Taxa de Desemprego Não Aceleradora da Inflação: Uma estimação da NAIRU para a economia brasileira no período de 2000 até 2013

Abstract

Resumo: Neste artigo são desenvolvidas estimativas da Taxa de Desemprego Não Aceleradora da Inflação (NAIRU) para a economia brasileira. Esta é estimada com dados trimestrais de 2000 ao segundo trimestre de 2013 da taxa de desemprego aberta no período de referência de 30 dias do DIEESE e da taxa de inflação pelo Índice Nacional de Preços ao Consumidor (INPC). A metodologia empregada condiz com uma equação de transferência. Os principais resultados dizem respeito à mudança do coeficiente de correlação entre a taxa de inflação e a taxa de desemprego, que passou de negativo para positivo e a permanência da taxa NAIRU acima da taxa de desemprego no período em questão.

Unemployment rate and wage growth in Brazil: evidence from a Markov-switching model

“…In relation to the NAIRU rate, as in Oliveira et al (2016), the estimation was performed through the transfer equation, because it is an unobserved component. Thus, the estimated NAIRU proved to be consistent with economic theory, which was evidenced by the result of the estimation of a simple equation relating the unemployment deviation from the natural rate and the current inflation.…”

“…The series used as proxy for the national unemployment rate was obtained from the Ipeadata's virtual platform. The natural unemployment rate (NAIRU) was estimated from the data (procedure explained in detail in subsection 4.3), using the transfer equation, as well as Portugal & Madalozzo (2000) and Oliveira et al (2016). The data set is expressed in a quarterly basis covering the period between 2000Q1 and 2016Q4.…”

“…The non-accelerating inflation rate of unemployment follows, as methodological approach, an autorregressive transfer equation, according to Enders (2008), because it is a non-observable variable. The articles of Portugal & Madalozzo (2000) and Oliveira et al (2016) also used this approach to estimate Brazil's NAIRU for different analysis period.…”

“…To overcome this problem, we chose to use Hoddrick-Prescott filter 7 , obtaining then, a stable unemployment data series. Finally, the expected inflation series for t + 1 was calculated, as well as in Portugal & Madalozzo (2000) and Oliveira et al (2016), by means of a ARMA model prediction. In this sense, the most accurate prediction model was an AR(2).…”