The last column of Table 9 attempts to address the strong dependence of the returns by cross-sectional de-meaning of the data prior to estimation, instead of adding common factors in the regression specification. This can be viewed as equivalent to a factor model imposing the implicit restriction that the loadings be constant across countries. The parameter estimates on the fundamental variables show some changes relative to Table 3 – particularly in the case of the real interest rate in the advanced-country sample, whose coefficient declines by half. In addition, the spatial effects appear overstated, especially in the full sample, and the huge t-statistic on the spatial lag hints at misspecification.

# **5 Conclusion**

Equity returns display strong international comovement, especially across advanced countries. Existing empirical literature has modeled it as reflecting either localized real and/or financial linkages across countries, or pervasive common shocks – i.e., weak and strong cross-sectional dependence, respectively. In this paper we have brought both perspectives together by assessing the comovement of equity returns in a setting that allows for both spatial dependence and latent common factors, using quarterly equity price data over the years 1995 to 2016 for 40 advanced and emerging countries.

In the paper’s framework, real equity returns are driven by three observable variables proxying for growth of the present value of anticipated dividends: the growth rates of GDP and real credit, and the change in the real interest rate. These variables are augmented with latent common factors and spatial effects accruing through equity prices themselves.

We estimate the model using a bias-corrected quasi-maximum likelihood procedure recently developed by Shi and Lee (2017), alternatively considering all 40 sample countries, or a subsample of 25 advanced economies. To capture the interactions among countries, we employ alternative spatial weight matrices based on bilateral trade, bilateral FDI stocks, and geographic distance. To determine the number of latent common factors driving equity returns, we use a variety of information criteria. On the whole, they indicate the presence of a single factor for both country samples considered.

Estimation results reveal that, in accordance with prior expectations, real equity returns are significantly positively related to real GDP growth, and negatively related to changes in the real interest rate. In the advanced-country subsample, real credit growth has no significant effect on equity returns. However, in the full sample, which includes countries with less-developed financial markets, credit growth carries a positive and strongly significant coefficient. In addition, equity returns display significant inertia in both samples.

The results show little variation across the three alternative specifications of the spatial weight matrix. They also provide strong evidence of spatial effects. The contemporaneous spatial lag coefficient is consistently positive and significant, while the spatial-time lag carries a negative coefficient that is significant in most specifications. The significant spatial effects imply that local interactions are important to understand the international comovement of equity returns.

In turn, the estimated common factor is strongly positively correlated with real 28