International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

line decor
  
line decor

 Volume 11, Issue 4 (April 2024), Pages: 93-99

----------------------------------------------

 Original research Paper

Impact of livestock and crop conversion support program on farm household income: A study in Chau Thanh A District

 Author(s): 

 Quang Vang Dang 1, Quoc Duy Vuong 2, *

 Affiliation(s):

 1Dean of Faculty of Economics, Ho Chi Minh University of Technology and Education, Ho Chi Minh City, Vietnam
 2Department of Finance and Banking, School of Economics, Can Tho University, Can Tho City, Vietnam

 Full text

  Full Text - PDF

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-6870-4106

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2024.04.011

 Abstract

This paper investigates the impact of a support program for livestock and crop conversion on the incomes of farm households in the Chau Thanh A district of Hau Giang province. It analyzes data from 250 farming households in the area using the propensity score matching (PSM) method. The study uses probit regression to identify three key factors that significantly affect a household's ability to benefit from the support program: the size of the land owned, as well as the age and gender of the household head. Additionally, the PSM analysis reveals that farm households participating in the support program earn significantly more income than those that do not, with an annual income difference of 159 million VND. These findings support earlier research on the subject. Based on these results, the authors suggest several strategies to encourage more farm households to join the livestock and crop conversion support program, which could help improve their incomes and overall quality of life.

 © 2024 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Livestock and crop conversion support, Farm household income, Propensity score matching method, Probit regression model

 Article history

 Received 17 December 2023, Received in revised form 28 March 2024, Accepted 1 April 2024

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Dang QV and Vuong QD (2024). Impact of livestock and crop conversion support program on farm household income: A study in Chau Thanh A District. International Journal of Advanced and Applied Sciences, 11(4): 93-99

 Permanent Link to this page

 Figures

 No Figure

 Tables

 Table 1 Table 2 Table 3 Table 4

----------------------------------------------   

 References (16)

  1. Akaakohol MA and Aye GC (2014). Diversification and farm household welfare in Makurdi, Benue State, Nigeria. Development Studies Research: An Open Access Journal, 1(1): 168-175. https://doi.org/10.1080/21665095.2014.919232   [Google Scholar]
  2. Alam T and Waheed M (2006). The monetary transmission mechanism in Pakistan: A sectoral analysis. MPRA Paper No. 2719, Munich Personal RePEc Archive, Munich, Germany. https://doi.org/10.2139/ssrn.971318   [Google Scholar]
  3. Allotey SSK, Adam H, and Hudu Z (2019). Impact of fertilizer subsidy programme on maize income in the northern region of Ghana. American Journal of Biomedical Science and Research, 6(2): 124-130. https://doi.org/10.34297/AJBSR.2019.06.001010   [Google Scholar]
  4. Barslund M and Tarp F (2008). Formal and informal rural credit in four provinces of Vietnam. The Journal of Development Studies, 44(4): 485-503. https://doi.org/10.1080/00220380801980798   [Google Scholar]
  5. Bhuiya MMM, Khanam R, Rahman MM, and Nghiem HS (2016). Impact of microfinance on household income and consumption in Bangladesh: Empirical evidence from a quasi-experimental survey. The Journal of Developing Areas, 50(3): 305-318.https://doi.org/10.1353/jda.2016.0111   [Google Scholar]
  6. Diagne A, Zeller M, and Sharma MP (2000). Empirical measurements of households' access to credit and credit constraints in developing countries: Methodological issues and evidence. FCND Discussion Paper No. 90, Food Consumption and Nutrition Division, Washington, USA.   [Google Scholar]
  7. Gadisi M, Owusu-Sekyere E, and Ogundeji AA (2020). Impact of government support programmes on household welfare in the Limpopo province of South Africa. Development Southern Africa, 37(6): 937-952. https://doi.org/10.1080/0376835X.2020.1757414   [Google Scholar]
  8. Mesra B(2018). Factors that influencing households income and its contribution on family income in Hamparan Perak Sub-District, Deli Serdang Regency, North. International Journal of Civil Engineering and Technology, 9(10): 461-469.   [Google Scholar]
  9. Moahid M and Maharjan KL (2020). Factors affecting farmers’ access to formal and informal credit: Evidence from rural Afghanistan. Sustainability, 12(3): 1268. https://doi.org/10.3390/su12031268   [Google Scholar]
  10. Nguyen PK and Pham HT (2015). The effects of the Government program 135 on household income in Dong Thap Muoi, Long An Province. Development and Integration Journal, 25(35): 91-98.   [Google Scholar]
  11. Sikwela MM and Mushunje A (2013). The impact of farmer support programmes on household income and sustainability in smallholder production: A case study of the Eastern Cape and KwaZulu Natal farmers, South Africa. African Journal of Agricultural Research, 8(21): 2502-2511.   [Google Scholar]
  12. Tran GT, Nanseki T, Chomei Y, and Nguyen LT (2023). The impact of cooperative participation on income: The case of vegetable production in Vietnam. Journal of Agribusiness in Developing and Emerging Economies, 13(1): 106-118. https://doi.org/10.1108/JADEE-05-2021-0108   [Google Scholar]
  13. Uddin MM, Chowdhury MM, and Ahmad A (2015). The impact of rural development program on poverty alleviation: A case of Bangladesh. Global Journal of Management and Business, 15(4): 17-24.   [Google Scholar]
  14. Wooldridge JM (2002). Econometric analysis of cross section and panel data. MIT Press, Cambridge, USA.   [Google Scholar]
  15. Wordofa MG and Sassi M (2018). Impact of farmers’ training centres on household income: Evidence from propensity score matching in Eastern Ethiopia. Social Sciences, 7(1): 4. https://doi.org/10.3390/socsci7010004   [Google Scholar]
  16. Xiong ZL and Niu Y (2010). Factors affecting the income of farmers. Asian Agricultural Research, 2(5): 18-26.   [Google Scholar]