Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam
Vietnam coffee sector plays a crucial role not only in the country’s economy but also in the global coffee market, and improving coffee production efficiency may benefit coffee producers. However, small-holder coffee farming households still encounter many difficulties regarding resources and socio-...
Lưu vào:
| Tác giả chính: | |
|---|---|
| Đồng tác giả: | |
| Định dạng: | Journal Article |
| Thông tin xuất bản: |
Trường Đại học Kinh tế Tp. Hồ Chí Minh
2017
|
| Chủ đề: | |
| Truy cập trực tuyến: | http://digital.lib.ueh.edu.vn/handle/UEH/55274 http://jabes.ueh.edu.vn/Home/SearchArticle?article_Id=3d33b1b7-ac74-4ef0-9480-7964a96fa6df http://doi.org/10.24311/jabes/2016.23.4.04 |
| Từ khóa: |
Thêm từ khóa bạn đọc
Không có từ khóa, Hãy là người đầu tiên gắn từ khóa cho biểu ghi này!
|
| id |
oai:localhost:UEH-55274 |
|---|---|
| record_format |
dspace |
| institution |
Đại học Kinh tế Thành phố Hồ Chí Minh |
| collection |
DSpaceUEH |
| topic |
Coffee Credit DakLak Income diversification Labor dependence Technical efficiency |
| spellingShingle |
Coffee Credit DakLak Income diversification Labor dependence Technical efficiency Ho Quoc Thong Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam |
| description |
Vietnam coffee sector plays a crucial role not only in the country’s economy but also in the global coffee market, and improving coffee production efficiency may benefit coffee producers. However, small-holder coffee farming households still encounter many difficulties regarding resources and socio-economic conditions affecting coffee production efficiency. This study examines relationships among income diversification, rural credit loan, labor dependence, and technical efficiency in coffee production through a face-to-face survey with participation of 143 coffee farming households conducted in Cu M’gar District, Dak Lak Province, Vietnam. The stochastic frontier model shows that the mean of technical efficiency scores is 0.64, and it also verifies the existence of inefficiency variation. Both Maximum Likelihood Estimate (MLE) and Feasible Generalized Least Square (FGLS) consistently indicate that a higher level of diversity in income sources negatively affects coffee production efficiency. Additionally, independence in labor resource for coffee farming may help farmers increase technical efficiency of coffee production. Credit loan has a positive and statistically significant relationship with technical efficiency of coffee production. These relationships hold especially true for smallholder coffee farms with ethnic minority household heads. The policy options of credit loan access, intensive investment in coffee production rather than diversification of coffee farmers’ income sources, and independent management strategies for labor sources are suggested as an integrated approach to improve technical efficiency in coffee production of smallholder coffee farms. |
| author2 |
Tuyet Hoa Niekdam |
| author_facet |
Tuyet Hoa Niekdam Ho Quoc Thong |
| format |
Journal Article |
| author |
Ho Quoc Thong |
| author_sort |
Ho Quoc Thong |
| title |
Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam |
| title_short |
Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam |
| title_full |
Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam |
| title_fullStr |
Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam |
| title_full_unstemmed |
Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam |
| title_sort |
labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of cu m’gar district, dak lak province, vietnam |
| publisher |
Trường Đại học Kinh tế Tp. Hồ Chí Minh |
| publishDate |
2017 |
| url |
http://digital.lib.ueh.edu.vn/handle/UEH/55274 http://jabes.ueh.edu.vn/Home/SearchArticle?article_Id=3d33b1b7-ac74-4ef0-9480-7964a96fa6df http://doi.org/10.24311/jabes/2016.23.4.04 |
| work_keys_str_mv |
AT hoquocthong labordependenceincomediversificationruralcreditandtechnicalefficiencyofsmallholdercoffeefarmsacasestudyofcumgardistrictdaklakprovincevietnam |
| _version_ |
1810056390420463616 |
| spelling |
oai:localhost:UEH-552742021-09-21T07:34:14Z Labor dependence, income diversification, rural credit, and technical efficiency ofsmall-holder coffee farms: a case study of Cu M’gar district, Dak Lak province, Vietnam Ho Quoc Thong Tuyet Hoa Niekdam Coffee Credit DakLak Income diversification Labor dependence Technical efficiency Vietnam coffee sector plays a crucial role not only in the country’s economy but also in the global coffee market, and improving coffee production efficiency may benefit coffee producers. However, small-holder coffee farming households still encounter many difficulties regarding resources and socio-economic conditions affecting coffee production efficiency. This study examines relationships among income diversification, rural credit loan, labor dependence, and technical efficiency in coffee production through a face-to-face survey with participation of 143 coffee farming households conducted in Cu M’gar District, Dak Lak Province, Vietnam. The stochastic frontier model shows that the mean of technical efficiency scores is 0.64, and it also verifies the existence of inefficiency variation. Both Maximum Likelihood Estimate (MLE) and Feasible Generalized Least Square (FGLS) consistently indicate that a higher level of diversity in income sources negatively affects coffee production efficiency. Additionally, independence in labor resource for coffee farming may help farmers increase technical efficiency of coffee production. Credit loan has a positive and statistically significant relationship with technical efficiency of coffee production. These relationships hold especially true for smallholder coffee farms with ethnic minority household heads. The policy options of credit loan access, intensive investment in coffee production rather than diversification of coffee farmers’ income sources, and independent management strategies for labor sources are suggested as an integrated approach to improve technical efficiency in coffee production of smallholder coffee farms. 2017-09-14T11:02:25Z 2017-09-14T11:02:25Z 2016 Journal Article 1859 -1124 http://digital.lib.ueh.edu.vn/handle/UEH/55274 http://jabes.ueh.edu.vn/Home/SearchArticle?article_Id=3d33b1b7-ac74-4ef0-9480-7964a96fa6df http://doi.org/10.24311/jabes/2016.23.4.04 Journal of Economic Development JED, Vol.23(4) Aigner, D. J., Lovell, C. A. K., & Schmidt, P.(1977). Formulation and estimation of stochastic frontier production functionmodels. Journal of Econometrics, 6(1), 21–37. Alvarez, A., & Arias, C.(2004). Technical efficiency and farm size: A conditional analysis. AgriculturalEconomics, 30(3), 241–250.http://doi.org/10.1111/j.1574-0862.2004.tb00192.x Battese, G. E. (1992).Frontier production functions and technical efficiency: A survey of empiricalapplications in agricultural economics. Agricultural Economics, 7(3–4),185–208. Battese, G. E., & Coelli,T. (1995). A model for technical inefficiency effects in a stochastic frontierproduction function for panel data. Empirical Economics, 20(2),325–332. http://doi.org/10.1007/BF01205442 Binam, J. N., Tonyè, J.,Wandji, N., Nyambi, G., & Akoa, M. (2004). Factors affecting the technicalefficiency among smallholder farmers in the slash and burn agriculture zone ofCameroon. Food Policy, 29(5), 531–545.http://doi.org/10.1016/j.foodpol.2004.07.013 Coelli, T. (1998). Amulti-stage methodology for the solution of orientated DEA models. OperationsResearch Letters, 23(3–5), 143–149.http://doi.org/10.1016/S0167-6377(98)00036-4 Coelli, T., & Fleming, E.(2004). Diversification economies and specialisation efficiencies in a mixedfood and coffee smallholder farming system in Papua New Guinea. AgriculturalEconomics, 31(2–3), 229–239.http://doi.org/10.1016/j.agecon.2004.09.010 Dak Lak Statistical Office.(2011). Dak Lak Statistical Yearbook 2011. Dak Lak Province, Vietnam:Dak Lak Statistical Office. Dang, H., & Shively, G.(2008). Coffee boom, coffee bust, and smallholder response in Vietnam’s CentralHighlands. Review of Development Economics, 12(2), 312–326.http://doi.org/10.1111/j.1467-9361.2007.00391.x D’haeze, D., Deckers, J.,Raes, D., Tran, A. P., & Nguyen, D. M. C. (2003). Over-irrigation of Coffeacanephora in the Central Highlands of Vietnam revisited: Simulation of soilmoisture dynamics in Rhodic Ferralsols. Agricultural Water Management, 63(3),185–202. http://doi.org/10.1016/S0378-3774(03)00181-1 Iliyasu, A., Mohamed, Z. A.,Ismail, M. M., Abdullah, A. M., Kamarudin, S. M., & Mazuki, H. (2014). Areview of production frontier research in aquaculture (2001–2011). AquacultureEconomics & Management, 18(3), 221–247. http://doi.org/10.1080/13657305.2014.926464 Illukpitiya, P., &Yanagida, J. F. (2010). Farming vs forests: Trade-off between agriculture andthe extraction of non-timber forest products. Ecological Economics, 69(10),1952–1963. http://doi.org/10.1016/j.ecolecon.2010.05.007 Kamil, A. A., Fatama, K.,Pinang, P., & Society, M. H. (2009). Technical efficiency in stochasticfrontier production model: An application to the manufacturing industry inBangladesh. Translog, 3(2), 1160–1169. Kehinde, A. L., Awoyemi, T.T., Omonona, B. T., & Akande, J. A. (2010). Technical efficiency ofsawnwood production in Ondo and Osun states, Nigeria. Journal of ForestEconomics, 16(1), 11–18. http://doi.org/10.1016/j.jfe.2009.04.001 Kumbhakar, S. C. (1996). Afarm-level study of labor use and efficiency wages in Indian agriculture. Journalof Econometrics, 72(1–2), 177–195.http://doi.org/10.1016/0304-4076(94)01719-0 Marsh, A. (2007). Diversification by smallholder farmers:Vietnam Robusta Coffee. Agricultural Management, Marketing, and FinanceWorking Document No. 19. Rome, Italy: Food and Agriculture Organisation ofthe United Nations. McDonald, J. (2009). Usingleast squares and tobit in second stage DEA efficiency analyses. EuropeanJournal of Operational Research, 197(2), 792–798.http://doi.org/10.1016/j.ejor.2008.07.039 Meeusen, W., & van DenBroeck, J. (1977). Efficiency estimation from Cobb-Douglas production functionswith composed error. International Economic Review, 18(2),435–444. Meyfroidt, P., Vu, T. P.,& Hoang, V. A. (2013). Trajectories of deforestation, coffee expansion anddisplacement of shifting cultivation in the Central Highlands of Vietnam. GlobalEnvironmental Change, 23(5), 1187–1198. http://doi.org/10.1016/j.gloenvcha.2013.04.005 Nchare, A. (2007). Analysis of factors affecting technicalefficiency of Arabica coffee producers in Cameroon. AERC Research Paper No.163. Nairobi: African EconomicResearch Consortium. Nowak-Lehmann, D. F., Herzer,D., Vollmer, S., & Martínez-Zarzoso, I. (2011). Modelling the dynamics ofmarket shares in a pooled data setting: Econometric and empirical issues. AppliedEconomics, 43(7), 823–835. http://doi.org/10.1080/00036840802599925 Obwona, M. (2002). Determinants of technical efficiencydifferentials among small- and medium-scale farmers in Uganda : A case oftobacco growers. Kampala, Uganda: Economic Policy Research Center. Ofori-Bah, A., &Asafu-Adjaye, J. (2011). Scope economies and technical efficiency of cocoaagroforesty systems in Ghana. Ecological Economics, 70(8),1508–1518. http://doi.org/10.1016/j.ecolecon.2011.03.013 Picazo-Tadeo, A. J.,Gómez-Limón, J. A., & Reig-Martínez, E. (2011). Assessing farmingeco-efficiency: A data envelopment analysis approach. Journal ofEnvironmental Management, 92(4), 1154–1164.http://doi.org/10.1016/j.jenvman.2010.11.025 Pitt, M. M., & Lee, L. F.(1981). The measurement and sources of technical inefficiency in the Indonesianweaving industry. Journal of Development Economics, 9(1), 43–64. Rahman, S. (2009). Whethercrop diversification is a desired strategy for agricultural growth inBangladesh? Food Policy, 34(4), 340–349. http://doi.org/10.1016/j.foodpol.2009.02.004 Tingley, D., Pascoe, S., &Coglan, L. (2005). Factors affecting technical efficiency in fisheries:Stochastic production frontier versus data envelopment analysis approaches. FisheriesResearch, 73(3), 363–376. http://doi.org/10.1016/j.fishres.2005.01.008 Vedenov, D., Houston, J.,& Cardenas, G. (2007). Production efficiency and diversification in Mexicancoffee-producing districts. Journal of Agricultural and Applied Economics,39(3), 749–763. none Portable Document Format (PDF) 22 41 Trường Đại học Kinh tế Tp. Hồ Chí Minh |