3,553 research outputs found

    Low fertility and long run growth in an economy with a large public sector

    Get PDF
    There is plenty of evidence that growth has a negative relation to fertility and dependency ratios. Recently it has been suggested that low fertility countries may be caught in a trap that is hard to get out of. One important mechanism in such a trap would be social interaction and its effect on the ideal family size. Such social interaction mechanisms are hard to capture in formal models, therefore we use an agent based simulation model to investigate the issue. In our experimental setup a stable growth and population path is provoked into a fertility trap by rising relative child costs linked to positive growth. Even rather large increases in child benefits are then insufficient to get out of the trap. However, the small number of children temporarily enables the economy to grow faster for several decades. Removing the adaptation of social norms turns out to disarm the trap.low fertility trap; social norms relative income; economic growth

    Towards a Sustainable Life: Smart and Green Design in Buildings and Community

    Get PDF
    This Special Issue includes contributions about occupantsโ€™ sustainable living in buildings and communities, highlighting issues surrounding the sustainable development of our environments and lives by emphasizing smart and green design perspectives. This Special Issue specifically focuses on research and case studies that develop promising methods for the sustainable development of our environment and identify factors critical to the application of a sustainable paradigm for quality of life from a user-oriented perspective. After a rigorous review of the submissions by experts, fourteen articles concerning sustainable living and development are published in this Special Issue, written by authors sharing their expertise and approaches to the concept and application of sustainability in their fields. The fourteen contributions to this special issue can be categorized into four groups, depending on the issues that they address. All the proposed methods, models, and applications in these studies contribute to the current understanding of the adoption of the sustainability paradigm and are likely to inspire further research addressing the challenges of constructing sustainable buildings and communities resulting in a sustainable life for all of society

    Low fertility and long-run growth in an economy with a large public sector

    Full text link
    Recently it has been suggested that low fertility countries may be caught in a trap that is hard to get out of. One important mechanism in such a trap would be social interaction and its effect on the ideal family size. Such social interaction mechanisms are hard to capture in formal models, therefore we use an agent-based simulation model to investigate the issue. In our experimental setup a stable growth and population path is calibrated to Swedish data using the Swedish social policy setup. The model is provoked into a fertility trap by increasing relative child costs linked to positive growth. Even rather large increases in child benefits are then insufficient to get out of the trap. However, the small number of children temporarily enables the economy to grow faster for several decades. Removing the adaptation of social norms turns out to disarm the trap.Il a รฉtรฉ suggรฉrรฉ rรฉcemment que les pays ร  basse fรฉconditรฉ pourraient รชtre victimes dโ€™un piรจge dont ils auraient du mal ร  se dรฉgager. Un mรฉcanisme essentiel dans ce piรจge serait lโ€™interaction sociale et son effet sur la taille idรฉale de famille. Des mรฉcanismes de ce type sont difficiles ร  reprรฉsenter dans un modรจle formel, et cโ€™est pourquoi nous avons eu recours ร  un modรจle de simulation multi-agents pour explorer le processus. Dans notre dispositif expรฉrimental, un modรจle de croissance et de population stable est calibrรฉ aux donnรฉes suรฉdoises, en utilisant la configuration suรฉdoise de politique sociale. Le modรจle est entraรฎnรฉ dans un piรจge de fรฉconditรฉ en รฉlevant les coรปts relatifs de lโ€™enfant en lien avec la croissance positive. Dans ce cas, mรชme des augmentations importantes des prestations familiales sont insuffisantes pour sortir du piรจge. Toutefois, le petit nombre dโ€™enfants permet temporairement ร  lโ€™รฉconomie de croรฎtre plus rapidement pendant quelques dรฉcennies. Lโ€™arrรชt de lโ€™adaptation aux normes sociales conduit ร  une neutralisation du piรจge

    Shrinking population and the urban hierarchy

    Get PDF
    This paper examines whether population shrinkage leads to changes in urban hierarchy in terms of their relative size and function from the standpoint of the new economic geography. We find some salient patterns in which small cities in the agglomeration shadow become relatively bigger as medium industries spill over on them. This appears to be quite robust against a variation in the rate of natural change among cities. Thus, rank-size relationship and the urban hierarchy are partly disrupted as population shrinks. Regarding the welfare of the residents, a lower demand for land initially causes rent to go down, which boosts the utility. However, the illusion is short-lived because markets soon begin to shrink and suppress wages. We also find that it is better to maintain a slow pace of overall population decline in the long-term perspective. More importantly, it is crucial to sustain the relative livability of smaller cities to minimize the overall loss of utility

    Overlapping Generations Computable General Equilibrium Model Approach

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๊ธฐ์ˆ ๊ฒฝ์˜ยท๊ฒฝ์ œยท์ •์ฑ…์ „๊ณต, 2019. 2. ๊ตฌ์œค๋ชจ.Over the last few decades, Korea has been recognized as one of the most dynamic economies in the world. Recently, however, the country has lost its growth momentum and concerns over its stagnant economy have mounted. Among many contributors, this study is centered on deindustrialization (shift to service economy) and an aging population. To address the two issues, an age-specific division of the labor system is proposed as an alternative. The core idea is to allocate workers of various ages to better suited sectors based on the sectoral and occupational productivity by age. The age-based reallocation of labor is believed to increase overall productivity, and thus, production of the entire economy. Among a number of policies to realize the intended division of labor, the purpose of this study is to investigate the effects of incentive policies in reallocating workers of different generations to better suited sectors. This paper designs five different incentive policy scenarios, each of which intends sectoral switches in different directions by various age-groups. To examine the reallocation incentive policies, this study adopts the four-period Overlapping Generations (OLG) Computable General Equilibrium Model, incorporating individuals heterogeneity in abilities and career path choices. The general trend of heterogeneous attributes is estimated with labor and income panel data. The findings show that there are two types of contributors to the labor reallocation results intended by the policies, the incentive beneficiaries changing their sector and non-recipients who also switch their sectors due to changes in economic variables, including wage rate. It is observed that for a certain incentive scenario, the contribution of sector switches indirectly affected by the policies is the same or even larger than that of direct incentive benefits. Furthermore, a different mix of incentive policies results in various levels of discrepancy in the sectoral standard wage rates. Hence, it is of great importance to carefully examine the direct and indirect effects of incentive policies in a long-term period, as well as the wage rate inequality for better policy-making.ํ•œ๊ตญ์€ ๊ณผ๊ฑฐ ๊ฐ€์žฅ ์—ญ๋™์ ์ธ ๊ฒฝ์ œ ์ค‘ ํ•˜๋‚˜๋กœ ๋ถ„๋ฅ˜๋˜์—ˆ์ง€๋งŒ, ํ˜„์žฌ๋Š” ๊ฒฝ์ œ ์„ฑ์žฅ์˜ ๋™๋ ฅ์„ ์žƒ์–ด ๊ฐ€๊ณ  ์žˆ๋‹ค. ๋‹ค์–‘ํ•œ ์š”์†Œ๋“ค ์ค‘์—์„œ, ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณ ๋ นํ™”์™€ ๊ฒฝ์ œ์˜ ํƒˆ์‚ฐ์—…ํ™”(์„œ๋น„์Šคํ™”)์— ์ค‘์ ์„ ๋‘๊ณ  ์žˆ๋‹ค. ์ด ๋‘๊ฐ€์ง€ ํ˜„์•ˆ์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ œ์•ˆ๋˜๋Š” ๋ฐฉ๋ฒ• ์ค‘ ํ•˜๋‚˜๋Š” ์ฒญ์žฅ๋…„์ธต๊ณผ ๊ณ ๋ น์ธต ๋…ธ๋™์ž๋ฅผ ๊ฐ๊ฐ ๋น„๊ต ์šฐ์œ„๊ฐ€ ์žˆ๋Š” ์‚ฐ์—…๊ตฐ์œผ๋กœ์˜ ๋…ธ๋™ ๋ถ„์—…์ด ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์—ฐ๋ น๋ณ„ ๋…ธ๋™ ๋ถ„์—… ์ •์ฑ… ๋ถ„์„์„ ์œ„ํ•œ ๊ธฐ์ดˆ ๋‹จ๊ณ„๋กœ ์—ฐ๋ น์— ๋”ฐ๋ฅธ ์‚ฐ์—…๊ตฐ ์ด๋™์„ ์œ ๋„ํ•˜๊ธฐ ์œ„ํ•œ ๋ณด์กฐ๊ธˆ์„ ์ œ๊ณตํ•˜๋Š” ์ •์ฑ…์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋ฅผ ์œ„ํ•ด์„œ 4๊ธฐ ์ค‘์ฒฉ์„ธ๋Œ€ ์—ฐ์‚ฐ๊ฐ€๋Šฅ ์ผ๋ฐ˜๊ท ํ˜•๋ชจํ˜•์„ ์ด์šฉํ•œ๋‹ค. ๋˜ํ•œ, ํ•œ๊ตญ ๋…ธ๋™ ๋ฐ ์ž„๊ธˆ ํŒจ๋„ ์ž๋ฃŒ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๊ฐœ์ธ์˜ ์‚ฐ์—…๋ณ„, ๊ทธ๋ฆฌ๊ณ  ์—ฐ๋ น๋ณ„ ๋Šฅ๋ ฅ ์ด์งˆ์„ฑ์„ ๋ฐ˜์˜ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด ๋ชจํ˜•์„ ํ†ตํ•˜์—ฌ ํŠน์ • ์—ฐ๋ น ๋˜๋Š” ํŠน์ • ์‚ฐ์—…์œผ๋กœ์˜ ์ง„์ž…์„ ์œ ๋„ํ•˜๋Š” 5๊ฐ€์ง€ ๋ณด์กฐ๊ธˆ ์ •์ฑ… ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ฐ€์ƒ์˜ ์‹œ๋‚˜๋ฆฌ์˜ค ๊ฒฐ๊ณผ๋Š” ๋ณด์กฐ๊ธˆ์˜ ์ง์ ‘ ์ˆ˜ํ˜œ์ž ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์ž„๊ธˆ๋ฅ ๊ณผ ๊ฐ™์€ ๊ฒฝ์ œ๋ณ€์ˆ˜๋“ค์˜ ๋ณ€ํ™”๋กœ ์ธํ•ด ๊ฐ„์ ‘์ ์œผ๋กœ ์ •์ฑ…์˜ ์˜ํ–ฅ์„ ๋ฐ›๋Š” ๋…ธ๋™์ž๊ฐ€ ์กด์žฌํ•จ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋˜ํ•œ, ํŠน์ • ์‹œ๋‚˜๋ฆฌ์˜ค์—์„œ๋Š” ๋ณด์กฐ๊ธˆ ๋น„์ˆ˜ํ˜œ์ž๊ฐ€ ์‚ฐ์—…๋ณ„ ๋…ธ๋™ ์žฌ๋ถ„๋ฐฐ์— ๊ธฐ์—ฌํ•˜๋Š” ๋ฐ”๊ฐ€ ๋ณด์กฐ๊ธˆ ์ˆ˜ํ˜œ์ž์™€ ๊ฐ™๊ฑฐ๋‚˜ ๊ทธ ๋ณด๋‹ค ํด ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์ด ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ํ•œ ์„ธ๋Œ€๋งŒ์˜ ์‚ฐ์—… ์ด๋™ ๋ณด๋‹ค๋Š” ๋‹ค์–‘ํ•œ ์„ธ๋Œ€์˜ ๋‹ค๋ฅธ ๋ฐฉํ–ฅ์œผ๋กœ์˜ ์‚ฐ์—… ์ด๋™์€ ์‚ฐ์—… ๊ตฐ ๊ฐ„์˜ ์ž„๊ธˆ ๊ฒฉ์ฐจ๋ฅผ ์ค„์ด๋Š” ๊ฒฐ๊ณผ๋ฅผ ๋ณด์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์‹ค์ฆ ๋ถ„์„์€ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์•˜์œผ๋‚˜, ๋‹ค์–‘ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด์„œ ๋ณด์กฐ๊ธˆ ์ง€์› ์ •์ฑ…์„ ์ž…์•ˆํ•˜๋Š”๋ฐ ์žˆ์–ด์„œ ์žฅยท๋‹จ๊ธฐ์ , ๊ทธ๋ฆฌ๊ณ  ์งยท๊ฐ„์ ‘์  ํšจ๊ณผ๋ฅผ ์ข…ํ•ฉ์ ์œผ๋กœ ๊ณ ๋ คํ•ด์•ผํ•จ์„ ์‹œ์‚ฌํ•˜๊ณ  ์žˆ๋‹ค.Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Research Purpose and Methodology 4 1.3 Outline of the Study 6 Chapter 2. Literature review 7 2.1 Age-Specific Labor Productivity 7 2.2 General Equilibrium Analysis of Labor Market 8 2.3 OLG-CGE Model Approaches 9 Chapter 3. Methods 11 3.1 OLG-CGE Model Description 11 3.1.1 Four-period life-cycle model 11 3.1.2 Basic concept of model 12 3.1.3 The model description 19 3.2 Career Path Choice Model 24 3.2.1 Career Path Choice Mechanism 25 3.2.2 Soft-linking with CGE Model 26 3.3 Calibration 28 3.3.1 Initialization 29 3.3.2 Population 30 3.3.3 Initial Steady-State 31 3.4 Incentive Policy Scenarios 32 Chapter 4. Simulations and Results 33 4.1 Scenario 1 33 4.2 Scenario 2 37 4.3 Scenario 3 40 4.4 Scenario 4 44 4.5 Scenario 5 48 4.6 Aggregate Effects Over All Time Periods 52 Chapter 5. Conclusions 54 Chapter 6. Bibliography 57 Appendix 1: Estimation of Earning Profile 61Maste

    ๋น„๋™์งˆ์  ๊ฒฝ์ œ์ฃผ์ฒด๋ฅผ ๊ฐ€์ •ํ•œ ๊ฑฐ์‹œ๊ฒฝ์ œ๋ชจํ˜•๊ณผ ๊ณต๊ณต์ •์ฑ…์— ๊ด€ํ•œ ์—ฐ๊ตฌ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ๊ฒฝ์ œํ•™๋ถ€, 2023. 8. ํ™์žฌํ™”.์ €์†Œ๋“ ๊ฐ€๊ตฌ์—๊ฒŒ ํ˜„๊ธˆ์ง€์›์„ ์ œ๊ณตํ•˜๋Š” ๋ณต์ง€์ œ๋„์ธ ๊ทผ๋กœ์žฅ๋ ค์„ธ์ œ(Earned Income Tax Credit, ์ดํ•˜ EITC)๋Š” ๊ฒฝ์ œํ™œ๋™์„ ํ†ตํ•œ ๊ทผ๋กœ์†Œ๋“์„ ์ˆ˜๊ธ‰์š”๊ฑด์œผ๋กœ ํ•œ๋‹ค๋Š” ์ ์—์„œ ๋‹ค๋ฅธ ๋ณต์ง€์ œ๋„์™€ ์ฐจ๋ณ„ํ™”๋œ๋‹ค. ์ด๋Ÿฌํ•œ ๋…ธ๋™์‹œ์žฅ์ฐธ์—ฌ ์š”๊ฑด์œผ๋กœ ์ธํ•ด EITC๋Š” ์ €์†Œ๋“ ๊ฐ€๊ตฌ์—๊ฒŒ ํ˜„๊ธˆ์ง€์›๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋…ธ๋™์‹œ์žฅ์— ์ฐธ์—ฌํ•˜๊ณ ์ž ํ•  ์œ ์ธ(incentive)์„ ์ œ๊ณตํ•œ๋‹ค. ๊ทธ ๋™์•ˆ Eissa and Liebman (1996)์„ ๋น„๋กฏํ•œ ๋งŽ์€ ์‹ค์ฆ์—ฐ๊ตฌ๋“ค์ด EITC์˜ ๋…ธ๋™๊ณต๊ธ‰ ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์—ฌ ๋…ธ๋™์‹œ์žฅ ์ฐธ์—ฌ๋ฅผ ๋Š˜๋ฆฐ๋‹ค๋Š” ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ Eissa and Liebman (1996)์ด ๊ฒฐ๋ก ์—์„œ ์–ธ๊ธ‰ํ•œ ๋ฐ”์™€ ๊ฐ™์ด ๋…ธ๋™๊ณต๊ธ‰ ํšจ๊ณผ๋Š” EITC์˜ ์ „์ฒด์ ์ธ ํ›„์ƒํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜๋Š”๋ฐ ํ•„์š”ํ•œ ์ •๋ณด์˜ ์ผ๋ถ€์ด๋‹ค: A full evaluation of [...] the EITC requires more than just an estimate of the [...] impact [...] on the labor supply of transfer recipients. It also requires information on the value of the additional income received by program beneficiaries as well as the change in the amount of leisure that they consume. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์†Œ๋“์— ๋Œ€ํ•œ ํšจ๊ณผ(Hoynes and Patel, 2018)๋‚˜ ํ›„์ƒ์ˆ˜์ค€ ํ˜น์€ ์ƒ์• ์ฃผ๊ธฐ์— ๊ฑธ์นœ ์žฅ๊ธฐ์  ํšจ๊ณผ(Athreya et al., 2014; Blundell et al., 2016)์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๋น„๊ต์  ์ ๊ฒŒ ์ด๋ฃจ์–ด์ ธ์™”๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์ด๋Ÿฌํ•œ ์ธก๋ฉด์—์„œ EITC์˜ ํšจ๊ณผ๋ฅผ ๋ณด๋‹ค ์ž˜ ์ดํ•ดํ•จ์œผ๋กœ์จ EITC ์—ฐ๊ตฌ ๋ฌธํ—Œ์˜ ํ‹ˆ์„ ๋ฉ”์šฐ๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์€ Huggett (1993)๊ณผ Aiyagari (1994)๋กœ ๋Œ€ํ‘œ๋˜๋Š” ํ˜„๋Œ€ ๊ฑฐ์‹œ๊ฒฝ์ œํ•™์˜ ์ฃผ์š” ๋ชจํ˜• ์ค‘ ํ•˜๋‚˜์ธ ๋น„๋™์งˆ์  ๊ฒฝ์ œ์ฃผ์ฒด ๊ธฐ๋ฐ˜์˜ ๊ฑฐ์‹œ๊ฒฝ์ œ๋ชจํ˜•(heterogeneous-agent macroeconomic model)์„ ๊ตฌ์ถ•ํ•˜์—ฌ ๋‹ค์Œ ์งˆ๋ฌธ๋“ค์— ๋‹ตํ•˜๊ณ ์ž ํ•œ๋‹ค: EITC์˜ (i) ๋…ธ๋™๊ณต๊ธ‰ ๋ฐ ์ƒ์• ์†Œ๋“, (ii) ์ €์ถ•, ์†Œ๋น„ ๋ฐ ํ›„์ƒ์ˆ˜์ค€์— ๋Œ€ํ•œ ์žฅ๊ธฐ์  ํšจ๊ณผ์— ์žˆ์–ด ๊ธฐ์กด์—ฐ๊ตฌ์—์„œ ๊ณ ๋ ค๋˜์ง€ ์•Š์€ ๊ณต์ ์—ฐ๊ธˆ์ œ๋„๊ฐ€ ์–ด๋–ค ์—ญํ• ์„ ํ•˜๋Š”๊ฐ€? (iii) ๋ฐ•์ง€ํ˜œ โ€ง ์ด์ •๋ฏผ(2018)์˜ ์‹ค์ฆ์—ฐ๊ตฌ์—์„œ ์ œ์‹œ๋œ ๋ฐ”์™€ ๊ฐ™์ด ์™œ ํ•œ๊ตญ์˜ ์ผ๋ถ€ EITC ํ™•๋Œ€๊ฐœํŽธ์€ ๋…ธ๋™๊ณต๊ธ‰์„ ๋Š˜๋ฆฌ๋Š”๋ฐ ํšจ๊ณผ์ ์ด์ง€ ๋ชปํ–ˆ๋Š”๊ฐ€? ๋…ผ๋ฌธ์˜ ์ฒซ ๋ฒˆ์งธ ์žฅ๊ณผ ๋‘ ๋ฒˆ์งธ ์žฅ์—์„œ๋Š” ๊ณต์ ์—ฐ๊ธˆ์ œ๋„๊ฐ€ EITC์˜ ์žฅ๊ธฐ์  ํšจ๊ณผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•ด ๋ถ„์„ํ•˜์˜€๋‹ค. ๋งŽ์€ ๋‚˜๋ผ์˜ ๊ณต์ ์—ฐ๊ธˆ์ œ๋„๋Š” ๊ทผ๋กœ์—ฐ๋ น ๋™์•ˆ ๋” ๋งŽ์€ ๋…ธ๋™๊ณต๊ธ‰์„ ํ†ตํ•ด ์—ฐ๊ธˆ๊ธฐ์—ฌ๊ธˆ(ํ˜น์€ ์—ฐ๊ธˆ๋ณดํ—˜๋ฃŒ)์„ ๋งŽ์ด ๋‚ผ์ˆ˜๋ก ์€ํ‡ด ํ›„ ๋ฐ›๊ฒŒ ๋  ์—ฐ๊ธˆ๊ธ‰์—ฌ๊ฐ€ ์ฆ๊ฐ€ํ•˜๋„๋ก ์„ค๊ณ„๋˜์–ด์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ทผ๋กœ์—ฐ๋ น ์ค‘ EITC์— ๋Œ€ํ•œ ๋…ธ๋™๊ณต๊ธ‰ ๋ฐ˜์‘์€ ํ˜„์žฌ ์†Œ๋“๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ณต์ ์—ฐ๊ธˆ์ œ๋„๋ฅผ ํ†ตํ•ด ์€ํ‡ด ํ›„์˜ ์—ฐ๊ธˆ์†Œ๋“ ๋˜ํ•œ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, Liebman and Luttmer (2015)์˜ ์—ฐ๊ตฌ๊ฐ€ ๋ณด์—ฌ์ฃผ๊ณ  ์žˆ๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ์‚ฌ๋žŒ๋“ค์ด ์ด๋Ÿฌํ•œ ๊ณต์ ์—ฐ๊ธˆ์„ ํ†ตํ•œ ๋…ธ๋™๊ณต๊ธ‰์˜ ๋ฏธ๋ž˜์ˆ˜์ต(dynamic return)์„ ์ž˜ ์ธ์ง€ํ•˜์ง€ ๋ชปํ•˜๊ณ  ์žˆ๋‹ค๋ฉด, ์ด์— ๋Œ€ํ•œ ์ •๋ณด์ œ๊ณต์„ ํ†ตํ•ด EITC์— ๋Œ€ํ•œ ๋…ธ๋™๊ณต๊ธ‰ ๋ฐ˜์‘์ด ๋” ์ปค์งˆ ์ˆ˜ ์žˆ๋‹ค. ๋” ๋‚˜์•„๊ฐ€ ์ด๋Ÿฌํ•œ ์ •๋ณด์ œ๊ณต์€ ์ €์†Œ๋“ ๊ฐ€๊ตฌ๋กœ ํ•˜์—ฌ๊ธˆ ๋…ธํ›„๋Œ€๋น„ ์ €์ถ•์„ ์ค„์ด๋ฉด์„œ ์€ํ‡ด ์ด์ „์—๋„ ์†Œ๋น„๋ฅผ ๋Š˜๋ฆด ์ˆ˜ ์žˆ๊ฒŒ๋” ํ•˜๋Š” ์†Œ๋น„ํ‰ํƒ„ํ™”(consumption smoothing) ํšจ๊ณผ๋ฅผ ํ†ตํ•ด EITC์˜ ํ›„์ƒํšจ๊ณผ๋ฅผ ๋” ํฌ๊ฒŒ ๋งŒ๋“ค ์ˆ˜ ์žˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ๋งฅ๋ฝ์—์„œ ๋ณธ ๋…ผ๋ฌธ์˜ 1, 2์žฅ์—์„œ๋Š” EITC์˜ ์ƒ์• ์†Œ๋“๊ณผ ํ›„์ƒ์ˆ˜์ค€์— ๋Œ€ํ•œ ์žฅ๊ธฐ์  ํšจ๊ณผ์™€ ๋”๋ถˆ์–ด ๊ณต์ ์—ฐ๊ธˆ์— ์˜ํ•ด ๋ฐœ์ƒํ•˜๋Š” ๋…ธ๋™๊ณต๊ธ‰์˜ ๋ฏธ๋ž˜์ˆ˜์ต์˜ ์ค‘์š”์„ฑ์„ ์ •๋Ÿ‰์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์šฐ์„  ๊ฐ€๊ตฌ์˜ ๋…ธ๋™์‹œ์žฅ์ฐธ์—ฌ์™€ ์†Œ๋น„, ์ €์ถ•์— ๋Œ€ํ•œ ์„ ํƒ์ด ๋‚ด์ƒ์ ์œผ๋กœ ์ด๋ฃจ์–ด์ง€๋ฉฐ ๊ฐ€๊ตฌ์˜ ์˜ˆ์‚ฐ์ œ์•ฝ์‹์— EITC ๋ฐ ๊ณต์ ์—ฐ๊ธˆ์ œ๋„๋ฅผ ๋ช…์‹œ์ ์œผ๋กœ ๊ณ ๋ คํ•œ ๋น„๋™์งˆ์  ๊ฒฝ์ œ์ฃผ์ฒด ๊ธฐ๋ฐ˜์˜ ์ƒ์• ์ฃผ๊ธฐ ๋ชจํ˜•(heterogeneous-agent life-cycle model)์„ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ ๋ชจํ˜•์ด ํ•œ๊ตญ๊ฒฝ์ œ๋ฅผ ์ž˜ ์„ค๋ช…ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋ชจ์ˆ˜๋“ค์€ ์„ค์ •(calibration)ํ•˜๊ณ , EITC์˜ ์ง์ ‘์  ์˜ํ–ฅ์„ ๋ฐ›๋Š” ๊ฐ€๊ตฌ๋“ค์— ๋Œ€ํ•œ ๋ถ„์„์— ์ดˆ์ ์„ ๋งž์ถ”๊ธฐ ์œ„ํ•ด ๋…ธ๋™์ƒ์‚ฐ์„ฑ์ด ๋‚ฎ์€ ์‚ถ์„ ์‚ด์•„๊ฐ€๊ฒŒ ๋  ์‹ ์ƒ์•„(newborn)์— ๋Œ€ํ•œ ์žฅ๊ธฐ์  ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ๊ณต์ ์—ฐ๊ธˆ์„ ํ†ตํ•œ ๋…ธ๋™๊ณต๊ธ‰์˜ ๋ฏธ๋ž˜์ˆ˜์ต์€ EITC์˜ ์ƒ์• ์†Œ๋“๊ณผ ํ›„์ƒ์ˆ˜์ค€์— ๋Œ€ํ•œ ํšจ๊ณผ ์ค‘ ๊ฐ๊ฐ ์ ˆ๋ฐ˜, 4๋ถ„์˜ 1 ์ •๋„๋ฅผ ์„ค๋ช…ํ•  ๋งŒํผ ์ค‘์š”ํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Š” ๋…ธ๋™๊ณต๊ธ‰์˜ ๋ฏธ๋ž˜์ˆ˜์ต์— ๋Œ€ํ•œ ์ •๋ณด์ œ๊ณต์ด EITC์˜ ๊ธ์ •์  ํšจ๊ณผ๋ฅผ ์ƒ๋‹นํžˆ ํฌ๊ฒŒ ๋งŒ๋“ค ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค. ๋งˆ์ง€๋ง‰ ์žฅ์—์„œ๋Š” ์•ž์„œ ๊ตฌ์ถ•ํ•œ ์ƒ์• ์ฃผ๊ธฐ ๋ชจํ˜•์„ ํ™œ์šฉํ•˜์—ฌ ๋ฐ•์ง€ํ˜œ โ€ง ์ด์ •๋ฏผ(2018)์˜ ์‹ค์ฆ๋ถ„์„ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ํ•ด์„์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ๋ฐ•์ง€ํ˜œ โ€ง ์ด์ •๋ฏผ(2018)์˜ ์ฃผ์š” ๊ฒฐ๊ณผ ์ค‘ ํ•˜๋‚˜๋Š” ๋ถ„์„๊ธฐ๊ฐ„์— 2014-2016๋…„์„ ํฌํ•จํ•˜๊ฒŒ ๋˜๋ฉด EITC ํ™•๋Œ€๊ฐœํŽธ์˜ ๋…ธ๋™๊ณต๊ธ‰ ํšจ๊ณผ๊ฐ€ ์ƒ๋‹นํžˆ ์ž‘๊ฑฐ๋‚˜ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š๊ฒŒ ์ถ”์ •๋œ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ํ•œ๊ตญ EITC ํ™•๋Œ€๊ฐœํŽธ์˜ ํŠน์ง• ์ค‘ ํ•˜๋‚˜๋Š” ๋‹จ๋…๊ฐ€๊ตฌ๊ฐ€ ์—ฐ๋ น๋ณ„๋กœ ์ ์ฐจ ์ˆ˜๊ธ‰ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜์—ˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ 2012๋…„๊นŒ์ง€๋Š” ์ˆ˜๊ธ‰๋Œ€์ƒ์— ๋‹จ๋…๊ฐ€๊ตฌ๊ฐ€ ํฌํ•จ๋˜์–ด์žˆ์ง€ ์•Š์•˜์œผ๋‚˜ 2013๋…„๋ถ€ํ„ฐ 60์„ธ ์ด์ƒ์˜ ๋‹จ๋…๊ฐ€๊ตฌ๊ฐ€, 2015๋…„๋ถ€ํ„ฐ 50๋Œ€ ๋‹จ๋…๊ฐ€๊ตฌ๊ฐ€, 2016๋…„๋ถ€ํ„ฐ 40๋Œ€ ๋‹จ๋…๊ฐ€๊ตฌ๊ฐ€ ์ˆ˜๊ธ‰๋Œ€์ƒ์— ํฌํ•จ๋˜์—ˆ๋‹ค. ์ด๋Š” EITC์— ๋Œ€ํ•œ ๋…ธ๋™๊ณต๊ธ‰ ๋ฐ˜์‘์ด ์—ฐ๋ น๋ณ„๋กœ ๋‹ฌ๋ž์„ ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค. ์ฆ‰, 2014๋…„ ์ดํ›„๋กœ ์ˆ˜๊ธ‰๋Œ€์ƒ์— ํฌํ•จ๋œ 50๋Œ€, 40๋Œ€์—์„œ์˜ ๋…ธ๋™๊ณต๊ธ‰ ๋ฐ˜์‘์ด ๋น„๊ต์  ์ž‘๊ฒŒ ๋‚˜ํƒ€๋‚ฌ์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์•ž์„  ์žฅ์—์„œ ๊ตฌ์ถ•ํ•œ ์ƒ์• ์ฃผ๊ธฐ ๋ชจํ˜•์— ์˜ํ•˜๋ฉด ์—ฐ๋ น๋ณ„ ๋…ธ๋™๊ณต๊ธ‰ ํƒ„๋ ฅ์„ฑ์ด 60๋Œ€์—์„œ ๊ฐ€์žฅ ๋†’๊ณ  40๋Œ€์—์„œ ๊ฐ€์žฅ ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚œ๋‹ค. ์ด๋Ÿฌํ•œ ์—ฐ๋ น๋ณ„ ๋…ธ๋™๊ณต๊ธ‰ ํƒ„๋ ฅ์„ฑ์˜ ์ฐจ์ด๋Š” ์—ฐ๋ น๋ณ„ ๋…ธ๋™์ƒ์‚ฐ์„ฑ๊ณผ ์ž์‚ฐ์ˆ˜์ค€์˜ ์ฐจ์ด์—์„œ ๋น„๋กฏ๋œ๋‹ค. ์—ฐ๋ น๋ณ„ ๋…ธ๋™์ƒ์‚ฐ์„ฑ์ด ๊ฐ€์žฅ ๋†’๊ณ  ๋…ธํ›„๋Œ€๋น„ ์ €์ถ•๋™๊ธฐ๋ฅผ ์–ด๋Š์ •๋„ ๊ฐ–๋Š” 40๋Œ€๋Š” EITC๊ฐ€ ์—†๋”๋ผ๋„ ์ด๋ฏธ ์ผ์„ ํ•˜๊ณ  ์žˆ์„ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’๋‹ค. ์ด๋Š” EITC๊ฐ€ ์ด๋“ค์˜ ๋…ธ๋™์‹œ์žฅ์ฐธ์—ฌ๋ฅผ ๋Š˜๋ฆด ์—ฌ์ง€๊ฐ€ ์ ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ๋ฐ˜๋Œ€๋กœ ์€ํ‡ด๊ฐ€ ๊ฐ€๊นŒ์šด 60๋Œ€์˜ ๊ฒฝ์šฐ, ๋…ธ๋™์ƒ์‚ฐ์„ฑ์ด 40๋Œ€๋ณด๋‹ค ๋‚ฎ๊ณ  ์ด๋ฏธ ๋…ธํ›„์†Œ๋น„๋ฅผ ์ถฉ๋‹นํ•˜๊ธฐ ์œ„ํ•œ ์ž์‚ฐ์„ ์–ด๋Š์ •๋„ ์ถ•์ ํ•œ ์ƒํƒœ์ด๊ธฐ ๋•Œ๋ฌธ์— EITC ์—†์ด ์ผ์„ ํ•  ์œ ์ธ์ด 40๋Œ€์— ๋น„ํ•ด ์ž‘๋‹ค. ์ด๋Š” EITC๊ฐ€ 60๋Œ€์˜ ๋…ธ๋™์‹œ์žฅ์ฐธ์—ฌ๋ฅผ ๋Š˜๋ฆด ์—ฌ์ง€๊ฐ€ ํฌ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” EITC์˜ ๋…ธ๋™๊ณต๊ธ‰์— ๋Œ€ํ•œ ํ‰๊ท ์  ํšจ๊ณผ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค์–‘ํ•œ ์‚ฌํšŒ์ธ๊ตฌํ•™์  ์ง‘๋‹จ๋ณ„ ํšจ๊ณผ์— ๋Œ€ํ•ด ๋ณด๋‹ค ๋งŽ์€ ์‹ค์ฆ๋ถ„์„์ด ์ด๋ฃจ์–ด์งˆ ํ•„์š”๊ฐ€ ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค.The Earned Income Tax Credit (EITC) is a means-tested income support program, but it differs from other welfare programs in that it requires earned income as a qualification. Therefore, the EITC provides labor supply incentives as well as cash transfers to low-income households. Pioneered by Eissa and Liebman (1996), many empirical studies have investigated its labor supply effect and found that tax credit programs increase the target individuals labor market participation. However, as noted by Eissa and Liebman (1996), the labor supply effect is a piece that shapes the picture of the overall welfare consequence of the EITC. In their conclusion, they stated: A full evaluation of [...] the EITC requires more than just an estimate of the [...] impact [...] on the labor supply of transfer recipients. It also requires information on the value of the additional income received by program beneficiaries as well as the change in the amount of leisure that they consume. Nevertheless, there have been only a few studies on its impact on income (Hoynes and Patel, 2018) and welfare, or the long-term impact over the life cycle (Athreya et al., 2014; Blundell et al., 2016). This dissertation mainly aims to fill this gap by expanding our understanding of the EITCs impacts in these dimensions. Specifically, I develop a heterogeneous-agent life-cycle model in the tradition of Huggett (1993) and Aiyagari (1994), one of the workhorse models in modern macroeconomics, to answer the following questions: How are the EITCs long-term impacts over the life cycle affected by the public pension system in terms of (i) labor supply and lifetime income and (ii) savings, consumption, and welfare? In addition, through the lens of the sophisticated model, I investigate (iii) why some EITC expansions in Korea were less effective in inducing labor market participation as found in the empirical literature (Park and Lee, 2018). In the first and second chapters of the dissertation, I explore the role of the public pension tax-benefit link in the benefits of the EITC program. In the public pension systems of many countries, contributions before retirement and benefits after retirement are linked. In other words, an increase in lifetime earnings and pension contributions through more labor supply during the working age increases pension benefits after retirement. Therefore, the labor supply response to the EITC during the working age of the life cycle increases pension income in retirement through the tax-benefit link of public pensions. This mechanism amplifies the income-increasing effect of the EITC by raising pension income. Moreover, salience literature on public pensions (Liebman and Luttmer, 2015) suggests that informational intervention about the dynamic incentive for work through the tax-benefit link could intensify the labor supply and earnings responses to the EITC. This channel also magnifies the EITCs welfare consequence by enabling the target household to reduce retirement savings and enjoy more consumption. I quantitatively analyze the EITCs long-term impacts on income and welfare over the life cycle and highlight the role of the pension tax-benefit link. To this end, I construct a heterogeneous-agent life-cycle model with consumption-savings and extensive margin labor supply choices, as well as a public pension system. The model is calibrated to the Korean economy running a sizable EITC program. I examine the EITCs effect on newborn individuals who will face unfavorable labor productivity histories over their lives, making their lifetime income low, to focus on the direct incentive effect of the program. By comparing the impacts of the EITC with versus without the dynamic labor supply return through the pension tax-benefit link, I find that the role of the tax-benefit link is quantitatively significant. For newborns with low lifetime income, the pension tax-benefit link explains more than half (a quarter) of the increase in lifetime income (welfare) due to the EITC. In the last chapter, I provide a possible mechanism for the empirical result of Park and Lee (2018) through the lens of the life-cycle model. One of the main findings of Park and Lee (2018) is that the estimated labor supply response to the EITC becomes substantially small and insignificant if 2014--2016 is included in the sample periods. One of the unique features of the EITC expansions in Korea is that there was an age limit for single households, which was gradually relaxed over time. Specifically, singles above 60 became eligible for the EITC in 2013, those above 50 in 2015, those above 40 in 2016, and so on. These observations suggest that the heterogeneous labor supply response by age could be the driving force behind the empirical result. Consistent with this conjecture, I find that the model implies substantially higher labor supply elasticity in the 60s than in middle age. The differential labor supply elasticity by age comes from heterogeneity in labor productivity and wealth by age. In the 40s, an EITC-eligible low income individual is likely to already be in the labor market even without the EITC because it is his prime age and he needs to accumulate more wealth against retirement. This means there is little room for the EITC to induce labor supply. For those nearing retirement, in contrast, their average labor productivity tends to be lower than at prime age, and they already have enough wealth to finance retirement consumption. This makes them closer to the participation margin, which implies more room for the EITC to induce labor market participation. The result suggests that we need more empirical work on for whom the EITC is effective in inducing labor supply, not just the estimates for the average effect.1 The Earned Income Tax Credit and the Tax-benefit Link of Public Pensions: Effects on Labor Supply and Income 1 1.1 Introduction 1 1.2 Model 7 1.2.1 EITC 8 1.2.2 Public pension 11 1.2.3 Income 12 1.2.4 Individuals problem 13 1.3 Calibration 16 1.3.1 Demographics and preferences 16 1.3.2 Endowments 16 1.3.3 Tax and transfer 18 1.3.4 Public pension 20 1.3.5 Model fit 21 1.4 Quantitative analysis 25 1.4.1 Who is mainly affected? 26 1.4.2 Results with both static and dynamic returns 29 1.4.3 Role of dynamic return through the pension tax-benefit link 35 1.5 Conclusion 40 2 The Earned Income Tax Credit and the Tax-benefit Link of Public Pensions: Effects on Savings, Consumption, and Welfare 42 2.1 Introduction 42 2.2 Effects on consumption and savings 43 2.2.1 Results with the static return only 45 2.2.2 Role of the dynamic return 46 2.2.3 Implication for the labor supply response 50 2.3 Effects on welfare 53 2.4 Discussion and conclusion 54 2.4.1 No knowledge in reality? 55 2.4.2 Design of pension systems 55 2.4.3 Old age labor supply 56 2.4.4 Part-time choice 57 2.4.5 General equilibrium 57 2.4.6 Avenues for future research 58 3 Why were some EITC expansions in Korea less effective in inducing labor supply? Role of heterogeneous labor supply elasticity by age 59 3.1 Introduction 59 3.2 The EITC in Korea and literature review 60 3.2.1 Institutional background 60 3.2.2 Literature 61 3.3 The analysis using the life-cycle model 63 3.3.1 Regression analysis 64 3.3.2 Inspecting the mechanism 66 3.4 Conclusion 69 Reference 70 Appendix 76 A Estimations 76 A.1 Labor income tax progressivity 76 A.2 Welfare benefits to the non-employed 77 B Additional features of the model 77 B.1 Firms 79 B.2 Government budgets 80 B.3 Definition of equilibrium 81 C Pension benefit formula 81 ๊ตญ๋ฌธ์ดˆ๋ก 82๋ฐ•

    Human-Machine Communication: Complete Volume. Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemic

    Get PDF
    This is the complete volume of HMC Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemi

    Macroeconomic effects of basic income funded by land holding tax

    Get PDF
    This study examines the macroeconomic effects of the introduction of a scheme to pay a basic income of approximately $900 per year to each citizen through land holding tax. In contrast to the existing literature, this study deals with the issue of whether household members decide to sell land due to a sharp increase in the land holding tax rate to raise funds for the payment of basic income. Furthermore, this study uses the relationship between holding assets and reservation wages to solve the problem of determining whether household members supply labor in accordance with the payment of basic income. Simulation results obtained using data for Korea show that the introduction of the scheme to pay the basic income decreases the real GDP, total labor demand, and social welfare by 1.3%, 0.3%, and 0.4%, respectively

    Vulnerability and Resilience of People and Places to Hurricane Damage in the US. Gulf and Atlantic Coasts from 1950 to 2018

    Get PDF
    Extreme weather events are expected to increase as a consequence of climate change, increasing the intensity and frequency of natural hazards. Their catastrophic impact is attributable to both the geophysical characteristics of a hazardous event itself and the socio-demographic characteristics of people who are at a greater risk of harm in the aftermath of natural hazards. Previous studies have largely used a place-based approach, measuring the relative level of social vulnerability between places using a social vulnerability index (SoVI), a prevalent spatially explicit method in geographic scholarship. As a composite index, SoVI, has been criticized by scholars due to its over-generalization; it cannot indicate the contribution of specific local social indicators to vulnerability, obscuring demographic heterogeneity and making it difficult to understand who is vulnerable. In contrast to the spatiality of vulnerability, the temporal dynamics of social vulnerability have been relatively understudied. This dissertation seeks to address these drawbacks of the SoVI approach and to assess hazard-specific vulnerability by incorporating geophysical characteristics of natural hazards and differential vulnerabilities of affected populations. There are four primary objectives of this study: (1) To investigate major patterns in the spatial and temporal dynamics of social vulnerability of U.S. counties from 1970 to 2010 using quantile standardization, sequence alignment analysis, and cluster analysis; (2) To identify the contributions of the components of SoVI and the local primary factors that contribute to social vulnerability using geographically-weighted principal component analysis (GWPCA) and explore how those factors have evolved over time using Greater Houston as a case study; (3) To estimate the spatial extent and intensity of storm surge inundation and wind damage caused by hurricanes along the Gulf and Atlantic Coasts in the United States from 1950 to 2018 using geospatial analysis; and (4) To understand differential vulnerabilities of distinctive demographics within hurricane at-risk areas using a spatial and temporal analysis. The results show that the U.S. counties have four major temporal trajectories, revealing areas of persistently low and high vulnerabilities and areas with dynamically changing vulnerabilities. The application of GWPCA reveals the most influential local social factors that constitute the SoVI index. Moreover, the spatial and temporal trends of the local factors can indicate what socioeconomic conditions are prevailing and consistently affect the vulnerability of a particular region. In terms of the vulnerability of people to hurricane hazards, this study also identifies generalized patterns of demographic changes that are within hurricane-risk zones and which population groups are increasingly or decreasingly exposed. The results in this study have significant implications for policymakers and national disaster management in surveilling vulnerable areas and establishing potential hazard mitigation plans. The findings reported here shed new light on social vulnerability assessment urging decision-makers to provide more resources to the hardest-hit groups living in the most exposed counties. This study is the first comprehensive investigation of hurricane-specific vulnerability encompassing the Atlantic and Gulf Coasts and at a national scale. The analytical framework suggested in this study can enrich the approach to vulnerability assessment of natural hazards by converging geographic and demographic perspectives
    • โ€ฆ
    corecore