Research projects

Project CEMAPRE internal

TitleBayesian Validation of Behavioural Parameters in Economic Models
ParticipantsRui Paulo (Principal Investigator), João F.D. Rodrigues
SummaryModels for assessing the impact of economic policies often require the specification of two types of
parameters: structural parameters, which can be calibrated using data from a baseline year, and
behavioural parameters, which require econometric estimation and/or assumptions which are not
amenable to direct testing. In this paper we address the problem of validating behavioural
parameters given a set of empirical observations that can be compared with the model predictions.
Our starting point is Bayesian model selection, which allows for assessing the change in a
practitioner's belief in different models given observations. We depart from the classical formulae
because a behavioural parameter is defined within a model and the practitioner has different models
at his/her disposal. We therefore introduce an explicit probability that an empirical observation
falls within the scope of a particular model. The Bayesian validation method developed here is
applied to the selection of technology assumptions in supply-use models, which disambiguate how an
industry uses a given input in the production recipe of multiple outputs, using the WIOD database as
a case study.