### Abstract

This paper examines the numerical properties of the nested fixed point 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 Dubé, Fox, and Su (2012).

Original language | English |
---|---|

Pages (from-to) | 1-21 |

Number of pages | 21 |

Journal | Journal of Economic Theory and Econometrics |

Volume | 28 |

Issue number | 4 |

Publication status | Published - 2017 Dec 1 |

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### Keywords

- Nested fixedpoint algorithm
- Newton’s method
- Numerical methods
- Random coefficients logit demand

### ASJC Scopus subject areas

- Economics and Econometrics

### Cite this

*Journal of Economic Theory and Econometrics*,

*28*(4), 1-21.

**Testing the nested fixed-point algorithm in BLP random coefficients demand estimation.** / Lee, Jinhyuk; Seo, Kyoungwon.

Research output: Contribution to journal › Article

*Journal of Economic Theory and Econometrics*, vol. 28, no. 4, pp. 1-21.

}

TY - JOUR

T1 - Testing the nested fixed-point algorithm in BLP random coefficients demand estimation

AU - Lee, Jinhyuk

AU - Seo, Kyoungwon

PY - 2017/12/1

Y1 - 2017/12/1

N2 - This paper examines the numerical properties of the nested fixed point 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 Dubé, Fox, and Su (2012).

AB - This paper examines the numerical properties of the nested fixed point 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 Dubé, Fox, and Su (2012).

KW - Nested fixedpoint algorithm

KW - Newton’s method

KW - Numerical methods

KW - Random coefficients logit demand

UR - http://www.scopus.com/inward/record.url?scp=85039857942&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85039857942&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:85039857942

VL - 28

SP - 1

EP - 21

JO - Journal of Economic Theory and Econometrics

JF - Journal of Economic Theory and Econometrics

SN - 1229-2893

IS - 4

ER -