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Economic Diversity and Regional Deve...

Chen, Jing.

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Economic Diversity and Regional Development: Geographical Scale, Structural Measurement, and Modeling Method.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Economic Diversity and Regional Development: Geographical Scale, Structural Measurement, and Modeling Method./
作者:	Chen, Jing.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	105 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-03, Section: A.
Contained By:	Dissertations Abstracts International80-03A.
標題:	Geography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10843742
ISBN:	9780438321618

Economic Diversity and Regional Development: Geographical Scale, Structural Measurement, and Modeling Method.
Chen, Jing.

Economic Diversity and Regional Development: Geographical Scale, Structural Measurement, and Modeling Method. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 105 p.

Source: Dissertations Abstracts International, Volume: 80-03, Section: A.

Thesis (Ph.D.)--West Virginia University, 2018.

This item must not be sold to any third party vendors.

The relationship between economic diversity and regional economic performance has been a recurrent topic among regional scientists, economic geographers and development practitioners. However, the empirical understanding of this relationship is often inconsistent with the theoretical assumptions of economic diversity. Thus, to offer suggestions to evaluate the empirical relationship between economic diversity and regional economic performance so that policymakers and economic planners can better understand, formulate and undertake economic development policies, this dissertation examines the roles of (1) geographical scales, (2) structural measurements, and (3) modeling methods in assessing the diversity-performance relationship in the context of U.S. regional economies. Geographical scales of regional economic systems can alter the empirical understanding of economic diversity on regional economic performance. Although scale-related issues can be study dependent, the diversity-stability relationship is studied among counties, states, Economic Areas, and Metropolitan Statistical Areas in the lower U.S. Based on the result of this multi-level analysis, several general concerns in quantifying regional economic structure are discussed. It is suggested to use functional rather than formal regions as the analytical units to reflect spatial interactions among regions. These units should also be large enough to form meaningful economic systems. In addition, possible temporal variations in the boundaries of functional regions should also be considered. Structural measurements of economic diversity have long ignored the coexistence of economic specialization and diversity. As such, a novel measure that allows for the interpretation of economic diversity as the presence of multiple specializations is developed. In essence, this measure considers the diversity of clusters for a regional economy. The empirical results indicate that industry and cluster diversity demonstrate different effects on regional economic performance: both industrial and cluster diversity contribute to long-term economic stability, while only cluster diversity stimulates short-term employment growth. Regions thus can pursue high and stable growth by developing diversified specializations. Modeling methods in existing economic structure research have not considered model uncertainty resulting from the set of control variables and the choice of an appropriate spatial weight matrix when studying the structure-performance relationship. Empirical evidence suggests that the model uncertainty can impact the understanding of economic diversity. A Bayesian Model Average (BMA) method is thus employed to address the model uncertainty. The result of BMA is used to estimate the effects of economic diversity on employment growth and economic stability, and comparisons are made between model estimates with and without model uncertainty.

ISBN: 9780438321618Subjects--Topical Terms:

524010
Geography.

Economic Diversity and Regional Development: Geographical Scale, Structural Measurement, and Modeling Method.
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520 $a The relationship between economic diversity and regional economic performance has been a recurrent topic among regional scientists, economic geographers and development practitioners. However, the empirical understanding of this relationship is often inconsistent with the theoretical assumptions of economic diversity. Thus, to offer suggestions to evaluate the empirical relationship between economic diversity and regional economic performance so that policymakers and economic planners can better understand, formulate and undertake economic development policies, this dissertation examines the roles of (1) geographical scales, (2) structural measurements, and (3) modeling methods in assessing the diversity-performance relationship in the context of U.S. regional economies. Geographical scales of regional economic systems can alter the empirical understanding of economic diversity on regional economic performance. Although scale-related issues can be study dependent, the diversity-stability relationship is studied among counties, states, Economic Areas, and Metropolitan Statistical Areas in the lower U.S. Based on the result of this multi-level analysis, several general concerns in quantifying regional economic structure are discussed. It is suggested to use functional rather than formal regions as the analytical units to reflect spatial interactions among regions. These units should also be large enough to form meaningful economic systems. In addition, possible temporal variations in the boundaries of functional regions should also be considered. Structural measurements of economic diversity have long ignored the coexistence of economic specialization and diversity. As such, a novel measure that allows for the interpretation of economic diversity as the presence of multiple specializations is developed. In essence, this measure considers the diversity of clusters for a regional economy. The empirical results indicate that industry and cluster diversity demonstrate different effects on regional economic performance: both industrial and cluster diversity contribute to long-term economic stability, while only cluster diversity stimulates short-term employment growth. Regions thus can pursue high and stable growth by developing diversified specializations. Modeling methods in existing economic structure research have not considered model uncertainty resulting from the set of control variables and the choice of an appropriate spatial weight matrix when studying the structure-performance relationship. Empirical evidence suggests that the model uncertainty can impact the understanding of economic diversity. A Bayesian Model Average (BMA) method is thus employed to address the model uncertainty. The result of BMA is used to estimate the effects of economic diversity on employment growth and economic stability, and comparisons are made between model estimates with and without model uncertainty.
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