The current study aimed to determine the best method for estimating latent variable interactions as a function of the size of the interaction effect, sample size, the loadings of the indicators, the size of the relation between the first-order latent variables, and normality. Data were simulated...

Comparative risk projects can provide broad policy guidance but they rarely have adequate scientific foundations to support precise risk rankings. Many extant projects report rankings anyway, with limited attention to uncertainty. Stochastic uncertainty, structural uncertainty, and ignorance are...

Incluye bibliografía ; For reasons of empirical tractability, analysis of cointegrated economic time series is often developed in a partial setting, in which a subset of variables is explictly modeled conditional on the rest. This approach yields valid inference only if the conditioning...

In this paper we solve the benchmark heterogeneous agents model by Aiyagari (1994) using Monte Carlo methods. In addition, the idiosyncratic shocks process is approximated using Tauchen's (1986) method. This we go beyond the 2 by 2 Markov matrix approximation of the AR(1) stochastic process. The...

Gravity type models are widely used in international economics. In these models the inclusion of time-fi0xed regressors like geographical or cultural distance, language and institutional (dummy) variables is often of vital importance e.g. to analyse the impact of trade costs on...

Using a novel methodology, we offer new evidence that a threshold relationship exists for Okun's law. We use a logistic smoothed transition regression (LSTR) model where possible threshold endogeneity is addressed based on copula theory. We also suggest a new test of the linearity hypothesis...

Operational risk management remains a major concern for financial institutions. Indeed, institutions are bound to manage their own funds to hedge this risk. In this paper, we propose an approach to allocate one's own funds based on a combination of historical data and expert opinion using the...

We explore the Monte Carlo steps required to reduce the sampling error of the estimated 99.9% quantile within an acceptable threshold. Our research is of primary interest to practitioners working in the area of operational risk measurement, where the annual loss distribution cannot be...

In the past two decades increasing computational power resulted in the development of more advanced claims reserving techniques, allowing the stochastic branch to overcome the deterministic methods, resulting in forecasts of enhanced quality. Hence, not only point estimates, but predictive...

Innovation risk in banks, a formalized instrument that is part of banks' financial and innovative strategies, influences the assessment of innovative activity, demonstrating the importance of forecasting and assessment models of potential innovation risks. Our research into general scientific...