EXHIBIT A

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 1 of 11 PageID #:2827
UNITED STATES DISTRICT COURT 

NORTERHN DISTRICT OF ILLINOIS 

EASTERN DIVISION 

 

NICK PEARSON, FRANCISCO PADILLA, | 

CECILIA LINARES, AUGUSTINA BLANCO, | 

ABL GONZALEZ, and RICHARD JENNINGS, | 

On Behalf of Themselves and All Others Similarly | 

Situated, | Case No.: 11CV 07972 

 | 

 Plaintiffs, | 

 | 

v. | 

 | 

NBTY, INC., a Delaware corporation; and | 

REXALL SUNDOWN, INC., a Florida corporation; | 

and TARGET CORPORATION, a Minnesota | 

Corporation, | 

 | 

 Defendants. | 

 | 

Supplemental Report of Keith A. Reutter, Ph.D., 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 2 of 11 PageID #:2828
2 

I. Introduction, Assignment and Summary of Conclusions 

 1. I am a Ph.D. economist and Principal in the Washington, D.C. office of the 

Berkeley Research Group (“BRG”). BRG is an economic and financial consulting firm with 

offices in major U.S. and foreign cities. I have been associated with BRG since shortly after its 

founding in early 2010, and have been professionally employed as an Economist for over 15 

years. I hold a Bachelor of Science and Master of Arts in Economics from the University of 

Texas-Arlington, as well as a Doctor of Philosophy in Economics from Auburn University. 

 2. On September 4, 2013, I submitted a report in the above captioned matter wherein 

I estimated the expected benefit that will accrue to consumers, including members of the 

proposed Class, as a result of the injunctive relief agreed to by the settling parties.1

 In that 

report, I relied on defendant Rexall’s internal documents to provide a reasonable estimate of the 

likely economic impact of the proposed labeling changes. That estimate was based on the 

information available to me at the time and predicted a lower price, a decline in sales volume, or 

both, as a result of the proposed labeling changes.2 Using historical dollar sales data for Osteo 

Bi-Flex as a proxy I estimated the lower prices, all other things equal, that might reasonably 

result due to the labeling changes and then used that as one measure of the economic impact of 

those labeling changes. I also predicted an expected drop in the sales volume of Osteo Bi-Flex. 

The predicted decline in sales volume was based on the expectation that some consumers will 

stop purchasing Osteo Bi-Flex when the “renews and rebuilds” cartilage representations are 

removed from the label. The expected decline in sales volume was based on Rexall’s internal 

documents that indicate that a high percentage of Osteo Bi-Flex purchasers responded that the 

“renews and rebuilds” cartilage representations are important to their purchasing decisions. 

 

1

 Report of Keith A. Reutter Regarding Settlement, dated August 30, 2013, hereinafter “Reutter Report.” 2

 Reutter Report, ¶ 8. 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 3 of 11 PageID #:2829
3 

 3. I understand that the Court has raised the question of whether it is possible to 

empirically measure the value of the labeling changes, required by the Settlement Agreement, by 

analyzing defendants’ sales and pricing data for products before and after the labeling changes 

are implemented, in order to assign a specific monetary value to the relief afforded to the Class 

and consumers brought about by the labeling changes. It is my opinion that such a computation, 

relying on defendant’s data alone, would not measure the actual economic impact of the labeling 

changes, and thus would not answer the question. This is because, like any retail product, there 

are other confounding economic factors, in addition to the proposed labeling changes, at work 

that continuously influence the price and sales of the covered products. These additional factors 

would have to be taken into consideration in order to measure the actual economic impact of the 

labeling changes in terms of prices and volume of sales. For example, a reduction in competition 

from companies selling comparable products or an increase in advertising by defendants may 

result in an increase in the price or volume sold of the covered products following the labeling 

changes. In such a situation, an observed increase (or decrease) in the price or volume sold of 

the covered products would mean little viewed in isolation, and would not value the effect of the 

labeling changes. A regression analysis would have to be performed to take into consideration 

these, and possibly other, additional factors, to isolate the actual monetary value of the labeling 

changes.3

 

3

 Regression analysis is a widely accepted statistical technique that is used to measure or determine the impact that 

one or more independent, or explanatory, variables has on a dependent variable. For instance, regression analysis 

can be used to determine the impact that an alleged price fixing cartel has on the price of a good. For a discussion of 

the use of regression analysis in determining impact in a legal context, see: William H. Page, editor, Proving 

Antitrust Damages: Legal and Economic Issues (American Bar Association, 1996); Daniel L. Rubinfeld, “Reference 

Guide on Multiple Regression”, in Reference Manual on Scientific Evidence: 2nd Edition (St. Paul: West Group, 

2000). For a general discussion of regression analysis, see: Damodar N. Gujarati, Basic Econometrics: 4th Edition

(Boston: McGraw-Hill, 2003). 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 4 of 11 PageID #:2830
4 

 4. In this regard I have reached the following conclusions: (1) a regression analysis, 

using defendant’s data alone, would not be able to estimate the monetary value of the labeling 

changes; (2) a regression analysis of the impact of the proposed labeling changes would require a 

substantial amount of data that is not currently available to plaintiffs, or defendants; and (3) 

assuming these data issues could be overcome, which in my opinion is unlikely, such a study 

could not commence for at least two years following the labeling changes, which I understand 

will not take place until 6 months following final approval of the settlement. Such a regression 

analysis would likely cost in excess of $500,000. This cost estimate is based on my experience 

having conducted at least two dozen such studies, where the data was readily available, over the 

last 15 years of my professional career. 

II. Inadequacy of Defendant Data 

 5. As described in the Reutter Report, the expected impact of the proposed labeling 

changes is to reduce the demand for Rexall’s Osteo Bi-Flex products, resulting in a decrease in 

both the price and quantity sold, all other things equal. Others in the industry, or Rexall itself, 

may be able to partially or completely mask the impact of the labeling changes by, among other 

things, increasing the amount of money spent advertising glucosamine/chondroitin products 

thereby increasing overall demand and price. 

 6. The only sales data that plaintiffs can obtain directly from defendants is Rexall’s 

sales transactions. As the manufacturer of Osteo Bi-Flex, Rexall’s sales transactions reflect the 

price and quantity at which sales are made to wholesalers, distributors and others. Rexall’s 

transaction data does not include the price at which Osteo Bi-Flex is sold to consumers at retail. 

Further, defendant’s data does not include the retail prices at which the covered private label 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 5 of 11 PageID #:2831
5 

glucosamine/chondroitin products, manufactured by defendants, are sold. Thus, Rexall’s 

transaction data alone is inadequate to address the impact the labeling changes will have on the 

prices paid by consumers. 

 7. It may be possible to overcome the inadequacy of defendant’s transaction data by 

purchasing retail sales data from a third party vendor, such as ACNielsen. ACNielsen collects 

retail sales data from the store checkout scanners of participating retail establishments across the 

U.S.4

 However, Osteo Bi-Flex is only one of many glucosamine/chondroitin products marketed 

to consumers. Hence, the actions taken by other glucosamine/chondroitin supplement 

manufacturers would have to be taken into account since they would likely have an impact on the 

sales volume and price of Osteo Bi-Flex. Because the sale of Osteo Bi-Flex is likely impacted 

by exogenous factors, i.e. events beyond the direct control of Rexall, a proper analysis of the 

impact of the labeling changes would require the purchase of retail sales data for all 

glucosamine/chondroitin products marketed by Rexall, as well as retail sales data for all of the 

many other glucosamine/chondroitin products marketed by competitors. The purchase price of 

this retail sales data would likely cost in excess of $100,000 given recent estimates I have 

received for similar data in unrelated matters. 

 a. Increased Marketing Spending by Rexall 

 8. As noted above, the expected impact of the labeling changes is to reduce the 

demand for Osteo Bi-Flex, resulting in a lower price and a lower quantity sold. In order to 

counter the expected impact of the labeling changes, Rexall could unilaterally increase the 

amount of advertising and marketing directed at the consuming public. By increasing the 

 

4

 www.nielsen.com 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 6 of 11 PageID #:2832
6 

amount of marketing directed at the consuming public, Rexall could effectively shift the demand 

curve for Osteo Bi-Flex to mask the actual impact caused by the labeling changes. If Rexall 

were to undertake such an action the price and quantity sold of Osteo Bi-Flex may very well 

exceed that which was observed prior to the labeling changes. But this would not mean that the 

labeling changes had no impact, but rather that these unilateral actions by Rexall masked the 

impact. Thus, the impact of the labeling changes cannot be determined by merely observing the 

retail, or wholesale, prices of Osteo Bi-Flex. It would also have to take into account Rexall’s 

advertising and marketing directed at the consuming public. 

 b. Increased Marketing Spending by Other Manufacturers 

 9. Because Rexall is not alone in the manufacturing and marketing of 

glucosamine/chondroitin supplements, the actions of others in the marketplace will necessarily 

impact the quantity and price of Osteo Bi-Flex sold. If, for example, after the labeling changes 

Rexall does nothing, but the other manufacturers in the industry either decrease or increase the 

amount of advertising and marketing directed at consumers, then the price and quantity sold of 

Osteo Bi-Flex likely will be affected. In the case of a decrease in advertising or marketing by 

competitors, Rexall may be able to take advantage and either maintain or increase the price of 

Osteo Bi-Flex, again masking the actual impact of the labeling changes. Further, in the case of 

an increase in advertising or marketing by competitors, Rexall might be able to maintain or even 

increase the price and quantity of Osteo Bi-Flex due to what is known as a spillover effect, 

whereby an increase in advertising of a competing glucosamine/chondroitin product results in 

higher sales for Rexall. All of this is out of Rexall’s control, i.e. is exogenous to Rexall, but 

must be taken into consideration to properly analyze the impact of the labeling changes. Absent 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 7 of 11 PageID #:2833
7 

their voluntary production of this proprietary information, it is highly unlikely that the 

advertising or marketing budgets of other competitors could be obtained. 

 c. Increased Marketing Spending by Retail Outlets 

 10. Similar to the actions taken by other manufacturers of glucosamine/chondroitin, if 

following the labeling changes, retailers of Osteo Bi-Flex increase the amount of advertising 

directed at the glucosamine/chondroitin consuming public, then retailers may be able to increase 

demand and hence affect the price and quantity of Osteo Bi-Flex despite the labeling changes. 

Again, the data necessary to determine the impact, if any, that retailers might have on the 

demand for Osteo Bi-Flex is exogenous to Rexall. Absent the voluntary production of this 

proprietary information, it is highly unlikely that the advertising or marketing budgets of retailers 

could be obtained. This confounding factor is further compounded by the fact that there are a far 

greater number of retailers in the marketplace than competitors. 

 d. Demographic Changes 

 11. Another factor that would likely impact the price and quantity sold of Osteo BiFlex is the demographic makeup of the country. An aging and active population may result in an 

increase in the demand for glucosamine/chondroitin products, all else equal. While the 

demographic data necessary to measure the impact of an aging population on the price and 

volume sold of covered products is likely available from organizations such as the U.S. Census, 

an analysis would need to be undertaken to determine what demographic information is most 

relevant. 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 8 of 11 PageID #:2834
8 

 12. The foregoing are just some of the confounding economic factors, or variables, 

that would have to be taken into account in order to perform an appropriate regression analysis to 

determine the true economic impact of the proposed labeling changes. 

III. An Economic Analysis of Proposed Labeling Changes 

 13. As noted, attempting to determine the actual economic impact of the proposed 

labeling changes will require a considerable amount of data, most of which is not available from 

Rexall. First, retail pricing data for glucosamine/chondroitin products will be needed for a 

period of time preceding and following the proposed labeling changes. Best economic practices 

suggest a minimum of two years, or 24 months, worth of data on either side of the labeling 

changes for a total of 48 months of data.5

 Second, it will be necessary to know the amount of 

advertising that Rexall spent on a monthly basis for the same 48 month period, broken down by 

product. Third, it will be necessary to know the amount of advertising dollars spent by 

manufacturers of competing glucosamine/chondroitin products, over the same 48 months. 

Fourth, the amount of money spent by retailers to advertise glucosamine/chondroitin products, 

on a product-by-product basis, will be needed for the 24 months preceding and following the 

labeling changes. Lastly, age-based demographic information will need to be collected. 

 14. Given the data described above, to determine the impact of the proposed labeling 

changes, a regression equation in the following form must be performed: 

POBF = 0 + 1(Rexall Advertising) + 2(Other Manufacturer’s Advertising) + 

3(Retail Advertising) + 4(Demographic Information) + 5(Labeling Changes); 

 

5

 A minimum of 48 months of data is necessary to guarantee the degrees of freedom necessary to yield statistical 

significance. 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 9 of 11 PageID #:2835
9 

where, POBF is the price of Osteo Bi-Flex and 5 is a binary, or indicator, variable that takes on 

the value “0” before the proposed labeling changes and the value “1” following the labeling 

changes. As noted, it is necessary that two years of monthly data, on either side of the labeling 

changes, be collected in order to yield sufficient statistical results. Some of the data would 

necessarily have to be provided by direct competitors. Using the above equation, the coefficient 

5 represents the impact of the labeling changes. If this value is negative, and statistically 

significant, it would mean that the impact of the labeling changes was to lower the price of Osteo 

Bi-Flex. 

 15. If it is possible to overcome the data issues described above, e.g. determining the 

level of advertising undertaken by manufacturers and marketers of competing 

glucosamine/chondroitin products, which is highly unlikely, the study as described would likely 

cost in excess of $500,000, which would include the value of my time, the time for my support 

staff, as well as the cost of acquiring the necessary data. Such a study could not be completed 

for two to three years following the implementation of the labeling changes. 

IV. Conclusion 

 16. I have been asked to determine the feasibility of undertaking a study to determine 

the actual economic impact of the proposed labeling changes agreed to by the settling parties. 

As described above, the actual value of the labeling changes cannot be gleaned from an analysis 

of defendant Rexall’s data alone. That is, defendant’s wholesale sales transaction data alone will 

not provide a measure of the actual impact of the labeling changes on consumers. In order to 

estimate the economic impact of the proposed labeling changes will require the purchase of retail 

sales data from a vendor such as ACNielsen, and will require knowledge of the advertising 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 10 of 11 PageID #:2836
budgets 

manufact

confident

following

sufficient

Keith A R

Novembe

of compet

turers or r

tial and prop

g the effecti

t time to adj

Reutter 

er 4, 2013 

ing manufa

retail outlet

prietary bus

ve date of th

ust to the ne

 

acturers and

ts would w

siness inform

he labeling 

ew labeling.

10 

d retail out

willingly an

mation neede

changes wou

utlets. It i

nd unilatera

ed. Further

uld be requi

is unlikely 

ally produc

r, a time per

ired in order

that comp

e the sens

riod of two 

r give the m

peting 

sitive, 

years 

market 

Case: 1:11-cv-07972 Document #: 137-1 Filed: 11/06/13 Page 11 of 11 PageID #:2837