Abstract
Estimating the values of the parameter estimates of econometric functions (maximum likelihood functions or nonlinear least squares functions) are often challenging global optimization problems. Determining the global optimum for these functions is necessary to understand economic behavior and to develop effective economic policies. These functions often have flat surfaces or surfaces characterized by many local optima. Classical deterministic optimization methods often do not yield successful results. For that reason, stochastic optimization methods are becoming widely used in econometrics. Selected stochastic methods are applied to two difficult econometric functions to determine if they might be useful in estimating the parameters of these functions.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 273-295 |
| Number of pages | 23 |
| Journal | Journal of Global Optimization |
| Volume | 20 |
| Issue number | 3-4 |
| DOIs | |
| State | Published - Aug 2001 |
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Keywords
- Econometrics
- Maximum likelihood estimation
- Stochastic optimization methods
ASJC Scopus subject areas
- Management Science and Operations Research
- Global and Planetary Change
- Applied Mathematics
- Control and Optimization
Cite this
Global Optimization of Econometric Functions. / Jerrell, Max E.; Campione, Wendy A.
In: Journal of Global Optimization, Vol. 20, No. 3-4, 08.2001, p. 273-295.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Global Optimization of Econometric Functions
AU - Jerrell, Max E.
AU - Campione, Wendy A
PY - 2001/8
Y1 - 2001/8
N2 - Estimating the values of the parameter estimates of econometric functions (maximum likelihood functions or nonlinear least squares functions) are often challenging global optimization problems. Determining the global optimum for these functions is necessary to understand economic behavior and to develop effective economic policies. These functions often have flat surfaces or surfaces characterized by many local optima. Classical deterministic optimization methods often do not yield successful results. For that reason, stochastic optimization methods are becoming widely used in econometrics. Selected stochastic methods are applied to two difficult econometric functions to determine if they might be useful in estimating the parameters of these functions.
AB - Estimating the values of the parameter estimates of econometric functions (maximum likelihood functions or nonlinear least squares functions) are often challenging global optimization problems. Determining the global optimum for these functions is necessary to understand economic behavior and to develop effective economic policies. These functions often have flat surfaces or surfaces characterized by many local optima. Classical deterministic optimization methods often do not yield successful results. For that reason, stochastic optimization methods are becoming widely used in econometrics. Selected stochastic methods are applied to two difficult econometric functions to determine if they might be useful in estimating the parameters of these functions.
KW - Econometrics
KW - Maximum likelihood estimation
KW - Stochastic optimization methods
UR - http://www.scopus.com/inward/record.url?scp=0035415864&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0035415864&partnerID=8YFLogxK
U2 - 10.1023/A:1017902001734
DO - 10.1023/A:1017902001734
M3 - Article
AN - SCOPUS:0035415864
VL - 20
SP - 273
EP - 295
JO - Journal of Global Optimization
JF - Journal of Global Optimization
SN - 0925-5001
IS - 3-4
ER -