FEEM working papers "Note di lavoro" series
2005 .047

Modeling Factor Demands with SEM and VAR: An Empirical Comparison


Autori: Matteo Manera
Serie: Energy: Resources and Markets
Editor: Carlo Carraro
Tipo: Journal
Parole chiave: Simultaneous equation models,Vector autoregression models,Factor demands,Dynamic duality
Numero JEL: C30,C52,D92
JEL: Journal of Productivity Analysis
Pagine: Vol. 26, No.2, pp. 121-146
Data: 10/2006

Abstract

The empirical analysis of the economic interactions between factors of production, output and corresponding prices has received much attention over the last two decades. Most contributions in this area have agreed on the neoclassical principle of a representative optimizing firm and typically use theory-based structural equation models (SEM). A popular alternative to SEM is given by the vector autoregression (VAR) methodology. The most recent attempts to link the SEM approach with VAR analysis in the area of factor demands concentrate on single-equation models, whereas no effort has been devoted to compare these alternative approaches when a firm is assumed to face a multi-factor technology and to decide simultaneously the optimal quantity for each input. This paper bridges this gap. First, we illustrate how the SEM and the VAR approaches can both represent valid alternatives to model systems of dynamic factor demands. Second, we show how to apply both methodologies to estimate dynamic factor demands derived from a cost-minimizing capital-labour-energy-materials (KLEM) technology with adjustment costs (ADC) on the quasi-fixed capital factor. Third, we explain how to use both models to calculate some widely accepted indicators of the production structure of an economic sector, such as price and quantity elasticities, and alternative measures of ADC. In particular, we propose and discuss some theoretical and empirical justifications of the differences between observed elasticities, measures of ADC, and the assumption of exogeneity of output and/or input prices. Finally, we offer some suggestions for the applied researcher.

Download file
Scarica il file PDF

FEEM Newsletter

Iscriviti per rimanere aggiornato.

I Suoi dati saranno trattati dalla Fondazione Eni Enrico Mattei. – Titolare del trattamento – per ricevere via posta elettronica la newsletter della Fondazione. Il conferimento dell’indirizzo e-mail è necessario alla fornitura del servizio. La invitiamo a consultare la Privacy Policy per ottenere maggiori informazioni a tutela dei Suoi diritti.

Questo Sito utilizza cookie tecnici e analytics, nonché consente l’invio di cookie di profilazione di terze parti.
Chiudendo questo banner o comunque proseguendo la navigazione sul Sito manifesti il tuo consenso all’uso dei cookie. Per ulteriori informazioni e per esprimere scelte selettive in ordine all’uso dei cookie vedi la   Cookie PolicyOk