Distribution Of Farm Income Research Articles

Distributive impacts of non-farm income on output and farm income of cassava farmers in Southwestern Nigeria

Non-farm income is a major source of income, along with farming for most rural households, that seems to offer a pathway out of poverty. It has gained prominence in recent times as an alternative strategy. However, it is often not clear how non-farm income can contribute to farm output and income because empirical results from existing literature remain somewhat ambiguous. Therefore, more robust research is needed to understand what conditions lead to what outcomes and to identify appropriate policy responses. We extend the previous literature in the direction of understanding more finely the potential impact of non-farm income on output and farm income distributions, applying a novel approach, IVQTEs, for the first time in this context. In this paper, we analyzed the drivers of non-farm income as an alternative strategy, and its distributive impacts on cassava farmers' output and farm income in Southwestern Nigeria. A multistage sampling procedure was employed to select 300 cassava farmers for the study. Data were analysed using the novel nehurdle estimation procedure of the double hurdle model. Our methodology of using an instrumental variable quantile treatment effect model (IVQTE) explicitly demonstrates the impact of non-farm income on farm output and income distribution at different levels. The first hurdle (Probit regression) of nehurdle results show that age, household size, years of education, years of experience, farm size, and access to credit may likely influence the decision to participate in non-farm income works; while, in the second hurdle, household size, age, years of education, farm size, gender, asset ownership, cooperative membership are the significant factors that may likely influence the amount realized from non-farm income works. Our results reveal a positive marginal impact of non-farm income at all quantiles of the conditional distribution of cassava farmers’ output and farm income, with the impact being the lowest at the lowest quantile (25th quantile) and increased across the other quantiles. In this regard, the study suggests that the creation of job opportunities outside farming will supplement on-farm works and enhance household's income. This study also suggests that measures such as education, extension services and cooperative societies, to enhance participation in non-farm income works, will spur the rural economy in Nigeria and other developing countries.

The transition of agriculture to low carbon pathways with regional distributive impacts

This study, based on agricultural sector modelling, shows how changes in food consumption and land use measures can reduce GHG emissions from Finnish agriculture, and what are the impacts on regional levels of agricultural production, land use, GHG emissions, and farm income. The results demonstrate that it is difficult to achieve a large reduction in GHG emissions from agriculture by just changing diet alone. There is a big disparity in the distribution of farm income among the main regions in Finland due to a radical decrease in the consumption of livestock products. However, land use measures alone do not create the disparity in farm income among the different regions. Combining changes in diet and land use is the most effective in mitigating GHG emissions from agriculture, but the relatively disadvantaged regions with high shares of livestock production and peatlands may experience major restructuring in agriculture and land use.

Intrahousehold distribution of sales revenue and household nutritional outcomes: What if the wives controlled the farm revenue?

AbstractIn most developing countries, crop sales represent a means of improving the nutritional status of rural households. However, the expected effect of farm income may or may not be achieved, depending on who controls it. In this study, we use panel data on rural households in Burkina Faso to analyze the effect of the wives’ share of farm revenue on nutritional outcomes. The estimates show that raising wives’ share of farm revenue increases household food demand and nutrition quality. Moreover, the effect of the wives’ share of farm revenue on household nutrition is greater than the effect of the overall income per capita, which indicates that the intrahousehold distribution of farm income affects household nutritional status. We also show that increase in food expenditure and, more specifically, reallocation of the budget toward highly nutritious foods could represent a channel through which the control of farm revenue by women improves the household dietary quality. These findings imply that facilitating women's access to productive resources, such as land and labor‐saving technologies, could be the fastest way to improve household food and nutritional security.

Does a farmland zoning program impact farm income: empirical evidence from farm households in Taiwan

Abstract Does farmland zoning affect farm income, and why? This study addresses these questions using a case study in Taiwan. We use a unique farmland-level dataset and apply the regression discontinuity design to quantify the effects of zoning on farm income. We find that the zoning program decreases farm income. The programme effects are heterogeneous, as they are more pronounced for farms in the higher percentiles of the farm income distribution. Moreover, a larger effect is found for elderly farm operators. Concerning the mechanism, we argue that the zoning program generated an optional benefit or wealth effect for eligible farms. This wealth effect then reallocates family labour to off-farm jobs. Consequently, the zoning program reduces income from farming.

Raising Farm Income in India: What Does a Simultaneous Quantile Regression Approach Tell?

This paper focuses on the contribution of farm income component of farmers’ income and traces its determinants by Situation Assessment Survey of Agricultural Households 2012–13. This study analyses the determinants of farm income by Simultaneous Quantile Regression Model (SQRM) and highlights that contribution of farm income to double farmers’ income would not be attainable without considering the variability of impact of different factors across farm income groups. The distribution of farm income is highly skewed; explanatory variables do not influence farm income in a similar manner across all quantiles, and the failure of identification of the specificity of the predictor variables is prone to be affected by generalization. Results indicate that coefficients estimated by SQRM mostly retain signs but their magnitude and significance differ across quantiles of farm income. The results further indicate that loan outstanding per hectare and machinery hiring inversely impact farm income at lower quantiles of agricultural households contrary to, insignificant or positive impacts on higher quantiles of farm income households. From the policy point of view, it may be argued that it is more important to focus on the low farm income households rather than considering the entire farm income distribution aggregately. Alternative sources of income have an immense role in the upgradation of the economic situation of the agricultural households, a frontal strategy to raise farm income will naturally have to take into account the determinants of this income of different groups of farmers, and in particular, strategies must target specific issues faced by low farm income groups.

Distributional effects of CAP liberalisation on western German farm incomes: an ex-ante analysis

We measure impacts of liberalising European agriculture on farm income distribution in western Germany. Unlike previous studies, we do not treat market income and policy support as independent income sources. We jointly apply a partial equilibrium and a programming model and find that liberalisation increases inequality in relative terms though it decreases inequality in absolute terms. In particular, we analyse the relevance of taking into account policy-induced production and market responses in an ex-ante inequality analysis. We find that although their inclusion generally does not affect the direction of distributional effects, it may have considerable impact on their magnitude

Farm Type Effects of an EU‐wide Direct Payment Harmonisation

AbstractIn this study, we analyse how three scenarios involving different levels of harmonisation of common agricultural policy (CAP) decoupled payments in the EU affect the distribution of farm income across regions and farm types. We use the farm type extension of the common agricultural policy impact (CAPRI) model, which captures farm heterogeneity across the EU. The first scenario (NUTS1) assumes uniform per‐hectare payments at the NUTS1 level. The second scenario (MS‐CONV) equalises the per‐hectare rates inside each Member State (MS) and partially harmonises the single payment scheme (SPS) across MS in line with the 2011 Commission proposal. The third scenario simulates a uniform per‐hectare payment at the EU level. Depending on the implementation of the SPS, the NUTS1 flat rate induces a substantial redistribution of payments across farm types and NUTS2 regions, particularly in regions that apply the historical SPS. The MS‐CONV and EU flat‐rate schemes have more significant impacts at the EU‐wide level. In the EU‐15, almost all farms lose payments from MS‐CONV and EU‐wide flat rates, whereas in the EU‐10, almost all farm types gain from these scenarios. Our conservative estimates indicate that the flat‐rate payments could redistribute up to €8.5 billion. Lower land rental costs partially offset the losses of farm income in the EU‐15 from payment redistribution. Land rents drop for all flat‐rate scenarios across most sectors and farm sizes in the EU‐15. In the less productive new MS, the landowners’ rental income is largely unaffected by the introduction of the flat rate.

The effect of the EU farm payments policy and its recent reform on farm income inequality

Farm direct payments (DPs) have been the main instrument of the Common Agricultural Policy (CAP) to support farm income in the EU. This paper addresses the role of direct payments granted in the context of the market and income support policies and of rural development policies in the distribution of farm income among farmers.Using the Gini coefficient and its disaggregation, this study investigates the impact of DPs on farm income inequality among a large sample of farms in Italy. The analysis is developed at a national level but also considers the three main regions of Italy and three types of farming.The DPs are very concentrated but reduce farm income inequality. However, the recent CAP reform has weakened this latter positive characteristic.The results of the analysis suggest the need to avoid a drastic reduction in the level of DPs because this is expected to increase farm income concentration and any attempt to change their distribution should be welcome if it results in a reduction of farm income concentration.

The Distributional Impact of Direct Payments on Irish Farm Incomes

The objective of this paper is to analyse the distributional effects of the different income components of Irish farm income with a Gini comparison method and by disaggregating the overall Gini coefficient of income inequality by income source. Using individual farm data for 1992 and 1996, the impact on farm income distribution of the MacSharry CAP reform is assessed. In addition, the change in the Gini coefficient between these years is decomposed into the changes in the within‐source distribution of each income stream and the share of each income stream. The favourable movement in the Gini coefficient is found to be due to the introduction of direct payments, which target less well‐off farmers. Market income remains the single largest influence on deciding the income ranking of a farm while contributing less to total income than before.

The Policy of Irrigation Water Pricing in Pakistan: Aims, Assessment and Needed Redirections

Pakistan operates the world's largest well-articulated irrigation system. Individual farms receive water from the gravity flow of a massive network of canals, distributaries and watercourses fed by the Indus River and its tributaries. In recent years public tubewells have become an additional, though somewhat limited, source of irrigation water. The canal system, which has been in operation for more than 100 years, is believed to have become too obsolete to cater for the needs of modern agriculture and is, therefore, in desperate need for rehabilitation. But resource-poor Pakistan cannot undertake the rehabilitation work on its own, and must depend on foreign loans or at least ensure full recovery of annual operation and maintenance (0 and M) expenditures [Chaudhry (1985); Duane (1975) and Hotes (1984)]. Apart from generating investment funds, the cost recovery, with higher water charges, would also lead to greater water-use efficiency and an equitable income distribution at the farm level [Chaudhry (1985) and Hotes (1984»). Can this all be accomplished by simply raising water charges? In this paper, we have attempted to answer this question. To answer the question systematically, we have divided the paper in five sections. The current state of Pakistan's irrigation system, water charges and cost recovery is discussed in Section 2. Section 3 deals with possible impact of rising water charges on cost recovery, investments, efficiency of water use and income distribution under the current system of water pricing. Section 4 presents policy alternatives that would ensure an effective cost recoyery, greater water-use efficiency and a more equitable distribution of farm income. Section 5 presents the summary and conclusions of the paper.

The Effects of Industrialization on Farm Income Distribution and Farm Numbers in New England

Affected by industrialization, agriculture in New England adapts to economic changes. Farms have become either large commercial units or small part time farms. Distributions of farm income have changed from an inverted-J distribution to a U-shaped distribution in the past three decades. Farm income grows slower and shows a larger dispersion in urban counties than in rural counties. Analyses of census data support the hypotheses (1) that farm income is lognormally distributed and (2) that industrialization has a complementary effect on agriculture while growth of urbanization essentially reduces farm numbers mostly in middle income classes.

L'évolution de la dispersion des revenus dans la région limoneuse belge

The development of the distribution of farm income in the belgian silt region - This article analyses the evolution of the ditribution of income between farmers during the period 1962-1974. Its objective is to determine the significance of this evolution, its importance and to give an explanation for it. The explanatory factors that have been retained describe the evolution of the technical production conditions and the prices policy implemented by the authorities. The statistics used are made up of accounts from a sampling of farms situated in the Belgian silt region. The distribution of income is measured by a variation coefficient. Its evolution is explained by the multiple regression method. The results of the analysis show that between the first stage (1962-63-64) and the final stage (1972-73-74) the prices policy has distinctly reduced the evolution of the distribution of incomes while the changes in the technical production conditions tended to increase it. The variation between incomes finally was reduced by 10,10 %. This proves the egalitarian role that a prices policy can play in farming.

Income Distributional Effects of the California Land Conservation Act

AbstractThe distribution of program benefits of California's use‐value assessment program has been a major issue in the political debate concerning the program's desirability. This study examines the income distributional effects of program benefits for a sample of participants in Sacramento County. The fraction of benefits received by lower income landowners was quite large when compared with their share of total income. Benefits received by lower income farmers were sufficient to cause a significant positive shift in farm income distribution, as measured by the Gini coefficient. For nonfarmers, the shift in the income distribution was slight.

Impact of New Agricultural Technology on Farm Income Distribution in West Godavari District, India

In selected regions, Indian agriculture has experienced a substantial impact of science and during the past decade. In recent years, a major focus has been the question of equity in the distribution of benefits accruing to individual farmers from development programs embracing new technology. The introduction of new technology in agriculture has many shortand long-run implications for the economy in general and for the farm sector in particular. One of the short-run effects is an increase in the incomes of those farmers who adopt new inputs and techniques. But the important aspect is the effect of adoption on the pattern of income distribution among farmers. The precise nature and exact magnitude of this effect is still unknown. This lack of knowledge is important in that it is now increasingly felt that the real farm problem lies not only in the low average incomes in agriculture but also in their unequal distribution among farmers. This study attempts to measure the farm income inequality in the West Godavari district for the years 1967-68 and 1970-71 and to isolate and measure the net influence of new farm technology on the farm income distribution in the district.' The study is restricted to an analysis of the distributional effects of new technology on farm incomes. It does not address the question of factoral distribution effects or distribution effects among consumers and producers. The Intensive Agricultural District Program district of West Godavari was selected because agricultural modernization in such districts has been attempted with relatively more vigor and over a comparatively longer period than in other districts.2 The data were taken from the Benchmark and Assessment surveys of the IADP district of West Godavari conducted by the Directorate of Economics and Statistics, Ministry of Agriculture, in 1967-68 and 1970-71 (Government of India). The former was selected because it was the year when the impact of new agricultural strategy launched in 1966-67 was having its first impact, and the latter was selected as it was the latest year for which the data were available. A stratified multiple-stage random sample of 400 farmers was selected in the whole district. The district is divided

The Economic Dimensions Of Rural Poverty

The farm sector of the United States is fast approaching its equilibrium asymptote in relation to the rest of the economy. The facts are simple and even startling to one who last looked at them five years ago. By 1967, as Table 1 shows, the one million successful American farms produced all but 15 percent of the output and wound up with a total family income averaging $14,000. Both the intermediate group (sales $2,500-10,000) and the non-commercial group (sales less than $2,500) were averaging nearly $7,000 per farm family from all sources. It is very clear that these two groups, comprising over 2 million farms are no longer primarily engaged in farming. In seven years, the intermediate group switched its income dependence from farm to non-farm income, and the non-commercial group did more than twice as well as before in non-farm income. Moreover, even the lower end of the farm income distribution is no longer in dire poverty; these families prudently substitute enough non-farm income to replace on-farm opportunities. It should also be noted that in the whole of farming, non-farm sources of income are just as important as farm sources.

Industrialization, Factor Markets, and Agricultural Development

Previous articleNext article No AccessIndustrialization, Factor Markets, and Agricultural DevelopmentWilliam H. NichollsWilliam H. Nicholls Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Journal of Political Economy Volume 69, Number 4Aug., 1961 Article DOIhttps://doi.org/10.1086/258498 Views: 11Total views on this site Citations: 19Citations are reported from Crossref Copyright 1961 The University of ChicagoPDF download Crossref reports the following articles citing this article:Arosikha Das, Ansar Khan, Pritirekha Daspattanayak, Soumendu Chatterjee, Mohammed Izhar Hassan Regional model for agricultural imbalances in West Bengal, India, Modeling Earth Systems and Environment 2, no.22 (Mar 2016).https://doi.org/10.1007/s40808-016-0107-9Mark S. Henry Modernizing a Slave Economy: The Economic Vision of the Confederate Nation by John Majewski, Journal of Regional Science 51, no.22 (Apr 2011): 419–420.https://doi.org/10.1111/j.1467-9787.2011.00727_13.xBruce L. Gardner Commercial Agriculture in Metropolitan Areas: Economics and Regulatory Issues, Agricultural and Resource Economics Review 23, no.0101 (Sep 2016): 100–109.https://doi.org/10.1017/S1068280500000460Margaret S. Andrews, Joel Chetrick Agricultural productivity in densely populated areas, Landscape and Urban Planning 16, no.44 (Dec 1988): 311–318.https://doi.org/10.1016/0169-2046(88)90004-7Mark S. Henry Agriculture's Stake in Rural Economic Development, Northeastern Journal of Agricultural and Resource Economics 15, no.22 (May 2017): 75–85.https://doi.org/10.1017/S0899367X00001069Daniel Todd Observations on the relevance of the industrial-Urban hypothesis for rural development, Geoforum 14, no.11 (Jan 1983): 45–54.https://doi.org/10.1016/0016-7185(83)90006-4A. Somwaru, T. C. Lee, S. K. Seaver The Effects of Industrialization on Farm Income Distribution and Farm Numbers in New England, Journal of the Northeastern Agricultural Economics Council 10, no.22 (May 2017): 45–52.https://doi.org/10.1017/S0163548400002958Mary E. Cawley ASPECTS OF RURAL-URBAN INTEGRATION IN WESTERN IRELAND, Irish Geography 13, no.11 (Aug 2009): 20–32.https://doi.org/10.1080/00750778009478912Dale J. Leuck An Econometric Model of Manufacturing Employment Growth in Rural Tennessee Counties from 1962 to 1976, Journal of Agricultural and Applied Economics 11, no.22 (Apr 2015): 63–67.https://doi.org/10.1017/S0081305200015041Aharon Kellerman Determinants of Rent from Agricultural Land Around Metropolitan Areas, Geographical Analysis 10, no.11 (Sep 2010): 1–12.https://doi.org/10.1111/j.1538-4632.1978.tb00641.xGavin Wright, Howard Kunreuther Cotton, corn, and risk in the nineteenth century: A reply, Explorations in Economic History 14, no.22 (Apr 1977): 183–195.https://doi.org/10.1016/0014-4983(77)90032-8Alan Gilbert A note on the incidence of development in the vicinity of a growth centre, Regional Studies 9, no.44 (Dec 1975): 325–333.https://doi.org/10.1080/09595237500185371 Bibliography, (Jan 1974): 175–188.https://doi.org/10.1016/B978-0-08-018055-7.50014-6M.J. Moseley The impact of growth centres in rural regions—I., Regional Studies 7, no.11 (Feb 2007): 57–75.https://doi.org/10.1080/09595237300185051M. J. Webber Empirical Verifiability of Classical Central Place Theory, Geographical Analysis 3, no.11 (Sep 2010): 15–28.https://doi.org/10.1111/j.1538-4632.1971.tb00345.xM.I. Logan The spatial dimensions of economic development: The case of the upper Midwest, Regional Studies 4, no.11 (May 1970): 117–125.https://doi.org/10.1080/09595237000185141F. Stirton Weaver Backwash, spread and the chilean state, Studies in Comparative International Development 5, no.1212 (Dec 1969): 241–251.https://doi.org/10.1007/BF02800614A. Grant Anderson Indian Small­Farming in Fiji: the Significance of Off­Farm Employment, Pacific Viewpoint 9, no.11 (May 1968): 12–32.https://doi.org/10.1111/apv.91002 , Journal of Rural Problems 3, no.33 (Jan 1967): 107–116.https://doi.org/10.7310/arfe1965.3.107

Multiple-Unit Operations and Gross Farm Income Distribution within the Old Cotton Belt

The Census concept of a is, for many purposes, peculiarly inappropriate for an analysis of the structure, organization, and income distribution of the agriculture of the Cotton South. The Census commonly designates and reports single units and the subunits of multiple-unit operations alike as farms, making it impossible to distinguish between them or to determine the characteristics of the larger management units of which the subunits are a part. As a result, the nature of a system of plantation agriculture, prevalent throughout the Old Cotton Belt, is almost wholly obscured. Some definitions will make the importance of these observations clearer. A multiple-unit farming operation consists of two or more subunits handled as a single farming enterprise. One of these subunits is usually the home farm, handled by the multiple-unit operator with the help of family or hired labor. The home farm contains the home of the multiple-unit operator or the headquarters where workstock and equipment are kept for the entire operation. The other subunits are usually operated by share-croppers under the supervision of the multipleunit operator, who maintains central control over sale of products, workstock, machinery and equipment, crop rotation, and purchase of supplies. The home farm includes all of the land associated with the overall operation which is not assigned to these other subunits. It is important to note that, from the standpoint of farm organization and management, the several operating subunits are a single management unit. In addition to such multiple units, there are in the South as elsewhere many single units, each of which is operated as a complete farm business by the operator, his family, or hired workers. A single unit is both an operating and a management unit. It is obvious that-because of these important differences in their organization and management-home-farm subunits, other subunits, and single units (all of them Census farms) may have distinctive characteristics of their own. But,