Two-sided Bayesian and frequentist tolerance intervals: general asymptotic results with applications

It is well known that that the construction of two-sided tolerance intervals is far more challenging than that of their one-sided counterparts. In a general framework of parametric models, we derive asymptotic results leading to explicit formulae for two-sided Bayesian and frequentist tolerance intervals. In the process, probability matching priors for such intervals are characterized and their role in finding frequentist tolerance intervals via a Bayesian route is indicated. Furthermore, in situations where matching priors are hard to obtain, we develop purely frequentist tolerance intervals as well. The findings are applied to real data. Simulation studies are seen to lend support to the asymptotic results in finite samples.     

FISCAL FEDERALISM,DECENTRALIZATION, AND ECONOMIC GROWTH: A META‐ANALYSIS

The theoretical literature on fiscal federalism has identified several channels through which government decentralization could affect economic growth. Much of the literature focuses on the efficiency aspects of a decentralized provision of public services, but decentralization may also increase growth by raising the ability of the political system to innovate and carry out reforms. In contrast, some authors argue that decentralization increases corruption and government inefficiency, and thus may diminish growth. Given this theoretical ambiguity, several studies have attempted to identify the effect of decentralization on economic growth empirically over the last two decades. We review and conduct a meta‐analysis of this empirical literature. Based on our analysis, we point out open questions and discuss possible ways to answer them. (JEL H77, O43, C52)