Inflation Expectations: Does the Market Beat Professional Forecasts?
Makram El-Shagi
North American Journal of Economics and Finance,
No. 3,
2011
Abstract
The present paper compares expected inflation to (econometric) inflation forecasts based on a number of forecasting techniques from the literature using a panel of ten industrialized countries during the period of 1988 to 2007. To capture expected inflation, we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect.
The extracted unexpected inflation is compared to the forecasting errors of ten
econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which
are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.
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The Financial Crisis from a Forecaster’s Perspective
Katja Drechsel, Rolf Scheufele
Abstract
This paper analyses the recession in 2008/2009 in Germany, which is very different from previous recessions, in particular regarding its cause and magnitude. We show to what extent forecasters and forecasts based on leading indicators fail to detect the timing and the magnitude of the recession. This study shows that large forecast errors for both expert forecasts and forecasts based on leading indicators resulted during this recession which implies that the recession was very difficult to forecast. However, some leading indicators (survey data, risk spreads, stock prices) have indicated an economic downturn and hence, beat univariate time series models. Although the combination of individual forecasts provides an improvement compared to the benchmark model, the combined forecasts are worse than several individual models. A comparison of expert forecasts with the best forecasts based on leading indicators shows only minor deviations. Overall, the range for an improvement of expert forecasts during the crisis compared to indicator forecasts is relatively small.
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Inflation Expectations: Does the Market Beat Professional Forecasts?
Makram El-Shagi
IWH Discussion Papers,
No. 16,
2009
Abstract
The present paper compares expected inflation to (econometric) inflation forecasts
based on a number of forecasting techniques from the literature using a panel of
ten industrialized countries during the period of 1988 to 2007. To capture expected
inflation we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect.
The extracted unexpected inflation is compared to the forecasting errors of ten
econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which
are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.
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A macroeconometric model for the Euro economy
Christian Dreger
IWH Discussion Papers,
No. 181,
2003
Abstract
In this paper a structural macroeconometric model for the Eurozone is presented. In opposite to the multi country modelling approach, the model relies on aggregate data on the supra-national level. Due to nonstationarity, all equations are estimated in an error correction form. The cointegrating relations are derived jointly with the short-run dynamics, avoiding the finite sample bias of the two step Engle Granger procedure. The validity of the aggregated approach is confirmed by out-of-sample forecasts and two simulation exercises. In particular the implications of a lower economic recovery in the US and a shock in the nominal Euro area interest rate are discussed.
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