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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.

This chapter reassesses the economics of interest rate risk management in light of the global financial crisis by developing a derivative-based integrated treatment of interest rate and credit risk interrelation. The decade-long historical data on credit default swap spreads and interest rate swap rates are used as proxy measures for credit risk and interest rate risk, respectively. An elasticity of interest rate risk and credit risk, considered a function of the business cycle phases, maturity of instruments, economic sector, creditworthiness, and other macroeconomic parameters, is investigated for optimizing economic capital. This chapter sheds light on how financial institutions may address hedge strategies against downside risks implementing the proposed derivative-based integrated treatment of interest rate and credit risk assessment allowing for optimization of interest rate swap contracts. The developed framework of integrated interest rate and credit risk management is of special importance for emerging markets heavily dependent on foreign capital as it potentially allows emerging market banks to improve risk management practices in terms of capital adequacy and Basel III rules. Analyzing diversification versus compounding effects, it allows enhancing financial stability through jointly optimizing Pillar 1 and Pillar 2 economic capital.

The purpose of this paper is to empirically investigate the influencing factors of loan demand in agriculture. With the structural changes that agriculture is undergoing and the accordingly higher financing requirements and volumes, the analysis of loan demand in agriculture is of particular interest.

Detailed actual loan data at farm level, which is provided by a major German development bank for the agricultural sector, is used for the analysis. The data set covers the period from 2010 to 2014 and consists of 68,430 observations. Due to the data structure, an ordinary least square regression is conducted with the loan amount as the dependent variable. Many explanatory variables are included, such as the interest rate, the intended use of the loan, grace periods, the gross value added (GVA) and the business climate index for agriculture.

Amongst others, the authors find that interest rate, GVA, grace periods and farmers’ business expectations have significant effects on the loan demand in agriculture. According to the results, the interest rate has a significant negative effect, whereas the granted grace periods, the GVA in agriculture and farmers’ business expectations have significant positive effects on the loan demand.

This paper investigates the determinants of loan demand in agriculture in a developed country by using unique and comprehensive data at loan and farm level. Amongst others, elasticities of loan demand in agriculture are determined.

Uses recently developed techniques in the estimation of non‐stationary time series to construct money demand functions for four African economies, using quarterly data. Finds that money demand depends not only on income, inflation and interest rates, but also on variability of inflation and interest rates: the more variable the return to an asset, the lower its demand. Reports the first quarterly models of money demand (as far as we are aware) in Cameroon, Nigeria and Ivory Coast. Finds that the model for Kenya encompasses existing models. The estimated models have important policy implications. Since high inflation tends to be associated with highly variable inflation, any calculation of the seignorage‐maximizing rate of inflation which ignores the variability effect will overestimate the optimal rate of inflation. Insofar as membership of a monetary union reduces not only the rate of inflation but also its variability, there are extra gains from membership of such a union (Cameroon and Ivory Coast are Franc Zone members; Nigeria and Kenya are not). However, the heter‐ogeneity of the estimated functions suggests that it would be very difficult to have an effective monetary policy were the four countries considered members of the same monetary union.

Applies an error‐correction model to demand for money in five African economies: Congo, Côte d′Ivoire, Mauritius, Morocco and Tunisia. Attention is given to a set of opportunity cost variables including expected inflation, domestic interest rate, foreign interest rate and expected exchange‐rate depreciation. The empirical results show that the domestic interest rate plays a significant role in the demand for money functions for three of the five countries and external opportunity cost variables are significant for one of the others. The results show some diversity in money demand behaviour in the countries studied, but the error correction mechanism is always significant and in four out of five cases there is a short‐run inflation impact. The equations are subjected to a battery of tests and found to be statistically well‐behaved.

This paper examines the existence and stability of both the long‐ and short‐run demand for narrow and broad money balances. The data for Singapore are used as a case study. The quarterly period examined is 1973:2‐1999:3 (105 observations). The study reveals the existence of a systematic long‐run relationship among real money balances, real income, interest rate and exchange rate. Results from testing the hypothesis of a unitary price elasticity confirm that only the broad money aggregate could be used as intermediate target of monetary policy. Using a formal test of parameter constancy designed specifically for cointegrating vectors, it is shown that nonstationarity and time invariance in the demand for money can be resolved by the inclusion of the exchange rate.

This paper aims to propose a general, yet simple model to estimate interest rate volatility.

The methodology is based on an extended Exponential Generalized ARCH (EGARCH) model that incorporates both interest rate levels as well as past information shocks in the volatility function. More importantly, the model is log‐linear thus eliminating collinearity problems and it can be easily estimated using standard maximum likelihood techniques.

The empirical evidence suggests that the elasticity of volatility to the level of interest rates, although statistically significant, is not as high numerically as previously thought. In fact innovations in the interest rate process are more significant than the level of interest rates. The most important feature of interest rates, however, is the high volatility persistence.

A limitation of the model is that it does not allow for structural shifts in its current form. Extending the model to accommodate possible shifts would probably improve the performance as well the forecasting accuracy.

The findings in this paper have important implications for the accurate pricing of fixed income derivative securities as well as the efficient risk management of fixed income portfolios.

The paper provides a convenient and unifying methodological framework for assessing the importance and forecasting ability of the various volatility components.

Applies a modified Keynesian money demand function to household money demand in Poland from 1969 to 1993. Co‐integration between the demand for broad money, income and shortage, despite the regime shifts during the 1980s and full liberalization of the Polish economy in the beginning of 1990. Compared to other studies, pays much attention to empirical evidence concerning portfolio arguments in the money demand function. Because the Polish economy has developed from a cash into a savings economy, over the sample period, observes an increase in price and interest rate elasticities of the demand for different financial assets.

The article is concerned with company demand for broad money in the post‐Competition and Credit Control period. Equations are estimated for (a) all industrial and commercial companies and (b) a sample of large manufacturing and non‐manufacturing companies. The main findings are (1) that economies of scale in money holdings are only evident for large companies, (2) that only the large manufacturing companies respond significantly to changes in long‐term interest rates and (3) that adjustment of money holdings to changes in income and interest rates is completed within six months.