[[alternative]]社會經濟變數之空間分析

博士[[abstract]]本研究論文基於空間與地理之量化分析架構，分別針對三個社會經濟問題進行探討。本文第二章，題名為「幸福感與之外溢效果之探討」，旨在檢驗跨國間幸福感是否存在空間相依性；研究採用的資料為2006年跨116個國家之幸福指標與其相關之特徵變數。研究結果指出，具相同特性之國家間，幸福感之外溢效果會高於不具相同特性之國家；在本研究中，已開發國家間存在正向幸福感之外溢效果，而社會主義國家間存在負向幸福感之外溢效果；據此，若忽略空間外溢效果將導致模型的設定錯誤，進而招致相關之政策推論與其意涵產生舛誤。 本文第三章題名為「台灣人口老化與所得不均度之關係—空間方法之應用」，其分析1998-2006間台灣22縣市間，所得不均度之空間分布與其決定因素，並應用適用於面板資料之空間落遲模型進行收斂性分析。空間固定效果模型之估計結果指出，所得不均度會受到鄰近區域之所得不均度所影響；再者，將人口老化與空間落遲因子納入考量後，估計結果指出人口老化與空間外溢效果對所得不均度具正向影響。這結果可歸因於於小家庭數與獨居老人數增加，使家庭中無收入比率增加；除此之外，本研究發現區域間所得不均的現象存在發散性，也就是說隨著時間的增加，區域間所得不均度高之地區與所得不均度低之地區兩者間的差距並無法縮減。 第四章，最後一個子題「全球化下幸福感之空間影響分析」運用145個國家之資料，並利用空間兩階段最小平方法(Spatial 2SLS ；Spatial two stage least square)討論納入幸福感之空間外溢性及全球化等因子後，對幸福感之空間分布有何影響。據文獻與研究之結果指出，衡量空間外溢效果之因子-空間落遲變數(Wh)具內生性，因此須將其內生性納入模型設定中，以避免估計結果產生偏誤。本研究子題亦將解釋變數外溢(WX)的可能性納入考量，該變數可協助控制解釋變數中因鄰近姓而產生的外溢效果。另外，本子題檢測出U型的Kuznet曲線，其指出平均幸福感與幸福感之不均度間存在非線性關係；也就是說幸福感的不均會造成羨慕和社會緊張的一個直接原因。子題最後將針對已開發與開發中國家幸福感之不均度進行比較分析。[[abstract]]This dissertation consists of three principle work investigating the spatial/geographical structure of different socio - economic phenomena with varying spatial econometric techniques. The second chapter titled “Happiness and Regional Segmentation: Does Space Matters?” examines cross-country happiness interdependencies across 116 countries of diverse characteristics using averaged happiness data for the year 2006. The result points to significant happiness spillovers indicating the importance of group clustering in the studies of happiness. The result suggests that the more homogenous the group is, the higher will be the spillover among them. We observe positive spillover for developed countries and negative spillover for socialist and equal countries. Ignoring such spatial spillover effect may lead to misunderstanding of various policy implications. The third chapter titled “Population Aging and Regional Income Inequality in Taiwan: A spatial Dimension” of the dissertation analyzes the spatial distribution of regional income inequality across 22 regions of Taiwan for the time period 1998-2006. The work employs a ‘spatial lag model’ to assess the importance of spatial clustering in the processes of growth convergence and income inequality. A spatial fixed effect panel data analysis reveals that the level of inequality in income distribution of own province is positively and significantly determined by inequality in the neighboring province. Further, when we control for spatial dependence we observe a positive relation between aging and income inequality. This regional inequality is explained by a decline in the multi-generational families followed by a rise in the elderly households with no additional income. In an additional analysis which forms the second part of the paper, we observe both absolute and conditional beta divergence. The result points to the famous catching up or falling behind phenomenon. The fourth chapter titled “Happiness and Globalization: A spatial Perspective” examines the impact of globalization on the level of happiness across 145 nations of the world. Based on the data from the Gallup World Poll Survey (GWP), we employ a spatial 2SLS (two stage least square) model to show that spatial lag of happiness adds something important to specify the distribution of the level of happiness, beyond what we would expect from a country’s level of globalization. We conclude endogeneity of the spatial lag term (Wh) which if not taken into account with appropriate instruments may result into biased estimates. The study also provides evidences of spatial dependencies in the independent variables (WX’s) which represents indirect effects from a change in X’s in the neighboring regions. We observe contrasting spillover effects (direct v/s indirect effect) of the same explanatory factor generating positive or negative synergies, respectively, across space. Further, an inverted ‘U’ Kuznet curve reveals a non-linear relationship between average happiness and happiness inequality. At low levels, an increase in well-being appears to hurt the poor; but beyond a certain threshold, it seems to reduce inequality possibly because it brings with it renewed impetus for reforms in international trade and immigration rule. We experience between countries inequality for developed regions compare to developing regions.[[tableofcontents]]Table of Contents 1. Introduction 1 1.1 Research questions 2 1.2 Theoretical significance 3 1.3 Policy significance 4 2. Happiness and regional segmentation: Does space matter? 5 2.1. Introduction 5 2.2. Conceptual framework and previous literature 7 2.3. Data and Methodologies 10 2.3.1. Data 10 2.3.2. Empirical strategy 12 2.4. Estimation Results 15 2.4.1. Global analysis: OLS vs. Spatial results 15 2.4.1.1. Developed vs. developing regions 16 2.4.1.2. Equal vs. Unequal regions 18 2.4.1.3. Socialist vs. Non-Socialist regions 19 2.4.2. Spatial multiplier analysis 21 2.5. Conclusion and Policy Discussion 23 3. Population Aging and Regional Income Inequality in Taiwan: A Spatial Dimension 32 3.1. Introduction 32 3.2. Literature Review 35 3.3. Data 39 3.4. Methodology 41 3.4.1. Fixed Effect and Spatial Panel Data Models 41 3.4.1.1. Fixed Effect Panel Data Models 41 3.4.1.2. Spatial Panel Models 44 3.4.2. Regional Convergence/Divergence and Spatial Dimension 45 3.5. Empirical Results 47 3.5.1. Non –Spatial v/s Spatial Panel results 47 3.5.2. Convergence-Divergence Hypothesis (Non–spatial v/s spatial results) 50 3.6. Concludary Remarks 51 4. Happiness and globalization: A Spatial Two Stage Least Square (2SLS) approach 63 4.1. Introduction 63 4.2. Literature Review 67 4.3. Data 71 4.4. Methodology: Spatial Dependence of Happiness 73 4.4.1. Moran’s I test 73 4.4.2. Spatial two stage least square estimation of the Spatial Lag happiness. 74 4.5. Empirical Results 77 4.5.1. Spatial Two-Stage Least Square Estimations 77 4.5.2. Relationship between happiness and happiness inequality 81 4.6. Concludary Remarks and Policy Implication 82 5. CONCLUSION 91 6. BIBLIOGRAPHY 94 7. Appendix 108 LIST OF TABLES Table 2- 1 Descriptive Statistics 26 Table 2- 2 OLS and SAR estimations: Global comparison 27 Table 2- 3 OLS and SAR estimations for Happiness: Developed and Developing countries 28 Table 2- 4 OLS and SAR estimations for Happiness: Equal and Unequal countries 29 Table 2- 5 OLS and SAR estimations for Happiness: Socialist and Non-Socialist countries 30 Table 2- 6 Spatial Parameter and Multiplier estimates for Happiness 31 Table 3- 1 Descriptive Statistics (panel fixed effect model) 54 Table 3- 2 Descriptive Statistics (convergence-divergence hypothesis) 55 Table 3- 3 Moran''s I of GINI Income Inequality 56 Table 3- 4 Moran''s I (Convergence-divergence model) 57 Table 3- 5 Fixed Effect Estimation - Non-Spatial v.s Spatial Model 58 Table 3- 6 Convergence - Divergence Hypothesis 59 Table 4- 1 Descriptive Statistics 85 Table 4- 2 Moran''s I (Average Happiness) 86 Table 4- 3 OLS, Spatial lag and Spatial Lag with IV 87 Table 4- 4 Kuznet Hypothesis: Relationship between Level and Inequality of Happiness 88 Table 2- 7 List of Developed and Developing Countries 108 Table 2- 8 List of Equal and Unequal Countries 111 Table 2- 9 List of Socialist and Non-Socialist Countries 114 LIST OF FIGURES Figure 3- 1 Gini for Taiwan (regional level) 60 Figure 3- 2 Average household income for Taiwan (1998 ~ 2006) 61 Figure 3- 3 Moran''s scatter plot for average household income growth 62 Figure 3- 4 Moran''s scatter plot for GINI (1999 & 2005) 62 Figure 4- 1 Moran''s I for average happiness (2012) 89 Figure 4- 2 Kuznet Curve: Global 89 Figure 4- 3 Kuznet Curve: Developed Countries 90[[note]]學號: 898540082, 學年度: 10