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      Design, innovation, and rural creative places: Are the arts the cherry on top, or the secret sauce?

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      1 , * , 2
      PLoS ONE
      Public Library of Science

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          Abstract

          Objective

          Creative class theory explains the positive relationship between the arts and commercial innovation as the mutual attraction of artists and other creative workers by an unobserved creative milieu. This study explores alternative theories for rural settings, by analyzing establishment-level survey data combined with data on the local arts scene. The study identifies the local contextual factors associated with a strong design orientation, and estimates the impact that a strong design orientation has on the local economy.

          Method

          Data on innovation and design come from a nationally representative sample of establishments in tradable industries. Latent class analysis allows identifying unobserved subpopulations comprised of establishments with different design and innovation orientations. Logistic regression allows estimating the association between an establishment’s design orientation and local contextual factors. A quantile instrumental variable regression allows assessing the robustness of the logistic regression results with respect to endogeneity. An estimate of design orientation at the local level derived from the survey is used to examine variation in economic performance during the period of recovery from the Great Recession (2010–2014).

          Results

          Three distinct innovation (substantive, nominal, and non-innovators) and design orientations (design-integrated, “design last finish,” and no systematic approach to design) are identified. Innovation- and design-intensive establishments were identified in both rural and urban areas. Rural design-integrated establishments tended to locate in counties with more highly educated workforces and containing at least one performing arts organization. A quantile instrumental variable regression confirmed that the logistic regression result is robust to endogeneity concerns. Finally, rural areas characterized by design-integrated establishments experienced faster growth in wages relative to rural areas characterized by establishments using no systematic approach to design.

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          Most cited references21

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          Location, control and innovation in knowledge-intensive industries

          R. Mudambi (2008)
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            • Abstract: not found
            • Article: not found

            Bohemia and economic geography

            R. Florida (2002)
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              • Record: found
              • Abstract: not found
              • Article: not found

              Recasting the Creative Class to Examine Growth Processes in Rural and Urban Counties

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 February 2018
                2018
                : 13
                : 2
                : e0192962
                Affiliations
                [1 ] Rural Economy Branch, Economic Research Service, U.S. Department of Agriculture, Washington, District of Columbia, United States of America
                [2 ] Office of Research and Analysis, National Endowment for the Arts, Washington, District of Columbia, United States of America
                University of Georgia, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-9863-1457
                Article
                PONE-D-17-32670
                10.1371/journal.pone.0192962
                5831055
                29489884
                01375988-ba04-4f40-a935-db989de0aee9

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 6 September 2017
                : 1 February 2018
                Page count
                Figures: 2, Tables: 6, Pages: 23
                Funding
                Wojan is employed by the USDA Economic Research Service and Nichols is employed by the National Endowment for the Arts. However, the views expressed are the authors' and should not be attributed to the Economic Research Service, USDA, or the National Endowment for the Arts. The authors received no specific funding for this work.
                Categories
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                Labor Economics
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                Mathematical and Statistical Techniques
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                Instrumental Variable Analysis
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                Earth Sciences
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                The authors confirm that all data underlying the findings are available but with restrictions mandated by the Confidential Information Protection and Statistical Efficiency Act (CIPSEA) that was invoked for the primary data collection activities. Implementation guidelines for CIPSEA are available here: https://obamawhitehouse.archives.gov/sites/default/files/omb/assets/omb/inforeg/proposed_cispea_guidance.pdf. CIPSEA does not allow granting access to these data without an approved research proposal and a signed Economic Research Service (ERS) confidentiality agreement. Queries about access to these data should be submitted to the ERS Associate Administrator Dr. Greg Pompelli ( POMPELLI@ 123456ers.usda.gov ). As of January 2018 access to these data is only available onsite at ERS in Washington, DC. Options for remote access without the need to be physically present at ERS to access these data may be available at some future date through external providers that are compliant with the Federal Information Security Modernization Act. However, an approved research proposal and a signed ERS confidentiality agreement will still be required. Additional fees to remotely access these data through a secure data enclave such as the National Opinion Research Center Data Enclave may apply. These data may also be available at some future date through the Census Bureau's Research Data Centers (RDCs). Access through the RDCs will require additional approval of the research proposal by the RDC and may also include a cost recovery fee.

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