We assess the performance of widely-used dynamic panel data estimators based on Monte Carlo simulations of a dynamic economic process. Knowing the true underlying coefficient of the autoregressive term, we show that most estimators exhibit a severe bias even in the absence of measurement errors,...

We present several fast algorithms for computing the distribution of a sum of spatially dependent, discrete random variables to aggregate catastrophe risk. The algorithms are based on direct and hierarchical copula trees. Computing speed comes from the fact that loss aggregation at branching...

In this paper, we consider Kumaraswamy-G distributions and derive a Uniformly Minimum Variance Unbiased Estimator (UMVUE) and a Maximum Likelihood Estimator (MLE) of the two measures of reliability, namely R(t) = P(X t) and P = P(X Y ) under Type II censoring scheme and sampling scheme of...

In this paper, we investigate the dynamics of age-cohort survival curves under the assumption that the instantaneous mortality intensity is driven by an affine jump-diffusion (AJD) process. Advantages of an AJD specification of mortality dynamics include the availability of closed-form...

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so....

A common practice in estimating parameters in DSGE models is to nd a set that when simulated gets close to an average of certain data moments; the model s simulated performance for other moments is then compared to the data for these as an informal test of the model. We call this procedure...

We study a nonlinear two-way fixed effects panel model that allows for unobserved individual heterogeneity in slopes (interacting with covariates) and (unknown) flexibly specified link function. The former is particularly relevant when the researcher is interested in the distributional causal...