Differences Between Classical and Bayesian Estimates for Mixed Logit Models: A Replication Study

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Differences Between Classical and Bayesian Estimates for Mixed Logit Models: A Replication Study. / Elshiewy, Ossama; Zenetti, German; Boztug, Yasemin.
in: Journal of Applied Econometrics, Jahrgang 32, Nr. 2, 01.03.2017, S. 470-476.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Elshiewy O, Zenetti G, Boztug Y. Differences Between Classical and Bayesian Estimates for Mixed Logit Models: A Replication Study. Journal of Applied Econometrics. 2017 Mär 1;32(2):470-476. doi: 10.1002/jae.2513

Bibtex

@article{85a34cb59c46450e91620a7c9ebae795,
title = "Differences Between Classical and Bayesian Estimates for Mixed Logit Models: A Replication Study",
abstract = "The mixed logit model is widely used in applied econometrics. Researchers typically rely on the free choice between the classical and Bayesian estimation approach. However, empirical evidence of the similarity of their parameter estimates is sparse. The presumed similarity is mainly based on one empirical study that analyzes a single dataset (Huber J, Train KE. 2001. On the similarity of classical and Bayesian estimates of individual mean partworths. Marketing Letters12(3): 259–269). Our replication study offers a generalization of their results by comparing classical and Bayesian parameter estimates from six additional datasets and specifically for panel versus cross-sectional data. In general, our results suggest that the two methods provide similar results, with less similarity for cross-sectional data than for panel data.",
keywords = "Management studies",
author = "Ossama Elshiewy and German Zenetti and Yasemin Boztug",
year = "2017",
month = mar,
day = "1",
doi = "10.1002/jae.2513",
language = "English",
volume = "32",
pages = "470--476",
journal = "Journal of Applied Econometrics",
issn = "0883-7252",
publisher = "John Wiley & Sons Ltd.",
number = "2",

}

RIS

TY - JOUR

T1 - Differences Between Classical and Bayesian Estimates for Mixed Logit Models

T2 - A Replication Study

AU - Elshiewy, Ossama

AU - Zenetti, German

AU - Boztug, Yasemin

PY - 2017/3/1

Y1 - 2017/3/1

N2 - The mixed logit model is widely used in applied econometrics. Researchers typically rely on the free choice between the classical and Bayesian estimation approach. However, empirical evidence of the similarity of their parameter estimates is sparse. The presumed similarity is mainly based on one empirical study that analyzes a single dataset (Huber J, Train KE. 2001. On the similarity of classical and Bayesian estimates of individual mean partworths. Marketing Letters12(3): 259–269). Our replication study offers a generalization of their results by comparing classical and Bayesian parameter estimates from six additional datasets and specifically for panel versus cross-sectional data. In general, our results suggest that the two methods provide similar results, with less similarity for cross-sectional data than for panel data.

AB - The mixed logit model is widely used in applied econometrics. Researchers typically rely on the free choice between the classical and Bayesian estimation approach. However, empirical evidence of the similarity of their parameter estimates is sparse. The presumed similarity is mainly based on one empirical study that analyzes a single dataset (Huber J, Train KE. 2001. On the similarity of classical and Bayesian estimates of individual mean partworths. Marketing Letters12(3): 259–269). Our replication study offers a generalization of their results by comparing classical and Bayesian parameter estimates from six additional datasets and specifically for panel versus cross-sectional data. In general, our results suggest that the two methods provide similar results, with less similarity for cross-sectional data than for panel data.

KW - Management studies

UR - http://www.scopus.com/inward/record.url?scp=84995691228&partnerID=8YFLogxK

U2 - 10.1002/jae.2513

DO - 10.1002/jae.2513

M3 - Journal articles

AN - SCOPUS:84995691228

VL - 32

SP - 470

EP - 476

JO - Journal of Applied Econometrics

JF - Journal of Applied Econometrics

SN - 0883-7252

IS - 2

ER -

DOI