The Changing Determinants of Economic Performance in the World Economy
Chapter 22: Summary of statistical results
The empirical research on economic growth and competitiveness tends to suffer from a lack of comparable data across many countries and years. One way to overcome this ‘small-n problem’ is to use pooled cross-sectional data which ranges both across space and time (Hicks 1994). Technically the pooled cross-sectional approach combines data on j countries and t years to produce a data set of j * t = n observations. Neither longitudinal single country studies nor cross-sectional one period studies could reach similar degrees of freedom, equally precise statistical estimates or as powerful statistical tests. In principle our benchmarking tables could offer such pooled cross-sectional data for 22 countries and 4 time periods, a total of 88 ‘nation-years’. However, due to missing observations for some indicators, we could not reach the maximum degrees of freedom in any of our statistical regressions. We used our database to study three different time periods: 1980s and 1990s together (max. n = 77), and the 1980s (max. n = 38) and 1990s (max. n = 39) separately. Splitting the database into two periods, the 1980s and 1990s, allowed us to study the changes in the relative importance of different competitiveness factors during the current paradigm shift. Moreover, by comparing the regression fits of the ‘two-decade’ and ‘single-decade’ models, we could test whether the paradigm shift had affected the structural relationships among the dependent and independent variables. Much weaker regression fits with the full data set would indicate that the regression procedure is averaging out two periods with very different underlying...
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