The performance of Monte Carlo integration methods like importance-sampling or Markov-Chain Monte-Carlo procedures depends greatly on the choice of the importance- or candidate-density. Such a density must typically be "close" to the target density to yield numerically accurate results with...

We deal with bootstrapping tests for detecting conditional heteroskedasticity in the context of standard and nonstandard ARCH models. We develope parametric and nonparametric bootstrap tests based both on the LM statistic and a neural statistic. The neural tests are designed to approximate an...

One of the most critical issues when using neural networks is how to select appropriate network architectures for the problem at hand. Practitioners usually refer to information criteria which might lead to over-parameterized models with heavy consequence on overfitting and poor ex-post forecast...

Recent empirical studies have demonstrated that behaviour of interest rate processes can be better explained if standard diffusion processes are augmented with jumps in the interest rate process. In this paper we examine the performance of both linear and non-linear one factor CKLS model in the...

We study the role of information sources on innovation in a two stage sequential probit model that can be used to analyze survey data in which questions are asked sequentially. Firms can fall into three catagories: (i) they do not innovation; (ii) they introduce a radical innovation on their...

Have interest rates been held “too low†in relation to the natural rate of interest? Economists have lately begun to worry that the cost of capital may have fallen below the worldwide expected return on capital, thereby causing excessive borrowing and allowing financial imbalances to...

This paper considers two models to deal with an outcome variable that contains a large fraction of zeros, such as individual expenditures on health care: a sample-selection model and a two-part model. The sample-selection model uses two possibly correlated processes to determine the outcome: a...

A number of recent papers have concluded that stochastic volatility plays a prominent role in describing the business cycle, particularly for the characterization of monetary policy. The impact of including stochastic volatility in DSGE models remains, however, unexplored. This paper therefore...