학술저널
Testing the Nested Fixed-Point Algorithm in BLP Random Coefficients Demand Estimation
- 한국계량경제학회
- JOURNAL OF ECONOMIC THEORY AND ECONOMETRICS
- Vol.28 No.4
-
2017.121 - 21 (21 pages)
- 27
This paper examines the numerical properties of the nested fixedpoint algorithm (NFP) using Monte Carlo experiments in the estimation of Berry, Levinsohn, and Pakes’s (1995) random coefficient logit demand model. We find that in speed, convergence and accuracy, nested fixed-point (NFP) approach using Newton’s method performs well like a mathematical programming with equilibrium constraints (MPEC) approach adopted by Dub´e, Fox, and Su (2012).
1. INTRODUCTION
2. MODEL AND ESTIMATION
3. MONTE CARLO SIMULATION
4. CONCLUSION
A. APPENDIX: ADDITIONAL TECHNIQUES FOR NEWTON’S METHOD
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