A time series analysis of household income inequality in Brazil 1977 to 2013

• Autor(a) principal: Caparoz, Marcel
• Data de Publicação: 2019
• Outros Autores: Marçal, Emerson Fernandes, Mattos, Enlinson
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Economia (Online)
• Texto Completo: https://periodicos.fgv.br/rbe/article/view/75062
• topic: evolution Income Inequality; time series analysis; public policies

Abstract This paper analyses the evolution of household income inequality in Brazil from 1977 and 2013 using Brazilian National Household Survey data at aggregated and regional levels. Four income shares quantiles are analyzed: Top 1%, Top 10%, Bottom 10% and Bottom 50%. The novelty of our study is to use time series techniques to understand the phenomenon of income inequality within this period. We use Markov-Switching Regime Change Model (Hamilton (1989)) and State Space Unobservable Model (Harvey (1990)) techniques. Both strategies suggest that income concentration periods are related to low growth rates but high inflation rates as opposed to many developed countries (Piketty and Saez (2014)). Results from Markov-switching models suggest a detection of a new regime during first decade of 2000's in poorest quantiles (bottom 10% and 50%) increasing their correspondent income shares. Moreover a regime of low shares started to prevail at the same time for Top 10% whereas for those at the Top 1% had prevailed a concentrated income share regime during eighties and nineties. We argue that Brazilian macroeconomic instability helped to produce a regime of low income shares at the bottom of the distribution. Our results suggest that recent inequality reduction in the shares of top 1% quantile can be seen as a “back to normality” instead of “a new era” whereas significant changes can be seen in other quantiles. State space models results also suggests that macroeconomic of the eighties had a severe effects on Brazilian inequality whereas the dynamics of Top 1% income shares reinforce the return of 70's level considering aggregated data. Last, our estimates unveil important regional differences in many quantiles mainly on the low brackets where poorer regions seem to have persistent income-inequality that take longer to be reduced.