Estimating a Demand System with Seasonally Differenced Data

Researchers estimating demand systems have often used annual data even though monthly or quarterly data are available. Monthly data may be avoided because with monthly data it becomes more difficult to specify seasonality, autocorrelation is more likely to be significant, and there is a greater chance of finding significant dynamics in demand. This paper shows how to obtain consistent and asymptotically efficient estimates of a demand system using seasonal differenced data. It also shows that several alternative estimators are either inefficient or implausible for demand systems.Demand and Price Analysis,

The Relationship between Oil, Exchange Rates, and Commodity Prices

Exchange rates have long been thought to have an important impact on the export and import of goods and services, and, thus, exchange rates are expected to influence the price of those products that are traded. At the same time, energy impacts commodity production in some very important ways. The use of chemical and petroleum derived inputs has increased in agriculture over time; the prices of these critical inputs, then, would be expected to alter supply, and, therefore, the prices of commodities using these inputs. Also, agricultural commodities have been increasingly used to produce energy, thereby leading to an expectation of a linkage between energy and commodity markets. In this paper, we examine the price relationship through time of the primary agricultural commodities, exchange rates, and oil prices. Using overlapping time periods, we examine the cointegration relationship between prices to determine changes in the strength of the linkage between markets through time. In general, we find that commodity prices are linked to oil for corn, cotton, and soybeans, but not for wheat, and that exchange rates do play a role in the linkage of prices over time.cointegration, commodity prices, crude oil, exchange rates, Agribusiness, Consumer/Household Economics, International Relations/Trade, Marketing, Production Economics, Resource /Energy Economics and Policy, C32, L71, Q11, Q40,

Market Integration for Shrimp and the Effect of Catastrophic Events

Seasonal unit-root testing and seasonal cointegration methods are employed to investigate the price transmission in U.S. shrimp markets. ARIMA and Vector Error Correction Models (VECM) are used to identify the effect of catastrophic events on individual price series in one region and the spillover effects in the price series for other regions. Results showed that a cointegrating relation exists between neighboring states, specifically between Alabama and Mississippi and Louisiana and Texas. Cointegrating relations also exist between the Gulf States and the Pacific region, but not the Atlantic region, and the price of imported shrimp is cointegrated with each of the domestic shrimp price series. Finally, while Katrina had an effect on shrimp prices in Gulf States, the effect was not long lasting.catastrophic events, cointegration, market integration, seasonal unit-roots, spillover effects, Marketing, Risk and Uncertainty, C13, Q11, Q13,

Factors Influencing Marketing Margins in Cattle and Beef Markets

Livestock Production/Industries,

Overlapping data and hedge funds

We consider the overlapping data problem. The conventional estimation approach with overlapping data is to use the Newey-West estimation procedure. When the standard assumptions hold generalized least squares is asymptotically efficient. Monte Carlo results show that the Newey-West procedure has considerably larger variances of parameter estimates and lower power than GLS. Hypothesis tests using the Newey-West procedure also have incorrect size even with sample sizes as large as one thousand. We also discuss possible estimation approaches when overlapping data occurs in conjunction with some other econometric problem. With lagged dependent variables or errors in the explanatory variables, GLS is no longer the preferred estimator

The Impacts of Market Structure and Contracts on Agricultural Markets

Experimental markets were used to isolate the effects of market structure and contract design on market outcomes. Preliminary results suggest that market structure drives outcomes, and not necessarily contract design. Future research will replicate experiments and add dimensions of market information.Political Economy,

A New Taxonomy of Thin Markets

The traditional conception of a thin market based on transactions volume remains relevant in many agricultural markets but does not adequately frame emerging thin market issues. As non-price means of pricing goods becomes more common, some cash commodity markets have become residual markets. In some of these markets, not only the volume of transactions but also the representativeness of transactions to those on the related contract market is an important issue. This paper develops a concept of thin markets that accounts for this dimension of market thinness and proposes a research agenda related to this topic.Marketing,

Crop Supply Response under Risk: Impacts of Emerging Issues on Southeastern U.S. Agriculture

In this paper we consider factors that affect both crop prices and yields in order to examine supply responses of major crops in the Southeast. Due to the variable nature of crop production in the Southeast, previous studies that ignore price and yield risk may fail to capture one of the salient features of the region’s agriculture. Our results indicate supply elasticity values for corn, cotton, and soybeans of approximately 0.670, 0.506, and 0.195, respectively. Compared with the results of studies in other regions, corn and cotton acres respond more to price changes and soybean acres respond less to price changes.acreage supply, crop supply response model, risk analysis, Southeast U.S. agriculture, Crop Production/Industries, Production Economics, Q12, Q13, Q16,

Overlapping data problem

This is a preprint of an article whose final version has been published in Quantitative and Qualitative Analysis in Social Sciences, Social Sciences Research Network, 2009.Overlapping data are often used in finance and economics, but applied work often uses inefficient estimators. The article evaluates possible reasons for using overlapping data and provides a guide about which estimator to use in a given situation.Agricultural Economic