KDI - Korea Development Institute - RESEARCH - Research Areas

Summary

Policy Study KOR Analyzing the Productivity Spillovers of Foreign Direct Investment (FDI) Considering the Characteristics of Industrial Complexes

Using large-scale panel data at the business unit level in South Korea, this study analyzes how the presence of FDI firms in industrial complexes impacts the productivity of domestic firms through vertical spillovers. Due to industrial agglomeration, FDI firms in industrial complexes are expected to engage more in vertical interactions with local firms and to procure a higher proportion of inputs locally compared to those outside the complexes. Therefore, the backward linkage effects of FDI firms in industrial complexes on domestic firms are anticipated to be more significant than FDI firms not operating in these complexes. To test this hypothesis, it constructs an indicator for the backward linkage effects of FDI and analyzes its relationship with the total factor productivity (TFP) of Korean manufacturing establishments.

This study finds that FDI firms located in industrial complexes exhibit significant positive backward linkage effects on the productivity of domestic firms. In contrast, the backward linkage effects of FDI firms outside the complexes are significantly lower and sometimes negative when domestic firm productivity is measured by value added per employee. These results support the hypothesis that, at least from 2010 to 2019, clustering into industrial complexes positively affects the productivity of domestic firms through the backward linkage effects of FDI firms.

Summary

KDI Policy Forum Impacts of Climate Policies on Industrial Competitiveness in Korea

■ As carbon reduction targets are being strengthened globally, it is increasingly important in Korea to comprehend the impact of two major greenhouse gas (GHG) reduction policies, Target Management System (TMS) and Emissions Trading System (ETS), on industrial competitiveness.

- ETS relies more on individual firms’ economic incentives compared to TMS, which is a command-andcontrol regulation.

■ While the transition from TMS to ETS in 2015 is found to have partially alleviated the burden for manufacturing firms, there is a need to enhance policy effectiveness by acknowledging their limited performance in reducing carbon emissions thus far.

- While TMS was introduced in 2011 with the aim of enforcing emissions reduction and enhancing energy efficiency across different sectors, heavy emitters have been managed separately through ETS since 2015.

- Knowing the low abatement performance in the manufacturing industry after mid-2010, the reduced burden can be attributed to two factors: i) improvement in efficiency resulting from the transition, and ii) alleviation of the burden through the provision of free allocations.

- The policy efforts should aim for a greater reduction by strengthening the targets for the regulated firms, which is in line with the reinforced policy goals announced in October 2021.

■ Stricter goals are inevitable in the future, and therefore, policymakers must endeavor to bolster the sustainability of the manufacturing sectors by developing a detailed roadmap based on multiple indicators.

- Taking into account the varying impacts of GHG reduction policies on the competitiveness based on the energy intensity and emission intensity of each sector, the roadmap needs to be carefully crafted in order to impose a feasible burden on the regulated firms.

Summary

Policy Study KOR Impacts of Climate Policies on Industrial Competitiveness in Korea

This study quantifies the impact of major climate policies on industrial competitiveness in manufacturing sectors that require large-scale decarbonization in the future. Two climate policies, the Target Management System for GHG and Energy (TMS), a command-and-control type policy introduced in 2011, and the Emission Trading System (ETS), a market-friendly policy introduced in 2015, are mainly considered, where both policies cover selected companies that emit heavily. Based on pathways through which climate policies can affect industrial competitiveness, we estimate impacts of the abatement burden through channels of the level of energy intensity (energy consumption per production) and the level of emission intensity (emissions per energy use) by covering 2011~2019. Furthermore, based a firm-level survey, we estimate determinants that drive and hinder the implementation of abatement practices and determinants that enhance environmental and economic performance.

As a result of the analysis, during the last 10 years (2011-19) it was confirmed that the higher the level of energy intensity and emission intensity, the negative impact on production cost and value added, which are direct indicators of the manufacturing industry’s competitiveness, was greater. Impacts become greater when limiting to the energy-intensive and emission-intensive sectors, such as “iron and steel”, “non-ferrous metals”, “chemicals”, “petroleum refining”, and “non-metal” industries. Meanwhile, it is found that there is no signficant impact on sales. Overall, it is understood that the upward pressure on production costs was at a level that could be endured through a decrease in value added rather than leading to a decrease in production. Furthermore, it is confirmed that while negative impacts on competitiveness through energy-intensity has gradually increased during the analysis period, that through emission-intensity has decreased after the introduction of ETS. Meanwhile, burden of carbon abatement has not yet been realized in earnest for some large companies that have been active in introducing abatement measures. Nevertheless, in line with the strengthening of climate policies in the future, policy considerations to ensure the sustainability of the manufacturing sector should be accompanied.

Policy suggestions this study provides are tow-fold. First, it is necessary to understand the extent to which TMS and ETS actually affect and to identify detailed impact pathways. Considering the results of previous studies and this study, there is a possibility that in the manufacturing industry the distribution of abatement burden is not proportional to that of emissions. Therefore, it is essential to broaden the perspective and consider impact pathways at the level of the production and supply chain. Second, it is necessary to set TMS targets and allocate ETS allowances using multiple indicators. Industries with high direct emissions such as fuel combustion can lower their emission intensity through their own strategies (switching to environmentally friendly fuels, etc.), while in industries with high indirect emissions, energy intensity adjustment may be a more effective means than emission intensity adjustment. Altogether, it needs to enhance the sustainability of manufacturing industry in the process of decarbonization by differentially allocating as much burden as necessary to the firms under TMS and ETS, and by alleviating the burden that firms outside the system may bear in a disproportionate way to their emissions.

Summary

KDI Policy Forum Trade Liberalization and Manufacturing Productivity Changes in Korea During the Past Three Decades

■ One of the key goals of trade policy, which includes FTAs, should be the enhancement of productivity in the overall economy through the improved productivity of the tradable sector.

- This can be achieved by ① enhancing the productivity of existing firms, and ② eliminating lowproductivity firms to improve overall industrial productivity.

■ This study examines the effects of Korea’s trade policies in terms of bolstering the productivity of existing firms in the tradable sector. It shows that Korea’s FTAs with major trade partners, such as the EU, US and China, have failed to provide meaningful impetus.

■ As for raising productivity through firm exits, this study confirms that it has a positive impact on raising total factor productivity (TFP) across industry. However, further studies are needed to substantiate that this is owed to trade liberalization.

■ To raise overall economic productivity, future trade policies should be designed ① to enhance the productivity of existing firms, and ② expel those with low productivity. A trade policy-driven expansion of imports and exports could brighten the prospects for the tradable sector, encouraging firms to boost productivity.

■ It is imperative that efforts are made to increase the positive effects of trade liberalization and minimize the negative effects on society by shifting the focus of the current Trade Adjustment Assistance system towards supporting workers instead of firms, and improving retraining and vocational programs for the unemployed, among others.

Summary

Research Monograph KOR Job Creation Strategy in an Knowledge-based Economy

Job creation is now at the top position in the Korean government’s agenda. But the means for achieving this goal as well as general understanding on the issue lag behind Korea’s rapid transition to a knowledge-based economy. Direct job creation constitutes an important part of government policy, and the business calls for labor market flexibility. This reports shows that Korea’s job creation mechanism has shifted from one of a manufacturing economy’s to that of a knowledge economy, and knowledge has been the major driving force of job creation since the 2000s. Manufacturing employment has peaked as early as in 1990, and job creation thereafter has been fueled by the growth of knowledge intensive service industry jobs as in any advanced economies. If we presume two sectors in an economy, tradable and non-tradable, a knowledge intensive service job in the tradable sector creates twice as many jobs in the non-tradable sector as a manufacturing job. The knowledge intensive jobs themselves are created by innovation in manufacturing as well as in services and by business profits. Higher service to manufacturing jobs ratios, the growing share of investment on intangibles, concentration of jobs in the Seoul metropolitan area, all such major changes are phenomena in a knowledge-based economy. Job creation has been active with a rapid transition to a knowledge economy and has slowed down with its weakening.

The nontradable sector is larger in numbers of jobs, but the tradable sector is the engine and the determinant of quality of jobs in an economy. Hence the focus of this report is on the latter. Paradoxically the nontradable sector is less related to the economy’s competitiveness, which allows rooms for labor market policies in the sector.

This report covers firm productivity and knowledge capital, local job creation multipliers, patents and firm values, knowledge property right protection, and university-company research collaboration issues. But this list is not at all comprehensive and further research is called for in order to set up a knowledge economy jobs strategy, in areas such as place-based policies, R&D strategies for job creation, et cetera.

Summary

Policy Study KOR Contract Type Selection and Economic Effect in Large-scale Retail Industry

This study analyzes the status of contract types between large retailers and manufacturing suppliers. It also demonstrates the factors affecting the choice of contract type as well as the economic effect of the contract type on the supplier’s performance.

The study found that direct purchase transactions accounted for 47% of total transactions, with the highest proportion, while contract types differed by product group and by industry, depending on the stability of demand, the importance of professional salesman service, and the degree of inventory risk.

The regression analysis showed how transaction cost and bargaining power affected the selection of contract types. As for transaction cost, the proportion of direct purchases tended to increase as retailer’s distribution system was developed, the more the supplier trusted the retailer, and the lower the level of interior decoration or specialized salesperson required for sales process. Regarding the bargaining power of the supplier, the proportion of direct purchase increases as the number of trading companies increases, and the type of transaction and the decision of margin ratio were based on the supplier's proposal.

Furthermore, the paper found that a supplier’s sales tend to decrease on average as the gap in the bargaining power between the retailer and the supplier increases, and the portion of the special contract purchase increases.

As a policy recommendation, this paper suggests that policy for enhancing supplier bargaining, including customer diversification, should be strengthened and that retailers should double their innovation efforts in the face of rapidly changing retail markets.

Summary

KDI FOCUS Smart Policies for Smart Factories

□ Smart factories have been found to enhance the productivity of the overall production process, proving to be an appropriate policy as a key strategy for domestic manufacturing innovation. However, to maintain its effectiveness even when the scale and recipients of policy support are expanded, there should be improvements in the policy details and action plans. Above all, making factories smart requires not only the adoption of relevant technologies, but also proper management practices and organizational operations necessary to utilize the new technologies. The government should place the policy priority on helping firms to align workers‘ incentives with the technological change. It is also necessary to smartize the governance system of the overall manufacturing innovation strategy which include smart factories.

- The scale of the smart factory fostering policy, a key element of Korea's manufacturing innovation strategy, is gradually expanding. It is time to check the effectiveness of the policy.

- This study provides policy implications by measuring the level of smartness at the factory-level, analyzing economic effects from enhanced smartiziation, and examining factors that can facilitate the smartization.

- Smart factory is a factory in which workers and equipment exchange information and thus can make better decisions.

- Recent technological progress is drawing much attention to smart factories, but adopting the technology is a way of helping factories become smarter, and not directly transforming them into a smart factory.

- The level of smartization in a factory can be measured based on their levels of system interconnection and data sharing and utilization.

- According to the analysis, the level of smartization in Korean firms is low overall with a huge gap between factories.

- Smartization is found to have varying effects on factories’ performance depending on the type of production process, but in general, smartization helps to significantly improve productivity.

- The US-China trade conflict could directly/indirectly reduce Korea's exports, which in turn, could lead to a fall in GDP.

- The nature of smartization is a fundamental transformation of the manufacturing system, using data as a proxy, and not replacing human labor through automation.

- Automation is likely to curtail labor demand while smartization is found to have different effects on different occupations. In particular, the demand for technicians specialized in process management is not expected to decrease.

- Responsive measures should be developed to support occupations that will likely experience a contraction in employment amid factory smartiziation.

- The adoption of technologies for smartization can be helpful only when it is well aligned with workers’ incentives.

- Technological and organizational factors that determine the level of smartization are complementary, meaning that it would be difficult to smartize by focusing on just one factor.

- To make the policy work more effectively, companies should be provided with management training and consulting support so that they can prepare for technological change. It is recommended support programs for consulting, training and human resource development are systemized.

- The government’s support system needs to be smartized to enhance the efficiency of support and to provide companies with more practical information.

- Effective educational and retraining programs should be provided, targeting occupations that will likely face a decrease in demand, through cooperation between large enterprises and SMEs and between suppliers and users.

- A public-private-academic network platform holding real authority should take the driving role in developing manufacturing innovation strategies and responding to the coming changes.

Summary

Research Monograph KOR Smart Factory: Economic Impacts and Policy Implications

Smart manufacturing, also known as Industry 4.0, represents the digital transformation that modern manufacturing is undergoing. Rather than employing individual technologies for traditional automation, firms try to make the whole manufacturing process more integrated and flexible to meet fast-changing demand. Collecting and utilizing data plays a crucial role in the integration of production.

As digital capabilities become more critical in firm survival and industry competitiveness, major countries put forward strategies to promote and support firms' digitization. The Korean government has also pursued policies to encourage firms, small and medium-sized in particular, to adopt smart manufacturing. The goal is to have 30,000 smart factories by 2022.

Despite its importance and difference from traditional automation, there has been little effort to understand the economics of smart manufacturing. This report is the first comprehensive study to measure the level of smart manufacturing, examine its economic impacts, and identify the determinants of adopting the smart factory. Based on the concrete quantitative evidence, this study provides policy suggestions for the effective digital transformation of manufacturing.

From a technical point of view, a smart factory is defined as "Digitization and networking of all processes, products, and resources." As the smart factory integrates the factory system to digitize and network all production activities―and thereby go beyond simple automation―it can improve the efficiency of the production process, flexibly cope with breakdowns and sudden changes in supply and demand, and even help to develop new products and predict future demands.

We first measure the level of the smart factory by two factory-specific characteristics: (1) the degree in which all the production activities in the factory are interconnected systemically (system integration) and (2) the degree to which the factory collects, shares and utilizes data for decision-making (data share and use). To collect necessary information, we surveyed about 1,000 domestic plants in the Korean manufacturing industry. From the survey result, we find that the sample factories were generally low in the smart factory level, but there was a modest improvement between 2015 and 2017. We also find a significant gap between factories in both levels and change.

Chapter 2 examines the effects of factory smartization on the three key performance indicators (KPI) of the factory: productivity, cost efficiency, and product variety. For productivity, we find that daily production increases when the smart factory level increases. We find similar effects on other KPIs, which are heterogeneous by the type of production process. For example, we find a significant reduction in the lead time only from continuous-process factories, while we observe a reduction in the defect rates, a cost-efficiency indicator, only from assembly line-process factories. For product variety, we find the most substantial positive effect from the batch (and job shop) process.

Chapter 3 explores the employment effect of factory smartization and compares it to that of automation. While economists find negative impacts of individual technologies, such as robots and AIs, engineers argue that smartization, a system-wide change distinct from automation, creates new labor demand for constant reconfiguration and training of workers. This chapter tests the hypothesis by examining the relationship between planned smartization and predicted labor demand by worker groups (production workers, technical engineers, and office workers). The results support the engineers' prediction. While automation is expected to decrease the demand for all three classes, improvement in the production process is not likely to decrease the demand for technical engineers. Smartization in even greater scale - integration of all business activities - is expected to have no adverse effects on all three worker groups. Having said that automation and smartization are different in their job impact, this chapter also emphasizes that there is considerable heterogeneity across firms and workers. Production workers and office workers, young and old workers, and workers at low-level smart factories are those more vulnerable to production smartization. Policymakers should encourage firms to provide them with proper retraining and reallocation program.

Given the effects of the factory smartization on performance and employment, it is important to understand what factors determine the level of smartization. Chapter 4 investigates the determinants including the adoption of technologies relevant to the smart factory with a focus on the role of complementary organizational features. We find that there is a complementarity between human resource management practices and technology adoption in driving smartization. Technology adoption leads to smartization, and such effect magnifies disproportionately with the level of structured human resources management. We also find other magnifiers, such as the presence of an ICT division and CEO's willingness to upgrade the manufacturing system.

The complementarity between technology and organizational practices suggests the need to reconsider the current policy direction. First, before providing support, there needs to be an accurate diagnosis of the target firm's organizational practices, needs, and expectations for the effects of the smartization. This “pre-consulting & post-support” approach will be more effective than merely helping firms to introduce specific technologies. Second, we propose to build a platform that provides one-stop services for SMEs. Third, we make suggestions to make the government's support system smart (government smartization) to increase the effectiveness of the support.

Chapter 5 concludes this study by proposing a plan to reform the governance for manufacturing innovation. The key message is that the private sector should play a central role in both policy-making and implementation process for policies to be effective in this transforming digital era. We suggest to organize a council by benchmarking the Germany’s Industrie 4.0 platform. The council is a network of representatives from business, science, government ministries and trade unions. The council is expected to present the economy- wide digitization strategy. We also argue that cooperation between SMEs and large corporations is crucial in pursuing smart manufacturing in the Korean business environment. We discuss possible policy measures to facilitate their cooperation and make the environment more favorable to SMEs.

Summary

Policy Study KOR Measuring Social Returns to R&D and Two Countervailing Spillovers

Corporate R&D investment creates additional economic value in the process of product development and technology transfer to related companies. The ripple effect of corporate R&D investment has been studied in various ways. It is known that there is a positive spillover effect; although the size of R&D investment returns varies depending on the type of technology, industry across country and time.

The purpose of this study is to accurately estimate the returns of R&D investment and the magnitude of the spillover effect of Korean manufacturing companies. Specifically, this study analyzed the private and public returns to R&D and spillover effects of 6,172 firms in industries where R&D investment was more than 1% of total private R&D investment in 2016. In particular, overestimations of the spillover effect of R&D was prevented by reflecting not only the positive effect of R&D but also the negative effect caused by competitive factors among firms.

The results of the analysis on corporate financial and patent data for 2007-2016 revealed that the average for the social and private returns of domestic R&D investment was approximately 14.24% and 11.77%, respectively―making the spillover effect about 2.47%p. The industries with high R&D spillover effects are the Manufacture of pharmaceuticals, medicinal chemical and botanical products, Manufacture of medical, precision and optical instruments, watches and clocks, and Manufacture of electrical equipment. The industries with small R&D spillover effects are the Manufacture of other transport equipment, and Manufacture of fabricated metal products, except machinery and furniture. As a result of examining the differences in social return by characteristics of firms, it was found that the larger the employment size, the larger the patent registration, and the higher the R&D investment ratio to the sales, the greater the spillover effect of R&D.

Korea's private R&D support policy is characterized by policies for future growth engine industries and small and medium-sized enterprise (SME) support policy. It is highly desirable if technologies and products with high social and economic impact are selected and fostered through such policies. However, if the goals and targets of R&D support are set too broadly without considering the R&D capabilities or influence of individual firms, the effectiveness of the policy may be diminished as it would be indistinguishable from non-R&D SME support policies.

In order to enhance the effectiveness of the R&D support policy, it is necessary to return to basics and raise the amount of knowledge production which is below the social optimum level, and to concentrate resources on more rigorous industries and technologies. This should not only be based on the criteria analyzed in this study, but should also begin with a more precise understanding of the spillover effects of R&D support.

Summary

KDI FOCUS Diminishing Role of Young Manufacturing Plants as Drivers of Growth

□ Korea’s aggregate productivity growth in the manufacturing industry is on the decline, considerably influenced by the slowing productivity growth of young plants. A particularly sharp decline has been observed in the high-tech industry over the past three years. As such, government support programs need to aim at promoting growth and driving innovation and the numerous targets for support programs should be streamlined towards young innovative firms. The criteria for such firms should involve private sector investment in order to enhance the effectiveness of the programs.

- Advanced countries are making renewed efforts to enhance innovation and competitiveness in manufacturing while concerns are growing in Korea over the industry’s waning competitiveness.

- This study analyzed the changes in the productivity growth of young manufacturing plants and proposed measures to improve the government’s entrepreneurship support policy.

- Young firms serve as a driving force for job creation and economic growth.

- The share of young plants in the manufacturing industry has continued to decline, pointing to a weakening of Korea’s economic dynamism.

- The manufacturing industry’s aggregate productivity growth has declined, particularly over the past three years.

- Young plants account for nearly half of the aggregate productivity growth on average in manufacturing while their value-added share is only 13%.

- The productivity growth of young plants has decreased over the past decade, diminishing its role as a growth engine.

- The stagnating growth of young plants is a bigger factor to their declining productivity growth than the falling number of new entries.

- The productivity growth of young plants in the high-tech industry, which has the highest R&D intensity, posted sharp decreases.

- Industries with high R&D intensity have been the driving force behind the productivity growth of the manufacturing industry for two decades. But, the last three years have seen a steep decline in the productivity growth of the high-tech industry.

- Although the average productivity of young plants is high, their contribution to aggregate productivity growth has declined due to their shrinking share of the industry.

- While streamling the targets for the support programs towards innovative firms, the government should refrain from selecting and supporting firms directly and reform regulations that hinder entrepreneurship and the growth of innovative firms.

- The government’s verification process should be abolished and innovative firms should be defined as young venture capital firms or R&D firms.

- Restructuring government programs should be based on objective project evaluations.

SITEMAP

HOT ISSUE

Summary

Summary

Summary

Summary

Summary

Summary

Summary

Summary

Summary

Summary