Do Futures Benefit Farmers?

Simulations are used to analyze welfare and market- and farm-level effects of making futures available to producers of a storable commodity. Key features of the model are the explicit consideration of dynamic impacts due to inventories, and of aggregate market effects associated with futures adoption by some producers. Application to the natural rubber market shows that futures availability can lead to sizeable market- and farm-level effects. Futures availability enhances consumer welfare, reduces non-adopter welfare, and yields important welfare gains for adopters when their market share is small and welfare losses when they account for a sufficiently large market share.Commodity markets; futures; natural rubber; rational expectations; storage model; welfare analysis

HOW LARGE IS THE COMPETITIVE EDGE THAT U.S.-BASED FUTURES PROVIDE TO U.S. FARMERS?

The present study advocates a simulation approach to analyze quantitatively the impact of having locally-based markets for price derivatives. A major result is that market outcomes do not appear to be sensitive to most of the underlying parameters of the model other than demand elasticity and transportation costs. For the case of inelastic demand, introduction of a futures market in a country provides domestic producers with a competitive edge if transportation costs. The most important insight of the present analysis is that, under realistic scenarios it need not be the case that local producers will gain a competitive edge over foreign producers by introducing a futures market based on the local spot prices.Commodity markets, derivative markets, futures markets, welfare analysis, rational expectations, Marketing,

A Comparative Marketing Analysis of Major Agricultural Products in the United States and Argentina

The second in a series of three papers focusing on Argentina, this paper analyzes issues pertinent to the relative advantages and disadvantages between the United States and Argentina for producing, transporting, processing, and marketing major agricultural commodities in the context of distribution to significant global markets. Designed as a tool for agribusiness students and prospective investment and trade partners, it provides a side-by-side analysis of major U.S. and Argentine agricultural commodities. All facts and figures are in U.S. currency and common U.S. (avoirdupois) weights and measures. Also, from a comparative perspective, it defines the differences in technologies between the countries and examines in detail the marketing channels for grains (corn, soybeans, wheat, and sunflower) and livestock (beef and pork)

Argentine Agriculture under GATT

Argentina is the world\u27s second largest exporter of grains, oilseeds, and oilseed products. Traditionally, Argentina\u27s economic policies have taxed the agricultural sector, which produces goods for exports, to subsidize the mostly insulated industrial sector. Despite this unfavorable treatment, the agricultural sector has remained Argentina\u27s economic mainstay and competes successfully in world markets. Recurrent economic crises have led to substantial changes in Argentine economic policies, which may eventually reduce the agricultural sector\u27s burden of subsidizing the manufacturing sector\u27s growth. Although this transition may take several years to accomplish, the predicted outcome is even greater competitiveness of Argentina\u27s agricultural exports in world markets. From the perspective of the General Agreement on Tariffs and Trade (GATT), Argentina\u27s agricultural sector stands to benefit greatly from trade liberalization. Argentine farmers have been taxed rather than subsidized, so they have no preferential treatment to lose in the GATT negotiations. Also, subsidized agricultural production and exports from countries such as those in the European Community have greatly undermined the profitability of Argentine farm businesses. If these countries agree to decrease or remove their subsidies as a result of the GATT, the Argentine agricultural sector should benefit

The Transformation of Spain’s Pork Sector: Can It Continue?

Compared with the other major players in the world pork market, Spain has experienced profound growth and transformation within its pork sector over the past 20 years. Between 1985 and 2003, pork production in Spain increased by 139%, reaching 3.3 million metric tons per year, and Spain became the second-largest pork producer in the European Unio

Dynamic firm behavior under uncertainty

This study examines and compares the behavior of forward-looking and myopic expected-utility-maximizing competitive firms. The first scenario analyzed is that of a speculative storing firm in the absence of forward markets. It is shown that there are important differences between forward-looking and myopic firms in that the former may store more or less than otherwise identical risk-neutral firms, whereas the latter will always store less than risk-neutral ones. If the forward-looking firm is constant absolute risk averse (CARA) and sufficiently risk averse, at low storage levels it will store more than if it were risk neutral. So long as the firm is CARA, storage is negatively related to current price and the interest rate and is independent from beginning stocks, irrespective of myopic or forward-looking attitudes;The second section introduces forward markets and shows that the speculative storing firm separates storage from hedging. Storage is independent of random variables, risk aversion levels, and forward-looking or myopic attitudes. Under unbiased forward prices, full hedging is optimal for a myopic risk-averse firm but suboptimal for a forward-looking firm. If certain conditions hold, the optimal forward-looking CARA hedge under unbiased forward prices will be less than a full hedge;Next, the model is modified to allow for production without storage. Most of the findings from the speculative storage framework apply to this case if the production function is nonstochastic Leontief, and if output and material input prices are positively related. Under certain conditions, the forward-looking CARA firm will produce more than the risk-neutral one at sufficiently low output levels;The final model considers the most general situation, in which firms are allowed to produce and to store and trade forward both output and material input. The results show that the firm separates physical decisions from hedging decisions regardless of forward-looking or myopic attitudes. Physical decisions depend only on current forward and cash prices, the interest rate, and the storage and production cost functions. A model of the soybean-processing sector is developed that supports the hypotheses advanced and shows that forward prices better explain processor behavior than either naive price expectations or perfect foresight

Relaxing the Assumptions of Minimum-Variance Hedging

The most important minimum-variance hedge-ratio assumptions are (a) that production is deterministic and (b) that all of the agent\u27s wealth is invested in the cash position. Stochastic production greatly reduces optimal hedge ratios. An alternative investment greatly reduces opportunity costs of not hedging by diluting the cash position. Stochastic production and/or alternative investments render the costs associated with hedging relatively more important, yielding almost negligible net benefits of hedging. Hence, hedging costs typically dismissed in hedging models for being seemingly negligible are important determinants of hedging behavior

Duality theory in empirical work, revisited

We compute a pseudo-dataset by Monte Carlo simulations featuring important characteristics of US agriculture, such that the initial technology parameters are known, and employing widely used datasets for calibration. Then, we show the usefulness of this calibration by applying the duality theory approach to datasets bearing as sources of noise only the aggregation of technologically heterogeneous firms. Estimation recovers initial parameters with reasonable accuracy. These conclusions are expected, but the proposed calibration sets the basis for analysing the performance of duality theory in empirical work when datasets have more observed and unobserved sources of noise, as those faced by practitioners

Testing for Cointegration in the Presence of Moving Average Errors

This study explores performance of the Johansen cointegration statistics on data containing negative moving average (NMA) errors. Monte Carlo experiments demonstrate that the asymptotic distributions of the statistics are sensitive to NMA parameters, and that using the standard 5% asymptotic critical values results in severe underestimation of the actual test sizes. We demonstrate that problems associated with NMA errors do not decrease as sample size increases; instead, they become more severe. Further we examine evidence that many U.S. commodity prices are characterized by NMA errors. Pretesting data is recommended before using standard asymptotic critical values for Johansen’s cointegration tests

Does Duality Theory Hold in Practice? A Monte Carlo Analysis for U.S. Agriculture

The Neoclassical theory of production establishes a dual relationship between the profit value function of a competitive firm and its underlying production technology. This relationship, usually referred to as the duality theory, has been widely used in empirical work to estimate production parameters without the requirement of explicitly specifying the technology. We analyze the ability of this approach to recover the underlying production parameters and its effects on estimated elasticities and scale economies measurements, when data available for estimation features typical realistic problems. We design alternative scenarios and compute the data generating process by Monte Carlo simulations, so as to know the true technology parameters as well as to calibrate the dataset to yield realistic magnitudes of noise. This noise introduced in the estimation by construction prevents duality theory from holding exactly. Hence, the true production parameters may not be recovered with enough precision, and the estimated elasticities or scale economies measurements may be more inaccurate than expected. We compare the estimated production parameters with the true (and known) parameters by means of the identities between the Hessians of the production and profit functions.duality theory, firm’s heterogeneity, measurement error, data aggregation, omitted variables, endogeneity, uncertainty, Monte Carlo simulations., Crop Production/Industries, Production Economics, Risk and Uncertainty, Q12, D22, D81,