Papers by Pawel Skrzypczynski
DSGE models have recently become one of the most frequently used tools in policy analysis. Nevert... more DSGE models have recently become one of the most frequently used tools in policy analysis. Nevertheless, their forecasting proprieties are still unexplored. In this article we address this problem by examining the quality of forecasts from a small size DSGE model, a trivariate VAR model and the Philadelphia Fed Survey of Professional Forecasters. The forecast performance of these methods is
SSRN Electronic Journal, 2000
DSGE models have recently become one of the most frequently used tools in policy analysis. Nevert... more DSGE models have recently become one of the most frequently used tools in policy analysis. Nevertheless, their forecasting proprieties are still unexplored. In this article we address this problem by examining the quality of forecasts from a small size DSGE model, a trivariate VAR model and the Philadelphia Fed Survey of Professional Forecasters. The forecast performance of these methods is analysed for the key U.S. economic variables: the three month Treasury bill yield, the GDP growth rate and the GDP price index inflation. We evaluate the ex post forecast errors on the basis of the data from the period of 1994–2006. We apply the Philadelphia Fed “Real-Time Data Set for Macroeconomists,” described by Croushore and Stark (2001a), to ensure that the information available to the SPF was exactly the same as the data used to estimate the DSGE and VAR models. Overall, the results are mixed. It appears that when comparing the root mean squared errors for some forecast horizons the DSGE model seems to outperform the SPF in forecasting the GDP growth rate. However, this characteristic turned out to be not statistically significant. In principle most forecasts of the GDP price index inflation and the short term interest rate by the SPF are significantly better than those from the DSGE model. The forecast quality of the VAR model turned out to be the worst one.
SSRN Electronic Journal, 2000
The literature on exchange rate forecasting is vast. Many researchers have tested whether implica... more The literature on exchange rate forecasting is vast. Many researchers have tested whether implications of theoretical economic models or the use of advanced econometric techniques can help explain future movements in exchange rates. The results of the empirical studies for major world currencies show that forecasts from a naive random walk tend to be comparable or even better than forecasts from more sophisticated models. In the case of the Polish zloty, the discussion in the literature on exchange rate forecasting is scarce. This article fills this gap by testing whether non-linear time series models are able to generate forecasts for the nominal exchange rate of the Polish zloty that are more accurate than forecasts from a random walk. Our results confirm the main findings from the literature, namely that it is difficult to outperform a naive random walk in exchange rate forecasting contest.
SSRN Electronic Journal, 2000
In this study, we use the tools of cross-spectral analysis and structural vector autoregression (... more In this study, we use the tools of cross-spectral analysis and structural vector autoregression (SVAR) modelling to investigate whether there exists a significant link between the movement of the cyclical component of real GDP in developed and emerging economies. Specifically, we look at the United States and six emerging countries: Brazil, Chile, Korea, Malaysia, Mexico and Singapore. The simple answer to the question posed in the title of our article is no. Our results indicate that there exists no significant relationship between cyclical fluctuations in the US and emerging countries at business cycle frequencies. Although a statistically and economically significant link is detected in the past decade (the 2000s), it seems that it reflects mostly the severity of the 2008-2009 recession and its effects reverberating throughout the globe rather than a structural convergence between the developed and emerging world which could be expected to persist into the future. In general, both spectral methods and SVAR models suggest that over a long horizon, GDP cycles in the US and the emerging countries are not related.
SSRN Electronic Journal, 2000
Journal of Money, Credit and Banking, 2012
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Papers by Pawel Skrzypczynski