We study a financial market adverse selection model where all agents are endowed with initial wealth and choose to invest as entrepreneurs or financiers, or not to invest. We show that often a lack of outside finance leads to the emergence of financial markets where availability of outside...

The Venture capital (VC) industry in India is of recent origin. However, the average investment value of each deal in India have grown from $3.85 million in 2000 to $7.89 million in 2001.These developments together with the recent steps taken by government to promote venture capitalism in India...

This article investigates which firms borrow directly from the capital markets and which raise funds through intermediaries. Our empirical results show that large companies with abundant cash and collateral tap the credit markets directly. These markets cater to safe and profitable industries,...

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...

In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, "diffuse'' priors on model-specific parameters can lead to quite unexpected...

Many production processes yield both good outputs and undesirable ones (e.g. pollutants). In this paper, we develop a generalization of a stochastic frontier model which is appropriate for such technologies. We discuss efficiency analysis and, in particular, define technical and environmental...

We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is very spread among many models suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results...

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...

I use numerical methods to test for the presence of one-time structural breaks in the conditional variance of nominal interest rate spreads in four European countries over a period of eleven years (Jan 1988 to Dec 1998). I start with an intuitive approach consisting of a sequence of breakpoint...

If each member of a group assigns a certain probability to a hypothesis, what probability should the collective as a whole assign? More generally, how should individual probability functions be merged into a single collective one? I investigate this question in case that the individual...