Several empirical studies are concerned with measuring the effect of currency and current
account crises on economic growth. Using different empirical models this paper serves two
aspects. It provides an explicit assessment of country specific factors influencing the costs of
crises in terms of economic growth and controls via a treatment type model for possible sample
selection governing the occurrence of crises in order to estimate the impact on economic
growth correctly. The applied empirical models allow for rich intertemporal dependencies
via serially correlated errors and capture latent country specific heterogeneity via random
coefficients. For accurate estimation of the treatment type model a simulated maximum
likelihood approach employing efficient importance sampling is used. The results reveal significant
costs in terms of economic growth for both crises. Costs for reversals are linked
to country specific variables, while costs for currency crises are not. Furthermore, shocks
explaining current account reversals and growth show strong significant positive correlation.
This article explores the influence of competitive conditions on the
evolutionary fitness of different risk preferences. As a practical example, the
professional competition between fund managers is considered. To explore how
different settings of competition parameters, the exclusion rate and the exclusion
interval, affect individual investment behavior, an evolutionary model based on a
genetic algorithm is developed. The simulation experiments indicate that the
influence of competitve conditions on investment behavior and attitudes towards risk
is significant. What is alarming is that intense competitive pressure generates riskseeking
behavior and undermines the predominance of the most skilled.
A growing body of literature reports evidence of social interaction effects in survey expectations. In this note, we argue that evidence in favor of social interaction effects should be treated with caution, or could even be spurious. Utilizing a parsimonious stochastic model of expectation formation and dy- namics, we show that the existing sample sizes of survey expectations are about two orders of magnitude too small to reasonably distinguish between noise and interaction effects. Moreover, we argue that the problem is com- pounded by the fact that highly correlated responses among agents might not be caused by interaction effects at all, but instead by model-consistent beliefs. Ultimately, these results suggest that existing survey data cannot facilitate our understanding of the process of expectations formation.
We develop a simple behavioral macro model to study interactions between the real
economy and the stock market. The real economy is represented by a Keynesian goods
market approach while the setup for the stock market includes heterogeneous speculators.
Using a mixture of analytical and numerical tools we find, for instance, that speculators may
create endogenous boom-bust dynamics in the stock market which, by spilling over into the
real economy, can cause lasting fluctuations in economic activity. However, fluctuations in
economic activity may, by shaping the firms’ fundamental values, also have an impact on
the dynamics of the stock market.