Department of Agricultural and Resource Economics

This paper reviews 40 years of tortured history of the Consultative Group on International Agricultural Research's (CGIAR) attempts at structural reform.  Yet the basic structure of independent centers created in the 1960's and 70's remains in place despite repeated attempts to restructure the basic building blocks of the system.  Instead successive layers of super structure: eco-regional programs; Challenge programs; CGIAR Research Programs (CRP's); and finally a Consortium with another Board and CEO have been added to foster inter-center and interdisciplinary research.  The failure of reforms is attributed to the unwillingness of donors, and the World Bank leadership of the CGIAR, to take on entrenched center interests.  Some success in modest reform has occurred at the sub-system/center level but only with much difficulty.  The paper concludes with some suggestions as to how reform might be fostered. 

This paper considers the estimation and testing of demand systems when the number of sample goods is smaller than the number of commodity choices available to consumers. In this case, the demand system is incomplete. The large majority of papers that appeared in the literature specifies and estimates a demand system in share format even when the system may be incomplete. The criterion for deciding whether a share format is admissible without loss of information is a test of the adding-up condition. This test, however, requires the estimation of a demand system in quantity format.

The Maximum Likelihood method estimates the parameter values of a statistical model that maximize the corresponding likelihood function, given the sample information. This is the primal approach that, in this paper, is presented as a mathematical programming specification whose solution requires the formulation of a Lagrange problem. A remarkable result of this setup is that the Lagrange multipliers associated with the linear statistical model (regarded as a set of constraints) is equal to the vector of residuals scaled by the variance of those residuals. The novel contribution of this paper consists in developing the dual model of the Maximum Likelihood method under normality assumptions. This model minimizes a function of the variance of the error terms subject to orthogonality conditions between the errors and the space of explanatory variables. An intuitive interpretation of the dual problem appeals to basic elements of information theory and establishes that the dual maximizes the net value of the sample information. This paper presents the dual ML model for a single regression and for a system of seemingly unrelated regressions.

The least-squares method was firmly established as a scientific approach by Gauss, Legendre and Laplace within the space of a decade, at the beginning of the nineteenth century.  Legendre was the first author to name the approach, in 1805, as "méthode des moindres carrés," a "least-squares method."  Gauss, however, is credited to have used it as early as 1795, when he was 18 years old.  He, subsequently, adopted it in 1801 to calculate the orbit of the newly discovered planet Ceres.  Gauss published his way of looking at the least-squares approach in 1809 and gave several hints that the least-squares algorithm was a minimum variance linear estimator and that it was derivable from maximum likelihood considerations.  Laplace wrote a very substantial chapter about the method in his fundamental treatise on probability theory published in 1812.  Surprisingly, there still remains an unexplored aspect of the least-squares method: since the traditional formulation is stated as minimizing the sum of squared deviations subject to the linear (or nonlinear) specification of a regression model, this mathematical programming problem must have a dual counterpart.  This note fills this gap and shows that the least-squares estimates of unknown parameters and deviations can be obtained by maximizing the net value of sample information. 

Shadow prices guide farmers' resource allocations, but for subsistence farmers growing traditional crops, shadow prices may bear little relationship with market prices. We econometrically estimate shadow prices of maize using data from a nationally representative survey of rural households in Mexico. Shadow prices are significantly higher than the market price for traditional but not improved maize varieties. They are particularly high in the indigenous areas of southern and southeastern Mexico, indicating large de facto incentives to maintain traditional maize there.

The primary purpose of this paper is to provide updated estimates of domestic own-price, cross-price and income elasticities of demand and estimated price elasticities of supply for various California commodities. Flexible functional forms including the Box-Cox specification and the nonlinear almost ideal demand system are estimated and bootstrap standard errors obtained. Partial adjustment models are used to model the supply side. These models provide good approximations in which to obtain elasticity estimates. The six commodities selected represent some of the highest valued crops in California. The commodities are: almonds, walnuts, alfalfa, cotton, rice, and tomatoes (fresh and processed). All of the estimated own-price demand elasticities are inelastic and, in general, the income elasticities are all less than one. On the supply side, all the short-run price elasticities are inelastic. The long-run price elasticities are all greater than their short-run counterparts. The long-run price supply elasticities for cotton, almonds and alfalfa are elastic, i.e., greater than one. Policy makers can use these estimates to measure the changes in welfare of consumers and producers with respect to changes in policies and economic variables.

Recent theoretical and empirical evidence suggests that risk (especially covariant risk that is correlated across producers) may discourage both the supply of agricultural credit and the willingness of small holders to utilize available credit and enjoy the higher expected incomes credit could make available to them. One possible resolution to this problem is to remove risk from the system by independently insuring it. However, conventional (all hazard) crop insurance has in almost every instance been rendered financially unsustainable by moral hazard and adverse selection problems. This paper instead analyzes two index-based insurance schemes, one based on a weather index, and a second based on measured average yields. While these index insurance products do not protect the farmer from all risks, our econometric analysis (which is based on data from the north coast of Peru) shows that they could have substantial value to the producer and could also crowd-in credit supply from lenders reluctant to carry too much covariant risk in their loan portfolios. We also show that insurance based on measured yields is markedly superior to a weather index (for both borrowers and lenders). We close by arguing that present and past public good failures justify public intervention in this area, and analyze the feasibility of a public scheme to initially underwrite the costs and uncertainties associated with area-based yield insurance. _________

The conquests of Alexander III ("The Great") transformed the economic as well as political landscape of ancient Greece and Persia. It produced a prolific coinage, part of which survives today. This paper uses a hedonic price modeling approach to analyze auction prices of the major coin type of Alexander the Great. The findings make it possible to identify the effects of specific coin characteristics on realized auction prices, sellers' reservation prices (auction price estimates), discrepancies between realized and estimated prices, and the variability of auction prices around predicted prices, or auction price surprise. The findings reveal that similar considerations shape estimated and realized prices, but bidders consistently value positive coin characteristics more highly than do sellers. Realized auction prices, the difference between realized and estimated prices, and auction price surprise are increasing over time, particularly for the highest grade coins.