Archive for Economic Development, Resilience, and Innovation

Agritourism and Recreational Services on US Farms: Data from the 2022 Census of Agriculture

A new data brief by Jason S. Entsminger (University of Maine) and Claudia Schmidt (Penn State and NERCRD) provides a snapshot of the national agritourism landscape and documents recent changes across the industry. The data brief, which was published by the Northeast Regional Center for Rural Development (NERCRD), is available below:

Authors: Jason S. Entsminger and Claudia Schmidt

Publication: NERCRD Data Brief Series   Date Published: May 7, 2024

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How export performance is mediated by innovation, owner characteristics, and location

Abstract: We investigate how innovation affects rural nonfarm exports, and thus the U.S. trade deficit. Previous European studies indicate a positive link between R&D expenditures, patented innovation, and exports, but no comparable U.S. firm-level research exists. Using data from the Longitudinal Firm Trade Transactions Database and Annual Business Survey, we examine the relationship between innovation and exports for the United States. Employing a two-stage selection model to address endogeneity concerns, our findings suggest a significant connection between innovation and export. The study contributes to understanding the pivotal role of rural nonfarm exports and highlights policy implications for both trade and rural innovation.

Authors: Luyi Han, Timothy R. Wojan, Zheng Tian, Stephan J. Goetz

Publication: Economics Letters   Date Published: March 28, 2024

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Testing biasedness of self-reported microbusiness innovation in the annual business survey

This study tests for potential bias in self-reported innovation due to the inclusion of a research and development (R&D) module that only microbusinesses (less than 10 employees) receive in the Annual Business Survey (ABS). Previous research found that respondents to combined innovation/R&D surveys reported innovation at lower rates than respondents to innovation-only surveys. A regression discontinuity design is used to test whether microbusinesses, which constitute a significant portion of U.S. firms with employees, are less likely to report innovation compared to other small businesses. In the vicinity of the 10-employee threshold, the study does not detect statistically significant biases for new-to-market and new-to-business product innovation. Statistical power analysis confirms the nonexistence of biases with a high power. Comparing the survey design of ABS to earlier combined innovation/R&D surveys provides valuable insights for the proposed integration of multiple Federal surveys into a single enterprise platform survey. The findings also have important implications for the accuracy and reliability of innovation data used as an input to policymaking and business development strategies in the United States.

Authors: Luyi Han, Zheng Tian, Timothy R. Wojan, and Stephan J. Goetz

Publication: Plos ONE   Date Published: January 12, 2024

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