This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm’s prior information is characterized by a Dirichlet process prior....

The standard growth accounting framework, which weights various inputs by their factor shares to measure their contributions to output growth, is known to underestimate the contribution of inputs in the presence of externalities and increasing returns. This paper develops a model in which, in...

Most macroeconomic models assume that aggregate output is generated by a specification for the production function with total physical capital as a key input. Implicitly this assumes that private and public capital stocks are perfect substitutes. In this paper we test this assumption by...

The knowledge production function is central to R&D-based growth models. This paper empirically investigates the knowledge production function and intertemporal spillover effects using cointegration techniques. Time-series evidence suggests there are two long-run cointegrating relationships. The...

This study seeks to explain economic growth differences in an aggregate production function framework, where labor reallocation from agriculture to modern sectors influences labor efficiency growth. The econometric analysis uses a panel of 65 countries over 1960-90. The results highlight: (a)...

Lucas (2004) asserts that ""Of the tendencies that are harmful to sound economics, the most seductive, and in my opinion the most poisonous, is to focus on questions of distribution. The potential for improving the lives of poor people by finding different ways of distributing current production...

We analyze the causes of the apparent bias towards optimism in growth forecasts underpinning the design of IMF-supported programs, which has been documented in the literature. We find that financial variables observable to forecasters are strong predictors of growth forecast errors. The greater...