Kuosmanen, Petri 1 , Nasib Nabulsi 2 & Juuso Vataja (2014). Financial Variables and Economic Activity in the Nordic Countries. University of Vaasa, Department of Economics, Working Papers 23, 29 p. The recent financial crisis has re-highlighted the importance of clarifying the predictive association between financial markets and the real economy. The previous literature suggests that the predictive ability of financial variables for economic growth appears to be largely coincidental for the main industrial countries. This study focuses on similar small open economies in the Nordic context. More specifically, we study the predictive content of stock returns, short-term interest rates and the term spread by using linear models and non-linear regime switching models for forecasting GDP growth in Denmark, Finland, Norway and Sweden. We apply the threshold autoregressive (TAR) model-switching approach and the novel regime-switching signals which combine the inversion of the yield curve and the recession as the signal to switch between economic states. The predictive ability of the observable and known switching approach is compared to the latent switch under the Markov switching approach. The results suggest that the TAR model approach with an inversion-recession signal is preferable for predicting economic activity in all four of the Nordic countries. However, the predictive ability of financial variables may differ between neighboring countries, although the Nordic countries are similar in terms of economic development and financial institutions. Moreover, the link between the financial sector and GDP growth may not depend straightforwardly on monetary regimes. Among the Nordic countries, the predictive relationship between financial variables and economic activity is found to be the strongest in Finland and Sweden.
Recently introduced measures for Economic Policy Uncertainty (EPU) included in the data from 1997 -2016 have a role in forecasting out-of-sample values for the future real economic activity for both the euro area and the UK economies. The inclusion of EPU measures, either for the US, the UK or for overall European economies, improves the forecasting ability of models based on standard financial market information, especially for the period before the 2008 global crisis. However, during and after the crisis period, the slope of the yield curve and excess stock market returns improves the out-of-sample forecast performance the most compared to an AR-benchmark model. Hence, the EPU information is important in times of normal business cycles, but it might contain similar information components to the financial market return variables, during turbulent crisis periods in the financial markets and in the real economy.
This paper examines the ability of financial variables to predict future economic growth above and beyond past economic activity in a small open economy in the euro area. We aim to clarify potential differences in forecasting economic activity during different economic circumstances. Our results from Finland suggest that the proper choice of forecasting variables is related to general economic conditions. During steady economic growth, the preferred choice for a financial indicator is the short‐term interest rate combined with past values of output growth. However, during economic turbulence, the traditional term spread and stock returns are more important in forecasting GDP growth. The time‐varying predictive content of the financial variables may be utilized by applying regime‐switching nonlinear forecasting models. We propose a novel application using the negative term spread and observed recession as signals to switch between regimes. This procedure yields a significant improvement in forecasting performance at the one‐year forecast horizon.
1. INTRODUCTION 2. STYLIZED FACTS AND EMPIRICAL REGULARITIES 2.1. Yield curve, real economy and inflation 2.2. Stock market, real economy and inflation 3. DATA 3.1. Variables 3.2. Research period 4. EMPIRICAL RESULTS 4.1. Estimation models 4.2. Preliminary analysis of the data 4.3. Estimation and out-of-sample forecasting results 4.4. Analysis of the results 5. CONCLUSIONS REFERENCES APPENDIX ABSTRACT Kuosmanen, Petri * & Juuso Vataja * (2008). The Role Stock Markets vs. the Term Spread in Forecasting Macrovariables in Finland. University of Vaasa, Department of Economics Working Papers 10, 31 p.Money talks, but can it foresee economic future? A rule of thumb suggests that stock markets react a half a year before changes occur in macrovariables. On the other hand, it was discovered in the late 1980s that the steepness of the yield curve is a very useful tool for predicting macroeconomy. There exist a substantial body of stylized facts and empirical evidence about relations between yield curve, stock market and macroeconomy regarding the U.S. economy. However, the question whether this holds true for small open economies is less known. This paper focuses on forecasting content of stock markets versus the yield curve regarding GDP, private consumption, industrial production and inflation rate in Finland. In addition to stock market returns, market volatility is explicitly addressed in this study, the issue that has been largely overlooked in previous literature. Thus, both the return and risk aspects of the stock markets are covered. The sample period is 1987-2006.The out-of-sample forecasting results suggest that the yield curve is a much better tool for predicting macroeconomy than the stock market variables. Only in the case of inflation the stock market variables appear to contain some additional information about the term spread and the best inflation forecasts are obtained by combining the information from the term spread and the stock market variables. The stock market volatility has not been found to contain any additional forecasting information about the stock returns. Overall, the empirical results confirm that the forecasting ability of the yield curve holds true also in small open economy like Finland.
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