Measuring a Roller Coaster

Abstract

The output gap-which measures the deviation of actual output from its potential-is frequently used as an indicator of slack in an economy. This paper estimates the Finnish output gap using various empirical methods. It evaluates these methods against economic history and each other by a simulated out-of-sample forecasting exercise for Finnish CPI inflation. Only two gap measures, stemming from a frequency domain approach and the Blanchard-Quah decomposition, perform better than the naïve prediction of no change in inflation-but do not improve upon a simple autoregressive forecast. The pronounced volatility of output in Finland makes it particularly difficult to estimate potential output, producing considerable uncertainty about the size (and sign) of the gap.Production;Economic forecasting;unemployment, unemployment rate, forecasting, statistics, rate of unemployment, natural rate of unemployment, time series, cointegration, statistical measures, equation, arithmetic, sample bias, linear trend, correlation, nairu, autocorrelation, correlations, descriptive statistics, employment, mean square, financial statistics, standard deviations, statistical methods, statistic, econometrics, prediction, parameter value, functional form, high unemployment, full-employment, time ? series, number of regressors, rising unemployment, official unemployment rate, sensitivity analysis, estimation period, sample sizes, total labor force, vector autoregression, full employment, estimation procedure, computation, time series analysis, standard deviation, polynomial, finite sample, cyclical unemployment, orthogonality, estimation technique, empirical methods