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) |
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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 |
Keywords
- Econometrics
- Maximum likelihood estimation
- Stochastic optimization methods
ASJC Scopus subject areas
- Computer Science Applications
- Management Science and Operations Research
- Control and Optimization
- Applied Mathematics