A Bayesian model averaging procedure is presented that makes use of a finite mixture of many model structures within the class of vector autoregressive (VAR) processes. It is applied to two empirical issues. First, stability of the Great Ratios in U.S. macro-economic time series is investigated,...

The empirical support for a real business cycle model with two technology shocks is evaluated using a Bayesian model averaging procedure. This procedure makes use of a finite mixture of many models within the class of

This paper assesses the role of sovereign risk in explaining macroeconomic fluctuations in Turkey. We estimate two versions of a simple New Keynesian small open economy model on quarterly data for the period 1994Q3-2008Q2: A basic version and a version augmented by a default premium on...

A recent literature has emerged providing compelling evidence that a major shift in the organization of the developed economies has been taking place: away from what has been characterized as the <I>managed economy</I> towards the <I>entrepreneurial economy</I>. In particular, the empirical evidence provides...</i></i>

Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership....

In practice structural equations are often estimated by least-squares, thus neglecting any simultaneity. This paper reveals why this may often be justifiable and when. Assuming data stationarity and existence of the first four moments of the disturbances we find the limiting distribution of the...

We show that the Anderson-Rubin (AR) statistic is the sum of two independent piv- otal statistics. One statistic is a score statistic that tests location and the other statistic tests misspecification. The chi-squared distribution of the location statistic has a degrees of freedom parameter that...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

The linear Gaussian state space model for which the common variance is treated as a stochastic time-varying variable is considered for the modelling of economic time series. The focus of this paper is on the simultaneous estimation of parameters related to the stochastic processes of the mean...