Economic Assessment of the Impact of Non-Agricultural Activities on Income from Crop and Livestock Production in Household Farms: The Case of Samarkand Region
DOI:
https://doi.org/10.54536/ajaset.v9i3.6447Keywords:
Crop Production, Household Farming, Latent Class (Gaussian) Model, Livestock Farming, Non-Agricultural ActivitiesAbstract
This study investigates the impact of non-agricultural activities on the income generated from household farming in rural areas. The research is based on data from a social survey conducted among 1,843 household farms in the villages of Samarkand region. Using a Latent Class (Gaussian) model, household farms engaged in non-agricultural activities related to farming were classified into “green,” “yellow,” and “red” zones. Furthermore, to identify the relationship between household farm income and influencing variables, an ANOVA (Analysis of Variance) test was applied. To address issues of heterogeneity and multicollinearity and ensure robustness of the results, a Variance Inflation Factor (VIF) diagnostic test was conducted. In addition, a Tobit model was employed to economically assess the effect of innovations on income from household farming activities. The findings revealed that the development and/or establishment of non-agricultural activities linked to household farming in rural areas has a statistically significant impact at the 1 percent level (***p<.01). Based on the results, scientifically grounded recommendations have been developed to increase the income of household farms.
Downloads
References
Adjognon, G. S., Liverpool-Tasie, L. S. O., Benfica, R., & de la Fuente, A. (2017). Rural non-farm employment and household welfare: evidence from Malawi. World Bank Policy Research Working Paper, 8096.
Akaike, H. (2003). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723.
Amemiya, T. (1984). Tobit models: A survey. Journal of Econometrics, 24(1–2), 3–61.
Amore, M. D., & Murtinu, S. (2021). Tobit models in strategy research: Critical issues and applications. Global Strategy Journal, 11(3), 331–355.
Baghernejad, J., Sabouri, M. S., Shokati Amghani, M., & Norozi, A. (2023). Developing strategies for stabilizing the livelihood of smallholder farmers through non-farm activities: the application of the SWOT-AHP-TOWS analysis. Frontiers in Sustainable Food Systems, 7, 1199368.
Barasa, L., Kinuthia, B. K., Araar, A., Maende, S., & Mariera, F. (2023). Nonfarm entrepreneurship, crop output, and household welfare in Tanzania: An exploration of transmission channels. Agribusiness, 39(3), 762–792.
Cai, L. A. (1998). Analyzing household food expenditure patterns on trips and vacations: a Tobit model. Journal of Hospitality & Tourism Research, 22(4), 338–358.
Collins, L. M., & Lanza, S. T. (2013). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. John Wiley & Sons.
Drall, A., & Mandal, S. K. (2025). Does Non-Farm Income Raise Farm Productivity? New Evidence from India. The Journal of Development Studies, 1–22.
Galstyan, A. G., Aksyonova, L. M., Lisitsyn, A. B., Oganesyants, L. A., & Petrov, A. N. (2019). Modern approaches to storage and effective processing of agricultural products for obtaining high quality food products. Herald of the Russian Academy of Sciences, 89(2), 211–213.
Haggblade, S., Hazell, P., & Reardon, T. (2010). The rural non-farm economy: Prospects for growth and poverty reduction. World Development, 38(10), 1429–1441.
Ike, P. C. (2015). Determinants of participation in non-farm economic activities in South East Nigeria: a tobit analysis approach. Journal of Biology, Agriculture and Healthcare, 5(2), 102–108.
McCutcheon, L. A. (1987). Latent class analysis. Sage.
McGuire, S. (2013). WHO, World Food Programme, and International Fund for Agricultural Development. 2012. The State of Food Insecurity in the World 2012. Economic growth is necessary but not sufficient to accelerate reduction of hunger and malnutrition. Rome, FAO. Advances in Nutrition, 4(1), 126–127.
Michailidis, A., & Lazaridou, D. (2020). Non-farm employment: A key challenge to achieve zero hunger. In Zero hunger (pp. 1–11). Springer.
Mittenzwei, K., Berglann, H., Hoveid, Ø., Matthews, A., & Storm, H. (2024). Decomposing household income differences between farmers and non-farmers: Empirical evidence from Norway. Journal of Agricultural Economics, 75(2), 672–687.
Qin, X., Li, Y., Lu, Z., & Pan, W. (2020). What makes better village economic development in traditional agricultural areas of China? Evidence from 338 villages. Habitat International, 106, 102286.
Ramaswamy, V., DeSarbo, W. S., Reibstein, D. J., & Robinson, W. T. (1993). An empirical pooling approach for estimating marketing mix elasticities with PIMS data. Marketing Science, 12(1), 103–124.
Saydullaeva, F., Pardaev, K., Muratov, S., & Tursunkulov, G. (2022). Empirical analysis of smallholder production effect to dietary diversity. Economic Science For Rural Development 2022, 555.
Schwarz, G. (1978). Estimating the dimension of a model, The Annals of Statistics, 6(2), 461–464. http://dx.doi.org/10.1214/Aos/1176344136.
Seogo, W. (2022). Preventing households from food insecurity in rural Burkina Faso: Does nonfarm income matter? Agribusiness, 38(4), 1032–1047.



