The conventional wisdom that technological advances in seed breeding and genetic modification of corn traits have lowered yield risk has recently been challenged by research that argues that the converse is true. The implications of this research have been applied to models of climate change and have led to the conclusion that these advances have actually increased agronomic risk, such that climate change is asserted to raise important concerns regarding the stability and viability of agricultural output in the future. In a large body of empirical work, the argument is based upon assertions that corn yields have become more sensitive to weather stresses. This increased sensitivity has coincided with the introduction of a variety of genetically engineered (GE) crops in the 1990s and 2000s. We use corn yields and data from the US federal crop insurance program to evaluate these claims. An initial examination of yield responses to droughts in 1988 and 2012 suggests more robust yields in the latter period, in spite of very comparable weather stresses. We next consider side-by-side data collected under the Biotech Endorsement (BE) to the federal crop insurance program between 2008 and 2011. This endorsement provided substantial discounts for growers using certain GE hybrids, reflecting policymakers' beliefs that these hybrids had lower yield risk. We find that risk, as measured by the rate of indemnities paid per units insured, was significantly lower for crops insured under the BE. We also find that the difference in risk tends to be greater when growing conditions are less favorable.

The long-distance transport of live sheep, cattle and goats by ship from Australia to Asia and the Middle East is an ongoing, contentious issue in Australia due to concern for the welfare of the animals during and after the voyage. This concern has been driven by internet-based and televised campaigns against animal cruelty which have triggered a significant reaction of anger from the Australian public. This study investigates a novel method of capturing and measuring the impact of these concerns on Australian meat demand. This is done by incorporating an aggregated live export Google Trends index as a proxy for consumer response to live export information in a demand system for Australian meat. This study provides an alternative method for capturing consumer response to non-traditional demand shift variables and provides insight into how Australian meat demand is affected by interest in the live export trade, as well as price, income, seasonality and pre-committed consumption.

Pre-committed consumption represents the portion of demand that is determined by non-price and non-income factors. This study uses quarterly data to estimate a Generalised Almost Ideal Demand System (GAIDS) to test for the existence of pre-committed meat consumption in Australia. Two specifications are estimated to evaluate the impact of seasonal and time trend factors on pre-committed demand. Evidence is found for the existence of pre-committed chicken consumption when jointly estimated with seasonal and time trend factors. Results support improved demand modelling of Australian meat consumption using the GAIDS and provide insights into how Australian meat demand is affected by price, expenditures, pre-committed consumption, seasonality, and trends.

In the event of wind-borne disease outbreaks, farmers have traditionally purchased insurance plans that issue indemnity payments upon infection. This paper highlights a possible alternative to standard programs by assessing potential benefits to infected area farmers through a check-off program. A simulation is conducted assuming three outbreak scenarios using Asian soybean rust (ASR) as a case and data collected by a USDA soybean rust tracking system. Results revealed that at 33.2, 39.4, and 59.3% probabilities of spread, the benefits to soybean producers after infestation are greater than the standard policy under the spread scenarios with $160.95, $221.31, and $527.21 million. Key words: Wind-borne disease, soybean rust, indemnity payments, check-off.

We investigate how to theoretically and empirically measure pre-committed quantities through price formation utilizing translating in the consumer distance function. The translated consumer distance function is defined as a dual to the translated utility, indirect utility, and expenditure functions. Translating procedures also provide more general analytical means to incorporate pre- committed quantities (and other shift or demographic variables) into inverse demand systems. This approach yields a class of inverse demand functions that can nest most known functional forms. For example, the Inverse Generalized Almost Ideal Demand (IGAI) model can be formed by applying translating procedures to the Inverse Almost Ideal Demand model. An empirical example of the IGAI model with inferences on the translating parameters themselves is provided for illustrative purposes.

In 2002, corn rootworm was estimated to have caused yield losses and control costs that exceeded $1 billion [1]. That was before the advent of corn rootworm-resistant biotech traits. Up to that time, a one-year corn rotation had been effective in limiting corn rootworm damages. However, the development of two opportunistic rootworm variants—the soybean variant and the extended diapause variant— resulted in decreasing yield and increasing control costs even with crop rotation. Subsequently, beginning in 2003 farmers began planting genetically engineered corn rootwormresistant varieties. Figure 1 plots the striking increase in acreage planted to corn with the rootworm-resistant trait since then.

Uncertain and changing economic conditions can have substantial effects on price relationships in spatially separated, linked markets. Although numerous studies have analysed price relationships to characterize market linkage structures, most assume that the relationships and associated linkages are time invariant. This study extends the literature by modelling and estimating time-dependent market linkages that are conditional on changes in exogenous factors. The methodology is used to investigate price relationships in North Carolina (NC) corn and soya bean markets. Empirical results indicate that generalized market-linkage models provide a better representation of price relationships over time, improving the understanding of price discovery dynamics and marketing strategies.

We pursue two distinct approaches to measuring the stability and validity of conventional approaches to measuring acreage response. Our focus is on corn and soybeans, which have perhaps been the most significantly impacted of the main commodities by market and policy changes. As noted, much of the change impacting commodity markets has been triggered by bio–energy policies, with ethanol from corn being the most prominent renewable fuel targeted by these policies. These policies have included ethanol tariffs and tax–credits for gasoline blenders. We first consider the structural stability of a standard acreage response model of the form often estimated in the empirical literature (see, for example, the seminal paper of Chavas and Holt (1990)). We apply structural change tests capable of identifying structural changes occurring at unknown break points and at the ends of a data series. The latter approach to testing is especially important in this application since the most substantial changes in markets have occurred since the 2007 Energy Independence Act. We then consider an analogous empirical evaluation of acreage response using panel data made up of annual observations taken at the crop reporting district (CRD) in the major corn producing states (i.e., the Corn Belt). We apply the newly developed inferential technique suggested by Cameron, Gelbach, and Miller (2011) that permits one to account for multi–dimensional clustering in panel data. Implications for modeling acreage response under changing market and policy conditions are discussed.

An extensive empirical literature has examined the behavior of crop yields over time. Corn yields have been characterized by signficant increases reflecting an array of technological developments that have substantially boosted productivity. While much of the focus has been on modeling deterministic and possibly stochastic trends in yields over time, an equally important question involves the extent to which yield changes may occur in response to price. This paper addresses two dimensions of this issue. We first look at the extent to which realized yields (i.e., at harvest) tend to be influenced by planting{time quotes of post{harvest futures contracts. Second, we examine the potential for intra{seasonal responsiveness of yields to significant price swings. The latter response is especially important in light of recent arguments that weather offers identification through instruments that are completely exogenous to market conditions; a view often expressed in terms of a natural experiment. We challenge this argument by finding that the potential does exist for yields to be affected by significant price changes that occur early in the growing season.

Introduction Corn rootworm (Diabrotica spp.) causes extensive economic damage in the United States. Before the advent of the corn-rootworm-resistant biotech traits, populations of western corn rootworm (D. virgifera virgifera) and northern corn rootworm (D. barber) together were estimated to cause annual yield losses and control costs that exceeded $1 billion in 2002 (Mitchell, Gray, & Steffey, 2002). The larvae hatch in the spring and feed on corn roots for several weeks. The damage to the roots can result in stunted growth of the corn plant, lodging, and eventual yield losses. Root damage may also make the corn plant less tolerant to environmental stresses such as heat and drought. In general, corn rootworms (CRW) cannot complete their life cycle without the food supplied by corn plants. A one-year corn rotation has been an effective strategy to limit the damage caused by rootworms. Lately, however, two opportunistic variants of the CRW have developed, making this former management strategy somewhat less effective. One variant, the rotation-resistant, or soybean-variant (SBV), CRW has developed the ability for females to lay their eggs in crops other than corn. A variant of the northern CRW, the extended diapause variant (EDV) has adapted such that some of the eggs hatch after two winters and, thus, the larval stages are able to feed on corn roots even in rotated corn. These variants have resulted in decreasing yield and increasing control costs in recent years. Figures 1 and 2 reveal the extent of the infestation of the northern and western CRW types in the United States as of 2009. As one can see from these figures, CRW has become a problem in the major corn-growing areas. Biotech traits for CRW protection were first introduced in the United States in 2003 with Monsanto’s YieldGard® rootworm trait, which was closely followed by Dow Agrosciences’ Herculex RW® trait in 2005 and Syngenta Seeds’ MIR 604 in 2007. In 2005, the first trait combination consisting of aboveand belowground insect protection and herbicide tolerance (or stacked hybrids) was introduced by Monsanto with its YieldGard® Plus with Roundup Ready® Corn 2, which was closely followed by similar products from other industry providers. These first-generation products contained a single insecticidal protein for above-ground protection of lepidopteron larvae and a single insecticidal protein for protection against CRW larvae. To prolong the durability of these insect protected products, Monsanto successfully combined two proteins each for aboveand below-ground insect protection, thereby protecting the plant with multiple modes of action targeting the same insects. Perhaps the most unique innovation yet in this regard is the introduction of SmartStax® corn, which includes eight biotechnology traits “stacked” together—six for insect protection (Bt) and two for herbicide tolerance. SmartStax® was created through collaboration between Monsanto and Dow AgroSciences Michele C. Marra, Nicholas E. Piggott, and Barry K. Goodwin North Carolina State University Recently, one type of corn rootworm has developed resistance to a single strain of Bacillus thuringiensis (Bt) that is genetically engineered into corn seed. This resistance development has occurred in small, localized areas of the Corn Belt, where corn has been grown continuously for a period of time. Some have suggested that the remedy for this problem is to revert back to a significantly higher-percentage, structured refuge to avoid further resistance development. This article explores the economic consequences of such a plan. Those consequences include lower average corn yields, leading to higher corn prices for all consumers of corn (including livestock producers) and corn sweetener, ethanol producers, and consumers of corn globally; less net income for corn producers; higher yield variability, leading to higher price volatility; negative environmental impacts; and higher human-safety risks. A more balanced approach to the problem is recommended; this includes best management, integrated pest-management practices, a phasing out of single corn rootworm-traited corn, and increased use of multiple corn rootworm-traited corn.

Wind-borne diseases can spread rapidly and cause large losses. Producers may have little incentive to prevent disease spread because prevention may not be welfare-maximizing. This study proposes a market-based mitigation program that indemnifies producers against disease-related losses and provides an incentive to neighboring producers to take preventive action, which can substantially mitigate infestations, reduce the likelihood of catastrophic losses, and increase social welfare. An equilibrium displacement model simulates introduction of the program for U.S. soybeans. Simulations reveal that the market-based solution contributes to minor market distortions but also reduces social welfare losses and could succeed for other at-risk commodities.

This article provides an overview of the literature on consumer and demand system analysis with emphasis on complete food demand systems. It presents theoretical foundations, constrained utility maximization, properties, and general demand restrictions. It discusses dual functions, including the expenditure function, the indirect utility function, and the distance function. The first three dual approaches are standard tools of the applied demand system analyst. Then it introduces the issue of welfare effects and integrability along with separability and aggregation. The article also provides a review of functional forms and covers econometric issues that include estimation, inference and hypothesis testing, specification tests, and other empirical issues. Models of the almost ideal demand and inverse systems as well as some additional hypothesis tests and inferences regarding model performance are estimated and reported.