000100031&lng=en&tlng=en

Abstract Panel data methodology is one of the most popular tools for quantitative analysis in the field of social sciences, particularly on topics related to economics and business. This technique allows simultaneously dressing individual effects, numerous periods, and in turn, the endogeneity of the model or independent regressors. Despite these advantages, there are several methodological and practical limitations to perform estimations using this tool. There are two types of models that can be estimated with Panel data: Static and Dynamic, the former is the most developed while dynamic models still have some theoretical and practical constraints. This paper focuses precisely on the latter, Dynamic panel data, using an approach that combines theory and praxis, and paying special attention on its applicability on macroeonomic data, specially datasets with a long period of time and a small number of individuals, also called long panels.