Migration, remittances and agricultural farm households’ income: evidence from Punjab, India

Improving farming activity competence of farm households has recently been considered one of the most important factors for increasing farm income. However, few studies examine the relationship between farm income and farming activity competence of farm households directly due to the lack of an available dataset. In this study, we examine the relationship between farm household technical·managerial competence and farm household income based on the nearly 30,000 farm households consulting data gathered by the Rural Development Administration, RDA. The major findings of this study are as follows: firstly, statistically significant differences in agricultural and farm household income exist between farm households categorized by farm activity competence levels in terms of technique and management. Secondly, a technically and managerially competent farm household group (high-rank farm household) has 2.2 times higher agricultural income and 1.9 times higher farm household income than the technically and managerially incompetent farm household group (low-rank farm household). Thirdly, farm household technical-managerial competence is one of the major factors that affect agricultural and farm household income. Regarding technical competence, agricultural income and farm household income increased by approximately 1,390,000 won and 1,530,000 won, respectively, as technical points increased by one point. However, with respect to managerial competence, agricultural income and farm household income increased by approximately 1,320,000 won and 2,070,000 won, respectively, as managerial points increased by one point.

I would further like to thank my second supervisor Prof. Dr. Sebastian Lakner. Throughout my master's thesis, you guided my academic path and encouraged me to apply and start my Ph.D. Without your encouragement, helpfulness, and continued interest in my work, I could have never completed this project. Thank you for always showing me the bright side of the coin. I also thank Prof. Dr. Claudia Neu, my third supervisor. Your feedback from discussing my work during the doctoral seminar and beyond was valuable and contributed to refining my research ideas and papers. In addition, I would like to extend my gratitude to Dr. Stefan Schüler for his ideas and feedback on my paper. I also thank Dr. Marius Michels for reviewing and discussing my second paper. Finally, I owe special thanks to Antje Wagener for supporting me in all administration matters, refreshing office chats, and everyday cordialities. Getting this far would have been a lot harder without the collaboration and support from my colleagues in the department, especially those with whom I shared an office or whose office I visited so often. Jost and Johanna, we started as colleagues and ended up being friends. Thank you, Jost, for the inspiring discussions, enriching cooperation, conference trip to Tänikon, and companionship. Thank you, Johanna, for your emotional support, for giving me perspective, and for all the good times during and after office hours. It's been a pleasure and joy to go on this journey with you both. On that note, I am incredibly thankful to Jasper for creating and filling our 'weekend island' with love and laughter. Thank you so much for your patience, support, and the fantastic food that kept me alive and made me smile, especially when things got tough. I thank my flat maids, especially Thorsten, for all the emotional support and friendship along the way. Thank you 'Kleine Stephie' for all the motivational cards and calls from afar. Lastly, I want to thank my parents for not giving up despite the long, exhausting years of illness, giving me hope and strength. "Health is not everything, but without health, everything is nothing."

This study uses U.S. farm household survey data to examine how participation in the Conservation Reserve Program (CRP) affects farm household economic well-being. Further, the study also examines the effects of CRP participation on farm household consumption, income, and imputed savings. In contrast to previous studies that assume the relationships are homogenous across the population, quantile regression is used to investigate the association between CRP participation across the entire distribution of farm household consumption and income. Empirical findings suggest that the effect of CRP participation on household economic well-being differs across the income and consumption distribution. For households in the lower percentiles of the distribution, the CRP participation is associated with an increase in household consumption, but a decrease in farm household income and savings. In contrast, farm households at the median and higher income and consumption quantiles, participation in CRP is associated with lower levels of household consumption and income, but with higher levels of savings.

This study uses U.S. farm household survey data to examine how participation in the Conservation Reserve Program (CRP) affects farm household economic well‐being. Further, the study also examines the effects of CRP participation on farm household consumption, income, and imputed savings. In contrast to previous studies that assume the relationships are homogenous across the population, quantile regression is used to investigate the association between CRP participation across the entire distribution of farm household consumption and income. Empirical findings suggest that the effect of CRP participation on household economic well‐being differs across the income and consumption distribution. For households in the lower percentiles of the distribution, the CRP participation is associated with an increase in household consumption, but a decrease in farm household income and savings. In contrast, farm households at the median and higher income and consumption quantiles, participation in CRP is associated with lower levels of household consumption and income, but with higher levels of savings.

PurposeThe determinants of income of rural and urban farm households, with emphasis on the role of off-farm employment by farm household members and of farm size, are examined using data from the 2016 Agricultural Resource Management Survey (ARMS) and quantile regression procedure. The implemented quantile regression technique is extended to allow for the decomposition of the income gap between the two groups of farm households. Findings indicate, regardless of the location of the farm, a positive and significant impact of a previous year's participation in off-farm work by household members on the distribution of current household income. Having operated a larger-sized farm in the previous year is shown with a similar effect in the upper range of the income distribution for urban households and with a comparable impact but across the whole income distribution for rural farm households.Design/methodology/approachData from the 2016 ARMS are used in conjunction with quantile regression in order for decomposition of the income gap between the two groups of farm households.FindingsFindings show that urban farm households who in a previous year have participated in off-farm work and operated larger-sized farms tend to earn higher incomes. Results further indicate higher rates of return to education for “urban” farm households in comparison to “rural” farm households, particularly for those with a college education and beyond who are at the lower portion of the income distribution.Research limitations/implicationsTo the extent that the ARMS is an annual cross-sectional data, the temporal impacts of factors that potentially may influence the incomes of farm households in urban and rural areas cannot be measured.Practical implicationsFindings from this research indirectly support previous published research where higher earnings by urban US population were documented in comparison to rural population and where earnings tend to rise as a result of participation in off-farm work and in expanding the size of the farming operation; this is in addition to the procurement of higher education.Social implicationsThe results of a higher rate of return to education for “urban” farm households in comparison to “rural” farm households have important policy implications for policymakers.Originality/valueThis is the first paper in the agricultural economic literature that implements a method of assessing the rural–urban divide across all of the quantiles of income distribution.

The overarching consensus in the applied migration literature is that international migration is typically used to transition out of agricultural sector by rural households in transition economies. In this paper, using data on rural Albanian households, we examine whether international migration of some household members affects the household’s nonfarm activity choices and earnings generated from these activities. In addition, we test whether remittance income received from migrant household members have an indirect effect on households’ agricultural production. We find no apparent relationship between nonfarm activity choice and the number of international migrants in the farm household. However, we find that remittance income is positively and significantly related to households’ propensity to reallocate farm labor to nonfarm self-employment activities, resulting in higher income from non-farm self-employment. In addition, remittance income affects farm income in a positive and significant way. This suggests that previous studies likely underestimated the overall impact of international migration on agricultural production in rural Albania, as they usually ignored the additional remittance income effect. Overall, our empirical findings support the basic tenets of rural income diversification, where the farm household has a diversified portfolio of income-generating activities, in addition to farming. The results suggest that international migration facilitates income diversification among Albanian farm households rather than their exit out of agriculture.

Income increase is an important way to achieve comprehensive human development and to escape from poverty, and the growing aging problem in rural China poses a challenge to farm household income increase. In order to gain a deeper understanding of the impact of China’s rural old-age burden on farm household income, this paper empirically examines the impact and mechanism of household old-age burden on farm household income based on the data from the 2023 micro-farm field survey of China’s Henan Province, utilizing linear regression modeling and mediation effect modeling, filling the research gaps in the related fields. The results of the study found that, firstly, family old-age burden has a significant impact on the income of farm households, and that the heavier the family old-age burden, the lower the total income of farm households. Secondly, from the results of the heterogeneity of the impact, the poorer the health condition, the greater the negative impact of family old-age burden on farm household income. Old-age burden has a greater impact on high-income farm households than on low-income farm households, and old-age burden has a significant impact on the income of part-time farm households, while the impact is not significant on purely farm and non-farm households. Thirdly, the heavier the household old-age burden, the more unfavorable it is to the non-farm employment of farm households, thus affecting the income capacity of farm households. Finally, corresponding countermeasures and recommendations are put forward in three areas, namely, the continuous improvement of the social old-age security system, the realization of the function of the social old-age mechanism as an old-age pocket for key special groups, and the improvement of the social flexible employment mechanism.

East Luwu Regency is one of the largest pepper centers in South Sulawesi Province. This study aims to: (1) know the production pepper farming, (2) analyze farmers’ income from pepper farming, (3) analyze the household income of pepper farmers and (4) analyze the level of welfare of pepper farmer households in Bantilang Village, Towuti District, East Luwu Regency. This research was conducted in Bantilang Village, Towuti District, East Luwu Regency from July to August 2021. The sample is 42 pepper farmers. The data was analysed using descriptive quantitative method. The results showed that (1) the level of pepper production in Bantilang Village, Towuti District, East Luwu Regency was quite high, that is 938.39 Kg/Ha. The income of pepper farmers is Rp. 4,353,953/month with the R/C-Ratio of 4.39, (2) household income of pepper farmers is relatively high, where their incomes are genterated from pepper farming, other farming, outside farming and income of household members, with the average household income of pepper farmers is Rp. 13,544,548/month, (3) the welfare of farmer households is high, where as many as 41 farmers are included in the prosperous category (97.62%).

<p>ABSTRACT</p><p>This study aims to analyze the broad influence corn field to the household income of corn farmers in Grobogan district, analyze the effect of educational level the head of family to the household income of corn farmers in Grobogan district, analyze the effect of the number of family members to the household income of corn farmers in Grobogan district, analyze the effect the food and non food expenditure to the household income of corn farmers in Grobogan district. Locations were taken intentionally, in Grobogan district, because Grobogan district has the widest corn harvested area in the province of Central Java. Total population that taken in this study is 150 household of corn farmers who scattered in several regions in Grobogan. The sample is a fraction of the number and characteristics which is owned by the population. Samples were corn farmers, the number of samples taken is 60 corn farmers in Grobogan. The results showed that land area of corn gave positive effect on household income of corn farmers in Grobogan, the educational level of husband’s household insignificant, the number of household members has a positive influence on the level of household income, food expenditure had a negative but not significant to household income and non-food expenditures have a significant negative effect on the level of household income. The result of the calculation of the proportion of food consumption and the proportion of non-food consumption showed that the average total expenditure for average food expenditure per farmer per month amounted Rp. 1.023.611,00 while the non-food expenditure amounted Rp. 2.619.552,00.</p>

This research was conducted (1) to understand the labor supply on the paddy farming (2) to estimate the factors affecting labor supply of farm household on the paddy farming (3) to understand source of farm household income and the contribution of farm household income. The primary method for this research is descriptive analysis. The research located in Margokaton Village, Sayegan Subdistrict, Sleman District were determined simple random sampling, there were 30 farm household of paddy farmers. The data was analyzed by paired sample t-test and multiple linier regression analysis by Ordinary Least Sugar(OLS). The result showed that (1) labor supply on paddy farming was 103,44 HKO/year which consists of family labor was 85,81 HKO/year and non family labor was 17,63 HKO/year, (2) labor supply of farm household on the paddy farming was affected positively by field area and technical irrigation (3) sources of farm household income were from farm income and non farm income meanwhile the contribution of farm income and non farm income to farm household income were 45,64% and 54,36% of. The contribution of paddy farming is 19,60% to farm household income.

Understanding dynamics behind farm household income provides insights to foresee future income change among farm households. To better understand the change in farm household income, this study decomposes farm household income by age effects, cohort(generation) effects, and year effects. Constructing pseudo panel by birth year of household heads, this study investigates which factor affects farm household income. The results show that age effects are pronounced in farm household income, agricultural income, and non-agricultural income. Farm household income moves drawing inverse U shape. Moreover, cohort effects show that younger generations have earned more income than older generation, which has been resulted from economic growth. It is also noteworthy that transfer from public sector increases by age and younger generations receive more benefits from government than older generations while transfer from family and friends changes in different directions. This implies that the role of government is getting bigger in safety net among farm households and welfare expenditure is likely to explosively increase as farm population rapidly gets old.

This study examines the effect of land area and income sources of agricultural households on their income in the context of reducing poverty in the agricultural sector. This study uses a quantitative approach and multiple regression methods as an analytical tool with data from the Agricultural Business Household Income Survey which is part of the 2013 Agricultural Census of West Sumatra Province. The data used in this study is cross-sectional data with total agricultural household income as the dependent variable and the amount of land owned by agricultural households, the area of ​​land controlled and cultivated by agricultural households, the percentage of agricultural household income from agricultural sector businesses, the percentage of agricultural household income from non-agricultural businesses, the percentage of other agricultural household income , the percentage of agricultural household income from wages in the agricultural sector, and the percentage of agricultural household income non-agricultural wage income. The results showed that the variable area of ​​land owned and the area of ​​land controlled and cultivated by agricultural households had a positive effect on their total income. Other variables that have a positive effect on total agricultural household income are the percentage of income from non-agricultural businesses and the percentage of non-agricultural wage income. On the other hand, the percentage of agricultural household income from agricultural sector businesses and the percentage of agricultural household income from wages in the agricultural sector have a negative effect on their total income. The results of this study suggest the need for redistribution of land to land-poor agricultural households and encourage them to diversify their business outside the agricultural sector but still based on agricultural products.

This study aims to analyze effects of adoption of motorized water pump on household farm income of smallholder farmers in Mirab Abaya and Arba Minch Zuria Woreda. The total sample size (n=196) was purposively selected from two Woredas and five Kebeles. Descriptive analysis, inferential analysis and Heckman two-stage mode were employed for data analysis. The ordinary least squares (OLS) model result revealed that among the 12 explanatory variables included in the model, four had significant effect on the household annual gross farm income. A unit increase in irrigated land of a household increases annual gross farm income of the households by Birr 6620.9 at 5% significance level. Adoption of motorized water pump has a positive effect on household annual gross farm income. The annual gross farm income of adopter households was higher by Birr 18555.35 than non-adopter households. Market distance and market information is found to influence income and hence well-being, significantly. The results indicated that a 1 km increase in distance of commodity supply market decreases annual gross farm income of farm households by Birr 3992.8 at 1% significance level. Male household heads had obtained significantly higher income compared to female household heads. Key words: Water pump, farm income, T-test, Chi-square, ordinary least squares (OLS), Heckman two-stage.

One of the vegetable crops that have high economic value and is always needed is red chili. Red chili farming in Sawang District is an activity of farmer households in obtaining income to meet household consumption needs in the form of food and non-food. The ability of farmers to obtain income that is used for household consumption will determine the level of welfare of red chili farmers' households. The purpose of this study was to analyze the household income and expenditure of red chili farmers in Sawang District, North Aceh Regency with a total sample of 40 families. Data were analyzed by quantitative descriptive method. The results showed that the household income of farmers came from agricultural and non-agricultural income with the total income of all respondents amounting to 62,523,981.25 IDR /production process or 10,420,663.54 IDR/month. The income is used to meet food and non-food needs in the amount of 3,579,227 IDR/month. Meanwhile, the welfare level of farmer households is low based on the income structure and expenditure structure.

Relatively little is known about the association between Internet use and environmentally‐friendly agricultural innovation adoption. To fill this void, this study examines the impact of Internet use on the adoption of sustainable agricultural practices (SAPs) and their heterogeneous effects on farm income and household income. Unlike previous studies that analyse the dichotomous decision of agricultural innovation adoption, this study captures the number of SAPs adopted. We apply both endogenous‐treatment Poisson regression model and unconditional quantile regression model to analyse unique farm‐level data collected from China. The empirical results show that Internet use exerts a positive and statistically significant impact on the number of SAPs adopted, and the joint effects of Internet use and SAP adoption on farm income and household income are heterogeneous. In particular, we show that Internet use has a larger impact at the upper tail of household income but it has no significant impact on farm income. SAP adoption is negatively associated with farm income and household income across the selected quantiles.