Chapter 1. Research Background and Purpose Study on The

Home , Buan County, Changnyeong County, Geumsan County, Jangseong County, Yesan County

Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging

Mungu Huh et al.*

Chapter 1. Research Background and Purpose

The rapid aging of the population is a serious issue for South Korea, as the sudden decline in the size of the working-age population is leading to a shortage of labor necessary to sustain local and national economic growth, while the increasing average age of workers is resulting in decreases in labor productivity. As population aging can pose a serious threat to the competitiveness of a regional or national economy, it is critical for policymakers to intervene in a timely manner by implementing effective measures. There is indeed a close correlation between demographic structures and economic growth. Population aging is always inversely related to economic growth, at both the local and national lev-

* Mungu Huh, Hyunwoo Kim, Jeonghong Kim, Hayool Song, Sangho Lee, Doohee Lee, Junho Jeong, Daegi Min, Hideki Endo Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 339 els. The increasing proportion of the elderly in given populations is irrefutably negatively correlated to the rates of growth of the gross domestic product (GDP) and gross regional domestic product (GRDP) of the 205 cities, counties, and boroughs of Korea, and the same goes for the 34 member states of the Organization for Eco-

Figure 1. Population Aging and Economic Growth

(A) 34 OECD member states (B) 205 cities, counties, and boroughs of Korea South Korea Rate of Rate of increase increase in GRDP in GDP (five-year average) Rate of increase in proportion of Proportion of elderly population elderly population (five-year average)

Figure 2. Working-Age Population and Economic Growth

(A) 34 OECD member states (B) 16 cities and provinces of Korea South Korea Chile Chungnam Gyeonggi Estonia Israel Turkey Rate of Rate of Chungbuk increase increase Mexico Gyeongbuk Incheon in GDP in GRDP Jeonnam Gwangju Jeonbuk Jeju Daejeon Ulsan Busan Seoul Gyeongnam Daegu Japan Gangwon Italy Rate of increase in working-age Rate of increase in working-age population population 340 nomic Cooperation and Development (OECD). On the other hand, there is a positive correlation between the size of the working-age population and GDP or GRDP growth. Changes in demographic structures, in other words, often serve as decisive factors of national and regional economic growth. Putting the generality of this phenomenon aside, there are certain Korean cities, counties, and boroughs that are experiencing remarkable economic growth despite the aging of their populations. In this study, our main objective is to identify the characteristics and determinants of the economic growth experienced by these special municipalities, with a view to developing a guideline for other similar regions. Most of the literature on population aging focuses on how the aging of the population affects the societies and economies of certain nations or communities. There are almost no studies prior to this one that analyze the correlation between population aging and economic growth at the level of basic municipalities. This study identifies basic municipalities in Korea that are showing clear patterns of growth with respect to three main structures— industrial, demographic, and spatial—and have achieved significant economic growth despite the aging of their populations. In doing so, this study identifies the different types and characteristics of economic growth experienced by these “aged” municipalities, and examines the factors that have contributed to offsetting the losses in labor productivity and thereby raised the rates of these municipalities’ economic growth above those of other regions. In our analysis, we employ a Solow production function. The (super)high-growth and (super)old municipalities we examine Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 341

Figure 3. Population Aging and Productivity under the Solow Production Function (Innovation) (Capital)

Y=A×(L, K)+ α(?) (Local resources) (Aging) show increases in total productivity, (Y) despite the decline in labor productivity (L) caused by population aging, thanks to increases in technological innovation (A) and/or capital (K). Acknowledg- ing that certain local resources (α) could also be involved besides A and K, on which little statistical information is available, we also conducted a thorough survey of local characteristics and conditions to identify and analyze such resources.

Chapter 2. Inter-Regional Comparison of Demographic Structures

National demographic structures change due mainly to the two natural causes, i.e., birth and death, as well as the one social cause, i.e., migration. At the local level in Korea, however, migration is the most prevalent cause of change in the demographic structures of different municipalities. There are strong age-associated patterns of migration that are characteristic of the demographic structure in Korea. The young population, which plays a central role in the national economy, tends to be concentrated in the Seoul-Gyeonggi region. Aside from Seoul, Incheon, and Gyeonggi, the Chungnam and Jeju provinces 342

Table 1. Types of Migration Occurring in Korea

Type Region Characteristics Incheon, Gyeonggi, Net inflow across age groups Chungnam, and Jeju High-growth regions Net inflow of young people Outflow of all other age (aged 15 to 29) Seoul groups Metropolitan cities Net inflow of children (aged 14 Busan, Daegu, and Gwangju experiencing outflow of all and under) other age groups Due to presence of Sejong Net outflow across age groups Daejeon City Net outflow of young people and children (aged 29 and Chungbuk and Gyeongbuk Inflow of most other age under) groups Gangwon, Jeonbuk, Jeonnam, Inflow of most other age Outflow of young people and Gyeongnam groups Outflow of young and middle- aged (50 to 65) people Ulsan Inflow of all other age groups also receive more young people than they lose. The net inflow of young people is an indication of the availability of quality jobs and existence of diverse cultural and social attractions. With the excep- tion of these five regions, all other regions of Korea are experiencing rapid population aging. The inflows and outflows of certain age groups cause dramatic changes in the structure of the local job market. Daejeon, Seoul, Chungnam, Gyeonggi, and Incheon are the regions in Korea with the highest proportions of young jobseekers in their 20s. Dae- jeon and Seoul offer relatively greater pools of R&D and knowl- edge-based jobs, which serve to attract and retain young people from other regions. The other three regions also attract young people with their relatively secure jobs in the manufacturing sector. Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 343

Table 2. Employment Structure by Region and Age Unit : % 20s 30s 40s 50s 60s 15-29 15-64 Nationwide 14.2 21.9 25.7 23.1 14.1 15.2 92.1 Seoul 16.3 24.7 23.8 22.4 12.0 17.1 94.0 Busan 14.1 20.5 24.0 25.3 15.3 14.9 92.8 Daegu 13.7 21.1 26.7 24.6 12.8 14.9 93.8 Incheon 14.6 23.0 26.3 23.5 11.6 15.6 94.4 Gwangju 14.3 23.6 27.6 21.8 11.6 15.4 93.6 Daejeon 16.6 22.9 25.7 23.0 10.9 17.4 94.7 Ulsan 12.5 22.8 28.3 25.1 10.3 13.4 95.0 Gyeonggi 15.0 23.4 28.1 22.1 10.3 16.1 94.9 Gangwon 11.5 17.5 25.6 25.7 19.2 12.2 88.8 Chungbuk 14.0 19.8 24.6 23.9 16.5 15.2 90.3 Chungnam 15.6 20.7 23.5 21.9 17.6 16.4 88.7 Jeonbuk 11.7 17.6 24.5 23.8 21.6 12.5 85.6 Jeonnam 9.0 15.9 22.9 23.5 27.7 10.0 80.0 Gyeongbuk 12.7 16.9 23.4 23.7 22.7 13.4 85.4 Gyeongnam 11.1 21.2 27.1 24.2 15.8 11.8 90.9 Jeju 12.0 19.8 26.7 22.2 18.0 13.5 88.3

Aside from Chungnam, all other regions outside the Seoul-Gyeo- nggi region have 20-something populations that are smaller than the national average. In the meantime, the phenomenon where the number of deaths exceeds the number of births is occurring much earlier in provinces outside the Seoul-Gyeonggi region than in the Seoul-Gyeong- gi region and other metropolitan cities, indicating that population aging in the provinces outside Seoul-Gyeonggi and other metropolitan cities is taking place at a faster pace. However, the recent increase in population migration from the Seoul-Gyeonggi region 344 and metropolitan cities into other provinces could serve to offset or delay this process of aging and loss in the populations of the provinces. Another interesting characteristic to note is that, while the regions outside Seoul-Gyeonggi have relatively larger proportions of the elderly, the rates of population aging in these regions are slower than that of Seoul-Gyeonggi. This suggests that the regions outside Seoul-Gyeonggi are likely struggling with labor shortages, while the economies of the Seoul-Gyeonggi region and other metropolitan cities, which have larger young populations and faster-aging populations, are likely to lose their vitality more quickly.

Chapter 3. Identification and Typology of High-Growth and Old Municipalities

Setting the 25 self-governing boroughs of Seoul aside, we ex-

Figure 4. Distribution of Regions by Figure 5. Proportions of Regions by Type Type

High-growth High-growth Super-growth and super-old and young and old regions regions regions - Population aging rate: 20% or up - GRDP: 5.6% or up - 150% of national average Rate of increase in GRDP per capita Low-growth Low-growth and young and old regions regions Super- High- High- Low- Low- growth growth growth growth growth and and and and and Population aging rate super-old old young old young regions regions regions regions regions Numbers of regions by type Proportions of regions by type Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 345

Table 3. Distribution of Regions by Type and Administrative Status Unit : % Rate of Type increase Proportion Number Seoul- Metropolitan Cities Counties in GRDP of elderly of regions Gyeonggi cities Super-growth, 0 0 6 29 super-old 7.5 25.4 35 (0.0) (0.0) (17.1) (82.9) High-growth, 4 9 22 17 old 6.5 15.6 52 (7.7) (17.3) (42.3) (32.7) High-growth, 15 10 8 1 young 6.5 8.9 34 (44.1) (29.4) (23.5) (2.9) Low-growth, 7 10 6 29 old 1.4 17.0 52 (13.5) (19.2) (11.5) (55.8) Low-growth, 15 10 7 0 young 0.5 8.8 32 (46.9) (31.3) (21.9) (0.0) Note : The figures in parentheses represent proportions (%). amined the rate of increase in GRDP per capita and the pace of population aging for each of the remaining 205 cities, counties, and boroughs of Korea. We divided these 205 municipalities into five types based on the patterns of their economic growth and population aging, which led us to identify 87 that were old yet experiencing high economic growth. Of these, we identified 35 “super-growth” and “super-old” municipalities, whose GRDP per capita was at least 150 percent of the national average and rates of population aging were at least 20 percent. Of the 35 super-growth and super-old regions, 29 were rural counties located outside the Seoul-Gyeonggi region. This is unsur- prising, given the prevalent assumption that populations in rural areas tend to be more aged than those in urban areas. Non-metropolitan cities and counties also make up over 65 percent of the regions classified as high-growth and old regions and low-growth and old regions. Over 70 percent of young regions, on the other 346

Table 4. Clustering Analysis on Super-Growth and Super-Old Regions

Cluster 1 Cluster 2 Cluster 3 Type Manufacturing-based regions Regions showing strong Regions specializing in retaining agriculture, forestry, service- and manufacturing- agriculture, forestry, or or fishery based growth fishery Agriculture, Proximity to major 0.8971 Young population 0.9024 forestry, and 0.7785 cities fishery

Full-time workers 0.8322 Service sector 0.8356 Middle-aged and 0.6358 Cluster center elderly population Childbearing-age Proximity to major Manufacturing 0.8186 women 0.8339 cities 0.5027 Manufacturing Prime-age workers 0.7989 Prime-age workers 0.8270 sector 0.4834 Commute to other regions 0.7106 Manufacturing 0.7767 Prime-age workers 0.3962 Young population 0.6953 Population size 0.6481 Service sector 0.3940 Childbearing-age Proximity to major women 0.6830 cities 0.5319 Full-time workers 0.3887 Tangible assets 0.6724 Full-time workers 0.4512 Crude birth rate 0.3523 Agriculture, forestry, and 0.6675 Tangible assets 0.4292 Childbearing-age 0.3331 fishery women Cluster center Crude birth rate 0.5770 Crude birth rate 0.4239 Young population 0.2844 Commute to other Population size 0.5155 regions 0.3758 Tangible assets 0.2204 R&D investment 0.4625 R&D investment 0.2871 Population size 0.1958 Agriculture, Service sector 0.3599 forestry, and 0.2422 Commute to other 0.1827 fishery regions Middle-aged and Middle-aged and elderly population 0.3162 elderly population 0.1690 R&D investment 0.0899 Manufacturing Agriculture, forestry, and - Workers commute to fishery Industrial nearby major cities Manufacturing-based and - Lack of other industries characteristics - Increase in business and service-led growth - Lack of incentives for R&D investment business growth Good demographic Superior demographic Demographic structure (full-time workers, structure (young people, Inferior demographic characteristics prime-age workers, and childbearing-age women, structure (middle-aged and young people) and prime-age workers) elderly populations) Spatial Nearby major cities (mixture Middle (mixture of urban Outskirts of major cities characteristics of urban and rural areas) and rural areas) (rural counties) (Continue) Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 347

Cluster 1 Cluster 2 Cluster 3 Type Manufacturing-based regions Regions showing strong Regions specializing in retaining agriculture, forestry, service- and manufacturing- agriculture, forestry, or or fishery based growth fishery Cheongyang Gunwi Geumsan County, Hoengseong County, County, County, Chungnam Gangwon Chungnam Gyeongbuk Taean Cheongsong Gimje City, Jeonbuk Hongseong County, County, County, Chungnam Chungnam Gyeongbuk Yeongyang Naju City, Jeonnam Yesan County, Chungnam Jinan County, County, Jeonbuk Gyeongbuk Yeongdeok Jangseong County, Jeonnam Jeongeup City, Jeonbuk Muju County, County, Jeonbuk Gyeongbuk

Jangsu Cheongdo Yeongcheon City, Mungyeong City, County, County, Gyeongbuk Gyeongbuk Jeonbuk Gyeongbuk

Sunchang Bonghwa Regions Seongu County, Gyeongbuk Miryang City, Gyeongnam County, County, Jeonbuk Gyeongbuk Gochang Uiryeong Changnyeong County, Geochang County, County, County, Gyeongnam Gyeongnam Jeonbuk Gyeongbuk Sancheong Buan County, County, Jeonbuk Gyeongnam Gurye Hamyang County, County, Jeonnam Gyeongnam Goheung Hapcheon County, County, Jeonnam Gyeongnam Hampyeong County, Jeonnam Cronbach’s α 0.777 hand, were found in Seoul-Gyeonggi and other metropolitan cities. We use K-means clustering to determine the specific characteristics and types of the super-growth and super-old regions. Cluster 1 (Type I-1) includes manufacturing-based regions retaining traces 348 of the agriculture, forestry, and fishery industries; Cluster 2 (Type I-2), regions experiencing growth in both service and manufacturing; and Cluster 3 (Type I-3), regions specializing in agriculture, forestry, or fishery. Regions in Cluster 1 have strong manufacturing sectors that attract workers and investment. Located on the outskirts of major cities, these regions are also home to many workers who regularly commute to and from the major cities nearby. Regions in Cluster 2 attract young, female, and prime-age working populations with their abundance of job opportunities in both the service and manufacturing sectors. These regions also feature self-sufficient service and commercial districts that thrive inde- pendently of the major cities nearby. Service-based regions, in particular, have large proportions of young people. Cluster 3 includes regions specializing in the primary sector that have little infrastructure for any other industries or sectors aside from the agriculture, forestry, and fishery industries. The populations of these regions are primarily middle-aged and elderly and have very few prime-age workers capable of contributing to the productivity of local economies. Despite these limitations, however, the primary sectors of these regions are flourishing to such an extent that the regions are experiencing unexpected economic growth.

Chapter 4. Characteristics of High-Growth and Old Regions

(1) Statistical analysis

The findings of our statistical analysis can be summarized as Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 349 follows. First, the Type-I regions, i.e., super-growth and super-old regions, which are the central focus of this study, have economies that are growing mainly thanks to the strengths of their agriculture, forestry, and fishery industries. Most regions included in this type are rural counties that are dependent upon the primary sector and show significantly higher rates of growth in their agriculture, forestry, and fishery industries than in any other industries during the analysis period. Second, Type-I regions show greater dependency on the primary sector than other regions, but Subtype I-1 shows relatively greater proportions of workers involved in the primary and secondary (manufacturing) sectors as well as larger year-end balances of tangible assets, which are used as a substitute variable for local investment. The considerable presence of manufacturing in Subtype I-1 regions reflects the rising cost of land in the nearby major cities, which has caused manufacturing businesses to relocate to Subtype I-1 regions. Yeongcheon, Seongju, Changnyeong, Jangseong, and other cities and counties included in this subtype are experiencing significant growth in their manufacturing infrastructures, which encompass major industrial clusters. Subtype I-2 shows significant dependency on the secondary and tertiary (service) sectors, suggesting that the service sector, including the business services, wholesale and retail, and accommodation industries, has grown since the establishment of major industrial clusters in these regions. Subtype I-3 includes regions whose economies are growing thanks to the production, wholesale, and retail distribution of the products of the primary sector. Third, our analysis on the correlation between the rate of 350 growth in the GRDP of regions of different types and industries with strong location factors reveals that (super-) growth and (super-) old regions (Types I and II) are home to growing agriculture, food processing, non-metal manufacturing, and social welfare service industries. The increase in the high value-added agricultural output and consequent growth of industries that process and man- ufacture such output are leading the economic growth of these regions. Subtype I-1 regions show multiple fast-growing manufacturing industries, while Subtypes I-2 and I-3 show significant growth in the accommodation industry, thanks to increasing tourism in those regions. Fourth, Type-I regions feature demographic structures that contain fewer young people, prime-age workers, childbearing-age women, full-time workers, and dependent underage minors and have lower crude birth rates than other regions. Nevertheless, Sub- types I-1 and I-2 have retained relatively greater proportions of young and female populations, thanks to their strong manufacturing and service sectors. The proportion of full-time workers in a given region tends to be proportional to the importance of manufacturing in the local economy. Fifth, Type-I regions are cities and counties that contain smaller populations and are located farther away from the centers of major cities than other regions. By comparison, Subtype I-1 regions tend to be closer to major cities, while Subtypes I-2 and I-3 are more distant. Subtype I-3 regions are also made up mostly of small rural counties with small populations. On the contrary, Type-III (high- growth and young) and Type-V (low-growth and young) regions are found in major cities with relatively large populations, while Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 351

Type-II (high-growth and old) and Type-IV (low-growth and old) regions are mid-sized cities and major counties located neither too far from nor too close to major metropolitan cities. From these findings, we conclude that super-growth and super-old regions are mostly small cities and counties with populations smaller than 100,000 each that are not economically self-sufficient but are experiencing rapid growth thanks to their connections to nearby major cities. In other words, these regions overcome the small size and advanced age of their populations by specializing in industries for which they are best suited, which has allowed them to achieve significant economic growth.

(2) Opinion poll

The opinion poll we conducted regarding the specific characteristics of the four types of regions reveals that regions experiencing growth and possessing aged populations (including super-growth and super-old regions) outperform the low-growth and old regions in all categories. The main factor behind the success of these super-growth and super-old regions is the endogenous factor, i.e., the presence of businesses with strong capabilities for innovation. These regions have also benefitted from some policy and locational (settlement) factors. To sustain the economic growth of these super-old regions, it is therefore important to not only attract young workers, but also improve the settlement conditions (e.g., expand infrastructure) of the regions and foster the leading local industries. High-growth and old regions show much stronger locational 352

Table 5. Ranking of the Four Types of Regions by Factor

Business factors Super-growth, super-old > High-growth, old > Low-growth, old Industrial factors High-growth, old > Low-growth, old > Super-growth, super-old Locational factors High-growth, old > Low-growth, old = Super-growth, super-old Policy factors High-growth, old > Super-growth, super-old > Low-growth, old Note : 1) If the rankings of the given regions differ in terms of the sum of the “high” and “very high” scores (on a 100-point scale) and the average of the scores on a five- point scale, the final rankings are determined based on the average of the sum of both scores. 2) The equivalence sign (=) indicates that the difference between the given regions amounts to less than two points when their scores for all seven factors are added up.

Figure 6. Opinion Poll on the Four Types of Factors

Business Industrial Locational Policy Super-growth, super-old High-growth, old Low-growth, old Note : Based on the sums of the “high” and “very high” scores on a 100-point scale

and industrial factors than super-growth and super-old regions, and also benefit from local policy factors. High-growth and old regions, however, possess relatively weak endogenous/business factors, which is preventing these regions from achieving super growth. Policy incentives are thus needed to induce local business- Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 353 es to enhance their capabilities for innovation. Finally, low-growth and old regions show relatively strong industrial and locational factors (compared to high-growth and old regions), but lack strong local policy and endogenous/business factors. These regions can benefit significantly from improvements in their settlement conditions, including the number and diversity of amenities available. Diverse policy measures are thus needed to enhance local businesses, industries, and locational conditions in these regions. A comparison of the three subtypes of the super-growth and super-old regions across these factors revealed little difference among the subtypes in terms of business factors. However, the two subtypes whose economic growth is based on manufacturing possess stronger industrial factors than the third subtype, which specializes in primary-sector industries. The subtype with manufacturing bases and retaining traces of primary-sector industries

Table 6. Ranking of Super-Growth and Super-Old Regions by Factor

Business factors Type I-1 = Type I-2 = Type I-3 Industrial factors Type I-1 = Type I-2 > Type I-3 Locational factors Type I-1 > Type I-2 = Type I-3 Policy factors Type I-1 = Type I-3 > Type I-2 Note : 1) If the rankings of the given regions differ in terms of the sum of the “high” and “very high” scores (on a 100-point scale) and the average of the scores on the five- point scale, the final rankings are determined based on the average of the sum of both scores. 2) The equivalence sign (=) indicates that the difference between the given regions amounts to less than two points when their scores for all seven factors are added up. 354

Figure 7. Opinion Poll on the Four Factors of the Subtypes of Super-Growth and Super-Old Regions

Business Industrial Locational Policy Manufacturing-based, with traces of primary-sector industries (Type 1-I) Growth led by service and manufacturing (Type I-2) Specializing in primary-sector industries (Type I-3)

Note : Based on the sums of the “high” and “very high” scores on a 100-point scale. also shows stronger locational factors than the other two subtypes. In addition, it was found that policy factors exert the most decisive influence on the subtype specializing in primary-sector industries. The results of the opinion poll overlapped to a great extent with common expectations. The opinion poll confirms the common suspicion that policy factors, such as the presence of local policy strategies for industrialization and the capabilities and motivation of local policymakers, are decisive factors in inducing economic growth in regions with aged populations. Based on these results, we need to conduct a more detailed analysis to find which factors are strong and which are weak in the given regions in order to identify the measures these regions should implement to overcome population aging and achieve economic growth. Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 355

Chapter 5. Analysis of the Decisive Factors of Economic Growth for High-Growth and Old Regions

This chapter provides two related analyses. The first is an analysis on the factors that promote the economic growth of regions of different types and involves comparing and contrasting the growth factors across the different types of regions. Here, we apply the structural factors identified by the neo-classical, endogenous, and neo-geographic theories of economic growth as explanatory variables to the changes in the GRDP of the regions observed from the years 2005 to 2013, and analyze them using the spatial econometric technique. The second analysis examines how population aging has affected the economic growth of high-growth and old regions and the 35 super-growth and super-old regions over the period from 1995 to 2014, using instrumental variables that capture the re- verse-causal relationship between demographic structure and economic growth. The findings of our analyses can be summarized as follows. First, our analysis on the growth factors of all 205 regions strongly supports the inter-regional income convergence hypothesis, thereby affirming the positive correlation between the employment rate and local economic growth rate. It was also found that the clustering effect of major and key industries has a positive effect on the growth of local economies. Second, different growth factors are involved in inducing the economic growth of regions of different types. The factors of economic growth for high-growth and old regions overlap with those for other types of regions, i.e., the inter-regional income conver- 356 gence hypothesis, the clustering effect of major and key industries, and the rise of the employment rate. In the 35 super-growth and super-old regions, however, the employment rate bears a negative correlation to economic growth, as does the clustering of major and key industries. Innovation-related variables, however, show a positive correlation to economic growth, once again affirming that the economic growth of these regions is largely the result of the innovation of local businesses. The super-growth and super-old regions, too, support the inter-regional income convergence hypothesis. Third, factoring the GRDP per capita of high-growth and old regions into the labor productivity and employment rates and using these factors as the dependent variables reveals that increases in labor productivity are proportionally related to local economic growth, while changes in the employment rate, whether upward or downward, negatively affect local economic growth. This suggests that, in regions with aging populations, the modernization of machinery and other facilities in the basic material manufacturing industries is the main source of the regions’ economic growth and does not lead to the creation of new jobs. Although young and middle-aged workers thus leave for jobs elsewhere, these regions continue to receive migrants attracted to their rural environments, and consequently experience increases in the number of jobs available in the primary sector. It is these jobs created in the agriculture, forestry, and fishery industries that keep the employment rates of these regions rising. Fourth, factoring the GRDP per capita of super-growth and super-old regions into the labor productivity and employment rates Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 357 and using these factors as the dependent variables reveals that increases in labor productivity are proportionally related to local economic growth, while changes in the employment rate, whether upward or downward, negatively affect local economic growth. However, changes in the proportions of people working in the primary sector and construction industry serve to raise these regions’ overall employment rates. Proximity to nearby major cities and the sizes of local markets also serve to increase employment rates. Increases in the labor productivity of these regions stem from the changes in the proportions of people working in the basic material manufacturing, light manufacturing, social service, and distribution industries. Finally, the cities, counties, and boroughs analyzed in this study are regions that have both relatively greater proportions of the elderly and rapidly growing income per capita. Our analysis of the effect of population aging on the economies of these regions reveals that the influence of productivity outweighs that of employment rates. In other words, restructuring and the modernization of machinery and facilities serve to sustain the economic growth of these regions without creating new jobs. Population aging in these regions tends to accelerate the process of economic growth. In addition, changes in the proportions of people working in the primary-sector industries of these regions also contribute to raising the overall employment rates. The presence of people who return to these regions to enjoy more rural living environments thus serve to replace the young and middle-aged workers who migrate to major cities in search of jobs and play central roles in sustaining the economic growth of these regions. 358

Table 7. Regression Analysis on Super-Growth and Super-Old Regions: GRDP Per Capita and Employment Rates

Period 2005-2014 1995-2014 Technique OLS 2SLS OLS 2SLS Dependent variable △ln(GRDP/N) △ln(L/N)

△ 0.216 -0.003 0.648 -0.555 ln(proportion of elderly population) (0.726) (-0.011) (1.918)* (-10.990)***

△ -0.020 -0.021 0.002 0.001 ln(proportion of primary sector) (-1.438) (-1.458) (0.163) (0.191) △ln(proportion of basic material -0.012 -0.014 -0.027 -0.031 manufacturing) (-0.575) (-0.692) (-0.768) (-0.851) △ln(proportion of processing and -0.045 -0.047 0.003 -0.017 assembly) (-4.848)*** (-5.114)*** (0.313) (-1.010)

△ -0.009 -0.011 -0.042 -0.040 ln(proportion of light manufacturing) (-0.302) (-0.323) (-1.029) (-0.899)

△ -0.031 -0.031 -0.361 -0.356 ln(proportion of distribution service) (-10.644)*** (-3.667)*** (-4.624)*** (-5.159)***

△ -0.093 -0.095 -0.056 -0.085 ln(proportion of producer services) (-3.278)*** (-3.831)*** (-2.607)** (-1.943)*

△ 0.137 0.128 -0.331 -0.396 ln(proportion of social services) (321.880)*** (26.627)*** (-4.878)*** (-4.523)***

△ -0.146 -0.153 -0.236 -0.260 ln(proportion of personal services) (-1.956)* (-2.040)** (-2.688)*** (-4.270)***

△ -0.016 -0.014 -0.023 -0.019 ln(proportion of construction) (-0.690) (-0.610) (-1.432) (-1.581) 0.009 0.009 0.009 0.004 ln(accessibility index) (0.586) (0.547) (2.288)** (0.971) 0.117 0.148 -0.103 0.172 Constant (0.661) (0.820) (-1.085) (6.183)*** R2 0.286 0.284 0.520 0.471 D-W statistics 2.025 2.052 2.244 2.291 N 70 70 140 140

Note : 1) *, **, and *** indicate statistical significance at ten-, five-, and one-percent levels, respectively. 2) Year dummy variables were added to the overall period, and the White standard errors were added to all estimates in order to control for potential heteroscedasticity. Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 359

Table 8. Regression Analysis on High-Growth and Old Regions: GRDP Per Capita

Period 2005-2014 2005-2010 2010-2014 Technique OLS 2SLS OLS 2SLS OLS 2SLS Dependent variable △ln(GRDP/N) △ln (proportion of 0.242 0.299 0.430 0.245 0.413 0.281 elderly population) (8.967)*** (16.558)*** (1.601) (0.594) (2.118)** (1.012) △ln (proportion of -0.025 -0.025 -0.028 -0.033 -0.012 -0.011 primary sector) (-2.753)** (-2.483)** (-1.106) (-1.265) (-0.749) (-0.724) △ ln (proportion 0.021 0.020 0.048 0.044 -0.006 0.001 of basic material (2.354)** (3.231)*** (0.636) (0.592) (-0.107) (0.012) manufacturing) △ ln (proportion -0.030 -0.029 -0.033 -0.039 -0.022 -0.024 of processing and (-4.777)*** (-4.262)*** (-0.867) (-0.980) (-1.077) (-1.259) assembly) △ln (proportion of -0.022 -0.025 -0.034 -0.020 -0.049 -0.040 light manufacturing) (-5.078)*** (-26.284)*** (-0.308) (-0.176) (-1.039) (-0.787) △ln (proportion of -0.145 -0.136 -0.222 -0.239 0.065 0.033 distribution services) (-1.693)* (-1.996)** (-1.158) (-1.214) (0.545) (0.255) △ln (proportion of -0.023 -0.019 -0.162 -0.168 0.083 0.075 producer services) (-0.279) (-0.243) (-1.697)* (-1.756)* (1.385) (1.260) △ln (proportion of -0.106 -0.108 -0.281 -0.271 0.040 0.041 social services) (-0.986) (-1.121) (-1.597) (-1.480) (0.383) (0.388) △ln (proportion of -0.060 -0.059 -0.410 -0.382 -0.037 -0.044 personal services) (-0.522) (-0.566) (-1.892)* (-1.699)* (-0.351) (-0.429) △ln (proportion of -0.067 -0.067 -0.165 -0.160 -0.017 -0.016 construction) (-1.312) (-1.460) (-2.983)*** (-2.853)*** (-0.413) (-0.373) -0.009 -0.010 -0.016 -0.013 -0.005 -0.004 Ln (accessibility index) (-3.070)*** (-3.479)*** (-1.763)* (-1.245) (-0.910) (-0.647) 0.039 0.039 0.053 0.054 0.026 0.025 Local dummy variable (4.430)*** (3.795)*** (1.478) (1.496) (1.410) (1.379) 0.248 0.249 0.288 0.291 0.186 0.184 Constant (8.180)*** (8.971)*** (3.317)*** (3.356)*** (3.174)*** (3.144)*** R2 0.161 0.158 0.244 0.228 0.128 0.122 D-W statistics 1.903 1.893 1.790 1.795 2.388 2.448 N 174 174 87 87 87 87 Note : 1) *, **, and *** indicate statistical significance at ten-, five-, and one-percent levels, respectively. 2) Year dummy variables were added to the overall period, and the White standard errors were added to all estimates in order to control for potential heteroscedasticity. 360

Chapter 6. Policy Suggestions

(1) Four-step process for determining main policy tasks

In order to identify and determine the policy tasks necessary to support the economic growth of regions with aged populations, we formulated the following four-step model. In the first step, we performed a statistical analysis to identify the characteristics of the industrial, demographic, and spatial structures of the given regions. Our main aim was to determine the common factors that made significant contributions to local economic growth. In the second step, we sought to identify the qualitative factors of economic

Figure 8. Four-Step Process for Determining Policy Tasks

Step 1 Step 2 Step 3 Step 4

Statistical Opinion Regression Fact-finding analysis poll analysis survey

Three main Four main Local economic structures factors growth Case study Spatial Policy Industrial Business Industrial Locational Four factors Demographic Decisive factors Local resources Three structures Economic growth (Elude statistical analysis) (Population aging and (Factors of economic growth) differentiation from (Determinants of old regions’ other regions) economic growth)

Identify factors of economic growth in each step Determine policy measures needed to promote the economic growth of old regions Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 361 growth on the basis of an opinion poll on the business, industrial, locational, and policy factors of the given regions. Such an opinion poll was necessary to obtain information on the presence of pio- neering businesses or cooperative networks promoting innovation, as such factors easily elude statistical and quantitative analysis. In the third step, we sought to determine how the changing demographic structures in (super-) growth and (super-) old regions influenced their economic growth and identify the characteristics of growth induced by population aging. In the fourth and final step, we performed a fact-finding survey on a number of regions to determine how they differed from one another in terms of the three main structures and four main factors. We also sought to identify the local resources that contributed to the economic growth of particular regions. This four-step process led to the creation of a list of growth-related factors with significant implications for policymaking, shown in Figure 9. We can summarize these factors further to provide the following four implications for policymaking. First, our analysis confirmed that the presence of industrial development strategies and businesses’ internal capabilities for innovation were the decisive factors of economic growth in (super-) growth and (super-) old regions. This indicates the need for both local businesses and local governments to establish mid- to long- term economic growth plans. Second, we were able to affirm that the manufacturing sector played the most significant role of all three sectors in the majority of regions experiencing high growth. We also ascertained that the general income level of locals in these manufacturing-based, high- 362 growth regions was relatively low. In low-income communities, manufacturing, due to its high productivity, is still more important than the service sector as a source of economic growth. The degree of specialization among workers in agriculture was

Figure 9. Four Main Policy Tasks and Ten Policy Actions

Growth Research characteristics methods Four main tasks 10 actions

Correlation 1. Establish master plans Industrial (Opinion poll/ (1) for local economic development fact-finding Establish mid- development in light of strategies survey) to long-term population aging. policy plans for Strong internal (Opinion poll/ local economic 2. Strengthen internal capability for fact-finding development. capabilities for economic innovation survey) growth. (Statistical 3. Modernize structures Food manufacturing analysis/fact- of conventional finding survey) manufacturing.

Non-metal (Regression (2) 4. Expand value chains manufacturing analysis) Foster into metropolitan and manufacturing. provincial regions. 5. Foster sixth sector, (Statistical i.e., convergence- and Poor R&D capability analysis/fact- agriculture-based finding survey) industries. Highest degree of (Statistical 6. Strengthen integrated specialization in analysis/fact- governance of agro- agriculture finding survey) management bodies. Growing value- (Fact-finding added of agro- survey/fact- (3) 7. Centralize and streamline processing finding survey) Enhance value- policy support. added of agriculture. Rising employment 8. Encourage and welcome rates in primary (Regression migration to rural areas sector leading analysis) to offset repercussions of economic growth jobless growth.

Service sector (Statistical 9. Utilize unique local concentrated in retail analysis) resources to attract and accommodation (4) tourists. Develop 10. Enhance value-added of (Statistical infrastructure for service industries based Clustering of leisure- analysis/fact- service sector. on sixth sector and related services finding survey) local cultural/ecological resources. Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 363

4.39 for super-growth regions and 1.44 for high-growth regions. This shows that agriculture was the industry with the highest degree of specialization. These regions were able to achieve economic growth by embracing the agro-processing industry, which has a high value-added. Of all industries, the degree of specialization was particularly high in the food manufacturing industry, supporting our hypothesis regarding the growing value-added of agriculture. Regions with aging populations show high degrees of specialization in daily service industries, such as retail and accommodation, as well as in public administration and social welfare services and leisure-related services supporting creativity, the arts, and recreation. Policymakers need to select and support these industries to promote the economic growth of old regions.

(2) Ten Policy Actions

1) Establish master plans for local economic development in light of population aging.

Because the degrees of population aging and economic growth differ significantly from municipality to municipality, it is important for local governments to establish master plans for local economic development that also include strategies reflective of particular local demographic structures. Local governments, however, face significant limitations in terms of the financial and non-financial resources available for such planning. As a result, they mostly adopt and implement the plans of metropolitan or provincial governments. 364

However, by launching initiatives for local economic growth, local governments can significantly enhance the effectiveness of the policies implemented to that end. Establishing these local master plans can also induce productive competition among municipalities. In South Korea, the Local Development Commission and the Ministry of Trade, Industry and Energy (MOTIE) devise five-year plans for metropolitan and provincial development. These five-year plans, however, fail to reflect and respond to the specific needs of the individual municipalities that make up these metropolitan cities and provinces. It is thus important for local governments to devise corresponding five-year plans of their own with the support of the national government. The effectiveness of such local plans can be improved further by allowing two or more municipalities to coordinate and organize collaborative projects together. The rapid aging of populations is raising concerns over the pos- sible disappearance and extinction of rural municipalities. In this regard, remote rural counties located in provinces far from the Seoul-Gyeonggi region are of particular concern. These counties therefore face stronger public demand than other regions to articu- late their visions and objectives concerning local development, and implement thorough and comprehensive plans accordingly. It is only by taking such initiative toward local planning that local governments can overcome the concerns regarding population aging and actually achieve economic growth.

2) Strengthen internal capabilities for economic growth.

Since Romer proposed his seminal new growth theory in 1986, Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 365 national and local policymakers worldwide have been struggling to enhance the productivity and innovation of their economies by increasing their endogenous resources, such as human capital and R&D capacity. Empirical studies have shown that innovation-related factors contribute significantly to the growth of local economies, thus confirming the innovation-led patterns of local growth hy- pothesized by Romer’s theory. Through our own statistical analysis and opinion poll, we were also able to conclude that endogenous factors play decisive roles in the economic growth of super-old regions, which lack other resources, working-age populations, and strong locational factors. We should note that super-growth and super-old regions boast local businesses with especially strong capabilities for innovation. Notwithstanding the challenges they face, such as shortages of working-age people and proximity to major cities, these businesses have been able to raise the growth rates of their regions well above those of other regions thanks to the sheer quality of innovation they have achieved. High-growth regions, as well, benefit from local industrial policies that promote the growth of local businesses. In other words, local policies that promote endogenous growth in fact play substantial roles in the growth of local businesses and regions. Jeongeup, a small city in Jeonbuk province, which is one of the super-growth and super-old regions, has actively attracted branches of major public research organizations in an effort to enhance its local R&D capacity and also provides significant support for business investment and manufacturing businesses. In order to enhance local capabilities for economic growth, it is critical to 366 introduce a systematic program that allows local businesses and (public) research organizations to engage in effective collaboration together. This, in turn, requires local policymakers to ascertain the specific needs of local businesses and utilize the available networks linking local governments to metropolitan or provincial governments, with the aim of enhancing the prospects and capability of the resulting program. In order for a region to achieve endogenous growth, it also needs to accumulate human capital. Unfortunately, human capital in Korea is concentrated in the Seoul-Gyeonggi region and other metropolitan cities. Other regions, 85.1 percent of which are made up of rural counties with aged populations, thus struggle to attract and develop human capital. The reason for this is that universities and other educational and training facilities are heavily concentrated in the country’s metropolitan cities. As local governments cannot attract and develop human capital on their own, it is critical that they participate actively in the industrial, academic, and research collaboration projects that encompass nearby metropolitan cities or provinces and make active use of the education infrastructure available in nearby major cities.

3) Modernize structures of conventional manufacturing.

Manufacturing has been pivotal to the remarkable, fast-paced economic growth of regions and nations. In most regions and nations, economic development starts from an industrial structure that is focused primarily on the agriculture, forestry, and fishery industries, which keeps the income level of citizens quite low. The Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 367 growing presence and proportion of manufacturing in the given economy, however, begins to raise productivity significantly, leading to increases in the income level of locals accordingly. How- ever, we must not lose sight of the fact that, although the (super-) growth and (super-) old regions analyzed in this study show much faster paces of economic growth than other regions, they are still plagued with low income levels. In order to raise the income levels of these regions significantly, policymakers must either develop and foster tourism or focus on fostering manufacturing, which of- fers far greater productivity than other industries. Our statistical analysis confirms that the rapid economic growth experienced by (super-) growth and (super-) old regions stems largely from the rapid expansion of local manufacturing industries. Most of these regions, however, specialize in manufacturing industries that feature low value-added, such as food processing, rubber production, and non-metal production, and offer poor prospects for additional growth. In order to sustain economic growth in these regions, it is important to identify the existing industries with relatively higher value-added, and modernize the local production structures accordingly. This is by no means a recommendation that these regions adopt plans for an abrupt transition from the current low value-added and light manufacturing industries to hi-tech and cutting-edge industries, as such plans would very likely fail due to the need of cutting-edge tech industries for an abundance of skilled workforces and advanced infrastructure capable of producing goods with high value-added. Because the majority of high-growth and old regions lack such human capital and infrastructure, they will be unable to attract advanced manufacturing industries with- 368 out first incurring significant costs to foster appropriate environments. It would thus be better for these regions to focus on fostering industries in which they already have competitive advantages and that are likely to offer high value-added. As empirical studies show, old regions’ attempts to attract and foster hi-tech manufacturing industries actually serve to hinder local economic growth. It is therefore much more cost-effective and less time-consuming for these old regions to enhance the value-added of the industries they already have. Regions with aging populations can facilitate this structural transformation of their industries by strengthening networks for industrial, academic, and research collaboration, as that would lead to the development of convergence-based technologies that could enhance their manufacturing bases.

4) Expand value chains into metropolitan and provincial regions.

Innovation enhances the value-added of products and industries while also creating new and better jobs for locals. Through this two-pronged process, innovation enhances the competitiveness of the entire local economy and drives local economic growth. (Super-) old regions find it nearly impossible to secure steady supplies of quality labor. One of the most effective ways of over- coming this shortage of human capital is to enhance the capability for innovation along the value chains of existing industries. Local governments possess systems of innovation along the value chains of the industries in which they specialize, notwithstanding the dif- ferences in the extents and quality of such systems. Some regions Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 369 possess incredibly small networks of innovation that focus on only a few products of agro-processing, while other regions boast extensive systems of innovation that encompass the metropolitan or provincial levels. The former are mostly regions focused on the agriculture, forestry, and fishery industries, where innovation oc- curs based on the initiatives of local cooperatives or unions, agricultural technology centers, and municipal support organizations, while the latter regions feature major industrial clusters, such as the Agricultural Machinery Cluster of Gimje, Jeonbuk province. Crucial to any system of innovation is the central organization that effectively coordinates a number of subsystems, such as manufacturing facilities, R&D organizations, and business support organizations, and works to expand the outward bounds of the system by presenting new visions. Such a central organization not only supports the network connecting producers, researchers, and policymakers, but also facilitates innovation within the given region, thereby playing a central role in fostering local specialized industries. To promote innovation across such a system, it is critical to first establish an efficient supply chain. This is especially important for regions that are centered on agro-processing and feature rapidly aging populations. It is also important to ensure the creation of an extensive supply chain that encompasses all three sectors of industries, and support it with a comprehensive strategy for maximizing productivity in all three sectors. Most (super-) old regions feature small-scale, Marshall-style clusters that cater mostly to small local businesses. On their own, these small clusters are incapable of establishing and sustaining supply 370 chains that encompass diverse resources for innovation. It is therefore crucial to expand these cluster-centered innovation systems through active networking with outside resources. In this way, multilayered systems of innovation can and should be established. This involves integrating individual and separate local systems of innovation into a single system that extends across metropolitan or provincial regions. It is also important to reduce the fragmentation of mini-clusters and enhance their networks and connections across municipalities. Toward this end, metropolitan cities should host regional hubs of the networks of such small local clusters, ensuring the integrated management of resources and connections that are scattered across these municipalities. For example, similar products can be merged together and placed under the management of a region-wide network hub located in a metropolitan city or province, so that all the municipalities making up that metropolitan city or province, with mini-clusters of their own, can effectively coordinate their production and innovation activities. As old regions lack self-sufficient value chains, it is critical for them to forge connections with nearby metropolitan cities or provinces.

5) Foster the sixth sector, i.e., convergence- and agriculture- based industries.

The Fourth Industrial Revolution has brought inter-industry convergence to the forefront of contemporary economics and society. Today, cutting-edge multinational corporations such as Google and Tesla are aggressively and proactively investing in next-generation Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 371 convergence technologies, such as self-driving cars, shifting the paradigm of industries in the process. However, convergence need not be confined to hi-tech industries only; it can occur on a much more familiar and smaller-scale level. Our analysis of the three subtypes of super-growth and super-old regions shows that manufacturing-based regions that have retained traces of the agriculture, forestry, and fishery industries and regions that are experiencing economic growth led by both the service and manufacturing sectors actually outperformed regions specializing in primary-sector industries. This suggests that inter-industry convergence can effectively promote the economic growth of super-growth and super-old regions. The old regions on which this study focused mostly feature economic structures that centrally, or at least partially, rely on the primary sector. In order to promote and sustain the economic growth of these regions, it is crucial to increase the income of locals by increasing the value-added of the products produced by these regions’ primary-sector industries. The key to this is found in the sixth sector, i.e., convergence- and agriculture-based industries This requires identifying and fostering secondary- and tertiary-sector industries that can grow based on the strengths of the existing primary-sector industries in the given regions. The convergence of industries across sectors should be encouraged to promote the development and emergence of the sixth sector in the long term, and local policymakers need to devise strategies for fostering such industrial development by identifying, selecting, and supporting the individual industries that make up the sixth sector. In addition, local governments should adopt roadmaps or 372 programs for, first, identifying the subcategories of the primary-, secondary, and tertiary-sector industries with growth potential in their respective regions and, second, promoting convergence among these industries.

6) Strengthen integrated governance of agro-management bodies.

Most (super-) old regions that rely on the agriculture, forestry, or fishery industries as their main source of income feature rural cooperatives or similar organizations for producing, processing, and distributing their products. This arrangement brings together actors specializing in production, processing, and distribution so as to enhance the competitiveness of the products from the given regions. Organizations specializing in certain industries or products, however, often fail to achieve the economies of scale necessary to ensure efficiency. Diverse factors of innovation are needed to ensure the sustainable economic growth of these regions, but such organizations are poorly equipped to provide these factors and resources of innovation. This highlights the importance of establishing a new governance structure that better integrates and manages the individual cooperatives and similar organizations. Toward this end, small-scale individual cooperatives that exist and operate in a fragmented manner should be brought closer together. An upper body of management encompassing these organizations should also be formed to carry out common tasks and establish connections with outside agencies and resources for innovation in R&D and marketing, thus complet- ing a single, integrated, region-wide system of innovation. Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 373

In other words, it is necessary to establish a region-wide system of innovation that brings individual cooperatives together and en- ables participants to share information, production facilities, workers, marketing, and technologies with one another to achieve an economy of scale. Local policymakers need to introduce diverse measures to support collaboration at the level of industrial organizations, and the types of collaboration should continuously evolve and become stronger, from loose research societies or joint venture commit- tees to strategic partnerships and, finally, cooperatives with binding rules. Moreover, local policymakers need to go beyond supporting individual businesses and introduce a systematic policy program that provides integrated support for all such organizations. Net- works among local businesses are crucial to maximizing the efficiency of region-wide production, purchasing, and distribution activities. In Korea, innovation centers promoting the agro-processing and food industries are found in all metropolitan cities and provinces. Management bodies governing individual businesses in cities and counties should team up with these metropolitan or provincial innovation centers to ensure the availability of a wider range of resources.

7) Centralize and streamline policy support.

Local governments provide diverse measures to support local businesses. Even in regions with aging populations, local policymakers actively devise and implement measures to enhance the competitiveness of local industries—whether primary, secondary, 374 or tertiary—and generate greater income for locals. These local policy support measures, however, lack systematic- ity and coherence, and remain separate from the policy programs of the national government, which themselves are fragmented as well. The compartmentalization of policy support programs min- imizes their effectiveness. Now that convergence is emerging as a key factor of sustainable economic growth, it is important to introduce a system that ensures the effective convergence of individual policy programs. Such a system is essential to maximizing the synergy of diverse local policy support programs. The key here is to devise a single, coherent, and integrated “umbrella” under which diverse policy measures can be customized and implemented. More specifically, it is important to identify the core factors of the existing local value chains encompassing raw materials, inter- mediary parts, modules and systems, and products, as well as diverse segments—including R&D, production, human resource development, business support, and innovation infrastructure—that are capable of generating and maximizing synergy, and strengthen those factors accordingly. This requires the introduction of integrated business support service programs that are designed to ensure that businesses themselves are able to identify and point out the various needs for technological support, human resource development, and marketing services. To achieve the common region-wide goals, it is important to centralize and streamline the diverse support programs handled by various departments and actors. Such a centralized system of policy support should reflect the conditions and needs of target Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 375 regions and industries.

8) Encourage and welcome migration to rural areas to offset the repercussions of jobless growth.

Large numbers of young people leave their hometowns for the Seoul-Gyeonggi region in search of jobs and other cultural and educational benefits. At the same time, however, there are also growing numbers of middle-aged and older people leaving the Seoul-Gyeonggi region to settle down in their rural hometown areas. Regions that have rapidly aging populations and are struggling with workforce shortages should welcome these returnees as valuable new assets for local development. Our empirical analysis confirms that, while the economic growth of (super-) growth and (super-) old regions reflects the increases in labor productivity, it is also mostly an outcome of the investment in the modernization of manufacturing facilities, which has raised income without creating new jobs. In the meantime, the primary-sector industries continue to raise the overall employment rates of these regions and contribute to local economic growth. Our analysis suggests that old regions that still rely on the primary sector need to increase employment in primary-sector industries in order to simultaneously raise the local income level and achieve local economic growth. The most effective way to achieve this is to attract and support returnees so as to realize economic growth that actually generates jobs. The increase in the number of returnees exerts various positive effects on old regions. First, returnees help restrain the pace of 376 rapid population aging in these regions. People in their 30s and younger make up more than 50 percent of the returnee population, and over a quarter of all returnees work in agriculture. The younger age makeup of these returnees thus provides newfound vitality and energy for old regions. Second, returnees also bring with them experience and exper- tise in diverse fields. With their urban savvy and education, many of these returnees even go on to serve as effective community leaders in rural communities. Third, and most importantly, returnees help enhance the value-added of agriculture and create new jobs, thereby promoting and sustaining local economic growth. Evidence for this is found in the fact that returnees own 13.2 percent of all sixth-sector businesses across Korea today. Their initiatives toward achieving innovation in agro-processing often generate new jobs for locals, which, in turn, serve to increase the income level of locals, induce greater consumption and spending, increase output, and create even more new jobs. In 2017, the working-age population in Korea will begin shrink- ing. The presence of young returnees in their 40s and younger is therefore crucial to sustaining the economic growth of rural regions with rapidly aging populations. In order for these returnees to create even greater value-added for their respective local economies, it is important for local governments to develop and provide effective training and human resource management programs and arbitrate conflicts with local natives. As the majority of returnees have no prior experience working in agriculture, local governments should design training programs that cater to their specific needs. Local Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 377 governments should also proactively organize venues for returnees and local natives to engage in communication, gain mutual un- derstanding, and build rapport, thereby minimizing unnecessary friction and enabling settlers to serve as new community leaders.

9) Utilize unique local resources to attract tourists.

An increasing number of local governments in Korea today are fostering tourism based on their unique cultural, historical, and en- vironmental resources. Unlike manufacturing, the tourism industry can grow and flourish without extensive infrastructure, and therefore requires comparatively little investment. The service industries found in (super-) growth and (super-) old regions show high degrees of specialization in creativity-, art-, and leisure-related services, due largely to the organization and hosting of local festivals and other such events that make active use of local resources to provide people with opportunities for recreation and leisure. Local festivals have been multiplying rapidly in Korea, as they are widely recognized as effective ways preserving and handing down local customs and cultures and strengthening the sense of community among locals. Many local governments, however, use local festivals merely to advertise their regions instead of offering unique and substantial programs for tourists, leading such festivals to become increasingly ineffective in attracting visitors. In order for old regions to attract more tourists, they need to do more than organize festivals and offer programs that merely ex- plain local historical or cultural resources; these regions should develop experience- and stay-oriented programs based on distinctly 378 local themes. Effective tourism promotion programs require: (1) the excavation and conservation of local cultural archetypes; (2) the development of storytelling-type programs; (3) the development of multimedia programs (offering spatio-sensuous experiences); and (4) the development of relevant merchandise catering to visitors’ demands for new experiences and satisfaction. As the examples of Mungyeong and Hamyang show, it is important to make active use of digital and multimedia technologies to organize available local resources. In order to achieve consistent increases in the number of tourists, local governments also need to introduce mid- to long- term plans and human resource development programs and foster related industries.

10) Enhance the value-added of service industries based on the sixth sector and local cultural/ecological resources.

The tertiary sector made up 58.1 percent of the local economies in super-growth and super-old regions whose economic growth was driven by both the service and manufacturing sectors. Re- gions falling into this subtype are relatively small cities located far from metropolitan or major cities. The resulting difficulty in access- ing the services of large cities is what seems to have fostered the growth of the service industries in these regions. The lack of an extensive transportation system serves to limit exchanges between these regions and larger cities, prompting the growth of small-scale retail commerce. Accordingly, these regions show relatively high degrees of specialization (with locational factors of one or greater) in the areas of specialized construction (1.16), retail (1.21), restau- Study on the Characteristics and Determinants of High-Growth Regions in the Era of Population Aging 379 rants and bars (1.10), accommodations (1.63), public administration (2.00), social welfare (1.44), and creativity-, art-, and leisure-related services (1.32). The factors driving the growth of these industries in this regional subtype can be summarized as follows. First, the service industries that are relatively strong in old regions are small-scale industries catering to the basic needs of con- sumers, such as the retail, restaurant, and accommodation industries. This is because locals prefer to satisfy their needs in these local industries rather than traveling long distances to other major cities to do so. Second, service industries grow in tandem with the expansion of the local manufacturing sector. The increasing productivity of local manufacturing businesses and the growing number of workers they attract from outside serve to boost the growth of both producer service industries and consumer service industries, such as the restaurant and retail industries. Third, the high proportions of the elderly in the populations of these regions keep the demand for social welfare services quite high, creating jobs and income in service industries that cater to seniors’ needs, such as retirement and rehabilitation facilities. Fourth, the growth of local festivals and other tourism programs foster the growth of restaurants, accommodation businesses, and creativity-, art-, and leisure-related services. The majority of service industries found in these (super-) old regions offer low value-added. Thus, in order to ensure the sustained economic growth of these regions, a number of changes need to be made, such as fostering a transition to service industries with higher value-added or enhancing the value-added of existing in- 380 dustries by strengthening their connections to other industries. Re- alistically, the diversification of service industries and enhancement of their value-added will be the most effective ways of increasing their productivity and the income they generate. Most (super-) old regions depend largely on the agriculture, forestry, and fishery industries; produce specialized crops or delicacies; and show high degrees of specialization (2.75 or higher) in food processing. As these regions possess the resources and capabilities to produce and process their own products, the service sector in these regions can be expanded by promoting the distribution and retail services. The service industries in these regions also need to be transitioned into the sixth sector by incorporating the use of local festivals and other tourism programs.