Search

This study provides an empirical investigation of the relationship between grocery retail concentration and retail dairy prices in the US. We perform the analysis based on a unique dataset on store-level retail prices provided by the Information Resources Inc. Further, we consider alternative measures of retail concentration including revenue and store selling space-based Herfindahl Hirschman Index, which we compute using a Nielsen TDLinx dataset on store characteristics. Results from a reduced-from empirical framework estimated via panel data techniques indicate that grocery retail concentration affects dairy retail prices favorably. This central result is robust to the way that retail concentration is measured and is consistent with the empirical evidence from both the US and oversees.

In the period leading up to the start of the Margin Protection Program for Dairy Producers (MPP-Dairy), a survey was undertaken to assess dairy farmer knowledge, attitudes, impressions and expected participation decisions. All surveys were collected in July and August 2014. There are six main conclusions of the survey. First, prior to the announcement of USDA rules regarding MPP-Dairy, most dairy producers felt they had ‘some knowledge’ of the program, with close to 30 percent declaring ‘no knowledge’ about the program. Second, about thirty percent of respondents had somewhat or very favorable impressions of MPP-Dairy while similar percent had somewhat or very unfavorable. Top four concerns about the program were too much government involvement, program complexity, lack of supply management and fear that the program would distort market signals to farmers. Third, close to 40 percent of producers indicated they were leaning towards registering for MPP-Dairy, while 30 percent were leaning against participation. Over 30 percent of producers had not decided if they would to participate or not. More knowledge about MPP-Dairy was associated with higher likelihood of participation. Fourth, we asked dairy farmers which coverage level they would choose in most years. Distribution of responses had two pronounced peaks, with $4.00/cwt and $6.00/cwt chosen by 28 and 25 percent of producers respectively. No other coverage choice was chosen by more than 12 percent of producers. Fifth, just under 70 percent of LGM-Dairy users indicated that when faced with a one-time irreversible choice between LGM-Dairy and MPP-Dairy, they would choose MPP-Dairy. Finally, just under 25 percent of producers indicated MPP-Dairy would ‘somewhat’ reduce their use of other risk management tools, while 18 percent replied they expected a ‘strong reduction’ in their use of other risk management instruments.

We develop a new parametric bootstrap-based statistical test for presence of futures price and options-based implied volatility biases. The new test is applicable to data with overlapping prediction horizons. Information on anticipated volatility embedded in options prices is explicitly used when testing for futures price biases. Our method is well adapted to analysis of fast changing commodity markets as it does not rely on asymptotic theory and does not require a time series spanning several decades. We apply the new test to investigate if futures and options biases can explain very low loss ratios exhibited by USDA’s Livestock Gross Margin for Dairy Cattle insurance program.

Price endogeneity has been ignored in previous analyses of food demand in China. We examine agricultural input price data from the China National Bureau of Statistics and use reduced-form price equations to account for price endogeneity in this setting. Applying our unique econometric approach to the analysis of provincial-level food demand in China, we find strong statistical evidence of price endogeneity. Models that ignore price endogeneity result in substantially biased elasticities and misleading estimates of future food demand in China.

The article offers measures of own and cross cost pass-through in a structural framework. Unlike the traditional reduced-form analysis used in the previous literature, our approach is applicable in situations where firm marginal cost data are unobserved. The empirical value of the model is illustrated in an application to retail pass-through for national and store brand yogurt using an inverse demand derived from the economic theory. We find that ignoring cross pass-through between the brands biases own pass-through estimates.

The endogeneity of retail market power arises in the retail pricing equation due to the correlation between margins and unobserved cost components. Nevertheless, it has long been ignored in the equilibrium analysis of retail behavior. We address the issue via a control function approach in a new conceptual framework with consumer preferences represented by a benefit function. We further offer three test procedures to evaluate the endogeneity of retail market power. The empirical value of the model is illustrated in an application to the US yogurt industry. Outcomes from endogeneity tests provide strong evidence for market power endogeneity. Moreover, ignoring the issue results in downward bias in retail market power.

In this analysis we compare the total expected government outlays and distribution of benefits under newly proposed dairy margin insurance programs to those under existing counter-cyclical payment programs. We combine simulation and structural modeling techniques to forecast milk price and dairy income-over-feed-cost margins. Using the price forecasts we employ Monte-Carlo experiments to evaluate the total expected government outlays for a sample of 5000 representative farms given a constant relative risk aversion utility framework. We find that expected outlays favor large farm operations and are an order of magnitude higher than those under existing programs. Under the current policy framework (MILC), farms with less than 100 cows (76% of farms) account for 42% of net payments and farms over 1000 cows (2% of farms) account for 6% of net payments. Under the new policy regime farms with fewer than 100 cows will get 17-21% of net program benefits, and farms over 1000 cows will get 36-43% of benefits.

A common approach in the literature, whether the investigation is about futures price risk premiums or biases in option-based implied volatility coefficients, is to use samples in which consecutive observations can be regarded as uncorrelated. That will be the case for non- overlapping forecast horizons constructed by either focusing on short time-to-maturity contracts or excluding some data. In this article we propose a parametric bootstrap procedure for uncovering futures and options biases in data characterized by overlapping horizons and correlated prediction errors. We apply our method to test hypotheses that futures prices are efficient and unbiased predictors of terminal prices, and that squared implied volatility, multiplied by time left to option expiry, is an unbiased predictor of terminal log-price variance. We apply the test to corn, soybean meal and Class III milk futures and options data for the period 2000-2011. We find evidence for downward bias in soybean meal futures, as well as downward volatility bias in Class III milk options. Importance of these results is illustrated on the example of premium determination for Livestock Gross Margin Insurance for Dairy Cattle (LGM-Dairy).

With increased volatility of feed prices dairy farm managers are no longer concerned with managing just milk price volatility but are considering the adoption of risk management programs that address income over feed cost (IOFC) margin risk. Successful margin risk management should be founded on understanding of the behavior of IOFC margins. To that end, we construct forward IOFC margins using Class III milk, corn and soybean meal futures prices. We focus on the characteristics of the term structure of forward IOFC margins, i.e. the sequence of forward margins for consecutive calendar months, all observed on the same trading day. What is apparent from shapes of these term structures is that both in times when margins were exceptionally high and when they were disastrously low, market participants expected that a reversal back to average margin levels would not come quickly, but would rather take up to 9 months. Slopes of the forward margin term structure prior to and after most of the major swings in IOFC indicate these shocks were mostly unanticipated, while time needed for recovery to normal margin levels was successfully predicted. This suggests that IOFC margins may exhibit slow mean-reverting, rather than predictable cyclical behavior, as is often suggested in the popular press. This finding can be exploited to design a successful catastrophic risk management program by initiating protection at 9 to 12 months prior to futures contract maturity. As a case study, we analyze risk management strategies for managing IOFC margins that utilize Livestock Gross Margin for Dairy Cattle (LGM-Dairy) insurance contracts. We created two farm profiles where the first one represents dairy farms that grow most of their feed. The second profile is designed to capture the risk exposure of a dairy farm that purchases all their dairy herd, dry cow, and heifer feed. Our case study of this program encompasses the 2009 period which was characterized by exceptionally poor IOFC margin conditions. We analyzed the dynamics of realized IOFC margins in 2009 under four different risk management strategies, and found that optimal strategies that are founded on principles delineated above succeeded in reducing the decline IOFC margins in 2009 by 93% for home-feed and 47% for market-feed profile, and performed substantially better than alternative strategies suggested by earlier literature.

Livestock Gross Margin Insurance for Dairy Cattle (LGM-Dairy) is a recently introduced tool for protecting average income over feed cost margins in milk production. In this paper we examine the assumptions underpinning the rating method used to determine premiums charged for LGM-Dairy insurance contracts. The first test relates to the assumption of lognormality in terminal futures prices. Using high-frequency futures and options data for milk, corn and soybean meal we estimate implied densities with flexible higher moments. Simulations indicate there is no strong evidence that imposing lognormality introduces bias in LGM-Dairy premiums. The remainder of the paper is dedicated to examining dependency between milk and feed marginal distributions. The current LGM-Dairy rating method imposes the restriction of zero conditional correlation between milk and corn, as well as milk and soybean meal futures prices. Using futures data from 1998-2011 we find that allowing for non-zero milk-feed correlations considerably reduces LGM-Dairy premiums for insurance contracts with substantial declared feed amounts. Further examination of the nature of milk-feed dependencies reveals that Spearman’s correlation coefficient is mostly reflecting tail dependence. Using the empirical copula approach we find that non-parametric method of modeling milk-feed dependence decreases LGM-Dairy premiums more than a method that allows only for linear correlation. Unlike other situations in portfolio risk assessment where extremal dependence increases risk, in agricultural margins, tail dependence between feed and the Class III milk price may actually decrease insurance risk, and reduce actuarially fair premiums.

Options on agricultural futures are popular financial instruments used for agricultural price risk management and to speculate on future price movements. Poor performance of Black’s classical option pricing model has stimulated many researchers to introduce pricing models that are more consistent with observed option premiums. However, most models are motivated solely from the standpoint of the time series properties of futures prices and need for improvements in forecasting and hedging performance. In this paper we propose a novel arbitrage pricing model motivated from the economic theory of optimal storage, and consistent with implications of plant physiology on the importance of weather stress. We introduce a pricing model for options on futures based on a Generalized Lambda Distribution (GLD) that allows greater flexibility in higher moments of the expected terminal distribution of futures price. We use times and sales data for corn futures and options for the period 1995-2009 to estimate the implied skewness parameter separately for each trading day. An economic explanation is then presented for inter-year variations in implied skewness based on the theory of storage. After controlling for changes in planned acreage, we find a statistically significant negative relationship between ending stocks-to-use and implied skewness, as predicted by the theory of storage. Furthermore, intra-year dynamics of implied skewness reflect the fact that resolution of uncertainty in corn supply is resolved between late June and middle of October, i.e. during corn growth phases that encompass corn silking through grain maturity. Impacts of storage and weather on the distribution of terminal futures price jointly explain upward sloping implied volatility curves.

Ph.D. Thesis advisor: Dr. T.Randall Fortenbery, University of Wisconsin-Madison [See http://marinbozic.info/research.php for other publications by this author]

Replaced with revised version of paper 02/10/10.

Advisors: Prof. Giovanni Pegoretti (Italy) and Prof. Brian W. Gould (USA) ... [See http://marinbozic.info/research.php for other publications by this author.]

The endogeneity of retail markups arises due to the correlation between the markups and unobserved costs in the retail pricing equation. This correlations may be a result unobserved product quality affecting both price and markups. Despite inconsistency resulting from markup endogeneity, it has long been ignored in the equilibrium analysis of retail behavior. We account for retail markup endogeneity using a control-function approach in which controls are derived from empirical evidence in the marketing literature. Furthermore, we adopt three test procedures to evaluate this endogeneity and apply our method in an econometric analysis of retail market behavior in the marketing of yogurt in the United States. The results provide strong statistical evidence for the fact that markup endogeneity has been overlooked, resulting in upward bias in retail markups.