Econometric modeling of productivity and technical efficiency in the Chilean manufacturing industry

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Abstract

This research presents models for assessing productivity and technical efficiency of the Chilean manufacturing sector by using a factor analysis as a methodological alternative to the standard model of productive factors, generating latent factors or input variables such as those proposed in the literature on the topic. The factor analysis allows us to synthesize the number of inputs available as latent factors, showing satisfactory quite results. Econometric and stochastic frontier analyses are performed (i) to determine the influential factors of the Chilean manufacturing output and (ii) to evaluate the levels of technical efficiency for each Chilean industrial sector. The results obtained show that, for both the standard model and the proposed factorial model, the economic theory is validated in terms of the importance of the inputs that form the manufacturing outputs. Moreover, a functional structure is defined as an adequate representation of the manufacturing outputs in Chile. The manufacturing sector of the country presents a downward trend in technical efficiency during the study period, with higher decline rates in the lowest efficient ratings. The results show a period of productivity growth from 1986 to 1996, a slowdown from 1998, and only a slight increase in 2004. Similarly, important intra-group variations in the manufacturing sector are observed, especially in the of food group, in which average efficiencies from 19% to 91% are reported. Innovative discussion, implications and recommendations concerning our investigation, as well as issues associated with industrial policies, are provided and suited within the “Industry 4.0” context.

Original languageEnglish
JournalComputers and Industrial Engineering
DOIs
StatePublished - 1 Jan 2019

Keywords

  • Cobb-Douglas and trans-logarithmic models
  • Cronbach coefficient
  • Data-driven decision making
  • Industry 4.0
  • Stochastic frontier analysis
  • Supply chain

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