Results 91 to 100 of about 47,776 (252)
Monte Carlo-Based Tail Exponent Estimator
In this paper we study the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small ...
Jozef Barunik, Lukas Vacha
core
Bias Adjustment for Mean Squared Error Estimation in M‐Quantile Models for Small Area Estimation
International Statistical Review, EarlyView.Summary M‐quantile (MQ) regression provides a robust and flexible alternative to mixed models for small area estimation. However, several theoretical aspects remain underexplored. In this paper, a parametric bootstrap method is proposed to approximate the distributions of area‐specific MQ coefficients and applied to adjust the bias in the mean squared ...
María Bugallo +3 more
wiley +1 more source
Driving Markov Chain Monte Carlo with a Dependent Random Stream
, 2012 Summary. Markov chain Monte Carlo is a widely-used technique for generating a dependent sequence of samples from complex distributions. Conventionally, these methods require a source of independent random variates.
Lloyd T. Elliott, Iain Murray
core
Goodness‐of‐Fit Tests for Positive Quadrant Dependence
International Statistical Review, EarlyView.Summary When two random variables are positive quadrant dependent (PQD), they are more likely to assume small (or large) values simultaneously compared with when the random variables are independent. This dependence structure is of interest in many areas, including finance, actuarial science and engineering.
Chuan‐Fa Tang, Joshua M. Tebbs
wiley +1 more source
Expert Asymmetry: Evidence From Securities Litigation
Journal of Empirical Legal Studies, EarlyView.ABSTRACT Modern litigation often involves two separate, extra‐legal features: (1) contingency fee arrangements with the plaintiff‐side attorney, and (2) a “battle of the experts” where the outcome of the case rests on conflicting expert witness testimony.
Adam Callister +2 more
wiley +1 more source
Generation of Random Numbers and Parallel Random Number Streams for Monte Carlo Simulations
, 2015 Modern methods and libraries for high quality pseudorandom number generation and for generation of parallel random number streams for Monte Carlo simulations are considered.
L. N. Shchur, L. Yu. Barash
core +1 more source
Mixing It Up: Inflation at Risk
Journal of Money, Credit and Banking, EarlyView.Abstract Understanding how risk factors shape the economic outlook is essential for guiding policy decisions. This paper develops a flexible framework that decomposes distributional risk forecasts of macro‐economic variables into underlying contributions and supports the construction of interpretable risk measures.
MAXIMILIAN SCHRÖDER
wiley +1 more source
Stochastic simulation: a package for Monte Carlo experiments on econometric models
The stochastic simulation of an econometric model is an application of Monte Carlo methods. Deterministic simulation is performed setting error terms to zero.
Corsi, Paolo +2 more
core
Revisiting the Health Spending‐Growth Nexus
Journal of Economic Surveys, EarlyView.ABSTRACT The relationship between health spending and economic growth is shaped by multiple transmission channels, leading to inconsistencies in the empirical literature and a lack of definitive conclusions. To address this issue, we perform a meta‐analysis encompassing 522 estimates from 107 studies that examine the effect of health spending on ...
Andreas Sintos +2 more
wiley +1 more source
Serial Correlation in the Generation of Pseudo-Random Numbers
JACM, 1960 R. R. Coveyou
semanticscholar +1 more source