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Agglomeration externalities, innovation and regional growth: Theoretical perspectives and meta-analysis
Technological change and innovation and are central to the quest for regional development. In the globally-connected knowledge-driven economy, the relevance of agglomeration forces that rely on proximity continues to increase, paradoxically despite declining real costs of information, communication and transportation. Globally, the proportion of the population living in cities continues to grow and sprawling cities remain the engines of regional economic transformation. The growth of cities results from a complex chain that starts with scale, density and geography, which then combine with industrial structure characterised by its extent of specialisation, competition and diversity, to yield innovation and productivity growth that encourages employment expansion, and further urban growth through inward migration. This paper revisits the central part of this virtuous circle, namely the Marshall-Arrow-Romer externalities (specialisation), Jacobs externalities (diversity) and Porter externalities (competition) that have provided alternative explanations for innovation and urban growth. The paper evaluates the statistical robustness of evidence for such externalities presented in 31 scientific articles, all building on the seminal work of Glaeser et al. (1992). We aim to explain variation in estimation results using study characteristics by means of ordered probit analysis. Among the results, we find that the impact of diversity depends on how it is measured and that diversity is important for the high-tech sector. High population density increases the chance of finding positive effects of specialisation on growth. More recent data find more positive results for both specialization and diversity, suggesting that agglomeration externalities become more important over time. Finally, primary study results depend on whether or not the externalities are considered jointly and on other features of the regression model specification
๋ค์์ค ์์ ๋ถํฌ์ ๊ฑด๊ฐ ๊ด๋ จ ์ถ์ ์ง
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๋ณด๊ฑด๋ํ์ ๋ณด๊ฑดํ๊ณผ(๋ณด๊ฑดํ์ ๊ณต), 2022. 8. ์กฐ์ฑ์ผ.์ฐ๊ตฌ ๋ฐฐ๊ฒฝ
์ต๊ทผ ์ธ๊ตฌ๊ตฌ์กฐ์ ๊ธ๊ฒฉํ ๊ณ ๋ นํ์ ๊ฒฝ์ ์์ค์ ๋ฐ์ ์ ๋ฐ๋ผ ๊ฑด๊ฐํจ๋ฌ๋ค์์ ์๋ช
์ฐ์ฅ๊ณผ ๊ฐ์ ๋จ์ํ ์์ ์งํ๋ฟ๋ง ์๋๋ผ ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง(health-related quality of life, HRQOL)๊ณผ ๊ฐ์ ์ง์ ์งํ์ ์ฃผ๋ชฉํ๊ณ ์๋ค. ๊ทธ๋ฌ๋ ๊ฒฝ์ ์์ ๋ฐ ์ธ์ ์์ ๋ง์ผ๋ก๋ ํฌ๊ด์ ์ด๊ณ ๋ค์ธต์ ์ธ ์ถ์ ์ง์ ์ค๋ช
ํ๋ ๋ฐ์ ํ๊ณ๊ฐ ์๋ค. ๋จ์ํ ๊ฐ์ธ์ด ๋ณด์ ํ ์์์ ์ ๊ทธ ์์ฒด ๋ณด๋ค๋, ์ ์๋ฏธํ ์์์ด ์์ฑ๋๋ ๊ธฐ์ ๊ณผ, ์ฌํ์ ๊ด๊ณ๋ฅผ ํตํ ์์์ ๋ถํฌ ๋ฐ ์์์ ํ์ฉ๊ฐ๋ฅ์ฑ์ ๋ํ ํญ๋์ ๊ณ ๋ ค๊ฐ ํ์ํ๋ค.
์ด์ ๋ณธ ์ฐ๊ตฌ์์๋ ์ฌํ์ ์์๊ณผ ์ฃผ๊ด์ ์ฌํ๊ณ์ธต ์ธ์ ์งํ๋ฅผ ํ์ฉํ์ฌ ์์์ ๊ฐ๋
์ ๋ณด๋ค ํญ ๋๊ฒ ์ดํดํ๋ฉฐ, ๊ฐ๊ตฌ ๋ฐ ์ง์ญ์ฌํ ์์ค์์ ๋ค์ธต์ ์ธ ์์์ ๋ถํฌ ๊ตฌ์กฐ๋ฅผ ํฌ์ฐฉํ๋ค. ๋ํ ๋ค์ธต์ ์์์ด ์๊ฐ๊ณผ ๊ณต๊ฐ์ ๋ฐ๋ผ ์ด๋ป๊ฒ ๋ถํฌํ๋์ง ํ์ธํ๋ฉฐ, ์ด์ ๋ํ ๊ฑด๊ฐ ์ํฅ์ ํ์
ํ๊ณ ์ ํ๋ค. ๊ฒฐ๊ณผ์ ์ผ๋ก, ์ถ์ ์ง์ ๋ํ ์ฌํ์ ๊ฒฐ์ ์์ธ์ ์ดํด์ ํ์ ํ์ฅ์ํค๊ณ , ์ฐ๋ฆฌ ์ฌํ์ ๋ด์ฌ๋ ๊ณ์ธต ๊ธฐ๋ฐ์ ๋ถํ๋ฑ ํํฉ์ ํ์
ํ๋ค.
์ฃผ์ ์ฐ๊ตฌ๋ชฉ์ ์ ์ฒซ์งธ, ๊ฐ๊ตฌ ํ๊ฒฝ ๋ฐ ๊ฐ์ธ์ ์์์ด ์ฃผ๊ด์ ์ฌํ๊ณ์ธต ์ธ์์ ํ์ฑ์ ๋ฏธ์น๋ ์ํฅ์ ํ์
ํ๋ฉฐ, ๊ฐ๊ตฌ์๊ฐ ์ธ์ ์ฐจ์ด๋ฅผ ํ์
ํจ์ผ๋ก์จ ๊ฐ๊ตฌ๋ด ์์์ ๊ณต์ ์ ๊ธฐ์ ์ ํ์
ํ๋ค. ๋์งธ, ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง ๊ถค์ ์ ํ์
ํ๊ณ , ์ฃผ๊ด์ ์ฌํ๊ณ์ธต ์ธ์๊ณผ ๊ฐ๊ด์ ์ฌํ๊ฒฝ์ ์ ์์ค์ ๋ฐ๋ฅธ ์ถ์ ์ง ๊ถค์ ์ ํ์
ํ ํ, ๋ ๊ถค์ ์ ์ฐ๊ด์ฑ์ ๋ถ์ํจ์ผ๋ก์จ ์ฌํ๊ฒฝ์ ์ ์ง์์ ์ข
๋จ์ ์ธ ๊ฑด๊ฐ์ํฅ์ ํ์
ํ๋ค. ์
์งธ, ์ง์ญ์ฌํ์ ๋ค์ฐจ์์ ์ธ ์ฌํ ์์์ ๊ตฌ์ฑ์ฒด๋ฅผ ์ ์ํ๊ณ , ์ธ๊ตฌ์ง๋จ์ ๊ฑด๊ฐ์ ์ํฅ์ ๋ฏธ์น๋ ์ฃผ์ํ ์ฌํ ์์์ ํ์
ํ๋ค. ๋ท์งธ, ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง์ ๊ณต๊ฐ ์๊ด์ ํ์
ํ๊ณ , ์ฌํ ์์์ด ๊ฑด๊ฐ์ ๋ฏธ์น๋ ํจ๊ณผ๋ฅผ ๊ณต๊ฐ์ ์ธ ๋น์ ํ์ฑ์ ๊ธฐ๋ฐ์ผ๋ก ํ์
ํ๋ค.
์ฐ๊ตฌ ๋ฐฉ๋ฒ
์ฒซ๋ฒ์งธ ์ฐ๊ตฌ์์๋ ์ 8์ฐจ ํ๊ตญ์๋ฃํจ๋ ์๋ฃ(2013๋
)๋ฅผ ํ์ฉํด 3,984 ๊ฐ๊ตฌ์์ 18์ธ ์ด์ ์ฑ์ธ 8330๋ช
์ ์ฐ๊ตฌ๋์์ผ๋ก ํ์๊ณ , ๋๋ฒ์งธ ์ฐ๊ตฌ์์๋ 2009๋
๋ถํฐ 2018๋
๋๊น์ง์ ํ๊ตญ์๋ฃํจ๋ (์ด10์ฐจ ์กฐ์ฌ) ์๋ฃ์ ๊ท ํํจ๋ ๋์์ ์๋ฃ๋ฅผ ํ์ฉํ์๋ค. ์ธ๋ฒ์งธ์ ๋ค๋ฒ์งธ ์ฐ๊ตฌ๋ ์ง์ญ์ฌํ ์์ค์ ์ฐ๊ตฌ๋ก์, ํต๊ณ์ฒญ(KOSIS)์ ๊ณต๊ฐ์๋ฃ ๋ฐ ์ง์ญ์ฌํ๊ฑด๊ฐ์กฐ์ฌ ์๋ฃ๋ฅผ ํ์ฉํ์ฌ 250๊ฐ ์ง์ญ์ฌํ ์์ค์ผ๋ก ๋ค์ํ ์ฌํ ์์ ๋ณ์๋ฅผ ๋ณํฉํ์๋ค.
์ข
์๋ณ์์ธ ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง ์ง์(HRQoL)๋ EQ-5D ์งํ๋ฅผ ํ์ฉํ์ฌ ํ๊ตญ์ธ ๊ณ ์ ์ ๊ฐ์ค์น๋ฅผ ์ ์ฉ ํ ์ฐ์ถํ์๋ค. ์ฃผ๊ด์ ์ฌํ๊ณ์ธต ์ธ์์ ์งํ๋ MacArthur scale ์ ์ฌ์ฉํ์๋ค. ์ฌํ์๋ณธ์ ์ฌํ์ ์ฐ๊ฒฐ๋ง, ์ ๋ขฐ, ์ฌํ ์ฐธ์ฌ๋ก ๊ตฌ๋ถํ๊ณ , ๊ทธ ์ธ์๋ ๋ฌธํ, ์ฒด์ก์์ค, ๊ณต์์ ์์ ๊ฐ์ ๋ฌธํ ์์๊ณผ, ์์ฌ ์, ํ์์ง๋ฃ๊ณผ ์์, ๋ณ์, ์์๋ณ์ ์์ ๊ฐ์ ์๋ฃ ์์ ๋ฐ ์ง์ญ์ฌํ์ ์ฌํ๊ฒฝ์ ์ ํ๊ฒฝ ๋ฑ์ ๋ฐ์ํ์๋ค.
๋ถ์ ๋ฐฉ๋ฒ์ ์ฒซ๋ฒ์งธ ์ฐ๊ตฌ์์ ์ฃผ๊ด์ ์ฌํ๊ณ์ธต ์ธ์์ ๋ํ ๊ฐ๊ตฌ์๊ฐ ์๋ต์ผ์น๋๋ฅผ ํ๊ฐํ๊ธฐ ์ํ์ฌ ์ง๋จ ๋ด ์๊ด๊ณ์๋ฅผ ๊ตฌํ์๊ณ , ๋ถ์ฐ ๋ถํด๋ฅผ ํตํด ๋ณ์๋ณ ์๋์ ์ค์๋๋ฅผ ๋น๊ตํ์๋ค. ๋๋ฒ์งธ ์ฐ๊ตฌ์์๋ ๊ทธ๋ฃน ๊ธฐ๋ฐ์ ๊ถค์ ๋ชจํ(Group-based trajectory modeling, GBTM)์ ์ ์ฉํ์์ผ๋ฉฐ, ํนํ ๊ฐ๊ด์ , ์ฃผ๊ด์ ์ง์์ ๋ณํ ํจํด์ ํ๋ฒ์ ํฌ์ฐฉํ๊ธฐ ์ํ์ฌ 2๊ฐ ๋ณ์์ ๋ณํ ํจํด์ ๋์์ ํฌ์งํ๋ ๋ค์ค ๊ทธ๋ฃน ๊ธฐ๋ฐ ๊ถค์ ๋ชจํ(multi-GBTM)์ ์ ์ฉํ์๋ค. ์ธ๋ฒ์งธ ์ฐ๊ตฌ์์๋ ์ฃผ์ฑ๋ถ ๋ถ์ ๋ฐ ์ฃผ์ฑ๋ถ ํ๊ท๋ถ์์ ์ฌ์ฉํ์๋ค. ๋ค๋ฒ์งธ ์ฐ๊ตฌ์์๋ ์ง๋ฆฌ์ ๊ฐ์คํ๊ท๋ถ์(Geographically weighted regression, GWR)์ ์ ์ฉํ๊ณ ๊ทธ ํ๊ท๊ณ์์ ๋ํด K-means ๊ตฐ์ง ๋ถ์์ ์ฌ์ฉํ์๋ค. ํต๊ณ ํ๋ก๊ทธ๋จ์ STATA 16, SAS ์ํํธ์จ์ด 9.4 ๋ฒ์ , R 4.1.3๋ฒ์ ์ ์ด์ฉํ์์ผ๋ฉฐ, ์ง๋ฆฌ ๋ถ์ ์ QGIS 3.24 ๋ฐ GeoDa 1.18.0 ํ๋ก๊ทธ๋จ์ ๋ณด์กฐ์ ์ผ๋ก ์ด์ฉํ์๋ค.
์ฐ๊ตฌ ๊ฒฐ๊ณผ
๋ฒ์งธ ์ฐ๊ตฌ์์, ์ฃผ๊ฑฐ์์ ์ฑ๊ณผ ๊ฐ์ ๊ฐ๊ตฌ์ ๋ถ์ ์์ค์ ์ฃผ๊ด์ ๊ณ์ธต ์ธ์ ํ๋ฝ์ ๋ํ์ฌ ์๋นํ ์์ถฉํจ๊ณผ๋ฅผ ๊ฐ์ง๊ณ ์์ผ๋, ๊ฐ๊ตฌ ๋ด์์ ์๋ก ์์์ ๊ณต์ ํ๋ ๊ธฐ์ ์ ๋ฐ๋ผ ๊ฐ๊ตฌ์ ๊ฐ ์ธ์์ ์ฐจ์ด๊ฐ ์๋ ๊ฒ์ ํ์ธํ์๋ค. ํนํ ๋ฏธ์ฑ๋
์๋
์ ์๊ฐ ๋ง์์ง์๋ก ๋ถ๋ถ๊ฐ ๊ณ์ธต ์ธ์์ ๊ฒฉ์ฐจ๊ฐ ๋ฒ์ด์ก๊ณ , ์๋
์ธ๋, ๊ฐ๊ตฌ์ฃผ ์ธ๋, ๊ฐ๊ตฌ์ฃผ์ ๋ถ๋ชจ ์ธ๋๋ณ๋ก ์ธ๋๊ฐ ์ธ์ ์ฐจ์ด๊ฐ ์์๋ค. ์ฆ, ์ด๋ฌํ ์ธ์ ๊ฒฉ์ฐจ๋ ๊ฐ๊ตฌ์์ผ๋ก์ ์ ์ฒด์ฑ ๋ฐ ๋ถ์์๋ฌด, ํน์ ๊ฐ๊ตฌ ๋ด์์ ์ ์ ์ธ๋์๊ฒ ์์์ด ์ง์ค๋๋ ์์์ ๊ธฐ์ธํ๋ค.
๋๋ฒ์งธ ์ฐ๊ตฌ์ ๊ถค์ ๋ถ์ ๊ฒฐ๊ณผ, HRQoL์ ์๊ฐ ๊ฒฝ๊ณผ์ ๋ฐ๋ผ ์ง์์ ์ผ๋ก ์ต๊ณ ์ ์ธ 1์ ์์ค์ ์ ์งํ๊ฑฐ๋, ๋ฎ์ ์์ค์์ ์์ํ์ฌ ํํฅ ๊ณก์ ์ ๊ทธ๋ฆฌ๋ฉฐ ๊ฑด๊ฐ์ด ์
ํ๋๋ ํํ๋ง ํ์ธ๋์๋ค. ๋ํ ํ๊ตญ ์ฌํ๋ ๋ถ์ ํ ๊ฐ๊ตฌ๊ฐ ์๊ฐ์ด ์ง๋จ์ ๋ฐ๋ผ ๋์ฑ ๋น ๋ฅด๊ฒ ์๋์ฆ๊ฐ๋ฅผ ์ด๋ฃจ๋ฉฐ ์ด๋ฌํ ๊ฒฝ์ ์ ๋ถํ๋ฑ์ด ์ฌํ์ ์ง๋จํ์ ๊ธฐ์ฌํ๊ณ ์์๋ค. ๋ํ ์ด๋ฌํ ์ฌํ๊ฒฝ์ ์ ์งํ๋ ์ค์ฅ๊ธฐ์ ์ผ๋ก ๊ฑด๊ฐ ๊ถค์ ํ๋ฅ ์ ์ํฅ์ ๋ฏธ์น๋ฉฐ ๊ฑด๊ฐ ๊ฒฉ์ฐจ๋ฅผ ์
ํ์ํค๋ ๊ฒ์ ํ์ธํ์๋ค. ํํธ, ์ค์ฅ๊ธฐ์ ์ธ ์ฃผ๊ด์ ๊ณ์ธต ์ธ์ ์์ค์ ๊ฐ๊ตฌ ์๋์ ๋ณํ๋ง์ผ๋ก๋ ์ค๋ช
๋์ง ์์๋๋ฐ, ์ด๋ ๊ฐ๊ตฌ์ ๋ฒ์ฃผ๋ฅผ ๋์ด์๋ ์ฌํ์ ์์ ๋ฐ ํ๊ฒฝ์ ์ค์์ฑ์ ์์ฌํ๋ค.
์ธ๋ฒ์งธ ์ฐ๊ตฌ์์, ์ง์ญ์ฌํ๋ ๋ฌผ๋ฆฌ์ ์์ค ํ๊ฒฝ ๋ฐ ๊ฒฝ์ ์ ์์ค ์ด์ธ์๋ ์ฐ๊ฒฐํ, ๊ฒฐ์ํ, ์ธ์ง์ ์ฌํ ์๋ณธ๊ณผ, ์๋ฃ์๋น์ค์ ๊ณต๊ธ ๋ฐ ์์ ํ๊ฒฝ์ผ๋ก ์ ํํ ๋๋ ํน์ง์ด ์์๋ค. ์ด๋ฌํ ์ง์ญ์ฌํ์ ์์ ๋ถํฌ์ ํน์ฑ์ ๊ทผ๋ฆฐํจ๊ณผ๋ก์ ์ธ๊ตฌ์ง๋จ์ ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง์ ํฌ๊ฒ ์ํฅ์ ๋ฏธ์ณค๋ค. ํนํ ๋จ์ ์์ค์ ์๊ฐ ์๋, ๋ฏธ์ถฉ์กฑ ์๋ฃํ์๋์ ๊ฐ์ ์ค์ง์ ์ธ ์์์ ์ด์ฉ๊ฐ๋ฅ์ฑ์ด ์ธ๊ตฌ ๊ฑด๊ฐ์ ์ํฅ์ ๋ฏธ์ณค๋ค.
๋ค๋ฒ์งธ ์ฐ๊ตฌ์์, ์ง๋ฆฌ์ ์ธ ๊ฑฐ๋ฆฌ๋ฅผ ๋ฐ์ํ ๊ณต๊ฐ ๋ถ์ ๊ฒฐ๊ณผ, ๊ฑด๊ฐ๊ด๋ จ ์ถ์ด ์ง์ ๋์ ์์ค์ ์ง๋ฆฌ์ ์๊ธฐ์๊ด์ ๊ฐ์ก๋ค. ์ฆ ๊ฑด๊ฐํ ์ง์ญ์ฌํ๋ ๊ฑด๊ฐํ ์ง์ญ๋ผ๋ฆฌ ์๋ก ์ง๋ฆฌ์ ์ผ๋ก ๋ฐ์ ํ ๊ณต๊ฐ์ ์๊ด์ฑ์ด ์์๋ค. ๋ํ ๊ฐ ์ง์ญ์ฌํ ์์์ด ๊ฑด๊ฐ์ ๋ฏธ์น๋ ํจ๊ณผ์ฑ์ ์ง์ญ๋ง๋ค ์์ดํ๋ฉฐ, ํด๋น ํจ๊ณผ์ฑ์ ๊ตฐ์งํ ํ์์ ๋ ๊ถ์ญ ๋จ์์์ ์งํฉ์ ์ผ๋ก ์๋ํ๋ ๊ฒ์ ํ์ธํ์๋ค. ์์ธ ๋ฐ ๊ฒฝ๊ธฐ๋์์๋ ์ฌํ ์ ๋ขฐ๊ฐ ์ ์ํ ๊ฑด๊ฐ ๋ณดํธ ํจ๊ณผ๊ฐ ์์๋ค. ๊ฒฝ์๋๊ถ์์๋ ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง ์์ค์ด ๋ฎ์ ์ฌ๋์ด ์ข
๊ตํ๋์ ๋ณด๋ค ๋น๋ฒํ๊ฒ ์ฐธ์ฌํ๋ ๊ฒฝํฅ์ด ์์๋ค. ์ ๋ผ๋๊ถ์์๋ ๋ฒฝ์ง ์ง์ญ์ 1์ธ ๊ฐ๊ตฌ๊ฐ ๊ฑด๊ฐ ์ํ ์์์์ผ๋ฉฐ, ๊ฐ์ ๋ฐ ์ถฉ์ฒญ๋๊ถ์์๋ ๋ฏธ์ถฉ์กฑ ์๋ฃ ํ์๋๊ฐ ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง๊ณผ ์ ์ํ ๋ถ์ ์ฐ๊ด์ฑ์ ๋ณด์๋ค.
๊ฒฐ๋ก
๋ค์์ค์ ๊ฑธ์น ์์์ ๋ถํฌ ๋ฐ ํ์ฉ๊ฐ๋ฅ์ฑ์ ๊ฒฉ์ฐจ๊ฐ ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง์ ๋ฏธ์น๋ ์ํฅ์ ํ์ธํ์๋ค. ํ๊ตญ ์ฌํ๋ ์๊ฐ ๊ฒฝ๊ณผ์ ๋ฐ๋ผ ๊ฐ๊ตฌ ์๋์ ๊ธฐ๋ฐํ ๊ณ์ธตํ๊ฐ ๊ฒฌ๊ณ ํด์ง๊ณ ์์ผ๋ฉฐ ๊ฐ๊ด์ , ์ฃผ๊ด์ ์ฌํ ์ด๋์ ๊ฐ๋ฅ์ฑ์ด ์ ์ฝ๋๋ ๊ฒฝ์ง๋ ์ฌํ์ด๋ค. ์ฃผ๊ฑฐ์์ ์ฑ์ ๊ฐ๊ด์ ์๋ ๋๋น ์ฃผ๊ด์ ์์ค์ด ๋ฎ์์ง๋๋ฐ ๋ํ ๋ณดํธํจ๊ณผ๊ฐ ์๋ค. ๊ทธ๋ฌ๋ ๋ฌผ๋ฆฌ์ ์ฃผ๊ฑฐ๊ณต๊ฐ๊ณผ ๊ฒฝ์ ์ ์์์ ๊ณต์ ํ๋ ํ ๊ฐ์ ์์์๋ ๋ถ์์๋ฌด์ ๊ฐ์ ๊ฐ๊ตฌ์ ์ ์ฒด์ฑ์ด ์์ ํ์ฉ์ ์ํฅ์ ๋ฏธ์ณ ์ฃผ๊ด์ ์ธ ์ฌํ๊ณ์ธต ์ธ์์ ๊ฒฉ์ฐจ๋ฅผ ๋ฐ์์ํค๊ณ ์๋ค.
ํํธ, ๊ฑด๊ฐ๊ด๋ จ ์ถ์ ์ง์ ์ข
๋จ์ ์ผ๋ก ์ํฅ๊ณก์ ์ ๋์ง ์์ผ๋ฏ๋ก ์
ํ๋ฅผ ๋ฐฉ์ง ๋ฐ ๋ณดํธํ๋ ๊ฒ์ด ์ค์ํ๋ค. ์ด๋ ๊ฐ์ธ๊ณผ ๊ฐ๊ตฌ ์์ค์ ๋์ด ๋ค์ํ ์ฌํ ์์์ผ๋ก์ ์ ๊ทผ ๊ฐ๋ฅ์ฑ ๋ฐ ํ์ฉ ๊ฐ๋ฅ์ฑ์ด ๋ณด์ฅ๋์ด์ผ ๊ฐ๋ฅํ ์ผ์ด๋ค. ์ง์ญ ์ฌํ์ ์์์ ์ ํํํด๋ณด๋ฉด, ๋ฌผ๋ฆฌ์ ์์ค์ด์ธ์๋ ๋ณด๊ฑด์๋ฃ์๋น์ค์ ์์์ ๊ณต๊ธ ๊ท ํ, ๊ทธ๋ฆฌ๊ณ ์ฌํ์๋ณธ ํ๊ฒฝ์ผ๋ก ํน์ฑํ ๋๋๋ฐ, ์ด๋ฌํ ์ง์ญ์ฌํ์ ์์ ์ ํ์ ์ธ๊ตฌ์ง๋จ ๊ฑด๊ฐ์ ์ํฅ์ ๋ฏธ์น๋ค. ๋ํ ๊ฑด๊ฐํ ์ง์ญ์ฌํ๋ ๊ฑด๊ฐํ ์ง์ญ์ฌํ๋ผ๋ฆฌ, ๊ฑด๊ฐ ๋ฐํ์ง์ญ์ ๋ฐํ์ง์ญ๋ผ๋ฆฌ ๋์ ๊ณต๊ฐ์ ์๊ธฐ์๊ด์ ๊ฐ์ง๋ฉฐ, ์์์ ํจ๊ณผ์ฑ์ด ๊ถ์ญ๋ณ๋ก ๊ตฐ์งํ ๋๋ ์ง์ญ์ฑ์ ๋๋ค๋ ์ ์ ์ ์ํ์ฌ ์์ ์ฌ๋ถ๋ฐฐ ์ ์ฑ
์ ์๋ฆฝํ์ฌ์ผ ํ๋ค. ์ฆ, ํฅํ ์ง์ญ ๋ณด๊ฑด ์ ์ฑ
์๋ฆฝ ์์๋ ๋จ์ํ ์์์ ์์ ๊ท ๋ฑํํ๋ ์ ์ฑ
๋ณด๋ค, ํ์ ๋ ์์์ ์์ ๊ฐ๊ตฌ ์ ํ๋ณ๋ก, ์ง์ญ๋ณ๋ก, ์ด๋ ์์ค์ผ๋ก ์ง์ค ๋ถ๋ฐฐํ๋ ๊ฒ์ด ๊ฐ์ฅ ๋น์ฉํจ๊ณผ์ ์ผ์ง์ ๊ธฐ๋ฐํ์ฌ ์ง์ญ ํนํ ์ ๋ต์ ์๋ฆฝํ์ฌ์ผ ํ๋ค.
์ด์์ ์ข
ํฉํ๋ฉด, ํ ๊ฐ์ธ์ด ์ด๋ ํ ๊ฐ์กฑ ์ญํ ์ ์๋ฌด๋ฅผ ๊ฐ์ง๋์ง, ์ด๋ ์ง์ญ์ฌํ์ ๊ฑฐ์ฃผํ๋์ง์ ๋ฐ๋ผ ์์์ ํ์ฉ๊ฐ๋ฅ์ฑ๊ณผ ํจ๊ณผ์ฑ์ ์์ดํจ์ ๋ณด์ฌ์ค๋ค. ์ด๋ฌํ ๋ด์ฌ์ ์์ฑ์ ์ค์ฅ๊ธฐ์ ์ผ๋ก, ๊ทธ๋ฆฌ๊ณ ๊ณต๊ฐ์ ์ผ๋ก ๋์ฑ ํฐ ๊ฑด๊ฐ ๊ฒฉ์ฐจ๋ฅผ ๋ถ๋ฌ์ผ์ผํจ๋ค๋ ์ ์์ ๊ฑด๊ฐ ํํ์ฑ ๋ฐ ์์์ ์ฌ๋ถ๋ฐฐ ์ ์ฑ
์ ์์ฌํ๋ ๋ฐ๊ฐ ํฌ๋ค.Background The recent dynamics of population aging and economic development have drawn renewed interest to the health paradigm. Rather than a quantitative indicator, such as a prolonged life, qualitative indicators, such as health-related quality of life (HRQoL), have become of interest. However, concepts of economic or human capital cannot fully explain the quality of life. Moreover, it is not only the amount of resources owned per se but also mechanisms of generation, distribution, and availability of valuable resources that are important for understanding the social determinants of HRQoL. In general, social determinants of health cumulatively operate over long periods of time and are more effectively investigated by longitudinal perspectives. These resources can be multidimensional, ranging from the material environment to social relationships, and can be distributed within a family or among communities. Ecological differentiation stems from community characteristics and is very much a spatial affair. Here, this thesis aims to evaluate the broader concept of resources using a subjective measure of social status and social resource indicators. Then, it aims to capture the structure of multilevel resource distribution as it is dispersed over time and space. Finally, this aims to expand the framework of social determinants of HRQoL and reveal the health inequalities embedded in our society.
The study objectives are as follows. First, the determinants of subjective social status (SSS) were investigated among household members, focusing on the household environment. Then, differences in SSS among members and gaps between objective income and SSS levels were assessed. Second, changing patterns of socioeconomic status were investigated over time and longitudinal effects of socioeconomic status on HRQoL trajectories were assessed. Then, combined changes in patterns of objective and subjective status (i.e., multiple socioeconomic status trajectories) and the HRQoL trajectories were derived, with time gaps. The prospective effects of socioeconomic transition on HRQoL trajectories were analyzed. Third, the resource composite was defined at the community level by combining healthcare resources, cultural infrastructure, and social capital, such as social networks, as well as the neighborhood environment. Then, types of outdoor resources that are crucial to population health were investigated. Finally, spatial correlations in HRQoL were determined and effects of social resources on HRQoL were investigated, considering geographical variations.
Methods The study population was adults over 18 years old in the eighth wave (2013) of the Korea Health Panel Survey for the first study, composed of 3,984 households and 8,330 individuals. As the second was a longitudinal study, we made the dataset a balanced panel that respondents answered in all ten waves of the Korea Health Panel (2009โ2018). As the third and fourth were ecological studies, we collected community variables via two types of data librariesโOSIS and the Community Health Survey website. We then aggregated overall data at the 250 community level.
The dependent variable of HRQoL was calculated using the EQ-5D index with the weights for Koreans. We used the MacArthur scale to measure household SSS. The other explanatory variables consisted of social resources (trust, social network, and social participation), cultural resources (cultural and sports infrastructures and parks), healthcare resources (doctors, essential medical clinics, tertiary hospitals, and nursing hospitals), and communityโs socioeconomic status.
Regarding methodologies, we applied the intra-class correlation coefficient to investigate the response reliabilities on household SSS among household members for the first study. In addition, we assessed the importance of determinants on SSS using variance decomposition. For the second study, we used group-based trajectory modeling to identify health trajectories and group-based multi-trajectory modeling to draw multi-SES trajectories. The third study was analyzed using principal component analysis and principal component regression modeling. For the spatial analysis, the fourth study used the geographically weighted regression (GWR) and k-means clustering of the GWR coefficients. We used the STATA 16, SAS software 9.4 version, R version of 4.1.3., QGIS 3.24 and GeoDa 1.18.0 in the adequate analysis.
Results For the first study, Housing safety and household wealth, which contributed to 65.7% of the variance in SSS, act as a buffer to downgrade one's SSS. However, there were significant differences between household members according to the dynamics of relational resource sharing. In particular, the perceptions of married couples were consistent, although this decreased as they nurtured more underage children. There are SSS gaps across generations between the ages of the head of household's parents, head of household, and children.
For the second study of trajectory modeling, four types of multi-SES trajectories were derived from 2009 to 2013. In the multi-SES trajectories, the richer in 2009 had steeper income growth during the period, while the shapes of the SSS were kept unchangeable over time. The following HRQoL trajectories from 2013 to 2018 showed three distinctive patternsโthe 4.3% of individuals showed a low and declining pattern while the other two trajectories remained high and stable. The objective and subjective socioeconomic status, respectively, at baseline were strongly associated with the following health trajectories.
For the third study, the communities can be categorized into several principal components (PC). The seven PCs explicitly represent the community characteristics such as (1) structural environments regarding facilities and physical structure; (2)-(3) the set of demand and supply in healthcare; (4) bridging; (5) cognitive; (6) bonding social capital; and (7) economic affluence of the community. These first to seventh PCs explain 46.4% of the HRQoL variance at the community level and are distinctively associated with the HRQoL level. In particular, the structural environment significantly influences population health, implying the neighborhood effect on health.
The fourth spatial analysis study showed that HRQoL at the community level has spatial autocorrelation, which means healthy regions are geographically clustered with healthy ones. Moreover, resources do or do not exert effectiveness depending on the regions. Social trust effectively increases HRQoL only in the Seoul and Gyeonggi-do regions. Meanwhile, the religious activities in the Busan and Gyunsang-do regions unexpectedly showed a negative association with health. Unmet medical needs have become a critical health agenda, specifically in the eastern and interior regions of South Korea. Urbanization of the city was positively associated with health on the west side. The aging index is negatively associated with the north and interior regions. The single-person household has become a risk factor in Jeollanam-do and Gangwon-do regions. This differential effectiveness can be spatially clustered and distinguished into five clusters based on the GWR coefficients. That is, the effectiveness of the resources works collectively with some degree of administrative spatial range.
Conclusion This study investigated the distribution of multiple levels of resources across households and communities and their health impacts. Taken together, the results indicate that South Korea is a risk-bearing society. The HRQoL patterns were either stable or decreased, but not increased. In addition, HRQoL was spatially clustered at high and low levels of HRQoL. These health patterns suggest longitudinal deterioration and geographical disparities in health. The availability of resources differed according to household environment and family roles. Furthermore, the effectiveness of social resources in the community, such as social capital, differed according to region. This geographical pattern of resource effects on health indicates a spatially shaped social process that gives rise to social inequality. In sum, these findings suggest that the originating family, and where a person lives, determines their health status, highlighting the importance of resource redistribution in enhancing population health. Considering that the administrative district boundary is an effective policy target, the regional-specific healthcare policy for communities should allocate limited resources to areas and households in need, and not focus on equalizing the resources.Chapter 1.
Overall introduction๏ผ
1.1. Study Background๏ผ
1.2. Study design and objectives๏ผ๏ผ
Chapter 2.
Resource sharing model for subjective social status at the
household level๏ผ๏ผ
2.1. Introduction๏ผ๏ผ
2.2. Methods๏ผ๏ผ
2.3. Results๏ผ๏ผ
2.4. Discussion ๏ผ๏ผ
2.5. Supplementary data ๏ผ๏ผ
Appendix A. Distribution of household income and subjective social status among the study population ๏ผ๏ผ
Appendix B. Detailed information on the intra-class correlation coefficients of subjective social status ๏ผ๏ผ
Appendix C. Post hoc analyses ๏ผ๏ผ
Chapter 3.
Trajectories of health-related quality of life by change pattern of objective and subjective social status ๏ผ๏ผ
3.1. Introduction ๏ผ๏ผ
3.2. Methods ๏ผ๏ผ
3.3. Results ๏ผ๏ผ
3.4. Discussion ๏ผ๏ผ
3.5. Supplementary data ๏ผ๏ผ
Appendix A. Sensitivity analyses for missing using MCAR and MAR test ๏ผ๏ผ
Appendix B. Selection criteria for the optimal trajectory model ๏ผ๏ผ
Chapter 4.
Diverse social resources for health-related quality of life in the communities๏ผ๏ผ๏ผ
4.1. Introduction ๏ผ๏ผ๏ผ
4.2. Methods ๏ผ๏ผ๏ผ
4.3. Results ๏ผ๏ผ๏ผ
4.4. Discussion ๏ผ๏ผ๏ผ
4.5. Supplementary data ๏ผ๏ผ๏ผ
Appendix A. Correlation of variables and OLS model ๏ผ๏ผ๏ผ
Appendix B. Detailed information on PCA and PCR results ๏ผ๏ผ๏ผ
Appendix C. Sensitivity analyses: Comparison to other dimension reduction methods๏ผ๏ผ๏ผ
Chapter 5
Spatial dependences of social resources on health-related quality of life๏ผ๏ผ๏ผ
5.1. Introduction ๏ผ๏ผ๏ผ
5.2. Methods ๏ผ๏ผ๏ผ
5.3. Results ๏ผ๏ผ๏ผ
5.4. Discussion ๏ผ๏ผ๏ผ
5.5. Supplementary data ๏ผ๏ผ๏ผ
Appendix A. Spatial distributions of HRQoL in 2011, 2015, and 2019๏ผ๏ผ๏ผ
Appendix B. Detailed information on the 2019 GWR modeling ๏ผ๏ผ๏ผ
Appendix C. Sensitivity analyses: Validation of the โreligious activitiesโ coefficient ๏ผ๏ผ๏ผ
Chapter 6
Overall discussion ๏ผ๏ผ๏ผ
6.1. Summary of the studies (Chapter 2-Chapter5) ๏ผ๏ผ๏ผ
6.2. Framework of Multilevel Resource Distribution ๏ผ๏ผ๏ผ
6.3. Overall discussion ๏ผ๏ผ๏ผ
6.4. Overall conclusions ๏ผ๏ผ๏ผ
References ๏ผ๏ผ๏ผ
๊ตญ๋ฌธ ์ด๋ก ๏ผ๏ผ๏ผ๋ฐ
Of milk and honey : returns to education and migration of filipinos
Previous studies show high returns to primary education and decreasing returns to education in the Philippines. The first part of this thesis shows that standard estimates of returns to education capture the effects of ability and education quality. It finds that accounting for education quality reduces returns to education and that returns to education quality amount to three-fourths the returns to quantity of education. Moreover, accounting for ability using sibling fixed-effects estimation reduces returns to schooling by 70 percent, yields no significant returns to basic education, and yields increasing returns to higher education. The study also finds unequal education returns across Philippine regions associated with uneven economic development, which may be driving internal and international migration of Filipinos. The second part of this thesis aims to estimate the impacts of proximate and underlying factors on both permanent and temporary migration from the Philippines. Contrary to theory, it finds that migration rises with increasing domestic wages, providing additional insight into the empirical literature on the 'migration hump'. While permanent and temporary migration respond the same way to most 'push and pull' factors, findings suggest that permanent migrants are positively selected from the Philippine labor force while temporary migrants are negatively selected in the destination labor force. Although temporary migrants earn lower wages than natives in the destination countries, they respond positively to destination wages. The third part of this thesis aims to estimate the returns to migration and education for overseas Filipino workers. It finds that earnings of overseas Filipino workers in most key destinations are higher than those of domestic workers, but their returns to schooling are not significantly different from, or are even lower than, those of domestic workers. These findings confirm the negative selection of temporary migrants. Apart from purchasing power parity gains to either earnings or returns to schooling, there are also monetary gains in the conversion of foreign earnings to the local currency through the US dollar (as in the case of remittances)
Equity and efficiency preferences of health policy makers in China - a stated preference analysis
Background Macroeconomic growth in China enables significant progress in health care and public health. It faces difficult choices regarding access, quality and affordability, while dealing with the increasing burden of chronic diseases. Policymakers are pressured to make complex decisions while implementing health strategies. This study shows how this process could be structured and reports the specific equity and efficiency preferences among Chinese policymakers.Methods In total, 78 regional, provincial and national level policymakers with considerable experience participated in a discrete choice experiment, weighting the relative importance of six policy attributes describing equity and efficiency. Results from a conditional logistic model are presented for the six criteria, measuring the associated weights. Observed and unobserved heterogeneities were incorporated and tested in the model. Findings are used to give an example of ranking health interventions in relation to the present disease burden in China.Results In general, respondents showed strong preference for efficiency criteria i.e. total beneficiaries and cost-effectiveness as the most important attributes in decision making over equity criteria. Hence, priority interventions would be those conditions that are most prevalent in the country and cost least per health gain.Conclusion Although efficiency criteria override equity ones, major health threats in China would be targeted. Multicriteria decision analysis makes explicit important trade-offs between efficiency and equity, leading to explicit, transparent and rational policy makin
Trade, Foreign Investment, and Industrial Policy
During the last three decades, developing countries have made enormous strides in opening up their protected domestic markets to international trade and foreign investment. Yet most countries have not simply opened up their markets. They have also instituted a range of policies to encourage exports, attract foreign direct investment(FDI), promote innovation, and favor some industries over others. This leads to the following question: is openness to trade and FDI alone sufficient to achieve high growth rates in developing countries? If harnessing the gains from globalization requires additional policies, can we identify them? While some types of complementary policies, such as building roads and ports, are not controversial, others are. Bhagwati's suggestion to "attract foreign funds" implies tilting incentives in favor of foreign investors, which means abandoning policy neutrality. Our goal in this chapter is to explore the popular but controversial idea that developing countries benefit from abandoning policy neutrality vis-a-vis trade, FDI and resource allocation across industries.Trade, Foreign Investment, Industrial Policy, Developing Countries
Essays on poverty issues: microeconomic evidence from african countries
Using household level panel data, the thesis provides comprehensive empirical evidence on poverty issues. The thesis constructs spatial and inter-temporal utility consistent poverty lines for Uganda, which are used as inputs to study the sources of poverty, distinguish chronic poverty from transitory poverty and the mechanisms affecting poverty persistence. Based on these poverty lines which are consistent across space and time, the poverty headcount in Uganda increases by about 9% as one moves from 2005 to 2009. In contrast, the official report suggests a reduction in poverty headcount by about 4.5% which is mainly due to low food and non-food consumer price indexes and low food share. Poverty in Uganda is largely chronic. The highest burden of inter-temporal poverty ascribes to households living in the North. Households with a large number of dependent members contribute to inter-temporal poverty more than their population share. The thesis estimates the dynamic random effect probit models and endogenous switching regression. After controlling for observed and unobserved differences in individual characteristics, the thesis still finds strong evidence of state dependence, which is that past poverty actually increases the risk of future poverty. In the presence of genuine state dependence, short run polices are effective.
Since consumption in the household surveys is often measured with error, the thesis applies the mixed latent Markov model to estimate the extent of true mobility into and out of poverty. It finds that measurement error overstates the observed poverty transition probabilities or understates the true poverty persistence. Since the actual poverty persistence rate is at least 61%, the poverty in Uganda is largely permanent, not transitory. Measurement error also understates the impacts of observed individual characteristics on making poverty transition from one state to another. Land size per capita, having mobile phone and TV-radio reduce the probability of transiting into poverty as well as increase the chances of poverty exit. The empirical evidence suggests that policy makers have to target households whose consumption slightly above the poverty line and households who are very poor. Since poverty is state dependence, short run policies are effective to keep individuals not to fall into poverty in the first place because once they are poor, they are less likely to exit poverty. Since poverty is mainly chronic in Uganda, on the other hand, long term intervention through increasing human and physical capital and the returns to these assets is effective to the very poor households. Using employer- employee panel data from Ghana, the thesis also finds that poor women are disproportionately sorting into low paying firms. Even after controlling for gender difference in individuals endowments and sorting effects, firms actually pay different wage premium for comparable female and male. When wage inequality increases among the poor, chronic poverty increases. The result suggests that targeting female dominant firms to increase their productivity helps mitigate the national level chronic poverty. The thesis also identifies the type of firms that pay equal premium for comparable gender attributes
ILR School Ph.D. Dissertations
Compiled by Susan LaCette.ILRSchoolPhD.pdf: 4022 downloads, before Oct. 1, 2020
Cultural capital in context: Heterogeneous returns to cultural capital across schooling environments
AbstractThis paper tests two competing explanations of differences in returns to cultural capital across schooling environments: Cultural reproduction (cultural capital yields a higher returns in high-achieving environments than in low-achieving ones) and cultural mobility (cultural capital yields higher returns in low-achieving environments). Using multilevel mixture models, empirical results from analyses based on PISA data from three countries (Canada, Germany, and Sweden) show that returns to cultural capital tend to be higher in low-achieving schooling environments than in high-achieving ones. These results principally support the cultural mobility explanation and suggest that research should pay explicit attention to the institutional contexts in which cultural capital is converted into educational success
The neighbourhood environment and profiles of the metabolic syndrome
Background: There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components.
Methods: We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO2 and PM2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles.
Results: LCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO2 were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM2.5 was associated with unhealthier metabolic profiles with MetS.
Conclusions: This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components
Social Uprisings: Conceptualization, Measurement, Causes and Implications
The PhD thesis titled Social Uprisings: Conceptualization, Measurement, Causes and Implications consists of four stand alone papers. The first two papers are the essential building blocks to the overall thesis. The first paper provides the conceptualization of social uprisings. Upon the findings of the first paper, the social uprisings composite indicator (SUCI) is constructed in a co-authored second paper with Prof. Hayo. The final two papers are applications for the study of social uprisings using the newly constructed SUCI.
The first paper is titled Conceptualizing Social Uprisings. The paper starts by identifying the gap in literature in the study of revolutions. Researchers criticize the ambiguity of the term revolution. It is interesting that this criticism has been reported in extant literature to researchers as early as Yoder (1926) and it is still validated by Beck (2014). Despite the advancement of research methods and various papers published on the topic of revolution. It appears that the term does not have a consensus for its meaning
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