Measuring Business Cycle and Inflation Forecast: The Case of Pakistan

Abstract

The output gap and inflation forecast are important factors to analyze current state of the economy and stance of monetary policy. In this study we have measured business cycle through estimating output gap using different methods namely the Linear Time Trend (LTT) method, Quadratic Time Trend (QTT) method, Hodrick-Prescott (HP filter), Band Pass Baxter-King Filter (BP), Double Exponential Smoothing Method (DES), Structural Vector Autoregressive (SVAR) method and Production Function (PF) method. For the analysis we have used annual data over the period 1960 to 2014 for Pakistan. Moreover, the inflation is forecasted with univariate and multivariate models. The results suggest that Quadratic Time Trend (QTT) method and Structural Vector Autoregression (SVAR) captures the history of Pakistan economy well. Whereas, output gap estimated through SVAR generate better inflation forecast compared to other methods.

Keywords: output gap, inflation forecast, univariate, multivariate, business cycle

JEL CLASSIFICATION: C22, C53, E32