. A recent strand of empirical work uses (S; s) models with time-varying stochastic bands to describe infrequent adjustments of prices and other variables. The present paper examines some properties of this model, which encompasses most micro-founded adjustment rules rationalizing infrequent...

The main contribution of this study is to develop a dynamic general equilibrium model linking financial markets to the real economy. In search of a unified framework, this study finds that a model with internal habit memory is able to generate asset pricing and business cycle predictions that...

We show that adjustment cost models with labor supply can explain both asset returns and business cycle facts when adjustment costs penalize the changes of investment. This conclusion stands in contrast to results obtained in the literature with adjustment costs that penalize the changes of capital.

In this paper, we report on the theoretical foundations, empirical context and technical implementation of an agent-based modeling (ABM) framework, that uses a high-performance computing (HPC) approach to investigate human population dynamics on a global scale, and on evolutionary time scales....

Parallel computation has a long history in econometric computing, but is not at all wide spread. We believe that a major impediment is the labour cost of coding for parallel architectures. Moreover, programs for specific hardware often become obsolete quite quickly. Our approach is to take a...

Parallel computation has a long history in econometric computing, but is not at all wide spread. We believe that a major impediment is the labour cost of coding for parallel architectures. Moreover, programs for specific hardware often become obsolete quite quickly. Our approach is to take a...

This paper reviews the need for powerful computing facilities in econometrics, focusing on concrete problems which arise in financial economics and in macroeconomics. We argue that the profession is being held back by the lack of easy to use generic software which is able to exploit the...

Atmospheric air quality modeling relies in part on numerical simulation. Required numerical simulations are often hampered by lack of computer capacity and computational speed. This problem is most severe in the field of global modeling where transport and exchange of trace constituents are...

Today’s high-performance computing environments, and the applications that must exploit them, have become much more complex than ever. We now build ensembles of large, shared-memory parallel computers, linked together with high-speed networks, in an attempt to achieve previously unheard-of...

We introduce a combined two-stage least-squares (2SLS)-expectation maximization (EM) algorithm for estimating vector-valued autoregressive conditional heteroskedasticity models with standardized errors generated by Gaussian mixtures. The procedure incorporates the identification of the...