The implicit theory of historical change in the work of Alan S. Milward

Alan S. Milward was an economic historian who developed an implicit theory ofhistorical change. His interpretation which was neither liberal nor Marxist positedthat social, political, and economic change, for it to be sustainable, had to be agradual process rather than one resulting from a sudden, cataclysmicrevolutionary event occurring in one sector of the economy or society. Benignchange depended much less on natural resource endowment or technologicaldevelopments than on the ability of state institutions to respond to changingpolitical demands from within each society. State bureaucracies were fundamentalto formulating those political demands and advising politicians of ways to meetthem. Since each society was different there was no single model of developmentto be adopted or which could be imposed successfully by one nation-state onothers, either through force or through foreign aid programs. Nor coulddevelopment be promoted simply by copying the model of a more successfuleconomy. Each nation-state had to find its own response to the political demandsarising from within its society. Integration occurred when a number of nation states shared similar political objectives which they could not meet individuallybut could meet collectively. It was not simply the result of their increasinginterdependence. It was how and whether nation-states responded to thesedomestic demands which determined the nature of historical change.

Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set

We evaluate conditional predictive densities for U.S. output growth and inflationusing a number of commonly used forecasting models that rely on a large number ofmacroeconomic predictors. More specifically, we evaluate how well conditional predictive densities based on the commonly used normality assumption fit actual realizationsout-of-sample. Our focus on predictive densities acknowledges the possibility that, although some predictors can improve or deteriorate point forecasts, they might have theopposite effect on higher moments. We find that normality is rejected for most modelsin some dimension according to at least one of the tests we use. Interestingly, however,combinations of predictive densities appear to be correctly approximated by a normaldensity: the simple, equal average when predicting output growth and Bayesian modelaverage when predicting inflation.