Pub Date : 2022-07-25DOI: 10.1108/afr-03-2022-0034
M. Ortez, N. Widmar, Mindy L. Mallory, C. Wolf, C. Bir
PurposeThis article quantifies public sentiment for dairy products using online media and investigates potential relationships between online media, both volume and sentiment, and future prices of Class III milk.Design/methodology/approachNetbase, an online media listening platform, was used to quantify US generated online media sentiment and number of mentions regarding dairy products. Granger-causality tests and Impulse Response Functions (IRFs) were used to study relationships between online media derived data and dairy futures prices.FindingsMilk and cheese have more mentions in online media than yogurt and ice cream. Online media net sentiment around milk was the lowest of the dairy products studied. Granger-causality tests showed that Class III milk price Granger-causes net sentiment of dairy as a whole and of fluid milk. Price additionally Granger-causes mentions of milk, ice cream and yogurt. Notably, milk and ice cream mentions Granger-cause the Class III milk price. IRF's reveals that increases in mentions have a positive, albeit small, effect on the Class III milk price that is statistically significant for ice cream, but not for milk. IRF's directionality of the relationship from price to online media derived data was mixed.Originality/valueThis is the first time that relationships between online media -volume and sentiment- and futures prices of an agricultural commodity are researched. Exploration of futures markets alongside online media advances the use of online media to glean insights in financial, along with food and agricultural markets.
{"title":"Online media in dairy markets: a US dairy futures market study","authors":"M. Ortez, N. Widmar, Mindy L. Mallory, C. Wolf, C. Bir","doi":"10.1108/afr-03-2022-0034","DOIUrl":"https://doi.org/10.1108/afr-03-2022-0034","url":null,"abstract":"PurposeThis article quantifies public sentiment for dairy products using online media and investigates potential relationships between online media, both volume and sentiment, and future prices of Class III milk.Design/methodology/approachNetbase, an online media listening platform, was used to quantify US generated online media sentiment and number of mentions regarding dairy products. Granger-causality tests and Impulse Response Functions (IRFs) were used to study relationships between online media derived data and dairy futures prices.FindingsMilk and cheese have more mentions in online media than yogurt and ice cream. Online media net sentiment around milk was the lowest of the dairy products studied. Granger-causality tests showed that Class III milk price Granger-causes net sentiment of dairy as a whole and of fluid milk. Price additionally Granger-causes mentions of milk, ice cream and yogurt. Notably, milk and ice cream mentions Granger-cause the Class III milk price. IRF's reveals that increases in mentions have a positive, albeit small, effect on the Class III milk price that is statistically significant for ice cream, but not for milk. IRF's directionality of the relationship from price to online media derived data was mixed.Originality/valueThis is the first time that relationships between online media -volume and sentiment- and futures prices of an agricultural commodity are researched. Exploration of futures markets alongside online media advances the use of online media to glean insights in financial, along with food and agricultural markets.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46570662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-12DOI: 10.1108/afr-02-2022-0025
Kenneth Hsien-Yung Chung, P. Adriaens
PurposeThis paper aims to quantify the impact of environmental contamination on farmland valuation. It applies data fusion and hedonic pricing approaches to quantify the contribution of nitrogen and phosphorus loading on farmland sales transactions. It further suggests approaches to improve internalization of environmental cost in valuation approaches using shadow pricing. The work informs the field of environmental, social and governance (ESG) investing by fusing environmental data with financial transactions.Design/methodology/approachThis paper is an empirical study implementing hedonic pricing of farmland in the Lake Huron major drainage area. Data sources and fusion were derived from AcreValue, the United States Department of Agriculture's Gridded Soil Survey Geographic database (gSSURGO) and the United States Geological Survey's Spatially Referenced Regression on Watershed Attributes database (SPARROW).FindingsThe results suggest that environmental contamination has statistically significant positive determination power on farmland prices such that prices increase with contamination. Conventional metrics such as percentage of cultivated land in the parcel, root zone depth, whether the parcel is designated by the Natural Resource Conservation Service as prime farmland, and the size of the farmland parcel contribution to farmland value as well. The results indicate that environmental impacts are not accurately accounted for in farmland transactions.Research limitations/implicationsThis paper points to inaccurate valuation of environmental contamination in farmland value. While geocoding allowed for positioning of farmland sales transactions relative to modeled areas of contaminant loading in the Lake Huron drainage area, the interpretation indicates that value is driven by cultivation. Hence, generalization to other areas needs a cautious approach. Empirical testing across locations and drainage areas with diverse farmland features will serve to verify the modeled data used in this study.Practical implicationsThe lack of integration of externalities in land valuation has implications on lending and disclosure practices, as financial service providers increasingly seek to account for ESG risk on their loan books and broader investment portfolios. The impact of farmland accounting practices for contamination such as shadow pricing may impact land valuation based on future cash flows, and may serve to inform sustainability-linked lending practices to farm operations.Originality/valueThis is the first paper to fuse data from AcreValue, gSSURGO and SPARROW to discover the explanatory power of nutrient contamination in farmland value in the Lake Huron major drainage area.
{"title":"Financial exposure to environmental liabilities in Lake Huron drainage area farmlands: a GIS and hedonic pricing approach","authors":"Kenneth Hsien-Yung Chung, P. Adriaens","doi":"10.1108/afr-02-2022-0025","DOIUrl":"https://doi.org/10.1108/afr-02-2022-0025","url":null,"abstract":"PurposeThis paper aims to quantify the impact of environmental contamination on farmland valuation. It applies data fusion and hedonic pricing approaches to quantify the contribution of nitrogen and phosphorus loading on farmland sales transactions. It further suggests approaches to improve internalization of environmental cost in valuation approaches using shadow pricing. The work informs the field of environmental, social and governance (ESG) investing by fusing environmental data with financial transactions.Design/methodology/approachThis paper is an empirical study implementing hedonic pricing of farmland in the Lake Huron major drainage area. Data sources and fusion were derived from AcreValue, the United States Department of Agriculture's Gridded Soil Survey Geographic database (gSSURGO) and the United States Geological Survey's Spatially Referenced Regression on Watershed Attributes database (SPARROW).FindingsThe results suggest that environmental contamination has statistically significant positive determination power on farmland prices such that prices increase with contamination. Conventional metrics such as percentage of cultivated land in the parcel, root zone depth, whether the parcel is designated by the Natural Resource Conservation Service as prime farmland, and the size of the farmland parcel contribution to farmland value as well. The results indicate that environmental impacts are not accurately accounted for in farmland transactions.Research limitations/implicationsThis paper points to inaccurate valuation of environmental contamination in farmland value. While geocoding allowed for positioning of farmland sales transactions relative to modeled areas of contaminant loading in the Lake Huron drainage area, the interpretation indicates that value is driven by cultivation. Hence, generalization to other areas needs a cautious approach. Empirical testing across locations and drainage areas with diverse farmland features will serve to verify the modeled data used in this study.Practical implicationsThe lack of integration of externalities in land valuation has implications on lending and disclosure practices, as financial service providers increasingly seek to account for ESG risk on their loan books and broader investment portfolios. The impact of farmland accounting practices for contamination such as shadow pricing may impact land valuation based on future cash flows, and may serve to inform sustainability-linked lending practices to farm operations.Originality/valueThis is the first paper to fuse data from AcreValue, gSSURGO and SPARROW to discover the explanatory power of nutrient contamination in farmland value in the Lake Huron major drainage area.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43654743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-21DOI: 10.1108/afr-01-2022-0009
S. Maji, A. Laha
PurposeThe article makes a modest attempt to explore the level of financial literacy (FL) amongst the farmers in India. An effort was also made to unearth the factors affecting such FL.Design/methodology/approachThe study used secondary data on 11,030 farmers across various regions of India from the Financial Inclusion Insight Survey, 2017. Standard and Poor Global FL questions were used to measure the level of FL amongst the respondents. In addition to the appropriate statistical tools and techniques, the censored tobit regression model and generalized structural equation model were applied to explore the determinants of FL of the Indian farmers.FindingsThe outcome of the study indicated that the majority of Indian farmers are financially illiterate. The average FL score obtained by the sample farmers was found to be only 33%. The results of the study signaled significant regional variation in FL amongst the farmers across India. Apart from the regional variation in FL, farmer type, state-specific agricultural productivity, gender, marital status, age, educational attainment and financial inclusion were found to be the major determinants of the FL amongst the farmers.Originality/valueEvaluation of FL amongst farmers is scanty in the literature in developed nations and especially in the context of emerging economies, like India. The authors tried to fill this gap by exploring FL and its determinants amongst Indian farmers. In addition to this, the study for the first time used a comprehensive and rich dataset of 11,030 Indian farmers while exploring the level of FL and its determinants.
{"title":"Financial literacy and its antecedents amongst the farmers: evidence from India","authors":"S. Maji, A. Laha","doi":"10.1108/afr-01-2022-0009","DOIUrl":"https://doi.org/10.1108/afr-01-2022-0009","url":null,"abstract":"PurposeThe article makes a modest attempt to explore the level of financial literacy (FL) amongst the farmers in India. An effort was also made to unearth the factors affecting such FL.Design/methodology/approachThe study used secondary data on 11,030 farmers across various regions of India from the Financial Inclusion Insight Survey, 2017. Standard and Poor Global FL questions were used to measure the level of FL amongst the respondents. In addition to the appropriate statistical tools and techniques, the censored tobit regression model and generalized structural equation model were applied to explore the determinants of FL of the Indian farmers.FindingsThe outcome of the study indicated that the majority of Indian farmers are financially illiterate. The average FL score obtained by the sample farmers was found to be only 33%. The results of the study signaled significant regional variation in FL amongst the farmers across India. Apart from the regional variation in FL, farmer type, state-specific agricultural productivity, gender, marital status, age, educational attainment and financial inclusion were found to be the major determinants of the FL amongst the farmers.Originality/valueEvaluation of FL amongst farmers is scanty in the literature in developed nations and especially in the context of emerging economies, like India. The authors tried to fill this gap by exploring FL and its determinants amongst Indian farmers. In addition to this, the study for the first time used a comprehensive and rich dataset of 11,030 Indian farmers while exploring the level of FL and its determinants.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49146141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-17DOI: 10.1108/afr-01-2022-0006
S. Adhikari, A. Khanal
PurposeThe purpose of this paper is to present theoretical synopsis of risk balancing hypothesis (RBH) and estimate empirical models examining debt, savings and debt-to-equity use decisions of small US farms.Design/methodology/approachThe authors use primary survey data from Tennessee and generalized linear models (GLMs).FindingsThe study’s findings suggest that the perceived higher business risk (BR) significantly increases the extent of debt use, savings use and debt-to-equity of small farmers. Moreover, results indicate that factors such as age and education of the operator, family involvement, incomes, land acreage, adoption of alternative on-farm enterprises and farmers' continuation plan significantly influence the financing decisions of small farm operations.Originality/valueThe authors investigated an essential empirical question examining the risk balancing behavior of small US farm operations. While risk balancing has been a theme of several studies, none of the previous studies have specifically looked at the behavior in the context of small US farms. The theoretical synopsis and empirical findings contribute to the literature of risk balancing, debt use and savings use decisions and the policy discussions on farm financial and support strategies.
{"title":"Business risk, financial risk and savings: does perceived higher business risk induce savings among small agricultural operations in the USA?","authors":"S. Adhikari, A. Khanal","doi":"10.1108/afr-01-2022-0006","DOIUrl":"https://doi.org/10.1108/afr-01-2022-0006","url":null,"abstract":"PurposeThe purpose of this paper is to present theoretical synopsis of risk balancing hypothesis (RBH) and estimate empirical models examining debt, savings and debt-to-equity use decisions of small US farms.Design/methodology/approachThe authors use primary survey data from Tennessee and generalized linear models (GLMs).FindingsThe study’s findings suggest that the perceived higher business risk (BR) significantly increases the extent of debt use, savings use and debt-to-equity of small farmers. Moreover, results indicate that factors such as age and education of the operator, family involvement, incomes, land acreage, adoption of alternative on-farm enterprises and farmers' continuation plan significantly influence the financing decisions of small farm operations.Originality/valueThe authors investigated an essential empirical question examining the risk balancing behavior of small US farm operations. While risk balancing has been a theme of several studies, none of the previous studies have specifically looked at the behavior in the context of small US farms. The theoretical synopsis and empirical findings contribute to the literature of risk balancing, debt use and savings use decisions and the policy discussions on farm financial and support strategies.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47400524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-27DOI: 10.1108/afr-12-2021-0168
Masaood Moahid, Ghulam Dastgir Khan, M. A. Bari, Y. Yoshida
PurposeNatural calamities impair agricultural households' ability to invest in their farms. Facilitating access to agricultural credit may assist farmers in the face of negative revenue shocks. The aim of this study is to investigate the impact of agricultural credit on the agricultural input expenditure of disaster-affected farmers in Bangladesh.Design/methodology/approachThe study utilizes data on 2,519 disaster-affected farming households from Bangladesh's Household Income and Expenditure Study (HIES) 2016–2017, which employs a nationwide representative five-year interval survey. Further, propensity score matching (PSM) identification strategy is used to estimate the average treatment effect on the treated (ATET), and Mahalanobis distance matching (MDM) is used for the robustness test. In addition, heterogeneous analysis has been conducted to explore the impact of agricultural credit on different types of farming households.FindingsThe findings reveal that access to agricultural credit has a favorable and significant effect on farm input expenditure for disaster-affected farmers. Therefore, agricultural credit accessibility could be utilized as a policy tool to assist disaster-affected farmers in improving their investment capacity, and hence, agricultural output.Originality/valueThis study, using a quasi-experimental design of access to agricultural credit on agricultural input expenditures of the disaster-affected farming households in coastal areas of Bangladesh to estimate the causal effect.
{"title":"Does access to agricultural credit help disaster-affected farming households to invest more on agricultural input?","authors":"Masaood Moahid, Ghulam Dastgir Khan, M. A. Bari, Y. Yoshida","doi":"10.1108/afr-12-2021-0168","DOIUrl":"https://doi.org/10.1108/afr-12-2021-0168","url":null,"abstract":"PurposeNatural calamities impair agricultural households' ability to invest in their farms. Facilitating access to agricultural credit may assist farmers in the face of negative revenue shocks. The aim of this study is to investigate the impact of agricultural credit on the agricultural input expenditure of disaster-affected farmers in Bangladesh.Design/methodology/approachThe study utilizes data on 2,519 disaster-affected farming households from Bangladesh's Household Income and Expenditure Study (HIES) 2016–2017, which employs a nationwide representative five-year interval survey. Further, propensity score matching (PSM) identification strategy is used to estimate the average treatment effect on the treated (ATET), and Mahalanobis distance matching (MDM) is used for the robustness test. In addition, heterogeneous analysis has been conducted to explore the impact of agricultural credit on different types of farming households.FindingsThe findings reveal that access to agricultural credit has a favorable and significant effect on farm input expenditure for disaster-affected farmers. Therefore, agricultural credit accessibility could be utilized as a policy tool to assist disaster-affected farmers in improving their investment capacity, and hence, agricultural output.Originality/valueThis study, using a quasi-experimental design of access to agricultural credit on agricultural input expenditures of the disaster-affected farming households in coastal areas of Bangladesh to estimate the causal effect.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46598906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-24DOI: 10.1108/afr-09-2021-0129
Charles C. Martinez, C. Boyer, Tun-Hsiang Yu, S. A. Smith, Adam N. Rabinowitz
PurposeThe authors examined the impact of the Market Facilitation Program (MFP) and Coronavirus Food Assistance Program (CFAP) payments to United States agricultural producers on non-real estate agricultural loans.Design/methodology/approachThe authors used quarterly, state-level commercial bank data from 2016–2020 to estimate dynamic panel models.FindingsThe authors found MFP and CFAP payments not associated with the percentage of non-real estate agricultural loans with payments over 90 days late. However, these payments associated with the percentage of non-real estate agricultural loans with payments between 30 and 89 days late. The available data utilized cannot consider when producers received the actual payment and what they specifically did with those funds.Originality/valueThe contribution of this study is for US policymakers and agricultural lenders. The findings could be helpful in designing and implementing future ad hoc payment programs and provide an understanding of potential shortcomings of the current safety net for agricultural producers in the Farm Bill. Additionally, findings can assist agricultural lenders in predicting the impact of ad hoc payments on their distressed loan portfolios.
{"title":"Ad hoc government payments impact on non-real estate farm debt","authors":"Charles C. Martinez, C. Boyer, Tun-Hsiang Yu, S. A. Smith, Adam N. Rabinowitz","doi":"10.1108/afr-09-2021-0129","DOIUrl":"https://doi.org/10.1108/afr-09-2021-0129","url":null,"abstract":"PurposeThe authors examined the impact of the Market Facilitation Program (MFP) and Coronavirus Food Assistance Program (CFAP) payments to United States agricultural producers on non-real estate agricultural loans.Design/methodology/approachThe authors used quarterly, state-level commercial bank data from 2016–2020 to estimate dynamic panel models.FindingsThe authors found MFP and CFAP payments not associated with the percentage of non-real estate agricultural loans with payments over 90 days late. However, these payments associated with the percentage of non-real estate agricultural loans with payments between 30 and 89 days late. The available data utilized cannot consider when producers received the actual payment and what they specifically did with those funds.Originality/valueThe contribution of this study is for US policymakers and agricultural lenders. The findings could be helpful in designing and implementing future ad hoc payment programs and provide an understanding of potential shortcomings of the current safety net for agricultural producers in the Farm Bill. Additionally, findings can assist agricultural lenders in predicting the impact of ad hoc payments on their distressed loan portfolios.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44456908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
USDA policies and programs support beginning farmers and ranchers in several ways that are consistent with improved competitiveness of the agricultural sector overall. These include initiatives, such as business planning education and technical assistance, on risk management and conservation decisions. The USDA also provides access to capital through its direct and guaranteed lending programs. Finally, the USDA supports beginning farmers and ranchers through statistical reporting and economic analysis on beginning farmers and ranchers. The USDA ’ s primary research insights into beginning farmer and rancher demographics and well- being come from an annual cross-sectional financial survey known as the Agricultural Resource Management Survey (ARMS) as well as the Census of Agriculture that takes place every five years. Farmers andrancherswhoaresurveyed throughtheARMSareasked torecordtheirproductionand financial information as well as how long they have been actively farming; this information allows researchers to compare outcomes between “ beginning ” farmers and ranchers vs others. Researchers at ERS and elsewhere have used successive Census of Agriculture data to understand what contributes to differences in the survival and growth of beginning farm operations. Research using the ARMS and Census of Agriculture data demonstrates the value of USDA ’ s commitment to long- term data collection to understand the structure and dynamics of the agricultural sector.
{"title":"Guest editorial: Special issue on beginning farmers and ranchers","authors":"J. Hopkins","doi":"10.1108/afr-06-2022-188","DOIUrl":"https://doi.org/10.1108/afr-06-2022-188","url":null,"abstract":"USDA policies and programs support beginning farmers and ranchers in several ways that are consistent with improved competitiveness of the agricultural sector overall. These include initiatives, such as business planning education and technical assistance, on risk management and conservation decisions. The USDA also provides access to capital through its direct and guaranteed lending programs. Finally, the USDA supports beginning farmers and ranchers through statistical reporting and economic analysis on beginning farmers and ranchers. The USDA ’ s primary research insights into beginning farmer and rancher demographics and well- being come from an annual cross-sectional financial survey known as the Agricultural Resource Management Survey (ARMS) as well as the Census of Agriculture that takes place every five years. Farmers andrancherswhoaresurveyed throughtheARMSareasked torecordtheirproductionand financial information as well as how long they have been actively farming; this information allows researchers to compare outcomes between “ beginning ” farmers and ranchers vs others. Researchers at ERS and elsewhere have used successive Census of Agriculture data to understand what contributes to differences in the survival and growth of beginning farm operations. Research using the ARMS and Census of Agriculture data demonstrates the value of USDA ’ s commitment to long- term data collection to understand the structure and dynamics of the agricultural sector.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42829501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-15DOI: 10.1108/afr-11-2021-0155
Ernest Christlieb Amrago, N. Mensah
PurposeThe purpose of this study is to examine trade credit from agrochemical vendors as an alternative source of finance for cabbage producers in the Bono East Region of Ghana. The determinants of trade credit supply and impact on cabbage producer’s profitability are investigated.Design/methodology/approachThe study sample size is 260. The perception index, probit regression, negative binomial regression and the propensity score matching (PSM) was employed to assess the perception of trade credit, factors influencing trade credit supply and the impact of trade credit supply on the cabbage producer’s profitability and agrochemical vendor’s welfare respectively.FindingsThe perception index analysis revealed that the agrochemical vendors, in general, had a positive perception of trade credit. Different groups of factors influence trade credit supply. Further along, the number of times trade credit was used by the cabbage producers was influenced by several factors. On the PSM result, trade credit use had a significant positive impact on the cabbage producer’s profitability. In detail, all the matching estimations revealed that profitability increased above Gh¢ 4,000.00 (US$ 692.04). Likewise, the robustness check result (Inverse Probability Weighted Regression Adjustment (IPWRA)), was no different from the matching estimations. Generally, the result indicates that the impact of trade credit supply on the agrochemical vendor's welfare using total household expenditure, total savings and income as proxy variables for welfare were positive.Originality/valueTrade credit has encountered less attention in the agricultural finance discourse; however, this study makes an imperative contribution on the same. Specifically, the study reveals the determinants of trade credit supply from agrochemical vendors and a positive impact of trade credit use on the cabbage producer’s profitability, a result which has not been investigated in the trade credit literature.
{"title":"Trade credit from agrochemical vendors as an alternative source of finance for cabbage producers in the Bono East Region of Ghana","authors":"Ernest Christlieb Amrago, N. Mensah","doi":"10.1108/afr-11-2021-0155","DOIUrl":"https://doi.org/10.1108/afr-11-2021-0155","url":null,"abstract":"PurposeThe purpose of this study is to examine trade credit from agrochemical vendors as an alternative source of finance for cabbage producers in the Bono East Region of Ghana. The determinants of trade credit supply and impact on cabbage producer’s profitability are investigated.Design/methodology/approachThe study sample size is 260. The perception index, probit regression, negative binomial regression and the propensity score matching (PSM) was employed to assess the perception of trade credit, factors influencing trade credit supply and the impact of trade credit supply on the cabbage producer’s profitability and agrochemical vendor’s welfare respectively.FindingsThe perception index analysis revealed that the agrochemical vendors, in general, had a positive perception of trade credit. Different groups of factors influence trade credit supply. Further along, the number of times trade credit was used by the cabbage producers was influenced by several factors. On the PSM result, trade credit use had a significant positive impact on the cabbage producer’s profitability. In detail, all the matching estimations revealed that profitability increased above Gh¢ 4,000.00 (US$ 692.04). Likewise, the robustness check result (Inverse Probability Weighted Regression Adjustment (IPWRA)), was no different from the matching estimations. Generally, the result indicates that the impact of trade credit supply on the agrochemical vendor's welfare using total household expenditure, total savings and income as proxy variables for welfare were positive.Originality/valueTrade credit has encountered less attention in the agricultural finance discourse; however, this study makes an imperative contribution on the same. Specifically, the study reveals the determinants of trade credit supply from agrochemical vendors and a positive impact of trade credit use on the cabbage producer’s profitability, a result which has not been investigated in the trade credit literature.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47367808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Agriculture Improvement Act of 2018 directed the US Secretary of Agriculture to report on the profitability and viability of beginning farmers and ranchers. Many beginning operations use local food markets as they provide more control, or a premium over commodity prices, and beginning operations cannot yet take advantage of economies of scale and subsequently have higher costs of production. Little research assesses the relationship between beginning farmer profitability and sales through local food markets. In this paper, the profitability implications of sales through local food markets for beginning farmers and ranchers are explored.
Design/methodology/approach
The authors utilize 2013–2016 USDA agricultural resource management survey data to assess the financial performance of US beginning farmers and ranchers who generate sales through local food markets.
Findings
The results point to four important takeaways to support beginning operations. (1) Local food channels can be viable marketing opportunities for beginning operations. (2) There are differences when using short- and long-term financial performance indicators, which may indicate that there is benefit to promoting lean management strategies to support beginning operations. (3) Beginning operations with intermediated local food sales, on average, perform better than those operations with direct-to-consumer sales. (4) Diversification across local food market channel types does not appear to be an indicator of improved financial performance.
Originality/value
This article is the first to focus on the relationship beginning local food sales and beginning farmer financial performance. It incorporates short-term and long-term measures of financial performance and differentiates sales by four local food market type classifications: direct-to-consumer sales at farmers markets, other direct-to-consumer sales, direct-to-retail sales and direct-to-regional distributor or institution sales.
{"title":"The profitability implications of sales through local food markets for beginning farmers and ranchers","authors":"Becca B.R. Jablonski, Joleen Hadrich, Allison Bauman, Martha Sullins, Dawn Thilmany","doi":"10.1108/afr-05-2021-0056","DOIUrl":"https://doi.org/10.1108/afr-05-2021-0056","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>The Agriculture Improvement Act of 2018 directed the US Secretary of Agriculture to report on the profitability and viability of beginning farmers and ranchers. Many beginning operations use local food markets as they provide more control, or a premium over commodity prices, and beginning operations cannot yet take advantage of economies of scale and subsequently have higher costs of production. Little research assesses the relationship between beginning farmer profitability and sales through local food markets. In this paper, the profitability implications of sales through local food markets for beginning farmers and ranchers are explored.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The authors utilize 2013–2016 USDA agricultural resource management survey data to assess the financial performance of US beginning farmers and ranchers who generate sales through local food markets.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The results point to four important takeaways to support beginning operations. (1) Local food channels can be viable marketing opportunities for beginning operations. (2) There are differences when using short- and long-term financial performance indicators, which may indicate that there is benefit to promoting lean management strategies to support beginning operations. (3) Beginning operations with intermediated local food sales, on average, perform better than those operations with direct-to-consumer sales. (4) Diversification across local food market channel types does not appear to be an indicator of improved financial performance.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This article is the first to focus on the relationship beginning local food sales and beginning farmer financial performance. It incorporates short-term and long-term measures of financial performance and differentiates sales by four local food market type classifications: direct-to-consumer sales at farmers markets, other direct-to-consumer sales, direct-to-retail sales and direct-to-regional distributor or institution sales.</p><!--/ Abstract__block -->","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":"47 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138515687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-08DOI: 10.1108/afr-09-2021-0123
M. Boyd, E. Belasco
PurposeThis paper examines the relationship between farm-level variables related to cash flow and premium rates on federal crop insurance coverage selection.Design/methodology/approachUsing farm-level data from the Agricultural Resource Management Survey (ARMS), the authors estimate a linear fixed effects model to evaluate the relationship between farm-level and regional variables and federal crop insurance coverage selections.FindingsThe authors find evidence indicating that expected cash flow plays an important role in coverage level decisions. For example, variables directly related to cash flow, such as higher costs, are associated with significant differences in coverage level selection, though the direction of the association is dependent on the type of costs, whether fixed or variable, while higher revenue higher acreage farms insure at higher coverage levels. In addition, higher premium costs are associated with lower coverage level selections, despite subsidy incentives.Originality/valueThis is the first paper that identifies a potential solution to the puzzling finding that farmers do not consistently maximize coverage level. This research points to the influence of credit constraints as playing a role in limiting coverage level selections.
{"title":"The impact of farm-level variables on federal crop insurance coverage selections","authors":"M. Boyd, E. Belasco","doi":"10.1108/afr-09-2021-0123","DOIUrl":"https://doi.org/10.1108/afr-09-2021-0123","url":null,"abstract":"PurposeThis paper examines the relationship between farm-level variables related to cash flow and premium rates on federal crop insurance coverage selection.Design/methodology/approachUsing farm-level data from the Agricultural Resource Management Survey (ARMS), the authors estimate a linear fixed effects model to evaluate the relationship between farm-level and regional variables and federal crop insurance coverage selections.FindingsThe authors find evidence indicating that expected cash flow plays an important role in coverage level decisions. For example, variables directly related to cash flow, such as higher costs, are associated with significant differences in coverage level selection, though the direction of the association is dependent on the type of costs, whether fixed or variable, while higher revenue higher acreage farms insure at higher coverage levels. In addition, higher premium costs are associated with lower coverage level selections, despite subsidy incentives.Originality/valueThis is the first paper that identifies a potential solution to the puzzling finding that farmers do not consistently maximize coverage level. This research points to the influence of credit constraints as playing a role in limiting coverage level selections.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":"1 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41339072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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