This paper studies the welfare consequences of a government regulation that forces a patented equipment to be supplied by a number of independent producers. On the one hand, such a regulation hurts the value of a patent and therefore reduces activities in the R&D sector. On the other hand, the...

Empirically R&D expenditure moves pro-cyclically, but the pro- cyclicality is a puzzle from the Schumpeterian point of view. The paper examines the cyclical property of R&D expenditure in the context of endogenous growth, and concludes that (i) substitutability between investing in physical...

This paper revisits the question if the user cost of capital plays an important role for investment decisions using Bayesian estimation techniques. These methods offer advantages over classical econometric tools in this area: The most important are that prior distributions offer a convincing way...

A two-block open economy model is estimated in this paper using Australian and U.S. data. Evaluation of the estimated model is carried out in relation to a simple closed economy alternative. Namely, we inspect the implied transmission mechanisms, and examine the relative out-of-sample...

This paper estimates a DSGE model with learning to re-examine the evidence on time variation in post-war U.S. monetary policy. Several papers document a regime switch, by showing that policy changed from `passive' and destabilizing in the pre-1979 period to `active' and stabilizing in the...

The elasticity of intertemporal substitution (EIS) at the macro level has been estimated mostly based on endowment economy models and these estimates are very sensitive to the choice of interest rates that are used for estimation. Estimates based on production economy models do not need...

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

In this paper we consider bayesian semiparametric regression within the generalized linear model framework. Specifically, we study a class of autoregressive time series where the time trend is incorporated in a nonparametrically way. Estimation and inference where performed through Markov Chain...

Various noninformative prior distributions have been suggested for scale parameters in hierarchical models. We construct a new folded-noncentral- t family of conditionally conjugate priors for hierarchical standard deviation parameters, and then consider noninformative and weakly informative...

This paper extends the analogy previously established by Leamer (1978a), between a Bayesian inference problem and an economics allocation problem, and shows that posterior modes can be interpreted as optimal outcomes of a bargaining game. This bargaining game, over a parameter value, is played...