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The Importance of Manufacturing in Economic Development: Has This Changed?
... An excellent review of Kaldor's momentous contributions to development economics is provided by Targetti (2005) who draws attention to Kaldor's emphasis on industrialisation and integration with global markets for successful development. More recent studies, such as Szirmai (2012), Storm (2015), Szirmai and Verspagen (2015), Tregenna (2015), Marconi et al. (2016), Haraguchi et al. (2017) and Hauge and Chang (2019) support the above-mentioned Kaldorian argument, which comprises Kaldor's growth laws. Similarly, Foster-McGregor et al. (2015) argue that the capability of countries to sustain high growth depends critically on the share of manufacturing in GDP, along with the sectoral diversification of production. ...
... Recent empirical studies demonstrate that the per-capita income levels at the turning point of the manufacturing employment shares (UNIDO, 2013;Rodrik, 2016;Felipe et al. 2019), value-added shares (Timmer et al., 2014) or both (Haraguchi et al. 2017;van Neus, 2018) are much lower in the case of DE and/or EME, as compared to the earlier experiences of the AE. If the manufacturing industry is the engine of growth à la Kaldor, 'premature deindustrialisation' can potentially lead to 'divergence' of incomes between DE/EME and AE, as opposed to the 'convergence' thesis of the conventional growth literature pioneered by Barro and Sala-i-Martin (1992). ...
... Table A1 provides also individual country level data used for computing the figures in Table 1. 4 The sub-periods are constructed to reflect roughly the dominant trade and financial policies adopted especially by the less-developed countries in the world economy: import-substituting industrialisation, trade protectionism and significant control of international capital movements (1960s and 1970s); the following post-1980 periods that were more or less characterised by trade liberalisation and financial liberalisation; and the further expansion of international trade and capital movements during the 2000s. 5 Alternatively, deindustrialisation can also be defined in terms of manufacturing employment shares (UNIDO, 2013;Rodrik, 2016;Felipe et al., 2019;Haraguchi et al., 2017. According to Tregenna (2009, on the other hand, deindustrialisation should better be defined in terms of MVA as the Kaldorian perspective maintains that manufacturing productivity is higher and consequently employment share tends to decline with economic growth. ...
We examine patterns and globalisation-related causes of premature deindustrialisation (PD) in recent decades, using a large panel of advanced, emerging and developing economies (AE, EME and DE). The results verify the existence of PD in EME and DE, except East Asian countries. African countries have been worst affected by PD. Globalisation-related determinants of PD vary across country groups. While trade openness leads to deindustrialisation in DE; it enhances ‘dependent’ industrialisation in Latin American countries and the ‘factory economies’ of East Asia, which have stronger linkages to global value chains. Financial openness fosters industrialisation in severely finance-constrained economies, whereas it brings about deindustrialisation in financially stronger ones. It is our contention that development possibilities can be expanded by aiming at more intense linkages to global value chains, but proactive industrial policies at the levels of EME and DE are required to achieve such expansion.
... Several measurements can be used to determine the level of industrialisation -in most cases, this depends on what the researcher seeks to understand. These measures include manufacturing value added (MVA) as a percentage of GDP, the industry as a percentage of GDP (Haraguchi et al., 2017;Simandan, 2009;UNIDO, 2019). However, this book used MVA contribution to GDP as its primary measure, because: it defines the industrialisation process as transforming a traditional agricultural economy into an industrial manufacturing one; it is a primary objective of the organisation of interest in this book. ...
... MVA is a recognised measure and indicator used by researchers and policymakers to assess a country's level of industrialisation. The MVA share of GDP reflects the role of manufacturing in each country's economy and in terms of national development in its entirety (Haraguchi et al., 2017;Mijiyawa, 2017;Simandan, 2009). The manufacturing sector introduced ground-breaking production structures in the postwar era and has become significant in diversifying and transforming economies in developing countries (Andreoni & Gregory, 2013;Cantore et al., 2017). ...
... Several authors note that the manufacturing productivity advantage begins to fade in high-income countries when they transition into economies driven by the service sector (Dadush, 2015;Haraguchi et al., 2017). Meanwhile, Fforde (2018) has been critical of over-emphasising the significance of manufacturing. ...
Since the beginning of decolonisation in Africa, regional integration has become one of the most potent defining characteristics of the continent’s quest for industrialisation and sustainable development. It was understood that the individual continental economies could not achieve the requisite level of industrial development to meet their respective development objectives due to the colonial policy of balkanisation, which divided the continent into small, economically unviable units. In 1992, the Southern African Development Community (SADC) adopted developmental integration, an approach to regional integration to engender industrialisation and address the region’s development challenges. This book offers a critical assessment and examination of this approach as to how it has influenced the industrialisation process in Southern Africa. If so, why has it failed to accelerate the region’s industrialisation and structural transformation process? It contributes significantly to cross-cutting development debates on the African continent, particularly in southern Africa. More importantly, in understanding the nexus between developmental integration and industrialisation.
... . Evidence that manufacturing shares have declined in some developing countries sooner than would formerly have been predicted from their levels of per capita income has led to concerns about "premature deindustrialization" and weakening of the role of manufacturing in development (Felipe, Mehta, and Rhee 2014;Rodrik 2016;Hallward-Driemeier and Nayyar 2018). The evidence underlying these concerns has been challenged, however, by Haraguchi, Cheng, and Smeets (2017), who show that for developing countries as a whole manufacturing's share of GDP at constant prices and of employment has continued to rise. ...
... Output data from UN National Accounts database. Employment data from Haraguchi, Cheng and Smeets (2017) database, supplemented with ILO and UNIDO data. Definitions: "Primary" is agriculture plus mining. ...
... Some recent research suggests that developing countries are deindustrializing much earlier than would formerly have been expected (Felipe, Mehta, and Rhee 2014;Rodrik 2016), while other recent research shows that for developing countries as a whole manufacturing's shares of real output and employment have continued to rise (Haraguchi, Cheng, and Smeets 2017). This conflict of evidence can be resolved by recognizing that the industrialization was mainly in land-scarce developing regions with larger countries, while the deindustrialization (observed also by McMillan, Rodrik, and Verduzco-Gallo 2014) was mainly in land-abundant regions with smaller countries. ...
... Researchers (Haraguchi, et. al., 2017;Naudé & Szirmai, 2012;Behun, et. al., 2018) concur that the manufacturing sector plays a significant role in national economies and contributes to sustainable economic growth. Manufacturing holds a crucial position in the economies of developing countries, and according to Haraguchi, et. al. (2017), countries have increased opportunities ...
... Researchers (Haraguchi, et. al., 2017;Naudé & Szirmai, 2012;Behun, et. al., 2018) concur that the manufacturing sector plays a significant role in national economies and contributes to sustainable economic growth. Manufacturing holds a crucial position in the economies of developing countries, and according to Haraguchi, et. al. (2017), countries have increased opportunities to participate in manufacturing activities as they progress along the path of modern industrialization. Naudé & Szirmai (2012) argue that the global market for manufacturing firms faces numerous challenges, such as the impact of China's rise, changes in geopolitics affecting global supply chains, ...
Recent geo-economic transformations have led to new challenges for countries in their economic development. The evolving global landscape has emphasized regional competitiveness and attractiveness in terms of capital, labor force, and information. Scholars widely agree that countries receiving foreign direct investment (FDI) gain new knowledge, management skills, and advanced production techniques, leading to increased competitiveness and economic growth (Bayar, et. al., 2020). Changing conditions have also influenced investors’ behavior. Globalization and digitalization have shaped international economic relations, focusing not only on resource acquisition, but also on leveraging human capital, knowledge, institutional structures, and networking for firm efficiency. This shift is reflected in changing investors’ preferences: the importance of natural resources, cheap labor, and the size of the national market has decreased, with greater attention given to service- and technology intensive manufacturing markets (Sadeghi, et. al., 2020). The aim of this study is to identify the factors that determine the attraction of foreign direct investment in the Lithuanian manufacturing sector and assess their impact. To accomplish this objective, several main tasks were formulated: 1) Highlight the necessity for assessing FDI attraction in the manufacturing sector. 2) Identify the factors that influence the attraction of foreign direct investment in the manufacturing sector. 3) Provide empirical evidence of the impact of these factors. The article is structured as follows: Firstly, a review of the scientific literature was conducted to address the research problem, which is the lack of literature on foreign direct investment at the sectoral level. Based on this literature analysis, the factors influencing investment attractiveness at the regional and sectoral levels were identified and compared. Additionally, the factors that determine the attractiveness of the manufacturing sector for investment were also identified. In the second part of the study, a research methodology was developed to assess the impact of these factors on foreign direct investment in the Lithuanian manufacturing sector. The results of the third part of the study indicated that although the Granger causality test did not reveal any causal relationship between FDI in Lithuanian manufacturing and variables such as exports, imports, gross domestic product, the number of educated individuals, government gross debt, government R&D expenditure in manufacturing, the number of FDI enterprises in manufacturing, the wage index, and labor productivity, the correlation analysis demonstrated that exports, gross domestic product, and labor productivity have a significant influence on attracting FDI to the industrial sector. These macroeconomic indicators were statistically significant both in the short term and in the long run. Empirical findings indicated that labor productivity has the greatest impact on the attractiveness of foreign direct investment in the Lithuanian manufacturing sector, both in the short and long term. To maintain the viability and promote the development of the manufacturing industry, Lithuania should focus on the factors that affect labor productivity in this sector. Keywords: investment attractiveness, foreign direct investment, manufacturing sector, sectoral determinants of investment.
... The international agenda aimed at SDG 9 reflects the importance of manufacturing in the current discussion. Despite its contentiousness, SDG 9 to "Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation" (UNIDO, 2022) acknowledges that industrialization is a necessary goal for countries to achieve to advance along the development path (Haraguchi et al., 2017;UNIDO, 2020). Since the early 2000s, the UNIDO has maintained an indicator called Competitive Industrial Performance (CIP) that represents a country's ability to expand its industry by capitalizing on increased competitiveness. ...
With the efforts of the United Nations, environmental sustainability is becoming the subject of countries. Policymakers and researchers closely follow the environmental dimensions of Sustainable Development Goals. This study offers a new perspective for the European Union economies by directly targeting SDG 9 and considers environmental sustainability policies in selecting variables. To be more precise, this study probes the effects of economic growth, trade openness, renewable energy, human capital, and competitive industrial performance on the load capacity factor for EU countries over the period of 1995-2018. This study uses the CUP-FM and CUP-BC approaches due to cross-sectional dependence and heterogeneity. In addition, the study does not ignore possible structural breaks. As a result of the empirical analysis, while economic growth, trade openness, and competitiveness worsen environmental quality, renewable energy and human capital contribute to environmental sustainability. Based on the panel data results, EU economies still rely on fossil fuels to maintain competitiveness in the industry. The EU, which has 2030 and 2050 targets, can eliminate the disadvantages of competitiveness by expanding the environmental quality-enhancing feature of renewable energy and human capital. Moreover, this study provides SDG-oriented policy recommendations for EU countries. K E Y W O R D S competitive industrial performance, environmental sustainability, European countries, load capacity factor, renewable energy consumption
... In addition, this paper's results contribute to the literature on 'premature deindustrialization', which Rodrik (2016) argues to be a widespread feature of recent development. Haraguchi et al. (2017), by contrast, show that developing countries in aggregate have not deindustrialized. These two seemingly conflicting views are actually consistent, because during the globalization of 1985-2014 manufactured output shares fell in land-abundant developing countries, while rising in (a smaller number of larger) land-scarce developing countries. ...
With a modified formalization of Heckscher–Ohlin theory as the basis of a novel econometric specification, this paper uses worldwide data over three decades to estimate how the effects of greater openness on industrialization vary among countries with differing endowments of land relative to labour. The results confirm the theoretical prediction that greater openness reduces manufactured output shares in land-abundant countries, while increasing them in land-scarce countries. The implications of these results for trade and development policy are debatable.
... Pertumbuhan PDB industri pengolahan memiliki performa cukup buruk karena masih berada di bawah rata-rata pertumbuhan PDB secara agregat dan justru kembali mengalami tren penurunan sejak kuartal 3 tahun 2022. Hal ini dikatakan buruk karena mencerminkan pertumbuhan yang tidak inklusif serta menjadi sinyal dari deindustrialisasi (Haraguchi, 2017). Buruknya kondisi industri pengolahan dapat berakibat fatal dalam pertumbuhan ekonomi sebuah negara karena sektor tersebut memiliki multiplier effect tertinggi bagi perekonomian sebuah negara (Gunasekaran, 2019). ...
The COVID-19 pandemic has caused significant changes in various aspects of life, especially in the economy sector in Indonesia in general and East Java Province specifically. The poor performance of Indonesia's logistics has been further burdened by the pandemic, hindering the industry as the main driver of the nation's economy. However, the pandemic that forced the entire community to adapt to the new normal era sparked the growth of digitalization. This is a breath of fresh air for the logistics aspect to utilize digital technology to achieve efficiency and re-drive economic growth. Using the digital competitiveness data (EV-DCI) and other digitalization indicators obtained from the Central Statistics Agency, this study attempts to prove the impact of digitalization at the provincial level in Indonesia on per capita GRDP growth through a reduction in logistics costs. This logistics cost reduction is assumed to be reflected in the Consumer Price Index for the transportation sector. From the 2SLS method used, although not statistically significant, the decrease in transportation CPI due to digitalization described by the increasing number of internet users, smartphone owners, and BTS in each province in Indonesia has an indicative impact to encourage economic performance. Through qualitative analysis, this study suggests policymakers, especially in East Java Province, to encourage digitalization in the logistics sector through the use of Warehouse Management System (WMS), Blockchain, and Transportation Management System (TMS) technologies in industries in East Java to optimize operational and cost efficiency
... The rationale for including the general economic development is that the cost of a transition is most likely easier to carry for a nation with a high GDP per capita. In developing countries, industrialisation will continue to play a key role in their growth [78], which can hinder transition. ...
Meeting the goals set out in the Paris Agreement will require rapid and deep reductions of greenhouse gas emissions (GHG) across all sectors of the global economy. Like all major societal transformations, this climate transition will impact both social and technical aspects of society and, depending on how it evolves, will real-locate social and economic benefits and costs differently. Recognising the importance of decarbonising key industry sectors with large GHG emissions and an significant impact on society, this study explores the opportunities and tensions involved in a transition of the petrochemical industry. We do so by analysing how access to natural resources, the petrochemical industry's role in the economy and the socio-political landscape in key petrochemical producing countries impacts prerequisites for change. The assessment shows that devising adequate policy responses, building legitimacy for change and potentially building bottom-up pressure for a timely climate transition are likely to look very different in the 10 countries with the greatest active petrochemical capacity in the world: China, and Taiwan. The indicators used to explore the prerequisites for change all point to areas where actions and policies must advance for a transition to be realised. This includes efforts to cap fossil feedstock supply and production capacity, efforts to limit and ultimately reduce demand for plastics and fertilisers, and measures to formulate transition strategies and policies that capture and provide agency for communities and groups that are currently on the receiving end of negative health and environmental impacts from the petrochemical industry and that will also, in many cases, be most closely affected by a transition.
... Failure to improve Fig. 2. Mechanisms between industrial structure distortion and energy poverty. employment rates is also detrimental to income growth [67]. In light of the above analysis, Hypothesis 2 is proposed. ...
Promoting energy system reform is an essential initiative to eradicate energy poverty (EP). However, industrial structure distortion (ISD) may hinder this process, thus potentially aggravating EP. This study aims to measure the impact of ISD on EP by using multiple panel econometric models. The results indicate that ISD significantly exacerbates EP in China. This impact is achieved by stimulating energy price increase, hindering the marketization process, and suppressing the rise in resident income. The estimation results of the Spatial Durbin Model show that EP in one region is influenced by its own ISD and the ISD of other regions. Heterogeneity analysis reveals that the primary sector distortion has the greatest impact on EP, and the western region is more prone to EP. In addition, since the launch of the green credit guidelines in China, green finance has substantially contributed to EP eradication. This study helps China recognize the current obstacles in eradicating EP, and provide policy insights to global industrial restructuring.
... Even today, industrial production is associated with development in emerging economies, partly because once a nation's industry begins to expand, rapid growth inevitably follows (Mahmood et al. 2020). As a result, manufacturing activity is widely regarded a key aspect of sustainable development (Haraguchi et al. 2017). ...
Industrialization plays a crucial role in socio-economic development as it holds significant potential for creating new jobs, tightening the income gap, and promoting the use of advanced technology. As global competition intensifies, emerging economies emulate industrialized economies in accelerating manufacturing activity to improve national welfare and join the new global order. However, policymakers’ understanding of how competitiveness in the industrial sector helps developing countries accomplish their sustainable development goals must be deepened. This paper aims to analyze the connections among competitive industrial performance, renewable energy consumption, urbanization, and load capacity factor (LCF) in the BRICS economies for the period between 1990 and 2018. Robust evidence from the continuously updated fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) models shows that greater industrial competitiveness enhances environmental quality. The findings also reveal that income growth ultimately evolves as an ecologically friendly factor, confirming the validity of the load capacity curve (LCC) hypothesis. Another outcome of the econometric analysis indicates that renewable energy consumption contributes to the LCF, whereas urbanization damages the environment. Therefore, BRICS policymakers should concentrate on maintaining their competitiveness, implementing resilient urban planning, and promoting the usage of renewable energy to safeguard the environment while simultaneously achieving rapid economic growth.
Graphical Abstract
... The phenomenon of industrialization has historically been one of the primary catalysts behind economic development (Di Meglio and Gallego 2022;Yazgan et al. 2022), as proven by the prosperity of advanced economies in Europe and North America ( [UNIDO] United Nations Industrial Development Organization 2021). As in the previous millennium, industrial development keeps playing a pivotal role in the development process of emerging economies (Kniivilä 2007;Haraguchi et al. 2017). In a world of escalating global competition, developing nations are pursuing proactive measures emphasizing manufacturing activity's significance in the national economy. ...
This research aims to expand the existing literature by bringing a new perspective to China's environmental quality. Existing literature concerning China's environmental sustainability disregards competitive industrial performance, which allows the analysis of Sustainable Development Goal-9. The study investigates the impact of competitive industrial performance, economic growth, and renewable energy consumption on the environmental quality (repre-sented by load capacity factor) within the load capacity curve framework. Considering the positive and negative shocks in industrial competitiveness, the study runs the novel asym-metric ARDL with Fourier terms method to examine the non-linear connection between competitiveness and the environment. Empirical analysis shows that industrial competitiveness asymmetrically affects environmental quality and that the load capacity curve hypothesis is invalid in China. It is also evident that renewable energy contributes to environmental quality. Based on these findings, the study presents sustainable development policies for China within the framework of SDG targets. In this context, country's rapid growth and higher-order industrial competitiveness strategies need to be redesigned in order to increase the share of high-tech activities in total manufacturing and the portion of renewable energy in total energy use. Accordingly, the Chinese policymakers' primary objectives should be regulations that guide fundamental principles for enhancing environmental quality while preserving the country's rapid growth and competitive advantage in the industrial process. ARTICLE HISTORY
... It can be seen from the strong linkages of the manufacturing industry to other sectors, both based on forward linkage (use of inputs from other sectors) and backward linkages (providing inputs for other sectors) (Yülek, 2017). In addition, the manufacturing industry is vital in creating fast economic growth and can last for a long time, at least for the past two decades (Haraguchi et al., 2017). Sector growth will also encourage the availability of broader employment opportunities and better wages so that they can contribute to poverty alleviation (Lavopa & Szirmai, 2012). ...
This study aims to identify priority sectors in the manufacturing industry in North Sumatra during the economic recovery from Covid-19 pandemic and analyze the impact of these priority sectors based on forward-backward linkage analysis using data from I-O table and GRDP of North Sumatra in 2021. The results revealed three priority sectors in North Sumatra, the Food and Beverage industry; the Base Metal industry; and the Paper and Paper Goods industry, Printing and Reproduction of Recording Media.
... More complex manufacturing is an indicator of a country's economic health [1]. In today's industrial sectors, milling is a critical operation, and optimizing the milling process is essential for realizing significant financial advantages and enhancing customer satisfaction. ...
Throughout the cutting operation, among the most crucial steps is that has a direct impact on machining accuracy and product quality is tool wear. If you can accurately forecast how quickly tools will wear out, you can make the necessary adjustments early on, minimizing downtime and maximizing product quality. The evaluation of cutting tool wears during the production stage is crucial. The main objective of this study is to track tool degradation over time to guarantee regular tool changes and prevent workpiece waste and potential machine damage from excessive tool wear or unexpected tool breakage. For this reason, it is necessary to develop a system that is both intelligent and capable of providing accurate solutions to these issues. The criteria of intelligent production are great, though, and traditional methods simply cannot match them. Because of this, a deep learning-based innovative approach is presented to advance the precision of tool wear prediction. Parallel convolutional neural networks were constructed and used to achieve multi-scale feature fusion. To improve the model's efficiency, the channel attention mechanism was integrated with the residual connection to take into account the relative importance of each feature map. To prove that the created approach is superior, several experiments were carried out to anticipate tool wear, and the findings are more reliable and accurate than those obtained using existing methods. To guarantee the excellence of the engine cylinder and the steadiness of the machining procedure, a tool wear monitoring system was created. Using the PHM 2010 milling cutter wear dataset, tests were performed to validate the model effect. Based on the experimental data, this model has an average RMSE of 2.67 and an average MAE of 2.5. The trial outcomes proved the effectiveness of the suggested approach in evaluating the tool's wear.
... Indeed, the rise of late industrializers like China will continue to exert powerful demand effects on the global production of manufactures, as wages continue to rise in these places (Hallward-Driemeier & Nayyar, 2017). There is no reason to believe that participation in the global trade in manufactured goods, or more broadly any kind of goods that display the features historically associated with exporting manufactures (see the discussion in the theoretical framework), will cease to be a powerful potential route to economic development (Haraguchi et al., 2017). ...
In the 21st century, international trade in manufactured goods in the 21st century operates through global value chains (GVCs). This thesis investigates whether this fact has changed the playing field for catch-up industrialization, and what limitations and opportunities it provides for developing
countries integrating with GVCs. It does so mainly through an analysis of the automotive GVC, relying on both secondary data for a broad set of emerging economies and on primary empirical data from the South African automotive industry, which has successfully integrated itself with the automotive GVC over the last thirty years. The thesis puts forward a holistic theoretical understanding
of catch-up industrialization. Combining this theoretical understanding with a deep appreciation of GVCs provides a strong analytical framework for analyzing catch-up industrialization attempts and achievements in the 21st century. This combination of three strands in the literature – the classical development economics perspective, the evolutionary innovation and technology perspective, and the GVC perspective – is novel and is capable of resolving the shortcomings of analytical frameworks that only use one or two of these perspectives.
The thesis finds that South Africa’s integration into the automotive GVC has achieved a major tenet of catch-up industrialization, namely the overcoming of domestic demand constraints and the exploitation of economies of scale through the penetration of export markets for manufactures. It shows that the dynamics associated with the automotive GVC have weakened some of the benefits traditionally associated with exporting manufactured goods. Product development and design capabilities have not emerged among domestic South African automotive component firms. The foreign lead firms in the automotive GVC and their global sourcing strategies neither require nor incentivize domestic component manufacturers to build up such capabilities. This thesis also
demonstrates that the backward inter-industry linkages from tapping into automotive export markets have been disappointing. The GVC-specific dynamics of follow sourcing and the proliferation of manufacturing technologies and material standards have undermined more substantial backward
linkages from exports of automobiles. Using secondary data on other emerging economies participating in the automotive GVC, this thesis shows that many of the trends observed in South Africa are common in other countries as well. The
emergence of design capabilities in domestic automotive component firms is extremely rare, even in countries with larger automotive production and export volumes. Given the dynamics of global sourcing and lead firm power in the automotive GVC, the successful development of backward interindustry
linkages from vehicle and component exports arguably requires more scale than before the emergence of GVCs. However, positive experiences in South Korea, China, and Taiwan, and to some extent also in Thailand and Turkey show that participation in automotive GVCs can still be leveraged for catch-up industrialization in a more successful way than South Africa has done. Industrial policy to aid the exploitation of economies of scale in vehicle and component production, alongside an industrial policy that facilitates the indigenization of technology and innovation and design capabilities in domestic companies rather than just the localization of productive activities are key elements of such strategies. These types of industrial policy have been largely absent in South Africa, as this thesis demonstrates. While catch-up industrialization seems to have become more challenging due to the emergence of GVCs, it remains possible.
... The manufacturing industry is an important component of the national economy [1,2]. As one of the important engines of economic growth [3][4][5], the manufacturing sector is indispensable in increasing employment, advancing technology, and boosting exports [1,6]. Researchers typically use the manufacturing purchasing manager's index (PMI) to measure and forecast the trend of manufacturing [7][8][9][10]. ...
Events such as COVID-19 and the Russia–Ukraine conflict have significantly increased the uncertainty and volatility of global economic policies. In the context of economic globalization, the key question we investigate is whether global economic policy uncertainty will have different impacts on the manufacturing of the three major economies in China, the United States, and Europe Union. This study employs the time-varying parameter vector autoregressive (TVP-VAR) model to examine how global economic policy uncertainty (GEPU) affected manufacturing from March 2008 to March 2023. The empirical results show that the effects of GEPU are time varying; its short-term effects on Chinese manufacturing are slightly greater than its medium- and long-term effects, whereas its medium- and long-term effects on manufacturing in the United States (US) and European Union (EU) are significantly greater than its short-term effects. The impact of European debt crisis, the China–US trade war and Russia–Ukraine conflict on EU manufacturing is higher than that of China and the US, and the impact of the COVID-19 pandemic on China’s manufacturing is much smaller than that of the US and the EU; thus, Chinese manufacturing has a greater capacity for risk mitigation than US and EU manufacturing. This study not only provides a new perspective on the study of global economic policy uncertainty; it also provides new empirical evidence on how global economic policy uncertainty affects the manufacturing sector in China, the US and Europe and provides policymakers with guidance for decision making.
... This world of work is constantly transforming through industrial development that has more recently been characterised by automation, connectivity and technological innovation. Industrial competence in a global context constitutes the engine of economic growth and employment of most nations (Haraguchi, Cheng & Smeets, 2017). ...
The South African trade test is a mandatory end-point assessment that certifies an apprentice to practise as a qualified artisan after a specified period of training. Whereas the manufacturing sector has relied on the traditional trade test to provide assurance of an artisan candidate’s required level of competence, recent competence-development studies based on the COMET Model of competence development and measurement have challenged the ability of traditional task-based trade tests to prepare candidates adequately for integrated work processes. Studies in other contexts have shown the potential for COMET-based assessments not only to serve as a means of measuring competence, but also to develop it. This article reports on research that investigated how, through the application of COMET assessments, occupational competencies were developed beyond those measured by the traditional apprentice trade test. A mixed-methods, quasiexperimental approach produced strong evidence that COMET-inspired authentic assessments enhanced learners’ levels of competence and developed vocational identity among candidates who undertook such preparation for a trade test.
... The industrial sector also acts as a productive factor in maximizing the development of industrial sector development not only characterized by the volume of production but with the increasing variety of products produced (Haraguchi et al., 2017). ...
The industrial sector is a sector that plays a vital role in economic development because it can increase economic growth. The industrial sector also plays a role as a factor productive in maximizing the development of the industrial sector marked only by the volume of production but by an increase in various products produced. This study aims to determine the factors that influence investment mode; results in the East Java manufacturing industry. This research method uses secondary data collected from the Central Statistics Agency of East Java Province. The population in the study is data on foreign investment, manufacturing business units, foreign exchange rates, and inflation, and the data used as a sample is annual data (time series). Data collection techniques using documentation and library studies. The data analysis technique used in this research is multiple linear regression. The survey results show that manufacturing industries, foreign exchange rates, and inflation significantly affect the foreign investment variable simultaneously. In contrast, partially, manufacturing industries and inflation have no significant positive impact on foreign investment. In contrast, the foreign exchange rate has a significantly positive effect on foreign investment.
... Manufacturing-centered economies increase the complexity of exports and ensure economic prosperity for their citizens. A recent study also demonstrated that the great importance of manufacturing as an engine of economic development has not changed significantly since 1990 (Haraguchi et al. 2017). In other words, manufacturing continues to contribute significantly to the wealth of nations. ...
While the oil boom played a positive role in Azerbaijan’s economy by reducing poverty and increasing overall prosperity, the country’s industrial structure became lopsided and favored oil and gas production. Typically, the contraction of non-oil tradeable sectors (e.g., manufacturing) in oil-rich countries places an economic and social burden on society. The manufacturing sector can stimulate innovative actions triggered by policy decisions and improve the political and institutional environment. To determine the reasons for the one-sided industrial production, it is crucial to explain Azerbaijan’s economy with sound theories and elucidate the largest economic challenges. Thus, the Dutch disease (DD)-related de industrialization of non-oil manufacturing is the main focus of this dissertation. DD is a form of de-industrialization when natural resources are discovered or commodity prices skyrocket, resulting in unexpectedly high revenues. This situation shifts the attention of resource-rich governments from non-commodity production to commodity exports, motivating them to spend natural resource revenues within a short period of time. However, not all de industrialization of a particular nonoil sector is likely to be due to an oil boom. The general institutional environment and human capital also play critical roles. DD is a useful theory for explaining why in a small, open, and oil-rich country like Azerbaijan, non-oil manufacturing deindustrialization has occurred in parallel with the oil boom since 2005/06.
... In developing economies, there have been fundamental changes in the last two decades and the speed of industrialization and the importance of manufacturing industry have decreased compared to previous periods defi ned as pre-mature deindustrialization (Eichengreen and Gupta, 2009;Rodrik, 2016). On the other hand, Haraguchi et al. (2017) showed that there is no evidence indicating that the share of the manufacturing industry in GDP has decreased signifi cantly. However, the existing body of research generally shows that economic crises reduce production levels (Chalikias, 2017), investments (Martinez et al., 2019;Silva et al., 2022) and employment (Gennard, 2009) and cause deterioration of the sector in many other parameters. ...
... Tools account for up to 25% of the total cost and up to 20% of machinery downtime. Additionally, it is estimated that cutting tools are used between 70 and 80% of their useful life [1], which increases the need for systems to accurately evaluate cutting tool wear, as costs can be reduced by 10-40% by maximizing tool utilization [2]. These wear monitoring and evaluation systems have been developed for decades, using a variety of physical properties and sensors in order to obtain information that indicates the condition of the tools used, in addition to using different methodologies and analysis techniques for extracting information from the measurements taken. ...
In the manufacturing industry, computer numerical control (CNC) machine tools are of great importance since the processes in which they are used allow the creation of elements used in multiple sectors. Likewise, the condition of the cutting tools used is paramount due to the effect they have on the process and the quality of the supplies produced. For decades, methodologies have been developed that employ various signals and sensors for wear detection, prediction and monitoring; however, this field is constantly evolving, with new technologies and methods that have allowed the development of non-invasive, efficient and robust systems. This paper proposes the use of magnetic stray flux and motor current signals from a CNC lathe and the analysis of images of machined parts for wear detection using online and offline information under the variation in cutting speed and tool feed rate. The information obtained is processed through statistical and non-statistical indicators and dimensionally reduced by linear discriminant analysis (LDA) and a feed-forward neural network (FFNN) for wear classification. The results obtained show a good performance in wear detection using the individual signals, achieving efficiencies of 77.5%, 73% and 89.78% for the analysis of images, current and stray flux signals, respectively, under the variation in cutting speed, and 76.34%, 73% and 63.12% for the analysis of images, current and stray flux signals, respectively, under the variation of feed rate. Significant improvements were observed when the signals are fused, increasing the efficiency up to 95% for the cutting speed variations and 82.84% for the feed rate variations, achieving a system that allows detecting the wear present in the tools according to the needs of the process (online/offline) under different machining parameters.
... One of the 17 goals included in this Agenda is Goal 9: "Industry, innovation and infrastructure," the implementation of which is expected to influence the construction of stable infrastructure, promote sustainable industrialization, and foster innovation. While the components of this goal contribute to economic growth, their impact varies depending on a country's stage of development (Haraguchi et al., 2017;Raszkowski & Bartniczak, 2019). For example, industrial development in developed economies depends on the degree of adoption of new technologies and smart production processes (Ringel et al., 2016). ...
Research background: Sustainable development of the modern world represents an opportunity to preserve economic growth and technological progress, as well as social development, without limiting the possibilities of this development for past generations. The directions of this development are included in the 17 goals and 169 tasks of the 2030 Agenda for Sustainable Development. The achievement of these goals and the implementation of the adopted
... Manufacturing has been an essential driver of economic development throughout the history of capitalism [1]. Despite the proclaimed transition to the so-called post-industrial age, commodity production and distribution processes are still crucial in contemporary capitalist economies characterized by the growing services sector [1,2]. During particular periods in history, specific geographical production patterns were observable, and with the transition from one production regime to another, the range of locational outcomes was extended. ...
Manufacturing activities are at the heart of contemporary capitalist economies, with observable geographical patterns of production. Debates about the interconnections between transportation technology advancements and land use acknowledge that airports can influence the spatial distribution of firms, including those involved in manufacturing. However, the manufacturing-related literature describes the land-use mix of airports and their surroundings without an in-depth spatial economic analysis of the firms positioned near airports. This study aimed to conduct a spatial economic analysis of manufacturing firms positioned in the environs of Cape Town International Airport, South Africa. Primary data were collected through survey interviews conducted with the representatives of 23 manufacturing firms situated in the environs of the airport. The study discovered the potential existence of a spatial cluster of manufacturing firms. This cluster is characterized by dense inter- and intraindustry linkages within the study area. It is recommended that planning authorities and other stakeholders augment the clustering of manufacturing firms in the vicinity of Cape Town International Airport, which comprises firms with direct and indirect linkages with the airport.
... Case study Methodology Objective (Chatterjee et al., 2017) India MABAC Machining process selection (Zhu et al., 2018) China IVPFS-Entropy-MABAC Evaluation and assessment of potential product failure risks (Nunić, 2018) -FUCOM-MABAC Assessment of PVC manufacturing centres (Can and Toktas, 2018) Turkey TFS-DEMATEL-MABAC Assessment of potential warehouse risks (Chakraborty et al., 2020b) -R-Entropy-MABAC Machining process selection (Agarwal et al., 2020) India DEMATEL-MABAC Evaluation of jute fibers for manufacturing purposes (Bose et al., 2020) India ARAS-MABAC Material selection (Bose et al., 2020) India BWM-MABAC Optimizing the wear parameter of CrN/TiAlSiN coating strategic importance sectors such as national infrastructure and defence (Haraguchi et al., 2017). Manufacturing systems include the manufacturing and processing of items and result in either creation of new goods or in value addition. ...
Multiple Criteria Decision-Making (MCDM) is one of the most reliable and applicable decision-making tools to address real-life complex and multi-dimensional problems in accordance with the concepts of sustainable development and circular economy. Although there have been several literature reviews on several MCDM methods, there is a research gap in conducting a literature review on the Multi-Attributive Border Approximation area Comparison (MABAC) as a useful technique to deal with intelligent decision-making systems. This study attempts to present a comprehensive literature review of 117 articles on recent developments and applications of MABAC. Future outlook is provided considering challenges and current trends.
... Alternatively, industrial value formation is resulting in a paradigm shift in manufacturing due to different factors such as the increase of global resource restraints and market heterogeneity, big variations in individual demands, and sustainability-related issues, which are supported by many evolving technologies in the information and communication domain (e.g., the internet, big data, blockchain, cyber-physical system, cloud computing, and internet of things (IoT)). In fact, manufacturing has a leading role in the economic development of nations and the creation of social value (Haraguchi et al., 2017;Marconi et al., 2016). The evolution of the manufacturing paradigm began from a single species of craft production and continues to mass production, to multivariety production, and then to a small batch of flexible production. ...
Since 2008, many academics have increasingly paid attention to blockchain technology from different perspectives. In general, researchers desire to achieve global blockchain systems within a sustainable manufacturing domain; however, a number of technical challenges have come to exist in the recent decade, for instance, consensus algorithms and computing paradigms that can meet the privacy protection requirements of manufacturing systems. Therefore, an integrated decision-making framework called Pythagorean fuzzy-entropy-rank sum-Combined Compromise Solution (PF-entropy-RS-CoCoSo) is developed in this study, including two main phases. In the first phase, the PF-entropy-RS method is applied to obtain the subjective and objective weights of criteria to evaluate the technical challenges of transforming blockchain technology for a sustainable manufacturing paradigm in the Industry 4.0 era. The PF-CoCoSo model is then utilized in the second phase to assess the preferences of organizations over different technical challenges of the blockchain technology transformation for the sustainable manufacturing paradigm in the Industry 4.0 era. An empirical case study is taken to assess the main technical challenges of blockchain technology transformation for the sustainable manufacturing paradigm. Furthermore, a comparison analysis and a sensitivity investigation are made to demonstrate the superiority of the developed framework.
... Survival and activeness rate are main indicators of small business development [3]. As well as the role of industrial policy in future of manufacturing [4], therefore the importance of manufacturing in economic development [5] and employment [6] studied and substantiated by several researches. Small and medium enterprises (SMEs) are a noteworthy driver of economic development [7], being vital to most economies across the world, particularly in developing and emerging nations [8]. ...
In this paper, conducted econometric analysis to estimate role of industry in socio-economic development of Khorezm region is given. Coefficient of elasticity for assessing role of industry on GRP was used. Based on the results, scientific-practical proposals and recommendations were developed to increase role of industry on socio economic development and added value.
... When a forecasting approach may reduce the gap between forecast and real values, it improves the precision of the industrial planning process (Haraguchi, Cheng & Smeets, 2017). The most important reasons for ineffective forecasting models are market uncertainty and volatility (Rieg, 2010). ...
In order to improve efficiency and profitability for supply chain management analysis, the study suggests a demand, price, and cost forecasting model for the supply chain process. The aim of this study was to develop a supplementary mathematical model that would determine the optimal price, variable costs, fixed costs, and production volume for profit maximization while taking into account various constraints, correlations between variables, and growth rates, and also with external dynamic factors and equations that take into consideration growth rates of variables that are related to dynamic factors over the supply chain process, as well as constraints and correlations between variables, in order to estimate the optimal points of sales price, number of goods sold, average variable cost, and fixed cost for profit maximization.
... Numerous studies have demonstrated that concentration of industrial activity (especially manufacturing) plays decisive role in (regional) development (Wandel, 2009;Dinc, 2015;Haraguchi, Fang Ching Cheng & Smeets, 2016;Rosenfeld, 2017 There are cases related to the "old" industry and include examples such as the carpet industry in Dalton in the United States, the ceramic industry around Stoke-on-Trent in England and the lace industry located in Nottingham (Devereux et al., 2004). Understanding this process has attracted attention of academia and politics for more than a century. ...
Health behavior appears to be one of the key factors in prevention, which also affects the health economy. Maintaining health care puts increasing pressure on Hungarian society due to the growing aging. Healthy lifestyle and health consciousness provide effective help in maintaining a good level and longtime of quality of life. The impact of health behaviors in the health economy on financing means an increasingly important social problem. In Hungary, health behavior is low compared to European nations. The reduction of economic factors can be achieved by prevention, health improvement and years of health. The professional basis of this research are given by the individual image of health and the individual and social health behavior which are supported by the healthcare/health economy. Our research examines local health behavior and satisfaction with health care, in which we analyze the results in comparison with regional environmental conditions compare with the European health behavior research. The correlation between health economic factors and health behavior was revealed by secondary research, while the method of our empirical study is a questionnaire survey that presents health image, local health opportunities and relationships in several age groups. Based on the results of our survey, it became evident that the results of the Hungarian health behavior were the same in the central settlement of the western region of the country, where the economic indicators show a higher proportion than the national average. The low level of health consciousness and the low level of health behavior did not show significance, as is the case in European countries, in terms of higher health image and higher economic factors. On the other hand, in terms of educational attainment, there was a higher level of health awareness. Health as an economic factor plays a key role in employment, as healthy employees participate in the maintenance of the nation as an economic factor.
Keywords: health image, health behavior, health economy, prevention, life living standard
... Szirmai dan Verspagen (2015) menilai dampak dari sektor industri terhadap pertumbuhan ekonomi cukup positif dan tidak menemukan effect sektor jasa. Kajian Haraguchi et al. (2017) dalam konteks negara maju dan berkembang, mengungkapkan bahwa pertumbuhan yang dirangsang oleh industrialisasi masih kuat untuk negara-negara berkembang. Meskipun adanya dugaan belakangan ini berkurangnya pembangunan industri dan berkurangnya relevansi industri untuk pembangunan ekonomi dan perubahan struktural dalam perekonomian. ...
This study examines the economic structure of Rokan Hilir Regency from 2011 to 2020 using indicators of localization and specialization in 17 sectors. This study utilizes the Gross Regional Domestic Product data published by the Central Bureau of Statistics of Rokan Hilir Regency. Two models are used empirically: (i) localization quotient and (ii) specialization coefficient. The results of the analysis show that the economic sector of Rokan Hilir Regency relies on the mining and quarrying sector, as well as the agriculture, fishery, and forestry sectors, with the remaining fifteen sectors classified as non-basic. Seventeen economic sectors in Rokan Hilir Regency have a coefficient of specialization less than one, indicating that there is no prominent sector with significant development or specialization between 2011 and 2020.
... The development potential of the industry is huge (Dou et al., 2021a), and its productivity growth is relatively high, which can drive the development of other industries (Haraguchi et al., 2017). Especially, it is the fundamental support for economic development (Szirmai and Verspagen, 2015). ...
This study aims to analyze the factor affecting the urban industry development in Guangzhou. Based on push-pull-mooring theory, we explain the reasons for choosing the above indicators and use order parameters to analyze their impact on the urban industrial development. The results show that: (1) Environment has an obvious promoting effect on the urban industrial development. This shows that the current environment and the urban industrial development have reached a balance. (2) Technology has a positive impact on the urban industrial development, but it needs to go through the technology running in period smoothly. (3) Different from other factors, finance has a crowding out effect on industrial development. However, the development of finance will promote the rapid development of industry in Guangzhou. (4) The impact of finance, technology and green on UID is applicable to different development stages of UID, that is, these variables are related. Lastly, we provided development suggestions for Guangzhou. This will lay a foundation for promoting its industry.
One of the key features of modern economic growth is the process of structural transformation, which is the movement of workers from agriculture to manufacturing and services. In this study, the author identifies different routes to structural transformation that we see in the developing world. They address the theoretical, empirical and policy implications of the 'varieties of structural transformation' in low and middle income countries. Firstly, using a comparable high-quality dataset, they set out the stylized facts of structural transformation across the developing world. Secondly, they assess the classical and neoclassical approaches to structural transformation and review the recent theoretical developments in the literature. Thirdly, they undertake descriptive and econometric analysis of the drivers of structural transformation, and the relationship between structural transformation and inequality. Finally, they assess the policy implications of our study for developing countries. This title is also available as Open Access on Cambridge Core.
Purpose
This study aims to synthesize and analyze research on the Supply Chain Management Practices (SCMPs)-performance nexus, examine current knowledge, identify emerging trends, and provide plausible suggestions for future research engagements in the manufacturing sector in the context of Developing and Emerging Economies (DEEs).
Design/methodology/approach
Following a systematic review approach, this study analyzed 20 peer-reviewed scientific journal articles published between 2007 and 2021. The study sample was systematically selected from the Web of Science (WoS) and Google Scholar databases, following strict evaluation and selection criteria.
Findings
Numerous dimensions of SCMPs have been considered in the extant literature; however, six have stood out as the most common. In addition, operational performance stood out as the most widely investigated measure in the SCM literature. Moreover, SCMPs have predominantly shown positive effects on performance outcomes. Methodological issues that future studies should consider are suggested.
Research limitations/implications
The sample size was not sufficiently large relative to the rule of thumb set in the literature because of the scarcity of studies in the manufacturing sector in the DEEs context. Despite these limitations, the results of this study provide crucial insights into knowledge and practice.
Originality/value
This review is the first of its kind to examine the SCMPs-performance nexus in the context of DEEs. Based on the findings of this study, future research directions are proposed.
Industrial wastewater discharge has become the main cause of water pollution in China. However, the spatial interaction mechanism between industrial structure and water pollution is still unclear. Accordingly, we evaluated and analyzed spatiotemporal changes of the agglomeration pattern of pollution-intensive industrial enterprises and the evolution of the water environmental pollution pattern, as well as the correlation between them. The study results show that the polluting industrial enterprises were located mainly along the Yangtze River and Taihu Lake Basin in southern Jiangsu in 2013 and 2018. However, we observed a spatial trend of pollution transfer to northern Jiangsu. The industrial water pollution discharge presents the distribution pattern of facing rivers, seas, lakes and cities. Papermaking and paper products industry are the leading factors of COD and NH3-N pollution, with explanatory power of 0.3666 and 0.6201 respectively. The spatial positive coupling effect between the concentration degree of polluting enterprises and the intensity of water environment pollution discharge is 94.95% of the region. The spatial agglomeration of polluting industrial enterprises is an important cause of water environment pollution. They promote and couple each other, proving the existence of "Pollution haven" and "Porter hypothesis".
Industrialisation has long been synonymous with economic progress and structural change. A controversial aspect of industrialisation is the role of industrial policy in supporting this process. This chapter examines the role of industrial policy, particularly in low- and lower-middle-income economies, in the current economic environment by focussing on three mega-trends—the fragmentation of production based around production value-chains, technological breakthroughs leading to production based on digital technology or ‘smart production’ and moves towards the greening of industrial development. The basic message is that industrial policy in its ‘modern’ version is highly relevant for today’s high-income economies, but for low-income and lower-middle-income economies that are technology importers not innovators, there is scope for industrial policy to play a more traditional role.KeywordsDeveloping countryGrowthTechnological changeDevelopment planningDevelopmental state
En este trabajo se identifican factores de competitividad para los subsectores de la manufactura del Estado de México y a partir de ellos se construye un índice de competitividad mediante el análisis por componentes principales (ACP). De esta forma, se muestra que las industrias más competitivas en el periodo analizado fueron: la fabricación de equipo de computación; la comunicación, medición y de otros equipos, componentes y accesorios electrónicos; la maquinaria y equipo; los derivados del petróleo y el carbón; y la química; por el contrario, las menos competitivas fueron: la alimentaria, la fabricación de prendas de vestir; y la industria de la madera.
The literature on the effect of trade openness on industrialization shows contrasting results. Using a new empirical framework, we contribute in this paper to the removal of this indeterminacy by studying the influence of trade openness on industrialization in a sample of Sub-Saharan African countries. We use the new measure of trade openness and approximate industrialization through three complementary indicators: manufacturing value-added as a percentage of GDP, manufacturing employment as a share of total employment, and the industrial competitiveness index. Estimations are carried out by a two-step system generalized method of moments (GMM). Over the period 1985–2014, our results show that in Sub-Saharan Africa, the level of industrialization is a decreasing function of trade openness. The magnitude of this negative effect is conditioned by very low levels of foreign direct investment and human capital. Our results, which stand up to many robustness checks, seem to support the implications of the infant industry argument.
Purpose- In the study, the effects of sectors on the growth of OECD member countries were determined by using the Fuzzy Goal Programming method. These findings may help policymakers see sector impacts that help countries in their growth targets. The study aims to contribute to the literature in two ways. The first of these analyses is based on long-term economic growth and primary sector analysis. The second contribution is to propose an alternative empirical methodology with clustering analysis which is not used to obtain the basic assumption of homogeneity in the application of panel data analysis.
Methodology- The effects of sectors on the growth of OECD member countries were determined by using the Fuzzy Goal Programming method. In the second step, countries were divided into groups using K-means clustering analysis according to these impact values. With the the help of these weights, the growth dynamics of similar countries and the contributions of sectors to this dynamic were obtained.
Findings- Countries analyzed in terms of the contribution of sectoral growth rates to the growth rate of the country were divided into groups by cluster analysis. It is determined that the countries grouped in terms of the contribution of sectors to growth are divided into 5 groups. The first group has 10 member countries. The second group has 12 countries and the third group has 7 countries, the fourth group has 4 countries and only 1 country belongs to the fifth group. The countries in group 1 are Estonia, Turkey, Greece, Italy, Poland, Portugal, Lithuania, Latvia, Slovakia, and Slovenia. The countries in group 2 are Australia, Belgium, Czech Republic, Germany, Denmark, Hungary, Ireland, Mexico, Netherlands, Norway, Sweden, and New Zealand. The countries in group 3 are Austria, Spain, Finland, France, the Republic of Korea, Luxembourg, Switzerland, the USA, Israel, Costa Rica, the United Kingdom, and Japan.
Conclusion- Countries that have similar sectoral structures can analyze growth with panel data analysis, but it is important to form homogeneous groups while doing this
This paper examines the relationship between the industrialization pattern and the structural change process.
This approach fits in a global economic context characterized by Global Value Chains (GVCs), which shake up the
pattern of industrialization. In fact, by entering a value chain, economies are able to industrialize and export
high-technology goods without building a broad set of industrial capabilities. Using a panel of 117 countries over
the period 1995–2017, our three-step analysis, first reveals that manufacturing exports may not automatically
bring about economic upgrading - measured by the transformation of the export basket. Secondly, the intersectoral approach demonstrates that developing countries, for which industrialization no longer seems to be
the main source of continuous development, are specialized in ‘textiles and textile articles’ for the poorest
countries and in ‘machinery and mechanical appliances’ for middle-income countries. Finally, the intra-sectoral
analysis shows that both of these sectors can become traps leading to either sectoral concentration or product
concentration with low domestic value-added, both of which hinder the continuity of the transformation process
in the productive structure. We introduce the idea of an ‘industrialization curse’ to illustrate our findings.
This study assesses the contribution of the food and beverage industry to the Indonesian economy based on firm characteristics. The comparative descriptive statistical method describes a detailed mapping of the firm's character and the main supporting factors, such as processed commodities, firm size, island region, capital ownership, and exporters. The contribution of the food and beverage sub-industry varies; the vegetable and animal oils and fats industry is the largest and most effective. Small and medium firms have the lowest contribution compared to large firms. Firms in the Sumatra region have the highest contribution compared to firms in other regions. PMDN firms have a higher contribution than PMA firms. Non-exporting firms have a high average contribution compared to exporting firms. Based on the results, policymakers can concentrate on the potential to increase the contribution of a particular group of firms.
Indonesia and Thailand engage in the competition of Foreign Direct Investment (FDI) for Electric Vehicle (EV) industry. This study aims to identify determinant factor of FDI in EV industry, analyse the strategy to attract FDI, and see the competitiveness between Indonesia and Thailand in EV manufacturing. Qualitative method used by comparing Indonesia and Thailand through Porter Diamond Model. The model consists of four parts such as factor of conditions; demand conditions; related and supporting business; firm strategy, structure, and rivalry. There are 14 variables inside the four parts to analyse both countries competitiveness through comparing them in every variable. Results indicate that Indonesia has 5 out of 14 variables better Thailand while Thailand has 9 out of 14 variables that is better than Indonesia. Indonesia has the advantage on consumer side due to the possible lower price of EV while Thailand has the advantage on production activities
Currently, there is a very marked trend toward digitization and robotic control of manufacturing processes; thus the target is to optimize the economic resources. Therefore, the monitoring resources usage such as tools monitoring in the machining process become vital into enterprise optimization strategy. The above, since important savings in manufacturing processes can occur. The 304 stainless steels are widely used in the industry due to its mechanical and corrosion protection features. However, its metallurgical characteristics are difficult to machine. In that sense, this work is focused to analyze surface finishing during milling by varying different operational parameters. Then, a Deep Learning algorithm was applied in order to predict the work hardening through its surface finishing by means of the differences in sound recorded during machining. The results suggests that most of the energy is concentrated below 12 kHz. In addition, test specimens machined without coolant fluid yielded shallow surface strains in comparison to the machined ones with coolant fluid. Finally, the mean absolute percentage error for roughness prediction was about 28% suggesting a good correlation. Thus, the proposed methodology can be incorporated to an appropriate alarm and roughness measurements can be employed to detect the increase in work hardening. In both cases to prevent the tool failure.Graphical abstract
Additive manufacturing (AM) processes are a family of net-shaped manufacturing systems that are widely being used and adopted for their distinctive characteristics. Recently, AM processes have positioned themselves to be worthy of playing a role in revolutionizing manufacturing. In general, these processes promise a range of advantages, including, but not limited to, achieving unprecedented degrees of freedom in design, saving on resources and minimizing waste, and realizing higher degrees of functionality by manufacturing assemblies/devices rather than simply components, among others. In this chapter, the AM processes that are available for metal 3D printing will be reviewed and assessed. Processes such as laser powder bed fusion, directed energy deposition, material jetting, binder jetting, and sheet lamination will be explained in terms of their operational concepts, advantages, and limitations.
This paper probes the effectiveness of competitive industrial performance (CIP) and renewable energy in enhancing load capacity factor in top-10 CIP economies for the period 1990–2018. We run panel econometric techniques that address cross-sectional dependence, endogeneity and heterogeneity to provide policy recommendations with the applications of industry, innovation, and infrastructure (SDG 9), which is linked to affordable and clean energy (SDG 7) and climate action (SDG 13). In the empirical analysis, two different environmental quality indicators such as CO2 emissions and load capacity factor are used. While cointegration between variables cannot be detected in the emissions model, evidence for the existence of cointegration is presented in the load capacity factor model. The findings in the paper suggest that economic growth and competitive industrial performance adversely impact environmental quality, while renewable energy consumption and human capital can improve load capacity factor. The result shows that human capital and renewable energy consumption can be strong tools for stimulating load capacity factor in top-10 CIP economies. Countries with high competitive industrial performance need to return to a green economy without losing their competitiveness.
We employ a recent empirical strategy to estimate country-specific and time-varying total factor productivity (TFP) levels for the manufacturing sector of 63 countries over 40 years. The methodology is based on estimated country-specific production functions while accounting for cross-section dependence and nonstationary series. We then analyze the derived TFP series across the entire sample and several regional groupings (Asia, Europe and Central Asia (ECA), Middle East and North Africa (MENA), Latin America and the Caribbean (LAC), and the USA). Our analysis reveals the following. Firstly, the TFP that is common across countries has an upward trend with a significant slump in 2008. Secondly, the leading positions in terms of productivity in the manufacturing sector remained the prerogative of major developed countries. Thirdly, several countries succeeded in climbing the ladder through outstanding productivity growth. Fourthly, despite a clear hierarchy in terms of manufacturing productivity across regional blocs, all regions witnessed an increase in productivity over the period. Fifthly, there is evidence of convergence in the TFP across countries and within Asia and ECA before a potential break in 2008.
Enterprise Risk Management (ERM) has heterogeneously practiced between financial and non-financial sectors across the world, although it is a more holistic approach to risk assessment and administration at all enterprise levels. Academics have studied the dimensions of ERM implementation, but there is no complete picture of the determinants and implications of such ERM dimensions yet, especially in developing countries. In this regard, through an extensive literature view, this study has found a theoretical link that exists between internal factors, external factors, structure, and process as main dimensions of ERM implementation and financial performance in developing countries' manufacturing firms. The conceptual model also examines the moderation role of the organizational culture in the relationship between the dimensions of ERM implementation and manufacturing firms' financial performance, where this study has also theoretically proven the importance of organizational culture as a major determinant in influencing the implementation of ERM dimensions and enhancing financial performance in developing countries' manufacturing firms. Based on this study's theoretical results, this study contributes to promoting awareness among manufacturing firm managers in developing nations about the importance of OC to enhance ERM dimensions implementation and in improving the financial performance of their companies.
Keywords: Enterprise Risk Management; Organizational Culture; Financial Performance; Internal Factors; External Factors; ERM Structure; ERM Process
I document a significant deindustrialization trend in recent decades that goes considerably beyond the advanced, post-industrial economies. The hump-shaped relationship between industrialization (measured by employment or output shares) and incomes has shifted downwards and moved closer to the origin. This means countries are running out of industrialization opportunities sooner and at much lower levels of income compared to the experience of early industrializers. Asian countries and manufactures exporters have been largely insulated from those trends, while Latin American countries have been especially hard hit. Advanced economies have lost considerable employment (especially of the low-skill type), but they have done surprisingly well in terms of manufacturing output shares at constant prices. While these trends are not very recent, the evidence suggests both globalization and labor-saving technological progress in manufacturing have been behind these developments. The paper briefly considers some of the economic and political implications of these trends.
Although both China and India are labor-abundant and dependant on manufactures, the two rely on very different export mixes. Only one product—refined petroleum—appears in the top 25 products for both, and services exports are roughly twice as important for India as for China, which is much more strongly integrated into global production networks. Even assuming India also begins to integrate into global production chains and expands exports of manufactures, there seems to be opportunity for rapid growth in both. Accelerated growth through efficiency improvements in China and India, especially in their high-tech industries, will intensify competition in global markets leading to contraction of the manufacturing sectors in many countries. Improvement in the range and quality of exports from both countries has the potential to create substantial welfare benefits to the world, and to each other, and to act as a powerful offset to the terms-of-trade losses otherwise associated with rapid export growth. However, without efforts to keep up with China and India, some countries may see further erosion of their export shares and high-tech manufacturing sectors.
This study has been prepared within a joint project of UNU-MERIT, UNU-WIDER, and UNIDO on Pathways to Industrialization in the 21st Century: New Challenges and Emerging Paradigms. UNU-WIDER gratefully acknowledges the financial contributions to the project by the Finnish Ministry for Foreign Affairs, and the financial contributions to the research programme by the governments of Denmark (Ministry of Foreign Affairs), Finland (Finnish Ministry for Foreign Affairs), Sweden (Swedish International Development Cooperation Agency—Sida) and the United Kingdom (Department for International Development). Abstract This paper examines the theoretical and empirical evidence for the hypothesis that manufacturing is the main engine of growth in developing countries. The paper opens with an overview of the main arguments supporting the engine of growth hypothesis and then examines each of these arguments using a mix of statistical analysis of secondary data and secondary literature. The paper concludes that manufacturing will continue to be important in accelerating growth and achieving catch-up in developing countries. However, compared to the past 60 years, market service sectors will become relatively more important as potential sources of growth and catch up.
China’s opening to trade is interpreted as a shift in world average factor endowments, which altered the comparative advantage
of other countries. In the rest of the world on average, this shift lowered the share of labour-intensive manufacturing in
the sum of labour-intensive manufacturing and primary output by 1–3.5 percentage points, and the corresponding export share
by 1.5–5 points. The de-industrialising effect varied among countries, and was clearest in East Asia. It was significant,
but not big enough to be a serious threat to growth or equity in most other developing countries.
KeywordsDevelopment–Heckscher-Ohlin theory–China–De-industrialisation
John Cornwall built his analysis of Modern Capitalism on a combination of two strands of thought; the Schumpeter-Svennilson view of capitalist development as a process of qualitative change driven by innovation and diffusion of technology, and the Kaldorian idea of static and dynamic economies of scale in manufacturing as the driving force behind economic progress in the industrialized world. Combining these (and other) insights into a coherent perspective on modern economic growth was an important achievement in itself. He also provided convincing evidence from a group of industrialized countries in the fifties and sixties that supported his interpretation of the events. What we have done in this paper is to update and extend his empirical analysis using a larger sample of countries and more recent data. We have found that the Schumpeter-Svennilson perspective of growth as a process of qualitative (and structural) change, and the emphasis on the importance of skills and flexibility, has a lot to commend it. On the second set of ideas the evidence is more ambiguous. At least for many of the technologically and economically most advanced countries, manufacturing does not seem to be the ‘engine of growth’ assumed by Kaldor and Cornwall.
This paper revisits the role of the manufacturing sector during the middle-income stage of development. By exploiting a large dataset that covers different sectors, we find that in the middle-income stage, manufacturing pulls along all the other sectors, including the services sector. A decline in manufacturing growth negatively affects the growth of all the other sectors, in both the short-run and long-run. Additionally, we attempt to identify the underlying mechanisms of the essential role played by manufacturing during this development stage. We find that a larger share of manufacturing in the economy not only promotes gross private saving ratio but also accelerates the pace of technological accumulation. Our empirical findings in this paper indicate that the manufacturing sector is still the key engine of economic growth for middle-income economies.
The scale of manufacturing employment in China dwarfs the numbers of manufacturing workers in other countries; China's manufacturing sector has shed surplus workers from inefficient state-owned factories, while increasing employment in the private sector.
The objective of this paper is to evaluate the role of the manufacturing sector in the development process based on two laws of Kaldor. The first law states that the higher the growth of the manufacturing output, the more significant is the growth rate of the economy's product as a whole. The second law, known as the Kaldor-Verdoorn law, establishes a deterministic relation between the growth of manufacturing productivity and manufacturing output growth. This paper begins showing stylized facts of the production and exports of manufactured goods to show that these remain related to the income level of countries in recent years. Thereafter, a theoretical reflection on the importance of manufacturing in the process of economic development is performed, associating it to the manufacturing exports and to the exchange rate regime. Then, the paper performs a Kaldorian model systematization to assess the importance of manufacturing and its exports on the economic development. Econometric tests are performed based on a dynamic panel data for a sample of 63 middle and high-income countries, excluding major exporters of fuels for the period between 1990 and 2011, to analyze whether there is any difference in growth dynamics between these two groups. Estimates attest the occurrence of the two Kaldor laws, demonstrating that output growth in the manufacturing sector is essential to increasing economic growth and productivity, particularly in middle-income economies. The results also confirm that manufacturing exports are relevant to the development process and that the exchange rate contributes to this process in middle-income countries.
Unlike economies as a whole, manufacturing industries exhibit strong unconditional convergence in labor productivity. The
article documents this at various levels of disaggregation for a large sample covering more than 100 countries over recent
decades. The result is highly robust to changes in the sample and specification. The coefficient of unconditional convergence
is estimated quite precisely and is large, at between 2–3% in most specifications and 2.9% a year in the baseline specification
covering 118 countries. The article also finds substantial sigma convergence at the two-digit level for a smaller sample of
countries. Despite strong convergence within manufacturing, aggregate convergence fails due to the small share of manufacturing
employment in low-income countries and the slow pace of industrialization. Because of data coverage, these findings should
be as viewed as applying to the organized, formal parts of manufacturing. JEL Codes: O40, O14
This article tests whether manufacturing has acted as an 'engine of growth' for the Indian states in the post-1990s.Our methodology involves regressing the state domestic product (SDP) growth rates on growth rates of manufacturing. If the coefficient of manufacturing growth is higher than the share of manufacturing in SDP, this is interpreted as supporting the engine of growth hypothesis. The results indicate that manufacturing has acted as an engine of growth in the post-nineties despite its declining share over the period. However, our study rules out the role of scale economies propelling productivity growth in the sector. Our analysis also suggests that it is primarily factor accumulation and not productivity growth that is driving output. Our characterisation of states based on output growth, TFP growth and employment growth suggests that for some states the current trend of growing without creating employment and improving TFP will not be sustainable.
This paper focuses on an interesting and controversial debate on the factors underlying economic growth. Kaldor's belief that increasing returns to manufacturing production are the driver of growth is confronted with data from 11 representative countries spanning nearly two decades. Various alternative and complementary specifications are investigated using a panel estimation methodology. The results show that growth in manufacturing output is an important determinant of both productivity growth and gross domestic product growth, and that, despite its increasing size, the service sector does not appear to play a similar role.
Since the middle of the eighteenth century, manufacturing has functioned as the main engine of economic growth and development. However, in recent research, questions have been raised concerning the continued importance of the manufacturing sector for economic development. This paper reexamines the role of manufacturing as a driver of growth in developing countries in the period 1950-2005. The paper makes use of a newly constructed panel dataset of annual value added shares (in current prices) for manufacturing, industry, agriculture and services for the period 1950-2005. Regression analysis is used to analyse the relationships between sectoral shares and per capita GDP growth for different time periods and different groups of countries. For the total sample, we find a moderate positive impact of manufacturing on growth in line with the engine of growth hypothesis. Splitting our sample into three subperiods, we only find a direct effect of manufacturing on growth for the middle period 1970-1990. We also find interesting interaction effects of manufacturing with education and income gaps. In a comparison of the subperiods, it seems that since 1990, manufacturing is becoming a more difficult route to growth than before.
Demonstrates that technical change is attributable to experience. The cumulative production of capital goods is used as the index of experience. New capital goods are assumed to completely embody technical change. The assumption is made that the model will be operating in an environment of full employment although reference is made throughout to the case of capital shortage. The implications of this model on wage earners are discussed, and profits and investments are examined. The rate of return is determined by the expected rate of increase in wages, current labor costs per unit output, and the physical lifetime of the investment. Learning is an act of investment that benefits future investors. Further analysis shows that the socially optimal ratio of gross investment to output is higher than the competitive level. (SRD)
Kaldor's 'laws' on 'manufacturing as the engine of growth' have been tested using cross-country data, mainly from developing countries, for the period 1960-1994. Instrumental variable techniques were used to explore problems associated with simultaneity and spuriousness. It has been found that manufacturing output growth rate is exogenous as Kaldor envisaged and his 'laws' are applicable to most of the developing world.
The purpose of this paper is to analyse whether specialisation has increased in European Union countries, and to determine whether specialisation patterns are consistent with trade theories. I present evidence of increasing specialisation in European Union countries between 1968 and 1990. I identify which industries have increased in geographical concentration and show that the characteristics of these industries are consistent with what is predicted by trade theories. The industries with increasing geographical concentration are characterised by high scale economies and high proportions of intermediate goods in production, providing support for the new trade theories and the economic geography theories.
This paper in an attempt to examine if the manufacturing sector is still the engine of growth delineates the inter-connections among several activities based on time series data on employment in different components of the organized sector in India. The analysis is pursued in the vector auto-regression (VAR) framework taking into account the results of variance decomposition analysis and the impulse response function. The findings suggest that some of the activities are growing independent of the manufacturing sector. Nevertheless manufacturing, construction and community, social and personal services are the most important drivers. Finally, the paper predicts the informal sector employment based on the magnitude of employment in different components of the organized or formal sector. Given the narrow margin of error of forecast the paper argues that in the absence of time series information on total employment, the time series on organized sector employment can be used for necessary predictions and planning required for employment and poverty.
Western Europe has a large number of sovereign micro-states and, in addition there are also a number of regions of the European Union (EU) which have an unusually high degree of autonomy. This paper examines the economic performance of these micro-states and autonomous regions, which is found to be superior to that of adjacent EU regions. The strong economic performance of these micro-states and autonomous regions is shown to be closely related to activity in the financial services sector, tourism and, where present, natural resources. Complex differences among the group of micro-states and autonomous regions are also revealed.
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