Agricultural Finance Review最新文献

Purpose

Farmer sentiment may be an important indicator for the agricultural sector, similar to the way that consumer sentiment is linked to the general economy. This study uses the Purdue University–CME Group Ag Economy Barometer to test the degree to which farmer sentiment is correlated with demand for United States Department of Agriculture Farm Service Agency (FSA) direct loan applications.

Design/methodology/approach

We estimate the dynamics between farmer sentiment and applications to FSA direct operating or farm ownership loans using monthly measures of farmer sentiment and loan applications from October 2015 to April 2023 and pairwise vector autoregression.

Findings

A negative relationship exists between farmer sentiment and FSA direct operating loan applications. In contrast, a positive relationship exists between farmer sentiment and FSA direct farm ownership loan applications. Together, the estimated nonzero relationships suggests that the Ag Economy Barometer may be a leading indicator for the Agricultural Economy and that FSA loan programs play a nuanced role in the agricultural credit market.

Originality/value

This study uses unique data sources to further the discussion on the link between farmer sentiment and real economic outcomes and the role of an important US Federal Government farmer lending program: FSA direct loans.

Purpose

Agricultural banks likely respond differently to economic downturns compared to nonagricultural banks. Limited previous research has examined the performance of agricultural banks under economic crisis and in the presence of banking regulations. This study aims to explore agricultural banks' responses to economic and regulation shocks relative to nonagricultural banks.

Design/methodology/approach

This study uses bank-quarter level data from 2002 to 2022 for virtually all commercial banks in the U.S. In this research, the Z-score measures the bank’s default risk, the return on assets measures bank profitability and changes in amount of farm loans indicate the wider impact on the agricultural sector. Effects of the financial crisis, Basel III reforms to banking regulation and the coronavirus (COVID-19) pandemic on these banking measures are assessed using distinct empirical frameworks. The empirical estimations use various subsamples based on bank types, bank sizes and time periods.

Findings

Economic downturns are associated with fluctuations in returns and the risk of default of commercial banks. Agricultural banks appeared to be more resilient to economic downturns than nonagricultural banks. However, Basel III regulated agricultural banks were more likely to fail amidst the pandemic-related economic shocks than the regulated non-agricultural banks.

Originality/value

This study examines the resiliency of agricultural banks during economic downturns and under postfinancial crisis regulation. This is one of the first empirical works to analyze the effectiveness of Basel III regulation across bank types and sizes considering the COVID-19 pandemic. The key finding suggests that banking regulation should consider not only size heterogeneity but also the heterogeneity in lending portfolios.

Purpose

The objective of the study is to explore explanations for the capital structure compositions of farmer cooperatives, which have a unique equity structure with allocated equity as well as unallocated equity.

Design/methodology/approach

Data came from a panel of US grain marketing and input supply cooperatives for the 2010–2020 period. The study is concerned with the proportions of debt, allocated equity and unallocated equity, which requires the application of a fractional multinomial panel model to ensure predictions fall within the observed data range (i.e. 0–1).

Findings

Larger cooperatives have relatively high debt proportions. Diversification of the product portfolio has a positive effect on the debt proportion. Profitability is associated with higher debt proportions in input supply cooperatives and higher allocated equity proportions in grain marketing cooperatives. Over time, the proportion of unallocated equity increased. Overall, some results differ across grain marketing and input supply cooperatives.

Practical implications

Increasing proportions of unallocated equity warrant a debate about the future value of ownership and governance by members of farmer cooperatives.

Originality/value

Previous empirical investigations of the capital structure compositions of cooperatives lacked a distinction between allocated and unallocated equity. Our results show that the proportions of the two equity accounts respond differently to given predictors. Furthermore, much of the prior empirical literature fails to separate cooperatives on the basis of economic activities (i.e. marketing, supply and mixed).

Purpose

Nonfamily farms are responsible for a disproportionate amount of US agriculture production. The importance of these operations to the volume of agriculture production in the United States has led researchers and policymakers to understand nonfamily farms as large commercial operations. This paper examines whether the distinction between family and nonfamily helps explain the financial outcomes of farm operations and households.

Design/methodology/approach

We test for differences in financial outcomes of the household and operations of family and nonfamily farms using an Oaxaca-Blinder decomposition. We compare these results to a decomposition of other possible typologies.

Findings

We present evidence that nonfamily farms are a heterogeneous group with a majority of small operations that are dominated by a small number of large operations. We discover that differences associated with the family-nonfamily distinction are largely explained by observable farm and operator characteristics that arise mechanically from the definition. However, we find suggestive evidence that family-nonfamily classification captures differences in economic behavior that lead to higher profitability measures to nonfamily farms. We find little evidence of any inherent structural differences between family and nonfamily farms that helps explain financial outcomes related to leverage or household finances.

Practical implications

We conclude that including nonfamily farms in official statistics of farm households may provide a more comprehensive overview of the farm sector, as our results suggest that family and nonfamily farms do not have innate differences that help explain many of their financial outcomes.

Originality/value

We incorporate previously unused data on nonfamily farm households and test the difference in mean financial outcomes between family and nonfamily farms.

Purpose

The purpose of this study is to examine how US farm sector performed in 2020, the first year of the pandemic. There were significant supply and demand shocks due to the pandemic. Furthermore, there was significant fluctuation in commodity prices and record high government payments in 2020. This study aims to examine the performance and position of US farm sector (financially) to system (and global economy) wide shocks.

Design/methodology/approach

The authors examine 2020 values for farm sector financial ratios before and after the onset of the Coronavirus (COVID-19) pandemic using the data from the United States Department of Agriculture to understand the financial position and performance of the US farm sector.

Findings

The authors find solvency ratios (which are indicators of the sector's ability to repay financial liabilities via the sale of assets) worsened in 2020 relative to pre-pandemic expectations. Efficiency ratios (which evaluate the conversion of assets into production and revenue) and liquidity ratios (which are indicators of the availability of cash to cover debt payments) showed mixed outcomes for the realized results in 2020 relative to the pre-pandemic forecasts. Four profitability ratios were stronger in 2020 relative to pre-pandemic expectations. All solvency, liquidity and profitability ratios plus 2 out of 5 efficiency ratios for 2020 were weaker than their respective average ratios obtained from 2000 to 2019 data.

Originality/value

This research is one of the first papers to use financial ratios to examine how the US farm sector performed in 2020 compared to expectations prior to the pandemic.

Purpose

Credit is an essential element in the production process in agriculture. There are two sources from which farm households can access credit: institutional sources and non-institutional or informal sources of credit. The informal sources of credit, such as moneylenders, charge exorbitant rates of interest, which further puts a financial burden on the farmers. Hence, to increase the flow of credit from institutional sources, a policy known as the interest subvention scheme (ISS) was introduced in the year 2006. This paper aims to find the effect of the ISS on the behaviour of farm households.

Design/methodology/approach

The author has used difference-in-difference analysis for estimation. In the analysis, the author has taken Madhya Pradesh as the treatment state and Andhra Pradesh as the controlled state. The author has used the Village Dynamics in South Asia (VDSA) dataset of ICRISAT for analysis. The author has used data from 2009 to 2014 for the two states.

Findings

The author has found that the difference between the average interest rate of Andhra Pradesh and Madhya Pradesh is significant for both pre-treatment and post-treatment periods and this gap has increased after the intervention period. The results suggest that the share of informal sector borrowings has reduced in the treatment group (Madhya Pradesh) as compared to the control group (Andhra Pradesh) in the post-treatment period.

Originality/value

This paper is particularly important because of the dearth of literature on the impact of this scheme in India and may shed light on the much-needed policy implications of this particular policy.