Statistical inference in micro-simulation models: incorporating external information
In practical applications of micro-simulation models (MSMs), 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 MSMs will l...
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| Published in | Mathematics and computers in simulation Vol. 59; no. 1; pp. 255 - 265 |
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| Main Author | |
| Format | Journal Article Conference Proceeding |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
10.05.2002
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0378-4754 1872-7166 |
| DOI | 10.1016/S0378-4754(01)00413-X |
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| Abstract | In practical applications of micro-simulation models (MSMs), 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 MSMs will loose in credibility. Differences between inference in static and dynamic models are noted and then the paper focuses on the estimation of behavioral parameters. There are four themes: calibration viewed as estimation subject to external constraints, piece meal versus system-wide estimation, simulation-based estimation and validation. |
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| AbstractList | In practical applications of micro-simulation models (MSMs), 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 MSMs will loose in credibility. Differences between inference in static and dynamic models are noted and then the paper focuses on the estimation of behavioral parameters. There are four themes: calibration viewed as estimation subject to external constraints, piece meal versus system-wide estimation, simulation-based estimation and validation. |
| Author | Anders Klevmarken, N. |
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| Cites_doi | 10.1093/0198774753.001.0001 10.2307/2290268 |
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| Keywords | Validation Alignment Constrained estimation Simulation estimation Micro-simulation Parameter estimation Computer simulation Estimation Behavioral model Inference Statistical estimation Dynamical system Simulation Simulation model Dynamic model Microsimulation model |
| Language | English |
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| References | S. Caldwell, Micro/macro-simulation of socioeconomic population processes, Paper presented at the IBM Computing Conference, Dallas, June 20, 1988. Deville, Särndal (BIB5) 1992; 87 C. Gouriéroux, A. Monfort, Simulation-Based Econometric Methods, Oxford University Press, Oxford, 1996. S. Caldwell, Health, wealth, pensions and life paths: the CORSIM dynamic microsimulation model, in: A. Harding (Ed.), Microsimulation and Public Policy, North-Holland, Amsterdam, 1996 (Chapter 22). C.F. Citro, E.A. Hanushek (Eds.), Assessing Policies for Retirement Income. Needs for Data, Research, and Models, National Research Council, National Academy Press, Washington, DC, 1997. S. Lundström, Calibration as a standard method for treatment of nonresponse, Department of Statistics, Stockholm University (diss.), 1997. N.A. Klevmarken, Statistical inference in micro-simulation models: incorporating external information, Working Paper, Vol. 20, Department of Economics, Uppsala University, 1998. S. Pudney, H. Sutherland, Statistical reliability in microsimulation models with econometrically-estimated behavioral responses, in: A. Harding (Ed.), Microsimulation and Public Policy, North-Holland, Elsevier, Amsterdam, 1996 (Chapter 21). S. Caldwell, Content, validation and uses of CORSIM 2.0, a dynamic microanalytic model of the United States paper presented at the IARIW Conference on Micro-simulation and Public Policy, Canberra, Australia, 1993. J. Merz, Microdata adjustment using the minimum information loss principle, Discussion Paper No. 10, Forschungsinstitut Freie Berufe, Universität Luneburg, 1994. J. Merz, ADJUST—A program package for adjustment of micro data by minimum information loss principle. Program Manual, FFB-Documentation No. 1, University of Luneburg, 1993. N.A. Klevmarken, Behavioral modeling in micro-simulation models. A survey. Working Paper, Vol. 31, Department of Economics, Uppsala University, 1997. K. Lindström, Utvärdering av framskrivnings-tekniken i FASIT-modellen (Evaluation of the calibration technique used in the FASIT model), Memo Statistics, Sweden, 1997. 10.1016/S0378-4754(01)00413-X_BIB1 10.1016/S0378-4754(01)00413-X_BIB2 10.1016/S0378-4754(01)00413-X_BIB3 10.1016/S0378-4754(01)00413-X_BIB4 10.1016/S0378-4754(01)00413-X_BIB6 Deville (10.1016/S0378-4754(01)00413-X_BIB5) 1992; 87 10.1016/S0378-4754(01)00413-X_BIB7 10.1016/S0378-4754(01)00413-X_BIB8 10.1016/S0378-4754(01)00413-X_BIB9 10.1016/S0378-4754(01)00413-X_BIB12 10.1016/S0378-4754(01)00413-X_BIB13 10.1016/S0378-4754(01)00413-X_BIB10 10.1016/S0378-4754(01)00413-X_BIB11 |
| References_xml | – reference: S. Caldwell, Health, wealth, pensions and life paths: the CORSIM dynamic microsimulation model, in: A. Harding (Ed.), Microsimulation and Public Policy, North-Holland, Amsterdam, 1996 (Chapter 22). – reference: S. Caldwell, Micro/macro-simulation of socioeconomic population processes, Paper presented at the IBM Computing Conference, Dallas, June 20, 1988. – reference: C. Gouriéroux, A. Monfort, Simulation-Based Econometric Methods, Oxford University Press, Oxford, 1996. – reference: C.F. Citro, E.A. Hanushek (Eds.), Assessing Policies for Retirement Income. Needs for Data, Research, and Models, National Research Council, National Academy Press, Washington, DC, 1997. – reference: S. Lundström, Calibration as a standard method for treatment of nonresponse, Department of Statistics, Stockholm University (diss.), 1997. – reference: J. Merz, ADJUST—A program package for adjustment of micro data by minimum information loss principle. Program Manual, FFB-Documentation No. 1, University of Luneburg, 1993. – reference: N.A. Klevmarken, Behavioral modeling in micro-simulation models. A survey. Working Paper, Vol. 31, Department of Economics, Uppsala University, 1997. – reference: S. Caldwell, Content, validation and uses of CORSIM 2.0, a dynamic microanalytic model of the United States paper presented at the IARIW Conference on Micro-simulation and Public Policy, Canberra, Australia, 1993. – volume: 87 start-page: 376 year: 1992 end-page: 382 ident: BIB5 article-title: Calibration estimators in survey sampling publication-title: J. Am. Stat. Assoc. – reference: J. Merz, Microdata adjustment using the minimum information loss principle, Discussion Paper No. 10, Forschungsinstitut Freie Berufe, Universität Luneburg, 1994. – reference: K. Lindström, Utvärdering av framskrivnings-tekniken i FASIT-modellen (Evaluation of the calibration technique used in the FASIT model), Memo Statistics, Sweden, 1997. – reference: N.A. Klevmarken, Statistical inference in micro-simulation models: incorporating external information, Working Paper, Vol. 20, Department of Economics, Uppsala University, 1998. – reference: S. Pudney, H. Sutherland, Statistical reliability in microsimulation models with econometrically-estimated behavioral responses, in: A. Harding (Ed.), Microsimulation and Public Policy, North-Holland, Elsevier, Amsterdam, 1996 (Chapter 21). – ident: 10.1016/S0378-4754(01)00413-X_BIB6 doi: 10.1093/0198774753.001.0001 – ident: 10.1016/S0378-4754(01)00413-X_BIB10 – ident: 10.1016/S0378-4754(01)00413-X_BIB11 – ident: 10.1016/S0378-4754(01)00413-X_BIB12 – ident: 10.1016/S0378-4754(01)00413-X_BIB9 – ident: 10.1016/S0378-4754(01)00413-X_BIB7 – ident: 10.1016/S0378-4754(01)00413-X_BIB8 – volume: 87 start-page: 376 year: 1992 ident: 10.1016/S0378-4754(01)00413-X_BIB5 article-title: Calibration estimators in survey sampling publication-title: J. Am. Stat. Assoc. doi: 10.2307/2290268 – ident: 10.1016/S0378-4754(01)00413-X_BIB4 – ident: 10.1016/S0378-4754(01)00413-X_BIB3 – ident: 10.1016/S0378-4754(01)00413-X_BIB1 – ident: 10.1016/S0378-4754(01)00413-X_BIB2 – ident: 10.1016/S0378-4754(01)00413-X_BIB13 |
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| SubjectTerms | Alignment Applied sciences Computer science; control theory; systems Constrained estimation Control system analysis Control theory. Systems Exact sciences and technology Micro-simulation Simulation estimation Validation |
| Title | Statistical inference in micro-simulation models: incorporating external information |
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