Can specific policy indicators identify reform priorities?

Several detailed cross-country datasets measuring specific policy indicators relevant to business regulation and government integrity have been developed in recent years. The promise of these indicators is that they can be used to identify specific reforms that policymakers and aid donors can target in their efforts to improve the regulatory and institutional environment. Doing so, however, requires evidence on the partial effects of the many specific policy choices reflected in such datasets. In this paper we use Bayesian model averaging (BMA) to document the cross-country partial correlations between detailed policy indicators and several measures of regulatory and institutional outcomes. We find major instability in the set of policy indicators identified by BMA as important partial correlates of similar outcomes: specific policy indicators that matter for one outcome are, on average, not important correlates of other closely-related outcomes. This finding illustrates the difficulties in using highly-specific policy indicators to identify reform priorities using cross-country data. Copyright Springer Science+Business Media New York 2013