Estimating complex production functions: The importance of starting values
| dc.creator | Neal, Mark | |
| dc.date | 2017-04-01T20:21:00Z | |
| dc.date.accessioned | 2026-07-09T07:12:12Z | |
| dc.description | Production functions that take into account uncertainty can be empirically estimated by taking a state contingent view of the world. Where there is no a priori information to allocate data amongst a small number of states, the estimation may be carried out with finite mixtures model. The complexity of the estimation almost guarantees a large number of local maxima for the likelihood function. However, it is shown, with examples, that a variation on the traditional method of finding starting values substantially improves the estimation results. One of the major benefits of the proposed method is the reliable estimation of a decision maker's ability to substitute output between states, justifying a preference for the state contingent approach over the use of a stochastic production function. | |
| dc.identifier | doi:10.22004/ag.econ.151178 | |
| dc.identifier | https://ageconsearch.umn.edu/record/151178/files/WPR07_1.pdf | |
| dc.identifier | http://ageconsearch.umn.edu/record/151178 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/585670 | |
| dc.language | eng | |
| dc.publisher | ||
| dc.source | http://ageconsearch.umn.edu/record/151178 | |
| dc.title | Estimating complex production functions: The importance of starting values | |
| dc.type | Text |