INDUSTRIAL PRODUCTIVITY ESTIMATION AND MAPPING (A CASE STUDY OF IRAN’S ECONOMY)

Authors

  • Paniz Donyadari Ms.
  • Dr Reza Mohammadpour University of Tehran, Tehran, Iran.
  • Dr. Jafar Rahmatizad Khajehpasha Islamic Azad University, Aligudarz Branch, Aligudarz, Iran.

DOI:

https://doi.org/10.1956/jge.v20i2.728

Keywords:

economics

Abstract

Recent empirical evidence underscores the vital role of industrial development in fostering structural change and promoting a country's long-run development objectives. Devising sound industrial policy institutions emerges as a key policy option to promote the reallocation of human, physical and financial resources to high value added sectors of the economy (Mbate, 2016). The total factor productivity (TFP) and partial factor productivity (PFP) are the prominent indices for the analysis of industrial development in countries or regions. This study addresses industrial productivity by using these indices. Furthermore, after these indices were estimated, the studied provinces were classified as high-productivity, medium-productivity, low-productivity, and poor-productivity groups through hierarchical clustering. The dispersion rates of all the TFP and PFPs were then shown on a geographical map of Iran. Before the productivity indices are estimated, theoretical and empirical foundations are first reviewed in the following section.

Author Biographies

Dr Reza Mohammadpour, University of Tehran, Tehran, Iran.

Ph. D in Economics,

Dr. Jafar Rahmatizad Khajehpasha, Islamic Azad University, Aligudarz Branch, Aligudarz, Iran.

Ph.D in Economics

References

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Nielsen, F. (2016). Hierarchical Clustering. In: Introduction to HPC with MPI for Data Science. Undergraduate Topics in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-21903-5_8.

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Published

14.07.2024

How to Cite

Donyadari, P., Mohammadpour, R. and Khajehpasha, J. R. (2024) “INDUSTRIAL PRODUCTIVITY ESTIMATION AND MAPPING (A CASE STUDY OF IRAN’S ECONOMY)”, Journal of Global Economy, 20(2), pp. 81–97. doi: 10.1956/jge.v20i2.728.

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