۱- Introduction

۲- Empirical model and data

۳- Empirical results

۴- Factor model

۵- Conclusion

References

Abstract

We study the forecasting power of financial variables for macroeconomic variables in 62 countries between 1980 and 2013. We find that financial variables such as credit growth, stock prices, and house prices have considerable predictive power for macroeconomic variables at the one- to four-quarter horizons. A forecasting model that includes financial variables outperforms the World Economic Outlook (WEO) forecasts in up to 85% of our sample countries at the four-quarter horizon. We also find that cross-country panel models produce more accurate out-of-sample forecasts than individual country models.

Introduction

The crisis of 2007−۲۰۰۹ caused widespread disruptions in the financial market, followed by a global economic downturn. These developments have led to an intense debate on macrofinancial linkages. The present paper contributes to this debate in the context of macroeconomic forecasts. Building our analysis on the extensive body of literature on forecasting, we examine the forecasting power of financial variables for macroeconomic variables in 62 countries between 1980 and 2013. We show that incorporating financial variables such as credit growth, stock prices, house prices, and bond yields in an otherwise simple model improves the accuracy of macroeconomic forecasts significantly. Our rationale for using financial variables to forecast macroeconomic variables is threefold. First, in the presence of financial market imperfections when the Modigliani-Miller theorem does not hold, changes in credit conditions are likely to result in changes in future macroeconomic conditions. In addition, by affecting the wealth of firms and households, changes in asset prices also affect their investment and consumption decisions. Second, the forward-looking nature of financial variables means that they incorporate information about the future of the economy that is not yet reflected in current macroeconomic outcomes. Finally, contemporaneous financial variables such as stock prices and interest rates can help to nowcast macroeconomic variables in countries where the latter are collected with considerable time lags.