Stochastic simulation
Some guidelines and guarantees for common random numbers
Management Science
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Should Macroeconomic Policy Makers Consider Parameter Covariances?
Computational Economics
Time Series Simulation with Quasi Monte Carlo Methods
Computational Economics
On Stochastic Simulation of Forward-Looking Models
Computational Economics
Assessing the Quality of Pseudo-Random Number Generators
Computational Economics
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Common random numbers (CRN) is a general variance reducing technique for comparing stochastic models via simulations. By inducing positive correlation between different simulations, CRN are likely to reduce the experimental or sampling variance of the difference between the simulations. However, in this paper my motivation for and interpretations of CRN go beyond the statistical design of a simulation experiment, and into the core of economic and econometric reasoning. In a counterfactual-, scenario- or policy analysis based on stochastic simulation, CRN implement the qualifier in partial analysis known as the ceteris paribus clause. In addition, CRN are consistent with the requirement of super exogeneity for valid policy analysis.