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The purpose of this paper is to use a linked-farm approach and a cohort approach to estimate farm entry and exit rates using the US Census of Agriculture. The number of new farms entering agriculture was re-estimated and adjusted upward since not all new and beginning farmers are known to US Department of Agriculture.

In addition to a linked-farm approach (linking farms over time), a cohort approach (farms that started operating in the same year) is used to determine exit rates conditional on the number of years a farm has been operating. Linear forecasting, moving-average forecasting, and using data from a later Census are used to re-estimate the number of new farms in their first year of operating.

Using the linked-farm approach, an average annual entry rate of 7.5 percent and exit rate of 8.5 percent is estimated for 2007 to 2012, which vary based on the farmer’s lifecycle. The cohort approach shows that exit rates are lower than 4 percent for the first 40 years of operating a farm business and then exit rates gradually increase. Revised estimates of approximately 70-80,000 new farms entering each year are calculated, which are considerably higher numbers than the 30-40,000 new farm entrants participating in the Census of Agriculture.

The linked-farm and cohort approaches are used to provide updated estimates for farm entry and exit using new Census data and to make comparisons with previous years. To the authors’ knowledge, this is the first study to provide revised estimates for new farm entrants into US agriculture.

This paper identifies factors that affect entry and exit of beginning, young and women farmers and ranchers.

The empirical framework is fixed effects regression analysis that uses county level data to evaluate how barriers to entry, access to and use of credit, local economic environment, and climate affect entry and exit of Beginning Farmers and Ranchers (BFRs). The dataset is assembled from several sources matching the Census of Agriculture years for the period of 1997–2017.

Results show that new farmers are more likely to enter in counties with more and smaller farms and with lower farm productivity, indicating that BFRs have the potential to improve the overall productivity in such counties if able to grow and succeed. The results also indicate that the high capital intensity nature of farming is an effective barrier to entry. BFRs are more likely to do better in counties where agriculture is more important to the economy and with more off-farm work opportunities. The net entry is positively associated with higher input/output price index and the use of insurance but is unaffected by government payments and farm and off-farm income. The authors observe substitutability between farming and alternative self-employment for more entrepreneurial young people. Net entry increases with availability of non-real-estate loans but decreases with real estate credit. Thus, for BFRs to acquire the assets needed to reach optimal scale, access to credit remains essential.

The authors are not aware of other work that estimates how barriers to entry and other economic factors including access to credit affect entry and exit of BFRs of various ages and young and women farmers using the Census of Agriculture data up to 2017.

Among the many things that land reform in South Africa suffers from is the lack of scientific attention paid to the willingness of commercial producers to exit or contract. This research aims to contribute to literature on this phenomenon.

The interplay between the business confidence and the opportunity costs of a farming enterprise represented in a survey sample of 450 commercial farm owners is investigated, paying special attention to owners who want to, but cannot exit.

The regression analysis suggests that both forces have a strong influence on structural change, as they depict the rather complex interplay between the two main factors that may keep farms in business, one of which is a positive business climate and the other the capital invested. A subsequent cluster analysis indicates that there is a major cluster of producers who are pessimistic about the prospects of their farming business, but who are unable or unwilling to leave their farms.

A limitation of our study is the fairly small sample size (91 exiters in the sample), so caution is advised in generalising the results. Another limitation is the overrepresentation of the Western Cape.

It is likely that the productivity of South African agriculture could improve if some of these producers caught in the “system” could leave farming to create new opportunities for entrepreneurial entrants.

The importance of a captured state has been neglected both in theoretical frameworks and in practical concepts of commercial agriculture in South Africa.

The purpose of this paper is to examine the occupational specialization in rural labor market by analyzing the nature of part-time farming in rural China and estimating the impact of off-farm experience on the individual’s persistence and exit of part-time farming as well as its heterogeneity.

Using the panel data collected in 100 villages and 2,000 households across five provinces in 2008, 2012 and 2016, this study provides insights on the nature of part-time farming in rural labor market and find the impact and mechanism of off-farm employment experience on exiting part-time farming by adopting event history analysis.

Part-time farming is a stable long-run occupation in rural labor market of China from 2008 to 2015. Off-farm employment experience generally has positive effects on long-term part-time farming and the probability of exiting part-time farming. It significantly promotes female to exit part-time farming.

Based on the two-sector model, this study builds a conceptual framework of off-farm experience and occupational specialization and sets a theoretical basis of hazard model when using event history analysis. This study contributes to identify the impact of off-farm experience on persistence and exiting part-time farming in recent years. The empirical findings support the policy of promoting off-farm employment to improve occupational specialization.

The number of farms engaged in grain production in China has been declining in recent years. Limited efforts have been devoted to examine why producers quit from grain production and how such exits affect China's grain output. Such information, however, is invaluable in understanding whether the exit from grain production should be encouraged and if so, how. The purpose of this paper is to identify the factors that influence farmers' decision to quit from grain production, with a view to drawing implications for devising policies to deal with such exits.

Both descriptive statistics and econometric techniques are used to analyse a set of unique and comprehensive farm‐level survey data to identify key factors that affect farmers' decision to quit from grain production.

Key factors that influence a farm to quit from, or stay in, grain production include: family size, the share of farming labour out of total family labour, per capita arable land, the proportion of land used for grain production, the share of family income from grains. It was also found that the level of grain prices and the sunk cost in farming, chiefly in grain production, also affect the likelihood that a household will stay or exit from grain production. Further, farmers in more economically developed regions are more likely to quit from grain production.

The paper's findings clearly indicate that farms with a larger scale of grain production and earning higher income from grain are the major contributors to China's grain production. Potential exists for China to raise its total grain output if the land from those exiting farmers is readily made available to larger producers, enabling them to further benefit from the economies of scale.

This paper examines household and community characteristics that influence the entry of rural households into non-farm entrepreneurship and investigates the various factors that influence the market exit of non-farm enterprises (NFEs).

The authors use data from three rounds (2011/12, 2013/14 and 2015/16) of the World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The authors employ panel logit and multilevel logit models to examine the probability of opening one or more enterprises and the enterprise exit rates.

Results indicate that the likelihood of starting a NFE is positively associated with primary education attainment, access to credit, experiencing idiosyncratic shocks and availability of formal financial institutions. Age, higher education attainment and rising farm input prices constrain entry into non-farm entrepreneurship. The enterprise exit rate is negatively associated with small-town residence, wealth, access to tar/gravel roads and cellphone communication.

Policymakers and administrators should strive to address the challenges that communities face in transportation, communication and financial services. Policies aimed at stabilizing prices and increasing access to mobile communication, primary education and road infrastructure could help expand the rural non-farm sector.

Previous studies primarily examined the determinants of participation in NFEs at a given time using cross-sectional data. The current study uses panel data to study the dynamics of NFE ownership by investigating households’ decisions to enter into or exit from the sector.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-09-2022-0611

In the past decade, there has been a dramatic decline in agricultural employment in Bulgaria and several reports have pointed at supply chain modernisation and poor milk quality as the main reasons for the dramatic decline in the number of farms. However, to date the policy debate is been based on ad hoc claims, while there is relatively little micro-level evidence. The purpose of this paper is to analyse the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009.

This paper analyses the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009, using a unique panel survey of 296 farm households in the North and South Central Region of Bulgaria. In order to control for sample attrition bias, the authors use a two-step Heckman model of farm survival and growth model.

The data confirms the rapid outflow of agricultural labour from dairy farming activities: 55 per cent of the farm households supplying milk to a dairy company in 2003 stopped supplying in 2009. The main reasons for quitting are ageing of the household, health problems and an increase in off-farm employment alternatives and not supply chain modernisation and milk quality standards. The institutional innovations which are associated with integration in modern supply chains, such as the provision of farm assistance programmes, have a positive impact on small farms’ growth.

The study is one of the first to use panel data to analyse the impact of standards on the survival and growth of small farms in value chains. The authors analyse the determinants of farm survival and growth in the Bulgarian dairy sector in the period 2003-2009, using panel surveys of 296 dairy farm households in the North and South Central Region of Bulgaria and panel data from interviews with dairy companies. The findings are relevant beyond the Bulgarian dairy sector as supply chain modernisation and changes in quality regulations are taken place in many other transition and developing countries.

The purpose of this paper is to investigate the impact of employer-provided health benefits (EPHBs) on labor supply decisions of documented and undocumented farm workers. By establishing a significant linkage between EPHB and farm work decisions, this study provides important implications for farm employment retention and the financial sustainability of farm businesses.

Using data from the National Agricultural Workers Survey, objective (actual) and subjective (expected) employment data are used as outcome variables analyzed under an ordered probit model, with the data pre-processed using the coarsened exact matching method to reduce endogeneity issues within the estimation.

Results confirm the influence of EPHB on farm workers’ decisions to remain employed on the farm as well as on the duration of their farm employment. Comparatively, EPHB significantly influences undocumented farm workers’ decisions on actual employment duration and subjective working expectations while documented workers seem to ascribe less importance to EPHB in their farm employment decisions.

This study provides important financial and business viability implications as the value of farm labor services retained through EPHB can translate to high opportunity losses, if ineffective. Alternative labor-saving strategies, such as mechanization, can only potentially lead to serious financial challenges for agribusiness firms, especially small-scale farm operations. This study emphasizes the need for more effective employment retention incentives for the sake of sustaining farm business viability.

This study presents empirical evidence on the important influence of EPHB on farm employment decisions, especially those made by undocumented farm workers, that have not been extensively explored in literature.

The purpose of this article is to document and evaluate patterns of nontraditional credit use among Wisconsin dairy farmers. Using a survey-based case study approach, this article analyzes farmer and farm characteristics, farmers’ utilization of credit and farmers’ perceptions of nontraditional lenders. The findings are connected to ongoing structural change in the dairy sector and economic theories of trade credit.

Data were collected using an incentivized online survey of Wisconsin dairy farmers distributed through existing university and industry networks. A total of 16 farmers completed the survey. The sample is treated as a focus group case study, and participants’ responses are examined using summary statistics and correlational analyses to describe emergent patterns in the industry.

Among survey respondents who utilize agricultural credit, nearly 80% (11 of 14) borrow from at least one nontraditional lender, and nontraditional credit comprises 17% of their total borrowing, on average. Much of this borrowing occurs through the financial arm of a vendor and is used to finance equipment or machinery purchases. Despite widespread use of nontraditional credit, no surveyed farmers preferred nontraditional lenders over traditional lenders.

This is the first study to analyze the use of nontraditional credit specifically among Wisconsin dairy farmers. Dairy farming is a capital-intensive endeavor, and recent structural change in the sector has increased surviving dairy farmers' demand for credit.

The purpose of this paper is to estimate the impact of Internal Revenue Code cost recovery provisions – Section 179 and “bonus depreciation” – on farm capital investment.

The authors construct a synthetic panel of data consisting of cohorts of similar farms based on state and production specialization using the USDA’s Agricultural Resource Management Survey for years 1996-2012. Employing panel data methods, the authors are able to control for time-invariant fixed effects, as well as the effects of past investment on current investment.

The authors estimate statistically significant investment demand elasticities with respect to the Section 179 expensing deduction of between 0.28 and 0.50. A change in bonus depreciation, on average, had little impact on capital investment.

The estimates suggest there is a modest effect of the cost recovery provisions on investment overall, but a stronger effect on farms that have more than $10,000 in gross cash farm income. There are other implications for the agricultural sector: the provisions may encourage technology adoption with its associated benefits, such as reduced cost of production and improved conservation practices. On the other hand, the policy could contribute to the growing concentration in production as large commercial farms expand their operated acreage to take advantage of increasingly efficient physical capital.

To the authors’ knowledge, this is the first research to use a nationally representative dataset to estimate to impact of Section 179 and “bonus depreciation” on farm investment. The findings provide evidence of the provisions’ impact on farm capital purchases.