Open Access
| Issue |
Cah. Agric.
Volume 30, 2021
|
|
|---|---|---|
| Article Number | 46 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/cagri/2021032 | |
| Published online | 01 December 2021 | |
- Abebaw D, Fentie Y, Kassa B. 2010. The impact of a food security program on household food consumption in northwestern Ethiopia: a matching estimator approach. Food Policy 35: 286–293. DOI: 10.1016/j.foodpol.2010.01.002 [CrossRef] [Google Scholar]
- Abebaw D, Haile MG. 2013. The impact of cooperatives on agricultural technology adoption: empirical evidence from Ethiopia. Food Policy 38: 82–91. doi:10.1016/j.foodpol.2012.10.003. [CrossRef] [Google Scholar]
- Akerlov GA. 1970. The market for lemons. Quality uncertainty and the market mechanism. Quarterly Journal of Economics 84: 488–500. doi:10.2307/1879431. [CrossRef] [Google Scholar]
- Belletti G, Marescotti A. 2011. Origin products, geographical indications and rural development. Labels of origin for food. Wallingford (UK): CABI, pp. 75–91. [Google Scholar]
- Belletti G, Marescotti A, Touzard JM. 2017. Geographical indications, public goods and sustainable development: the roles of actors’ strategies and public policies. World Dev 98: 45–57. doi:10.1016/j.worlddev.2015.05.004. [CrossRef] [Google Scholar]
- Biénabe E, Marie-Vivien D. 2017. Institutionalizing geographical indications in southern countries: lessons learned from Basmati and Rooibos. World Dev 98: 58–67. doi:10.1016/j.worlddev.2015.04.004. [CrossRef] [Google Scholar]
- Bontemps C, Bouamra-Mechemache Z, Simioni S. 2013. Quality labels and firm survival: some first empirical evidence. European Review of Agricultural Economics 40(3): 413–439. doi:10.1093/erae/jbs034. [CrossRef] [Google Scholar]
- Bramley C, Biénabe E, Kirsten J. 2009. The economics of geographical indications: towards a conceptual framework for geographical indication research in developing countries. The Economics of Intellectual Property: 109–149. [Google Scholar]
- Caliendo M, Kopeinig S. 2008. Some practical guidance for the implementation of propensity score matching. J Econ Surv 22: 31–72. doi:10.1111/j.1467-6419.2007.00527.x. [CrossRef] [Google Scholar]
- Chagwiza C, Muradian R, Ruben R. 2016. Cooperative membership and dairy performance among smallholders in Ethiopia. Food Policy 59: 165–173. doi:10.1016/j.foodpol.2016.01.008. [CrossRef] [Google Scholar]
- Cook ML, Chambers M. 2007. Role of agricultural cooperatives in global netchains. In: Working Paper for the Montpellier Workshop organized by INRA-MOISA and Wageningen University. Montpellier (France): INRA-MOISA. [Google Scholar]
- Dehejia RH, Wahba S. 2002. Propensity score-matching methods for nonexperimental causal studies. Rev Econ Stat 84: 151–161. doi:10.1162/003465302317331982. [CrossRef] [Google Scholar]
- Deng H, Huang J, Xu Z, Rozelle S. 2010. Policy support and emerging farmer professional cooperatives in rural China. China Economic Review 21(4): 495–507. doi:10.1016/j.chieco.2010.04.009. [CrossRef] [Google Scholar]
- Desquilbet M, Monier-Dilhan S. 2015. Are geographical indications a worthy quality label? A framework with endogenous quality choice. European Review of Agricultural Economics 42(1): 129–150. doi:10.1093/erae/jbu008. [CrossRef] [Google Scholar]
- Diaz V, Wang H, Moustier P, Luan NN. 2009. Consumers’ demand for sticky rice in Hanoi. In: Moustier P, Anh DT, Sacklokham S, eds. Linking small-scale farmers to supermarkets and other quality chains, Superchain report, Hanoi: Cirad, Malica, pp. 16–20. [Google Scholar]
- Durand C, Fournier S. 2017. Can geographical indications modernize Indonesian and Vietnamese agriculture? Analyzing the role of national and local governments and producers’ strategies. World Development 98: 93–104. doi:10.1016/j.worlddev.2015.11.022. [CrossRef] [Google Scholar]
- Fałkowski J, Ciaian P. 2016. Factors supporting the development of producer organizations and their impacts in the light of ongoing changes in food supply chains: a literature review. JRC Technical Report No. EUR 27929 EN. Joint Research Centre, European Commission. [Google Scholar]
- Galtier F, Belletti G. Marescotti A. 2013. Factors constraining building effective and fair geographical indications for coffee: Insights from a Dominican case study. Development Policy Review 31: 597–615. doi:10.1111/dpr.12027. [CrossRef] [Google Scholar]
- Giovannucci D, Josling TE, Kerr W, O’Connor B, Yeung MT. 2009. Guide to geographical indications: linking products and their origins. Geneva: International Trade Centre. https://mpra.ub.uni-muenchen.de/27955/. [Google Scholar]
- Hughes J. 2009. Coffee and chocolate: can we help developing country farmers through geographical indications? Report prepared for the International Intellectual Property Institute. Washington DC (USA), 136 p. doi:10.2139/ssrn.1684370. [Google Scholar]
- Ilbery B, Morris C, Buller H, Maye D, Kneafsey M. 2005. Product, process and place: an examination of food marketing and labelling schemes in Europe and North America. European Urban and Regional Studies 12(2): 116–132. doi:10.1177/0969776405048499. [CrossRef] [Google Scholar]
- Imbens GW. 2004. Nonparametric estimation of average treatment effects under exogeneity: a review. Rev Econ Stat 86: 4–29. doi:10.1162/003465304323023651. [CrossRef] [Google Scholar]
- Jalan J, Ravallion M. 2003. Estimating the benefit incidence of an antipoverty program by propensity-score matching. J Bus Econ Stat 21: 19–30. doi:10.1198/073500102288618720. [CrossRef] [Google Scholar]
- Jena PR, Grote U. 2012. Impact evaluation of traditional Basmati rice cultivation in Uttarakhand State of Northern India: what implications does it hold for Geographical Indications ? World Development 40(9): 1895–1907. doi:10.1016/j.worlddev.2012.04.004. [CrossRef] [Google Scholar]
- Khandker SR, Koolwal GB, Samad HA. 2010. Handbook on impact evaluation: quantitative methods and practices. Washington DC (USA): The World Bank. [Google Scholar]
- Koenker R, Bassett G. 1978. Regression Quantiles. Econometrica 46(1): 33–50. [CrossRef] [Google Scholar]
- Ma WL, Abdulai A. 2017. The economic impacts of agricultural cooperatives on smallholder farmers in rural China. Agribusiness 33(4): 537–551. doi:10.1002/agr.21522. [CrossRef] [Google Scholar]
- Maertens M, Swinnen JFM. 2009. Trade, standards and poverty: evidence from Senegal. World Dev 37(1): 161–178. doi:10.1016/j.worlddev.2008.04.006. [CrossRef] [Google Scholar]
- Michalek J, Ciaian P, Pokrivcak J. 2018. The impact of producer organizations on farm performance: the case study of large farms from Slovakia. Food Policy 75: 80–92. doi:10.1016/j.foodpol.2017.12.009. [CrossRef] [Google Scholar]
- Moustier P, Tam PTG, Anh DT, Binh VT, Loc NTT. 2010. The role of farmer organizations in supplying supermarkets with quality food in Vietnam. Food Policy 35(1): 69–78. doi:10.1016/j.foodpol.2009.08.003. [CrossRef] [Google Scholar]
- Neilson J, Wright J, Aklimawati L. 2018. Geographical indications and value capture in the Indonesia coffee sector. Journal of Rural Studies 59: 35–48. doi:10.1016/j.jrurstud.2018.01.003. [CrossRef] [Google Scholar]
- Ofori E, Sampson GS, Vipham J. 2019. The effects of agricultural cooperatives on smallholder livelihoods and agricultural performance in Cambodia. Natural Resources Forum 43(4): 218–229. doi:10.1111/1477-8947.12180. [CrossRef] [Google Scholar]
- Tregear A, Török Á, Gorton M. 2016. Geographical indications and upgrading of small-scale producers in global agro-food chains: a case study of the Makó Onion Protected Designation of Origin. Environment and Planning A 48(2): 433–451. doi:10.1177/0308518x15607467. [CrossRef] [Google Scholar]
- Williams RM. 2007. Do Geographical Indications Promote Sustainable Rural Development? Two UK case studies and implications for New Zealand rural development policy. Lincoln University report. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.