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This article reviews the development and future of the Farm Credit System (FCS) as a government sponsored source of credit for American agriculture. While agriculture is now a minor sector of the U.S. economy, and there is considerable competition for the FCS from other lenders suggesting no further need for GSE status, it still may be possible to argue that there is some ongoing need. Although credit market imperfections are no longer as clear cut as in the past, they may still act as an impediment to a desirable allocation of capital. Consequently, refocusing the FCS may provide a relatively efficient form of government intervention that can enhance capital flows in rural areas.

Motivated by recent congressional interest in eradicating government sponsored enterprises (GSE), the purpose of this paper is to develop a framework to price the implicit government guarantee embedded in the bonds issued by the Farm Credit System.

The paper uses the Black‐Scholes model to extract the implied volatilities of the guarantee and then substitute into the model the volatility in historical land prices. The model is developed along the lines of Merton's bond pricing formulation of implicit calls and puts on bond yield risk and default.

Bottom line results show that the average bond yield for a 3M Farm Credit bond from January 13th 2009 to February 10th 2011 would be 0.3744 percent if the Farm Credit System had no GSE status, which is 13.62 bps higher than the actual bond yield. The difference between the hypothetical yield and the actual yield increases with increasing maturity and reaches its peak with 10Y bond where the difference between the hypothetical yield and the actual yield is 68.81 bps. The paper concludes that given the current state of the agricultural credit market in the USA that loss of GSE status and the implied guarantee of Farm Credit bonds would have a minimal effect on short term notes, with a more substantive increase in longer term yields.

The GSE status of the Farm Credit System is an important political issue. This paper provides first estimates of what impact might result from its loss of GSE status. The methods employed are consistent with current models of bond pricing and the results are of direct relevance to Farm Credit System regulators and congressional discussions.

Farm credit is important, if the Farm Credit System loses its GSE status this might affect the competitive balance between commercial and system lenders.

This paper uses option price theory based upon the spread between farm credit bonds and treasury. The approach used requires daily data, but not all attributes of bonds are known. Nonetheless, the results show remarkable consistency for a problem that is largely understudied. There is a need for policy makers, including the US congress to understand the value of government guarantees whether implicit or explicit.

The purpose of this paper is to investigate the market microstructure related to the Farm Credit System (FCS), Commercial Banks (CB) and Farm Services Administration (FSA). The commercial banks frequently call out the FCS as having an unfair advantage in the agricultural finance market place due to tax exempt bonds, and an implied guarantee of those bonds. This paper addresses the issue by examining the interrelationships since 1939, while addressing the historically distinctive roles that the FCS, CB and FSA have played in the US agricultural credit market.

There are two components to our model. The first is the estimation of short and long run credit demand elasticities, as well as land elasticities. These are estimated from a dynamic duality model using seemingly unrelated regression. The point elasticity measures are then used as independent variables in least square regressions, combined with farm specific and related macro variables, for the Cornbelt states. The dependent variable is the year-over-year changes in paired FCS, CB and FSA loans.

The genesis of the FCS was to provide credit to farmers in good and bad years. Therefore, we expected to see a countercyclical relationship between FCS and CB. This is found for the farm crisis years in the 1980s but is not a continuous characteristic of FCS lending. In good times the FCS and CB appear to compete, albeit with differentiated market segmentation into short- and long-term credit. The FSA, which was established to provide tertiary support to both the FCS and CB, appears to be responding as designed, with greater activity in bad years. The authors find the elasticity measures to be economically significant.

The authors conclude that the market microstructure of the agricultural credit market in the US is important. Our analysis applies a broader definition of market microstructure for institutions and intermediaries and reveals that further research examining the economic frictions caused by comparative bond vs deposit funding of agricultural credit is important.

The authors believe that this is the first paper to examine agricultural finance through the market microstructure lens. In addition our long-term data measures allow us to examine the economics through various sub-periods. Finally, we believe that our introduction of credit and land demand elasticities into a comparative credit model is also a first.

The purpose of this paper is to provide a review of major historical developments in agricultural finance, with particular emphasis on agricultural credit. It reviews the development of Raiffeisen and related banks that emerged in Germany and Europe throughout the nineteenth century and how the cooperative banking system made its way into the banking system of the USA in the early twentieth century. The paper emphasizes the role of the state in the developing of agricultural credit, especially with respect to farm mortgages, securitization, and bond structures.

This paper presents a historical synthesis of historical literature on agricultural credit.

This paper shows the direct linkage between the developments in Raiffeisen credit cooperatives and the Farm Credit System (FCS) and details the emergence of the land banks, farm credit banks, agricultural bonds and the role of joint-stock banks in agricultural credit policy.

In total, 2016 marks the 100th anniversary of the passing of the 1916 Federal Farm Loan Act which set in motion the USs’ first Government Sponsored Enterprise and catalyzed the formation of the FCS as it operates today to provide credit to farmers and rural communities on a cooperative basis. Although there are a few wonderful books written on certain aspects of the FCS the story of how the FCS was initiated and the many struggles it faced up to the 1933 Act has not been told often enough. This paper tells the story of the evolution of agricultural credit that ultimately led to the formation of the FCS.

Agricultural credit markets are dominated by two institutional retail lender groups, the cooperative Farm Credit System (FCS) and commercial banks. Analysis of farm loans made over the 1991S1993 and 2001S2002 periods indicates that FCS lenders were more likely to serve full‐time commercial farmers and farmers located in regions with less competitive credit markets. In contrast, commercial banks were more likely to serve small, part‐time, and hobby farmers. This segmentation of farm credit markets is consistent with federal regulations requiring the FCS to provide credit to “bona fide” farmers with a basis for credit.

The purpose of this paper is to provide evidence of the positive impact of the FCS lending on farm incomes which should be useful to policymakers as they consider reforms and further support for this 100-year-old major agricultural lender.

The authors construct a panel for the 1991-2010 period from the FCS financial statements and evaluate how lending by the FCS institutions has affected farm incomes and farm output. The authors use fixed effects estimations and control for credit by other agricultural lenders as well as the stock of capital, prices, and interest rates. Since previous work suggests that rural financial markets are segmented and the FCS serves larger full-time farmers with mostly real-estate backed loans, the authors evaluate the impacts of farm real-estate backed loans and of short-term agricultural loans separately for a shorter period for which the data is available. The authors also perform robustness checks with alternative estimation techniques.

The authors found a positive association between credit by the FCS institutions and farm income and output. The magnitude of the estimated impact is larger during the 1990s than in the 2000s.

The positive link between the FCS institutions’ credit and farm incomes and output supports the notion that the FCS lending was beneficial to farmers. The evidence also supports the segmentation hypothesis of rural financial markets. The financial reports data for 1991-2010 are from the ACAs and FLCAs aggregated on the regional level because there is no clear way to classify FCS lending to a more disaggregate level like the state. The authors also assemble and analyze a state-level data set that contains state-level balance sheet data for the period 1991-2003.

The authors are not aware of another work that directly links (real estate and non-real estate) credit by FCS institutions to agricultural output and farm incomes.

Logistic regression techniques for panel data are used to identify factors affecting farm credit transition probabilities. Results indicate that most farm‐specific factors do not have adequate explanatory influence on the probability of farm credit risk transition. Class upgrade probabilities are more significantly affected by changes in certain macroeconomic factors, such as economic growth signals (from changes in stock price indexes and farm real estate values) and larger money supply that relax the credit constraint. Increases in interest rates, on the other hand, negatively affect such probabilities.

Farm Credit is a major provider of credit to agricultural producers in Oklahoma and nationally. The decision to place a new Farm Credit office reduces borrower search and travel costs and should increase loan volume. The purpose of this paper is to model the new loan volume as function of distance from east central Oklahoma county centroids to Farm Credit offices. The model is then used to predict the impact of placing new offices in underserved areas.

County aggregate new loan volume is regressed on distances to Farm Credit branch and field offices and other variables expected to impact agricultural loan volume. The estimated model is used to predict new loan volume impact of adding additional branch and field offices in counties that did not have these offices. Confidence intervals are used to measure the significance of predicted loan volumes.

Distances from county centroids to both branch and field offices were found to significantly reduce new loan volume. The results were used to simulate the addition of new branch and field offices. The simulation predicted the added annual new loan volume associated with office additions.

Using spatial models, Farm Credit of east central Oklahoma and other agricultural lenders can better plan for expansion (or consolidation). These models indicate counties where annual new loan volume will likely be higher (or lower for consolidation) than other nearby counties. The result can be improved borrower access and system financial performance.

While spatial modeling has been utilized in other sectors, little has been done relative to agricultural credit access and impact on loan volume. The model here explicitly models the impact that distance to Farm Credit offices have on annual new loan volume.

Many associations in the Farm Credit System, which are financial cooperatives, pay their member‐borrowers a cash patronage payment based on the amount of loan volume with the association. In today's competitive lending environment, some Farm Credit associations have offered lower interest rates on new loans but these new member‐borrowers have to forgo their cash patronage payment to receive this new, lower‐interest rate loan. The purpose of this paper is to identify Farm Credit member‐borrowers' preferences for patronage refunds received as a cash payment versus lower fixed real estate interest rates.

Preferences for patronage refunds or lower fixed interest rates are elicited from Farm Credit Services of East Central Oklahoma member‐borrowers via conjoint analysis.

Results show that member‐borrowers strongly prefer patronage refunds compared to lower fixed interest rates.

This paper fulfills a need to better understand patronage refund programs within the Farm Credit System.

The migration approach to credit risk measurement is based on historic rates of movements of individual loans among the classes of a lender’s risk‐rating or credit‐scoring system. This article applies the migration concept to farm‐level data from Illinois to estimate migration rates for a farmer’s credit score and other performance measures under different time‐averaging approaches. Empirical results suggest greater stability in rating migrations for longer time‐averaging periods (although less stable than bond migrations), and for the credit score criterion versus ROE and repayment capacity.