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There is a growing empirical evidence of premature deindustrialization in developing countries wherein the share of manufacturing in GDP and employment declined at a much lower level of per capita income as compared to the trend observed in developed countries. This study examined the manufacturing performance of India, which has been persistent with industrialization as its catch-up strategy. While the study finds no evidence of deindustrialization in the conventional sense, it presents compelling evidence in terms of wage share in value added and wage rate. Therefore, the study argues that a realistic analysis of deindustrialization should consider the quality of employment, wage share and wage rate along with employment share and GDP share. The study attributes deindustrialization in India as an outcome of its strategy to build international competitiveness based on price/wage cost advantage and the failure to build a vibrant learning, innovation and competence building system. Resumo Existe crescente evidência empírica de desindustrialização prematura nos países em desenvolvimento, onde a participação do emprego industrial no PIB diminuiu em um nível muito mais baixo de renda per capita em comparação com os países desenvolvidos. Este estudo examinou o desempenho da indústria da Índia, que tem persistido com a industrialização como estratégia de catch-up. Embora o estudo não encontre evidências de desindustrialização no sentido convencional, ele apresenta evidências convincentes em termos da qualidade do emprego gerado e da sua participação no PIB. Portanto, o estudo argumenta que uma análise realista da desindustrialização deve considerar a qualidade do emprego, a participação e a taxa dos salários, juntamente com a parcela do emprego e do PIB. O estudo atribui a desindustrialização na Índia como resultado da estratégia de ganhar competitividade internacional via vantagens de preço / custo de salário e o fracasso em construir um sistema vibrante de aprendizagem, inovação e construção de competências.

This research aims to identify the nature of deindustrialisation on Indonesia’s economy. To test the negative deindustrialisation, this research performed a descriptive analysis on value-added, export-import, and productivity data of manufacturing sector. To test the premature deindustrialisation, this research conducted a regression analysis to create a simulation of value of GDRP per capita at the top of industrialization taken place on Indonesia’s economy. Descriptive analysis shows that deindustrialization in Indonesia prevails with downward trend of value-added, trade performance, and productivity of manufacturing sector. Subsector analysis also shows that manufacturing subsectors having high value added experienced negative trend in all mentioned indicators. The result of premature deindustrialization model regression shows that the peak of industrialization in Indonesia achieved at lower level income per capita compared to several thresholds of premature deindustrialization. Those results show that negative and premature deindustrialisation prevailed in Indonesia’s economy. The consequence of these research’s results is to promote the politics of reindustrialization. There are several recommendations for policy makers to enhance performance of manufacturing sector. From demand-side, it is important to expand market of manufacturing product internationally and domestically. From supply side, the policy makers should increase the investments and insentives for businesses.

We add to recent evidence on deindustrialization and document a new pattern: increasing industry polarization over time. We assess whether these patterns can be explained by a dynamic open economy model of structural change in which the two primary driving forces are sector-biased productivity growth and sectoral trade integration. We calibrate the model to the same countries used to document our patterns. We find that sector-biased productivity growth is important for deindustrialization, and sectoral trade integration is important for industry polarization through specialization. The interaction of these two driving forces is also essential. The key transmission channel is the declining relative price of manufacturing goods to services over time.

Introduction. Under the conditions of increasing interregional economic imbalances and deindustrialization of the economy the industrial potential of regions as a catalyst for regional leveling and economic growth becomes particularly important. Due to the development of manufacturing and other activities included in production chains the economies of backward regions can be revitalized. Purpose. The purpose of the article is the development of recommendations of the regional industrial policy implementation using the industrial potential of regions to level out interregional imbalances. Method (methodology). The statistical analysis based on variation coefficients and mapping approach are used for assessing the extent of socio-economic regional imbalances. Using the correlation analysis the relationship between the industry’s share by the number of employees in a regional economy and GRP per capita is estimated. The evaluation of industrial specialization of the regions is performed by industries’ localization coefficients. The regional industrial potential is determined according to the current production performance and its possible increase, internal and external investment resources and human capacity. The recommendations on directions and instruments of regional industrial policy are developed using the generalization of domestic and international experience according to new challenges of industrial and regional development of Ukraine. Results. It is determined that during 2010-2017 the level of regional divergence in Ukraine has significantly increased. The industrial, investment and labour potentials of the regions that may become a driving force for regional leveling are disclosed. The forms of inclusion of the regions with low industrial potential in interregional production chains are substantiated. The new objectives of the modern regional industrial policy arising from modern paradigms of neoindustrial, innovative economies and industrial policy are determined and are directed on overcoming centrifugal trends of regional development in terms of decentralization reform.

This paper argues that rising food staple prices can pose a significant barrier to the growth of labour‐intensive manufacturing by raising real wage rates. This is important because an expanding manufacturing sector has both comparative static and dynamic effects on labour productivity growth. The experience of Indonesia is used to illustrate these ideas.

What happens when the most dynamic entrepreneurial businesses in a country are effectively born global, or when most advanced production facilities are owned and operated by foreign firms which turn out products invented elsewhere? Is thin industrialization the result of policy failure, or is it systemic and unavoidable? Can it be unwound by neo-nationalists? What impact does this have on working and middle classes and social development?

This study aims to identify the causes of deindustrialization among ASEAN countries with years of analysis from 2000 to 2017. Secondary data in this study were obtained from CEIC and the analysis method used an econometric model approach to panel data. The variable used to describe deindustrialization in this study (dependent variable) is manufacturing value added (MANVASUR) and the share of manufacturing in GDP (MANSHA). The results of the analysis show that per capita income, population, and economic openness have a significant effect on manufacturing value added (MANVASUR), while the share of manufacturing in GDP (MANSHA) is influenced by the wealth of natural resources, population, and economic openness. The population and per capita income of ASEAN member countries are positively related to the added value of the industrial sector, while economic openness is negatively related. This means that the more open the economy of a country, on the contrary the value added of the industrial sector actually decreases. Economic openness and natural resource wealth of ASEAN countries are positively related to the contribution (share) of the industrial sector to GDP, while the population is negatively marked by contribution (share) industrial sector to GDP. That means, the fewer the population, the less human resources involved in industry and industry will involve a lot of technology (capital intensive).

This paper theoretically and empirically investigates deindustrialization in a group of selected countries, from 1970 to 2017, viewing it as a process of varied and complex causes, sensitive to the degree of economic development. Supported by the theoretical framework on the centrality of the manufacturing industry for economic growth and the contextualization of recent trends in global industry, we seek to understand empirically the main determinants of deindustrialization through an econometric model of panel data analysis. The main objective, which is also the main contribution of this research, is to empirically investigate the determinants of deindustrialization considering the degree of development of the countries and with the understanding that the causes of this process can differ substantially. Our main results, in general, were aligned with the theoretical and empirical literature on the topic, while corroborating the hypothesis that certain variables are dependent on the level of economic development. In less developed countries, the exchange rate (depreciation) is correlated positively with the value added of the manufacturing sector, as is trade openness but in a negative way. In advanced countries, on the other hand, the relocation of physical production and the degree of financialization are highlighted as factors that negatively affect the manufacturing value added, while trade openness is positive. In view of these results, a more critical analysis on the causes and costs of deindustrialization is considered important, especially in developing countries.

Contrary to the notion of a natural tendency in deindustrialization, this paper, performing a cross-country long-term analysis, documents the existence of a variety of patterns of deindustrialization. Looking at industrial sectors and their technological characteristics, categorised on the ground of the Pavitt (1984) taxonomy, we do find a markedly uneven process of deindustrialization with Science Based and Specialised Suppliers not presenting any inverted U-shaped pattern, neither in employment nor in value added. The heterogeneity holds both for the four Pavitt aggregates and under further disaggregation at industry level. We then study whether the uneven sectoral composition had an impact on the timing of deindustrialization. Overall, our analysis supports the notion that “microchips” are not “potato chips” in their influence on the patterns of long-term economic development of different countries. Moreover, during the phase of globalization the probability for low-income countries to be stuck to produce “potato chips” has increased and that of transition toward the production of “microchips” has been reducing.

This paper examines the income inequality implications of a ‘premature deindustrialization’ trend in middle-income countries. To identify the premature deindustrialization phase, we arrive at five conditions based on the trends in employment and value-added share of manufacture. Among these five conditions, the first and second examine the deindustrialization pattern in economies. The last three classify the identified deindustrialization phase as premature or not. We apply panel fixed-effects and bootstrap-corrected dynamic fixed-effects models to empirically examine the relationship between premature deindustrialization and income inequality. Our findings suggest that income inequality rises with premature deindustrialization if the displaced workers are absorbed into low-productivity and informal market services (especially with employment increase in non-business market services such as trade, transport, hotels, and accommodation activities). In contrast, if high-productivity non-market services are the dominant employment provider, this helps to reduce income inequality even in the presence of premature deindustrialization.

The effect of premature deindustrialization on the distribution of gains from growth has thus far been understudied. Using census data from eleven countries spanning five decades and shift...

The steady rise of income inequality in the United States coincides with trade union decline and structural changes to the economy, but prior studies do not consider whether these phenomena interact in ways that magnify inequality. Drawing on institutional and market accounts of inequality, the author develops the argument that trade union decline, occurring within the context of deindustrialization and the offshoring of routinemanufacturing jobs, creates more profound distributional effects than these factors would create in isolation. This argument is tested (net of other important determinants of income inequality) using time-series regression models and national-level data from 1947 to 2015. Results support the proposed interaction effects, suggesting that a thorough understanding of inequality and social stratification must consider not only institutions and markets, but how they interact. The results also suggest that inequality is driven by financialization, public sector retrenchment, and unemployment, but not necessarily by technological change.

Sanayisizleşmeyi ölçmek için genellikle GSYH içinde imalat sanayinin payı kullanılır. Çalışma, kişi başına imalat sanayi katma değerini alternatif bir gösterge olarak önermektedir. Bu iki gösterge, farklı coğrafyalardan ve farklı sanayileşme düzeylerinden seçilen örnek ülkelerde sanayisizleşmeyi incelemek için kullanıldı. Sonuçlar, sanayileşmenin varlığına ilişkin değerlendirmelerin kullanılan göstergeye göre farklılaşabileceğini göstermektedir. İmalat sektörünün payı azalsa bile kişi başına katma değer artabilir ve bu da sanayisizleşme olduğuna dair yanıltıcı bir değerlendirmeye yol açabilir., Share of manufacturing in GDP is widely used as the main indicator to measure the degree of deindustrialization. The paper proposes per capita manufacturing value added as an alternative indicator. These two indicators are employed to scrutinize the deindustrialization in the selected sample countries from different regions and different industrialization levels. Results show that assessments regarding the existence of industrialization may differ depending on the indicator used. Even if the share of the manufacturing sector decreases, the value added per capita may increase, which may lead to a misleading assessment that there is a deindustrialization.

Deindustrialization is a dynamic process that began to attract the attention of economic theorists in the 60s of the 20th century, which is characterized by a reduction in the share of the industrial sector in GDP and employment. A descriptive analysis of the deindustrialization process in Montenegro was carried out. It was established that throughout the observed period, the process of deindustrialization in Montenegro has characteristics present in developed countries. However, a deeper analysis and taking into account the key indicators showed that deindustrialization in Montenegro did not just arise as a sole consequence of positive economic trends. In addition, the entire process took place under the influence of various non-economic indicators. Moreover, the global economic crisis had a significant economic impact on Montenegro's industrial sector. In the process of accession to the EU and in addressing global challenges, the country's industrial sector, in line with key development strategies, is heading towards reindustrialization, i.e. development and progress under changing conditions.

The article examines the production sphere of Ukraine's economy in the context of reduction of the knowledge-intensity as a result of the processes of deindustrialization. The main reasons for the reduction of knowledge-intensity of manufacturing and decline in the economy of Ukraine are analyzed. The article also describes possible consequences of deindustrialization in the present conditions.

The article adds to the debate around the ‘premature deindustrialization’ of developing countries by analyzing the contribution of services to aggregate productivity and output growth within a Kaldorian framework. We revisit Kaldor´s Growth Laws (KGL) and empirically test them for a number of economic activities, including four service branches, across twenty-nine developing economies in Asia, Latin-America and Sub-Saharan Africa over three decades (1975-2005). Panel data estimations are complemented by a shift-share decomposition of labour productivity growth. We find support to the Kaldorian argument for both manufacturing and business services contribution to aggregate productivity growth. Conversely, other services slow down aggregate productivity and output growth. We suggest qualifying and repositioning the debate on premature deindustrialization within a broader reflection on the opportunities for development linked to structural change. We claim that these opportunities might include not only manufacturing sectors but also business services.

The increase of the manufacturing's share in GDP has reached its peak in the early 2000s while the growth rate of the manufacturing employment is relatively low. Both facts demonstrate that the process of industrialization has slowed down and an indication of deindustrialization in Indonesia. Deindustrialization that occurs in the countries with low GDP per capita is called premature deindustrialization. This study measures the rate of deindustrialization and identification of premature deindustrialization on period 1986- 2015. The result shows that the speed of deindustrialization varies between indicators and between islands. Descriptive analysis showed indication of premature deindustrialization in Indonesia. Keywords: Deindustrialization, Premature deindustrialization, Manufacturing, Indonesia JEL classification: L16, L50, L52, L60, O14, O25

This study will analyse the deindustrialization process in El Salvador. Deindustrialization has been a factor in the Latin American countries since the 1980s and contributes to economic stagnation and quality job loss. The first section reviews selected studies in the literature on this subject and is followed by an exploration of the possible causes of deindustrialization in El Salvador. The idea that remittances may have triggered a bout of Dutch disease is the first possibility to be examined, but it is then ruled out. The focus then turns to the repercussions of economic reforms carried out in the 1990s and, by estimating cointegration equations, evidence is found that the extreme form of trade liberalization that was implemented in El Salvador is the chief reason for the contraction of tradable goods sectors. The study closes with a series of recommendations and conclusions.

For the last four decades, ratio of services sector to economic growth has been increased among several developing countries. Like other developing economies Pakistan also experienced similar trends i.e. the share of services sector in Gross Domestic Product has expanded as compared to agriculture sector whereas manufacturing sector share remained stagnant. This situation is basically named as deindustrialization by some economists. In this context, present research tries to find out empirically the effects of deindustrialization on economic growth of Pakistan using time series data set ranging from 1972 to 2017. Auto Regressive Distributed Lag modelling technique has been used for estimation of the model. Empirical findings verified the fact that manufacturing value added has positive and significant impact on economic growth. The key finding suggested that Pakistan became a service economy without having proper experience of industrialization hence indicating deindustrialization in Pakistan. It is also concluded that Pakistan requires introducing such policies that encourage manufacturing sector growth as well as agriculture sector by curbing services sector. The study suggests that services sector should be prompted but not at the cost of manufacturing sector. This will render the growth journey of the country smoother and sustainable.

The term ‘deindustrialization’ stands for an element of structural change, indicating some form of decline within the secondary sector of a national economy. Sociologists use relative decline of manufacturing as their standard definition while economists often consider reductions in sectoral output as equally or even more important. There is a variety of other current descriptions. Rigid definitions were constituted and utilized in a model of industrialization and deindustrialization based on compound annual growth rates (CAGRs) of macro-economic indicators. For this article, the scenario model was applied on twelve mature countries (i.e. fully industrialized states beyond their maximum relative employment in manufacturing). The analysis covers the years 1973-2008 with successive 15 + 5 +15-year sub-periods. On the basis of the model-based findings and additional socio-economic analyses, different paths of industrial development (patterns of deindustrialization) were distinguished for mature economies with regard to their final outcome, i.e. the sectoral parameters and the resulting GDP per capita, employment rate and trade indicators.

In this modern era, environmental pollution is the biggest problem attached to industrialization. This study tries to ensure the relationship between industrialization and CO2 emissions in Pakistan for the time period 1980–2018 by using nonlinear ARDL model while controlling for urbanization, GDP, and human capital variables as a likely factor of CO2 emissions. Our foremost study objective is to examine whether or not the outcome of industrialization on CO2 emissions is symmetric or asymmetric for Pakistan that is one of the core suppliers to CO2 in South Asia, as the emissions were 0.82 million tons in 2018. Our result approves the presence of an asymmetric effect of industrialization shocks on CO2 emissions both in the short run and long run. The results reveal that industrialization increases emissions and deindustrialization decrease emissions, in short as well as long run, in Pakistan. Moreover, our finding also advises that urbanization and GDP variables have exerted a positive impact on CO2 emissions. Based on the findings, some policy suggestions are proposed for Pakistan.

This chapter outlines the contours of contemporary structural change and economic development along the following lines: in all developing regions agriculture shares of GDP and employment have fallen substantially—albeit they still persist at high levels among the poorest countries; regional manufacturing shares are consistent with deindustrialization or stagnant industrialization in employment shares and value-added; and, service shares of GDP and employment are on an upward trend in general, with the exception of East Asian economic growth, which has been driven by an inter-sectoral movement toward manufacturing. There is also a trend toward greater capital intensity of growth. Further, while in East Asia there have been substantial changes in the composition of exports, this is not the case in all regions.

A theoretical analysis of the crisis of the neoliberal model of globalization, which led to the processes of deindustrialization in many countries of the world, including Ukraine, is presented. It is shown that through the restoration of the development of high-tech sectors of the real economy, a global economic model is changing, that gives a chance to overcome negative consequences of the global crisis. The analysis of various models of capitalism under conditions of neoliberal globalization, including those in the countries emerging in the postsocialist space, has been carried out. It is shown that solving the contradiction that has developed in Ukrainian economy between current and long-term tasks is possible on the basis of a reproductive approach.

This article examines conceptions of social justice and economic fairness with regard to employment. It does so through an analysis of the management of deindustrialization in the Scottish coalfields between the 1940s and 1980s. Emphasis is placed on the historical roots and social and political constitutions of labor market practices. The analysis is grounded within Karl Polanyi’s Great Transformation; industrial relations within coal mining are conceived through an ongoing conflict between commodifying, liberalizing market forces and a “counter-movement” of worker and community resistance and state regulation, which works to embed markets within social and political priorities. E. P. Thompson’s moral economy provides the basis for an understanding of the formulation of communal expectations and employment practices that acted to mitigate the disruption caused by pit closures. The analysis grounds the historical roots of the moral economy within Poalnyi’s counter-movement and illuminates the operation of specific practices of a Thompsonian character within the nationalized industry, which maintained individual and collective employment stability. This is constructed utilizing interviews with former mineworkers and members of mining families. These are supplemented by archival sources that include the minutes of Colliery Consultative Committee meetings, which took place before pit closures. They reveal the moral economy was fundamentally centered on the control of resources, collieries, and the employment they provided rather than simply elements of financial compensation for those suffering from labor market instability. Resultantly procedure centering on collective consultation was fundamental in legitimating colliery closures.

This work analyzes the phenomenon of premature deindustrialization for Colombia and for other seven Latin American countries. Through a Koyck transformation model for the Colombian case, and a panel data fixed effects model for the complete sample of eight Latin American countries, this work documents that the fall in the average effective tariff in the region is the main economic explanation of the premature reduction in the manufacturing share. Also, it provides evidence that relates negative performance of manufacturing to foreign investment flows and to Dutch disease. On the other hand, taking into account the importance of manufacturing on productive sophistication and economic development, this work applies product space methodology in order to determine strategic manufacturing sectors for the establishment of a selective industrial policy for the Colombian case. As a result, the sectors that must be encouraged by the Colombian State are manufactured intermediate goods, mainly goods in the chemical industry.

This study estimates Technical Efficiency (TE) and Total Factor Productivity (TFP) to analyze the sources of growth in the province of East Java in Indonesia. Technological progress, technical efficiency change, and scale effects are estimated through a stochastic frontier analysis (SFA) to break up different sources of growth within manufacture. This study looks at patterns of output expansion by differentiating gains from conventional sources –input growth and technological progress- and non-conventional sources –technical efficiency change and scale effects-. Results are aggregated based on tech-intensity, firm size, capital to output ratio employed, and labor skills. It also compares East Java with the other five provinces in the Java Island, the manufacturing corridor of the country. As expected, manufacturing sector is growing through input growth effects and tech progress-conventional sources- but underperforming in productivity by having negative efficiency change and negative scale effects. Labor has the largest elasticity to output (0.436), capital and raw materials have a much lower elasticity, and energy has a large negative one (-3.097) also causing a sharp increase in the cost of production. Low-tech firms, higher skills, and medium in size perform 72% better than average (TFP). MLT firms with labor-intensive and medium-size firms perform 58% better than average. However, champion industries have lower skills, good access to materials, and are less intensive in energy use. Some features of firm performance are: firm with larger portions of human skills capture the largest TE and higher TP values; those under high skills report larger losses due to negative scale effects; labor-intensive firms have larger TFP (less efficient but less exposed to energy prices).

The industrial sector of the Republic of Croatia is subject to deindustrialization, which was globally recognized as early as in the 1960s. Such a situation is a challenge in terms of implementing new sources of economic growth and industrial production, with a particular emphasis on investing in research and development, education and their products. Since 2011, special emphasis has been placed on the need to implement the concept of Industry 4.0. The problem surveyed in this research derives from insufficient readiness of the Republic of Croatia to implement Industry 4.0, mainly resulting from its major orientation towards traditional industrial sectors and a low share of high value added activities, which is particularly visible through the share of high technology products in total exports. However, the Republic of Croatia is characterized by low levels of scientific research and innovative activities, which greatly slows down this process. The aim of the conducted research is to present the theoretical aspects of the process of deindustrialization and Industry 4.0, to make projections of the key indicators of deindustrialization and Industry 4.0 until 2025, and to propose scientifically based measures to be taken in the direction of securing digital transformation of the Croatian industry. The purpose of the conducted research is to analyse trends in the industrial sector in the Republic of Croatia and to determine the current state of the (de)industrialization process and the level of implementation of Industry 4.0. The research has showed that the process of deindustrialization in the Republic of Croatia is characterized by a reduction in the share of employment in the primary sector, by a growing employment in the secondary sector, and by a relative increase in industrial production and labour productivity. However, since 2015 there has been an increase in employment in the secondary sector, which is in contrast to the theoretical concepts of deindustrialization and indicates a new trend in the industrial sector. This situation is a challenge concerning the implementation of Industry 4.0, which requires increased investment in research and development and the improvement of knowledge and the ability of the population and their implementation in the economic sector. By analysing this segment of the Croatian economy, some progress has been made. Also, it has also been found that in some segments it significantly lags behind the EU levels.

As in most developing countries, Turkey has witnessed the deindustrialization process in 1990s. However, unlike the others, the reindustrialization experience has started in the country since 2002. Despite the existence of some arguments about the environmental impact of such structural changes, they are mostly ignored by empirical studies. For this purpose, the main purpose of this study is to examine the impact of structural changes on environmental degradation in Turkey for the period from 1970 to 2017. In addition, the impact of real income, urbanization and human capital on environmental degradation is also observed. In doing so, the study employs the NARDL approach to clearly obtain the impact of industrialization with both positive and negative shocks. Moreover, both CO2 emission and ecological footprint are used as the indicator of environmental degradation to compare the environmental impact of structural transformation on different degradation indicators. The findings show that deindustrialization results in reduced carbon emissions, but with no significant impact on ecological footprint. Furthermore, we discovered that while both industrialization and reindustrialization lead to lower environmental quality, reindustrialization holds the potential to be less harmful to the environment because of advancements in technology.

Deindustrialization is a widespread phenomenon, both in developed economies or developing countries in the history. This paper examinate the impact of deindustrialization, which is caused by administrative measures aimed at overcapacity, on China’s economic growth in the lastest decade. We adopt empirical approach to estimate the impact, the results show deindustrialization have a significantly negative effect on economic growth in the central and western China, which is stronger in the cites with fast deindustrialization, and in medium and small cities. It provides evidence that rapid deindustrialization hinders the sustainability and magnifies the vulnerability of economic growth, especially premature deindustrialization.

Economic recovery is longer in service-providing economies than in goods-producing economies. Services cannot be produced and inventoried ahead of demand; goods can. We are the first to document this macroeconomic repercussion of the sectoral shift away from the secondary sector toward the tertiary sector, that is, of deindustrialization and the rise of services. We distinguish between nontradable services and all other sectors, using U.S. state-level employment data for post-1960 recessions. Concerns over the endogeneity of services are addressed in two ways: by using 3-year pre-recession averages of sector shares, and separately by invoking instrumental variables. Our results are robust to alternative specifications. The increase in service production and deindustrialization in the United States over the last half-century lengthens the trough-to-peak employment recovery from recessions by about 40%. (JEL E24, E32, L80, N12)

There is growing evidence of two related global processes happening. The late industrializers are deindustrializing at earlier stages of development than their predecessors, and the global trends in the gender composition of manufacturing and industrial employment are evolving. What is less well known is how these two trends are related to one another. Starting from the premise that industrial upgrading has been observed to have a male bias, we test the hypothesis that premature deindustrialization is likely to amplify that bias. For the empirical test and simulation, we use an economy’s global competitive position as a proxy for the deindustrialization regime type. To get to this position, we bring together the work of Nicholas Kaldor, feminist scholarship, and structuralist critiques. The results for sixty-two countries, spanning the years from 1990 to 2013, support our hypothesis that premature deindustrialization is likely to amplify the male bias of industrial upgrading.

Purpose The purpose of the paper is to determine why premature deindustrialization is occurring in many developing countries. Design/methodology/approach A theoretical structure for explaining premature deindustrialization is utilized. Then the comparative experiences of a number of developing countries are used to illustrate the operation of the theory. Findings The results indicate that increasing inequality among a number of developing countries has reduced the domestic market for labor intensive manufactured goods, resulting in stagnation in manufacturing. Also, the increasing inequality in developed countries has reduced international demand for labor intensive manufacturing. Thus developing countries have fewer opportunities to export labor intensive manufacturing. Research limitations/implications Data on inequality is limited and it is very difficult to determine causality. However, intuition indicates that causality is most likely bi-directional. Practical implications Strategies of economic development must concern themselves with the effects that increasing inequality will likely have on the development of labor intensive manufacturing. Social implications Social programs that bolster the purchasing power of poor families are likely to be important (social safety net). Broad-based agricultural growth will provide a basis for labor intensive manufacturing. Originality/value The originality stems from the linking of deindustrialization with rising inequality.

1IntroductionDeindustrialization, which has gained substantial traction among scholars since the 1980s, is sometimes viewed as the cause of diverging per capita incomes between developed countries (Rowthorn & Wells, 1987). In the past, deindustrialization was considered to occur when the share of value-added in GDP and that of manufacturing employment in total employment began to fall (Kaldor, 1967). However, the proliferation of automation and machinery in manufacturing has reduced the significance of employment as a measure of deindustrialization. Thus, the share of manufacturing employment in total employment is likely to drop before a commensurate fall in the share of manufacturing value-added in GDP. Rasiah (2011) argues that deindustrialization is characterized by a fall in the GDP share of industry value-added in general and of manufacturing value-added in particular, rather than by a fall in the share of manufacturing employment in total employment.Positive deindustrialization occurs as a result of the falling share of manufacturing in GDP while manufacturing productivity continues to rise. This type of deindustrialization is inevitable even among countries experiencing rapid technological change and productivity growth as production shifts to more capital-intensive and knowledge-intensive activities. Negative deindustrialization, which is undesirable, occurs when the share of manufacturing in GDP falls in the face of falling manufacturing productivity (Rowthorn & Wells, 1987).Rasiah (2011) defines premature deindustrialization as the falling share of manufacturing in GDP, accompanied by low manufacturing productivity growth when manufacturing industries have yet to mature technologically. This type of deindustrialization is a pathological phenomenon, where simple disequilibrium restricts the economy from fulfilling its development potential. Premature deindustrialization entails not only the falling share of manufacturing in GDP, but also a downward structural shift from high-value-added to low-value-added economic activities or manufacturing stagnation in the latter. In Malaysia, this occurred as a consequence of the substantial import of low-skilled foreign labor into the manufacturing sector.The most severe form of negative deindustrialization arises in low-income and middle-income economies when manufacturing contracts prematurely and is still characterized by low-value-added activities, declining productivity, stagnant output growth and shrinking jobs. When such countries experience negative deindustrialization that is accompanied by either a contraction or slowdown in the growth of per capita income, they become vulnerable to undesirable structural change as they are trapped in low-productivity services.Indeed, many countries in Asia, Africa and Latin America have experienced an expansion in low-productivity services, which offer little potential for long-term growth. Such premature deindustrialization is a threat to sustained economic growth in low- and middle-income countries on two counts. First, such countries have appropriated few of the 'growth-enhancing' benefits of manufacturing. Second, manufacturing tends to be replaced by unproductive rather than productive services, including informal services.In contrast, when 'mature' or positive deindustrialization sets in, the shift toward productive services helps to build knowledge-synergizing linkages characterized by technological upgrading and productivity increments (Rowthorn & Wells, 1987; Kollmeyer, 2009; Rasiah, 2011). It is only then that the services sector becomes an engine of growth: its growth stimulates not only the sector's own expansion, but also that of the other sectors in the economy. Such policies are likely to deindustrialize the economy. Both the deregulation of tariffs too quickly, without giving manufacturing the time to restructure, as well as the continued application of protection and other forms of rent without stringent performance standards to drive technological upgrading contribute substantially to deindustrialization (Rasiah & Nazeer, in press). …

Background The health gap between the top and the bottom of the income distribution is widening rapidly in the USA, but the lifespan of America’s poor depends substantially on where they live. We ask whether two major developments in American society, deindustrialization and incarceration, can explain variation among states in life expectancy of those in the lowest income quartile. Methods Life expectancy estimates at age 40 of those in the bottom income quartile were used to fit panel data models examining the relationship with deindustrialization and incarceration between 2001 and 2014 for all US states. Results A one standard deviation (s.d.) increase in deindustrialization (mean = 11.2, s.d. = 3.5) reduces life expectancy for the poor by 0.255 years [95% confidence interval (CI): 0.090–0.419] and each additional prisoner per 1000 residents (mean = 4.0, s.d. = 1.5) is associated with a loss of 0.468 years (95% CI: 0.213–0.723). Our predictors explain over 20% of the state-level variation in life expectancy among the poor and virtually the entire increase in the life expectancy gap between the top and the bottom income quartiles since the turn of the century. Conclusions In the USA between 2001 and 2014, deindustrialization and incarceration subtracted roughly 2.5 years from the lifespan of the poor, pointing to their role as major health determinants. Future research must remain conscious of the upstream determinants and the political economy of public health. If public policy responses to growing health inequalities are to be effective, they must consider strengthening industrial policy and ending hyper-incarceration.

Sanayisizleşme kavramı, bir ekonomi yüksek gelir düzeyine ulaştığında imalat sanayinin payının azalmasını tanımlamak için kullanılır. Kuznets, üretim çıktısı ve istihdamdaki düşüş eğiliminin bir ülkenin kalkınmasının doğal bir sonucu olduğunu belirtir. Bununla birlikte, Kuznets'teki yapısal değişime ek olarak, dünya çapında üretimin Çin'e kayması da gelişmiş ve gelişmekte olan ülkelerde sanayisizleşmeyi hızlandırabilecek başka bir faktör olarak gösterilmektedir. Makale, seçilmiş MENA ülkelerinde imalat sanayinin gelişiminin belirleyicilerini incelemeyi amaçlamaktadır. Kuznets'in yapısal değişim hipotezi, makaledeki ampirik model tanımlamasında başlangıç noktası olarak alındı. Model, Çin'in ekonomik genişlemesine ek olarak dışa açıklık ve doğal kaynak laneti etkilerini de yakalayacak şekilde de tasarlandı. Ampirik modellerin tahmini için panel veri kullanıldı. Sonuçlar, MENA ülkelerinde ortak bir Kuznets tipi ters U eğrisinin olmadığını ve doğal kaynak lanetinin sanayileşmeyi belirlediğini ortaya koydu. Tahmin edilen model MENA imalat sanayisi üzerinde Çin yayılmasının herhangi bir etkisini belirlemedi., The deindustrialization concept is used to define the decline in the share of manufacturing as an economy reaches to a high-income level. Kuznets indicates that a decreasing trend in manufacturing output and employment is a natural outcome of development of a country However, in addition to the structural change a la Kuznets, the worldwide shift of manufacturing to China is also shown another factor, which may accelerate the deindustrialization in developed and developing countries. The paper aims to examine the main determinants of the manufacturing development in the selected MENA countries. The Kuznets’ structural change hypothesis is taken as the starting point of the empirical model specification in the paper. The model is also designed to capture the effects of openness and resource curse, in addition to the Chinese economic expansion. A panel data estimation is used for empirical models. The results reveal that there is no common Kuznets type invers U curve and resource curse dominates the industrialization in the MENA countries. The model estimated do not detect any impact of Chinese expansion on MENA manufacturing.

A recent literature documents that manufacturing employment growth in developing countries has been sluggish over the past decades, and that deindustrialization has often set in at historically low levels of income. However, there is little evidence on which kind of jobs are disappearing prematurely, and some debate on whether the phenomenon is structural or transitory. In this article, I use a new data set on manufacturing employment by occupation to document four stylized facts about `premature deindustrialization’: first, it is mostly unskilled jobs that have disappeared, and also the wage premium of workers with little formal education in manufacturing relative to other industries has declined. Second, the disappearing jobs have been among the most formal–both relative to other industries, and to the manufacturing average. Third, premature deindustrialization has been driven by occupations which are intensive in tasks that are vulnerable to an increasing adoption of ICT. Fourth, the phenomenon pertains most clearly to middle income countries, as low income countries have been spared from premature job losses. Overall, the employment patterns are consistent with a pervasive shift of the `automation frontier' separating tasks that are automated from those which are not, and suggest a structural decrease in the ability of manufacturing to employ unskilled labor productively.

This study puts forward a model of a multisector economy and embeds it in a novel theoretical framework to address the relationship between commodity revenues and manufacturing output with a special focus on the role of the agricultural sector. The three-sector model lays the groundwork for analyzing policy choices in more complex sectoral settings. Based on the theoretical analysis, the study identifies the weight of the individual economic sectors in the public revenue generation as a determinant of the magnitude of rent seeking epitomized in the crowding out effect of investments in manufacturing. We find that enclave agriculture contributes to the deindustrialization pressure in the face of natural resource windfalls. The central finding of the multisector analysis is the conclusion that not diversification per se but rather a diversification with the substantial domestic factor or market orientation has the capability to limit the magnitude of deindustrialization. For the empirical validation of the theoretical findings, the study employs fixed effects, fully modified OLS, dynamic common correlated effects estimators and dynamic fixed effects estimators for the dataset of 113 developing and transition economies for 1963&ndash, 2014 period. The estimations reveal that natural resource revenues correspond with a higher level of the manufacturing sector output. In the economies with a low level of economic diversification, commodity bonanza leads however to the shrinkage of the manufacturing. In the commodity revenue dependent settings, nevertheless, agricultural sector exports have a negative impact on the performance of the manufacturing sector. These findings are in line with the predictions of the theoretical model.

Nigerian faces complex and mounting challenges of underdevelopment. However, this challenge could not have been so intimidating if negative socioeconomic, political and technological forces have also not combined to ensure the demise of her once bolstering ‘night economy’. Contrary to the experience in the 70s when Nigerians worked and were moving 24 hours daily, the crowding out of ‘night economy’ and the growing culture of idleness have combined to dealt a great blow to the chances of Nigerian becoming a comparatively developed nation as some of the Asian tigers. With a retrospective case study of what then used to be Ikeja Industrial Estate, the two most destructive forces that have combined to retard Nigeria’s progress are the trajectories of deindustrialization and demise of night economy both of which are serendipities of economic policy summersault that happened in the mid-80, to which subsequent heightened prevalence of insecurity have added the nodal norm of near complete social disorder. This paper, being product intuitive personal insights and area-specific field observation, argues that the only way to rapidly move Nigeria out of the doldrums of pervasive underdevelopment is to fast-track Nigerians back to work starting with rapid and massive facilitation of primary productive engagement. Towards achieving this, it recommends that government must simultaneously adopt pragmatic economic strategies of fiscal discipline, conspicuous interventionist posture to accelerate aggressive diversification, reindustrialization, state-enforced import substitution, selective outward orientation, and revival of her demised night economy. Keywords: Deindustralization, night economy, Nigeria

From being the second most industrialized country in Sub-Saharan Africa at independence in 1980, Zimbabwe’s economy has declined rapidly to a point where the country ranks among the poorest economic performers in the region. The three pillars which had underpinned the country’s vibrant economy, namely, agriculture, mining and manufacturing, have suffered greatly from poor government policy choices, resulting in the near collapse of each of the sectors and massive unemployment. As a result, an estimated 90% of the Zimbabwean population was unemployed at 2015 and was forced to eke out a living in the informal sector, mostly through vending of second-hand clothes and other basic items. With regard to the manufacturing sector specifically, the sector had all but collapsed by 2015, as companies either folded or relocated to escape the country’s harsh economic climate. This article traces the decline of the Zimbabwean manufacturing sector from 1990 to 2015 and seeks to explain the factors contributing to this decline.

Deindustrialization is considered as the sustained reduction of industrial activity and as a result can lead to a contraction of labor demand in this sector. However, it is essential to emphasize that deindustrialization, depending on the level of economic development that an economy has reached, can be positive or negative. In developed countries deindustrialization is not a negative phenomenon, but is a natural consequence of higher growth and therefore an increase in industrial productivity, thereby displacing the work released to the service sector. In the case of Latin America, specifically in the South, this phenomenon is premature and can cause serious repercussions in the economic systems, for this reason, this research focused its interestin analyzing through a data panel the contribution of commercial openness -among others causes -in deindustrialization. On the other hand, the obtained models were applied the multiplier tests of LaGrange, Hausman, F, Wooldridge, Wald, Breusch -Pagan LM, in order to obtain reliable results. Subsequently, the empirical evidence allowed accepting the hypothesis raised about the influence of trade liberalization on the deindustrialization of the countries of South America, this variable being statistically significant in the proposed regressions, concluding that, in view of increases in trade liberalization,employment in the industrial sector decreases La desindustrialización es considerada como la reducción sostenida de la actividad industrial y como resultado puede conducir a una contracción de la demanda laboral en este sector. Sin embargo, es indispensable destacar que la desindustrialización, dependiendo del nivel de desarrollo económico al que haya llegado una economía, puede ser positiva o negativa. En los países desarrollados la desindustrialización no es un fenómeno negativo, sino que es una consecuencia natural de un mayor crecimiento y por ende un aumento en la productividad industrial, desplazando de tal modo, el trabajo liberado al sector de los servicios. En el caso de Latinoamérica, específicamente en el Sur, este fenómeno es prematuro y puede ocasionar graves repercusiones en los sistemas económicos, por tal motivo, está investigación centró su interés en analizar mediante un panel de datos la contribución de la apertura comercial –entre otros causantes –en la desindustrialización. Por otro lado, a las modelaciones obtenidas se les aplicaron los test del: multiplicador de LaGrange, Hausman, F, Wooldridge, Wald, Breusch –Pagan LM, con la finalidad de conseguir resultados fiables. Posteriormente, la evidencia empírica permitió aceptar la hipótesis planteada acerca de la influencia de la apertura comercial sobre la desindustrialización de los países de América del Sur, siendo esta variable estadísticamente significativa en las regresiones propuestas, concluyendo en consecuencia que, ante aumentos en la apertura comercial, el empleo en el sector industrial disminuye.