ResumenSe detallan los factores que podrían explicar la presencia de la trampa de ingresos medios o de lento crecimiento económico. Se incorporan los criterios para medir si una economía cualquiera se ubica dentro de esas categorías. Asimismo, con información estadística entre 1870 a 2014 se evalúa bajo diferentes metodologías si 18 economías latinoamericanas y la región en su conjunto se pueden incorporar en estas tipologías. Se concluye que la mayoría de las economías de la región y el conjunto se ubican en dicha trampa o tienen bajo * Se agradecen las observaciones de Patricia del Hierro a una versión inicial del documento. Asimismo, a los comentarios de los dictaminadores anónimos, aunque el resultado final es de nuestra exclusiva responsabilidad.Palabras clave: crecimiento económico, lento crecimiento, trampa de ingresos medios, AbstractThis paper presents the explaining factors of the presence of the middle income trap (and slow economic growth trap). It also incorporates the criteria to measure whether any economy falls within those categories. Additionally, it evaluate a sample of 18 Latin American economies and the regional average between 1870 and 2014 under different methodologies for incorporated these in the tipology. It is concluded that most of the economies of the region and the whole are in the middle income trap or slow economic growth conditions and that the probability of reaching the status of high-income economy would be very reduced.
This paper begins by reviewing the literature on the relation between economic growth and the functional distribution of income since the time of the classical economists, highlighting the work of Kalecki and the post-Keynesians who develop the growthregimes approach. It reconstructs and analyses statistics on the shares of wages, income from self-employment (or from mixed sources) and profits in Peru's GDP between 1942 and 2013, and then compares these shares with the averages for Latin America and other economies. The study then makes a comparative analysis of trends in the wage share and rate of growth, and it estimates a simultaneous equations model using three-stage least squares (3SLS) and generalized method of moments (GMM) to determine the growth regime. The conclusion is that growth is wage-led, so distributional policies to increase this component would likely boost the level of economic activity. 1 While the final content of this article is the authors' sole responsibility, they are grateful for comments by Patricia del Hierro and an anonymous referee.
<p>Construimos un índice de desigualdad considerando la distribución de la riqueza, la distribución factorial y la distribución personal del ingreso. Con este indicador de dos o tres componentes estimamos y analizamos los resultados para las diferentes economías de América Latina y la región en su conjunto entre 1980 y 2016. Asimismo, determinamos la dispersión entre los diferentes componentes del indicador. Por último, evaluamos la vinculación entre el crecimiento económico y el indicador de desigualdad mediante un análisis econométrico por economía con base en mínimos cuadrados ordinarios (MCO) y en un panel dinámico para toda la región utilizando el método de Arellano Bond. Los coeficientes para toda la región tienen signo negativo reflejando que a mayor desigualdad la variación porcentual del producto interno bruto (PIB) es menor o a menor desigualdad el producto aumenta.</p><p><strong> </strong></p><p align="center">INEQUALITY INDEX AND ECONOMIC GROWTH IN LATIN AMERICA</p><p align="center"><strong>ABSTRACT</strong><strong></strong></p>The paper presents an inequality composite index of three components: wealth distribution, factorial income distribution and personal income distribution. This index allows us to analyze different results for the various Latin American economies and for the region as whole in the period 1980-2016. In addition, the paper assesses a dispersion analysis for each of the index components. Finally, we evaluate the effects of the inequality index on economic growth for each Latin American economy by using Ordinary Least Squares (OLS) and dynamic panel data models. The negative coefficient for the entire region shows that the greater (lower) social inequality, the lower (greater) the percentage variation of Gross Domestic Product (GDP).
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