Free Economic Zones and Firm Performance: Evidence from Korea^†

I. Introduction

Special Economic Zones (SEZs) are established to stimulate international economic activities, thereby enhancing resource utilization and promoting economic growth (Ge, 1999). Among the different types of developments, Korean Free Economic Zones (KFEZs) seek to provide a corporate-friendly environment in which to attract foreign investment and initiate growth at both the regional and national level. This initiative aims to attract multinational corporations by offering various incentives, such as reduced customs duties, lower taxes, deregulation, and financial and site support. The endeavor encompasses a wide array of industries, including research and development (R&D), manufacturing, logistics, tourism, and education. Many different types of SEZs are implemented in many countries worldwide. While there have been successful cases, there are also countries and attempts that have not been successful. This paper provides evidence that firms benefit from the FEZ designation.

In the context of globalization, establishing platforms that facilitate firm interaction by reducing regulatory and trade barriers is essential for integration into the global value chain (GVC). In the initial stages of development of Korea’s Special Economic Zones (SEZs), policy efforts primarily emphasized trade and industrialization, focusing on enhancing production, logistics, distribution, and international collaboration. Since 2003, Korea has shifted toward a more business-oriented approach, aiming to attract foreign investment and stimulate regional economic growth, demonstrating continued progress in leveraging SEZs for economic development.

This study investigates the impact of KFEZ designation on firm performance, specifically examining the performance outcomes of small and medium-sized enterprises (SMEs) that are not publicly traded. The dataset includes over 50,000 firms located within seven of the nine designated KFEZ areas, each with distinct designation dates. The FEZs assessed here are Incheon (August 2003), Gyeonggi (April 2008), Chungbuk (February 2013), Daegu-Gyeongbuk (April 2008), East Coast (February 2013), Busan-Jinhae (October 2003), and Gwangyang Bay Area (October 2003). Ulsan and Gwangju are excluded due to their designation in 2020 and the lack of financial data beyond that year.

Utilizing a difference-in-difference (DiD) methodology, the analysis reveals that firms within KFEZs experienced significant increases in sales, labor productivity, and exports compared to firms outside these zones. The comparative analysis is conducted on two levels: first by comparing KFEZ firms to all other firms nationwide and second by comparing KFEZ firms to nearby firms in similar areas but not within the designated zones. Both approaches yield consistent results, demonstrating that KFEZ designation positively impacts firm performance.

Our study advances the existing literature by presenting empirical findings based on a comprehensive dataset of Korean firms, encompassing over 600,000 firm-year observations. This dataset includes both publicly listed and private firms located within and outside of Free Economic Zones (FEZs) in South Korea. Our analysis reveals that firms within FEZs exhibit significant improvements in performance metrics such as sales, productivity, and exports. These findings provide a robust methodological framework that other countries could adopt to optimize the impact of their SEZ policies.

TABLE 1

FEZ DESIGNATION BY YEAR

Source: Korea Free Economic Zone (https://www.fez.go.kr/).

The rest of the paper proceeds as follows. Section 2 reviews the literature on Free Economic Zones and Special Economic Zones. Section 3 explains the data and empirical strategy. Section 4 presents our results. Section 5 concludes the paper.

II. Literature Review

Researchers use many different names for place-based policies and evaluate their effects on multiple dimensions. Busso et al. (2013) find that wages and employment increase in federal urban Empowerment Zones. Special Economic Zones (SEZs) are found to affect economic growth, export behavior, government revenue, efficiency, and foreign direct investment (Bräutigam and Tang, 2014; Davies and Mazhikeyev, 2019; Ge, 1999; Schweinberger, 2003; Yücer and Siroën, 2017). SEZs were initially designed to offer tax incentives, streamlined regulatory environments, and improved infrastructure to attract foreign direct investment (FDI) and spur economic activity (Crane, 2019). SEZs have been particularly instrumental in regional development strategies. Ambroziak and Hartwell (2018) explored the impact of SEZs on regional development in Poland, finding that SEZs significantly improved economic conditions in less developed regions by attracting investment, reducing unemployment, and increasing the number of businesses.

However, their impact was less pronounced or even negative in relatively wealthier regions, highlighting the importance of contextual factors with regard to SEZ effectiveness. Frick, Rodríguez-Pose, and Wong (2019) emphasized the dynamic nature of successful SEZs, which not only attract initial investments but also create agglomeration economies and positive spillover effects that benefit surrounding areas. Their study emphasized how robust local governance, integration with the local economy, and infrastructure investments are critical for maximizing the benefits of SEZs. China’s SEZs are among the most studied, given their significant role in the country’s economic transformation.

Lu, Wang, and Zhu (2019) analyzed China’s SEZ program and found that these zones not only facilitated economic agglomeration but also enhanced productivity and innovation through concentrated industrial activities. The success of China’s SEZs is attributed to comprehensive support policies, including fiscal incentives, regulatory exemptions, and investments in public infrastructure. Wang (2013) provides robust empirical evidence of the economic impact of SEZsin China, highlighting significant positive effects on local economies through increases in investments, employment rates, and industrial output. Similarly, Yeung et al. (2009) examine the evolution of China’s SEZs over three decades, offering a comprehensive analysis of their successes and challenges.

Hartwell (2021) and Mugano (2021) emphasize that the effectiveness of Special Economic Zones (SEZs) is contingent upon a multitude of factors, including governance, infrastructure, and integration with broader economic policies.

Numerous studies have examined the impact of Free Economic Zones (FEZs) in South Korea on various economic variables since their initiation. Song (2012) emphasizes that the success of the Busan-Jinhae FEZ relies on the interconnectedness of industrial, environmental, governmental, and subjective factors. Kim et al. (2021a) and Lee (2024) document significant increases in foreign direct investment (FDI) attributable to FEZ initiatives in Incheon. Jeong et al. (2011; 2016) assess Korea’s SEZs, providing benchmarks for successful implementation. Zeng (2021) delivers a comprehensive review of the historical evolution, current practices, and future prospects of Special Economic Zones (SEZs), emphasizing their critical role in economic growth and structural transformation. The study underscores the diversity of SEZ models globally and highlights the necessity of tailoring policies to local conditions to optimize their impact. Similarly, Farole (2011) identifies global lessons from SEZ successes and failures, highlighting the importance of effective governance, domestic economy linkages, and robust infrastructure.

Despite these positive outcomes, annual investments in Korea’s FEZs have shown a declining trend since 2018, raising concerns about their ability to adapt to global changes such as protectionism and heightened competition in emerging industries. To address these challenges, the Korean government introduced a new policy framework, redefining the operational direction of FEZs. Legislative revisions in June of 2021 introduced long-term development goals and sector-specific strategies tailored to each free zone (So et al., 2024). The Ministry of Trade, Industry, and Energy has committed to developing zone-specific plans, identifying key strategic industries, and expanding incentives for both domestic and international firms. For further success, a sophisticated development strategy involving expert consultations, performance management systems, and autonomous business discovery processes is essential (Kim et al., 2021b).

Although prior research has assessed KFEZ impacts at the regional level, no studies that we are aware of have utilized firm-level data from both public and non-public companies to analyze the before-and-after effects of FEZ designation on firm performance. This study contributes to the literature by utilizing a comprehensive firm-level panel dataset to provide insights into the overall effectiveness of FEZ policies in South Korea.

III. Data and Methodology

Our analysis utilizes firm-level data sourced from KISreport, encompassing both listed and unlisted firms in South Korea from 1998 to 2020. The dataset includes 54,623 firms presented in a firm-year panel data format, comprising a total of 666,110 observations. The primary variables of interest include sales, business profits, exports, and labor productivity.

Sales and export figures are transformed using the natural logarithm of total revenue and export values as reported in financial statements. Business profit data are scaled by a factor of one million (0.000001) to account for the magnitude of the values, and logarithmic transformation is not applied due to the presence of firms with negative profit values. Labor productivity is calculated as the natural logarithm of total revenue divided by the number of employees. The scale variable, categorized as Small, Medium, or Large, is used as an ordinal indicator of firm size.

Despite the desire for additional control variables, our analysis is constrained by the limited financial information available for unlisted companies. Additional information that can control for firm heterogeneity in the corporate finance literature includes size (total assets), liquidity, profitability, and leverage, among others. However, these data do not exist in our dataset.

Firms are categorized based on their location within designated Free Economic Zones (FEZs), with designation information obtained from the official Korean FEZ website (https://www.fez.go.kr/). FEZs are established to enhance business environments and attract foreign investment through various incentives.

Using the firm-level data, we assess the performance of firms located within FEZs compared to those outside. Firms report the locations of their headquarters or operational sites, including city or province (si/do), county (gun/gu), and region (eup/myeon/dong). This location data enables us to identify firms operating within designated FEZs and those in neighboring regions that do not benefit directly from the FEZ incentives. Consequently, firms within the designated FEZs are treated as the experimental group, while firms in the same county (gun/gu) but outside the FEZs serve as the control group. This methodology allows for a robust comparison of firm performance attributable to the FEZ designation.

Figure 1 illustrates the Free Economic Zones (FEZs) in red. These shaded areas indicate regions where firms benefit from the FEZ designation, while firms located outside these red-shaded areas do not receive such benefits. This distinction exists even within the same county or region containing both beneficiaries and non - recipients. This geographic delineation allows us to assess the impact of FEZ designation on firm performance by comparing firm performance outcomes.

FIGURE 1.

BUSAN-JINHAE FREE ECONOMIC ZONE

Source: Naver Maps.

Our main empirical specification is as follows:

where Performance_i,t denotes firm i’s performance measures, in this case sales, labor productivity, profit, and exports in yeart t. FEZ_i,z indicates whether firm i operates in a FEZ during year t . Post_z,t takes on a value of 1 after region z is designated as a FEZ. X_i,t includes the following control variables: scale, time-effect, industry-effect, fixed-effect, and region-effect.

IV. Results

Table 2 presents the summary statistics. FEZ is a dummy variable that takes on a value of 1 if a firm is located in the designated FEZ, and 0 given otherwise. FEZ_a is 1 if a firm is in FEZ-designated country (gun/gu). Here, 1.9943% of our sample belongs to a FEZ, and 9.57% of firms are in FEZ areas.

TABLE 2

SUMMARY STATISTICS

Note: This table presents the summary statistics of the key variables used in this study. Listed and unlisted firms from 1998 to 2020 are included in the sample. FEZ is an indicator variable that takes on a value of 1 if it operates in a KFEZ. FEZ_a is 1 for firms that are either in a KFEZ or nearby (gun/gu).

Table 3 presents the differential impacts on firm performance based on FEZ status and designation period. A binary variable is constructed wherea value of 1 is given for the post-designation period (Post) for each FEZ and 0 for the pre-designation period (Pre).

Panel A of Table 3 reveals a significant increase in sales for firms within FEZs following the designation, while firms outside FEZs also experienced sales growth, albeit to a lesser extent. Panel B indicates a statistically significant increase in profits for firms within FEZs, with profits more than doubling post-designation. Panel C shows an overall increase in productivity for both FEZ and non-FEZ firms, with the percentage change being substantially larger for firms within FEZs. Panel D illustrates a general decline in exports, which can be complex to analyze due to the propensity of firms to transition to foreign direct investment (FDI) as they grow.

TABLE 3

DIFFERENCES IN FIRM PERFORMANCE OUTCOMES BEFORE AND AFTER THE FREE ECONOMIC ZONE DESIGNATION

Note: This table shows that sales, profits, and productivity increased on average for both FEZ firms and non-FEZ firms, although the magnitude differs. Export decreased for both groups. t-statistics are in parentheses. ***, **, and * denote significance correspondingly at the 1%, 5%, and 10% levels.

Source: Authors’ compilation

As firms become more productive and gain access to foreign capital, they may shift their focus to foreign direct investment (FDI) rather than direct exports, which can result in exports no longer being reported. For instance, Samsung Electronics records zero exports in the Dataguide dataset, reflecting this transition. Consequently, the impact of FEZs on exports may exhibit non-linear patterns, rendering export measures less suitable for analyzing FEZ effects, particularly for large publicly listed firms that operate as multinational enterprises. Nonetheless, given that export data is available for non-public (smaller) firms, the analysis includes this metric to provide additional insights into the effects of FEZ policies.

Subsequently, we conduct a fixed-effect panel regression analysis along with a difference-in-difference (DiD) approach. The statistical model incorporates a variable indicating whether a firm is located within a FEZ (FEZ variable) and a time variable (POST_sgg) representing the period after the respective county (si/gun/gu, hence sgg) received FEZ designation. An interaction term (FEZ*POST_sgg) is utilized to determine the impact of FEZ designation on firm performance.

Table 4 demonstrates that FEZ designation has a positive effect on sales, productivity, and exports when compared to firms not situated within FEZs. The control group comprises firms located outside FEZs. Although there is a positive association between FEZ designation and profits for firms within FEZs, this relationship does not reach statistical significance. This finding contrasts with the results in Table 3, Panel B, where a significant increase in profits was observed. The discrepancy can be attributed to the inclusion of fixed effects for firms, time, industry, and county in the latter analysis. While average profit levels may have increased, the rise does not remain significant once these fixed effects are accounted for. This could be due to increased competition within the FEZs, which may have tempered profit margins despite the overall growth in industry size fueled by foreign investment.

TABLE 4

FIRM PERFORMANCE AND FEZ

Note: This table shows how the firm performance metrics of sales, export, labor productivity, and profit are affected by FEZ designation. FEZ indicates whether a firm operates in the designated regions. POST indicates regions after the official designation. This result includes all firms in Korea. t-statistics are in parentheses. ***, **, and * correspondingly denote significance at the 1%, 5%, and 10% levels.

Source: Authors’ compilation

FEZ*POST_sgg is the interaction term capturing the combined effect of being in an FEZ post-designation. The coefficient being 0.19 for sales in Column 1 indicates that firms within the FEZs experience a 19% increase in sales post-designation compared to their peers outside the FEZ before the designation. This statistically significant improvement underscores the sales boost from FEZ policies. Exports for FEZ firms rise by 9% post-designation, significant at the 5% level, reflecting enhanced export capacity or market access due to FEZ benefits. Labor productivity for FEZ firms increases by 20% post-designation, a highly significant result, indicating that the FEZ policies effectively enhance operational efficiency. The profit coefficient is positive but not statistically significant, suggesting a limited or inconsistent impact on profitability, potentially due to offsetting factors such as increased operational costs or greater market competition.

Understanding the marginal impact of a FEZ can be achieved by looking at the equation below:

The equation above shows that the impact of a FEZ after designation on sales is positive. However, the impact is only 0.04. In our study, we use less than 20 years of data to assess the efficacy of each FEZ. Our findings suggest that the FEZ does indeed have a positive influence on firm performance, but due to the lack of time-series data availability, the long-term effect remains to be observed. This is especially the case for regions that were more recently designated. It is important to continue collecting information to evaluate the policies from FEZ endeavors correctly.

There are possible endogeneity issues in that the selection of FEZ regions may not be arbitrary. Some areas can be chosen for political reasons or due to the region being a business-friendly region. To account for this, we use a closer proximity within the same county (si/gun/gu) to appoint control firms for the DiD analysis, where the treated firms are firms within the designation FEZs. Instead of utilizing control firms from across the entire country, it is more reasonable to select control firms located in close proximity to those within the FEZ. These neighboring firms, although sharing the same county (si/gun/gu) as the FEZ beneficiaries, have not been subjected to any regulatory reforms or received benefits associated with FEZ designation. This approach allows for a more accurate analysis to ascertain the impact of FEZ designation on firm performance by comparing FEZ firms with nearby non-FEZ firms.

In the analysis of a subsample of firms within the county areas of FEZs, the dataset comprises 6,057 firms with 63,747 firm-year observations, of which approximately 20.8% are within FEZs. Consistent with previous findings, Table 5 illustrates that firms within FEZs experienced significant increases in sales, labor productivity, and exports relative to the control firms. However, the analysis did not show a statistically significant impact on profits, which is reflected in the negative coefficients for FEZs.

This outcome suggests that regions designated as FEZs were initially underperforming and that the policies implemented aimed to stimulate economic activity in these areas. The positive coefficients for the interaction terms indicate improvements in firm performance metrics, in this case sales, exports, and productivity, post-designation. These results underscore the net positive effect of FEZ policies on regional firms.

Table 5 presents the results of the analysis focusing on firms located within Free Economic Zones (FEZs) and their neighboring regions. The findings indicate that FEZ designation has a statistically significant positive impact on the key performance metrics of sales, exports, and productivity. Specifically, the interaction term (FEZ*POST_sgg) shows a 19% increase in sales, an 8% rise in exports, and a 20% improvement in productivity for firms within FEZs post-designation, all of which are significant at the 1% or 5% levels. These results confirm that FEZ policies effectively stimulate operational growth and global market integration. However, the impact on profitability remains inconclusive, as the coefficient for profit is positive but not statistically significant, potentially reflecting heightened competition or increased operational costs within the zones. The consistent positive effects sales, exports, and productivity suggest that FEZ policies successfully enhance firm performance in tangible ways, reinforcing their role as a tool for regional economic development.

TABLE 5

FIRM PERFORMANCE AND FEZ: WITHIN FEZ AREAS

Note: This table shows how the firm performance metrics of sales, export, labor productivity, and profits are affected by FEZ designation. FEZ indicates whether a firm operates in the designated regions. POST indicates regions after the official designation. This result includes only firms in neighboring regions. t-statistics are in parentheses. ***, **, and * correspondingly denote significance at the 1%, 5%, and 10% levels.

Source: Authors’ compilation

A. Robustness Check

In Table 6, we look at which industries benefit the most from KFEZ designation. Industries with more than 1,000 firm-year observations were used for this analysis. The industries were Transportation and Storage, Wholesale and Retail, Construction, Real Estate, Pluming and Waste Disposal, and Manufacturing. Table 6 shows the results for the four largest industries in Korea. We find that sales of firms in the Transportation and Storage (Column 4), Wholesale and Retail (Column 3), and Manufacturing (Column 1) industries are positively impacted by KFEZs while other industries such as Construction (Column 2) have insignificant effects.

TABLE 6

BY INDUSTRY: THE IMPACT OF FEZS ON SALES

Note: This table shows how sales are affected by FEZ designation by industries. FEZ indicates whether a firm operates in the designated regions. POST indicates regions after the official designation. This result includes only firms in neighboring regions. t-statistics are in parentheses. ***, **, and * respectively denote significance at the 1%, 5%, and 10% levels.

Source: Authors’ compilation

Table 7 provides an analysis of how sales growth is influenced by the year of FEZ designation, using 2003, 2008, and 2013 as the benchmarks. The results reveal that the interaction term (FEZ*POST_sgg) is statistically significant only for the 2003 FEZ designations, with a coefficient of 0.30, indicating a 30% increase in sales for firms located within these early-designated zones post-designation compared to firms outside the FEZ region beforehand. This finding underscores the stronger and more sustained impact of earlier-established FEZs, likely due to the longer time frame that allows policies to take effect and infrastructure to mature. In contrast, the interaction terms for the 2008 and 2013 designations are not significant, which may reflect the shorter duration for policy effects to materialize or potential delays in implementation and/or infrastructure development. These results highlight the importance of time when evaluating the effectiveness of FEZ policies and suggest that assessing long-term data is essential for accurately assessing the impact of such policies.

Table 8 presents the regional analysis results of the impact of FEZ designation on sales growth. These results demonstrate that the interaction term is statistically significant only for Incheon and Busan, with coefficients of 0.22 and 0.20, respectively. These findings suggest that firms in these two regions experienced a meaningful increase in sales following their FEZ designation, highlighting the effectiveness of the policies in these locations. In contrast, the other regions, in this case Gwangyang Bay, Gyeonggi, Daegu-Gyeongbuk, Gangwon (East Coast), and Chungbuk, do not show statistically significant interaction terms, indicating that FEZ designation in these areas has not yet produced similarly notable sales growth. These disparities may be attributed to variations in the implementation of FEZ policies, infrastructure development, and/or regional economic conditions, emphasizing the need for tailored strategies to enhance the efficacy of FEZs across different regions. Lastly, Table 9 presents the results of a staggered difference-in-differences (DiD) analysis conducted to evaluate the impact of FEZ designation over time, following the methodology proposed by Callaway and Sant’Anna (2021). This approach accounts for the variation in FEZ designation years across regions. The findings suggest that early-designated FEZs, such as Incheon and Busan-Jinhae, had sufficient time for their policies, infrastructure, and incentives to materialize into tangible economic benefits. Conversely, the 2008 and 2013 designations show less pronounced or statistically insignificant impacts, likely due to the shorter duration for these zones to develop and generate results. This finding aligns with the findings in Tables 7 and 8, emphasizing the role of time with regard to how effective FEZ policies are and highlighting the need for continued and consistent attention to enhance the benefits of FEZs.

TABLE 7

FEZ DESIGNATION YEAR AND SALES GROWTH

Note: This table shows how sales are affected by FEZ designation according to the year of FEZ designation. FEZ indicates whether a firm operates in a designated region. POST indicates regions after the official designation. This result includes only control firms in neighboring regions. t-statistics are in parentheses. ***, **, and * correspondingly denote significance at the 1%, 5%, and 10% levels.

TABLE 8

BY REGION: THE IMPACT OF FEZ ON SALES

Note: This table shows how sales are affected by FEZ designation by regions. Each column uses firms in the following FEZ-designated regions: Incheon, Busan-Jinhae, Gwangyang Bay, Gyeonggi, Daegu-Gyeongbuk, East Coast (Gangwon), and Chungbuk. Ulsan and Gwangju were designated in 2020 and were therefore excluded from the analysis. This result includes only firms in neighboring regions. t-statistics are in parentheses. ***, **, and * respectively denote significance at the 1%, 5%, and 10% levels.

Source: Authors’ compilation

Table 9 highlights the nature of FEZ policy impacts, demonstrating that significant benefits often take more than a decade to materialize fully. However, the results lack strong statistical significance, which may stem from several limitations in the study. First, firm-level heterogeneity may not be adequately controlled for, as our dataset lacks variables such as firm size, liquidity, and leverage. Second, the temporal scope of the analysis may be insufficient, as the available data do not extend far enough to capture the full long-term effects of FEZ policies, particularly for more recently designated zones. These limitations suggest the need for richer datasets and longer time horizons to gain a better understanding of the economic impact of FEZ initiatives.

TABLE 9

STAGGERED DID ANALYSIS BY FEZ DESIGNATION YEAR

V. Conclusion

This study provides a comprehensive analysis of the impact of Free Economic Zone (FEZ) designation on firm performance in South Korea, utilizing an extensive dataset of over 600,000 firm-year observations. We find that firm performance improved due to FEZ designation, especially for firms in the manufacturing, transportation, and wholesale/retail industries. The findings of this study offer several key policy implications for governments and policymakers aiming to enhance the performance of firms through place-based policies such as those pertaining to Free Economic Zones (FEZs). The evidence indicates that FEZ designation significantly improves firm outcomes in terms of sales, productivity, and export activities, providing a robust foundation for continued investment in such initiatives. However, the nuanced effects on profitability and the potential challenges stemming from increased competition or underperforming baseline regions warrant targeted strategies to maximize the overall benefits of FEZs. We find that the economic benefits of FEZ designation are most pronounced in earlier designations, suggesting that time is crucial for infrastructure to develop, policies to be implemented, and economic benefits to materialize.

Globalization experienced a significant slowdown during the COVID-19 pandemic, potentially disrupting the trajectory of Korea’s Free Economic Zones (KFEZ) and their intended impacts. Additionally, the growing competitiveness of other Asian economies presents a challenge to Korea’s economic growth and its position in the global market. In response, policy efforts should prioritize enhancing export-related infrastructure, such as transportation and logistics, to improve efficiency and connectivity. Furthermore, providing targeted technical and financial support to firms seeking to integrate into or expand within global value chains and to be able to compete along with AI Tech giants will be critical aspects to those attempting to maintain Korea’s economic competitiveness and sustain the growth of KFEZ initiatives.

Successful outcomes depend heavily on robust governance frameworks and strategic implementation. Governments must ensure transparency during the selection of FEZ regions, an equitable distribution of benefits, and ongoing monitoring to address any emerging challenges. Additionally, maintaining a stable regulatory environment and providing consistent support are crucial strategies to attract and retain investments. Deregulations that promote financial openness and new innovations must be complemented with prior benefits to attract foreign capital over other financial hubs.

Our study contributes by providing empirical evidence from a large sample of Korean firms and supports the notion that SEZ policies can effectively stimulate economic growth and improve firm performance. The evidence from South Korea’s FEZs offers valuable insights for policymakers in other countries considering similar economic zones. This study emphasizing the importance of a balanced approach that combines incentives, infrastructure investment, and targeted support for firms.