Abstract:
This paper investigates whether the post-tax and transfer growth rate in the Gini index can help in forecasting the equity premium in the G7 countries (Canada, France, Germany, Italy, Japan, United Kingdom (UK), and United States (US)). To this end, we use a panel data-based predictive framework, which controls for heterogeneity, cross-sectional dependence, persistence and endogeneity. When we analyze the annual out-of-sample period of 1990–2011, given an in-sample period of 1967–1989, our results show that: (a) Time series based predictive regression models fail to beat the benchmark of historical average, except for Italy; and, (b) the panel data models beat the benchmark in a statistically significant fashion for all the seven countries. Further, our results highlight the importance of pooling information when trying to forecast excess stock returns based on a measure of inequality.
