Premature Deindustrialisation and Income Inequality Dynamics: Evidence from Middle-Income Economies

Abstract

The structural transformation path in most developing economies follows an employment shift towards service activities, skipping an industrialisation phase. In this paper, we explore how this premature deindustrialisation trend affects the inclusive growth trajectory of middle-income economies. Considering the trends in manufacturing employment and value-added share, we identify premature deindustrialisation phases in economies. We apply panel fixed-effects and bootstrap-corrected dynamic fixed-effects models to empirically examine the relationship between premature deindustrialisation and income inequality. Our findings suggest that income inequality rises with premature deindustrialisation if the displaced workers are absorbed into market services (especially with employment movement towards non-business market services such as trade, transport, hotels, and accommodation). In contrast, if non-market services (such as education and health) or business services (such as banking and financial services) are the dominant employment provider, it helps to reduce income inequality even in the presence of premature deindustrialisation.

Keywords:

• premature deindustrialisation
• income inequality
• middle-income countries
• manufacturing employment
• service sector employment
• structural transformation

JEL classification:

• C23
• O10
• O1
• O47

Acknowledgements

The authors gratefully acknowledge Simone Schotte, Kunal Sen, Michael Danquah, and Carlos Gradín for their valuable feedback and comments that helped to shape the paper. We thank the UNU-WIDER team for extending constant support throughout the research period. A preliminary version of the paper was published as the UNU-WIDER working paper. We are extremely grateful to the editor and the anonymous reviewers for their insightful suggestions, which have helped to improve the quality of the manuscript.

Disclosure statement

The authors confirm that there are no relevant financial or non-financial competing interests to report.

Data availability

The data that supports the findings of this study are derived from ILO (https://ilostat.ilo.org/topics/employment), UNSD (https://unstats.un.org/unsd/snaama/Index), ETD(https://www.rug.nl/ggdc/structuralchange/etd/), WIID (https://www.wider.unu.edu/database/wiid) and WDI (https://databank.worldbank.org/source/world-development-indicators) sources openly available in the public domain.

Notes

1 Structural transformation implies the movement of labour and other resources from one sector to another during the process of economic development (McMillan, Rodrik, & Verduzco-Gallo, 2014). In the traditional pattern of structural transformation, labour movement occurs from agriculture to industry in the initial phase of economic growth. Later, as the economy reaches higher stages of development, the shift in labour occurs from industry to the service sector. Generally, advanced economies experience this pattern of structural transformation.

2 The World Bank country classification (the fiscal year 2021) specifies that middle-income countries are those with a GNI (gross national income) per capita of between US$1,036 and $12,535 in 2019. High-income countries are those with a GNI per capita of $12,536 or more. Low-income countries are those with a GNI per capita of $1,035 or less.

3 Deindustrialisation generally implies a fall in the manufacturing employment (or value-added) share in total employment (or total output) after reaching a peak. Hence, it follows a hump-shaped relationship with income level (Herrendorf, Rogerson, & Valentinyi, 2014).

4 Appendix Tables A1 and A2 provide the aggregation of activities into sectors based on the ISIC of all economic activities, Revision 4 (Rev. 4).

5 The grouping of service sector activities based on ETD classification are given in Appendix Table A5.2.

6 In this alternative definition of premature deindustrialisation, we use conditions 1, 3, 4, and 5 as described in Section 2.