Premature Deindustrialization Risk in Thailand

Premature Deindustrialization Risk in Thailand

Ni Lar, Hiroyuki Taguchi
Copyright: © 2022 |Pages: 15
DOI: 10.4018/IJABIM.302248
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This study investigates the possibility of premature deindustrialization risk in Thailand, where the pressure of globalization and uneven industrial policies remain. This study adopts the latecomer index to materialize premature deindustrialization risk, which is expressed as the downward shift of the manufacturing–income relationship at the earlier level of income. The results of our empirical analysis confirm the presence of premature deindustrialization risk in Thailand’s regions as a result of globalization pressure (represented by China’s entry into the World Trade Organization) and uneven industrial policies conducted by the Thai government. Thus, the current industrial policies of the Thai government should be reconsidered to overcome premature deindustrialization risk in remote regions.
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Conventionally, scholars attempt to outline economic developments by referring to the system of improving the economic and social well-being of people. Lewis (1955) presented the two-sector growth model of structural changes with an unlimited supply of labor, and Petty-Clark’s law (Clark, 1940) presented the three-sector hypothesis for the developed and developing world. Developing countries, such as those classified as low and middle incomers, however, still experience from poverty traps and income inequalities among their provinces, regions, or districts within territories, and search for ways to mitigate them. In the literature, the flying geese model by Akamatsu (1962) is renowned for charting Asian countries’ growth paths after its success in Japan, while the balanced growth (Nurkse, 1953) and the imbalanced growth (Hirschman, 1958) are also practical theories for regional development of a country. From the industrial perspective, the manufacturing sector is considered the engine of growth for a country. Kaldor (1966, 1967) found a positive relationship between the growth of manufacturing output and growth of GDP, now called Kaldor’s law. Manufacturing sector expansion improves the primary sector’s labor productivity by shifting oversupplied labor from the primary to the manufacturing sector. Therefore, the manufacturing output expands quickly, and the productivity growth, employment creation, and income growth persist. Thus, various forms of industrialization strategies and growth models have been adopted for regional development. The premature deindustrialization issue among regions/provinces, however, has not yet been fully discussed.

Recently, the concept of “Premature Deindustrialization” has gained attention among scholars, economists, and policy-makers. Specifically, Dasgupta and Singh (2007) and Rodrik (2016) have stressed developing countries’ quick transition into the services sector with the reduction or destruction of the manufacturing sector. Advanced countries have already been experiencing this line of deindustrialization. However, labor productivity achievement rather than not prematurity has led to the structural changes from the secondary sector to the tertiary sector. This has resulted in employment loss but not output loss. It has, however, not been the case for developing countries since the 1980s. Developing countries have experienced a reduction in their manufacturing share of output with a reduction in their income levels. The theoretical framework of Rodrik (2016) considered developing countries as the price taker with a lack of comparative and competitive advantages; thus, they are compelled to import considerable amounts of manufacturing products from developed countries, which is called “import deindustrialization.” This premature deindustrialization should be examined since the interruption in manufacturing output would lessen the catching-up effect for developing countries.

This paper examines the premature deindustrialization risk with a focus on Thailand’s regions for 1995-2019. Specifically, this study concerns manufacturing output and the latecomer index represented by the ratio of a region’s per capita gross regional product (GRP) relative to that of a benchmark region. Bangkok is selected as the benchmark region because it records the highest per capita GRP at the 2002 constant prices. The latecomer index makes it possible to identify the downward shift of the manufacturing-income relationship, thereby suggesting the existence of premature deindustrialization risk. The estimation methodology in this study follows Rodrick (2016), and Taguchi and Tsukada (2021). The ultimate objective of this study is to evaluate the industrial policies’ performance and the degree of its inclusive growth in Thailand by examining whether premature deindustrialization risk has been emerging in its local regions. The research area and scope in this study are crucial in business and academic circles and policy makers in that alleviating premature deindustrialization risk in the latecomer’s regions would lead to attaining “inclusive growth,” one of the Sustainable Development Goals established by the United Nations.

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