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Geographic aggregation and induced innovation in American agriculture

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  • Qinghua Liu
  • C. Richard Shumway

Abstract

The induced innovation hypothesis is tested for the USA and western regions using cointegration procedures. An error correction model separates short-run and long-run effects of relative price changes. A significant difference in the elasticities of factor substitution along the isoquant and the innovation possibility curve implies induced innovation. The estimated results support the hypothesis for Washington, the Pacific Northwest, and the Western Region, but not for the nation. Corroborative tests of weak exogeneity fail to support the hypothesis in any of the geographic units. Changes in output level and research investment do not significantly bias agricultural technology in the USA.

Suggested Citation

  • Qinghua Liu & C. Richard Shumway, 2006. "Geographic aggregation and induced innovation in American agriculture," Applied Economics, Taylor & Francis Journals, vol. 38(6), pages 671-682.
  • Handle: RePEc:taf:applec:v:38:y:2006:i:6:p:671-682
    DOI: 10.1080/00036840500397457
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    References listed on IDEAS

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    1. Alston, Julian M. & Craig, Barbara J. & Pardey, Philip G., 1998. "Dynamics in the creation and depreciation of knowledge, and the returns to research:," EPTD discussion papers 35, International Food Policy Research Institute (IFPRI).
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    Cited by:

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    2. Ka Kei Gary Wong & Min Qiang Zhao, 2023. "Induced innovation and its impact on productivity growth in China: a latent variable approach," Empirical Economics, Springer, vol. 65(1), pages 371-399, July.
    3. Yucan Liu & C. Richard Shumway, 2009. "Induced Innovation in U.S. Agriculture: Time-series, Direct Econometric, and Nonparametric Tests," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 224-236.
    4. Yucan Liu & C. Richard Shumway & Robert Rosenman & Virgil Eldon Ball, 2011. "Productivity growth and convergence in US agriculture: new cointegration panel data results," Applied Economics, Taylor & Francis Journals, vol. 43(1), pages 91-102.
    5. Zhang, Congying & Xiang, Jingru & Chang, Qian, 2023. "Does Informatization Cause the Relative Substitution Bias of Agricultural Machinery Inputs for Labor Inputs? Evidence from Apple Farmers in China," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 4(3), September.
    6. Orachos Napasintuwong Artachinda, 2011. "Modeling Directions of Technical Change in Agricultural Sector," Working Papers 201101, Kasetsart University, Department of Agricultural and Resource Economics.
    7. Xilong Jiang & Guanyi Yin & Yi Lou & Shuai Xie & Wei Wei, 2021. "The Impact of Transformation of Farmers’ Livelihood on the Increasing Labor Costs of Grain Plantation in China," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
    8. Yaohui Wang, 2023. "A blessing or a curse? China’s Arctic involvement and its environmental policy to prevent further climatic change and pollution," Climatic Change, Springer, vol. 176(8), pages 1-19, August.
    9. Shumway, C. Richard & Liu, Yucan, 2006. "Induced Innovation in the Agricultural Sector: Evidence From a State Panel," 2006 Annual meeting, July 23-26, Long Beach, CA 21089, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Hua Lu & Hualin Xie & Qianru Chen & Jinfa Jiang, 2018. "Impact of Agricultural Labor Transfer and Structural Adjustment on Chemical Application: Comparison of Past Developments in the Ecological Civilization Pilot Zones of China and Their Future Implicatio," Sustainability, MDPI, vol. 10(6), pages 1-14, June.

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