Volume 5, Issue 6, November 2020, Page: 304-312
Factor Affecting Adoption of IPM Technology; an Example from Banke and Surkhet District of Nepal
Arjun Khanal, Institute of Agriculture and Animal Science, Tribhuwan University, Kirtipur, Kathmandu
Punya Prasad Regmi, Agriculture and Forestry University, Rampur, Chitwan
Gopal Bahadur KC, Department of Plant Pathology, Institute of Agriculture and Animal Science, Kirtipur, Kathmandu
Dilli Bahadur KC, International Maize and Wheat Improvement Center (CIMMYT), Lalitpur, Nepal
Kishor Chandra Dahal, Department of Horticulture, Institute of Agriculture and Animal Science, Tribhuwan University, Kirtipur, Kathmandu
Received: Oct. 29, 2020;       Accepted: Nov. 9, 2020;       Published: Nov. 23, 2020
DOI: 10.11648/j.ijae.20200506.19      View  127      Downloads  60
Abstract
This study evaluates the factor affecting adoption of IPM technology in Banke and Surkhet district of Nepal. An adoption analysis is necessary for describing and measuring the adoption of IPM technologies, which can provide important policy information that can lead to improvement of farmers’ lives. The dependent variable in the following adoption analysis can take four values 1, 2, 3 and 4, indicating different levels of adoption. Due to the ordered nature of the dependent variable the model used was an ordered probit model. The determinants of adoption included in the present model belong in three main categories: socio-demographic, economic, and institutional characteristics. Five variables were statistically significant at 1% level for practicing IPM technology, they were; experience, training, MPC, mass media, and farmer field school. Two variables were statistically significant at 5% level for practicing IPM technology, they were; awareness of pesticides alternatives and field day. One variable age is statistically significant at 10% level for practicing IPM technology. Seven others variables namely gender, total family member, education, farm area, extension agent, credit and visit were statistically non significant. The sign of the coefficient in the coefficient columns shows the type of impact, positive or negative, by the particular variable.
Keywords
IPM Technology, Factor Affecting, Adoption and Market Planning Committee
To cite this article
Arjun Khanal, Punya Prasad Regmi, Gopal Bahadur KC, Dilli Bahadur KC, Kishor Chandra Dahal, Factor Affecting Adoption of IPM Technology; an Example from Banke and Surkhet District of Nepal, International Journal of Agricultural Economics. Vol. 5, No. 6, 2020, pp. 304-312. doi: 10.11648/j.ijae.20200506.19
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Crissman, C., P. Espinosa, C. E. H. Ducrot, D. C. Cole, and F. Carpio. "The Carchi Study Site: Physical, Health, and Potato Farming Systems in Carchi Province." Economic, Environmental, and Health Tradeoffs in Agriculture: Pesticides and the Sustainability of Andean Potato Production, C. Crissman, J. Antle and S. Capalbo, eds. Boston: Kluwer Academic Publishers, 1998.
[2]
Feder G., R. E. Just, and D. Zilberman. 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey." Economic Development and Cultural Change 33(2): 255-298.
[3]
Wooldridge, J. M. 2006. Introductory econometrics: A modern approach. Mason, OH: Thomson/South-Western.
[4]
Mauceri, M. “Adoption of Integrated Pest Management Practice: A Case Study of Potato Farmers in Carachi Ecuador.” M. S., Virginia Tech, 2004.
[5]
Feder, G. and D. L. Umali. 1993. ''The Adoption of Agricultural Innovations A Review.” Technological Forecasting and Social Change 43: 215-239.
[6]
Wooldridge, J. M. 2002. Econometric analysis of cross section and panel data. Cambridge, Mass: MIT Press.
[7]
Mullen, J. D., G. W. Norton, and D. W. Reaves. 1997. "Economic Analysis of Environmental Benefits of Integrated Pest Management." Journal of Agricultural and Applied Economics 29(2): 243-253.
[8]
Rauniyar, G. P., and F. M. Goode. 1996. "Managing Green Revolution Technology: An Analysis of a Differential Practice Combination in Swaziland." Economic Development and Cultural Change 44(2): 413-437.
[9]
Bonabana-Wabbi, Jackline. Assessing Factors Affecting Adoption of Agricultural Technologies: The Case of Integrated Pest Management (IPM) in Kumi District, Eastern Uganda. MS thesis, Virginia Polytechnic Institute and State University, 2002.
[10]
IPM CRSP. (2008c). IPM CRSP Countries at a Glance. Retrieved 09/08/08, from http://www.oired.vt.edu/ipmcrsp/IPM_2008/Countries.htm.
[11]
De Souza-Filho, H. M., T. Young, and M. P. Burton. 1999. “Factors Influencing the Adoption of Sustainable Agricultural Technologies Evidence from the State of Espirito Santo, Brazil.” Technological Forecasting and Social Change 60:97-112.
[12]
Adesina, A., and M. Zinnah. Technology characteristics, farmers. Perceptions and adoption decisions: A Tobit model application in Sierra Leone.. Agricultural Economics 9(1993):297-311.
[13]
Feder G., and R. Slade. 1984. "The Acquisition of Information and the Adoption of New Technology." Amer. J. of Agri. Econ. 66(3):312-320.
[14]
Chaves, B., and J. Riley. 2001 "Determination of factors influencing integrated pest management adoption in coffee berry borer in Colombian farms." Agriculture, Ecosystems & Environment 87, (2):159-177.
[15]
Adesina, A. A., D. Mbila, G. B. Nkamleu, and D. Endamana. 2000. "Econometric analysis of the determinants of adoption of alley farming by farmers in the forest zone of southwest Cameroon." Agriculture, Ecosystems & Environment 80(3): 255-265.
[16]
CBS 2011, National Population and Housing Census.
[17]
Borooah, V. K. 2002. Logit and probit: Ordered and multinomial models. Thousand Oaks, CA: Sage Publications.
[18]
Nhemachena, C. and R. Hassan. 2007. Micro level analysis of farmers’ adaptation to climate change in Southern Africa. IFPRI Discussion Paper No. 00714. International Food Policy Research Institute, Washington D.C.
[19]
Gbetibouo, G. A. 2009. Understanding farmers’ perceptions and adaptations to climate change and variability, the case of the Limpopo Basin, South Africa. IFPRI Discussion Paper No. 00849. Environment and Production Technology Division, International Food Policy Research Institute.
[20]
Feder G., R. Murgai, and J. B. Quizon. The Impact of Farmer Field Schools in Indonesia. World Bank Policy Research Working Paper 3022. April 2003.
[21]
Negatu, W. and A. Parikh. The impact of perception and other factors on the adoption of agricultural technology in the Moret and Jiru Woreda (district) of Ethiopia.. Agricultural Economics 21(1999): 205-216.
Browse journals by subject