8,679 research outputs found

    Evaluating the quality of society and public services

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    A personโ€™s quality of life is not only shaped by individual choices and behaviour: the surrounding environment and the public services on offer have a big influence on how people perceive the society they live in and on their evaluation of their own quality of life. Institutions influence the quality of society through collective actions that individuals cannot undertake themselves: for example maintaining schools, hospitals and roads. Public policies are also responsible for ensuring that water and air are not polluted, and for reducing tensions between different social groups. If public policies are effective and these services are provided to a high standard, the quality of society will improve, with a positive impact on the overall quality of life of citizens. This is why European policymakers and citizens share a common concern regarding the quality of society and public services: the actions of policymakers should contribute to improving the quality of citizensโ€™ lives. To evaluate whether this is in fact happening, one needs to look beyond objective measures of material wealth such as gross domestic product (GDP) and find out how citizens assess the conditions in their society. The second European Quality of Life Survey (EQLS), carried out by the European Foundation for the Improvement of Living and Working Conditions (Eurofound) in 2007, asks European citizens to evaluate multiple aspects of quality of society. The result is a comprehensive picture of the diverse social realities in the 27 EU Member States, in Norway, Croatia, the former Yugoslav Republic of Macedonia and Turkey

    Applications of the Comprehensive Rural Village Development Project and Transportation Accessibility

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ๋†๊ฒฝ์ œ์‚ฌํšŒํ•™๋ถ€(์ง€์—ญ์ •๋ณด์ „๊ณต), 2021. 2. ์ด์„ฑ์šฐ.The purpose of this research is to propose pragmatic policy evaluation models with scientific rigor and to empirically analyze the effectiveness of large-scale public policies implemented in rural areas of South Korea. The impacts of two policies, the Comprehensive Rural Village Development Project (CRVDP) and the improved transportation accessibility, on agricultural income are analyzed from the ex-post standpoint applying quantitative policy evaluation methods. This dissertation is composed of three empirical essays. In the first essay, the impact of the CRVDP on agricultural income is analyzed using a quasi-experimental research design. The Heckman selection model was used to overcome selection bias, and the Blinder-Oaxaca decomposition method was employed to estimate the causal impact of the CRVDP. The results revealed that the project had a positive impact on raising farm households agricultural income. A higher probability of making agricultural income was found in the project implemented areas vis-ร -vis project not-implemented areas and in the period after the project implementation vis-ร -vis period before the project implementation. The second essay attempts to analyze the impact of the CRVDP on agricultural income by sub-groups of rural population. The analysis was conducted by applying the propensity score matching and the double cohort model developed from the age-period-cohort framework. The results find that young farmers in their early-career stage experienced a significant increase in the probability of making a higher agricultural income with the implementation of the CRVDP. On the other hand, significant effect was not visible for the cohorts of middle-aged and elderly farmers at all experience levels. The last essay explores the benefits of transportation infrastructural investments to the agricultural sector and rural areas. The paper examines the impact of changes in transportation accessibility over the course of 2005 to 2015 on agricultural income. The impact was analyzed from both micro- and macro-levels of farm households and rural autonomies utilizing the multilevel model and the spatial econometrics model. According to the results, a positive association was found in 2005, but the effect turned negative starting in 2010 which suggest that public investments in transportation accessibility had a meager or negative impact on agricultural income. There has been a rising call to come up with evidence-based recommendations employing scientifically credible evaluation methods in the public sector. Under this context, this research presents pragmatic approaches to policy evaluation for using credible secondary data. In this research, practical yet rigorous policy impact evaluation methods were applied to Koreas rural sector where evaluation of policies using rigorous scientific methods remains relatively limited.๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์ฒด๊ณ„์ ์ด๊ณ  ๊ณผํ•™์ ์ธ ์ •์ฑ…ํ‰๊ฐ€๋ชจํ˜•์„ ๊ตฌ์ถ•ํ•˜๊ณ , ์šฐ๋ฆฌ๋‚˜๋ผ ๋†์ดŒ์ง€์—ญ์—์„œ ์‹œํ–‰๋œ ๋Œ€๊ทœ๋ชจ ๊ณต๊ณต์ •์ฑ…์˜ ํšจ๊ณผ์„ฑ์„ ์‹ค์ฆ์ ์œผ๋กœ ๋ถ„์„ํ•˜๋Š” ๋ฐ์— ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋†์ • ์ „ํ™˜๊ธฐ์— ์‹œํ–‰๋œ ๋Œ€ํ‘œ์  ๋†์ดŒ์ •์ฑ…์ธ ๋†์ดŒ๋งˆ์„์ข…ํ•ฉ๊ฐœ๋ฐœ์‚ฌ์—…๊ณผ ๊ตํ†ตSOC ํˆฌ์ž์— ๋”ฐ๋ฅธ ๊ตํ†ต์ ‘๊ทผ์„ฑ ๊ฐœ์„ ์ด ๋†์—…์†Œ๋“ ์ฆ์ง„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์ •๋Ÿ‰์  ํ‰๊ฐ€๊ธฐ๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ ์‚ฌํ›„์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ 3๊ฐœ์˜ ์‹ค์ฆ๋ถ„์„์œผ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ์ฒซ ๋ฒˆ์งธ ์‹ค์ฆ๋ถ„์„์—์„œ๋Š” ๊ฐ€์šฉ์ž๋ฃŒ๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ํ—คํฌ๋งŒ์„ ๋ณ„๋ชจํ˜•(Heckman Selection Model)์„ ์ด์šฉํ•ด ์„ ํƒํŽธ์˜๋ฅผ ๋ณด์ •ํ•˜๊ณ , ํ•ด์ฒด๊ธฐ๋ฒ•(Decomposition Method)์„ ํ™œ์šฉํ•˜์—ฌ ๋†์ดŒ๋งˆ์„์ข…ํ•ฉ๊ฐœ๋ฐœ์‚ฌ์—… ์‹œํ–‰์—๋”ฐ๋ฅธ ๋†์—…์†Œ๋“ ์ฆ๋Œ€ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ์‚ฌ์—…์‹œํ–‰์ง€์—ญ์€ ๋ฏธ์‹œํ–‰์ง€์—ญ์— ๋น„ํ•ด ๋†์—…์†Œ๋“ ์ฆ๋Œ€ํšจ๊ณผ๊ฐ€ ์กด์žฌํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ์‚ฌ์—…์‹œํ–‰์ง€์—ญ์€ ์‚ฌ์—…์‹œํ–‰ ์ด์ „๋ณด๋‹ค ๋†์—…์†Œ๋“์ด ์ฆ๊ฐ€ํ•˜์—ฌ ์ •์ฑ…ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ํ‰๊ฐ€๋˜์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ์‹ค์ฆ๋ถ„์„์€ ์„ฑํ–ฅ์ ์ˆ˜๋งค์นญ(Propensity Score Matching)๊ณผ APC(Age-Period-Cohort) ๋ชจํ˜•์— ๊ธฐ์ดˆํ•œ ์ด์ค‘์ฝ”ํ˜ธํŠธ ๋ชจํ˜•(Double Cohort Model)์„ ์ ์šฉํ•˜์—ฌ ๋†์—…์ธ์˜ ์—ฐ๋ น๊ณผ ์˜๋† ๊ฒฝ๋ ฅ์— ์˜ํ•ด ๋ถ„๋ฅ˜๋œ ์ฝ”ํ˜ธํŠธ๋ณ„๋กœ ๋†์ดŒ๋งˆ์„์ข…ํ•ฉ๊ฐœ๋ฐœ์‚ฌ์—…์˜ ๋†์—…์†Œ๋“ ์ฆ์ง„ ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ๋†์ดŒ๋งˆ์„์ข…ํ•ฉ๊ฐœ๋ฐœ์‚ฌ์—…์€ ๊ฒฝ๋ ฅ ์ดˆ๊ธฐ๋‹จ๊ณ„ ์ฒญ๋…„ ๋†์—…์ธ์˜ ๊ณ ์†Œ๋“ ๊ฐ€๋Šฅ์„ฑ์„ ๋†’์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚œ ๋ฐ˜๋ฉด, ์ค‘๋…„ ๋ฐ ๋…ธ๋…„๊ธฐ ๋†์—…์ธ ์ฝ”ํ˜ธํŠธ์— ์žˆ์–ด์„œ๋Š” ๊ทธ ํšจ๊ณผ๊ฐ€ ๋ฏธ๋ฏธํ–ˆ๋˜ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์„ธ ๋ฒˆ์งธ ์‹ค์ฆ๋ถ„์„์€ ๋‹ค์ธต๋ชจํ˜•(Multilevel Model)๊ณผ ๊ณต๊ฐ„๊ณ„๋Ÿ‰๋ชจํ˜•(Spatial Econometrics Model)์„ ํ™œ์šฉํ•˜์—ฌ ๊ตํ†ตSOC ํˆฌ์ž์— ์˜ํ•œ ๊ตํ†ต์ ‘๊ทผ์„ฑ ๊ฐœ์„ ์ด ๋†์—…์†Œ๋“์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ฏธ์‹œ์  ์ˆ˜์ค€์˜ ๋†๊ฐ€๋‹จ์œ„์™€ ๊ฑฐ์‹œ์  ์ˆ˜์ค€์˜ ์ง€์—ญ๋‹จ์œ„ ์ธก๋ฉด์—์„œ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด 2005๋…„์—๋Š” ๊ตํ†ต์ ‘๊ทผ์„ฑ์˜ ๋ณ€ํ™”๊ฐ€ ๋†์—…์†Œ๋“์— ๊ธ์ •์ ์ธ ๋ฐฉํ–ฅ์œผ๋กœ ์ž‘์šฉํ•œ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ์œผ๋‚˜, 2010๋…„ ์ดํ›„์—๋Š” ๋ณ„๋‹ค๋ฅธ ์˜ํ–ฅ์ด ์—†๊ฑฐ๋‚˜ ๋ถ€์ •์ ์ธ ๋ฐฉํ–ฅ์œผ๋กœ ์ž‘์šฉํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณต๊ณต์ •์ฑ…์˜ ์ค‘์žฅ๊ธฐ์  ์„ฑ๊ณผ ๋ฐ ์žฌ์ • ํˆฌ์ž… ํšจ์œจ์„ฑ ํ‰๊ฐ€์— ๋Œ€ํ•œ ๊ฐ๊ด€์ ์ด๊ณ  ๊ณผํ•™์ ์ธ ๋ถ„์„์ด ์š”๊ตฌ๋˜๋Š” ์ƒํ™ฉ์—์„œ ์ด์šฉ ๊ฐ€๋Šฅํ•œ ๊ฐ๊ด€์  ํ†ต๊ณ„์ž๋ฃŒ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฒด๊ณ„์ ์ด๊ณ  ์ •๋Ÿ‰์ ์ธ ํ‰๊ฐ€๋ชจํ˜• ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค๋Š”๋ฐ ์ผ์ฐจ์  ์˜๋ฏธ๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ, ๊ธฐ์ดˆํ†ต๊ณ„ ๋ฐ ์ •์„ฑ์  ์ง€ํ‘œ ์œ„์ฃผ์˜ ์ •์ฑ…ํ‰๊ฐ€๊ฐ€ ์ฃผ๋ฅผ ์ด๋ฃจ์—ˆ๋˜ ๋†์ดŒ์ •์ฑ… ๋ถ€๋ฌธ์— ์ •๋Ÿ‰์  ์‚ฌํ›„ํ‰๊ฐ€๋ชจํ˜•์„ ์ ์šฉํ•˜์—ฌ ํ‰๊ฐ€๊ฒฐ๊ณผ์˜ ํ†ต๊ณ„์  ํƒ€๋‹น์„ฑ์„ ์ œ๊ณ ํ•˜์˜€๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ์žˆ๋‹ค.Chapter 1. Introduction 1 1.1. Recent Trends in Rural Korea 1 1.2. Towards Evidence-based Policymaking in the Rural Sector 6 1.3. Purpose and Scope of the Research 8 1.4. Structure of the Research 10 Chapter 2. Koreas Rural Development Policies 13 2.1. A Chronological Overview 13 2.2. The Comprehensive Rural Village Development Project 17 Chapter 3. The Impact of the Comprehensive Rural Village Development Project on Agricultural Income 21 3.1. Introduction 21 3.2. Methodological Challenges in Counterfactual Analysis 22 3.3. Methodology 24 3.4. Data and Variables 34 3.5. Empirical Results 37 3.6. Conclusion 54 Chapter 4. Decoupling the Impact of the Comprehensive Rural Village Development Project on Agricultural Income by Birth and Experience Cohorts 57 4.1. Introduction 57 4.2. Literature Review 58 4.3. Conceptual Framework 63 4.4. Theoretical Framework: The Double Cohort Model 67 4.5. Data and Variables 70 4.6. Methodology 73 4.7. Empirical Results 79 4.8. Conclusion 91 Chapter 5. Micro- and Macro-Level Investigations of the Impact of Transportation Infrastructure on Agricultural Income, 2005-2015 93 5.1. Introduction 93 5.2. Literature Review 95 5.3. Data and Variables 102 5.4. Methodology 107 5.5. Empirical Results 112 5.6. Conclusion 127 Chapter 6. Concluding Remarks 129 6.1. Summary of Findings and Policy Implications 129 6.2. Limitations of the Studies and Future Research 135 Bibliography 138 Appendix 154 Abstract in Korean 158Docto

    An assessment of Multilevel Governance in Cohesion Policy, 2007-2013

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    This study offers a thorough overview of Multi-Level Governance in Cohesion Policy in the current programming period of 2007-2013 by examining the evolution of the concept in terms of its definition and conceptual framework, analysing the current processes of implementing Multi-Level Governance in the EU27, as well as describing the advantages and disadvantages of partnerships in policy-making. Moreover, the study aims to formulate strategic and operational recommendations in the context of the preparation of the 2014- 2020 programming perio

    Community Partnerships for Cultural Participation: Concepts, Prospects, and Challenges

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    Evaluates the first year of the Wallace Foundation's Community Partnerships for Cultural Participation Initiative, which funded nine community foundations working to increase participation in the arts and culture in their communities

    Examining the Relationship Between Social Capital and the Built Environment: A Case Study in Measuring Community Sustainability

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    The concepts of sustainability and sustainable development are frequently described as having three main components, sometimes referred to as the three pillars or the triple bottom line: environmental, economic, and social. Because the origins of sustainability come from a desire to right environmental wrongs much consideration has been given to the environmental issues, especially how they interface with economic ones. Frequently mentioned but rarely examined, the social aspects of sustainability have been considered the weakest and least described pillar. This work explores the utility of social capital, the value of one\u27s networks and connections, as a measure of sustainability. As an individual and group based concept, social capital is often thought of in the context of communities. Communities have both physical and social infrastructures and how we develop and use the land we live on has many implications for society. The idea that we would have more interactions with neighbors and fellow citizens if we lived in neighborhoods that promoted walking and were built on the human scale seems logical but there has been little evidence to suggest that a relationship between social capital and the built environment exists (Litman, 2010; Leyden, 2003; Kathlene & Wallick, 1999). Through a case study approach this dissertation examines the relationship between social aspects of sustainability (specifically social capital) and the built environment. Residents living in neighborhoods of varying built form and thus varying levels of walkability in three communities in New Hampshire were surveyed about their levels of social capital and travel behaviors. Survey respondents were asked how many locations they could walk to within their neighborhood or community and these responses were used to develop a walkability index. Responses to questions about trust and community involvement were compiled into two indices that served as the key measures of social capital. Comparisons between the more walkable and less walkable neighborhoods show that levels of social capital are higher in more walkable neighborhoods, even after controlling for key demographic variables. The findings suggest that social capital and walkability may be potent measures of community sustainability and that communities might benefit from shaping the built environment in ways that promote destination walking
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