Bayesian monthly index for building activity based on mixed frequencies: the case of Chile
ISSN: 0144-3585
Article publication date: 5 April 2021
Issue publication date: 29 March 2022
Abstract
Purpose
This paper combines the objective information of six mixed-frequency partial-activity indicators with assumptions or beliefs (called priors) regarding the distribution of the parameters that approximate the state of the construction activity cycle. Thus, this paper uses Bayesian inference with Gibbs simulations and the Kalman filter to estimate the parameters of the state-space model, used to design the Imacon.
Design/methodology/approach
Unlike other economic sectors of similar importance in aggregate gross domestic product, such as mining and industry, the construction sector lacked a short-term measure that helps to identify its most recent performance.
Findings
Indeed, because these priors are susceptible to changes, they provide flexibility to the original Imacon model, allowing for the assessment of risk scenarios and adaption to the greater relative volatility that characterizes the sector's activity.
Originality/value
The classic maximum likelihood method of estimating the monthly construction activity index (Imacon) is rigid to the incorporation of new measures of uncertainty, expectations or different volatility (risks) levels in the state of construction activity. In this context, this paper uses Bayesian inference with 10,000 Gibbs simulations and the Kalman filter to estimate the parameters of the state-space model, used to design the Imacon, inspired by the original works of Mariano and Murasawa (2003) and Kim and Nelson (1998). Thus, this paper consists of a natural extension of the classic method used by Tejada (2006) in the estimation of the old Imacon.
Keywords
Acknowledgements
The valuable comments of Javier Lozano are appreciated. Special thanks to Camilo Torres and Orlando Robles for their efficient contribution in the development and updating of the database. The authors thank the editor and an anonymous referee for their helpful comments and suggestions. The programming codes and database used in this work are available from the corresponding author upon request. Contreras–Reyes's research was partially supported by Grant FONDECYT (Chile) No. 11190116.
Citation
Idrovo-Aguirre, B.J. and Contreras-Reyes, J.E. (2022), "Bayesian monthly index for building activity based on mixed frequencies: the case of Chile", Journal of Economic Studies, Vol. 49 No. 3, pp. 541-557. https://doi.org/10.1108/JES-01-2021-0022
Publisher
:Emerald Publishing Limited
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