A model for estimating industry compliance costs of food labeling regulations

A Model for Estimating Industry Compliance

Costs of Food Labeling Regulations

Michael T. French Dierdre M. Neighbors

Lori K. Carswell Richard A. Williams

Laina M. Bush

One of the most publicized and controversial issues in the food industry today is whether or not food labels convey the appropriate product information to consumers. This study models firms’ response to labeling mandates and estimates the costs to the food industry of new or revised labeling regulations. Lengthy personal interviews were conducted with 30 domestic food manufacturers and a questionnaire was administered to nearly 1,500 food manufacturing firms. The model incorpo- rates variables to adjust for the type of food manufactured, the number and sizes of the firms affected, the frequency of label redesigning, the type of printing equipment used, the value of labels ordered, and the frequency of inventory turnover. The model is used to estimate the compliance costs for two past labeling regulations-sulfiting agents and sodium.

This study was funded by the Center for Food Safety and Applied Nutrition, US Food and Drug Administration through a contract to the Research Triangle Institute. John Conner, Allen Miedema, Josephine Mauskopf, and Tayler Bingham provided valuable suggestions on earlier drafts. Maria Bachteal and Judy King deserve special thanks for editing the manuscript and preparing tables. Finally, we would like to acknowledge the support and contributions of the firms, trade associations, and other industry officials that participated in this project. The views expressed in this article are those of the authors and do not represent an official position of the Food and Drug Administration or the US Department of Health and Human Services.

Michael T. French, Dierdre M . Neighbors, and Lori K . Carswell are Senior Economist and Program Director, Economist, and Operations Research Specialist, respectively, Center for Economics Research, Research Triangle Park, North Carolina

Richard A . Williams and Laina M . Bush are Chieh Economics Section, and Economist, respectively, Ofice of Compliance, Center for Food Safety and Applied Nutrition, US Food and Drug Administration.

Agribusiness, Vol. 8, No. 2, 165-186 (1992) 0 1992 by John Wiley & Sons, Inc. CCC 0742-4477/92/020165-22904.00

166 FRENCH ET AL.

The US Food and Drug Administration (FDA) regulates the size, appearance, and content of labels for most food products consumed in the United States. FDA has promulgated several food labeling regulations recently that stirred debate among the food industry and consumer groups. These regulations include saccharin warnings, sulfiting agent disclosures, and sodium disclosures and claims. The extent of the requirements of the Nutrition Labeling and Education Act of 1990, however, is overshadowing these past labeling regulations. Many firms and food industry groups are concerned that adding or significantly revising the nutrition panel as directed by this Act will impose significant costs on the industry, which they may or may be able to pass on to the consumer in the form of higher prices.

Being a government agency acting on behalf of the public, FDA also is concerned with the economic impacts of its actions. Occasionally, an individual firm or trade association attempts to estimate the magnitude of compliance costs, but these estimates are not based on scientific, unbiased studies. Given this dearth of valid information on the compliance process and costs of food labeling regulations, new studies are needed to help guide present and future policies.

The main objective of this article is to model the activities and process that food manufacturers follow when complying with food labeling regulations promulgated by FDA. The model can be used by industry representatives, individual firms, government officials, and policymakers to generate cost estimates for past and future labeling regulations. * Although the cost model only calculates identi- fiable compliance costs incurred by the regulated firm, it is important to re- member that other costs associated with a government labeling regulation are also present. For example, FDA incurs costs to research, design, and promulgate a regulation, most of which taxpayers bear. Another cost is that of industry adjusting to changes in the demand for certain products due to real or perceived differences brought about by new labels.

This study collected data in two phases over 3 years. In the first phase, 30 firms of various sizes and 4-digit Standard Industrial Classifications (SICs) were interviewed about operating procedures and compliance costs. In return for providing candid and sometimes sensitive information, these officials required anonymity. Thus, all names of manufacturers and individual contacts are con- fidential.

To collect additional data on label printing and label inventory practices, a brief survey instrument, the Food Labeling Survey, was developed during the second phase of the research. This survey was mailed to 1,489 firms in 38 target populations (4-digit standard industrial classifications [SICs]). The sample was stratified to reflect approximately proportional allocation among 4 firm-size categories (small, medium, large, and unknown size). A total of 331 completed questionnaires were received, for an overall response rate of 22%. Table I shows the 38 targeted SICs, corresponding populations as reported by Dun and Bradstreet, and number of survey responses. Firms were strongly encouraged in a letter from the acting FDA commissioner to respond to the survey, but par- ticipation was voluntary.

The end products of this study included a final report1 summarizing the project’s objectives, activities, and results and an interactive computer model

*From a social welfare perspective, regulatory costs provide little guidance for policymakers without a comparable measure of regulatory benefits. Although this study does not examine labeling benefits, FDA does consider the benefits of labeling regulations when designing policies.

ESTIMATING COMPLIANCE COSTS 167

Table I. Survey Responses by 4-Digit SIC.

(1) 4-Digit SIC

(2) Industry

Description

(3) (4) Number of Number of

Firms" Responsesb

2021 2022 2023 2024 2026 2032 2033 2034

2035

2037 2038 2041 2043 2044 2045 2046 2051

2052 2053 2061 2062 2063 2064 2066 2067 2068 2975 2079

2083 2086 2087

2091 2092 2095 2096 2097 2098 2099

Total

Creamery Butter Natural, Processed, and Imitation Cheese Dry, Condensed, and Evaporated Dairy Products Ice Cream and Frozen Desserts Fluid Milk Canned Specialties Canned Fruits, Vegetables, Preserves, Jams, and Jellies Dried and Dehydrated Fruits, Vegetables, and Soup

Pickled Fruits and Vegetables, Vegetable Sauces and

Frozen Fruits, Fruit Juices, and Vegetables Frozen Specialties, Not Elsewhere Classified Flour and Other Grain Mill Products Cereal Breakfast Foods Rice Milling Prepared Flour Mixes and Doughs Wet Corn Milling Break and Other Bakery Products, except Cookies and

Cookies and Crackers Frozen Bakery Products, except Bread Cane Sugar, except Refining Cane Sugar Refining Beet Sugar Candy and Other Confectionery Products Chocolate and Cocoa Products Chewing Gum Salted and Roasted Nuts and Seeds Soybean Oil Mills Shortening, Table Oils, Margarine, and Other Edible

Malt Bottled and Canned Soft Drinks and Carbonated Waters Flavoring Extracts and Flavoring Syrups, Not Elsewhere

Canned and Cured Fish and Seafood Prepared Fresh or Frozen Fish and Seafoods Roasted Coffee Potato Chips, Corn Chips, and Similar Snacks Manufactured Ice Macaroni, Spaghetti, Vermicelli, and Noodles Food Preparations, Not Elsewhere Classified Unknown

Mixes

Seasonings, and Salad Dressings

Crackers

Fats and Oils, Not Elsewhere Classified

Classified

125 664 192 930 914 369 973 228

640

302 61 1 426 64 63

229 76

3,131

684 86 57 31 47

322 23

100 97

131

30 1,808

557

345 745 214 361 947 334

2,836

21,156 -

9 41) 30 7

34 17 39 10

27

16 12 28 11 11 3 9

45

8 16 4

16 5

23 7

12 41)

8 5

1 20 16

13 25 11 80 6

11 35 2

713

"According to a 1988 Dun and Bradstreet database. bThe total number of responses is greater than the total number of firms responding because

some firms produce in more than one Cdigit SIC and thus provided multiple responses.

168 FRENCH ET AL.

that allows the user to quickly estimate the costs of real or hypothetical labeling regulations. From a series of user-specified regulatory assumptions-such as the severity of the regulation (i.e., how intense the firms’ efforts must be to comply), the scope of the regulation (i.e., the industries and products affected), and the length of the compliance period (i.e., the amount of time the firms have from the date of announcement of the regulation until the date of required compliance)- the program generates compliance cost estimates by activity and firm-size category within each 4-digit SIC. The program is simple, easy to use, and can be updated as new data become available. Economists at FDA are now using the computer model to estimate the compliance costs of candidate labeling regulations.

The first section presents the underlying theory of the compliance process as revealed in the first phase of the study. The second section presents the empirical model developed to estimate compliance costs. It describes the five compliance activity categories and outlines the assumptions necessary to estimate the costs associated with each one. The third section demonstrates the applications of the model by estimating compliance costs for two previous labeling regulations as if they were promulgated in 1990. The last section summarizes the results of the study, including its limitations, and discusses avenues of future research.

CONCEPTUAL FRAMEWORK

Virtually all food products undergo label changes; firms initiate most changes and FDA mandates others. As a result, most firms possess standard procedures for approving and implementing label changes. Although mandatory and voluntary changes have some key differences, many steps in the process are identical. The compliance process presented in this article is for a representative firm in the food industry. It may not, however, model the actions of all firms. For instance, the compliance process may be less formal than the model presented here for small firms and more complex for large firms. Figure 1 illustrates the compliance process and associated activities typically followed by a representative firm for a hypothetical food labeling regulation.

After a labeling regulation is proposed in the Federal Register, the firm ex- pends administrative effort internally or through a supporting association to identify and interpret the new policy and determine which, if any, products would be affected. If no products are affected, the firm terminates the process with no label changes. If the regulation affects one or more of the firm’s products, additional events occur.

A firm normally uses management and legal personnel to establish a corporate position supporting or opposing the regulation. It then decides whether to for- mally file that position with FDA.? Regardless of the firm’s decision, it begins formulating a method for complying with the regulation. For many straightforward labeling regulations, the compliance method is simply management approval of a minor label change. For more complex labeling regulations, the firm may study its alternatives more carefully, possibly requesting analytical and marketing support. After approving a compliance method, the firm implements the plan and

tSince smaller firms do not typically have personnel trained in this area, they usually rely on trade associations or other industry groups to represent their interests.


Compliance Activitbr Compliance Process

Identify the Regulation

Administrative Regulation

Establish a

I Analytical

for compliance

Figure 1. Compliance Process and Compliance Activities.

changes its labels. In cases where compliance will have a significantly negative impact on product image, products are reformulated or discontinued.

Perhaps the biggest difference in resource use between mandated and voluntary label changes is the potentially intensive administrative and research effort that begins immediately after proposal of a labeling regulation and continues at least until a compliance method is approved. The magnitude of this effort is related to firm size, but all firms commit some amount of resources either directly through employee time or indirectly through membership dues to support associations and lobbyists.

Analytical and/or market testing are not typically performed for voluntary label changes but are often required for mandatory changes. Voluntary label changes in the food industry may be cost- or marketing-based. Marketing-based changes include recipes, advertisements, and various product promotions such as coupons and give-a-ways. Mandated label changes are primarily safety and nutrition based. Reporting safety and nutrition information often requires the support of analytical data. Some firms are able to obtain analytical data from in-

170 FRENCH ET AL.

house laboratories, while others submit product samples to independent laboratories for analysis. Several firms reported using marketing tests (e.g., internal taste panels, consumer focus groups) if the composition of a product was altered in any way of if the label was changed significantly.

Printing new labels and managing label inventories are familiar activities for many firms. Any differences in resource use for similar voluntary and mandated changes probably reflect the length of time given to complete the mandated change. Because firms usually have more control and flexibility with planned changes, a relatively short compliance period could significantly increase the resources required for label inventory management.

EMPIRICAL MODEL Total compliance cost (CC) for a representative firm is estimated as the sum of the dollar value of resources expended in each of five activity categories: administrative (AC), analytical (ANC), marketing (MC), printing (PC), and label inventory (IC).

CC = AC + ANC + MC + PC + IC (1) Resource use for each activity category is influenced by various firm- and

industry-specific operating variables and the characteristics that define any particular regulation. Several assumptions underlie the compliance cost equation:

Industries are classified by 4-digit SICS. Each industry is composed of firms of three sizes (small, medium, and large), grouped by total sales and number of employees. Each firm-size and industry category is represented by a “representative” firm possessing a set of parameter values; the parameter values are computed as averages over firms responding to the Food Labeling Survey, where possible. Every product in a particular firm-size category and industry has the same number of stockkeeping units (SKUs).$ The share of total industry products by firm-size category is proportional to the share of total industry SKUs by firm-size category. There are two types of labeling regulations: Type I and Type 11. A Type I regulation has little if any effect on product composition or marketability. A Type I1 regulation changes the composition or marketability of a product, leading to analytical and possibly market testing for all affected products.

Further justification for these assumptions is provided throughout the article. Collecting more detailed data on labeling costs and practices would be necessary to relax these and other assumptions and provide more precise estimates of cost changes for specific products, firms, and regulations. The following sections specify the compliance cost equations and provide calculations for hypothetical examples.

$Simply stated, a stockkeeping unit or SKU is a distinct product label. Information on the number of SKUs within each 4-digit SIC came from data collected by the A.C. Neilsen Co. The number of SKUs for each firm size/industry combination was estimated based on data from the Food Labeling Survey.


Administrative Cost

Administrative cost (AC) is a function of several operating and regulatory variables: the scope of the regulation (SC), the severity of the regulation (SV), the length of the compliance period (CP), and firm size (S).

AC = AC(SC, SV, CP, S )

Administrative effort is assumed to vary with firm size but not across industries. Larger firms tend to have a more formal and comprehensive approval process for label changes and invest more resources in developing a compliance method. Larger firms also tend to have more products and SKUs, implying more labels to change. Administrative cost may vary somewhat across industries, but this relationship is impossible to develop using currently available information.

In this article, administrative parameter estimates are presented by firm size (i) and severity of the regulation (k). FDA provided administrative cost estimates for firms with fewer than 100 employees (small and medium). For firms with 100 or more employees (large), administrative cost estimates were averaged from information provided by the large firms interviewed during the first phase of the study. Table I1 presents those administrative cost estimates for Type I and Type I1 labeling regulations, as well as regulatory monitoring estimates. Monitoring activities occur even if no government labeling policies are promulgated. Whether

Table 11. Administrative Cost Estimates for Large Firms.

Type I Type I1 Regulatory Regulation Regulationa Monitoringb

Finn Primary SIC ($/firm) ($/firm) ($/firm/year)

#l #2 #lo #11 #12 #13 #14 #18 #19 #20 #23 #24 #25 #26 #27 #28 $30

Averages

22,24,26 33

51,% 96

33,37 43 52

38,45,53 52,%

43 37

33,79 33

33,34 33.37 33,34 86

1,600 250

12,500 27,600

12,800

3,000 5,000 1,250

1,500 4,000

5,000 1,200

$6,308

1,600 8,750

100,000

18,400

20,000 10,000

100,000 15,000 62,500

$34,225

520 104,000

4,500 7,000

15,000 150,000 100,000 15,000 3,000

85,000 75,000 7,500 1,200

30,000 9,500

$41,076

OCaution should be used when interpreting and using a single Type I1 regulation cost estimate because the true value is highly sensitive to the nature of a regulation.

bMonitoring costs are not included in the compliance cost model.

172 FRENCH ET AL.

these tasks should be classified as regulation-induced activities or simply normal business operations is debatable. Monitoring activities are not classified as part of the administrative effort for a specific regulation but as indirect, recurring costs of government labeling activity.

The administrative cost estimates control for firm size and severity of the regulation, but another regulatory variable must be considered: the length of the compliance period. Because the firms provided cost estimates based on a standard 12-month compliance period, adjustment factors were applied for 6-month and 24-month compliance periods. On average, firms estimated that total administrative cost would double if they were required to complete label changes within 6 months after promulgation of a regulation. Conversely, if allowed a 24-month compliance period, firms said they could perform many administrative activities more cost-effectively. On average, the firms estimated that total administrative cost would decrease by 50% for a 24-month compliance period.

The following notation convention is used throughout this article. Subscripts denote operating variables (e. g., label types) and aggregation identifiers (e.g., firms and industries). Superscripts denote regulation-related variables (e. g., regulation type, length of compliance period). To calculate administrative cost (Act? for a representative firm in firm-size category i and 4-digit SIC j , the firm size/severity of regulation administrative parameter estimate (Act,) is multiplied by the compliance period adjustment factor (CPAT).

ACkm is multiplied by the total number of affected firms in firm-size category i in industry j(Fi;l? to determine the administrative cost for firm-size category i in industry j . These calculations are performed for each firm-size category in industry j and summed over firm-size categories to determine the total administrative cost for industry j .

LJ

ACkm J = C (ACtCPA?) * F , (4)

Analytical Cost

Analytical cost (ANC) is a function of the analytical test(s) being performed (ANT) and the number of affected products (PD).

ANC = A ~ C ( A ~ ~ PD) (5) The following assumptions are made when estimating analytical cost:

All affected products are subjected to the same analytical test(s). Each test is performed once. Analytical effort for a particular test is constant across products, firm sizes, and industries.

As stated in the overall model assumptions, if a Type I1 regulation affects a particular industry, all products of affected firms in that industry are analytically tested. The first assumption listed above is difficult to avoid because information is not available to predict which tests will be given to which products. Regarding


Table 111. Analytical Testing Costs for Independent Labs.

Test

Average Fee per

Test (8)

Testing Fees for Selected Labs ($/product)

Nutrition Package 354 270 345 400 459 360 330 265 400 Cholesterol 89 100 80 90 105 100 75 50 110 Total Dietary Fiber 97 100 97 100 110 N/A 125 50 100 Fatty Acid Profilea 103 110 98 90 126 95 85 130 90 Proximate 79 70 54 75 76 61 125 92 80 Vitamin 229 165 208 197 299 250 235 200 275 Mineral 59 55 62 39 84 54 60 75 45 Sodium 20 N/A 23 13 28 18 20 25 15 Potassium 20 N/A 23 13 28 18 20 25 15

"This test was used to estimate the analytical costs of the sulfiting agent regulation; each test costs approximately the same amount.

the second assumption, some firms indicated that repeat testing is often necessary to reconfirm analytical data. During the interviews of the first phase of the project, however, determining a consistent pattern of repeat testing across firms was impossible. The last assumption is plausible given that most laboratories use similar testing procedures and no consistent evidence exists of the presence of economies of scale for testing multiple products.

A wide range of analytical tests are possible for food products. Table I11 presents fees for nine of the most common analytical tests. Eight food testing laboratories from various regions across the United States provided this cost information. Internal laboratories supported by food firms have similar costs because independent laboratories are a competitive alternative.

To calculate analytical cost for a representative firm in firm-size category i and industry j (ANC;), the unit cost estimate for test t (ANTj) is multiplied by the number of products produced by a firm of size i in industry j (PDJ .

ANC; = ANT,PD, (6)

To determine the analytical cost for firm-size category i in industryj, ANCb is multiplied by the total number of affected firms in firm-size category i (FJ. These calculations were performed for each firm-size category in industryj and summed over firm-size categories to determine the analytical cost for industry j (ANC;).

Marketing Cost

Marketing cost (MC) is a function of the market test (MT) being performed and the number of products (PO) tested.

MC = MC(MT, PD) (8)

174 FRENCH ET AL.

If a firm is affected by a Type I1 regulation, it may test the marketability of its products by first assembling an internal taste panel. An internal taste panel is administered at the firm's facilities to a randomly selected sample of employees. If the results of the internal taste panel indicate that a change to a product's label significantly affects consumer perception (and thus possibly the decision to buy), the firm may follow with a more expensive type of market test such as a consumer focus group. A consumer focus group brings together consumers in a small-group setting to sample products and answer questions. A consumer focus group test is usually only conducted after an internal taste panel test has been completed.

Marketing cost estimates were calculated by averaging values provided by the 30 firms interviewed in the first phase of the study (see Table IV). The simplify- ing assumptions applied to the marketing cost equation are as follows:

If a Type I1 regulation affects a particular industry, either all products of the

If market testing occurs, each dected product is tested once per regulation. Marketing testing effort for a particular test is constant across products, firm

affected firms are market tested or no products are market tested.

sizes, and industries.

Table IV. Market Testing Costs.

Internal Consumer Taste Panel Focus Group"

Firm ($/product) ($/product)

#11 10,000 #16 1,000 10,000 #18 4,500 #19 2,000 #20 3,000 12,500 #2l 4,000 #23 1,000 4,000 #24 8 0 0 b #25 500= #26 1,200 3,000 628 3,500d #30 1,200 5,000

Averages $1,633 $6,563

.The eflectiue average cost of a consumer focus group is IbS,l%, the sum of the average costs of an internal taste panel and a consumer focus group.

bThe cost of an employee taste panel using trained personnel; the cost of an employee taste panel using untrained personnel is $1,85O/product.

cThe cost of an employee taste panel using trained personnel.

dThe cost of a consumer focus group using a sample from 20,000 pretested households; the average cost of a consumer focus group using a sample from 300,000 pretested households is $8,000.


To calculate marketing cost for a representative firm in firm-size category i and is multiplied by the industryj, the unit cost estimate for marketing test t

number of products produced by a firm of size i in industryj (PDG).

To determine the marketing cost for firm-size category i in industryj, MC; is multiplied by the total number of firms in firm-size category i and industryj (F$. These calculations are performed for each firm-size category in industry j and summed to determine the marketing cost for industry j.

MCj = C [ (MTijPDij) * Fiji.] i

Printing cost

Printing cost (PC) for a firm is the dollar value of incremental printing effort expended for a particular labeling regulation. Several operating and regulatory variables affect printing cost for a representative firm, including printing process(es) (PP), the frequency of label redesigning (RD), the number of SKUs affected (SKU), the complexity of label changes (COM), and the length of the compliance period (CP).

PC = PC(PP, RD, SKU, COM, CP) (11)

The Food Labeling Survey provided the distribution of printing processes and the frequency of label redesigning over total SKUs, by SIC and firm-size categories. The number of SKUs in each industry and firm-size category was estimated by weighting the total number of SKUs in each industry to incorporate three factors: the number of SKUs reported in the survey, the number of firms responding to the survey, and the actual number of firms in each SIC and firm-size population.

Listed below are the assumptions used to estimate incremental printing cost:

If a regulation affecting a particular firm (in a given SIC and firm-size category) is likely to result in label changes, all labels for the firm’s products will be changed. Printing effort occurs at the SKU level for each SIC and firm-size category and can be aggregated to the firm-size and industry levels. Printing effort varies across firms and industries because of differences in the use of printing processes and frequencies of label redesign. On average, the amount of time from when a regulation is promulgated to when a firm’s labels would normally be redesigned is half of the average amount of time between normal label redesigns.

The first assumption simplifies the determination of the impact of a labeling regulation within a given SIC and firm size. Rather than attempting to determine the fraction of labels changed for each firm affected by each regulation, it was assumed that if a firm is affected, all its labels are affected. The second assumption reflects the fact that each SKU requires a different label and, therefore, a separate printing effort. The fact that printing costs differ across printing pro-

176 FRENCH ET AL.

cesses and label redesign frequencies is reflected in the third assumption. Flex- ography is the least expensive printing method and gravure is the most expensive.2 Also, the higher the frequency of planned label redesigns, the lower the incremental cost of mandated label changes. Because firms and industries differ in printing processes and redesigning schedules, printing cost varies by firm size and industry.

The fourth assumption reflects the difficulty of measuring the extent to which new regulations require additional label redesigns (i.e., redesigns that would not have been conducted otherwise). To approximate the likelihood of additional label redesigns, the average amount of time between normal label redesigns was calculated from the Food Labeling Survey. The results showed that firms are at different stages in their redesign processes. At any point in time, some firms will be close to conducting a normal redesign, some will be halfway between redesigns, and some will have just completed a normal redesign. If one assumes that firms are evenly spread out in their redesign schedules, then, on average, firms will be about halfway between normal redesigns when a regulation is promulgated. Therefore, the time from the announcement of a rule to the next normal redesign is assumed to be half the average time between normal redesigns.

Printing cost (for a given label change and SKU) is a function of the type of printing process used and the number of color changes. Parameter estimates, by printing process, for a one-color label change were calculated as mathe- matical averages across the firms that provided information. To simplify the calculation of incremental printing cost for the wide range of possible label changes, a linear relationship was assumed between printing cost and affected colors for the first three affected colors. When four or more colors are affected, the assumption is that the label will be completely redesigned with a corresponding incremental printing cost of double the cost of a three-color change (six times the cost of a one-color change) because of the additional artwork required. Table V presents incremental printing cost estimates by printing process for a one-color label change and a redesign change.

To represent the effect of printing processes on the printing cost calculations, data from the Food Labeling Survey were used to estimate the distribution of printing process use by firm size for each 4-digit SIC. The printing cost estimates were weighted by the proportion of SKUs printed with each process, or “printing process SKU shares,” for the average firm in each firm-size category.

To represent the effect of label redesigning frequency on printing cost, the fraction of SKUs redesigned at intervals greater than 12, 24, and 48 months was estimated for each industry. As described earlier, these fractions are assumed to be the best estimate of the fraction of SKUs greater than 6, 12, and 24 months away from their next planned redesign.

To calculate printing cost for the average firm in firm size i and industryj, the one-color printing cost estimates for each printing process p (PC g) is multiplied by the corresponding printing process SKU shares and SumrneBacross printing pracesses. The result is a weighted (by printing process SKU shares) average printing cost estimate for a one-color label change. This value is multiplied by the expected number of colors affected by the mandated label change COME^) to estimate the per-SKU printing cost for the actual label change. This per-SKU cost is then multiplied by the total number of SKUs for a representative firm in the

Table

V.

Incr

emen

tal P

rint

ing

Cos

ts.

One

-Col

or C

hang

e ($

/SK

U)

Red

esig

n C

hang

e ($

/SK

U)

Prim

ary

Firm

SI

C

Lith

ogra

phy

Gra

vure

Fl

exog

raph

y L

ithog

raph

y G

ravu

re

Flex

ogra

phy

~

#1

#2

#3

#4

#6

#7

#8

#9

#lo

#11

#12

#1

81

4

#15

#16

#17

#18

#19

#20

#21

#23

#26

#27

#28

#30

300

22,2

4,26

33

24

,37,

43,6

4,87

,95

64,6

6,95

35

52

86

32,3

3 51

,%

96

33,3

7 43

52

52

22

,24,

26

22,2

4,35

38

,45,

53

52,9

6 43

51

37

33

,34

33,3

7 33

,34

86

1,oo

O

1,50

0 35

0 35

0

2,00

0 1,

500

2,30

0 1,

200

5,00

0 1,

000

2,00

0

12,0

00

9,00

0 13

,800

7,

200

30,0

00

6,000

12,0

00

350

350

2,10

0 2,

100

600

500

500

3,40

0 3,

000

3,00

0

6,00

0

150

500

150

900

3,00

0 90

0 15

0 90

0 2

,m

2,25

0 2,

750

12,0

00

13,5

00

16,5

00

1,30

0 55

0 18

3 2,

000

850

200

108

7,80

0 3,

300

1,09

8 12

,000

5,10

0 1,

200

648

153

3.40

0 91

8 20

,400

55

0 15

0 90

1,50

0

3,30

0 90

0 54

0 9,

000

150

900

1,OOO

1,

150

167

650

500

2,25

0 6,

150

13,5

00

36,9

00

500

$450

/SK

U

3,00

0

$2,7

00/S

KU

$7

00/S

KU

$2

,425

/SK

U

$4,2

00/S

KU

$1

4,55

O/S

KU

A

vera

ges

1 78 FRENCH ET AL.

SIC and firm-size category (SKUJ to estimate the printing cost per firm to change all SKUs. Finally, the per-firm cost is multiplied by the share of total SKUs that are not otherwise redesigned during the compliance period (RD$ to account for the printing costs that can be attributed to planned label changes.

(12) SKUp,

PC,,, = c PCPij - - COM; - SKU, * RD; P c SKUp,

P

PO" is multiplied by the total number of firms in firm-size category i and industry; (Fi.) to determine the printing cost for firm-size category i in industry;. These calculations are performed for each firm-size category in industryj and summed across firm-size categories to determine the printing compliance cost for industry J .

*J

PCj" = c c PC,, ' sKuPij * COMG SKU, * RDk F , (13) i P c SKUPij

P

Label Inventory Cost

Label inventory cost (IC) is influenced by several operating and regulatory variables, including firm size (S), label inventory when a new label order is delivered (ID), label amount ordered (ZO), the cost of a label order (CO), the severity of the regulation (SV), and the length of the compliance period (CP).

IC = IC(S, ID, 10 , CO, SV, CP) (14)

Information on label ordering schedules and label costs provides the information to estimate the value of label inventory loss for a typical firm in each firm- size category by 4-digit SIC. Measuring label inventory cost starting at the SKU level is preferable but impractical given the type of data available on inventories. From information provided by respondents to the Food Labeling Survey, it is possible to estimate the average minimum and maximum supply of label inventory by firm size and 4-digit SIC. Estimating the monthly value of label inventory is also possible from label order costs and label order amounts provided by respondents. These estimates are then converted into the value of average label inventory, making it possible to estimate the value of inventory loss using an inventory adjustment factor and the proposed compliance period. Table VI presents monthly values of label inventory by firm-size category and 4-digit SIC reported in the Food Labeling Survey.

Survey respondents also reported the total cost of a typical label order and number of months the order would last. To estimate the average value of one month of label inventory for all firms in a firm-size category, the monthly value for individual firms responding to the survey is first calculated by dividing the cost for a typical label order by the order amount (in months). The monthly values of label inventory are then averaged for individual firms within each firm-size category.


Table VI. Average Monthly Value of Label Inventory.

Firm Size

SIC Small Medium Large

2021 2022 2023 2024 2026 2032 2033 2034 2035 2037 2038 2041 2043 2 M 2045 204.6 2051 2052 2053 2061 2062 2063 2064 2066 2067 2068 2075 2079 2983 2086 2987 2091 2092 2095 2096 2097 2098 2099

$65 1 119

1,307 100

2,000 378 314

1,250 1,025

758 73 1 398 23

3,873 5,073 1,547

454 993 250

4 159 31

619 4.31 792

1,889 173

3,510 12

219 331

1,107 1,572

54 4,667 1,806

183 614

$16,273 19,342 6,960 6,944)

20,777 36,005 5,055 6,889 1,3% 3,333 1,290 4,333 6,333

20,344 29

8,ooo 4,323

17,823 4,128

4.3, 100 10

12,625 1,083

47 1 583

2,169 6,569 4,333

63 5,979 1,837

594 2,979

861 26,627 3,782 6,368 1,150

$5,172 40,ooo 36,108 8,500

380,216 196,375 79,678 36,061 42,835 43,115 8,952

77,417 35,000

107,301 167,154 42,992 46,362 14,889 20,000

190,983 5,244)

68,958 2,854

13,750 25,521 30,986 29,876

11 1,336 333

184,179 972

57,389 8,917 4,873

109,015 24,756 29,028

124,806

Other important variables in the label inventory cost model are the severity of the regulation (SV), the length of the compliance period (CP), and firm size (S). Table VII presents the compliance period adjustment factors by firm size and regulation type, derived from the interviews with 30 firms. These factors represent the time needed beyond the supply (in months) of average label inventory to deplete the existing stock of labels. The adjustment factors are assumed to be

180 FRENCH ET AL.

Table VII. Compliance Period Adjustment Factor.

Firm Size ~

Regulation Type Small Medium Large

Type I 3 months 2 months 1 month Type I1 6 months 4 months 3 months

constant across industries and to control for the effect of regulation type and firm size on the probability of label inventory loss.

To illustrate the need for the adjustment factor, consider the following sce- nario. If the average supply of labels for a firm is less than the compliance period, existing label inventory could be entirely depleted before the compliance period ends, resulting in zero inventory cost. But firm size and the severity of a regulation (the greater the severity, the longer the time needed to comply) influence the rate of label inventory depletion and the label reordering schedule. Based on discussions with firms during the first phase of the study, smaller firms were found to require a longer period to complete the transition to new labels than larger firms-probably due to slower sales, relatively higher inventories, and less frequent label changes. For a Type I1 regulation, analytical and market testing will delay the design and order for new labels for all firm sizes. Firms must wait for the results of product tests before authorizing label changes and ordering new labels. The adjustment variable also accounts for the possibility of unexpected delays in design work and printing. As discovered earlier in the project, label printers are likely to receive an unusually large number of orders after a regulation is promulgated.

To estimate label inventory cost for an average firm of size i in industryj, the average label inventory for firm size i in industry j is first computed as one-half the sum of the average minimum and maximum supply (ID, + 0.510,). The next step is to estimate the expected amount of average label inventory that is discarded due to the regulation. Next, average label inventory for a firm of size i in industry j (ID, + 0.5I0,) is added to the compliance period adjustment variable for a firm of size i industry j with regulation type k (CPIFj). Subtracting the length of the compliance period in months (CP$ estimates the amount of average label inventory that is discarded. If this value is nonpositive, no label inventory loss is expected. If the value is positive, multiplying this average label inventory loss (in months) by the average monthly value of label inventory (AMV,) estimated earlier is appropriate. The result is an estimate of the value (cost) of expected label inventory loss for an average firm of size i in industry j.

(16) Multiplying ICfj by the total number of firms in the firm-size category (FJ

determines the label inventory cost for firm-size category i in industry j. These calculations for each firm-size category in industry j are summed across firm-size categories to determine the label inventory cost for industry j.

IC!j = Max (0, IdG + 0.510, + CPItj - CP?} - AMV,

IC) = 2 Max (0, ID, + 0.510, + CPI: - CPT} . AMV, * Fij (17) i


Summary of Model Equations Recall from the earlier discussion that the compliance cost equation for a representative firm is the sum of the costs incurred for each activity category. Com- pliance cost equations for each activity category were developed as a function of operating and regulatory variables. By collecting the equations for each activity category, it is now possible to specify the structural form of the full compliance cost equation for a representative firm of size i in industryj.

CCf,Wc = (ACtCPA;) + (ANT;,PDi,) + (MT;,PD,,)

+ c SKUPij - PC, , - COM; SKU, RD; p SKU,;,.

P

+ Max (0, ID, + 0 . 5 1 0 , + CPl$ - CPg} * AMV,

The full compliance cost equation derives estimates for a representative firm in each firm-size category. These firm-level estimates can be multiplied by the number of firms in each firm-size and industry category and then aggregated to obtain the total industry compliance cost estimate.

EXAMPLE CALCULATIONS M)R PAST LABELING REGULATIONS

Compliance cost estimates are influenced by many different operating and regulatory variables. In estimating the cost of hypothetical regulations, French et al. demonstrated that some activity categories require more effort (and dollars) than others. This section demonstrates the compliance cost calculation for two labeling regulations (sulfiting agents and sodium) as if they were promulgated in 1990.

Sulfiting Agent Labeling

FDA promulgated a sulfiting agent labeling regulation in 1986 after identifying sulfiting agents, or “sulfites,” as the common substance causing some indi- viduals to experience allergic reactions after consuming certain food products. The sulfiting agents included under this rule are sulfur dioxide, sodium sulfite, and sodium or potassium bisulfite or metabisulfite. Since sulfites are an effective preservative and only a very small percentage of the US population experiences

Table VIII. Total Compliance Costs of the Sulfiting Agent Regulation by SIC and Firm Size.

Firm Size

SIC Small Medium Large Total

$4,204,153 $8,~6,7a9 $14,814,098 2033 $1,763,156 2034 $694,205 $949,414 $1,490,603 $3,134,222

$5,153,567 $10,337,392 $17,948,320 Total $2,457,361

182 FRENCH ET AL.

Table M. Firm Compliance Costs of the Sulfiting Agent Regulation by SIC and Firm Size.

Firm Size

SIC Small Medium

2033 $8,559 $20,813 $1 12,698 2034 $13,350 $20,418 $99,374

adverse health effects because of them, an outright ban was deemed unjustified. Instead, FDA mandated that if a “detectable” level of sulfites is found in a finished food (whether the sulfites were directly added by the manufacturer or indirectly added by an ingredient supplier) the manufacturer must include sulfites in the list of ingredients, which is normally found in black and white lettering on the information panel of a label. FDA defines a detectable amount of sulfites as ten parts per million.

The following is a list of the base case regulatory variable settings for the sulfiting agent regulation:

The regulation is a Type 11, resulting in a sulfiting agent analytical test (similar

The regulation requires a one-color label change to the information panel. The compliance period is 12 months.$ One-half of all firms in SIC 2033, Canned Fruits and Vegetables, and SIC

in cost to a fatty acid profile) and an internal taste panel market test.

2034, Dehydrated Fruits, Vegetables, and Soups, are affected.

Using the previously discussed compliance cost model, the total compliance cost for the sulfiting agent regulation if it were promulgated in 1990 is estimated to be $17,948,320. Table VIII shows the distribution of costs among SICS and firm sizes. Table IX presents the compliance costs a typical firm in each firm-size category incurred because of the regulation. Table X shows the distribution of compliance costs among compliance activities and firm sizes.

Sodium Labeling

In 1984 FDA promulgated a regulation requiring that the amount of sodium contained in a product be listed if the product uses a nutrition label. This information may be listed on either the principal display panel or the information panel by milligrams per serving or portion. Sodium labeling is an example of a regulation that may both benefit and damage a product’s marketability. If the label of a product did not disclose the amount of sodium prior to the regulation because it would have a negative impact on the product’s image, then complying

$A 12-month compliance period is assumed, implying that no adjustments are made to the parameter estimates. Although the final rule allowed only for a 6-month effective date, the rule was proposed one year before it was finalized, allowing the industry at least that much time to incorporate the label change. (51 FR 25012, July 9, 1986)


Table X. Total Compliance Costs of the Sulfiting Agent Regulation by SIC and Compliance Activity.

Compliance Activity

SIC Admin. Analytical Marketing Printing Inventory Total

2033 $4,522,663 $460,359 $7,298,694 $2,303,383 $229,001 $14,814,098 2034 $956,625 $107,017 $1,696,687 $373,893 $0 $3,134,222 Total $5,479,288 $567,376 $8,995,381 $2,677,276 $229,001 $17,948,320

with the regulation may cause the sales of the product to decrease. Alternatively, if a firm did not make any sodium claims on the labels of its low-sodium products prior to the regulation, it may increase sales by adding the standardized sodium claims to its principal display panel. Because the net impact on a given product’s marketability could be positive or negative, it is assumed that, on average, there

Table XI. Total Compliance Cost by SIC and Firm-Size Category: Sodium Regulation.

Size of Firm

SIC Code

202 1 2022 2023 2024 2026 2032 2033 2034 2035 2037 2038 2043 2045 2051 2052 2053 2064 2066 2067 2068 2086 2091 2092 2096 2098 2099

Total

Small

$43,65 1 389,438 62,343

433,659 277,537 166,338 397,755 136,037 349,794 95,215

264,866 24,420 96,618

1,339,549 362,35 1 29,921

1,364,263 167,626

3,599 50,716

855,935 24&,615 668,295 138,921 168,590

1,412,417

$9,544,%9

Medium

$65,614 309,798 %,314

616,477 364,232 207,797 520,971 213,036 199,779 122,306 412,763

18,376 79,247

260,950 72,847

662,586 113,117

6,365 302,53 1 833,995 158,836 321,847 212,725 193,423

1,129,752

1,263,084

$8,758,768

Large

$164,504 473,089 268,432 737,598

2,207,132 323,145

1,116,843 270,690 599,885 554,011 690,473 135,997 247,084

3,986,062 1,081,478

235,131 725,037 109,893 134,726 253,318

2,358,854 192,134 498,347 416,651 177,293

1,463,153

$19,420,960

Total

$273,769 1,172,325

427,089 1,787,734 2,848,901

697,280 2,035,569

619,763 1,149,458

771,532 1,368,102

178,793 422,949

6,588,695 1,704,779

337,899 2,751,886

390,636 144,690 606,565

4,048,784 595,585

1,488,489 768,297 539,306

4,005,322

$37,724,197

184 FRENCH ET AL.

Table XII. Firm Compliance Cost by SIC and Firm-Size Category: Sodium Regulation.

Size of Firm

SIC Code

202 1 2022 2023 2024 2026 2032 2033 2034 2035 2037 2038 2043 2045 2051 2052 2053 2064 2066 2067 2068 2086 2091 2092 2096 2098 2099

Small

$2,322 3,346 2,326 2,383 2,253 2,272 2,414 3,270 2,535 2,380 2,417 2,348 2,300 2,258 2,990 3,937 3,769 2,315 2,999 2,949 3,566 4,023 4,914 2,4Lia 2,381 2,334

Medium Large

$3,038 2,531 2,800 4,188 2,522 3,684 3,224 5,727 2,290 2 , m 4,212 2,297 2,251 2,355 2,416 3,717 3,641 2,262 2,652

18,008 2,397 2,392 2,424 3,303 3,530 2,520

$17,136 17,653 17,207 17,234 22,522 17,562 17,784 22,557 19,477 18,717 18,763 17,894 17,159 32,566 24,358 34,578 17,429 17,171 24,058 42,220 17,396 18,474 17,304 17,959 22,162 18,108

is no compliance cost associated with market tests resulting from the sodium regulation.

As for printing costs, if a firm chooses to alter a product's principal display panel to take advantage of the regulation, the associated expenses should not be attributed to the regulation. However, the expense of adding another ingredient to the information panel should be included as a compliance cost. Therefore, a one-color label change is assumed.

The following is a list of the base case regulatory variable settings for the sodium regulation:

The regulation is a Type 11, resulting in analytical testing of sodium, but no

The regulation requires a one-color label change to the information panel. The compliance period is 24 months. (50 FR 26984, July 1, 1985) Forty percent of all firms in 26 of the 4-digit SICS are afTected.11

market testing.

lh'his is based on an estimate that 4Q% of all food products at the time of the sodium regulation displayed a nutrition panel on their label (49 FR 15512, April 18, 1984).


Table XIII. Total Compliance Cost by SIC and Cost Category: Sodium Regulation.

Type of Cost

SIC Code Administrative Analytical Printing Inventory Total

202 1 2022 2023 2024 2026 2032 2033 2034 2035 2037 2038 2043 2045 2051 2052 2053 2064 2066 2067 2068 2086 2091 2092 2096 2098 2099

Total

$255,180 995,915 4@l,655

1,473,115 2,279,125

606,470 1,809,065

382,650 1,033,765

710,830 1,096,840

171,455 420,120

4,636,170 1,275,495

177,565 1,935,880

384,920 103,930 179,175

3,643,455 464,170

1,097,644) 669,710 419,500

3,753,290

$30,380,085

$1,496 35,328

1,912 58,480 33,000 13,608 71,512 16,624 47,4130 29,048 14,752 6,368 840

80,456 46,720 14,920 48,840

712 2,928

18,200 49,144 11,744 12,640 23,136 18,552 80,456

$738,816

$17,094 141,081 20,523

256,139 536,776 77,203

154,991 220,488 68,293 31,654

256,509 970

1,989 1,872,069

382,564 145,414 767,166

5,004 37,832

409,190 41,185

119,672 378,209

75,451 101,254 171,577

$6,290,297

$0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

315,000 0 0 0 0 0

$315,000

$273,770 1,172,324

427,090 1,787,734 2,848,901

697,281 2,035,568

619,762 1,149,458

771,532 1,368,101

178,793 422,949

6,588,695 1,704,779

337,899 2,751,886

390,636 144,690 606,565

4,048,784 595,586

1,488,489 768,297 539,306

4,005,323

$37,724,198

The total compliance cost for the sodium regulation if it were promulgated in 1991 is estimated to be $37,724,198. Tables XI through XI11 show the distribution of costs among 4-digit SICS, firm sizes, and compliance activities.

SUMMARY AND CONCLUSIONS

This is the first study to rigorously examine and model the compliance costs of food labeling regulations. This research shows that many firms engage in a complex set of activities to comply with labeling mandates. These activities were grouped into five categories: administrative, analytical, marketing, printing, and label inventory management.

After describing the compliance cost model, estimates were calculated for the cost of the sulfiting agents regulation and the sodium regulation if they were promulgated in 1990. The model estimates that the sulfiting agents regulations would cost firms approximately $18 million. The sodium regulation would cost

186 FRENCH ET AL.

firms more than double the sulfiting agents regulation (almost $38 million) because more industries are affected. For both regulations, the compliance period and the severity of the regulation are the variables with the strongest influence on the total compliance cost, followed by the extent of label redesign required by the regulation.

Although this compliance cost model is more comprehensive and reliable than any previous models used by industry and government to estimate the costs of labeling regulations, it is not without limitations. For example, little objective data exist on the administrative costs of compliance. Several firms provided administrative cost estimates for Type I and Type I1 regulations, but these estimates were highly variable. Another limitation of the model relates to an inherent difficulty with any labeling regulation-predicting the distribution of affected firms. Even changes of 5 to 10% in the predicted coverage could result in cost estimates that vary by billions of dollars. Furthermore, the model is clearly static, but the parameter estimate must be updated regularly to ensure reliability of the estimates. This is especially true for the number of SKUs, the distribution of printing processes, and label inventory parameters. Finally, this model estimates the cost of labeling regulations to private industry; it does not, however, address the costs to taxpayers for promulgating the regulation. Both private and public costs should be tallied to estimate the full cost of a regulation.

Despite these limitations, this model is a major improvement over the previous methods FDA was using to estimate compliance costs. Equipped with estimates of the dollar benefits of labeling regulations, FDA is better positioned to determine the economic viability of candidate regulations.

REFERENCES

1. M.T. French, D.M. Neighbors, L.K. Carswell, K.B. Heller, and G.L. McDougal, Compliance Costs ofFood Labeling Regulations, Final report prepared for the US Food and Drug Administra- tion, Research Triangle Institute, Research Triangle Park, NC, 1991.

2. M.H. Bruno, Label I d u s t r y Facts a d Guidelines, Label Printing Industries of America, Arling- ton, VA, 1986.

Documents

A model for estimating industry compliance costs of food labeling regulations