an economic model of adultery

Doug Henwood dhenwood at panix.com
Sat Aug 4 10:32:00 PDT 2001


"Simple 3-step Censored Quantile Regression and Extramarital

Affairs"

BY: VICTOR CHERNOZHUKOV

Massachusetts Institute of Technology (MIT)

Department of Economics

HAN HONG

Princeton University

Department of Economics

Document: Available from the SSRN Electronic Paper Collection:

http://papers.ssrn.com/paper.taf?abstract_id=272499

Paper ID: MIT Dept. of Economics Working Paper No. 01-20

Date: March 2001

Contact: VICTOR CHERNOZHUKOV

Email: Mailto:vchern at mit.edu

Postal: Massachusetts Institute of Technology (MIT)

Department of Economics

50 Memorial Drive

Cambridge, MA 02142 USA

Phone: 617-253-4767

Fax: 617-253-1330

Co-Auth: HAN HONG

Email: Mailto:doubleh at princeton.edu

Postal: Princeton University

Department of Economics

202-26 Prospect Avenue

Princeton, NJ 08544 USA

Paper Requests:

Contact: Linda Woodbury, MIT Department of Economics, E52-251;

50 Memorial Drive; Cambridge, MA 02142. Phone:(617)253-8885.

Fax:(617)253-1330. Mailto:lwoodbur at mit.edu Individual working

papers $7 (domestic including Canada and Mexico) and $10

international.

ABSTRACT:

This paper suggests simple 3- and 4-step estimators for censored

quantile regression models with an envelope or a separation

restriction on the censoring probability. The estimators are

theoretically attractive (asymptotically as efficient as the

celebrated Powell's censored least absolute deviation

estimator). At the same time, they are conceptually simple and

have trivial computational expenses. They are especially useful

in samples of small size or models with many regressors, with

desirable finite sample properties and small bias. The envelope

restriction costs a small reduction of generality relative to

the canonical censored regression quantile model, yet its main

plausible features remain intact. The estimator can also be used

to estimate a large class of traditional models, including

normal Amemiya-Tobin model and many accelerated failure and

proportional hazard models. The main empirical example involves

a very large data-set on extramarital affairs, with high 68%

censoring. We estimate 45%-90% conditional quantiles. Effects of

covariates are not representable as location-shifts. Less

religious women, with fewer children, and higher status, tend to

engage into the matters relatively more than their opposites,

especially at the extremes. Marriage longevity effect is

positive at moderately high quantiles and negative at high

quantiles. Education and marriage happiness effects are

negative, especially at the extremes. We also briefly consider

the survival quantile regression on the Stanford heart

transplant data. We estimate the age and prior surgery effects

across survival quantiles.

Keywords: Quantile regression, median regression, censoring,

duration, survival, classification, discriminant analysis

JEL Classification: C14, C24, C41, C51, D13



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