What Makes Hemp Economically Attractive? A Case of Kentucky Hemp Farmers

Buddhika Patalee

Department of Agricultural Economics, University of Kentucky, Charles E. Barnhart Bldg. 400, Lexington, KY 40546, USA

Hoyeon Jeong

Department of Agricultural Economics, University of Kentucky, Charles E. Barnhart Bldg. 400, Lexington, KY 40546, USA

Tyler Mark

Department of Agricultural Economics, University of Kentucky, Charles E. Barnhart Bldg. 400, Lexington, KY 40546, USA

DOI: https://doi.org/10.36956/rwae.v5i2.1077

Received: 9 April 2024; Received in revised form: 1 May 2024; Accepted: 8 May 2024; Published: 27 May 2024

Copyright © 2024 Buddhika Patalee, Hoyeon Jeong, Tyler Mark. Published by Nan Yang Academy of Sciences Pte. Ltd.

Creative Commons LicenseThis is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.


Industrial hemp is a versatile plant that can be grown for fiber, grain, and extraction. Over the past decade, hemp has generated significant interest because of its environmentally friendly and sustainable production practices. Kentucky has been one of the pioneer states to reintroduce hemp production in the United States. This paper aims to explore the factors affecting hemp production in Kentucky using a farm-level panel dataset accounting for county-specific economic, environmental, and agronomic factors. The main objective of this study is to provide preliminary insights into the relationship between variables rather than establishing causal relationships due to data constraints. A reduced form econometric model on farm-level hemp acres was developed using unique Kentucky data on hemp production from 2017 to 2019. The regression analysis results show that Kentucky hemp acreage positively responds to an increase in cannabidiol (CBD) biomass price. When CBD prices increase by 10%, hemp acreage would increase by approximately 1%. Based on the "with" and "without" county-level weather information model results, the study demonstrates that weather is an important determinant of Kentucky's total hemp acreage. Our analysis concludes that the hemp acreage response is due to changes in farm-specific, plant-specific, county-specific factors, and market information availability, meaning that a platform for CBD biomass price reporting and a friendly regulatory environment are critical for producers seeking to plan their hemp production. In addition, inconsistencies in state regulations and reporting standards may create additional challenges for hemp production. Thus, additional support through university extension programs and other statewide support services may help hemp producers to expand their production.

Keywords: Hemp; THC content; CBD prices; Quantile regression; Weather


[1] North Dakota State University, Department of Agribusiness and Applied Economics, Agricultural Economics Reports [Internet]. Industrial Hemp as an Alternative Crop In North Dakota [cited 3 April 2024]. Available from: https://ageconsearch.umn.edu/record/23264/?v=pdf

[2] Fortenbery, T.R., Bennett, M., 2004. Opportunities for commercial hemp production. Applied Economic Perspectives and Policy. 26(1), 97–117.

[3] Williams, D.W., Mundell, R., 2018. An introduction to industrial hemp and hemp agronomy. University of Kentucky College of Agriculture, Food, and Environment. 250.

[4] Congressional Research Service [Internet]. Defining hemp: A Fact Sheet [cited 3 April 2024]. Available from: https://sgp.fas.org/crs/misc/R44742.pdf

[5] United States Department of Agriculture (USDA). Economic Research Service. Economic Information Bulletin [Internet]. Economic Viability of Industrial Hemp in the United States: A Review Of State Pilot Programs [cited 3 April 2024]. Available from: https://ageconsearch.umn.edu/record/302486/

[6] Kolodinsky, J., Lacasse, H., Gallagher, K., 2020., Making hemp choices: evidence from vermont. Sustainability. 12(15), 6287. DOI: https://doi.org/10.3390/su12156287

[7] Adesina, I., Bhowmik, A., Sharma, H., et al., 2020., A review on the current state of knowledge of growing conditions, agronomic soil health practices and utilities of hemp in the United States. Agriculture. 10(4), 129. DOI: https://doi.org/10.3390/agriculture10040129

[8] Kaiser, C., Cassady, C., Ernst, M., 2015., Industrial hemp production. Cent Crop Diversification University Kentucky. 27, 101–6.

[9] Lotus, J., 2023. Hemp Cinder Block Under Development at U Nebraska [Internet]. HempBuild Magazine [cited 3 April 2024]. Available from: https://www.hempbuildmag.com/home/hemp-cinder-block

[10] Cherney, J.H., Small, E., 2016. Industrial hemp in north america: production, politics and potential. Agronomy. 6(4), 58. DOI: https://doi.org/10.3390/agronomy6040058

[11] Stöckle, C.O., Donatelli, M., Nelson, R., 2003. CropSyst, a cropping systems simulation model. European Journal of Agronomy. 18(3–4), 289–307. DOI: https://doi.org/10.1016/S1161-0301(02)00109-0

[12] Verburg, P.H., Kok, K., Pontius, R.G., et al., 2006. Modeling Land-Use and Land-Cover Change. Land-Use and Land-Cover Change. Global Change - The IGBP Series. Springer, Berlin, Heidelberg. pp. 117–135. DOI: https://doi.org/10.1007/3-540-32202-7_5

[13] Gebbers, R., Adamchuk, V.I., 2010. Precision agriculture and food security. Science. 327(5967), 828–831. DOI: https://doi.org/10.1126/science.1183899

[14] Anita, W., Dominic, M., Neil, A., 2010. Climate change and agriculture impacts, adaptation and mitigation: impacts, adaptation and mitigation. OECD Publishing. p. 139. DOI: https://doi.org/10.1787/9789264086876-en

[15] Pal, M., Mather, P., 2003. An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sensing of Environment. 86(4), 554–565. DOI: https://doi.org/10.1016/S0034-4257(03)00132-9

[16] Rosenzweig, C., Elliott, J., Deryng, D., et al., 2014. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proceedings of the National Academy of Sciences. 111(9), 3268–3273. DOI: https://doi.org/10.1073/pnas.1222463110

[17] Iizumi, T., Ramankutty, N., 2015. How do weather and climate influence cropping area and intensity? Global Food Security. 4, 46–50. DOI: https://doi.org/10.1016/j.gfs.2014.11.003

[18] Malek, Ž., Verburg, P.H., 2020., Mapping global patterns of land use decision-making. Global Environmental Change. 65, 102170. DOI: https://doi.org/10.1016/j.gloenvcha.2020.102170

[19] Githinji, M., van Noordwijk, M., Muthuri, C., et al., 2023. Farmer land-use decision-making from an instrumental and relational perspective. Current Opinion in Environmental Sustainability. 63, 101303. DOI: https://doi.org/10.1016/j.cosust.2023.101303

[20] Nguyen, T.T., Nguyen, L.D., Lippe, R.S., et al., 2017. Determinants of farmers’ land use decision-making: comparative evidence from Thailand and Vietnam. World Development. 89, 199–213. DOI: https://doi.org/10.1016/j.worlddev.2016.08.010

[21] Wang, T., Luri, M., Janssen, L., et al., 2017. Determinants of motives for land use decisions at the margins of the corn belt. Ecological Economics. 134, 227–37. DOI: https://doi.org/10.1016/j.ecolecon.2016.12.006

[22] Aheibam, M., Singh, R., Feroze, S.M., et al., 2017. Identifying the determinants and extent of crop diversification at household level: an evidence from Ukhrul District, Manipur. Economic Affairs. 62(1), 89. DOI: https://doi.org/10.5958/2230-7311.2017.00043.5

[23] Parvez, R., Roberts, D.C., Ripplinger, D., 2018. Factors impacting crop acreage decision: a case study of North Dakota Agriculture. Agricultural Development. 3, 16–36. DOI: https://doi.org/10.20448/journal.523.2018.31.16.36

[24] Miao, R., Khanna, M., Huang, H., 2016. Responsiveness of crop yield and acreage to prices and climate. American Journal of Agricultural Economics. 98(1), 191–211. DOI: https://doi.org/10.1093/ajae/aav025

[25] Shepherd, J., Mark, T., 2020. Estimates of What it is Going to Cost Me to Destroy my “HOT” Hemp Crop [Internet]. [cited 3 April 2024]. Available from: https://agecon.ca.uky.edu/estimates-what-it-going-cost-me-destroy-my-hot-hemp-crop

[26] Miller, D.J., Plantinga, A.J., 1999. Modeling land use decisions with aggregate data. American Journal of Agricultural Economics. 81(1), 180–94. DOI: https://doi.org/10.2307/1244459

[27] Arora, G., Feng, H., Anderson, C.J., et al., 2020. Evidence of climate change impacts on crop comparative advantage and land use. Agricultural Economics. 51(2), 221–36. DOI: https://doi.org/10.1111/agec.12551

[28] Deschênes, O., Greenstone, M., 2007. The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. American Economic Review. 97(1), 354–385. DOI: https://doi.org/10.1257/aer.97.1.354

[29] Beillouin, D., Schauberger, B., Bastos, A., et al., 2020. Impact of extreme weather conditions on European crop production in 2018. Philosophical Transactions of the Royal Society B: Biological Sciences. 375(1810), 20190510. DOI: https://doi.org/10.1098/rstb.2019.0510

[30] Stack, G., Toth, J., Carlson, C., et al., 2021. Season‐long characterization of high‐cannabinoid hemp (Cannabis sativa L.) reveals variation in cannabinoid accumulation, flowering time, and disease resistance. GCB Bioenergy. 13(4), 546–561. DOI: https://doi.org/10.1111/gcbb.12793

[31] Roberts, M., Schlenker, W., Eyer, J., 2012. Agronomic weather measures in econometric models of crop yield with implications for climate change. American Journal of Agricultural Economics. 95, 236–243. DOI: https://doi.org/10.1093/ajae/aas047

[32] Lobell, D.B., Schlenker, W., Costa-Roberts, J., 2011. Climate trends and global crop production since 1980. Science. 333(6042), 616–620. DOI: https://doi.org/10.1126/science.120453

[33] Schlenker, W., Roberts, M.J., 2009. Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change. Proceedings of the National Academy of Sciences. 106(37), 15594–155598. DOI: https://doi.org/10.1073/pnas.0906865106

[34] Isik, M., 2004. Environmental regulation and the spatial structure of the U.S. dairy sector. American Journal of Agricultural Economics. 86(4), 949–962.

[35] MIT Press [Internet]. Geography and Trade [cited 3 April 2024]. Available from: https://ideas.repec.org/b/mtp/titles/0262610868.html

[36] Schmidt, C., Goetz, S.J., Tian, Z., 2021. Female farmers in the United States: research needs and policy questions. Food Policy. 101, 102039. DOI: https://doi.org/10.1016/j.foodpol.2021.102039

[37] Lambert, D.M., McNamara, K.T., 2009. Location determinants of food manufacturers in the United States, 2000–2004: are nonmetropolitan counties competitive? Agricultural Economics. 40(6), 617–630. DOI: https://doi.org/10.1111/j.1574-0862.2009.00403.x

[38] Goetz, S.J., Debertin, D.L., 2001. Why farmers quit: a county-level analysis. American Journal of Agricultural Economics. 83(4), 1010–1023.

[39] Brinkman, J., Mok-Lamme, D., 2019. Not in my backyard? Not so fast. The effect of marijuana legalization on neighborhood crime. Regional Science and Urban Economics. 78, 103460. DOI: https://doi.org/10.1016/j.regsciurbeco.2019.103460

[40] Kim, G., Mark, T., 2023. What factors make consumers in the USA buy hemp products? Evidence from Nielsen consumer panel data. Agricultural and Food Economics. 11(1), 5. DOI: https://doi.org/10.1186/s40100-023-00245-y

[41] Netafirmusa [Internet]. Hemp Production [cited 3 April 2024]. Available from: https://www.netafimusa.com/agriculture/solutions-for-your-crop/hemp/

[42] Pest and Crop Newsletter [Internet]. Increased Rain Hinders Hemp Production [cited 3 April 2024]. Available from: https://extension.entm.purdue.edu/newsletters/pestandcrop/article/increased-rain-hinders-hemp-production/

[43] Hill, R., Jablonski, B., Van, L., et al., 2023. Producers marketing a novel crop: a field-level view of hemp market channels. Renewable Agriculture and Food Systems. 38, e22. DOI: https://doi.org/10.1017/S1742170523000145

Online ISSN: 2737-4785, Print ISSN: 2737-4777, Published by Nan Yang Academy of Sciences Pte. Ltd.