Non-farm Wage Research Articles

Income inequality of tribal households in Bangladesh: A decomposition analysis

This paper uses field survey data to examine farm and non-farm income to reduce income inequality among tribal households in Sylhet district, Bangladesh. It uses a decomposition method and a regression-based decomposition method to measure income and expenditure inequality by source of income as well as by household and family characteristics. For this, non-farm income was considered as an external transfer of total income to decompose the Gini index and as a potential substitute for farm income, taking into account household preferences. The results indicate that income differences exist between farm and non-farm income, thereby increasing income inequality. The endowment effect on household characteristics was positive and significant, directly supporting the increase in non-farm income per capita daily household expenditure. On the other hand, in terms of its components, non-farm self-employment income reduces income inequality, while non-farm wage income increases income inequality. At the 50th quantile results, an additional year of age of the household head increases the per capita expenditure of farm and non-farm households by BDT 300 to BDT 400, respectively. Moreover, the education of household heads also positively and significantly affects the per capita expenditure of non-farm households. As estimated by the 50th quantile, farm and non-farm households with graduation had higher per capita daily expenditure than household heads with primary education. Raising household education level and total farm household income to a better level, adopting farm-income enhancement programs, and enacting policies to increase alternative income opportunities that will shift income from non-agricultural to agricultural tribal households, reduce income inequality, and bring about the well-being of tribal society.

Determinants of choices of livelihood strategies among young people in Rwanda

ABSTRACT Using data from the 2016/2017 wave of the Integrated Household Living Condition Survey, this paper assesses livelihood strategies, the return to labour and drivers of choice of livelihood strategies among rural youth in Rwanda. The findings show that youth in Rwanda pursue four livelihood strategies, namely, agriculture, non-farm wages, self-employment, and diversification. Apparently, a non-farm wage is the most rewarding strategy. Age, sex, education, household size, land size, land productivity, and distance to the nearest urban centre influence the choice of livelihood strategies. The study recommends strengthening agricultural productivity-enhancing policies and the expansion of employment frontiers in the non-farm rural economy.

The effects of the Indonesian conditional cash transfer program on transition out of agriculture

This study evaluates the effect of a conditional cash transfer (CCT) on the structural transformation process in a developing economy. It uses randomized control trial (RCT) data from Indonesia’s Conditional Cash Transfer program, the Family Hope Program (PKH), to examine whether the PKH program has a significant impact on whether or not agricultural households have moved to other sectors after six years of implementation of the program. The estimates reveal modest impacts of the PKH program on diversification of livelihoods outside agriculture. The treatment group has a 28 percent higher participation in nonfarm wage employment and a 23 percent higher rate of employment in a nonfarm enterprise (NFE) compared to the control group. The heterogeneous impact analysis reveals that distance from a market is a major factor in determining the type of non-agricultural employment. Individuals in households with only a small amount of land who reside near a market are more likely to be casual workers, while individuals in households with only a small amount of land who reside far from a market are more likely to have an NFE. Interestingly, participation in a CCT program has larger effects on households residing in nonindustrial areas than in industrial areas, in terms of both nonfarm wage employment and employment in a nonfarm enterprise.

Examining rural income and employment in Bangladesh: A case of structural changes in the rural nonfarm sector in a developing country

AbstractThis study uncovers some important stylised facts about the structural changes in the rural nonfarm (RNF) economy in Bangladesh for the period 2000–2016 and identifies some broad determinants. Our work uses household‐level, secondary sources such as Household Income and Expenditure Survey, Labour Force Survey and Bangladesh Integrated Household Survey. We find that the positive relationship between landownership and rural income has become weaker in recent years, indicating the increasing role of nonland inputs in generating rural income. The share of RNF income in total rural income has increased substantially over the years. The increase in nonfarm income is largely driven by the nonfarm wage income of the richer households, indicating adverse distributional consequences. There are also indications for specialisation in nonfarm activities—the share of income from the ‘mixed’ sources of farm and nonfarm has decreased, and the ‘only nonfarm’ source has increased. Households tend to move away from agriculture and specialise in RNF occupations as the education level increases. Our results offer important insights into rural development strategies and contribute to the broader questions of the development discourse on the structural changes in developing countries.

Structural transformation and the gender pay gap in Sub-Saharan Africa.

The focus of this study is the implications of structural transformation for gender equality, specifically equal pay, in Sub-Saharan Africa. While structural transformation affects key development outcomes, including growth, poverty, and access to decent work, its effect on the gender pay gap is not clear ex-ante. Evidence on the gender pay gap in sub-Saharan Africa is limited, and often excludes rural areas and informal (self-)employment. This paper provides evidence on the extent and drivers of the gender pay gap in non-farm wage- and self-employment activities across three countries at different stages of structural transformation (Malawi, Tanzania and Nigeria). The analysis leverages nationally-representative survey data and decomposition methods, and is conducted separately among individuals residing in rural versus urban areas in each country. The results show that women earn 40 to 46 percent less than men in urban areas, which is substantially less than in high-income countries. The gender pay gap in rural areas ranges from (a statistically insignificant) 12 percent in Tanzania to 77 percent in Nigeria. In all rural areas, a major share of the gender pay gap (81 percent in Malawi, 83 percent in Tanzania and 70 percent in Nigeria) is explained by differences in workers' characteristics, including education, occupation and sector. This suggests that if rural men and women had similar characteristics, most of the gender pay gap would disappear. Country-differences are larger across urban areas, where differences in characteristics account for only 32 percent of the pay gap in Tanzania, 50 percent in Malawi and 81 percent in Nigeria. Our detailed decomposition results suggest that structural transformation does not consistently help bridge the gender pay gap. Gender-sensitive policies are required to ensure equal pay for men and women.

Effects of population spatial redistribution on vegetation greenness: A case study of Chongqing, China

With the continuous increase in urbanization and non-farm wages, many rural labor forces have transferred to urban areas, significantly changing the population distribution and affecting vegetation restoration and ecological environment improvement. This study analyzed the spatiotemporal patterns of vegetation in Chongqing from 2000 to 2018 based on the MODIS EVI dataset, and 862 samples were randomly selected to quantitatively analyze the contribution degree of population emigration to vegetation greenness by using the multivariate linear regression model under the conditions of controlling climate, topography, and policy factors. The results showed that the vegetation in Chongqing presented a significant improvement trend. Human activities played a dominant role in the vegetation restoration in Chongqing from 2000 to 2018. The contribution of population spatial redistribution to vegetation changes was 62.47%, and the contributions gradually decreased with increasing elevation, which were 73.90%, 45.02%, and 17.87% in the low, medium, and high altitude areas, respectively. Furthermore, the Grain-for-Green program significantly affected vegetation variation, and the project had the greatest ecological benefits in medium-altitude areas.

Is There an Informal Employment Penalty in Food Security? Evidence from Rural Vietnam.

In this paper, we investigate the association between informal non-farm wage employment and household food security in rural Vietnam. The data for our analyses come from a nationally representative panel dataset of 1390 rural households from Vietnam Household Living Standards Survey. We conduct multivariate regression analysis using robust quantitative tools to show that informal employment is associated with a reduction in the consumption of nutritious foods. Our analysis also shows that informal employment reduces consumption of vegetables and fruits, using both the calorie- and expenditure-based shares of food groups.

Immediate impacts of COVID-19 on female and male farmers in central Myanmar: Phone-based household survey evidence.

This article provides evidence of the immediate impacts of the first months of the COVID‐19 crisis on farming communities in central Myanmar using baseline data from January 2020 and follow‐up phone survey data from June 2020 with 1,072 women and men. Heterogeneous effects among households are observed. Fifty‐one percent of the sample households experienced income loss from various livelihood activities, and landless households were more severely affected by the crisis, mainly because of lost farm and nonfarm employment and negative impacts on rural enterprises. Women and men in these landless households were equally engaged and affected by lower wages or more difficulties in finding farm work; fewer women were engaged in nonfarm work, but almost all of them lost such nonfarm wage employment. Women in landless households are also particularly vulnerable in terms of worsened workload and increased tension in the household during COVID‐19. Landed households were also affected through lower prices, lower demand for crops, and difficulties in input access. Women and men differ in levels of stress, fear, and pessimism regarding the effects of COVID‐19. In most households, there were no signs that household task‐sharing and work balance improved, and no clear shift in intrahousehold relations was observed.

Modeling Spatiotemporal Population Changes by Integrating DMSP-OLS and NPP-VIIRS Nighttime Light Data in Chongqing, China

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing’s population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased.

The composition and determinants of rural non-farm income diversification in Nigeria

Farming has been considered as main source of income for rural households in Nigeria, despite their involvement in other income generating activities. Focusing on income derivable from farming alone may be partially responsible for the ineffective poverty reduction strategies in Nigeria. Using the National Living Standard Survey data collected by the National Bureau of Statistics, this paper investigated the composition and determinants of non-farm incomes of rural households in Nigeria. The results show that the share of farm, non-farm wage (NFW)- and self-employment (NFS) incomes in total household incomes were 24.3%, 43.0% and 23.7% respectively. Households whose heads are male (0.647), had formal education (0.522), increased the likelihood of households’ participation in NFW activities, while access to credit (-0.307) and having larger farm size (-0.221) decreased it. Access to credit (0.379); community participation (0.103); larger family size (0.193) and possession of capital assets (0.069) increased the likelihood of participation in NFS-employment activities, while having larger farm size (-0.211) decreased it. The study concludes that policy targeting poverty reduction should focus on providing enabling environment for poor households’ access to non-farm activities in the study area.

Landscapes of opportunity: patterns of young people’s engagement with the rural economy in sub-Saharan Africa

While much has been said in recent years about the importance of engaging rural youth in sub-Saharan Africa’s development, the factual data about how African youth currently engage in rural economies remain sparse. We use recent nationally representative household survey data from six countries to describe the patterns of such engagement. We find that young people participate in agriculture at similar rates to older people. However, participation in non-farm wage employment and business activity changes with age, peaking in the 30s. The likelihood of reporting no activity is greatest for people in their 20s. In more remote places, people leave school earlier and are less likely to engage in the non-farm sector, compared with people in more accessible places. We also find evidence that the non-farm economy is more diversified in relatively more accessible places, offering a larger set of options for economic engagement. We show that ‘landscapes of opportunity’ , defined by economic remoteness and agricultural potential, are an important way of assessing the choices available to young rural people. A key conclusion is that efforts to develop a ‘youth lens’ for rural development should not abandon the mainstays of rural investment strategies such as infrastructure, education, and agricultural R&D.

Youth and Adult Agrifood System Employment in Developing Regions: Rural (Peri-urban to Hinterland) vs. Urban

Using a unique dataset covering 178,794 households with 460,654 individuals spanning Africa, Asia, and Latin America, we explore employment of youths across rural zones (peri-urban, intermediate, hinterland) and urban areas. Using full-time equivalents (FTEs), we compare own-farming versus farm-wage labour, and nonfarm wage- and self-employment. Nonfarm includes: (a) agrifood system (AFS) jobs post-farmgate, in food processing, wholesale, logistics, retail, and food service; (b) non-AFS. Key findings are noted in order by Africa, Asia, and Latin America (whose youth employment rates are 61%, 39%, and 48%). (1) AFS shares in FTEs of employed rural youths are substantial (21%, 21%, and 23%). Wage employment share of AFS is lower in Africa (25%) versus Asia and Latin America (75%). (2) Own-farming in FTEs of employed rural youths are higher in Africa (51%, 19%, and 12%). The share for adults in Africa is 36%. Regressions show youths’ being in school does not reduce employment in own-farming (they are compatible), but reduces nonfarm labour. (3) Farm-wage employment shares in FTEs are small (4%, 13%, and 16%). (4) Regressions show that rural youths’ being in a peri-urban area sharply increases AFS and non-AFS employment compared with hinterland youths who depend more on own-farming.

Agricultural wages in India: trends and determinants.

Structural change in employment has been slow, particularly in agriculture, and its share in income has declined faster than employment has transitioned. This shift requires us to focus on the trends in agricultural wages. Our analysis shows that non-farm wages, the MGNREGS, irrigation facility, and rural literacy have a significant and positive effect on agricultural wages, and farm mechanization helps reduce the wage rate significantly. Creating more non-farm employment opportunities and supporting literacy programmes and irrigation will help improve farm wages, and incentivizing farm mechanization will reduce the cost of cultivation for farmers and the rural poor.

Income Diversification Among Rural Households in the Mekong River Delta, Vietnam: A Look Back at the Economic Transition Period

Based on five Living Standard Measurement Surveys (LSMSs) conducted over a thirteen year period (1993 to 2006), this paper examined patterns of income diversification in rural areas of the Mekong River Delta (MRD). In terms of quintile specific patterns, over the period 1993-2006, across all quintiles there is a sharp reduction in the time spent on farm self-employment (9.4 to 20.7 percentage points) and an increase in the share of time spent on non-farm wage employment (11.3 to 14.3 percentage points). While there are differences across quintiles, the patterns are broadly similar across expenditure groups and it does not seem that the increase in non-farm wage employment is restricted to particular groups of households. As may be expected given the changes in the activity-allocation pattern, over time, there is an increase in reliance on non-farm wage income by about 6.4 to 11.4 percentage points across quintiles. The interesting aspect is that while households in the poorest income quintiles still continue to rely heavily on agriculture related income (61.2 versus 39.9 percent for the richest quintile) they experience similar patterns of change in terms of a movement from relying on farm income to non-farm sources of income.

Farmers income and savings pattern in Benue State, Nigeria

The study analysed farmers’ income and savings pattern in Benue State. Both multi-stage random and purposive sampling procedures were employed to select 140 respondents for the study. The study employed primary data which were collected through the use of the structured questionnaire. The result showed that farm size, level of access to credit, diversification of income sources, types of investment and risks inherent in the business are the major determinants of the income level of the small scale farmers. The farmers engaged in the following farm activities, crop production, hunting, fishing, gathering of forest products, marketing of agricultural products and livestock production. Meanwhile, trading, teaching, and non-farm wage labour were the main non-farm activities they engaged in. The result equally showed that farmers adopted both formal and informal savings methods but have higher preference for the informal method as indicated by their preference for savings in rotational savings and credit Association (ESUSU) and daily contribution schemes. Educational attainment, annual income, farming experience, and farm size had positive influence on the farmers’ savings pattern. The test of the hypothesis indicated that the socio-economic characteristics of the small scale farmers have significant effects on the savings pattern adopted in the area. Consequently, the study recommended the establishment of banks in the rural area so as to increase farmers’ savings capacity in formal sector; establishment of enlightenment programme to create awareness among the rural farmers, and introduction of risk reduction policy to minimize risks associated with farming, thereby encouraging farmers to remain in farming business.Keywords: Farm activities, non-farm activities, farmers, formal and informal savings

U.S. Domestic Workers' Willingness to Accept Agricultural Field Jobs Before and During COVID-19

Worker shortages in US agricultural field jobs are widespread. Since US domestic workers typically forgo agricultural field jobs, their participation could potentially alleviate the labor shortfalls. We used an attribute-based discrete choice experiment administered before and during COVID-19 to evaluate US domestic workers' willingness to accept agricultural field jobs and determine domestic workers' valuation for non-pecuniary benefits. Results indicate that before the pandemic, domestic workers have an average reservation wage of \$23.57 per hour, which is substantially larger (\$9.58 or 68\%) than the 2019 national average wage rate of \$13.99 for field work, but similar to the national average non-farm wage rate of \$23.51 per hour. This partially explains why a minority of field workers are born in the United States. However, non-pecuniary benefits for insurance, housing, food allowance, and transportation notably increase domestic workers' willingness to accept agricultural field jobs by reducing mean reservation wage. Respondents' willingness to accept agricultural field work increased during the COVID-19 pandemic, particularly for respondents with previous field-work experience, those that prefer domestically produced food, and those who believe food is a national security issue. Respondents that lost employment or income due to the pandemic had the lowest mean WTA of \$17.16 and \$18.79 without any additional non-pecuniary benefits. The results generally suggest that the non-pecuniary benefits clearly increase domestic workers willingness to accept agricultural field jobs. Hence, it is possible to entice domestic workers to work in agricultural fields, with a combination of reasonable wages and mix of non-pecuniary benefits.

Climate Change Adaptation Strategies and Income Inequality Among Cocoa Farmers in The Ashanti Region of Ghana

Cocoa production is highly vulnerable to fluctuations in some weather parameters and efforts are now channeled at reducing farmers' vulnerability through provision of some adaptive strategies. This study analyzed the effects of climate change adaptation strategies on income inequality among Ghanaian cocoa farmers. The data were collected from cocoa farmers using multi-stage sampling method. Out of the districts where cocoa is grown in the Ashanti region, Ahafo Ano North district was randomly selected. The sampling proceeded with compilation of the names of the villages in the District where cocoa is largely grown. Although 379 cocoa farmers were interviewed with structured questionnaires, this study made use of 349 respondents with completed information on their sources of income. Data were analyzed with factor component income inequality decomposition and regression-based approaches focusing on the Gini coefficient. The analyses were carried out with Distributive Analysis Stata Package (DASP) software. The results showed that high temperature was 69.63% of the farmers in 2015, while 70.20% observed more crop pests. Cocoa farmers tried to adapt to climate change through regular spraying of cocoa (74.9%), planting of hybrid seeds (68.50%) and changing of planting time (66.10%), diversification of livelihood sources (70.60%), monitoring of weather through media houses (59.6%) and indigenous knowledge (59.3%). The results further showed high income inequality among cocoa farmers (Gini = 0.6838). Farmers indicated they were among others spraying cocoa regularly, planting of hybrid seeds and changing cocoa's planting time as means of adapting to climate change. Crop income source was inequality reducing having accounted for 55.34% of all incomes but contributed 48.37% of inequality. Other income sources that reduced inequality were livestock, non-farm wages and remittances. Farmers' incomes were significantly influenced (p<0.05) with land area, possession of formal education, access to agricultural extension services, planting of hybrid seeds, change of planting time, coping index and diversification into other crops. Among these, income inequality increased with coping index and diversification into other crops. It was concluded that provision of more effective climate adaptation methods would enhance farmers' income and reduce inequality given recent fluctuations in some weather parameters.

Effect of off-farm income on multi-dimensional poverty among rural farm households in Nigeria

PurposeThe purpose of this paper is to analyze the effect of the different components of off-farm income on multi-dimensional poverty. Furthermore, the study aims to measure multi-dimensional poverty and also identify the determinants of multi-dimensional poverty in Nigeria. The paper reveals the different contributions of the dimensions of education, health and living standard.Design/methodology/approachThe study focuses on rural farm households in Nigeria. Data are obtained from the Nigeria General Household Survey, 2013. The survey covers both urban and rural areas of the 36 states of Nigeria. Owing to the interest of this study in the rural farm household’s sub-sector, a nationally representative sample of 836 rural farm households are selected for the study after the data merging process. Rural farm households in this paper earn 50 percent of their total income from crop and livestock production. The paper employs the Multi-dimensional Poverty Index (MPI) to measure multi-dimensional poverty across the six different geographical zones of Nigeria. The probit regression model is used to estimate and analyze the effect of off-farm income components on multi-dimensional poverty and also to identify the determinants of multi-dimensional poverty.FindingsThe results of the study show that among the off-farm income components, the non-farm wage income and non-farm self-employment income have negative association with multi-dimensional poverty. Findings show that multi-dimensional poverty is high in Nigeria with deprivations in health contributing the most. Northern Regions have a higher estimate. Results reveal that sex, age, number of adults, formal credit access, access to extension services and location characteristics are key determinants of multi-dimensional poverty. The MPI for Nigeria averaged 47 percent. Across regions, deprivation in the health dimension contributes about 44 percent to multi-dimensional poverty. Deprivation in living standards contributes 40.5 percent, while deprivation in education contributes 15.5 percent to multi-dimensional poverty.Research limitations/implicationsDue to the nature of the data used, the health indicators (nutrition and child mortality) are absent but proxies are used instead. Future research could introduce gender dimensions.Practical implicationsImproving the involvement of rural farm households in non-farm self-employment sector could improve their livelihoods and prevent migration to urban centers, especially among the youths.Social implicationsImproving the quality of health, education and living standards will lead to lower poverty levels in Nigeria. Farmers can best reduce their multi-dimensional poverty by engaging in more off-farm jobs.Originality/valueThis paper provides information to policy makers on the effect of different components of income from the off-farm sector on multi-dimensional poverty alongside with the determinants of multi-dimensional poverty at a national level for the rural farm households. By using MPI, the contribution of the different dimensions used in computing the MPI across the six geographical regions within the country is revealed. This provides policy makers with more information for development purposes.

Push and (or) Pull? Drivers of Labour Force Participation in Indian Agriculture

Labour force participation rate in the Indian agricultural sector is gradually declining. This paper wants to investigate the possible causes behind it. Here both possible push and pool factors behind this decline are considered simultaneously. Initially, on the basis of 70th round NSSO data on agricultural households, it is tested whether or not marginal farmers are enjoying comparative advantage during the time of getting employment in the agricultural sector as agricultural labourer. But as ‘decline’ is a flow concept, to investigate possible reasons behind this decline, we have considered six rounds state-level NSSO data on Employment Unemployment Survey of India and its 20 major states. Applying fixed effect panel data regression technique after considering state-specific possible factors, it is found that gradual decline of per capita land holdings is the major push factor responsible for gradual decline of labour force participation rate in Indian agriculture. Apart from that, other push factors like hike of real agricultural wage rate, improvement in education level of the agricultural households and pull factor like hike of non-farm real wage, employment opportunities in construction and other non-farm activities are found significant for gradual decline of labour force participation rate in Indian agriculture.

Rural labour employment and livelihoods in tribal villages of eastern India

This study examines the changing employment and livelihood patterns of rural labour households in tribal villages of eastern India. The study is based on the high frequency panel data collected under the ICAR-ICRISAT project on Village Dynamics Studies in eastern India from 2010 to 2014. The findings revealed that the work participation rate of landless labour households had a declining trend whereas that of land owning labour households had a mixed trend in tribal villages of Jharkhand. The employment in the farm sector declined for males but increased for women. Employment in non-farm sectors registered an increase in both the genders and the magnitude of the increase was higher in the non-farm sector as compared to the farm sector. Similar trend was observed for wage rate which showed faster growth in the non-farm wage compared to the farm wage. Both the sectors witnessed an increase in the labourer’s wages during the past four years, however, the increase was much higher in the non-farm sector than the farm sector. The study also indicated that male labourers were employed at higher wages than their female counterparts in both sectors but the difference was narrowed down during last four years. A wage determinant analysis revealed that a healthy, educated, landowning adult male labour is likely to get higher wages than others. Non-farm wage employment is emerging as the most important source of income on labour households contributing 63 to 74% to their total income. The survey further revealed that income from farming constituted only 6 to 13% of the total income of labour households, but it showed increasing trend due to implementation of various mega agricultural development projects in the state.