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Barges on the Mississippi River system are traded via a forward market. We find that risk premiums to use this market vary by season and in terms of which party bares the cost of forward contracting. During the summer season barge operators pay a risk premium. Yet during the rest of the year, elevator operators pay a premium to lock in rates.
Bradley Isbell; Andrew M. McKenzie; Wade Brorsen. The cost of forward contracting in the Mississippi barge freight river market. Agribusiness 2019, 36, 226 -241.
AMA StyleBradley Isbell, Andrew M. McKenzie, Wade Brorsen. The cost of forward contracting in the Mississippi barge freight river market. Agribusiness. 2019; 36 (2):226-241.
Chicago/Turabian StyleBradley Isbell; Andrew M. McKenzie; Wade Brorsen. 2019. "The cost of forward contracting in the Mississippi barge freight river market." Agribusiness 36, no. 2: 226-241.
The CIF NOLA “river market” represents an important but opaque forward market that serves Gulf exporters and elevators. CIF NOLA bids function similarly to traditional forward contracts; however, like a futures market, firms can offset their forward contractual obligations by offsetting positions in a liquid off-exchange paper market. Analysis shows grain sellers pay a risk premium for fall harvest delivery contracts. However, outside of fall harvest, contract liquidity, coupled with a good institutional balance of long and short market participants, mostly removes the pricing bias commonly found in farmer forward contracting in corn and soybeans.
Andrew M. Mckenzie; Bradley J. Isbell; Wade Brorsen. THE COST OF FORWARD CONTRACTING IN THE CIF NOLA EXPORT BID MARKET. Journal of Agricultural and Applied Economics 2019, 51, 164 -181.
AMA StyleAndrew M. Mckenzie, Bradley J. Isbell, Wade Brorsen. THE COST OF FORWARD CONTRACTING IN THE CIF NOLA EXPORT BID MARKET. Journal of Agricultural and Applied Economics. 2019; 51 (1):164-181.
Chicago/Turabian StyleAndrew M. Mckenzie; Bradley J. Isbell; Wade Brorsen. 2019. "THE COST OF FORWARD CONTRACTING IN THE CIF NOLA EXPORT BID MARKET." Journal of Agricultural and Applied Economics 51, no. 1: 164-181.
Commodity futures markets play an important role, through risk management and price discovery, in helping firms make sustainable production and marketing decisions. An important related issue is how pricing signals between futures exchanges impact traders’ risk. We address this issue by shedding light on risk transmission between the most mature (U.S.) and the fastest growing (Chinese) commodity futures markets. Gaining greater insight of risk transmission between these key markets is vitally important to firms engaged in the efficient and sustainable trade of commodities needed to feed the world. We examine the risk transmission between Chinese and U.S. agricultural futures markets for soybean, corn, and sugar with a Copula based conditional value at risk (CoVaR) approach. We find significant upside, and to a lesser extent downside risk transmission, between Chinese and U.S. markets. We confirm the dominant pricing role of U.S. agricultural futures markets while acknowledging the increasing price discovery role performed by Chinese markets. Our results highlight that soybean markets exhibit greater risk transmission than sugar and corn markets. We argue that our findings may be explained by Chinese government policy intervention, and by the large role played by U.S. firms in the underlying cash commodity markets–both in terms of production and trade.
Yangmin Ke; Chongguang Li; Andrew M. McKenzie; Ping Liu. Risk Transmission between Chinese and U.S. Agricultural Commodity Futures Markets—A CoVaR Approach. Sustainability 2019, 11, 239 .
AMA StyleYangmin Ke, Chongguang Li, Andrew M. McKenzie, Ping Liu. Risk Transmission between Chinese and U.S. Agricultural Commodity Futures Markets—A CoVaR Approach. Sustainability. 2019; 11 (1):239.
Chicago/Turabian StyleYangmin Ke; Chongguang Li; Andrew M. McKenzie; Ping Liu. 2019. "Risk Transmission between Chinese and U.S. Agricultural Commodity Futures Markets—A CoVaR Approach." Sustainability 11, no. 1: 239.
Government crop data have been shown to contribute to the efficient operation of agricultural commodity markets. In 2013, the USDA curtailed its crop report publication for the first time in decades due to an appropriations lapse, thereby offering the chance to study the impact on markets of missing government data. As expected, derivatives markets for corn and soybeans did not display characteristic short-run patterns in terms of uncertainty resolution and price changes that are normally observed around scheduled USDA release times. We are unable to detect evidence of a prolonged period of heightened uncertainty, realized volatility around the missing report, or abnormal pricing errors in the absence of government data. However, an unsurprisingly large 2013 corn and soybean crop could confound that attempt.
Michael Adjemian; Robert Johansson; Andrew McKenzie; Michael Thomsen; Spiro Stefanou. Was the Missing 2013 WASDE Missed? Applied Economic Perspectives and Policy 2017, 40, 653 -671.
AMA StyleMichael Adjemian, Robert Johansson, Andrew McKenzie, Michael Thomsen, Spiro Stefanou. Was the Missing 2013 WASDE Missed? Applied Economic Perspectives and Policy. 2017; 40 (4):653-671.
Chicago/Turabian StyleMichael Adjemian; Robert Johansson; Andrew McKenzie; Michael Thomsen; Spiro Stefanou. 2017. "Was the Missing 2013 WASDE Missed?" Applied Economic Perspectives and Policy 40, no. 4: 653-671.
Rice is a predominant food staple in many regions of the world, and it is important to determine how efficiently the U.S. rice market helps to ensure world food security. This question can be answered by gauging the price discovery performance of the U.S. rice futures market and the economic usefulness of the U.S. government's supply and demand forecasts. So, to this end, we employ two event study approaches: (1) to examine variability in returns on report-release days as compared to returns on pre- and post-report days, and (2) to regress price reactions on changes in usage and production information. It is found that the USDA provides the rice futures markets with valuable information and rice futures respond to the information in an economically consistent manner.
Andrew M. McKenzie; Jessica L. Darby. Information Content of USDA Rice Reports and Price Reactions of Rice Futures. Agribusiness 2016, 33, 552 -568.
AMA StyleAndrew M. McKenzie, Jessica L. Darby. Information Content of USDA Rice Reports and Price Reactions of Rice Futures. Agribusiness. 2016; 33 (4):552-568.
Chicago/Turabian StyleAndrew M. McKenzie; Jessica L. Darby. 2016. "Information Content of USDA Rice Reports and Price Reactions of Rice Futures." Agribusiness 33, no. 4: 552-568.
There is a widely held belief among public consumers that rice prices are manipulated in Bangladesh. This manipulation may have led to price asymmetry in the vertical chain of Bangladesh rice markets. This paper is an attempt to investigate the existence of asymmetry between wholesale and retail rice prices in Bangladesh. Maximum likelihood estimation (MLE) based cointegration test was applied to determine long-run equilibrium relationship. We examine whether the wholesale market dominates the retail market—in terms of price discovery and price leadership—or vice versa. Finally, we analyze whether the wholesale-retail price relationship is asymmetric with respect to price increases and price decreases. To test the asymmetric price transmission we used the asymmetric error correction-EG approach. Our results show that wholesale and retail prices are cointegrated, and wholesale market plays a leadership role in determining retail prices, which is in line with industrial organization theory. Our results confirm the fear and concerns of consumers about the existence of price asymmetry. [JEL Classification: Q110; Q113].
Mohammad Jahangir Alam; Andrew M. McKenzie; Ismat Ara Begum; Jeroen Buysse; Eric J. Wailes; Guido Van Huylenbroeck. Asymmetry Price Transmission in the Deregulated Rice Markets in Bangladesh: Asymmetric Error Correction Model. Agribusiness 2016, 32, 498 -511.
AMA StyleMohammad Jahangir Alam, Andrew M. McKenzie, Ismat Ara Begum, Jeroen Buysse, Eric J. Wailes, Guido Van Huylenbroeck. Asymmetry Price Transmission in the Deregulated Rice Markets in Bangladesh: Asymmetric Error Correction Model. Agribusiness. 2016; 32 (4):498-511.
Chicago/Turabian StyleMohammad Jahangir Alam; Andrew M. McKenzie; Ismat Ara Begum; Jeroen Buysse; Eric J. Wailes; Guido Van Huylenbroeck. 2016. "Asymmetry Price Transmission in the Deregulated Rice Markets in Bangladesh: Asymmetric Error Correction Model." Agribusiness 32, no. 4: 498-511.
We extract low- and high-frequency volatility from China’s Shanghai gold futures market using an asymmetric Spline-GARCH (ASP-GARCH) model. We then regress monthly low-frequency volatility on selected monthly macroeconomic indicators to study the impact of macroeconomy on gold futures market and to test for excess volatility. Our main result is volatility in China’s Shanghai gold futures market resulting from both macroeconomic fluctuations and investor behaviour. Chinese Consumer Price Index Volatility and US dollar volatility are the two main determinants of low-frequency gold volatility. We also find significant evidence of excess volatility, which can in part be explained in terms of loss-aversive investor behaviour.1. IntroductionThe price of gold has undergone a series of drastic fluctuations since the 2008 global financial crisis. By September 2011, gold prices had climbed to an unprecedented high level of $1921 per troy ounce from a level of $682 per troy ounce in October 2008. However, gold prices quickly dropped by $400 per troy ounce in merely 20 trading days following this historic peak. Since 2012 gold price volatility has continued unabated with many macroeconomic factors such as the global economic recovery and appreciating the US dollar—according to analysts—potentially playing a driving role. However, extremely large gold price shocks such as a 14.8% decline that occurred over a three-day trading period in April 2013 have puzzled both academicians and industry analysts alike [1]. As a precious metal, gold is widely regarded as both a store of wealth and an inflation hedge and there is much interest in the investment community in determining if gold price volatility is simply excessive noise or is driven by sound macroeconomic fundamentals.The Efficient Market Hypothesis (EMH) asserts that asset prices only respond to changes in fundamentals [2]. This has driven a large body of the literature to explore possible macroeconomic variables that can explain gold market volatility. For example, Wang et al. [3] found that the US dollar, crude oil prices, and global stock market performance had a significant impact on Shanghai’s gold futures market. Tully and Lucey [4] similarly looked to macroeconomic effects to explain gold price shocks. They employed an asymmetric power GARCH model (APGARCH) to show that the US dollar is the main macroeconomic variable which influences gold. In contrast, Batten et al. [5] showed that gold price volatility responded primarily to monetary variables like M2 (broad money) and the inflation rate. In addition, Christie-David et al. [6] and Cai et al. [7] reported that announcements of macroeconomics news have a significant impact on gold prices.The methodological approaches used in previous studies suffer from two noticeable flaws. First, prior research has utilized traditional GARCH-type models which set unconditional volatility as a constant and consequently are unlikely to capture the true dynamics of long-run market volatility. Long-run volatility is equivalent to low-frequency volatility which is assumed to be determined by slowly evolving macroeconomic variables, while high-frequency or short-run volatility is mainly attributed to noise.Second, the observed frequency of macroeconomic variables does not synchronize with observed gold prices. Macroeconomic variables are generally compiled monthly or even quarterly while gold prices are reported daily or intradaily. Incorporating variables with different frequencies in the same model creates econometric modeling difficulties.To address these issues, Engle and Rangel [8] and Rangel and Engle [9] developed Spline-GARCH and an asymmetric Spline-GARCH (ASP-GARCH) model which relax the assumption that unconditional volatility is constant. They use a quadratic spline to isolate the proportion of variation in daily price data that is plausibly caused by macroeconomic variables. Then, using the isolated variation, Engle and Rangel [8] construct a measure of low-frequency volatility in the same sampling frequency as macroeconomic data, which effectively bridges high-frequency commodity price with its low-frequency macroeconomic determinants. Karali and Power [10] followed Engle and Rangel [8] and decomposed daily price volatility into high- and low-frequency components. They found that low-frequency volatility in US gold futures market responds strongly to changes in the industrial production index, consumer price index, and the US dollar. However, to our knowledge, this modelling approach has not been used to study factors affecting volatility in China’s gold futures market, which is the primary objective of this paper.Although much research efforts have been devoted to studying the macroeconomic determinants of gold price volatility, it remains unclear whether these macroeconomic determinants sufficiently explain the high levels of observed gold market volatility. In this paper we examine whether Chinese gold futures market exhibits “excess volatility,” a term first coined by LeRoy and Porter [11] and Shiller [12] and attributed to the portion of an asset’s volatility that cannot be explained by fundamentals. Evidence of excess volatility poses a challenge to the Efficient Market Hypothesis (EMH)—the cornerstone of traditional finance theory—first outlined in Malkiel and Fama [2]. A growing body of the literature spanning the last 40 years has accumulated significant empirical evidence of excess volatility in a variety of financial markets. For example, De Long and Becht [13] reported excess volatility in German stock market after the Second World War. Similarly, Campbell and Cochrane [14] showed that US stock market volatility is far greater than dividend volatility. This result indicates that, contrary to the EMH, movements in dividends cannot be the sole determining factor of stock market volatility. There is also considerable evidence of excess volatility in Chinese stock and bond markets (e.g., [15–19]). Our paper extends this literature by shedding light on whether excess volatility is a prevalent feature of Chinese gold futures market.The EMH and “Homo Economicus Assumption” fail to provide us with a widely accepted explanation of excess volatility in financial market. Proponents of behavioural finance would argue that classical theories fail because people are not rational in the classical economic sense. A number of studies grounded in behavioural finance theory—where market actors are assumed to be susceptible to cognitive biases—have been relatively successful in explaining excess volatility in stock markets. For example, investor sentiment has been shown to be a good explanation of excess volatility [18, 20–22]. Drawing from Kahneman and Tversky’s prospect theory, Barberis et al. [23] found that stock market investors are loss-aversive and their utility is affected by their previous investment returns. As a result, this form of loss aversion changes investors’ required risk premium and hence impacts market volatility. In a similar vein, a recent study by Wang and Hua [24] found that volatility in China’s copper futures markets correlates with investors’ loss aversion, which supports the claim that investors’ behaviour affects futures markets volatility.In this paper we use an ASP-GARCH model to extract low-frequency volatility in China’s gold futures market and its response to changes in macroeconomic variables. We find evidence of excess volatility in the market, which we explain in a behavioural framework following Barberis et al.’s [23] loss aversion modelling approach. Our main contributions are as follows: we present the first empirical study to extract low-frequency volatility in China’s gold futures market; we are able to explain a portion of low-frequency volatility in terms of macroeconomic news; and we find significant evidence of excess volatility in China’s gold futures market, which we at least in part explain in terms of investor loss aversive behaviour.2. Modelling Approach and Hypotheses Testing2.1. ASP-GARCH ModelThe assumption underlying almost all traditional GARCH models is that volatility is mean reverting to a constant level and unconditional volatility is constant. However, the mean reverting assumption has been greatly challenged by observation of real market movements. For example, it is widely recognized that volatility is higher during recessions and following “news” announcements [8]. Traditional GARCH model does not adequately capture the low-frequency changes in unconditional volatility whereas it is generally useful in modelling high-frequency conditional volatility. To address this issue Engle and Rangel [8] proposed a semiparametric Spline-GARCH model which relaxes the assumption that volatility is mean reverting to a constant level. To better understand how the Spline-GARCH model works, it is helpful for us to briefly review the traditional GARCH model. Bollerslev [25] proposed the GARCH model:where is the investment return at time , the expectation is conditional on an information set at time , is the innovation term assumed to be distributed with mean 0 and variance 1, again conditioned upon the information set at time , denotes the conditional variance of returns for period , and is a function of past errors and squared errors and variances observed at time . The terms , , and are the estimated coefficients on these conditional variance ARCH and GARCH terms. Equation (1) is the mean equation and (2) is the conditional variance equation.Following Engle and Rangel [8], and focusing on the long-run properties of the model, the conditional variance equation can be rewritten in terms of the unconditional variance:where is the unconditional variance. However, this model designed to capture conditional volatility fails to model long-term trends in unconditional volatility. When , the unconditional variance reverts to its mean value at a geometric rate of . Therefore, as noted by Engl
Song Liu; Tingfei Tang; Andrew M. McKenzie; Yibin Liu. Low-Frequency Volatility in China’s Gold Futures Market and Its Macroeconomic Determinants. Mathematical Problems in Engineering 2015, 2015, 1 -8.
AMA StyleSong Liu, Tingfei Tang, Andrew M. McKenzie, Yibin Liu. Low-Frequency Volatility in China’s Gold Futures Market and Its Macroeconomic Determinants. Mathematical Problems in Engineering. 2015; 2015 ():1-8.
Chicago/Turabian StyleSong Liu; Tingfei Tang; Andrew M. McKenzie; Yibin Liu. 2015. "Low-Frequency Volatility in China’s Gold Futures Market and Its Macroeconomic Determinants." Mathematical Problems in Engineering 2015, no. : 1-8.
Michael Thomsen; Andrew M. McKenzie; Gabriel J. Power. Was there a peso problem in cattle options? Agricultural Finance Review 2013, 73, 526 -538.
AMA StyleMichael Thomsen, Andrew M. McKenzie, Gabriel J. Power. Was there a peso problem in cattle options? Agricultural Finance Review. 2013; 73 (3):526-538.
Chicago/Turabian StyleMichael Thomsen; Andrew M. McKenzie; Gabriel J. Power. 2013. "Was there a peso problem in cattle options?" Agricultural Finance Review 73, no. 3: 526-538.
This paper investigates nonlinear dynamics in monthly rice prices of 16 regions in the Philippines at three levels: farm gate, wholesale and retail, over the period of January 1990 to December 2012. We used a series of tests to investigate whether the regional prices are characterized by linear processes or non-linear smooth transition autoregressive (STAR)-type dynamics. Results indicate that STAR-type nonlinearity exists in several regions, and particularly for farm gate prices. The most common process is a logistic STAR dynamic characterizing an asymmetric price behavior determined by two regimes and a smooth switching process.
Valerien O. Pede; Harold Glenn A. Valera; Mohammad Jahangir Alam; Andrew M. McKenzie. Nonlinearities in Regional Rice Prices in the Philippines: Evidence from a Smooth Transition Autoregressive (STAR) Approach. 2013, 1 .
AMA StyleValerien O. Pede, Harold Glenn A. Valera, Mohammad Jahangir Alam, Andrew M. McKenzie. Nonlinearities in Regional Rice Prices in the Philippines: Evidence from a Smooth Transition Autoregressive (STAR) Approach. . 2013; ():1.
Chicago/Turabian StyleValerien O. Pede; Harold Glenn A. Valera; Mohammad Jahangir Alam; Andrew M. McKenzie. 2013. "Nonlinearities in Regional Rice Prices in the Philippines: Evidence from a Smooth Transition Autoregressive (STAR) Approach." , no. : 1.
The article examines the dynamic relationship between the world and the domestic market price of rice for Bangladesh given agricultural trade liberalization. A Johansen multivariate cointegration test was used, followed by an error correction model. Results show that there exists a long-run unidirectional equilibrium relationship, meaning that the domestic prices adjust to the world prices but not vice versa. Our results highlight the dependence of the Bangladeshi rice market on the world rice market and underline the need for adequate policies which specifically address the issue of food security when world prices are very high. The goal of such policies should be to dampen or reduce domestic price volatility induced by the world market.
Mohammad Jahangir Alam; Jeroen Buysse; Andrew M. McKenzie; Ismat Ara Begum; Eric J. Wailes; Guido Van Huylenbroeck. The dynamic relationships between world and domestic prices of rice under the regime of agricultural trade liberalization in Bangladesh. Journal of the Asia Pacific Economy 2012, 17, 113 -126.
AMA StyleMohammad Jahangir Alam, Jeroen Buysse, Andrew M. McKenzie, Ismat Ara Begum, Eric J. Wailes, Guido Van Huylenbroeck. The dynamic relationships between world and domestic prices of rice under the regime of agricultural trade liberalization in Bangladesh. Journal of the Asia Pacific Economy. 2012; 17 (1):113-126.
Chicago/Turabian StyleMohammad Jahangir Alam; Jeroen Buysse; Andrew M. McKenzie; Ismat Ara Begum; Eric J. Wailes; Guido Van Huylenbroeck. 2012. "The dynamic relationships between world and domestic prices of rice under the regime of agricultural trade liberalization in Bangladesh." Journal of the Asia Pacific Economy 17, no. 1: 113-126.
Valeri Natanelov; Mohammad J. Alam; Andrew M. McKenzie; Guido Van Huylenbroeck. Is there co-movement of agricultural commodities futures prices and crude oil? Energy Policy 2011, 39, 4971 -4984.
AMA StyleValeri Natanelov, Mohammad J. Alam, Andrew M. McKenzie, Guido Van Huylenbroeck. Is there co-movement of agricultural commodities futures prices and crude oil? Energy Policy. 2011; 39 (9):4971-4984.
Chicago/Turabian StyleValeri Natanelov; Mohammad J. Alam; Andrew M. McKenzie; Guido Van Huylenbroeck. 2011. "Is there co-movement of agricultural commodities futures prices and crude oil?" Energy Policy 39, no. 9: 4971-4984.
The response of Arkansas Delta and Gulf soybean basis levels to barge rate shocks is investigated. Results suggest basis levels react negatively to an increase in the barge rate, implying the burden of higher transportation costs are at least in part transmitted to the farm level. Internal Arkansas Delta markets are highly integrated with the Gulf export market. For example, Gulf soybean shocks, which reflect unexpected increases in soybean export demand, are simultaneously transmitted to internal markets, and result in correspondingly higher Arkansas Delta basis levels. Domestic market disturbances such as crush margin and financial storage cost shocks are found to immediately affect barge rates and to subsequently impact both Gulf and internal basis levels. [EconLit citations: F150.] © 2005 Wiley Periodicals, Inc. Agribusiness 21: 37-52, 2005.
Andrew M. McKenzie. The effects of barge shocks on soybean basis levels in Arkansas: A study of market integration. Agribusiness 2005, 21, 37 -52.
AMA StyleAndrew M. McKenzie. The effects of barge shocks on soybean basis levels in Arkansas: A study of market integration. Agribusiness. 2005; 21 (1):37-52.
Chicago/Turabian StyleAndrew M. McKenzie. 2005. "The effects of barge shocks on soybean basis levels in Arkansas: A study of market integration." Agribusiness 21, no. 1: 37-52.
Andrew M. McKenzie; Michael R. Thomsen; Bruce L. Dixon. The performance of event study approaches using daily commodity futures returns. Journal of Futures Markets 2004, 24, 533 -555.
AMA StyleAndrew M. McKenzie, Michael R. Thomsen, Bruce L. Dixon. The performance of event study approaches using daily commodity futures returns. Journal of Futures Markets. 2004; 24 (6):533-555.
Chicago/Turabian StyleAndrew M. McKenzie; Michael R. Thomsen; Bruce L. Dixon. 2004. "The performance of event study approaches using daily commodity futures returns." Journal of Futures Markets 24, no. 6: 533-555.
This study examines short-run and long-run unbiasedness within the U.S. rice futures market. Standard OLS, cointegration, and error-correction models are used to determine unbiasedness. In addition, the forecasting performance of the rice futures market is analyzed and compared to out-of-sample forecasts derived from an additive ARIMA model and the error-correction model. The results of our unbiasedness tests and the forecasting performance of the rice futures market provide supporting evidence that the U.S. long-grain rough rice futures market is efficient. The results have important price risk management and price discovery implications for Arkansas and U.S. rice industry participants.
Andrew M. McKenzie; Bingrong Jiang; Harjanto Djunaidi; Linwood A. Hoffman; Eric J. Wailes. Unbiasedness and Market Efficiency Tests of the U.S. Rice Futures Market. Review of Agricultural Economics 2002, 24, 474 -493.
AMA StyleAndrew M. McKenzie, Bingrong Jiang, Harjanto Djunaidi, Linwood A. Hoffman, Eric J. Wailes. Unbiasedness and Market Efficiency Tests of the U.S. Rice Futures Market. Review of Agricultural Economics. 2002; 24 (2):474-493.
Chicago/Turabian StyleAndrew M. McKenzie; Bingrong Jiang; Harjanto Djunaidi; Linwood A. Hoffman; Eric J. Wailes. 2002. "Unbiasedness and Market Efficiency Tests of the U.S. Rice Futures Market." Review of Agricultural Economics 24, no. 2: 474-493.
Meat and poultry recalls, while voluntary, are carried out under governmental oversight. If firms have financial incentives to avoid being implicated in a recall situation, governmental involvement in recalls may cause firms to internalize social costs when making investment decisions concerning food safety controls. To examine these incentives, we analyze federally supervised meat and poultry recalls from 1982 to 1998 within an event study. Results show significant shareholder losses when publicly traded food companies are implicated in a recall involving serious food safety hazards. We find no evidence that the stock market reacts negatively when recalls involve less severe hazards.
Michael R. Thomsen; Andrew M. McKenzie. Market Incentives for Safe Foods: An Examination of Shareholder Losses from Meat and Poultry Recalls. American Journal of Agricultural Economics 2001, 83, 526 -538.
AMA StyleMichael R. Thomsen, Andrew M. McKenzie. Market Incentives for Safe Foods: An Examination of Shareholder Losses from Meat and Poultry Recalls. American Journal of Agricultural Economics. 2001; 83 (3):526-538.
Chicago/Turabian StyleMichael R. Thomsen; Andrew M. McKenzie. 2001. "Market Incentives for Safe Foods: An Examination of Shareholder Losses from Meat and Poultry Recalls." American Journal of Agricultural Economics 83, no. 3: 526-538.