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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 study examines credit score migration rates of farm businesses, testing whether migration probabilities differ across business cycles. Results suggest that agricultural credit ratings are more likely to improve during expansions and deteriorate during recessions. The analysis also tests whether agricultural credit ratings depend on the previous period migration trends. The findings show that credit score ratings exhibit trend reversal where upgrades (downgrades) are more likely to be followed by downgrades (upgrades).

One of the important and strategic aspects in developing entrepreneurship in the agricultural sector, especially corn commodity, is the institutional aspect. Institutions have an essential role in reducing production costs and transaction costs to improve farm profits and impact economic growth. This study aimed to map the key variables and actors in reducing transaction costs in maize farming in Dompu Regency, West Nusa Tenggara. Data collection techniques in this study used questionnaires, expert interviews, and focus group discussions (FGD). Data analysis in this study used the prospective analysis method with the MICMAC and MACTOR tools. MICMAC performs critical variable mapping analysis, while MACTOR performs strength analysis between objectives and actors. The MICMAC analysis results show that 10 key variables determine the success of the development of corn farming in Dompu Regency, West Nusa Tenggara, namely the input market, capital, land, pesticides, seeds, fertilizers, labor, pests, bonds, and output markets. MACTOR analysis shows that the relationship between actors has weak direct interactions. We need a collaborative and integrative institution that is formed at the local level through the Village Integrated Agribusiness Service Center (PLATDes) and BUMDes in the form of BKD and UDes legal entities.

Farm level data are essential to accurate setting of crop insurance premium rates, but their time series tends to be too short to allow them to be the sole data source. County level data are available in longer time series, however. The purpose of this paper is to present a methodology to make full use of the information inherent in each of these data sets.

The paper uses a novel application of statistical tools for using farm and county level yield data to generate farm level yield densities that explicitly incorporate within county yield heterogeneity while accounting for systemic risk and other spatial or intertemporal correlations among farms within the county.

The empirical analysis shows that current approaches used by the Risk Management Agency to individualize premiums for a farm result in substantial mispricing of crop insurance premiums because they do not adequately capture farm yield variability and yield correlations between farms. The new premium setting method is empirically shown to substantially reduce government subsidies for crop insurance premiums.

The paper demonstrates how to extract more information from available data when setting crop insurance premiums, which allows the government to more closely tailor premiums to the farm than do current approaches.

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.

A simulation methodology is applied to the loan loss reserve process of an agricultural lender. Weaknesses of the point‐estimate approach to estimating loan loss reserves are addressed with a “bottom‐up” model. Modeling includes consideration of the producer’s and the lender’s diversification efforts. Implementation of this model will provide the lender a better understanding of the institution’s portfolio risk, as well as the credit risk associated with each loan. This study compares the lender’s loan loss estimates to a distribution of losses with associated probabilities. The comparative results could provide the lender a basis for setting probability levels for determining the regulatory required level of loan loss reserve.

The purpose of this paper is to estimate production and scale efficiency of maize producing farms in South-Western Nigeria.

This study is based on a semi-parametric approach and uses a combination of econometrics and linear programming to build two stage Data Envelopment Analysis (DEA) model.

Model findings shows existence of production and scale inefficiencies in maize production. The study concludes that there is still room for efficiency improvements in the existence of the current maize production technology. It also finds several socio-economic variables such as, off-farm work, education, extension services and credit, which positively impact on technical efficiency of farm households.

Efficiency indicators could be used to monitor resource use efficiency in crop production by local government.

Efficiency improvements will increase maize production in the country which in turn reduce social unrest and food insecurity.

This study is one of the first which has employed DEA approach to analyze maize productivity and pioneer in using non-traditional bootstrapping approach to obtain robust efficiency scores in the case of Nigeria.

The aim of this paper is to go beyond the “What to outsource” and “To Outsource or Not” debate. Recognizing outsourcing as a fast growing reality that firms have to depend upon, the paper concerns itself with optimal management of outsourcing arrangements through the practice of “outsourcing capability”. It argues that outsourcing failure can be mitigated if organizations see outsourcing as an “ongoing activity” to be managed as opposed to treating it as a one-time opportunistic “act”.

Based on the review of existing literature and drawing upon recent instances of outsourcing successes and failures, the paper develops a conceptual framework which divides various organizational processes into four different classes. It delineates the varied aspects of “outsourcing capability” that a firm would need to use to manage these varied class of processes as and when they are outsourced.

There is no “one-size-fits-all” approach to managing outsourced processes. Different processes require emphasis on different aspect of outsourcing capability if outsourcing is to deliver the envisaged benefits.

The traditional focus in outsourcing literature has been on the core/non-core process with the recommendation to keep core processes in-house and outsource the non-core processes. This distinction can be transitory and hence detrimental in the era of hyper-competition. I argue that firms should instead focus on developing and refining aspects of “outsourcing capability” relevant to the varied class of processes that they wish/need to outsource.

The Government's aim to curb CO₂ emissions from energy production has resulted in the growth of a new environmental feature; the wind turbine. Whilst this may help tackle climate change, there is concern that the visual and aural presence of these turbines could have a negative impact on house prices. Opinion studies undertaken within the UK appear to show significant variations in attitudes towards wind farms in different locations (in particular between Scotland and southern England) and at different stages during the development process. However, to date, no research has established the actual impact on proximate house values. Therefore, the purpose of this study, sponsored by the RICS, is to develop a methodology to measure the likely impact of onshore wind farms on house prices in the UK.

This study focused on residential property surrounding two wind farms in Cornwall. Transaction data for 1,052 house sales completed between 2000 and 2004 were obtained and analysed using regression modelling and comparative sales analysis. A second study undertook an analysis of the planning objections to wind farms in this location.

The analysis of transaction data found some correlation between distance from a wind farm, and value. However, the data were insufficiently detailed to draw any sound conclusions. The analysis of planning objections revealed that 95 percent of objections came from people living outside Cornwall.

Whilst the methodology is sound, the available data were limited to house type and selling price, and therefore not sufficiently detailed to highlight any small changes in value.

The paper establishes general criteria which could be used to evaluate the potential impact of onshore wind farms on property values.

This case series describes the startup of Farm to School of Park County, an emerging nonprofit organization in the US state of Montana. Case (A) describes the community, the need, and the origins of Farm to School in Livingston, Montana. The leaders of Farm to School face a budget crisis and need to evaluate four options to decide whether, when, and how it should become an independent organization. As Case (B) begins, Farm to School has decided to enter into a fiscal sponsorship agreement with the local community foundation. The next task for the organization's leaders is recruiting founding board members. They need to decide whom to ask and how to do it. In Case (C), the board develops a strategic plan and establishes committees. However, the board members and leaders start to feel fatigue in the face of the demands of a startup organization, leading to questions about what is truly strategic and how work will get done. The Farm to School organization in Case (D) has just issued its first annual report, filled with meaningful accomplishments. The leaders of the organization begin to plan to build an organization that will outlast them and the founding board members.