The presence of high inflation rates during 80's and first half of 90's
deviates the attention of policy makers to the monthly fluctuations in the
price indexes focusing the economic policy to the stabilization plans.
Therefore since 1994 the brazilian price stabilization have been bringing
on economic literature and economic policy as a central problem the
existence of long run fluctuations in variables like unemployment and
industrial production. The main purpose of this paper is to investigate the
presence of long run fluctuations in two representative series of Rio
Grande do Sul economy: the industrial production Index and the
unemployment rate. The classical methodology consists on detrending
the series and then filter the cyclical component. This procedure has a
disadvantage if the series presents unit roots in the specification of the
true stochastic process that governs the series. An alternative way is to
use the Structural Time Series Models and the Kalman Filter to isolates
the cyclical component. In particular this methodology was adopted in this
paper. Our results suggests the existence of four distinct cycles foa a
period of sixteen years (1982-1998).The presence of high inflation rates during 80's and first half of 90's
deviates the attention of policy makers to the monthly fluctuations in the
price indexes focusing the economic policy to the stabilization plans.
Therefore since 1994 the brazilian price stabilization have been bringing
on economic literature and economic policy as a central problem the
existence of long run fluctuations in variables like unemployment and
industrial production. The main purpose of this paper is to investigate the
presence of long run fluctuations in two representative series of Rio
Grande do Sul economy: the industrial production Index and the
unemployment rate. The classical methodology consists on detrending
the series and then filter the cyclical component. This procedure has a
disadvantage if the series presents unit roots in the specification of the
true stochastic process that governs the series. An alternative way is to
use the Structural Time Series Models and the Kalman Filter to isolates
the cyclical component. In particular this methodology was adopted in this
paper. Our results suggests the existence of four distinct cycles foa a
period of sixteen years (1982-1998)
