Statistical Inference in Micro Simulation Models: Incorporating external information
In practical applications of micro simulation models very little is usually known about the properties of the simulated values. This paper argues that we need to apply the same rigorous standards for inference in micro simulation work as in scientific work generally. If not, then micro simulation models will loose in credibility. The paper first discusses how the structure of the model will determine inference and then follow sections on estimation and validation. Differences between inference in static and dynamic models are noted and then the paper focuses on the estimation of behavioral parameters. There are three themes: calibration viewed as estimation subject to external constraints, piece meal vs. system-wide estimation, and simulation based estimation.
|Date of creation:||01 Oct 1998|
|Date of revision:|
|Publication status:||Published in Mathematics and Computers in Simulation, 2002, pages 255-265.|
|Contact details of provider:|| Postal: Department of Economics, Uppsala University, P. O. Box 513, SE-751 20 Uppsala, Sweden|
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- Klevmarken, N.A., 1998.
"Statistical Inference in Micro Simulation Models: Incorporationg External Information,"
1998:20, Uppsala - Working Paper Series.
- Anders Klevmarken, N., 2002. "Statistical inference in micro-simulation models: incorporating external information," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(1), pages 255-265.
- Klevmarken, N. Anders, 1998. "Statistical Inference in Micro Simulation Models: Incorporating external information," Working Paper Series 1998:20, Uppsala University, Department of Economics.
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