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Thesis (Ph. D.)--University of Wisconsin--Madison, 1984. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 339-343).

由於科技的飛速發展以及全球化的進程的加深，競爭力這個概念在各個尺度都受到廣泛的關注。特別是最近20年，隨著城市間競爭的加劇，有關城市尺度的競爭力的研究也十分興盛。城市競爭力受到了學術界和政府等的普遍關注，然而大家對城市競爭力的概念解釋各執己見，無法統一，導致至今沒有統一的衡量城市競爭力的體系。本文從城市競爭力的角度出發，對中國24 個主要的地級及地級以上的城市競爭力進行實證研究，研究時間跨度從1995年到2008年。為了使競爭因素重要程度得到正確的反應，層次分析法被創造性的應用於此研究中。實證研究的目的是分析城市的優勢和劣勢，城市競爭力的動態演化以及具體的政府政策對城市競爭力的影響。 / 城市競爭力模型中各因素的建立是基於大量前人的有關解釋城市競爭與城市增長等理論和實證研究。該綜合競爭力模型集合了經濟，社會，環境以及外部聯繫四個重要部分。以該綜合競爭力模型為基本框架，我們進一步建立了城市綜合競爭力評價體系，該體系由四個競爭力方面組成，每個競爭力方面又有數個競爭因素，每個競爭力因素又由多個指標來代表。因此，整個競爭力評價體系是包含4個分項競爭力，15個競爭因素和59個指標的層級結構。本文采用層次分析法作為賦權重的方法以更準確的反應各競爭力方面和因素的實際重要程度。實證分析的結果可以反應更城市的優勢與劣勢，競爭力的動態變化，以及競爭力的政府含義。本研究希望對城市競爭力的概念和理論體系，研究方法以及實證研究方面有所貢獻和突破。 / 根據2008年城市競爭力排名結果可知，每個城市的四個部分的相對排名都不是完全匹配。北京，上海，廣州位於城市競爭力體系的頂端，在經濟，社會和外部聯繫上都佔據优势位置，但是都存在環境競爭力較弱的缺點。重慶，溫州和哈爾濱排在24個城市的最後面。此外，城市的優勢與劣勢組合具有多樣性，構成了城市獨特的競爭力表現。 / 城市在1995 到2008年競爭力得分和排名的變化反應了城市長期競爭力的形態。所有城市的競爭力在這一時期都有提升，但是城市競爭力在早期越強的城市其競爭力指數提升的空間越小。如珠海、北京、深圳、廣州和上海在1995年的競爭力得分排在前列，但是他們的競爭力指數增長率都非常低。通過相關性分析，該研究發現前後年份間的競爭力指數相關性很高，表明競爭力具有路徑依賴性，過去競爭性因素的積累有利於將來競爭力的提升。此外,這些主要城市間的競爭力差距在縮小，表明排名落後的城市正在追該排名靠前的城市。 / 該研究以北京為案例，通過分析其在各競爭力方面的表現，分析該表現的影響因素，得出中央政府和地方政府在推動城市競爭力發展中起到了重要作用。北京的各優勢因素和劣勢因素的組合，相互作用，構成了北京的競爭優勢。北京過分追求經濟競爭力也使得環境競爭力受損。 / 綜合以上研究發現，該研究認為綜合考慮和衡量城市競爭力是符合中國現實城市發展的必然選擇。儘管經濟競爭力仍然是重要的方面，其他因素也是影響城市發展和競爭的重要因素。 / Under the deepening influence of globalization and advancement in science and technology, the issue of competitiveness, from national to local levels, has won considerable attention from researchers as well as policy makers. For more than two decades, the contention on its definition has been persisting, leading to inconsistent measurement methods. Some studies of competitiveness at the municipal level in China have also been done. / This study conducts an empirical study on urban competitiveness of 24 major Chinese cities at prefecture-level or above in a period from 1995 to 2008. Based on intensive previous research on this issue, urban competitiveness is interpreted from a comprehensive perspective integrating economic, social, environmental and external connection competitiveness components. Based on this comprehensive understanding of urban competitiveness, a composite indicator system has been constructed including four competitiveness components, fifteen subgroups and fifty-nine indicators. The Analytic Hierarchy Process (AHP) weighting method is used in order to reflect the opinions of experts on the importance of various components as precisely as possible. Based on empirical analysis, this research has revealed the strengths and weaknesses of the major cities, the dynamic changes of urban competitiveness and the policy implications of urban competitiveness results. All these contribute to the study of urban competitiveness conceptually, methodologically and empirically. / The empirical research in 2008 revealed that each city does not have same performance in their economic, social, environmental and external connection competitiveness. Shanghai, Beijing and Guangzhou are the most competitive cities which take the top three positions in the ranking list, but they all show disappointing performance in environmental competitiveness. Chongqing, Wenzhou and Harbin are ranked at the bottom in terms of composite indicator. In other words, each city has its special complex of strengths and weaknesses. / This thesis makes the first attempt to reveal the changes in urban competitiveness over a period of time using the same indicator system. The changes of urban competitiveness scores and ranks during the period from 1995 to 2008 indicate long-term competitiveness patterns. In general, all cities obtained improvement in urban competitiveness scores during this period, but cities with higher competitiveness scores in the early years tended to obtain less significant improvement. Zhuhai, Beijing, Shenzhen, Guangzhou and Shanghai obtained a relatively higher competitiveness scores in 1995 but had the smallest growth rate from 1995 to 2008. The high correlation coefficient of competitiveness ranks between two sub-periods indicates that most major cities tend to remain in their relative position. However, there is also a catching up effect among the major Chinese cities revealed by the decreased disparities. / The policy implications of this empirical study are significant. By tracing the performances of Beijing’s competitiveness in the four components, it is concluded that both the central government and the local government played an important role in enhancing local competitiveness. Economic competitiveness has been overemphasized, but environmental problems have become severe, which restricts Beijing’s development. / With the above findings, this research concludes that a comprehensive understanding and measurement of urban competitiveness is necessary, especially in the context of China. Although economic competitiveness is still the key issue, the other three components are also of importance in affecting the success of cities. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Yang, Xiaolan. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 226-245). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / ABSTRACT OF THESIS ENTITLED --- p.I / ACKNOWLEDGEMENTS --- p.V / TABLE OF CONTENTS --- p.VII / LIST OF TABLES --- p.X / LIST OF FIGURES --- p.XI / ABBREVIATIONS --- p.XII / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- RESEARCH BACKGROUND AND CHALLENGES --- p.1 / Chapter 1.1.1 --- Increasing concerns on the issue of competitiveness --- p.1 / Chapter 1.1.2 --- Growing concerns on Chinese urban competitiveness --- p.2 / Chapter 1.2 --- SCOPE OF THIS RESEARCH --- p.3 / Chapter 1.3 --- RESEARCH QUESTIONS AND OBJECTIVITIES --- p.5 / Chapter 1.4 --- RESEARCH SIGNIFICANCE --- p.7 / Chapter 1.5 --- ORGANIZATION OF THE RESEARCH --- p.8 / Chapter CHAPTER 2 --- A REVIEW OF URBAN COMPETITIVENESS: CONCEPT AND MEASUREMENT --- p.10 / Chapter 2.1 --- INTRODUCTION --- p.10 / Chapter 2.2 --- UNDERSTANDING COMPETITIVENESS AT THE URBAN LEVEL --- p.11 / Chapter 2.3 --- DETERMINANTS OF URBAN COMPETITIVENESS --- p.16 / Chapter 2.3.1 --- Trade and globalization forces --- p.16 / Chapter 2.3.2 --- Agglomeration and urban growth --- p.17 / Chapter 2.3.3 --- Innovation and knowledge-based development --- p.18 / Chapter 2.3.4 --- Institutional thickness --- p.19 / Chapter 2.3.5 --- Environment impact on competitiveness --- p.19 / Chapter 2.4 --- COMPETITIVENESS MEASUREMENT --- p.21 / Chapter 2.4.1 --- Competitiveness measurement model --- p.21 / Chapter 2.4.2 --- The applications of indicators in the competitiveness researches --- p.23 / Chapter 2.5 --- RESEARCH ON THE COMPETITIVENESS OF CHINESE CITIES --- p.31 / Chapter 2.5.1 --- The economic competitiveness measurement model --- p.31 / Chapter 2.5.2 --- The comprehensive competitiveness measurement model --- p.32 / Chapter 2.5.2 --- Weighting methods --- p.36 / Chapter 2.6 --- Conclusion --- p.37 / Chapter CHAPTER 3 --- CONCEPTUAL FOUNDATION, ANALYSIS MODEL AND RESEARCH FRAMEWORK ON URBAN COMPETITIVENESS --- p.40 / Chapter 3.1 --- INTRODUCTION --- p.40 / Chapter 3.2 --- CONCEPTUALIZING URBAN COMPETITIVENESS --- p.40 / Chapter 3.3 --- URBAN COMPETITIVENESS MEASUREMENT MODEL IN THE CHINESE CONTEXT --- p.44 / Chapter 3.3.1 --- Economic competitiveness component --- p.44 / Chapter 3.3.2 --- Social competitiveness component --- p.46 / Chapter 3.3.3 --- Environmental competitiveness component --- p.49 / Chapter 3.3.4 --- External connection competitiveness component --- p.50 / Chapter 3.3.5 --- The role of government --- p.53 / Chapter 3.3.6 --- Differences in the measurement of urban competitiveness and sustainable development --- p.55 / Chapter 3.4 --- RESEARCH FRAMEWORK FOR THIS STUDY --- p.57 / Chapter 3.5 --- CONCLUSION --- p.60 / Chapter CHAPTER 4 --- METHOD OF URBAN COMPETITIVENESS ANALYSIS --- p.62 / Chapter 4.1 --- INTRODUCTION --- p.62 / Chapter 4.2 --- CONSTRUCTING THE INDICATOR SYSTEMS --- p.63 / Chapter 4.2.1 --- Indicators in Economic Competitiveness Component --- p.64 / Chapter 4.2.2 --- Indicators in the Social Competitiveness Component --- p.66 / Chapter 4.2.3 --- Indicators in Environmental Competitiveness Component --- p.68 / Chapter 4.2.4 --- Indicators in External Connection Competitiveness Component --- p.69 / Chapter 4.3 --- SAMPLE CITIES --- p.70 / Chapter 4.3.1 --- Section of the sample city --- p.70 / Chapter 4.3.2 --- Urban area --- p.71 / Chapter 4.3.3 --- Urban population --- p.74 / Chapter 4.4 --- THE TIME PERIOD --- p.75 / Chapter 4.5 --- DATA PROCESSING AND NORMALIZATION --- p.76 / Chapter 4.5.1 --- Log transformation --- p.76 / Chapter 4.5.2 --- Normalization methods --- p.76 / Chapter 4.6 --- WEIGHTING METHOD BASED ON AHP --- p.76 / Chapter 4.6.1 --- Expert survey and pair-wise comparison matrixes --- p.78 / Chapter 4.6.2 --- Consistency testing --- p.79 / Chapter 4.6.3 --- Computing the weighting --- p.79 / Chapter 4.7 --- CONCLUSION --- p.84 / Chapter CHAPTER 5 --- ANALYSIS OF THE URBAN COMPETITITVENESS OF 24 MAJOR CITIES IN 2008 --- p.85 / Chapter 5.1 --- INTRODUCTION --- p.85 / Chapter 5.2 --- AN OVERVIEW OF THE URBAN COMPETITIVENESS OF 24 CITIES --- p.87 / Chapter 5.2.1 --- The top 8 cities --- p.88 / Chapter 5.2.2 --- The bottom eight cities --- p.89 / Chapter 5.3 --- THE RELATIONSHIP AMONG THE FOUR COMPETITIVENESS COMPONENTS --- p.91 / Chapter 5.4 --- A COMPARISON OF THE CITIES ACROSS THE FOUR COMPETITIVENESS COMPONENTS --- p.93 / Chapter 5.4.1 --- Economic competitiveness --- p.93 / Chapter 5.4.2 --- Social competitiveness --- p.97 / Chapter 5.4.3 --- Environmental competitiveness --- p.102 / Chapter 5.4.4 --- External connections competitiveness --- p.104 / Chapter 5.5 --- THE WEAKNESSES AND STRENGTHS OF INDIVIDUAL CITIES --- p.109 / Chapter 5.6 --- COMPARISON OF RELATIVE RANKS WITH PREVIOUS RESEARCH --- p.113 / Chapter 5.7 --- CONCLUSION --- p.115 / Chapter CHAPTER 6 --- ANALYSIS ON THE CHANGING PATTERNS OF URBAN COMPETITIVENESS FROM 1995 TO 2008 --- p.117 / Chapter 6.1 --- INTRODUCTION --- p.117 / Chapter 6.2 --- THE CHANGING PATTERN OF URBAN COMPETITIVENESS --- p.117 / Chapter 6.2.1 --- Improvement in scores --- p.119 / Chapter 6.2.2 --- Shift in ranks --- p.122 / Chapter 6.3 --- THE GROWTH PATTERNS OF THE SUBGROUP COMPONENTS --- p.123 / Chapter 6.3.1 --- Shifting patterns in the economic competitiveness component --- p.124 / Chapter 6.3.2 --- Shifting patterns in the social competitiveness component --- p.128 / Chapter 6.3.3 --- Shifting patterns in the environmental competitiveness component --- p.130 / Chapter 6.3.4 --- Shifting patterns in external connection competitiveness component --- p.133 / Chapter 6.4 --- THE RELATIONS AMONG SUBGROUP COMPONENTS --- p.135 / Chapter 6.5 --- TREND OF DISPARITY IN COMPETITIVENESS --- p.137 / Chapter 6.6 --- CONCLUSION --- p.141 / Chapter CHAPTER 7 --- A CASE STUDY ON URBAN COMPETITIVENESS OF BEIJING --- p.143 / Chapter 7.1 --- INTRODUCTION --- p.143 / Chapter 7.2 --- BEIJING’S COMPETITIVENESS POSITION --- p.145 / Chapter 7.2.1 --- Economic competitiveness of Beijing --- p.147 / Chapter 7.2.2 --- Social competitiveness in Beijing --- p.149 / Chapter 7.2.3 --- Environment competitiveness of Beijing --- p.155 / Chapter 7.2.4 --- External connection competitiveness of Beijing --- p.155 / Chapter 7.3 --- THE DETERMINANTS FOR URBAN COMPETITIVENESS OF BEIJING --- p.158 / Chapter 7.3.1 --- Specialized industries in Beijing --- p.158 / Chapter 7.3.2 --- Social capital and institutions --- p.162 / Chapter 7.3.3 --- The environmental constraints --- p.167 / Chapter 7.3.4 --- Impact on external connection competitiveness --- p.169 / Chapter 7.4 --- GOVERNMENT STRATEGIES IN ENHANCING COMPETITIVENESS --- p.171 / Chapter 7.4.1 --- Knowledge-based development strategy --- p.171 / Chapter 7.4.2 --- Attracting high talented people --- p.173 / Chapter 7.4.3 --- Information strategies --- p.174 / Chapter 7.4.4 --- Olympic strategy --- p.177 / Chapter 7.5 --- CONCLUSION --- p.179 / Chapter CHAPTER 8 --- CONCLUSION --- p.182 / Chapter 8.1 --- INTRODUCTION --- p.182 / Chapter 8.2 --- MAJOR FINDINGS --- p.183 / Chapter 8.2.1 --- Understanding and assessing urban competitiveness: a comprehensive perspective --- p.183 / Chapter 8.2.2 --- The overall evaluation of urban competitiveness in major cities --- p.184 / Chapter 8.2.3 --- The shifting pattern of urban competitiveness in major cities --- p.185 / Chapter 8.2.4 --- The case study on urban competitiveness in Beijing --- p.186 / Chapter 8.3 --- DISCUSSION AND IMPLICATION OF URBAN COMPETITIVENESS STUDIES --- p.187 / Chapter 8.4 --- LIMITATION AND SUGGESTION FOR FURTHER RESEARCHES --- p.188 / Chapter APPENDIX A --- DATA PROCESSING AND SOURCES --- p.191 / Chapter APPENDIX B --- JUDGING THE DISTRIBUTION PATTERN --- p.202 / Chapter APPENDIX C --- CHINESE URBAN COMPETITIVENESS EVALUATION RESEARCH: QUESTIONNAIRE FOR CALCULATING THE WEIGHTS OF VARIOUS EVALUATION FACTORS --- p.203 / Chapter APPENDIX D --- INFORMATION OF THE EXPERTS AND RESEARCHERS WHO GIVE FEEDBACK TO SURVEY --- p.209 / Chapter APPENDIX E --- EIGENVECTORS AND CONSISTENCY TEST --- p.212 / Chapter APPENDIX F --- THE LOCATION QUOTIENT IN MANUFACTURES AND SERVICES IN PART CITIES --- p.220 / REFERENCES --- p.226

Thesis (Ph. D.)--UCLA, 2009. / Vita. Description based on print version record. Includes bibliographical references (leaves 201-212).

Firms seeking sites for new or expansion plants rely on their ability to assess the benefits and costs generated by locating operations in a given state. State governments strive to understand the issues important to firms who are seeking a site for new operations or branch plants. They do so because attracting branch plants and new firms is critical to their economic growth. In addition to factors traditionally considered important to industrial location decisions (energy prices, wage levels, unionization, taxes, and public services), this study also considers the impact of the average level of education attained by the population of a state. Specifically, this study hypothesizes that the average level of education attained by a state's labor force significantly affects the location decisions of firms oriented toward local inputs. Results indicate that educational attainment is a significant determinant of where firms in the transportation industry decide to locate or expand operations. However, educational attainment is not a significant determinant for the electronic equipment industry. Wage and unemployment levels are significant factors for both industries. With the exception of educational attainment and tax levels, the results do not vary across industries. Since industries such as transportation equipment seem to place a premium on states with a relatively high level of education attainment, states wishing to attract this type of companies may find it beneficial to encourage higher education, both for the well-being of its residents and for the economy of the state. / Master of Arts

No description available.

My dissertation studies political economy issues in the development of China. Chapter 1 lies in the intersection of urban economics and political economy. This chapter exploits plausibly exogenous variation generated by a unique national policy in China that requires all residential buildings to receive sufficient hours of sunshine to study a central question in urban economics, namely, whether urban density facilitates the diffusion of information. The policy creates higher degrees of restriction on density at higher latitudes, where longer shadows require buildings to be further apart. Data on individual housing projects across China reveal that the cross-latitude variation in regulatory residential Floor Area Ratio can be described quite well by a formula linking structure density to latitude through the solar elevation angle. These differences in building density further induce differences in population density and land prices across latitudes. Using differential topic dynamics on a national petition platform to measure information diffusion, this chapter shows that people respond to shifts in government attention with varying speeds across latitudes. Increases in local government reply rate to a topic raises the volume of subsequent posts on the same topic, exhibiting an S-shaped time trajectory consistent with local information diffusion about shifting government priorities. These responses are systematically faster in southern cities, where density is higher. Survey evidence further indicates that otherwise similar individuals are more likely to gossip about public issues in a southern city. Chapter 2, coauthored with Junyan Jiang and Tianguang Meng and forthcoming at the journal Governance, examines the flip side of the interaction between local governments and citizens studied in Chapter 1. This chapter studies the response of government policies to opinions expressed online. We address this question by studying the patterns and consequences of online participation at a major electronic petition platform in China. Content analysis of around 900,000 petitions reveals that a substantial share of them concern lower-class issues and are originated from less developed rural and suburban areas. Linking variations in petition volumes to an original dataset of government policy priorities, we further show that online participation led governments to place greater emphasis on social welfare policies and to increase the coverage of a key low-income assistance program. These results underscore the potential of online participation as an important mechanism to improve the quality of governance. Chapter 3, coauthored with Amit Khandelwal, Suresh Naidu and Heiwai Tang, turns to a systematic examination of China's reform process. We apply natural language processing methods to analyze a comprehensive corpus of 1.4 million legal documents issued by the Chinese government at central and local levels since 1949, and measure their market orientation in a data-driven fashion. We document an active introduction of market-oriented legal infrastructure from the mid-1980s to around 2000, which slowed down in the last fifteen years. These dynamics are present within fine-grained policy domains. We find that the market orientation of policies explains just an extra 2% of provincial variation in GDP per capita growth beyond province and time fixed effects. Variable selection based on richer representations of the text exhibits similarly limited predictive power for provincial growth. Taken together, these findings suggest the importance of studying the informal arrangements between market participants and government officials.

Chapter 1, “The Impact of Trade Shocks on Local Labor Markets” estimates the effects of increased trade with China on Brazilian local labor markets using longitudinal individual data on the universe of Brazilian formal sector workers. First, I use reduced-form estimation strategies commonly found in the literature to compare my results to previous findings. I show that my results at the regional level mirror those found in prior studies based on cross-sectional data. I argue that these estimates are potentially biased as they do not take into account the flows of factors and goods between regions. I complement the reduced-form approach with a structural analysis based on the model by Caliendo et al. (2015) in order to endogenize such flows and to study welfare effects. I find that in the absence of the Chinese shock the Brazilian Commodities sector would have shrunk while Manufacturing and Services would have expanded. Relative to this baseline, the employment effect of increased trade with China at the national level was a slower reduction in the share of the Commodities sector and a slower growth in the Manufacturing subsectors that were relatively more exposed to Chinese import competition. My analysis suggests that while the average Brazilian worker benefitted from this shock, the welfare effects were very heterogeneous across sectors and across locations. I find that this heterogeneity is vastly underestimated if instead of using data at the level of metropolitan areas I use data aggregated by States and I explain why the choice of spatial units affects these results. Chapter 2, “Agglomeration: A Long-Run Panel Data Approach” studies the sources of agglomeration economies in cities. We begin by incorporating within and cross-industry spillovers into a dynamic spatial equilibrium model in order to obtain a panel data estimating equation. This gives us a framework for measuring a rich set of agglomeration forces while controlling for a variety of potentially confounding effects. We apply this estimation strategy to detailed new data describing the industry composition of 31 English cities from 1851-1911. Our results show that industries grew more rapidly in cities where they had more local suppliers or other occupationally-similar industries. We find no evidence of dynamic within-industry effects, i.e., industries generally did not grow more rapidly in cities in which they were already large. Once we control for these agglomeration forces, we find evidence of strong dynamic congestion forces related to city size. We also show how to construct estimates of the combined strength of the many agglomeration forces in our model. These results suggest a lower bound estimate of the strength of agglomeration forces equivalent to a city-size divergence rate of 1.6-2.3% per decade. Chapter 3, “Gravity estimation with unobserved bilateral flow data” adapts the methodology by Miscio & Soares (2016) to predict domestic trade flows by sector between Brazilian metropolitan areas. This methodology, initially developed to infer commuting flows from aggregate data on population by place of residence and by place of work, relies on moment conditions derived from a general gravity equation and it is consistent with a large class of trade models. I show that it can also be applied to infer domestic trade flows by sector. Before using the methodology on Brazilian data, where we only observe flows between States, I test it on US data from the Commodity Flow Survey, where we observe both flows between States and between finer spatial units similar to metropolitan areas. I argue that the predicted bilateral flows obtained from this methodology are highly correlated with actual flows. Alternative approaches found in the recent literature differ from the one presented here in that they require stronger assumptions and deliver weaker results. In particular, the other approaches only describe aggregate flows (i.e. summing across all sectors) and cannot be used to predict sectoral flows.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

This dissertation consists of three independent chapters. Chapter 1 examines the determinants and welfare implications of the increased geographic of workers by skill from 1980 to 2000. I estimate a structural spatial equilibrium model of local labor demand, housing supply, labor supply, and amenity levels. The estimates indicate that cross-city changes in firms' demands for high and low skill labor were the underlying forces driving the increase in geographic skill sorting. I find that the combined effects of changes in cities' wages, rents, and endogenous amenities increased well-being inequality between high school and college graduates by a significantly larger amount than would be suggested by the increase in the college wage gap alone. / Economics