Search results

The purpose of this paper is to determine if there are positive microeconomic effects from a state‐funded loan participation program on farm productivity and investment behavior.

The authors take the approach that access to credit solves a liquidity problem. If a credit constraint exists it results in a suboptimal allocation of resources and a reduction in farm output and profitability. A two‐stage regression model approach is used to analyze farmer survey and loan application data. In the first stage, a probit regression model is used to identify the farmers who are likely to be credit rationed. In the second stage, switching regression models are used to observe the effect of credit rationing on farm productivity and on farm investment behavior.

It is found that there are liquidity effects of credit constraints for a significant share of the beginning and low‐resource farmers who participated in the state‐funded farm loan program. After controlling for various farm and farmer characteristics, the estimated productivity and investment demand equations imply that a 1 percent increase in credit received by credit constrained farmers under the state program increased their gross income by about 0.49 percent, and their investments in depreciable assets by about 0.33 percent.

This paper is the first to apply the switching regression model to a state‐funded farm loan program for the purpose of evaluating the financial impacts on farmer participants.

The purpose of this study is to explore the determinants of investment decisions of Estonian farms after the transition to market economy and accession to the European Union (EU), in the period 2006–2019.

The paper employs Estonian Farm Accountancy Data Network (FADN) individual farm-level data from the period 2006–2019, and standard and augmented accelerator investment models. Generalised methods of moments (GMM) and bias-corrected least-squares dummy variables (LSDVC) regressions were used to estimate parameters of these models.

In the considered period, farm investments were positively affected by sales growth, investment subsidies and the cash flow. Decomposition of cash flow into volatile, market income related part, and more stable, farm subsidies related part indicated that investments do not depend on market income part of cash flow. Instead, the stable part of the cash flow (farm subsidies) had a significant and positive effect on investments. This suggests that credit rationing could be present in the EU agriculture, and it depends on the farm subsidies not market income of farms.

Despite the wealth of literature on the investment behaviour of farmers, this article is the first attempt to decompose farm cash flow into stable (farm subsidies) and volatile (market income) parts to explain the role of subsidies as a part of cash flow in credit rationing.

The purpose of this paper is to examine the impact of changes in farm economic conditions and macroeconomic trends on US farm capital expenditures between 1996 and 2013.

A synthetic panel is constructed from Agricultural Resource Management Survey (ARMS) data. A dynamic system GMM regression model is estimated for farms as a whole and separately within farm typology categories. The use of farm typologies allows for comparison of the relative magnitudes of these estimates across farms by farm sales level and the operator’s primary occupation.

Changes in gross farm income levels, tax depreciation rates, and interest rates have a significant impact on crop farm investment, while changes in output prices, net cash farm income levels, tax depreciation rates, and farm specialization levels have significant impacts on livestock farm capital investment. The relative significance and magnitudes of these impacts differ within farm typologies. Significant differences include a greater responsiveness to change in tax policy variables for residential crop farms, greater responsiveness to changes in output prices and debt to asset ratios for intermediate livestock farms, and larger changes in commercial crop and livestock farm investment given equivalent changes in farm sales or the returns to investment.

These findings are of interest to agricultural economists when constructing farm investment models and employing pseudo panel methods, to those in the agricultural equipment and manufacturing sector when constructing models to manage inventories and plan for production needs across regions and over time, to those involved in drafting tax policy and evaluating the potential impacts of tax changes on agricultural investment, and for those in the agricultural lending sector when designing and executing agricultural capital lending programs.

This study uniquely identifies differences in the level of investment and the magnitude of investment responsiveness to changes in farm economic conditions and macroeconomic trends given differences in income levels and primary operator occupation. In addition, this study is one of the few which utilizes ARMS data to study farm capital investment. Utilizing ARMS data provides a rich panel data set, covering producers across many different crop production types and regions. Finally, employing pseudo panel construction methods contributes to efforts to effectively employ cross-sectional data and dynamic models to study farm behavior across time.

The purpose of this paper is to provide empirical evidence on the relationship between capital structure and technical efficiency (TE) for Italian cereal farms during the 2008–2014 period. Emphasis is given in the understanding of the relationship between the level of financial leverage for cereal farms and their production performance.

The methods employed in this research article are based on non-parametric techniques in order to derive TE estimates for a sample of Italian cereal farms based on available Farm Accountancy Data Network data to explore in depth the relationship amongst the financial exposure of the sector and the capacity to utilise an efficient and effective production technology. Furthermore, subsidies are considered in the model as a non-discretionary variable and therefore, as an input that farmers cannot directly influence within the production function. Hence, the non-discretionary Data Envelopment Analysis model is a more appropriate framework since it is not penalising farms at a lower level of Pillar I payments when benchmarked with farms that receive a higher level of payments.

The results show that significant improvements could be achieved for most of the farms in the sample by improving production and management practices. Furthermore, results provide an empirical support of the adjustment theory by showing a negative impact of debt to asset ratio to TE.

This research article provides a first insight on the evolution of the Italian cereal farms debt-TE relationship in periods where high price instability has been observed.

The literature argues on ambiguous impacts of different types of the common agricultural policy (CAP) subsidies on farm technical efficiency (TE). The purpose of this paper is to estimate and analyse the TE and the impact of the CAP subsidies on the TE of wine farms in Hungary using the farm accountancy data network data set in the period 2013–2019.

The authors use stochastic frontiers analysis (SFA) models to estimate the TE scores for the Hungarian wine farms with four wine farm-level inputs in terms of agricultural land, labour, capital and intermediate consumption. The TE scores are explained by the CAP subsidies and economic wine farm size. The different SFA models were applied with robustness tests to investigate the drivers of the TE values of wineries.

Like for Hungarian farms in general, the distribution of the wine farm structure is a dual with a greater number of smaller wine farms and a smaller number of bigger wine farms. The agricultural land, capital and intermediate consumption are significantly positively associated with the wine farm TE. With higher capital intensity wine farm TE increase. The results imply that the CAP subsidies decrease the TE of the Hungarian wine farms, whereas economic farm size increase.

To the best of the authors’ knowledge, this is one of the first specific efficiency studies on the wine sector in the Central and Eastern European region and the first one for Hungary to evaluate the TE at wine farm level and to assess the impact of CAP subsidies and economic farm size on wine farm (in)efficiency to apply production technologies and use farm resources. This study is among the first that applied the fixed-effects stochastic frontier model at the wine farm level to measure the drivers of the TE scores.

The purpose of this paper is to test the impact of the soybean rejuvenation plan and the subsidy on farmers' land allocation decisions, which may reference policy adjustment from a micro perspective.

The paper develops a multi-objective optimized programming model on farm-level, which simulated the land-use changes, as well as the resulting changes in benefits of the rational “typical farm”. The simulation scenarios include changes in subsidy policy and production efficiency, and the baseline scenario was the production status in 2018.

The results show that an increase in soybean producer subsidy will encourage farmers to allocate more land for soybean planting, which can be considered as a policy tool in promoting soybean production in China. Besides, the effect of subsidy in adjusting soybean acreage for farms is further affected by external conditions such as production technology (such as breeding technology, pesticide and fertilizer application efficiency). Meanwhile, large-scale farms show more significant land adjustments when facing changes in policies and external conditions.

The value of this paper is to simulate the effects of soybean policy and subsidy change on farmers' land-allocation decisions through a multi-objective farmer decision-making model, which provides a micro perspective to understand the implementation effect of the soybean revitalization plan.

This study aims to explore the relationship among five types of power (expert, referent, legitimate, reward and coercive power), two dimensions of cooperative behavior (specific investments and communication) and three types of alliance performance (alliance stability, income increase and cost decrease) in contract farming. By investigating the dyadic perspectives of companies and contract farmers, the authors examine how power use influences cooperative behavior, which further enhances alliance performance.

The authors construct a theoretical model grounded on resource dependence theory (RDT). Data from 202 companies and 462 farmers in China are used to test the proposed hypotheses using structural equation modeling.

The authors' results show that the five types of power play different roles in cooperative behavior. On the one hand, farmers' expert, reward and coercive power enhance the company's specific investments; farmers' expert power enhances the company's communication but farmers' coercive power harms the company's communication. Also the company's specific investments enhance communication that is positively related to alliance ability, income increase and cost decrease. On the other hand, the company's expert, referent and legitimate power enhance farmers' communication, while the company's coercive power harms farmers' communication; the company's reward and coercive power enhance farmers' specific investments. Moreover, farmers' communication is positively related to alliance ability, income increase and cost decrease, but farmers' specific investments do not significantly influence such.

This study contributes to the literature on contract farming supply chain management by examining the relationships among power use, cooperative behavior and alliance performance from the dyadic perspective of companies and farmers. These findings have practical implications for agricultural companies and farmers promoting cooperative behavior and alliance performance through appropriate power use in contract farming supply chains.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

The purposes of the study are to compare the investment behavior of farmers in Kazakhstan as a transforming country and in Germany as a Western industrialized country as well as to analyze whether the investment behavior of farmers is consistent with the normative benchmarks of the net present value approach or the real options (RO) approach.

The paper conducted an experiment with 100 Kazakhstani and 106 German farmers. The first part of the experiment describes an investment opportunity in an agricultural and in a non-agricultural treatment. The second part refers to a Holt and Laury lottery to determine farmers' risk attitude that could influence the investment behavior.

The results show that both approaches do not provide an exact prediction of the investment behavior of farmers. However, German farmers invest later than Kazakhstani farmers meaning that the investment behavior of German farmers is closer to the RO approach. This might imply that German farmers are more likely to take into account the value of flexibility when making investment decisions than Kazakhstani farmers.

Since investment behavior is country-specific, it is worth investigating whether farmers from other transforming countries would show different investment behavior compared to farmers from other Western industrialized countries. Furthermore, decision-making behavior related to investments could be different from that related to disinvestments. Therefore, it may be interesting to analyze the disinvestment decisions of farmers in transforming and Western industrialized countries.

The results show that it is not acceptable to apply the results of experiments investigating the investment behavior of entrepreneurs in a transforming country to entrepreneurs in a Western industrialized country and vice versa. Furthermore, training for farmers is needed because there is still room for improvement in order to achieve the RO benchmark. Finally, taking into account RO effects could improve the results of policy impact analysis.

This is the first experimental study comparing the investment behavior of farmers from a transforming country and from a Western industrialized country.

In self‐directed retirement plans, farmers are responsible for selecting the types of risky investments toward which the funds in their retirement plan are allocated. Furthermore, farmers do not necessarily purchase sufficient annuities with their savings upon retirement. There is little empirical evidence on the level of income sought or obtained. The purpose of this study is to analyze the long‐term investment behavior with respect to retirement planning.

Two types of data were merged for the analysis: data from the Farm Accountancy Data Network (FADN) cross‐sectional dataset, and subjective data collected by a questionnaire survey. A response rate of 39 percent was achieved enabling analysis of 440 farm records. By means of regression analysis, the impact of subjective elements, for example level of income sought, as well as farm structure and financial farm characteristics on income obtained at the time of retirement were revealed.

By decomposing the underlying decision alternatives, it was shown that the long‐term investment behavior differed substantially among farmers, but the alternative decisions made were hardly affected by structural and objective parameters. The current study reveals the dilemma faced by any farmer who has the option to invest in his own business. Off‐farm retirement investments simply provide an alternative destination for investible funds and it is a rational decision to invest these funds in their own business, thus making the farm itself their retirement “nest‐egg”. However, a discrepancy between the level of income sought and obtained was found.

There is a need to study how farmers can be encouraged to use existing options for obtaining a more comprehensive retirement plan.

In the investigated case, farmers are entitled like all residents to receive retirement benefits provided by the state, referred to as state pension. The use of three alternative retirement plans complementing the state‐sponsored retirement benefits is investigated. Perceptions about whether or not the state pension was sufficient to rely on as the sole source of income did not affect participation in a retirement plan. This stresses the importance that the contributions made and assets reserved should be regularly evaluated and reviewed (via, for example, extension or internet tools) to ensure that the available capital will meet the future income sought.

It is a challenge to identify the adequacy to attain retirement readiness by self‐directed investment plans. The strategic choices to be made are complex, while the outcome is risky. In the current study, the long‐term investment behavior with respect to retirement planning is analyzed by decomposing the underlying decision alternatives.