10.57647/amc.2026.100108

Human Capital Thresholds and the International Absorption of Agricultural Technology: Evidence from Emerging Economies

  1. Department of Economics and Administrative Science, Gonbad Kavous University, Gonbad Kavous, Iran

Received: 2026-01-25

Revised: 2026-02-25

Accepted: 2026-03-03

Published in Issue 2026-06-30

How to Cite

Mohammadi Khyareh, M. (2026). Human Capital Thresholds and the International Absorption of Agricultural Technology: Evidence from Emerging Economies. Agricultural Marketing and Commercialization, 10(1). https://doi.org/10.57647/amc.2026.100108

PDF views: 1

Abstract

The international absorption of agricultural technology (agri-tech) is essential for enhancing agricultural productivity and ensuring global food security, particularly in emerging economies. Despite increasing flows of Foreign Direct Investment (FDI) and growing international collaboration in agricultural innovation, the effectiveness of these channels remains uneven. This study examines whether human capital quality (HCQ) constitutes a critical threshold condition for the effective absorption of foreign agricultural technologies. Using an unbalanced panel of 30 emerging economies over the period 2002–2023, the study employs a dynamic panel data framework. System Generalized Method of Moments (System-GMM) is applied to address endogeneity, persistence, and unobserved heterogeneity. To capture potential non-linearities, a Panel Threshold Regression (PTR) model is used to identify regime shifts in the relationship between external technology inflows and domestic agricultural innovation outcomes. The results indicate that human capital quality significantly enhances the absorptive capacity for agricultural technology transmitted through both FDI and international co-patenting networks. However, these effects are highly non-linear. Meaningful spillovers to agricultural productivity and patenting emerge only once HCQ exceeds a critical threshold, estimated at a human capital index value of approximately 0.55. Below this threshold, FDI-related technology spillovers are statistically insignificant. The findings highlight the existence of human capital thresholds in international agri-tech diffusion. Policies aimed solely at attracting FDI or promoting international collaboration are insufficient unless accompanied by sustained investments in education quality and skill formation.

Keywords

  • Human capital thresholds,
  • Agricultural technology absorption,
  • International knowledge spillovers,
  • foreign direct investment,
  • emerging economies

References

  1. Abdelkawy, N. A., & Alzuwaidi, L. (2025). Institutional quality, energy efficiency, and natural gas: Explaining CO2 emissions in the GCC, 2000–2023. Sustainability, 17(15), 6746.
  2. Agrawal, A., Kapur, D., & McHale, J. (2008). How do spatial and social proximity influence knowledge flows? Evidence from patent data. Journal of urban economics, 64(2), 258-269.
  3. Ali, M., Cantner, U., & Roy, I. (2016). Knowledge spillovers through FDI and trade: the moderating role of quality-adjusted human capital. Journal of Evolutionary Economics, 26(4), 837-868.
  4. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The review of economic studies, 58(2), 277-297.
  5. Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of econometrics, 68(1), 29-51.
  6. Bada, O., & Liebl, D. (2014). phtt: Panel data analysis with heterogeneous time trends in R. Journal of Statistical Software, 59, 1-33.
  7. Ben Hassine, H., Boudier, F., & Mathieu, C. (2017). The two ways of FDI R&D spillovers: Evidence from the French manufacturing industry. Applied Economics, 49(25), 2395-2408.
  8. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of econometrics, 87(1), 115- 143.
  9. Cheng, X. (2025). Structural characteristics and determinants of the patent collaboration network in China’s agricultural sector. Agricultural Economics, 71(6), 285-297.
  10. Choi, N. (2015). Accounting for quality differences in human capital and foreign direct investment. The Journal of International Trade & Economic Development, 24(2), 228-246.
  11. Choudhury, P. (2016). Return migration and geography of innovation in MNEs: A natural experiment of knowledge production by local workers reporting to return migrants. Journal of Economic Geography, 16(3), 585-610.
  12. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative science quarterly, 35(1), 128-152.
  13. Croissant, Y., & Millo, G. (2008). Panel data econometrics in R: The plm package. Journal of statistical software, 27, 1-43.
  14. Cuadros, A., Navas, A., & Paniagua, J. (2022). Moving ideas across borders: Foreign inventors, patents and FDI. The World Economy, 45(12), 3652-3678.
  15. Czajkowski, Z., Kowalski, A. M., Michorowska, B., & Weresa, M. A. (2013). Human Capital and Innovation, Basic concepts, measures, and interdependencies. In Innovation, Human Capital and Trade Competitiveness: How Are They Connected and Why Do They Matter? (pp. 53-80). Cham: Springer International Publishing.
  16. Delevic, U. (2024). Human Capital and the Quality of Foreign Direct Investments. Eurasian Journal of Business and Economics, 17(33), 29-51.
  17. Gkypali, A., Arvanitis, S., & Tsekouras, K. (2018). Absorptive capacity, exporting activities, innovation openness and innovation performance: A SEM approach towards a unifying framework. Technological Forecasting and Social Change, 132, 143-155.
  18. Guenichi, H., & Omri, N. A. E. (2025). Threshold effects of institutional quality on FDI-economic growth nexus: a panel smooth transition regression (PSTR) model. Environment, Development and Sustainability, 27(8), 19097-19119.
  19. Han, Y., Smith, R. B., & Wu, L. (2024). The impacts of foreign direct investment on total factor productivity: an empirical study of agricultural enterprises. China Agricultural Economic Review, 16(1), 20-37.
  20. Han, Y., Sun, Y., Huang, K., & Xu, C. (2025). The nexus of foreign direct investment and agricultural productivity: does absorptive capacity matter?. Kybernetes, 54(4), 2389-2413.
  21. Hansen, B. E. (1999). Threshold effects in non-dynamic panels: Estimation, testing, and inference. Journal of econometrics, 93(2), 345-368.
  22. Haq, N. U. (2023). Impact of FDI and its absorption capacity on the national innovation ecosystems: evidence from the largest FDI recipient countries of the world. Foreign Trade Review, 58(2), 259- 288.
  23. Hoenen, S., Kolympiris, C., Wubben, E., & Omta, O. (2017). Technology transfer in agriculture: the case of Wageningen University. In From Agriscience to Agribusiness: Theories, Policies and Practices in
  24. Technology Transfer and Commercialization (pp. 257-276). Cham: Springer International Publishing.
  25. Hu, S., & Fu, Z. (2023, November). Analysis of Factors Influencing the Formation of Agricultural Science and Technology Collaborative Innovation Network: Empirical Evidence from ERGM. In International Symposium on Knowledge and Systems Sciences (pp. 230-245). Singapore: Springer Nature Singapore.
  26. Jinji, N., Zhang, X., & Haruna, S. (2021). Vertical versus horizontal foreign direct investment and technology spillovers. In Deep Integration, Global Firms, and Technology Spillovers (pp. 99-126). Singapore: Springer Nature Singapore.
  27. Kastratović, R. (2023). Exporting decision of agricultural firms: The role of foreign direct investment. Agribusiness, 39(4), 960-984.
  28. Lauvås, T., & Steinmo, M. (2021). The role of proximity dimensions and mutual commitment in shaping the performance of universityindustry research centres. Innovation, 23(2), 182-208.
  29. Li, P., & Xu, J. (2010, August). The Effect of Human Capital Flow on FDI Technological Advances: An Empirical Study Based on Absorptive Capacity. In 2010 International Conference on Management and Service Science (pp. 1-4). IEEE.
  30. Liu, K. (2014). Human capital, social collaboration, and patent renewal within US pharmaceutical firms. Journal of management, 40(2), 616-636.
  31. Lucas Jr, R. E. (1988). On the mechanics of economic development.Journal of monetary economics, 22(1), 3-42.
  32. Mason, G., Rincon-Aznar, A., & Venturini, F. (2020). Which skills contribute most to absorptive capacity, innovation and productivity performance? Evidence from the US and Western Europe. Economics of Innovation and New Technology, 29(3), 223- 241.
  33. Meyer, J. P. (2023). Social capital as the main driver of organizationally valuable innovation. European Journal of Innovation Management, 26(5), 1293-1311.
  34. Mohamad, A. M., & Yunus, N. M. (2024). Knowledge Spillovers and Workers’ Absorptive Capacity in Manufacturing Industry. Jurnal Ekonomi Malaysia, 58(1), 77-90.
  35. Molina-Morales, F. X., García-Villaverde, P. M., & Parra-Requena, G. (2014). Geographical and cognitive proximity effects on innovation performance in SMEs: a way through knowledge acquisition. International Entrepreneurship and Management Journal, 10(2), 231-251.
  36. Mubarik, M. S., Devadason, E. S., & Govindaraju, C. (2020). Human capital and export performance of small and medium enterprises in Pakistan. International Journal of Social Economics, 47(5), 643- 662.
  37. Nguyen, H. T. Y. (2024). Determinants of foreign direct investment in the agricultural sector: Empirical evidence based on economic regional data in Vietnam. Journal of Infrastructure, Policy and Development, 8(3), 2702.
  38. Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica: Journal of the econometric society, 1417- 1426.
  39. Nyameino, A. A., & Saurombe, A. (2025). Challenges in commercialisation of protected university agricultural research outputs: a review in the context of global hunger and the Kenyan experience. International Journal of Intellectual Property Management, 15(3), 233-249.
  40. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372.
  41. Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in Stata. The stata journal, 9(1), 86-136.
  42. Sabir, S., Rafique, A., & Abbas, K. (2019). Institutions and FDI: evidence from developed and developing countries. Financial Innovation, 5(1), 1-20.
  43. Saini, S., & Keswani Mehra, M. (2024). Quality of Schooling, Fertility and Economic Growth. Review of Economic Analysis, 16(2), 175- 220.
  44. Sarker, B., & Serieux, J. (2022). Foreign-invested and domestic firm attributes and spillover effects: Evidence from Brazil. Journal of Multinational Financial Management, 63, 100719.
  45. Schiffauerova, A., & Beaudry, C. (2012). Collaboration spaces in Canadian biotechnology: A search for gatekeepers. Journal of Engineering and Technology Management, 29(2), 281-306.
  46. Skytt-Larsen, C. B. (2018). The influence of the early formation of human and social capital on inventiveness: perspectives from a Swedish case study. GeoJournal, 83(6), 1181-1192.
  47. Slesman, L., Abubakar, Y. A., & Mitra, J. (2021). Foreign direct investment and entrepreneurship: does the role of institutions matter?. International Business Review, 30(4), 101774.
  48. Sugiharti, L., Yasin, M. Z., Purwono, R., Esquivias, M. A., & Pane, D. (2022). The FDI spillover effect on the efficiency and productivity of manufacturing firms: Its implication on open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 8(2), 99.
  49. Tawiah, V., Gyapong, E., & Usman, M. (2024). Returnee directors and green innovation. Journal of Business Research, 174, 114369.
  50. Teixeira, A. A., & Heyuan, W. (2012). Is human capital relevant in attracting innovative foreign direct investment to China?. Asian Journal of Technology Innovation, 20(1), 83-96.
  51. Wang, C., & Zhang, G. (2019). Examining the moderating effect of technology spillovers embedded in the intra-and inter-regional collaborative innovation networks of China. Scientometrics, 119(2), 561-593.
  52. Windmeijer, F. (2000). A finite sample correction for the variance of linear two-step GMM estimators. Institute for Fiscal Studies Working Paper No. W.
  53. Xiang, J., Ma, F., & Wang, H. (2023). The effect of intellectual property treaties on international innovation collaboration: A study based on USPTO patents during 1976–2017. Library Hi Tech, 41(2), 666-682.
  54. Zhao, T., Yang, M., Cao, Z., & Wang, X. (2022). Understanding the joint impacts of cognitive, social, and geographic proximities on the performance of innovation collaboration between knowledgeintensive business services and the manufacturing industry: empirical evidence from China. Frontiers in Psychology, 13, 862939.