The multivariate heterogeneous preference estimator for switching Multiple Price List data

Conte, Anna, Moffatt, Peter G. and Riddell, Mary (2024) The multivariate heterogeneous preference estimator for switching Multiple Price List data. Experimental Economics. ISSN 1386-4157 (In Press)

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Abstract

The Multiple Price List (MPL) and Switching Multiple Price List (sMPL) provide a useful framework for estimating preference parameters, most usually risk aversion, from a sample of experimental subjects or survey respondents. In this paper, we consider designs in which more than one sMPL is presented to each subject, allowing more than one preference parameter to be estimated simultanously, and we propose a consistent estimator in this setting – the Multivariate Heterogeneous Preference (MHP) estimator. Focusing on the bivariate case of two sMPL’s and two preference parameters, we demonstrate that non-standard econometric techniques, namely Monte Carlo integration with importance sampling, are required to implement the MHP estimator. Via a Monte Carlo exercise, we show that our estimator has good finite-sample properties. Finally, we apply the MHP estimator to a real data set and compare the estimates to those obtained using an inconsistent estimator applied in previous studies.

Item Type:	Article
Uncontrolled Keywords:	risk preference,monte carlo simulations,importance sampling,economics, econometrics and finance(all),3* ,/dk/atira/pure/subjectarea/asjc/2000
Faculty \ School:	Faculty of Social Sciences > School of Economics
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Centres > Norwich Institute for Healthy Aging Faculty of Social Sciences > Research Groups > Behavioural Economics Faculty of Social Sciences > Research Groups > Applied Econometrics And Finance Faculty of Social Sciences > Research Centres > Centre for Behavioural and Experimental Social Sciences
Depositing User:	LivePure Connector
Date Deposited:	27 Nov 2024 10:46
Last Modified:	27 Nov 2024 10:46
URI:	https://ueaeprints.uea.ac.uk/id/eprint/97773
DOI:	issn:1386-4157

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