Examining The Role of Livelihood Diversification as a Part of Climate-Smart Agriculture (CSA) Strategy
Abstract
Climate change poses a
severe threat to agricultural livelihood due to the increased intensity of
environmental shocks and weather variability. Livelihood diversification plays
an important role to cope with climate variability and diminishing food
insecurity. This study investigates the main drivers of livelihood
diversification such as crop production, livestock farming, and off-farm income
diversification, particularly focusing on the part of climate-smart agriculture
(CSA) strategy and its impact on farm households’
welfare. Data were collected from 420 farmers in 35 villages located in
different agro-ecological zones (AEZs) of Punjab province, Pakistan. We used
the Seemingly Unrelated Regression (SUR) model to regress a system of equations
consists of the crop, livestock, and off-farm income-generating livelihood
activities. Estimation shows that crop, livestock and off-farm diversification
on average have a positive and significant impact on welfare when farmers
adopted it as an adaptation strategy to mitigate the impact of climate change
and earned more 9.3 % income than nonadopted farmers. Moreover, positive and
significant determinants of assets endowment such as human, physical, natural,
social and financial capital confirmed that well-endowed farmers were enabled
more to adopt livelihood diversification than other farmers. Based on the
findings, we suggest the policy implications regarding the institutional
interventions aimed at strengthening the most important livelihood
diversification drivers, to support for improving the household strategic
assets endowments.
Supporting Institution
Atatürk Üniversitesi, Ziraat Fakültesi Tarımsal Yapılar ve Sulama Bölümü
Project Number
Turkish Government (TBS), Grant No. 18PK015832
Thanks
This study is the part of PhD joint research work conducted in Department of Agricultural Structures and Irrigation, Ataturk University, Turkey and Department of Economics, Federal Urdu University of Arts, Science and Technology Islamabad, Pakistan. We gratefully acknowledge the financial support for this study provided by Turkish Government (TBS), Grant No. 18PK015832, Turkey. Moreover, we are thankful to the enumerators, agricultural departments, and farmers for their support and cooperation in successfully data collection for this research work.
References
- Abid, M., Schilling, J., Scheffran, J., & Zulfiqar, F. (2016). Climate change vulnerability, adaptation and risk perceptions at farm level in Punjab, Pakistan. Science of The Total Environment, 547, 447–460. https://doi.org/10.1016/J.SCITOTENV.2015.11.125Arslan, A., McCarthy, N., Lipper, L., Asfaw, S., Cattaneo, A., & Kokwe, M. (2015). Climate Smart Agriculture? Assessing the Adaptation Implications in Zambia. Journal of Agricultural Economics, 66(3), 753–780. https://doi.org/10.1111/1477-9552.12107Brown, P. R., Afroz, S., Chialue, L., Chiranjeevi, T., El, S., Grünbühel, C. M. Williams, L. J. (2018). Constraints to the capacity of smallholder farming households to adapt to climate change in South and Southeast Asia. Climate and Development, 1–18. https://doi.org/10.1080/17565529.2018.1442798FAO. (2013). Sourcebook on Climate-Smart Agriculture, Forestry and Fisheries. Retrieved from http://www.fao.org/climate-smart-agriculture/72611/en/.Jiao, X., Pouliot, M., & Walelign, S. Z. (2017). Livelihood Strategies and Dynamics in Rural Cambodia. World Development, 97, 266–278. https://doi.org/10.1016/J.WORLDDEV.2017.04.019Kassie, G. W., Kim, S., Fellizar, F. P., & Ho, B. (2017). Determinant factors of livelihood diversification: Evidence from Ethiopia. Cogent Social Sciences, 3(1). https://doi.org/10.1080/23311886.2017.1369490Kurukulasuriya, P., Kala, N., & Mendelsohn, R. (2011). Adaptation and climate change impacts: a structural Ricardian model of irrigation and farm income in Africa. Climate Change Economics, 2(02), 149-174. https://doi.org/10.1142/S2010007811000255Lipper, L., Thornton, P., Campbell, B. M., Baedeker, T., Braimoh, A., Bwalya, M., Torquebiau, E. F. (2014). Climate-smart agriculture for food security. Nature Climate Change, 4(12), 1068–1072. https://doi.org/10.1038/nclimate2437Nielsen, Ø. J., Rayamajhi, S., Uberhuaga, P., Meilby, H., & Smith‐Hall, C. (2013). Quantifying rural livelihood strategies in developing countries using an activity choice approach. Agricultural Economics, 44(1), 57-71.Rosenstock, T. S., Lamanna, C., Chesterman, S., Bell, P., Arslan, A., Richards, M., Zhou, W. (2016). The scientific basis of climate-smart agriculture: A systematic review protocol. Retrieved from https://cgspace.cgiar.org/handle/10568/70967Sardar, A., Javed, S. A., & Amir-ud-Din, R. (2016). Working paper, Natural Disasters and Economic Growth in Pakistan: An Enquiry into the Floods Related Hazards’ Triad. Islamabad: Pakistan Institute of Development Economics. Retrieved from https://www.pide.org.pk/pdf/Working Paper/EE_Working_Paper-10.pdfSkaf, L., Buonocore, E., Dumontet, S., Capone, R., & Franzese, P. P. (2019). Food security and sustainable agriculture in Lebanon: An environmental accounting framework. Journal of cleaner production, 209, 1025-1032.Stern, N., & Stern, N. H. (2007). The economics of climate change: the Stern review. cambridge University press.Su, W., Liu, M., Zeng, S., Štreimikienė, D., Baležentis, T., & Ališauskaitė-Šeškienė, I. (2018). Valuating renewable microgeneration technologies in Lithuanian households: A study on willingness to pay. Journal of Cleaner Production, 191, 318–329. https://doi.org/10.1016/J.JCLEPRO.2018.04.199Terza, J. V., Basu, A., & Rathouz, P. J. (2008). Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling. Journal of Health Economics, 27(3), 531–543. https://doi.org/10.1016/J.JHEALECO.2007.09.009Thornton, P. K., Rosenstock, T., Förch, W., Lamanna, C., Bell, P., Henderson, B., & Herrero, M. (2018). A qualitative evaluation of CSA options in mixed crop-livestock systems in developing countries. In Climate Smart Agriculture (pp. 385–423). Springer.Williams, P. A., Crespo, O., Abu, M., & Simpson, N. P. (2018). A systematic review of how vulnerability of smallholder agricultural systems to changing climate is assessed in Africa. Environmental Research Letters, 13(10), 103004. https://doi.org/10.1088/1748-9326/aae026Xu, D., Zhang, J., Rasul, G., Liu, S., Xie, F., Cao, M., & Liu, E. (2015). Household livelihood strategies and dependence on agriculture in the mountainous settlements in the Three Gorges Reservoir Area, China. Sustainability, 7(5), 4850-4869.Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348–368. https://doi.org/10.1080/01621459.1962.10480664
Abstract
İklim değişikliği, çevreye
ilişkin ani şokların yoğunluğu ve havanın değişkenliği nedeniyle tarımsal
geçim kaynakları için ciddi tehdit unsuru durumuna gelmiştir. Geçim
kaynaklarındaki çeşitlilik iklimin değişkenliği ile baş etmede ve gıda güvenliğini
artırmada önemli bir rol oynamaktadır. Bu çalışma, özellikle İklim-Akıllı Tarım
stratejisinin tarımsal hanehalkının refahı üzerindeki etkisine odaklanarak,
bitkisel üretim, hayvancılık ve tarım dışı geçim kaynaklarının çeşitliliğini
belirleyen temel faktörleri araştırmaktadır. Bu amaçla Pakistan'ın Punjab
bölgesindeki farklı tarımsal ekolojik bölgelerinde (AEZ) bulunan 35 köyde 420
çiftçi ile anket yapılarak veri toplanmıştır. Bitkisel üretim, hayvancılık ve
tarım dışı gelir getirici faaliyetlerden oluşan bir denklem sistemini
geliştirmek için Görünürde İlişkisiz Regresyon (SUR) modeli kullanılmıştır. Tahminler,
hayvancılık ve tarım dışı faaliyetlerin çiftçiler üzerinde iklim değişikliğinin
etkisini hafiflettiği ve iklim değişikliğine uyum sağlayamayan çiftçilerden %
9.3 daha fazla gelir sağladığı için,
refah üzerinde ortalama olarak olumlu ve önemli bir etkiye sahip
olduğunu göstermektedir. Buna ek olarak, sermaye varlığının (insan gücü,
fiziksel sermaye, doğal kaynaklar, sosyal sermaye ve ekonomik güç) pozitif ve
önemli belirleyicileri, iyi donanımlı tarımsal hanehalklarının diğer tarım
işletmelerinden daha fazla geçim çeşitliliği benimsemelerine olanak sağladığını
doğrulamaktadır. Bulgulara dayanarak, kurumsal katkıların işletmelerde geçim
çeşitliliği sağlayan en önemli itici güçlerini artırmayı ve hanehalkının
stratejik mal varlığını iyileştirmeyi destekleyen politikalar şeklinde olması
önerilmiştir.
Project Number
Turkish Government (TBS), Grant No. 18PK015832
References
- Abid, M., Schilling, J., Scheffran, J., & Zulfiqar, F. (2016). Climate change vulnerability, adaptation and risk perceptions at farm level in Punjab, Pakistan. Science of The Total Environment, 547, 447–460. https://doi.org/10.1016/J.SCITOTENV.2015.11.125Arslan, A., McCarthy, N., Lipper, L., Asfaw, S., Cattaneo, A., & Kokwe, M. (2015). Climate Smart Agriculture? Assessing the Adaptation Implications in Zambia. Journal of Agricultural Economics, 66(3), 753–780. https://doi.org/10.1111/1477-9552.12107Brown, P. R., Afroz, S., Chialue, L., Chiranjeevi, T., El, S., Grünbühel, C. M. Williams, L. J. (2018). Constraints to the capacity of smallholder farming households to adapt to climate change in South and Southeast Asia. Climate and Development, 1–18. https://doi.org/10.1080/17565529.2018.1442798FAO. (2013). Sourcebook on Climate-Smart Agriculture, Forestry and Fisheries. Retrieved from http://www.fao.org/climate-smart-agriculture/72611/en/.Jiao, X., Pouliot, M., & Walelign, S. Z. (2017). Livelihood Strategies and Dynamics in Rural Cambodia. World Development, 97, 266–278. https://doi.org/10.1016/J.WORLDDEV.2017.04.019Kassie, G. W., Kim, S., Fellizar, F. P., & Ho, B. (2017). Determinant factors of livelihood diversification: Evidence from Ethiopia. Cogent Social Sciences, 3(1). https://doi.org/10.1080/23311886.2017.1369490Kurukulasuriya, P., Kala, N., & Mendelsohn, R. (2011). Adaptation and climate change impacts: a structural Ricardian model of irrigation and farm income in Africa. Climate Change Economics, 2(02), 149-174. https://doi.org/10.1142/S2010007811000255Lipper, L., Thornton, P., Campbell, B. M., Baedeker, T., Braimoh, A., Bwalya, M., Torquebiau, E. F. (2014). Climate-smart agriculture for food security. Nature Climate Change, 4(12), 1068–1072. https://doi.org/10.1038/nclimate2437Nielsen, Ø. J., Rayamajhi, S., Uberhuaga, P., Meilby, H., & Smith‐Hall, C. (2013). Quantifying rural livelihood strategies in developing countries using an activity choice approach. Agricultural Economics, 44(1), 57-71.Rosenstock, T. S., Lamanna, C., Chesterman, S., Bell, P., Arslan, A., Richards, M., Zhou, W. (2016). The scientific basis of climate-smart agriculture: A systematic review protocol. Retrieved from https://cgspace.cgiar.org/handle/10568/70967Sardar, A., Javed, S. A., & Amir-ud-Din, R. (2016). Working paper, Natural Disasters and Economic Growth in Pakistan: An Enquiry into the Floods Related Hazards’ Triad. Islamabad: Pakistan Institute of Development Economics. Retrieved from https://www.pide.org.pk/pdf/Working Paper/EE_Working_Paper-10.pdfSkaf, L., Buonocore, E., Dumontet, S., Capone, R., & Franzese, P. P. (2019). Food security and sustainable agriculture in Lebanon: An environmental accounting framework. Journal of cleaner production, 209, 1025-1032.Stern, N., & Stern, N. H. (2007). The economics of climate change: the Stern review. cambridge University press.Su, W., Liu, M., Zeng, S., Štreimikienė, D., Baležentis, T., & Ališauskaitė-Šeškienė, I. (2018). Valuating renewable microgeneration technologies in Lithuanian households: A study on willingness to pay. Journal of Cleaner Production, 191, 318–329. https://doi.org/10.1016/J.JCLEPRO.2018.04.199Terza, J. V., Basu, A., & Rathouz, P. J. (2008). Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling. Journal of Health Economics, 27(3), 531–543. https://doi.org/10.1016/J.JHEALECO.2007.09.009Thornton, P. K., Rosenstock, T., Förch, W., Lamanna, C., Bell, P., Henderson, B., & Herrero, M. (2018). A qualitative evaluation of CSA options in mixed crop-livestock systems in developing countries. In Climate Smart Agriculture (pp. 385–423). Springer.Williams, P. A., Crespo, O., Abu, M., & Simpson, N. P. (2018). A systematic review of how vulnerability of smallholder agricultural systems to changing climate is assessed in Africa. Environmental Research Letters, 13(10), 103004. https://doi.org/10.1088/1748-9326/aae026Xu, D., Zhang, J., Rasul, G., Liu, S., Xie, F., Cao, M., & Liu, E. (2015). Household livelihood strategies and dependence on agriculture in the mountainous settlements in the Three Gorges Reservoir Area, China. Sustainability, 7(5), 4850-4869.Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348–368. https://doi.org/10.1080/01621459.1962.10480664
Details
| Primary Language | English |
|---|---|
| Journal Section | ARAŞTIRMALAR |
| Authors | |
| Project Number | Turkish Government (TBS), Grant No. 18PK015832 |
| Publication Date | January 25, 2020 |
| Published in Issue | Year 2020 Volume: 51 Issue: 1 |
Cite
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