Assessing Time-Series Versus Cross-Sectional Influences in Panel Estimates: International Financial Architecture and Expected Equity Premia

In the study of economic and financial panel data it is often important to differentiate between time-series and cross-sectional effects. We present two estimation procedures that can do so and illustrate their application by examining international variations in expected equity premia and financial architecture where a number of variables vary across time but not cross-sectionally while other variables vary cross-sectionally but not across time. Using two different estimation procedures we find a preference for market financing to be negatively associated with the size of expected premia. However, we also find that U.S. corporate bond spreads negatively determine financial architecture according to the first procedure but not according to the second estimation as U.S. Corporate bond spreads change value each year but have the same value across countries. Similarly some measures that change across countries but do not change across time, such as cultural dimensions as well as the an index of measures against self dealing, are significant determinants of financial architecture according second estimation but not according to the first estimation. Our results show that using these two estimation procedures together can assess time-series versus cross-sectional variations in panel data. This research should be of considerable interest to empirical researchers.