Estimating the production function for the Brazilian industrial sector: A Bayesian panel VAR approach

Artikel

The scope of this paper is to estimate the production function for the Brazilian industrial sector from a longitudinal panel of the industrial sector (Annual Industrial Survey produced by the Institute of Geography and Statistics-PIA/IBGE-and the Ministry of Labour and Employment's Annual Relation of Social Information-RAIS/MTE-ranging from 1996 until 2005) through a Bayesian Vector Autoregressive (BVAR) approach. This new method adds to the empirical industrial organization another way to estimate the demand, avoiding cumbersome calculations. It gives the possibility of analysing not only the dynamic relationships among the variables but also the shocks through the impulse response function (IRF). Additionally, it gives the opportunity to analyse the industry sector's productivity by minimizing the problem of endogeneity and therefore it also sheds some light on the trend of this variable throughout the period abovementioned.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Cogent Business & Management ; ISSN: 2331-1975 ; Volume: 9 ; Year: 2022 ; Issue: 1 ; Pages: 1-16

Klassifikation und Themen

• Klassifikation: Management ; Bayesian Analysis: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models ; Production, Pricing, and Market Structure; Size Distribution of Firms
• Thema: Bayesian panel vector autoregressive ; production function ; productivity

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Filho, Roberto Ivo Da Rocha Lima
• Ereignis: Veröffentlichung
• (wer): Taylor & Francis
• (wo): Abingdon
• (wann): 2022

Weitere Informationen

• DOI: doi:10.1080/23311975.2022.2025752
• Letzte Aktualisierung: 10.03.2025, 11:41 MEZ