The Role of the Financial Market Variables in Forecasting Macrovariables in Finland: Does the Financial Crisis Make a Difference? (original) (raw)
Related papers
The role of stock markets vs. the term spread in forecasting macrovariables in Finland
The Quarterly Review of Economics and Finance, 2011
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.
Review of Financial Economics, 2014
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.
Bank of Finland staff forecasts: an evaluation
2018
Monetary policy decisions are based on assessment of the current and future state of the Monetary policy decisions are based on assessment of the current and future state of the economy. In order to obtain forecasts, central banks build models, which are simplified economy. In order to obtain forecasts, central banks build models, which are simplified representations of the complex interactions among macroeconomic variables. The Bank representations of the complex interactions among macroeconomic variables. The Bank of Finland regularly publishes its forecasts, using a large set of data regarding current of Finland regularly publishes its forecasts, using a large set of data regarding current economic developments. Analysis of this large set of data includes the use of formal economic developments. Analysis of this large set of data includes the use of formal macroeconomic models, which are also employed to make projections for the future macroeconomic models, which are also employed to make projections for the future course of the economy. These projections represent the most likely values for the main course of the economy. These projections represent the most likely values for the main macroeconomic variables of the Finnish economy. macroeconomic variables of the Finnish economy. This article documents the performance of Bank of Finland forecasts for GDP, inflation, unemployment and the components of GDP over the years 2004-2017. This period has been particularly challenging for forecasting. The financial crisis originating in the United States in 2007 spread globally. As a consequence Finland, as well as many other countries, experienced a severe contraction in output and a slow recovery. New policy measures were implemented in response to the crisis, and their effects on the economy were highly uncertain and difficult to anticipate. Macroeconomic models and their ability to predict developments in the economy were called into question, as the models used for forecasting by Central Banks failed to predict Bofbulletin.fi-Bank of Finland articles on the economy
Financial variables and economic activity in the Nordic countries
International Review of Economics & Finance, 2015
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.
Assessing the Forecasting Performance of a Macroeconomic Model
Journal of Policy Modeling, 1999
This paper contains a description of a small quarterly forecasting model for the Finnish economy. We evaluate the forecasting properties of the model by means of stochastic simulation involving both the endogenous and exogenous variables of the model. The simulations allow us to identify and quantify the main sources of forecasting uncertainty. We are also able to assess the linearity of the model. Forecasting performance is also analyzed in a conventional way by means of dynamic simulation. The important issue in these simulations is the stability of the model: how simulated values depend on the estimation period and the ordering of time periods.
Do financial variables help forecasting inflation and real activity in the euro area?
Journal of Monetary Economics, 2003
The paper uses a large data set, made up by 447 monthly macroeconomic time series concerning the main countries of the Euro area to simulate out-of-sample predictions of the Euro area industrial production and the harmonized inflation indexes and to evaluate the role of financial variables in forecasting. We considered two models which allows forecasting based on large panels of time series: Forni, Hallin, Lippi and Reichlin (2001b) and . Performance of both models were compared to that of a simple univariate AR model. Results show that, in general, multivariate methods outperform univariate methods and that financial variables help forecasting inflation, but do not help forecasting industrial production. We also show that Forni et al.'s method outperforms SW's. JEL subject classification : C13, C33, C43.
Structural breaks, ARIMA model and Finnish inflation forecasts
International Journal of Forecasting, 2001
Via the use of the rolling regression technique and a specific procedure for analysing strong structural breaks in a univariate time series model, we forecast the rate of future inflation in Finland for the time period of unregulated financial markets since the beginning of 1987. The identified structural changes in the data generating process (DGP) of inflation are labelled with both economic events and changes in the main leading inflation indicators. The final intervention model yields, in some cases, better forecasts than the pure rolling regression technique without identification of the strong breaks. When comparing the obtained forecasts with certain noncontinuous time series based on inflation expectation surveys with respect to actual future inflation, we find that the comparable point forecasts from our rolling regressions perform better than the corresponding point expectation proxies from questionnaires. When compared with the performance of the forecasts by the Research Institute of the Finnish Economy, the recursive procedure also produces more accurate forecasts.
Special Issue on Economic Forecasts: Guest Editorial
Jahrbucher Fur Nationalokonomie Und Statistik, 2011
Forecasts guide decisions in all areas of economics and finance. Economic policy makers base their decisions on business cycle forecasts, investment decisions of firms are based on demand forecasts, and portfolio managers try to outperform the market based on financial market forecasts. Forecasts extract relevant information from the past and help to reduce the inherent uncertainty of the future. The recent years have witnessed a large increase in the use and publication of forecasts in different fields of economics and finance. The general progress in information and communication technology has increased the availability and ease of use of data and econometrical software packages, and the methodological progress has provided us with sophisticated forecasting procedures. The topic of this special issue of the Journal of Economics and Statistics is the theory and practise of forecasting and forecast evaluation. The purpose is to provide an overview of the state of the art of forecasting; a specific focus is on business cycle forecasts and forecasting in finance. The papers included in this volume deal with both methodological issues and empirical applications.
The BOF5 macroeconomic model of Finland : Structure and equations
1998
This report is the basic documentation of the present (fifth) version of the Bank of Finland macroeconomic model, BOF5, built for policy simulation and forecasting.In constructing the model, consistent treatment of expectations is emphasized.Following current theoretical literature, intertemporal optimization with rational expectations is taken as the starting point, and Euler equations are applied in the estimation of the key behavioural equations.Consistent treatment of technology on the supply side has been another important aim.We illustrate the properties of the model with some simulation experiments.A complete list of equations and an outline of the derivation of the key equations are presented.We also show how forward-looking equations have been transformed to facilitate simulation under alternative assumptions concerning the formation of expectations. Keywords: macroeconomic models, Finland, econometric modelling, policy simulations, expectations, Euler equations