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The aim of this paper is to discuss the challenges in attracting and securing adequate budgets for departments of agricultural and applied economics, while recognizing that the institutional and political contexts matter. Agricultural and applied economics departments that operate with an entrepreneurial mindset, that maintain and grow their student numbers, and that have a vibrant demand for their extension and research activities will thrive. The good news is we often have considerable control over the factors that contribute to our longer‐term success. [ABSTRACT FROM AUTHOR]

Coronavirus 2019 (COVID‐19) has caused ongoing disruptions to U.S. meat markets via demand and supply‐side shocks. Abnormally high prices have been reported at retail outlets and meat packers have been accused of unfair business practices because of widening price spreads. Processing facilities have experienced COVID‐19 outbreaks resulting in shutdowns. Using weekly data on wholesale and retail prices of beef, pork, and poultry, we characterize the time series behavior and dynamic linkages of U.S. meat prices before the COVID‐19 pandemic. We model vertical price transmission using both linear and threshold autoregressive (AR) models and vector error correction (VEC) models. With the estimated models, we then compare price movements under COVID‐19 to model predictions. All three meat markets are well‐integrated and we observe unexpected, large price movements in April and May of 2020. Early COVID‐19 related shocks appear to be transitory with prices returning to expected levels at a pace consistent with the speed of transmission prior to the pandemic. This well‐functioning market process suggests a degree of resilience in U.S. meat supply chains. [ABSTRACT FROM AUTHOR]

This paper explores the behavior of real commodity prices over a 50–year period. Attention is given to how the shifting means for various commodity prices have changed with a special emphasis on behavior since the mid 2000s. To identify structural changes in commodity prices, we estimate shifting–mean autoregressions by using: the Bai and Perron (1998) procedure for determining structural breaks; low frequency Fourier functions; and a procedure that specifies shifts to be smooth logistic functions of time. We find that the pattern in the timing of shifts is suggestive of the causal factors underlying the recent boom. [ABSTRACT FROM AUTHOR]

Price dynamics for North American oriented strand board markets are examined. The role of transactions costs are explored vis-à-vis the law of one price. Nonlinearities induced by unobservable transactions costs are modeled by estimating time-varying smooth transition autoregressions (TV-STARs). Results indicate that nonlinearity and structural change are important features of these markets; price parity relationships implied by economic theory are generally supported by the estimated models. Implications for the efficiency of spatial market linkages and the dynamics associated with price adjustments are also examined. [ABSTRACT FROM AUTHOR]

We extend Holt and Bishop’s (2002) normalized quadratic inverse demand function by obtaining measures of precision of elasticities and consumer welfare loss estimates due to reductions in commercial landings in the U.S. Great Lakes. Even with curvature constraints imposed, confidence intervals are obtained by using the bootstrap, subsample bootstrap, and subsample jackknife. [ABSTRACT FROM AUTHOR]

This article reviews the major contributions of agricultural and resource economists in the area of econometrics over the past 100 years. Early on, a number of agricultural economists were in on the ground floor in terms of developing new econometric methods. Over time as the economics profession became more empirically oriented, agricultural and resource economists increasingly assumed the role of “early adopters” of new econometric methods. Even so, agricultural and resource economists continue to make useful modifications to econometric techniques in order to adapt the methods to the unique nature of the problems and applications that we study. [ABSTRACT FROM AUTHOR]

In recent years, the theoretical restrictions of consumer demand have been examined in post-sample forecasting exercises. However, this work has uniformly ignored associated curvature restrictions. In this paper we evaluate a series of Normalized Quadratic Inverse Demand System (NQIDS) specifications by using rolling windows and generating one- to four-step ahead forecasts. Data for eleven categories of South Atlantic fish spanning 1980 through 2001 are used in estimation. In addition to the NQIDS, we also examine the forecasting performance of a Cobb–Douglas model with autoregressive errors. We find that the best predictions are achieved using a composite forecast. [ABSTRACT FROM AUTHOR]

The article analyzes the structural changes that take place in the agricultural market with the help of time-series data. It uses an inverse demand model, Inverse Almost Ideal Demand System (IAIDS), to study the demand for meat in the U.S. It mentions that the methodology used is built on the time-varying regression models and also considers the possibility of structural change being continuous and nonmonotonic.

This article extends the recent literature on the Prebisch–Singer hypothesis of a long-run decline in the relative prices of primary commodities. Our main innovation is testing for and estimating nonlinear alternatives to a secular deterioration. Specifically, we use bootstrap procedures to test the linear unit root model against models belonging to the family of smooth transition autoregressions (STARs) for twenty-four commodities, 1900–2003. In nineteen cases we reject the linear null at usual significance levels. In sixteen cases we are able to successfully fit STAR-type models. Simulation results show there is little support for the Prebisch–Singer hypothesis. [ABSTRACT FROM AUTHOR]

The linearity of the U.S. hog–corn cycle has been questioned by Chavas and Holt (1991) . Even so, attempts have not been made to model the potential nonlinear dynamics in the hog–corn cycle by using regime-switching models. One popular alternative is Teräsvirta's smooth transition autoregressive (STAR) model, which assumes regime switching is endogenous and potentially smooth. In this article, we examine monthly data for the U.S. hog–corn cycle, 1910–2004. A member of the STAR family, the time-varying STAR, is fitted to the data and its properties examined. We find evidence of nonlinearity, regime-dependent behavior, and time-varying parameter change. [ABSTRACT FROM AUTHOR]

A statistically optimal inference about agents' ex ante price expectations within the US broiler market is derived using futures prices of related commodities along with a quasi-rational forecasting regression equation. The modelling approach, which builds on a Hamilton-type framework, includes endogenous production and allows expected cash price to be decomposed into anticipated and unanticipated components. We therefore infer the relative importance of various informational sources in expectation formation. Results show that, in addition to the quasi-rational forecast, the true supply shock, future prices, and ex post commodity price forecast errors have, at times, been influential in broiler producers' price expectations. [ABSTRACT FROM AUTHOR]

Examines the foreign exchange hedging ratios estimation alongside freight and commodity rations in portfolio framework. Reduction of uncertainty for traders by foreign exchange futures; Support of the result to cease trading of futures contract; Impact of low level of trading activity on hedging instrument.

Examines the effectiveness of using crude oil, heating oil and unleaded gasoline futures contracts to reduce price uncertainty for energy-traders. Development of a conceptual framework for crack spread hedging; Comparison between hedge ratio estimation techniques and multivariate GARCH model; Incorporation of the volatility spillovers between markets.

The reaction of labor markets to economic reforms is an important indicator of the progress of transition. Because of diminished government support and the breakup of state and collective enterprises, labor market adjustments in the transition economies have been particularly severe in the agricultural sector. This article evaluates the off-farm labor market for a sample of agrarian households in transition Bulgaria. We give particular attention to the distributional assumptions that underlie standard approaches to the evaluation of labor supply. A variety of specification tests are considered and support for standard maximum likelihood estimates which rely on normality as a maintained hypothesis is mixed. Alternative semiparametric (distribution-free) estimators are also considered. The empirical results indicate that, five years after the initiation of the transition, off-farm labor supply patterns for Bulgarian agricultural households are similar to what is commonly observed in developed market economies. Labor supply is positively affected by factors such as education and work experience which are hypothesized to increase off-farm wages. Social benefit programs providing monetary or in-kind support payments are shown to significantly decrease off-farm work. [ABSTRACT FROM AUTHOR]

This paper makes three related points useful in teaching first-year graduate production theory. First, the local applicability of the classical function coefficient idea for short-run nonhomogeneous production technologies is shown for returns to scale, satisfaction of second-order and total conditions for profit maximization, and delineation of the economic region of production in factor space. Second, the general applicability of Euler’s Theorem results to nonhomogeneous (variable-proportional-return) cases is developed. Lastly, it is shown that short-run, nonhomogeneous production/yield functions are fully consistent with long-run linear homogeneity. [ABSTRACT FROM AUTHOR]

In this paper we introduce inverse demand systems that include quadratic scale terms. These systems are similar to regular quadratic demand systems introduced by Howe, Pollak, and Wales. A unique feature of these specifications is that they maintain linear scale curves as a special case. For illustrative purposes we estimate the Normalized Quadratic Inverse Demand-Quadratic Scale System using monthly South Atlantic fish landings and valuation data, 1980-1996. In estimation concavity is maintained locally, and the rank reduction procedures advocated by Diewert and Wales (1988a) are employed. The estimated model is then used to obtain welfare estimates associated with catch restrictions. [ABSTRACT FROM AUTHOR]

Presents information on a study regarding price transmission and adjustment in the United States beef industry. Details on Threshold effect and modeling threshold autoregressive processes; Application of threshold tests on beef prices; Evaluation of the timing of shifts between the alternative regimes.

Examines the effectiveness of forecasting method in generating information raising the prices received by agricultural producer. Reduction of exposure to unfavorable price moves; Types of monthly forecasting model used in the study; Diversification of livestock and crop as a form of risk reduction.

The objective of this paper is to use a GARCH model to characterize the conditional mean and variance of expected price in an aggregate supply equation for the U.S. broiler industry. Unlike previous studies, a full information maximum likelihood (FIML) estimator is used to simultaneously model a price equation with GARCH errors and a structural supply equation with risk. The resulting estimator is closely related to the multivariate GARCH models described by Engle and Bollerslev [16] and the ARCH-M model of Engle, Lilien, and Robins [17]. Also, by using FIML to simultaneously estimate the price, production, and conditional variance equations, we avoid many of the estimation problems associated with other methods [33]. This paper has explored the potential for using a new method to estimate risk effects in aggregate supply equations. Specifically, a time-series procedure known as GARCH processes was presented as an alternative for modeling producers' subjective price and risk expectations. GARCH models differ from standard time-series models in that the conditional variance of the underlying stochastic process is specified as a function of past realizations of the random variable of interest. The result is that the conditional variance derived from a GARCH process will vary over time. Moreover, the modeling procedure developed here is similar to that proposed by Engle and Bollerslev [16] for the multivariate GARCH model and Engle, Lilien, and Robins [17] for the ARCH-M model in that the parameters of the production, price, and conditional variance equations were estimated simultaneously. [ABSTRACT FROM AUTHOR]

Determines role of risk in beef marketing channel. Generalized auto regressive conditional heteroskedalicity-in-mean (GARCH-M) model; Issues in retail price expectations and time-varying risk measures; Application of GARCH-M model on test data; Risk assessment.

Investigates the potential role of nonlinear dynamics in generating market stability using a simple market equilibrium model of the American dairy industry. Instability and chaos; Price analysis.

Discusses a multimarket bounded price variation model (BPVM) for agricultural commodities in the United States. Framework for estimating BPVM; Multimarket model in the corn and soybean markets; Market equilibrium effects of removing price support and acreage set-aside programs.

Evaluates the hog-corn price ratio using new methods for analyzing nonlinear dynamic processes in the United States. Focal point of dynamic analysis; Chaos associated with a general system of state equations; Tools for nonlinear dynamic analysis.

Analysis an acreage supply response model developed under expected utility maximization. Use of the model to specify and estimate a system of risk-responsive acreage equations for corn and soybeans in the United States; Truncation effects of government price supports on the distribution of corn and soybean prices; Inclusion of wealth variable in the acreage equation.

This study examines the empirical implications of extending the rational expectations hypothesis (REH) to include price uncertainty. A general estimation framework that incorporates both the restrictions on structural parameters and the variance-covariance terms is developed. GARCH time-series processes are used to generate time-varying expectations of both the means and the variances of exogenous variables. The empirical application is with a quarterly model of the U.S. broiler industry; the results indicate that the rational expectation of price variance is an important determinant of broiler supply. A formal test indicates that the restrictions implied by the REH cannot be rejected. [ABSTRACT FROM AUTHOR]