Court Opinion

ID: 4303403
Source: CourtListenerOpinion
Date Created: 2018-08-13 22:01:35.898255+00
Date Added: 2024-06-11T14:33:02.290808
License: Public Domain

Slip Op. 18–

               UNITED STATES COURT OF INTERNATIONAL TRADE
___________________________________________
                                              :
THE STANLEY WORKS (LANGFANG)                  :
FASTENING SYSTEMS CO., LTD. and               :
STANLEY BLACK & DECKER, INC.,                 :
                                              :
                        Plaintiffs,           : Before: Richard K. Eaton, Judge
                                              :
            v.                                : Court No. 17-00071
                                              :
UNITED STATES,                                :
                                              :
                        Defendant,            :
                                              :
            and                               :
                                              :
MID CONTINENT STEEL & WIRE, INC.,             :
                                              :
                        Defendant-Intervenor. :
___________________________________________:

                                          OPINION
[United States Department of Commerce’s final results are sustained.]

                                                                        Dated: "VHVTU

       Lawrence J. Bogard, Neville Peterson, LLP, of Washington, DC, argued for plaintiffs.
With him on the brief was Peter J. Bogard.

       Sosun Bae, Trial Attorney, Commercial Litigation Branch, Civil Division, U.S.
Department of Justice, of Washington, DC, argued for defendant. With her on the brief were
Chad A. Readler, Acting Assistant Attorney General, Jeanne E. Davidson, Director, and Patricia
M. McCarthy, Assistant Director. Of counsel on the brief was Jessica R. DiPietro, Attorney,
Office of the Chief Counsel for Trade Enforcement & Compliance, U.S. Department of
Commerce, of Washington, DC.

       Ping Gong, The Bristol Group PLLC, of Washington DC, argued for defendant-
intervenor. With her on the brief was Adam H. Gordon.

       Eaton, Judge: Before the court is The Stanley Works (Langfang) Fastening Systems Co.,

Ltd. and Stanley Black & Decker, Inc.’s (collectively, “Stanley” or “plaintiff”) motion for
Court No. 17-00071                                                                          Page 2

judgment on the agency record challenging the final results of the United States Department of

Commerce (“Commerce” or the “Department”) in Certain Steel Nails From the People’s

Republic of China, 82 Fed. Reg. 14,344 (Dep’t Commerce Mar. 20, 2017), P.R. 290, bar code

3551507-01, ECF No. 34 (“Final Results”), as amended by 82 Fed. Reg. 19,217 (Dep’t

Commerce Apr. 26, 2017), P.R. 307, bar code 3566359-01, ECF No. 34 (“Amended Final

Results”), and accompanying Issues and Decision Memorandum, P.R. 289, bar code 3551476-

01, ECF No. 34 (“Final I&D Memo”).

       Stanley objects to the Final Results on three grounds, claiming that (1) Commerce

contravened 19 C.F.R. § 351.414(f) (2008) by, among other things, self-initiating a targeted

dumping analysis; (2) the differential pricing analysis manifests an unreasonable interpretation of

19 U.S.C. § 1677f–1(d)(1)(B) primarily because the Cohen’s d test is not reasonably used to

evaluate targeted dumping and is incorrectly calculated; and (3) the World Trade Organization

(“WTO”) Appellate Body has held that the differential pricing analysis contravenes U.S.

obligations under the antidumping agreement, thereby calling into question Commerce’s

arguments regarding the reasonableness of its differential pricing analysis. See Pls.’ Mem. Supp.

Mot. J. Admin. R., ECF No. 29-1 (“Pls.’ Br.”) 2-3, 46.

       Defendant, the United States (the “Government” or “defendant”), on behalf of

Commerce, argues that (1) 19 C.F.R. § 351.414(f) (2008) does not apply to administrative

reviews; (2) many of Stanley’s arguments have been foreclosed by the Federal Circuit; and

(3) Stanley’s WTO argument notwithstanding, Commerce was reasonable in interpreting the

relevant statute and regulations when conducting its differential pricing analysis to reach the

conclusion that an alternative comparison method should be used to calculate Stanley’s dumping

margin. See Def.’s Resp. Opp’n Pls.’ Mot. J. Agency R., ECF No. 31 (“Def.’s Br.”) 4-5.
Court No. 17-00071                                                                                 Page 3

        For its part, Defendant-Intervenor, Mid Continent Steel & Wire, Inc., argues that

Commerce’s implementation of the differential pricing analysis is reasonable and adds that “[t]he

WTO decision . . . is not binding on the United States unless and until Congress and the

Administration implement it pursuant to the statutory scheme.” Def.-Int.’s Resp. Br., ECF No. 30

(“Def.-Int.’s Br.”) 2, 4.

        The court has jurisdiction pursuant to 28 U.S.C. § 1581(c) (2012). For the reasons set

forth below, Commerce’s Final Results are sustained.

                                     LEGAL FRAMEWORK

        In an administrative review of an antidumping duty order, Commerce determines the

amount of any antidumping duty by first determining “the normal value[1] and export price[2] (or

        1
                Normal value is:

        the price at which the foreign like product is first sold (or, in the absence of a sale,
        offered for sale) for consumption in the exporting country, in the usual
        commercial quantities and in the ordinary course of trade and, to the extent
        practicable, at the same level of trade as the export price or constructed export
        price . . . .

19 U.S.C. § 1677b(a)(1)(B)(i) (2012).
        2
                Export price is:

        the price at which the subject merchandise is first sold (or agreed to be sold)
        before the date of importation by the producer or exporter of the subject
        merchandise outside of the United States to an unaffiliated purchaser in the
        United States or to an unaffiliated purchaser for exportation to the United States,
        as adjusted under subsection (c) of this section.

19 U.S.C. § 1677a(a).
Court No. 17-00071                                                                                Page 4

constructed export price[3]) of each entry of the subject merchandise” and then calculates “the

dumping margin for each such entry.” 19 U.S.C. § 1675(a)(2)(A)(i)-(ii) (2012). A “dumping

margin” is “the amount by which the normal value exceeds the export price or constructed export

price of the subject merchandise.” 19 U.S.C. § 1677(35)(A). In an antidumping investigation,

there are three methods by which Commerce may compare normal value with export price to

determine whether merchandise is being sold for less than fair value (i.e., whether it is being

dumped). See 19 U.S.C. § 1677f–1(d). Generally, Commerce uses one of two methods: (1) a

comparison of the weighted-average of an exporter’s normal values to the weighted-average of

its export prices for comparable merchandise (the “A-A” method), or (2) a comparison of the

normal values of an exporter’s individual transactions to the export prices of an exporter’s

individual transactions for comparable merchandise (the “T-T” method).4 See 19 U.S.C.

§ 1677f–1(d)(1)(A)(i)-(ii).

             3
                           Constructed export price is:

         the price at which the subject merchandise is first sold (or agreed to be sold) in the
         United States before or after the date of importation by or for the account of the
         producer or exporter of such merchandise or by a seller affiliated with the
         producer or exporter, to a purchaser not affiliated with the producer or exporter,
         as adjusted under subsections (c) and (d) of this section.

19 U.S.C. § 1677a(b). The export price or constructed export price is sometimes referred to as
the U.S. price.
         4
                  Although § 1677f–1(d)(1)(A) lists both the A-A and T-T methods as Commerce’s
general methods for comparing normal value with export price to determine whether
merchandise is being dumped, in actual practice, Commerce’s regulations specify that T-T will
be rarely used. See 19 C.F.R. § 351.414(c)(1)-(2) (2015) (“In an investigation or review,
[Commerce] normally will use the [A-A] method unless [Commerce] determines another method
is appropriate in a particular case. . . . [Commerce] will use the [T-T] method only in unusual
situations . . . .”).

Court No. 17-00071                                                                             Page 5

        If Commerce finds, however, that there is evidence of targeted dumping, i.e., that “there

is a pattern of export prices (or constructed export prices) for comparable merchandise that differ

significantly among purchasers, regions, or periods of time,” and “explains why such differences

cannot be taken into account using” the A-A or T-T methods, it may use an alternative method

and compare “the weighted average of the normal values to the export prices (or constructed

export prices) of individual transactions” (the “A-T” method). 19 U.S.C. § 1677f–1(d)(1)(B).5

             5
                           19 U.S.C. § 1677f–1(d)(1)(A), provides:

        In an investigation under [19 U.S.C. § 1673], [Commerce] shall determine
        whether the subject merchandise is being sold in the United States at less than fair
        value—

        (i)      by comparing the weighted average of the normal values to the weighted
                 average of the export prices (and constructed export prices) for
                 comparable merchandise, or

        (ii)     by comparing the normal values of individual transactions to the export
                 prices (or constructed export prices) of individual transactions for
                 comparable merchandise.

19 U.S.C. § 1677f–1(d)(1)(A). Section 1677f–1(d)(1)(B) (targeted dumping) provides:

        [Commerce] may determine whether the subject merchandise is being sold in the
        United States at less than fair value by comparing the weighted average of the
        normal values to the export prices (or constructed export prices) of individual
        transactions for comparable merchandise [i.e., by using the A-T method], if—

        (i)      there is a pattern of export prices (or constructed export prices) for
                 comparable merchandise that differ significantly among purchasers,
                 regions, or periods of time, and

        (ii)     [Commerce] explains why such differences cannot be taken into account
                 using a method described in paragraph (1)(A)(i) or (ii).

19 U.S.C. § 1677f–1(d)(1)(B).

Court No. 17-00071                                                                                Page 6

        Commerce has promulgated a targeted dumping regulation to flesh out the statute, 19

C.F.R. § 351.414(f) (2008). See Antidumping Duties; Countervailing Duties, 62 Fed. Reg.

27,296, 27,373-76 (Dep’t Commerce May 19, 1997) (“Final Rule”). The salient elements of this

regulation are:

        (f)(1) [Commerce] may apply the [A-T] method . . . in an antidumping
        investigation if:

        (i) As determined through the use of, among other things, standard and
            appropriate statistical techniques, there is targeted dumping in the form of a
            pattern of export prices (or constructed export prices) for comparable
            merchandise that differ significantly among purchasers, regions, or periods of
            time . . . [§ 351.414(f)(1)(i)] . . . .

        (2) [Commerce] normally will limit the application of the [A-T] method to those
            sales that constitute targeted dumping . . . [§ 351.414(f)(2) (2008) (i.e., the
            Limiting Rule)].

        (3) [Commerce] normally will examine only targeted dumping described in an
            allegation . . . . Allegations must include all support factual information, and
            an explanation as to why the [A-A] or [T-T] method could not take into
            account any alleged price differences [§ 351.414(f)(3) (2008)].

19 C.F.R. § 351.414(f)(1)-(3) (2008) (emphasis added). Notably, by their plain language, the

statute and the regulation only address antidumping investigations. 19 U.S.C. § 1677f–

1(d)(1)(A)-(B) (“In an investigation . . . [Commerce] may determine whether subject

merchandise is being sold in the United States at less than fair value by comparing the weighted

average of the normal values to the export prices (or constructed export prices) of individual

transactions for comparable merchandise . . . .”); 19 C.F.R. § 351.414(f) (2008) (“[Commerce]

may apply the [A-T] method . . . in an antidumping investigation . . . .”).6

             6
                           Commerce attempted to withdraw this regulation in 2008, but the Federal Circuit
later invalidated the withdrawal. See Withdrawal of the Regulatory Provisions Governing

                                                                              (footnote continued . . . )

Court No. 17-00071                                                                             Page 7

       As to administrative reviews, although the statute and regulations give Commerce a

framework for determining whether, in antidumping investigations, merchandise is being sold at

less than fair value, or whether targeted dumping may be occurring, the section of the code

addressing reviews (§ 1677f–1(d)(2)) does not specify which comparison method it must use.

See 19 U.S.C. § 1677f–1(d)(2).7 Commerce’s regulations, however, state that it will apply the A-

A method in both investigations and reviews “unless [Commerce] determines another method is

appropriate in a particular case.” 19 C.F.R. § 351.414(c)(1) (2015). To determine whether

another method is appropriate, Commerce’s practice, where there appears to be targeted

dumping, is to use the same approach in administrative reviews that it does in investigations. See

JBF RAK LLC v. United States, 790 F.3d 1358, 1364 (Fed. Cir. 2015). Thus, in an administrative

review, Commerce will apply the A-T method when it (1) finds that there is evidence of targeted

dumping, i.e., “a pattern of export prices (or constructed export prices) for comparable

Targeted Dumping in Antidumping Duty Investigations, 73 Fed. Reg. 74,930 (Dep’t Commerce
Dec. 10, 2008); see also Mid Continent Nail Corp. v. United States, 846 F.3d 1364, 1368 (Fed.
Cir. 2017) (“Commerce violated the requirements of the APA in withdrawing the regulation,
leaving the regulation in force . . . .”). Thus, the Limiting Rule (i.e., the provision of the
regulation directing Commerce to limit its application of the A-T method to those sales that
constitute targeted dumping) remained in force for investigations following the attempted
withdrawal. In Apex Frozen Foods Private Ltd. v. United States, however, the Federal Circuit
found that this provision did not apply to administrative reviews. See Apex Frozen Foods Private
Ltd. v. United States, 862 F.3d 1322, 1336 (Fed. Cir. 2017).
       7
               Title 19 U.S.C. § 1677f–1(d)(2) states:

       In a review under section 1675 of this title [i.e., in an administrative review of an
       antidumping duty order, countervailing duty order, or a notice of suspension of
       liquidation], when comparing export prices (or constructed export prices) of
       individual transactions to the weighted average price of sales of the foreign like
       product, [Commerce] shall limit its averaging of prices to a period not exceeding
       the calendar month that corresponds most closely to the calendar month of the
       individual export sale.

19 U.S.C. § 1677f–1(d)(2).
Court No. 17-00071                                                                              Page 8

merchandise that differ significantly among purchasers, regions, or periods of time,” and

(2) explains “why such differences cannot be taken into account using [the A-A or A-T

methods].” 19 U.S.C. § 1677f–1(d)(1)(B)(i)-(ii).

       In both investigations and reviews, when determining whether targeted dumping may be

occurring in both investigations and reviews, and therefore, whether Commerce may apply the

A-T method, Commerce uses the differential pricing analysis. See Timken Co. v. United States,

40 CIT __, __, 179 F. Supp. 3d 1168, 1173 (2016); see also Certain Steel Nails From the

People’s Republic of China, 81 Fed. Reg. 62,710 (Dep’t Commerce Sept. 12, 2016)

(“Preliminary Results”), and accompanying Preliminary Issues and Decision Memorandum, P.R.

256, bar code 3503883-01, ECF No. 34 (“Preliminary I&D Memo”) at 19. The differential

pricing analysis is a two-stage process involving three separate “tests.” In the first stage,

Commerce uses what it calls the “Cohen’s d test”8 together with the “ratio test” to determine

whether there is “a pattern of export prices (or constructed export prices) for comparable

merchandise that differ significantly among purchasers, regions, or periods of time.” 19 U.S.C.

§ 1677f–1(d)(1)(B)(i); see Preliminary I&D Memo at 20.

       If the results of these tests do not suggest that there is a pattern of prices that differ

significantly for comparable merchandise among purchasers, regions, or periods of time, then

Commerce may not consider the application of the A-T method. See Preliminary I&D Memo at

20-21. If, however, the results of these tests reveal that such a pattern exists, that is, that targeted

dumping may be occurring, Commerce will move to the second stage of the differential pricing

analysis, and use the “meaningful difference test” to determine whether the price differences can

             8
                           As will be seen, labeling the formula Commerce uses as a “Cohen’s d test” has
raised questions as to its appropriateness for identifying differential pricing.

Court No. 17-00071                                                                           Page 9

be taken into account using the A-A method. See Preliminary I&D Memo at 20-21; Timken, 179

F. Supp. 3d at 1173-74; Apex Frozen Foods Private Ltd. v. United States, 40 CIT __, __, 144 F.

Supp. 3d 1308, 1331 (2016), aff’d, 862 F.3d 1337 (Fed. Cir. 2017) (“Apex I”) (“Once Commerce

establishes that there is a pattern of significant price differences, Commerce’s practice in reviews

requires it to explain whether A-A cannot account for such price differences before deciding to

apply A-T. Commerce has chosen to answer whether A-A cannot account for such price

differences by engaging in its meaningful differences analysis, which is the second stage of the

differential pricing analysis.”). Thus, Commerce uses the Cohen’s d test to determine whether

targeted dumping may be occurring, the ratio test to see if any potential targeted dumping

matters, and the meaningful difference test to determine whether the A-A method can account

for any pricing differences found, i.e., whether the       A-A method can “unmask” targeted

dumping.

       As currently applied, Commerce’s differential pricing analysis is product specific and is

performed at the level of individual product control numbers (i.e., “CONNUMs”9), net of

adjustments to gross U.S. selling price. Before Commerce begins its differential pricing analysis,

it (1) disaggregates sales data collected from respondents and then (2) sorts the sales of each

CONNUM into sales made to particular purchasers, geographic regions, or time periods. A group

of CONNUM sales specific to one particular purchaser, region, or time period will form a “test”

group, while the CONNUM’s remaining sales (i.e., sales to all other purchasers, regions, or from

all other time periods) will form a “comparison” or “base” group. See Preliminary I&D Memo at

             9
                           A CONNUM is a product control number, or “a numerical representation of a
product consisting of a series of numbers reflecting characteristics of a product in the order of
their importance used by Commerce to refer to particular merchandise.” Tri Union Frozen
Prods., Inc. v. United States, 40 CIT __, __, 163 F. Supp. 3d 1255, 1301 n.28 (2016).

Court No. 17-00071                                                                              Page 10

19-20. The differential pricing analysis serially analyzes prices to each purchaser, region, and

time period as a test group, and then reuses those prices when forming other comparison groups

for that particular CONNUM.

        As to the purpose of the first test, the so called Cohen’s d test, Commerce seeks to

measure the “effect size” between two groups.10 That is, this test measures the extent to which

“the net prices to a particular purchaser, region, or time period differ significantly from the net

prices of all other sales of comparable merchandise” by taking the difference between the

weighted-average net prices of the test and comparison groups, divided by the “pooled” standard

deviation of the net prices of the two groups.11 Final I&D Memo at 18. The resulting coefficient

is then categorized as either falling within a “small,” “medium,” or “large” threshold.12

Preliminary I&D Memo at 20. Notably, Commerce does not consider whether a test group’s

weighted-average price is higher or lower than the comparison group’s weighted-average price in

determining the effect size.

        Of these thresholds, Commerce has concluded that the “large” threshold (a 0.8 standard

deviation or greater) indicates a significant difference between the two groups. Thus, if the

resulting coefficient meets or exceeds the “large” threshold (i.e., if the weighted-averages of the

             10
                           Commerce describes “effect size” as “‘quantify[ing] the size of the difference
between two groups, and may therefore be said to be a true measure of the significance of the
difference.’” Final I&D Memo at 10 (quoting Xanthan Gum From the People’s Republic of
China, 78 Fed. Reg. 33,351 (Dep’t Commerce June 4, 2013) and accompanying Issues and
Decision Mem., Cmt. 3).

        11
              To calculate the pooled standard deviation, Commerce takes the square root of:
the sum of the square of the comparison group’s standard deviation and the square of the test
group’s standard deviation, divided by two.
        12
              These thresholds were developed, and used by, Dr. Jacob Cohen himself. See
Stanley Submission of Factual Material, P.R. 230, bar code 3483603-01, Attach. A, ECF No. 34
(“Robert Coe, It’s the Effect Size, Stupid”) at 5.

Court No. 17-00071                                                                                   Page 11

comparison group and the test group differ by at least 0.8 standard deviations), the sales within

that test group are considered to have “passed” the Cohen’s d test. Commerce has further

determined that sales “passing” the test differ significantly from all other sales for that particular

CONNUM. See Preliminary I&D Memo at 20. Commerce then performs the same analysis on a

different CONNUM test group and continues until it has cycled through all of a respondent’s

sales.

         Following the Cohen’s d test, Commerce uses the “ratio test” to “assess[] the extent of

significant price differences for all sales measured by the Cohen’s d test.” Preliminary I&D

Memo at 20. Under the ratio test, if the value of sales to certain purchasers, regions, and time

periods that “pass”13 the Cohen’s d test account for 66 percent or more of the value of a

respondent’s total sales, then Commerce considers there to be an “identified pattern of prices that

differ significantly” such that it may consider the application of the A-T method to all sales.

Preliminary I&D Memo at 20. If the value of passing sales accounts for only 33 percent or less

of the value of a respondent’s total sales, however, then the results do not support the

consideration of the application of the A-T method to any of respondent’s sales. If the value of

passing sales is more than 33 percent but less than 66 percent of the value of a respondent’s total

sales, then Commerce may consider the application of the A-T method for all passing sales, but

the A-A method will be used for all remaining sales. Preliminary I&D Memo at 20.

         In those instances where the Cohen’s d test and the ratio test have found evidence that

targeted dumping may be occurring, i.e., where passing sales represent more than 33 percent of

             13
                           As described above, a sale “passes” the Cohen’s d test if the Cohen’s d coefficient
falls within the “large” classification threshold, i.e., if the Cohen’s d test results in a 0.8 or higher
standard deviation.

Court No. 17-00071                                                                       Page 12

the value of a respondent’s total sales, Commerce then moves on to the second stage of its

analysis. In the second stage of Commerce’s differential pricing analysis, Commerce seeks to

determine “whether using only the [A-A method] can appropriately account for such differences”

found in the previous stage by applying what is known as the “meaningful difference test.”

Preliminary I&D Memo at 20. Under this test, Commerce first calculates the dumping margin

that would result by applying the A-A method to all sales and then calculates dumping margins

using the A-T method based on the results of the Cohen’s d and ratio tests described above (i.e.,

by (1) applying the A-T method to all passing sales and the A-A method to the remaining sales,

and (2) applying the A-T method to all sales). Preliminary I&D Memo at 20. Commerce then

compares the A-A margin with the appropriate A-T margin to determine if there is a “meaningful

difference” between the two. Commerce considers there to be a “meaningful difference” when

the comparison demonstrates: (1) where both margins calculated are above the de minimis

threshold, that there is a 25 percent relative change in the margins; or (2) where the margin

calculated using the A-A method is de minimis, that the A-T method generates a dumping margin

that crosses the de minimis threshold. If a meaningful difference exists, Commerce infers that the

A-A method is unable to account for the price differences to particular purchasers, regions, or in

particular periods of time (i.e., that the A-A method would not “unmask” observed pricing

differences which evidence targeted dumping). See Preliminary I&D Memo at 20-21.

                                       BACKGROUND

       In August 2008, Commerce published an antidumping duty order covering certain steel

nails from China. See Certain Steel Nails From the People’s Republic of China, 73 Fed. Reg.

44,961 (Dep’t Commerce Aug. 1, 2008) (order). In October 2015, following a request by, among

others, Stanley, Commerce initiated the seventh administrative review of the order for the period
Court No. 17-00071                                                                     Page 13

of August 1, 2014, through July 31, 2015 (the “POR”). Initiation of Antidumping and

Countervailing Duty Admin. Review, 80 Fed. Reg. 60,356, 60,360 (Dep’t Commerce Oct. 6,

2015). Stanley was named as a mandatory respondent in the review and submitted responses to

all of Commerce’s initial and supplemental antidumping questionnaires. Selection of

Respondents for Individual Review Mem. (Dec. 16, 2015), P.R. 76, bar code 3426396-01, ECF

No. 34; Stanley Section A-D Questionnaire Resp., P.R. 90, bar code 3433013-01, P.R. 110, bar

code 3442643-01, P.R. 117, bar code 3442681-01, ECF No. 34; Stanley Suppl. Section A, C, and

D Questionnaire Resp., P.R. 198, bar code 3472991-01, ECF No. 34.

       During the course of the review, the Department, on its own initiative, considered

whether targeted dumping was present during the POR. Commerce published the preliminary

results of its seventh administrative review in the Federal Register on September 12, 2016,

employed its differential pricing analysis, and, having found evidence of targeted dumping,

preliminarily calculated a weighted-average dumping margin of 5.90 percent for Stanley.

Preliminary Results, 81 Fed. Reg. at 62,711; see also Preliminary I&D Memo 19-20. As part of

its analysis, Commerce concluded that there was a pattern of export prices for comparable

merchandise that differed significantly among purchasers, regions, or time periods. Preliminary

I&D Memo at 21. Specifically, the Department found that 77.8 percent of the value of Stanley’s

U.S. sales “passed” the Cohen’s d test, “confirm[ing] the existence of a pattern of prices that

differ significantly among purchasers, regions, or time periods.” Preliminary I&D Memo at 21.

       Commerce also preliminarily found that the A-A method could not account for such

differences because the differences in the weighted-average dumping margins were meaningful,

i.e., Stanley’s margin crossed the de minimis threshold when calculated using the A-T method.

Preliminary Results Analysis Memorandum for Stanley (Sept. 6, 2016), P.R. 259, bar code

Court No. 17-00071                                                                     Page 14

3504519-01, ECF No. 34 (“Preliminary Analysis Memorandum”) at 16. In other words,

Commerce determined that the A-A method could not account for the observed differences in

prices among purchasers, regions, or periods of time. Thus, in accordance with the ratio test,

because the value of passing sales represented 66 percent or more of Stanley’s total U.S. sales

value, Commerce applied the A-T method to all of Stanley’s sales and calculated a 5.90 percent

dumping margin.See Preliminary Analysis Memorandum at 16.

         On March 20, 2017, Commerce issued its Final Results, which were amended on April

26, 2017, for a ministerial error. See Final Results, 82 Fed. Reg. at 14,344; Amended Final

Results, 82 Fed. Reg. at 19,217. In its Final Results, Commerce again employed its differential

pricing analysis and all of its elements. In so doing, Commerce quoted two academic articles in

support of the use of the Cohen’s d test: It’s the Effect Size, Stupid,14 by Robert Coe, and

Difference Between Two Means,15 by David Lane. Final I&D Memo at 10, 11 n.70. Based on the

results of its differential pricing analysis, Commerce calculated a final dumping margin for

Stanley of 5.78 percent. Amended Final Results Analysis Memorandum for Stanley (Apr. 19,

2017), P.R. 305, bar code 3565149-01, ECF No. 34 (“Amended Final Results Analysis Memo”)

at 2. Had Commerce not applied the A-T method, Stanley’s dumping margin would have been

zero. See Amended Final Results Analysis Memo at 2.

             14
                           Robert Coe, It’s the Effect Size, Stupid.
         15
             Stanley Submission of Factual Material, P.R. 230, bar code 3483603-01, Attach.
B, ECF No. 34 (“David Lane, Difference Between Two Means”).

Court No. 17-00071                                                                       Page 15

                                    STANDARD OF REVIEW

       “The court shall hold unlawful any determination, finding, or conclusion found . . . to be

unsupported by substantial evidence on the record, or otherwise not in accordance with law.” 19

U.S.C. § 1516a(b)(1)(B)(i).

                                         DISCUSSION

I.     The “Allegation” and “Appropriate Statistical Techniques” Requirements of 19
       C.F.R. § 351.414(f) and Their Application to Administrative Reviews

       In 1997, Commerce promulgated regulations dealing with its procedures and standards

for determining whether a respondent in an investigation is engaged in targeted dumping. See

Final Rule, 62 Fed. Reg. at 27,373-76. As a procedural matter, since the regulation dealt with

investigations, Commerce was directed to “normally . . . examine only targeted dumping

described in an allegation” that included “all supporting factual information, and an explanation

as to why the [A-A] or [T-T] method could not take into account any alleged price differences.”

19 C.F.R. § 351.414(f)(3) (2008).

       Additionally, the regulations directed Commerce to (1) use “standard and appropriate

statistical techniques” when determining whether there is a pattern of prices that differ

significantly, and (2) “limit the application of the [A-T] method to those sales that constitute

targeted dumping” (i.e., the Limiting Rule). 19 C.F.R. §§ 351.414(f)(1)(i), (f)(2) (2008). In Apex

Frozen Foods Private Ltd., the Federal Circuit found that the Limiting Rule only applied to

antidumping investigations, not administrative reviews. See Apex Frozen Foods Private Ltd. v.

United States, 862 F. 3d 1322, 1336 (Fed. Cir. 2017). Stanley argues, however, that the Final

Results violate the remaining sections of the 1997 targeted dumping regulation—in particular,

Court No. 17-00071                                                                                   Page 16

the “allegation” requirement and the “appropriate statistical techniques” requirement—which,

Stanley notes, the Federal Circuit did not specifically address in Apex.16 Pls.’ Br. 16-17.

        A. The “Allegation” Requirement Does Not Apply to Administrative Reviews

        As to the “allegation” requirement found in § 351.414(f)(3) (2008), Stanley claims that

Commerce acted unlawfully by initiating a differential pricing analysis without an allegation by

an interested party that Stanley was engaged in targeted dumping (i.e., by self-initiating a

targeted dumping analysis). Pls.’ Br. 16. According to Stanley, Commerce previously

“recognized the substantive importance of requiring a petitioner to allege targeting” when

Commerce promulgated its targeted dumping regulation, but failed to explain why here it “no

longer needs a petitioner’s ‘intimate knowledge’ and ‘expertise’ to ‘focus appropriately any

analysis of targeted dumping.’” Pls.’ Br. 16 (quoting Final Rule, 62 Fed. Reg. at 27,296).

Therefore, plaintiff maintains that Commerce’s sua sponte initiation of its differential pricing

analysis in this review was unlawful.

        Stanley’s argument is unconvincing because it ignores the differences in the manner in

which investigations and reviews are commenced. Investigations, in nearly every case, begin

with the filing of a petition by a domestic interested party (normally a manufacturer or labor

union). See 19 C.F.R. § 351.201. These petitions may be hundreds of pages long and must

contain reasonably available data supporting the allegations of dumping. See 19 C.F.R.

§ 351.202.

             16
                           Plaintiff additionally claims that the Final Results contravene the Limiting Rule of
§ 351.414(f)(2), but concedes that the Federal Circuit has found that the Limiting Rule applies
only to antidumping investigations. Pls.’ Br. 16 (“The Final Results also contravene the ‘limiting
rule’ in § [351.414(f)(2)]. However . . . the [Federal Circuit] recently concluded that the limiting
rule only applies to antidumping investigations.”).

Court No. 17-00071                                                                       Page 17

       A request for a review, on the other hand, is a far less detailed affair. Indeed, a request

need not contain any allegations or data at all. All that is required is that the interested party

requesting a review provide a reason why a review should be commenced. See 19 C.F.R.

§ 351.213(b)(1). Moreover, any interested party, including a foreign manufacturer or exporter,

may request a review. See 19 C.F.R. § 351.213(b)(1) (“Each year during the anniversary month

of the publication of an antidumping or countervailing duty order, a domestic interested party or

an interested party . . . may request in writing that [Commerce] conduct an administrative review

. . . of specified individual exporters or producers covered by an [antidumping] order . . . .”).

Indeed, these requests are typically a letter of one or two pages that contain no more specific

claim than that dumping may have been occurring or that a company wishes to have an accurate

dumping margin for the period of review. Given the differences in commencing these two

proceedings, it is not reasonable that the “allegation” requirement be retained in administrative

reviews.

       In addition, the court notes that the “allegation” requirement specifically states that a

targeted dumping allegation must be “filed within the time indicated in § 351.301(d)(5),” a

subsection that, by its own terms, applies only to investigations. 19 C.F.R. § 351.414(f)(3)

(2008); see 19 C.F.R. § 351.301(d)(5) (2008); see also Final Rule, 62 Fed. Reg. at 27,336

(“[Section] 351.301(d)(5) sets forth the time limit for a targeted dumping allegation in an

[antidumping] investigation.”). Therefore, the court finds that the “allegation” requirement of

§ 351.414(f)(3) (2008) does not apply to administrative reviews, and therefore, Commerce did

not act unlawfully by self-initiating its targeted dumping analysis.
Court No. 17-00071                                                                               Page 18

        B. The “Appropriate Statistical               Techniques”       Requirement        Applies     to
           Administrative Reviews
        Next, Stanley claims that the Final Results violate the “appropriate statistical techniques”

requirement of 19 C.F.R. § 351.414(f)(1)(i) (2008) because “the Cohen’s d [test] is not

appropriately used in a targeted dumping context.” Pls.’ Br. 16-17.

        In response, the Government argues that the “appropriate statistical techniques”

requirement does not apply to administrative reviews. Def.’s Br. 11 (“Stanley fails its heavy

burden of showing that Commerce’s interpretation of its own regulation, 19 C.F.R. § 351.414(f),

as not applying to administrative reviews, such as the one presently at issue, is not entitled to

deference. As such, the Court should sustain Commerce’s final results.”).

        Even considering Commerce’s sometimes extravagant claims for deference, stating that it

need not comply with the requirement that it use an appropriate statistical technique to determine

if targeted dumping may be present in a review, is surprising. Having chosen to employ the same

method to ferret out targeted dumping in reviews as in investigations,17 the Department cannot

willy-nilly decide to use portions of the regulations that lay out the method and discard others.

Using a statistical technique that is not appropriate would simply not be reasonable. In fact, it

would be an abuse of discretion to use an inappropriate statistical technique. See Impact Steel

Can. Corp. v. United States, 31 CIT 2065, 2074, 533 F. Supp. 2d 1298, 1305 (2007). Therefore,

Commerce must comply with the “appropriate statistical techniques” part of its regulation. As

shall be seen, however, the court further finds that an appropriate statistical technique was used

here.

             17
                           Commerce first used the Cohen’s d test in the antidumping investigation Xanthan
Gum From the People’s Republic of China, 78 Fed. Reg. 33,351 (Dep’t Commerce June 4, 2013)
(final determination).

Court No. 17-00071                                                                              Page 19

II.     Differential Pricing is a Reasonable Interpretation of the Statute

        Stanley argues that “[a]ll three elements [of differential pricing] manifest an unreasonable

interpretation of the statute and do not effectuate the statute’s purpose.” Pls.’ Br. 18.

        A. The Cohen’s d Test

        Stanley’s first argument against the use of Commerce’s differential pricing analysis is

that the Cohen’s d test “contravenes both congressional guidance and Commerce’s obligation to

calculate dumping margins as accurately as possible.” Pls.’ Br. 18-19 (citation omitted).

According to Stanley, this is primarily because the Cohen’s d measures the effect of an

intervention, and not just the difference between two groups or sets of data, and therefore its use

is inappropriate in the targeted dumping context. Pls.’ Br. 19.

        As an initial matter, Stanley’s claims, taken as a whole, invite the court to answer the

question as to whether the Cohen’s d test, as used by Commerce, together with the ratio test

constitute a reasonable way of determining if differential pricing is present. In other words, the

question is whether Commerce’s method is fit for the purpose to which it is put. While it may be

that, were the question whether the Cohen’s d statistic, as originally envisioned by Dr. Cohen, is

a reasonable way of identifying a pattern of prices that differ significantly among purchasers,

regions, or periods of time, then Stanley’s arguments would have some purchase.18 Because,

             18
                           Commerce stated in its Final Results that it “has relied upon . . . a specific
approach developed by Jacob Cohen called the ‘d’ statistic or, as the Department has labeled it,
the ‘Cohen’s d coefficient.’” Final I&D Memo at 9. As shall be seen, while there are some
differences in how Commerce calculates the Cohen’s d and the method generally used in the
social sciences to determine the effect size of a particular intervention, Commerce’s calculation
is nevertheless based on the method developed by Dr. Cohen himself, and any differences do not
make the test unrecognizable, but instead, appear to be the result of Commerce’s ultimate
purpose for conducting the test, i.e., determining whether prices for comparable merchandise
differ significantly by purchaser, region, or period of time.

Court No. 17-00071                                                                           Page 20

however, the court is tasked with determining whether Commerce’s method, as actually applied,

is a reasonable interpretation of the statute (as distinct from, for instance, a reasonable

interpretation of Dr. Cohen’s work) it must look at what Commerce has actually done, not what

the Cohen’s d has been used for in other contexts.

       Notwithstanding the origin of the Cohen’s d as generally for use in the social sciences,

Commerce states that the test “may be instructive for purposes of examining whether to apply an

alternative comparison method in this administrative review” because it “is a generally

recognized statistical measure of the extent of the difference between the mean . . . of a test

group and the mean of . . . a comparison group.” Preliminary I&D Memo at 19-20. Although

Stanley argues that using the Cohen’s d test is inappropriate in the targeted dumping context,

plaintiff points to no evidence demonstrating why the test cannot be used in a “business” or

“finance” context or should be restricted to the social sciences. Moreover, it is not the case, as

Stanley argues, that effect size may only be used to quantify the effectiveness of a particular

intervention. See, e.g., Robert Coe, It’s the Effect Size, Stupid at 1. As Commerce notes:

       The difference in two prices, such as the difference in the mean prices for two
       groups (e.g., ten dollars), has no inherent meaning unless it is relevant to a given
       benchmark. For example, a ten dollar difference in the price of two cars is
       substantially different than a ten dollar difference in the price of a
       hamburger. . . . For the Cohen’s d coefficient, this examination of the price
       differences between test and comparison groups is relative to the “pooled standard
       deviation.” The use of a simple average in determining the pooled standard
       deviation equally weighs a respondent’s pricing practices to each group and the
       magnitude of the sales to one group does not skew the outcome. . . . The pooled
       standard deviation reflects the dispersion, or variance, of prices within each of the
       two groups. . . . When the difference in the weighted-average sale prices between
       the two groups is measured relative to the pooled standard deviation, then this
       value is expressed in standardized units based on the dispersion of the prices
       within each group. This is the concept of an effect size, as represented in the
       Cohen’s d coefficient.

Court No. 17-00071                                                                        Page 21

Final I&D Memo at 11-12. Thus, as used by Commerce, the Cohen’s d test performs a task

frequently performed by statistical analysis by converting absolute differences to standardized

variations from a mean. Here, Commerce hopes to find whether there is a “pattern of export

prices” for comparable merchandise that “differ significantly” among purchasers, regions, or

periods of time, as required by the statute. See 19 U.S.C. § 1677f–1(d)(1)(B)(i). The purpose of

the Cohen’s d test is to help determine whether the difference between two groups is significant

enough to be of practical importance. See, e.g., Robert Coe, It’s the Effect Size, Stupid, at 2. In

other words, Cohen’s d can contextualize the difference between two means by using the

variation found within each group of sales as a yardstick to compare the differences in prices to

certain purchasers, regions, or periods of time. By looking at the results of the test, Commerce

can determine how far apart the means of the two sales groups are in standardized units, which,

when combined with Cohen’s general interpretation conventions, allows Commerce to

contextualize the magnitude of that difference, and whether that difference is large enough to

matter (i.e., whether Commerce should consider the application of the A-T method).

       This, to the court, is a reasonable way to determine whether prices “differ significantly”

as required by the statute, particularly because, as Commerce emphasizes, simply finding a

difference between the groups in terms of a dollar amount does not necessarily inform

Commerce about the magnitude of that difference (i.e., whether it is “significant”). Commerce

has supplied an adequate explanation as to why it is useful to use a statistical analysis, such as

the Cohen’s d test (as applied by Commerce), as distinct from an arithmetical comparison.

Stanley has supplied no reason why Commerce’s use of the Cohen’s d is not an appropriate

statistical technique and the court cannot find one. Therefore, the court finds that Commerce’s
Court No. 17-00071                                                                         Page 22

use of the Cohen’s d test as used in Commerce’s targeted dumping analysis is reasonable,

adequately explained, and therefore, lawful and supported by substantial evidence.

        Next, Stanley argues that Dr. Cohen’s classification of effect sizes as small, medium, and

large is “arbitrary” and the classifications are “neither fixed nor defined by Cohen’s d,” but are

“merely conventions . . . that Jacob Cohen himself acknowledge[d] the danger of using . . . out of

context.” Pls.’ Br. 22 (internal quotations marks omitted) (“Commerce defended [Dr. Cohen’s

classifications] by asserting that ‘the large threshold provides the strongest indication that there

is a significant difference between the means of the test and comparison groups.’ This rationale

merely relies on the obvious: something ‘large’ is bigger than something ‘small.’ It fails to

explain why any of Cohen’s classifications are appropriately used to analyze nail prices or why

price differences that are a fraction (0.8) of a standard deviation mean anything at all in selling

nails.”).

        The court is unconvinced, however, that Commerce’s use of the “small,” “medium,” and

“large” thresholds is not reasonable. First, as Commerce stated, its classifications are “generally

accepted thresholds for the Cohen’s d test” which “have been widely adopted” by practitioners

using the Cohen’s d coefficient. Final I&D Memo at 11 (internal quotation marks omitted); see

also David M. Lane, Difference Between Two Means at 2. The articles referenced by Stanley19

demonstrate as much. See, e.g., Robert Coe, It’s the Effect Size, Stupid, at 5 (“Another way to

interpret effect sizes is to compare them to the effect sizes of differences that are familiar. For

        19
                Stanley submitted several academic articles for the record of this review,
including: It’s the Effect Size, Stupid: What Effect Size Is and Why It Is Important by Robert Coe,
and Difference Between Two Means by David M. Lane. See Stanley Submission of Factual
Material (July 1, 2016), P.R. 230, bar code 3483603-01, Attachs. A, B, ECF No. 34.
Court No. 17-00071                                                                            Page 23

example, Cohen . . . equates [an effect size of 0.8] to the difference between the heights of 13

year old and 18 year old girls.”).

        Moreover, Commerce does not apply the chosen thresholds in an arbitrary manner: only

the “large” threshold (which Cohen generally described as a “grossly perceptible [effect size]

and therefore large” and has also equated it to the difference in IQ between a Ph.D.20 degree

holder and a typical college freshman) becomes the touchstone measure of a “significant”

difference in prices. Robert Coe, It’s the Effect Size, Stupid, at 5; see Final I&D Memo at 11-12.

Keeping in mind that the Cohen’s d does not identify dumping, but rather a pattern of export

prices for comparable merchandise that differ significantly among purchasers, regions, or periods

of time, the use of a grossly perceptible standard is reasonable. Accordingly, the court finds that

Commerce lawfully used these thresholds to help it determine which sales “pass” its Cohen’s d

test.

        Stanley then argues thatthe Cohen’s d is “a form of statistical inference” which should

not be “used when the entire data population is known” and must generally be accompanied by a

“confidence interval,”21 which Commerce failed to provide. Pls.’ Br. 23-24. In addition, Stanley

             20
                           While it may be that only the holder of a Ph.D. such as Dr. Cohen would have
used this example, the point is well taken.
        21
                In statistics, determining how well a sample statistic (i.e., when the entire
population is not known) estimates the underlying population value can be addressed by using a
confidence interval which provides a range of values likely to contain the population parameter
of interest. In It’s the Effect Size Stupid, Coe explains how a confidence interval may be used in
the context of determining effect size:

        Clearly, if an effect size is calculated from a very large sample it is likely to be
        more accurate than one calculated from a small sample. This ‘margin for error’
        can be quantified using the idea of a ‘confidence interval’, which provides the
        same information as is usually contained in a significance test: using a ‘95%

                                                                            (footnote continued . . . )

Court No. 17-00071                                                                                                                                             Page 24

claims that Commerce must account for “statistical significance” in conducting its differential

pricing analysis. Pls.’ Br. 25.

             Stanley’s complaints about the use of a form of the Cohen’s d test when the entire

population is known are a bit puzzling. As Commerce notes

             the data upon which the statistical measure of effect size is based are not random
             samples, but rather the entire population of data (i.e., the U.S. sales to each
             purchaser, region, and time period). Stanley has reported all of its sales of subject
             merchandise in the U.S. market during the [POR], and it is this data upon which
             the Department is basing its analysis consistent with the requirements of [19
             U.S.C. § 1677f–1(d)(1)(B)], just as it has when calculating Stanley’s weighted-
             average dumping margin. Accordingly, the Department's calculation of the
             Cohen’s d coefficient includes no noise or sampling error as the underlying means
             and variances used to calculate the Cohen’s d coefficient are not estimates, but the
             actual values based on the complete U.S. sales data as reported by Stanley in this
             review.

Final I&D Memo at 10-11.

             This is an important observation, as normally the Cohen’s d is used to make inferences

from samples. Then, another test, a statistical significance test, is used to determine whether the

findings were likely due to chance. Statistical significance and effect size are difference

concepts: the former demonstrates that there is a difference between groups that is probably not

             confidence interval’ is equivalent to taking a ‘5% significance level’. To calculate
             a 95% confidence interval, you assume that the value you got (e.g. the effect size
             estimate of 0.8) is the ‘true’ value, but calculate the amount of variation in this
             estimate you would get if you repeatedly took new samples of the same size (i.e.
             different samples of 38 children). For every 100 of these hypothetical new
             samples, by definition, 95 would give estimates of the effect size within the ‘95%
             confidence interval’. If this confidence interval includes zero, then that is the
             same as saying that the result is not statistically significant. If, on the other hand,
             zero is outside the range, then it is ‘statistically significant at the 5% level’. Using
             a confidence interval is a better way of conveying this information since it keeps
             the emphasis on the effect size – which is the important information – rather than
             the p-value.

Robert Coe, It’s the Effect Size, Stupid, at 8.

Court No. 17-00071                                                                          Page 25

the result of chance, while the latter says something about the size of the difference. See, e.g.,

Robert Coe, It’s the Effect Size, Stupid, at 8 (“It is important to know the statistical significance

of a result, since without it there is a danger of drawing firm conclusions from studies where the

sample is too small to justify such confidence. However, statistical significance does not tell you

the most important thing: the size of the effect.”). Because the Cohen’s d test, as used by

Commerce, employs the entire universe of data, there is no need to test for statistical

significance. That is, no inference is being made from a sample. See Final I&D Memo at 10-11.

Thus, since the entire data population is available, the concerns that normally require a finding of

statistical significance using a second test and an accompanying confidence interval are not

present in Commerce’s differential pricing analysis.

       Moreover, simply because the Cohen’s d has traditionally been applied as a form of

statistical inference (i.e., a test used when only samples of a population are available), plaintiff

points to no evidence tending to suggest that it cannot be used when the entire population is

known. As with many statistical tests, the appropriateness of a particularly formula depends on

how the problem is defined. Where, as here, Commerce has defined the problem as determining

whether the magnitude of the difference among sales is worth paying attention to (and knowing

that the pricing data is not merely a sample, but represents the entire population), using the

Cohen’s d test is not unreasonable. See Final I&D Memo at 10-11. The Cohen’s d has been

described as the “standardised mean difference between two groups,” and as such, can be useful

to Commerce in finding whether there is a pattern of prices that differ significantly, as required

by the statute. See Robert Coe, It’s the Effect Size, Stupid, at 3. Put simply, the results of the

Cohen’s d test, where 100 percent of the sales are known, are likely to be more reliable because

they do not rely on inference.

Court No. 17-00071                                                                         Page 26

       For these reasons, the court finds that Commerce’s use of the Cohen’s d test in the

context of a targeted dumping evaluation is not unreasonable and that it aids in Commerce

fulfilling its obligation to calculate dumping margins as accurately as possible.

       B. Commerce’s Calculation of the Cohen’s d

       Next, Stanley argues that “[e]ven if it were reasonable to use the Cohen’s d statistic in a

targeted dumping context, the Final Results would nevertheless be unlawful because Commerce

incorrectly calculates the Cohen’s d statistic, which inflates the Cohen’s d coefficients and the

resulting [Cohen’s d test] ‘pass’ rates.” Pls.’ Br. 26. Stanley makes three arguments to support its

position.

       First, Stanley claims that the Cohen’s d test is incorrectly calculated because Commerce

“calculated the pooled standard deviation[22] in the Cohen’s d statistic,” which gives equal weight

to the squared standard deviations of the test and comparison price groups, “despite irrefutable

evidence that the test groups for Stanley were much smaller in volume and had smaller standard

deviations than the comparison groups.” Pls.’ Br. 26-27. To bolster its argument, Stanley looks

to the Robert Coe article it submitted, It’s the Effect Size, Stupid (often cited by Commerce),

which the company claims “is clear that where either the size or the variability of the test and

comparison groups is different, the correct calculation of the pooled standard deviation in the

Cohen’s d statistic requires that the standard deviations must be weighted by size.” Pls.’ Br. 27

(“‘The use of a pooled estimate of standard deviation depends on the assumption that the two

calculated standard deviations are estimates of the same population value,’ and ‘[i]nterpretation

of effect-size generally depends on the assumptions that ‘control’ and ‘experimental’ group

       22
                 The pooled standard deviation is an aggregate measure of the distribution of
prices (that is, the variances) within the test and comparison groups.
Court No. 17-00071                                                                         Page 27

values are normally distributed and have the same standard deviations.’” (quoting Robert Coe,

It’s the Effect Size, Stupid, at 6, 9)). Thus, Stanley claims that, by not weighting the standard

deviations of the groups, Commerce’s approach effectively assumed the test and comparison

groups for Stanley’s CONNUMs were of equal population values with equal standard deviations

from the mean. For Stanley, because the test and comparison groups are not of equal population

value and do not have the same variances, Commerce’s method is unreasonable.

       Commerce’s calculation of its Cohen’s d test is reasonable. Stanley’s argument is

essentially that what Commerce calls the “Cohen’s d test” is not actually the Cohen’s d test, and

that Commerce’s tinkering with the test has resulted in an unreasonably high number of

“passing” sales. It is possible that Commerce’s insistence that it is applying the Cohen’s d, rather

than a variation of it, has caused some mischief. While it may be that the Department concluded

that affixing a famous name to its calculations would enhance its claim that it was satisfying the

injunction found in the regulation that it use “standard and appropriate statistical techniques,”

attaching the Cohen’s d name has opened a world of possibilities to talented lawyers. The court

reiterates, however, that the appropriateness of any statistical formula depends on how the

problem is defined. Indeed, even the Coe paper, relied on by Stanley, demonstrates that there are

different ways to calculate a Cohen’s d statistic depending on population sizes and type of

intervention.23 See, e.g., Robert Coe, It’s the Effect Size, Stupid, at 10-11.

       23
                It bears repeating that here the entire universe of sales is known, and there is no
intervention.
Court No. 17-00071                                                                                 Page 28

        Here, the calculation of the pooled standard deviation is important because a smaller

standard deviation can result in small price differences24 having a “large” effect size (and

therefore, “passing” the Cohen’s d test). Stanley is correct in noting that the test group will likely

have a smaller number of observations (and variance) than the comparison group,25 and that in

these circumstances, using a simple average of the groups’ standard deviations would result in a

lower pooled standard deviation than would a pooled standard deviation based on a weighted-

average of the groups’ standard deviations. Commerce, however, has stated that the pooled

standard deviation should reflect the average pricing behavior for the two groups, and not

necessarily an average of all individual sales. See Final I&D Memo at 12 (“The use of a simple

average in determining the pooled standard deviation equally weighs a respondent’s pricing

practices to each group and the magnitude of the sales to one group does not skew the

outcome.”) (emphasis added).

        Commerce’s decision to use a simple average is reasonable in the targeted dumping

context where the nature of the problem is to ferret out certain unlawful pricing behavior, i.e.,

that higher priced sales are being used to mask other dumped sales. Accordingly, a standard

deviation that gives equal weight to the pricing behavior toward a certain purchaser, or in a

certain region or period of time, is a reasonable way to create a benchmark by which to measure

the differences in a certain group of sales to the overall range of differences in the test and

comparison groups. See Mid Continent Steel & Wire, Inc. v. United States, 41 CIT __, __, 219 F.

             24
                           Price differences, in this case, refer to differences in the weighted-average net
prices of the test and comparison groups.
        25
                And indeed, the specific numbers given by Stanley show that this was the case
here. Pls.’ Br. 27-28.

Court No. 17-00071                                                                           Page 29

Supp. 3d 1326, 1342 (2017) (“It is discernible from Commerce’s explanations that Commerce

views the pooled standard deviation as an average reflective of the respondent’s average pricing

behavior for these two groups, rather than an average reflective of all of the individual prices.”).

       In the Final Results, Commerce states that its goal is to determine if an exporter’s pricing

behavior as to a certain purchaser, region, or period of time differs significantly from that

exporter’s pricing behavior as to all other purchasers, regions, or periods of time, and thus, that

an exporter’s pricing behavior in a “test” group is equally important to its pricing behavior in a

“control” group. See Final I&D Memo at 12. Because of this, Commerce reasonably found that

using a simple average achieved this balance:

       The pooled standard deviation reflects the dispersion, or variance, of prices within
       each of the two groups. When the variance of prices is small within these two
       groups, then a small difference between the weighted-average sale prices of the
       two groups may represent a significant difference, but when the variance within
       the two groups is larger (i.e., the dispersion of prices within one or both of the
       groups is greater), then the difference between the weighted-average sale prices of
       the two groups must be larger in order for the difference to perhaps be significant.
       When the difference in the weighted-average sale prices between the two groups
       is measured relative to the pooled standard deviation, then this value is expressed
       in standardized units based on the dispersion of the prices within each group. This
       is the concept of an effect size, as represented in the Cohen’s d coefficient.

Final I&D Memo at 12. In other words, any price differences found using Commerce’s Cohen’s

d test are relative to the variance of prices within the two groups, and thus are tailored to the

individual pricing behavior at issue. See Final I&D Memo at 12; see also Soc Trang Seafood

Joint Stock Co. v. United States, 42 CIT __, __, Slip Op. 18-75, at 17 (June 21, 2018)

(“Commerce’s [Cohen’s d test] evaluates whether the price variance is significant as compared

to the actual prices at issue, and not as compared to some other set of prices. The statute allows

Commerce to look at individual pricing behavior.”). The court finds this explanation reasonable

because Commerce is able to contextualize the magnitude of the pricing differences between the

Court No. 17-00071                                                                          Page 30

test and comparison groups, which helps it to determine whether there is a pattern of prices that

differ significantly among purchasers, regions, or periods of time. That is, notwithstanding the

difference in population and variance between the two groups, the pricing behavior in each group

is of equal importance, and therefore, using a simple average to calculate the pooled standard

deviation (thereby giving equal weight to the standard deviations in both groups) is reasonable.

         Plaintiff’s second argument is that there is an “upward bias” in Commerce’s Cohen’s d

test calculations which is “systemic.” Pls.’ Br. 29. Stanley argues that Commerce’s use of the

Cohen’s d test in the targeted dumping context, together with its method of calculating the

pooled standard deviation, results in a test meant to lead to high pass rates. See Pls.’ Br. 30. To

support its position, Stanley references a chart attached to its initial case brief that reviews the

preliminary results of Commerce’s proceedings from March 2013 (its first use of the Cohen’s d

test in Xanthan Gum From the People’s Republic of China) through September 30, 2016 (shortly

after Commerce published the Preliminary Results of this review). Pls.’ Br. 29 (citing Stanley

Case Br., Addendum C, P.R. 269, bar code 3518140-01). For Stanley, the chart demonstrates that

“Commerce’s incorrect calculations of the Cohen’s d coefficient generate ‘pass’ rates that exceed

the Department’s 33 percent threshold for using the A-T method in over three-quarters of the

decisions.”26 Pls.’ Br. 29. This upward bias, according to plaintiff, “leads to an unreasonably

             26
                           Specifically, Stanley claims:

         As of September 30, 2016, Commerce had issued preliminary decisions with
         respect to 279 respondents that exported a wide variety of merchandise ranging
         across an array of industries. Of these 279 respondents, the Department found
         only 25 not to have any sales that “passed” [Cohen’s d test] and only 45 more to
         have [Cohen’s d test] “pass” rates below the 33 percent threshold. The remaining
         209 respondents included 95 respondents with [Cohen’s d test] “pass” rates over
         66 percent and three respondents with [Cohen’s d test] “pass” rates of 100

                                                                          (footnote continued . . . )

Court No. 17-00071                                                                                                                                             Page 31

frequent use of the ratio and meaningful difference tests,” which “[does] not effectively protect

respondents from the bias inherent in the [Cohen’s d test]” and ultimately results in an

inappropriate use of the A-T method. Pls.’ Br. 30-31.

             Commerce’s use of the Cohen’s d test in the targeted dumping context is not

“systemically biased” toward finding passing sales. The court has previously explained its view

as to the reasonableness of using the Cohen’s d test in the targeted dumping context as well as

Commerce’s calculation of the pooled standard deviation. See supra Part II.A, B. As to the chart

cited by Stanley purporting to show an upward bias in its calculation method, the court agrees

with defendant that the data fails to establish “that a bias exists in Commerce’s application of the

Cohen’s d test.” Def.’s Br. 22. Commerce states:

             The data show that 207 of the 276 cases cited involved a sufficient percentage of
             sales passing the Cohen’s d test to consider the application of an alternative
             comparison methodology. Of these, the Department only applied the [A-T]
             method to either a portion or all of a respondent’s sales in 85 of these 207
             determinations. Accordingly, relying upon Stanley’s own data, there does not
             exist a bias in the Department’s application of the differential pricing analysis,
             including the Cohen’s d test, based on the use of a simple average in determining
             the pooled standard deviation. Around one-third of the cases to which Stanley
             cites resulted in the application of an alternative comparison methodology,
             representing less than one-half of the cases in which there existed a pattern of
             prices that differ significantly pursuant to the Cohen’s d and ratio tests.

             percent. In other words, Commerce has concluded that 45 percent of the
             respondents in preliminary decisions each targeted more than two-thirds of their
             sales – and that three respondents targeted every sale. It makes no economic or
             financial sense for any one company to “target” the majority of its sales. It is
             unreasonable to conclude that almost half of all investigated companies do so,
             particularly when those companies sell a wide variety of products under an
             equally wide variety of market dynamics. Moreover, Commerce's conclusions that
             three companies targeted all of their sales is simply illogical – if all of a
             company's sales are “targeted,” then none can be.

Pls.’ Br. 29-30.

Court No. 17-00071                                                                          Page 32

       Stanley states that the data show 95 respondents with [Cohen’s d test] “pass” rates
       of over 66 percent, and three with “pass” rates of 100 percent. Stanley avers that
       this demonstrates the unreasonableness of differential pricing because it makes no
       economic sense for any one company to “target” the majority of its sales, and
       because if all sales are “targeted,” then none can be. This line of reasoning
       demonstrates a misunderstanding of how the Department determines the existence
       of a pattern of export prices that differs significantly among purchasers, regions,
       or time periods. Indeed, the focus is not on “targeting” and economic decision-
       making, but on the difference between export prices. For example, consider two
       purchasers, A and B. If the prices to purchaser A are found to differ significantly
       from the prices to purchaser B, then it follows that the prices to purchaser B differ
       significantly from the prices to purchaser A. Here, it is reasonable to conclude
       that all prices differ significantly. Similarly, if the prices to purchaser A do not
       differ significantly from the prices to purchaser B, then it follows that the prices
       to purchaser B do not differ significantly from the prices to purchaser A. Here, it
       is reasonable to conclude that none of the prices differ significantly. While
       Stanley pointed to three instances where all of the respondent’s sales prices
       differed significantly, there are also 25 cases in the data where none of the sales
       prices differed significantly. This demonstrates that the Department’s approach is
       reasonable and does not exhibit a bias; the phenomenon to which Stanley points
       as proof of bias is greatly outweighed by the opposite result, i.e. that no sales pass
       the Cohen’s d test. Accordingly, Stanley’s own data demonstrate that, if anything,
       there is a tendency against finding a pattern of prices that differ significantly
       across purchasers, regions, or time periods.

Final I&D Memo at 14-15 (emphasis added). In addition, Stanley’s own numbers show that the

ratio test and meaningful difference test weed out circumstances in which the A-T method need

not be applied (i.e., circumstances in which there is not sufficient evidence that targeted dumping

may be occurring). Therefore, since less than half of the cases cited in Stanley’s numbers

resulted in an application of the A-T method, it is apparent that there is no unreasonable, or

biased, result in Commerce’s use of the Cohen’s d test.

       Finally, Stanley claims that it is “unreasonably difficult” for a respondent to revise its

pricing to avoid high “pass” rates “because the standard deviations of the test and comparison

groups comprising the pooled standard deviation become smaller as any differences in a

respondent’s prices for that CONNUM are eliminated.” Pls.’ Br. 31. Plaintiff then argues that

Commerce’s calculation fails to account for “decreases in the size of price variances that result
Court No. 17-00071                                                                          Page 33

from a respondent’s efforts to eliminate differences in its prices.” Pls.’ Br. 32. For plaintiff,

because “smaller price differences render smaller pooled standard deviations” in Commerce’s

application of the Cohen’s d test, Cohen’s d coefficients will fall into the “large” category (and

thus, “pass” the Cohen’s d test) even if a respondent attempts to attain price homogeneity. Pls.’

Br. 32.

          Stanley’s argument appears to misunderstand the relation of the Cohen’s d test to the

statute. The Cohen’s d test does not determine whether Commerce will calculate a dumping

margin using the A-T method, but rather, is only one of two tests27 used to determine whether

prices differ significantly, i.e., whether there is a pattern of differing prices for comparable

merchandise among purchasers, regions, or periods of time. Indeed, under the ratio test, before

Commerce can even consider applying the A-T method to any of Stanley’s sales, more than 33

percent of its total sales value must pass the Cohen’s d test. In addition, even if Commerce’s

Cohen’s d and ratio tests suggest there is a pattern of export prices that differ significantly among

purchasers, regions, or periods of time, such that Commerce may consider the application of the

A-T method, it still must explain why the A-A method cannot account for these differences.

          As the Department noted, “[a] company may sell subject merchandise in the United

States market at significantly different prices, yet none of these sales are priced at less than

normal value,” and that in such situations, “the [A-A] method will be able to account for such

differences” because there are no dumped sales. Final I&D Memo at 15. Moreover, in the

hypothetical suggested by plaintiff, where an exporter has changed its pricing practices to attain

near homogeneity, there will likely not be a “meaningful difference” between the margin

             27
                           The other test is the ratio test.

Court No. 17-00071                                                                          Page 34

calculated using the A-A method and that calculated using the A-T method. This is because,

under such circumstances, the weighted-average export price (i.e., the export price calculated

using the A-A method) would be very close to the price of individual transactions in the United

States, and therefore, the A-A method would be deemed able to account for such differences. See

infra Part II.C.ii. Thus, high Cohen’s d pass rates do not automatically lead to the application of

the A-T method. In any event, all that is required of Commerce under the statute at this stage in

its analysis is to determine whether “there is a pattern of export prices (or constructive export

prices) for comparable merchandise that differ significantly among purchasers, regions, or

periods of time.” 19 U.S.C. § 1677f–1(d)(1)(B)(i). Commerce’s calculation of the Cohen’s d test,

in conjunction with its ratio test, is a reasonable method for making this determination.

       C. Differential Pricing Does Not Contravene the Statute

           i. The Ratio Test

       Following the Cohen’s d test, Commerce uses the “ratio test” to “assess[] the extent of

the significant price differences for all sales as measured by the Cohen’s d test.” Preliminary

I&D Memo at 20. If the value of sales to certain purchasers, regions, and time periods that

“pass” the Cohen’s d test accounts for 66 percent or more of the value of a respondent’s total

sales, then, for Commerce, “the identified pattern of prices that differ significantly supports the

consideration of the application of the [A-T method] to all sales . . . .” Preliminary I&D Memo at

20. If the value of passing sales accounts for 33 percent or less of the value of a respondent’s

total sales, however, then the results do not support the application of the A-T method to any of

the respondent’s sales. If the value of passing sales is between 33 and 66 percent of the value of a

respondent’s total sales, then Commerce may consider the application of the A-T method for all

Court No. 17-00071                                                                          Page 35

passing sales, but the A-A method will be used for all remaining sales. See Preliminary I&D

Memo at 20.

       Stanley argues that the differential pricing analysis fails to meet either of the two

preconditions necessary before Commerce may apply the A-T method under 19 U.S.C. § 1677f–

1(d)(1)(B). Pls.’ Br. 32. That is, for Stanley, the differential pricing analysis does not identify a

“pattern” of prices that differ significantly among purchasers, regions, or periods of time, nor

does it explain why the A-A method cannot account for such differences. Stanley asserts that this

is because (1) the “ratio” test merely “stratifies Cohen’s d test pass rates,” it does not describe a

pattern; and (2) the meaningful difference test fails to explain why Commerce cannot account for

a perceived price difference using the A-A method. Pls.’ Br. 33, 35.

       Defendant responds that “Commerce explained in the final results how the stratification

of pass rates under the Cohen’s d test identifies a pattern of prices that differ significantly.”

Def.’s Br. 26. According to defendant, Commerce uses the ratio test to “complete its

determination of whether there exists a pattern of prices that differ significantly by purchaser,

region, or period of time” because, even if sales for one or more groups of comparable

merchandise may pass the Cohen’s d test, “it does not necessarily follow that, in relation to the

total volume of a respondent’s export sales, there is sufficient evidence that a pattern of prices

exists that differ significantly.” Def.’s Br. 26. In other words, for Commerce, the ratio test

completes Commerce’s determination of whether a pattern of prices exists that differ

significantly by “assess[ing] the extent of the significant price differences for all sales as

measured by the Cohen’s d test.” Preliminary I&D Memo at 20.

       Commerce has reasonably explained how the ratio test, in conjunction with the Cohen’s d

test, satisfies 19 U.S.C. § 1677f–1(d)(1)(B)(i) (i.e., how the tests identify a “pattern of export

Court No. 17-00071                                                                        Page 36

prices” for comparable merchandise that “differ significantly among purchasers, regions, or

periods of time.”). Here, Commerce has found that, when the value of a respondent’s U.S. sales

that “pass” the Cohen’s d test accounts for more than 33 percent of the value of its total sales,

this indicates a pattern of price differences exists such that Commerce may consider applying the

A-T method to a limited amount of the respondent’s sales. See Final I&D Memo at 18. Likewise,

Commerce maintains that when the value of a respondent’s U.S. sales that “pass” the Cohen’s d

test accounts for 66 percent or more of the value of its total sales, this indicates there exists a

pattern of price differences such that Commerce may consider applying the A-T method to all of

the respondent’s sales. See Final I&D Memo at 17-18. By creating these thresholds, Commerce

reasonably identified when price differences are more than just random occurrences, i.e., when a

“pattern” exists. Indeed, in order for Commerce to apply A-T to all of a respondent’s sales, most

of the respondent’s sales (roughly two thirds) must have “passed” the Cohen’s d test, a threshold

unlikely to be the result of chance.

       This method is a reasonable one for meeting the prerequisite of § 1677f–1(d)(1)(B)(i),

particularly since the statute gives no guidance as to how Commerce should make its

determination. 19 U.S.C. § 1677f–1(d)(1)(B); see also Final I&D Memo at 17 (“Neither the

statute nor the SAA[28] provide any guidance in determining how to apply the [A-T] method once

the requirements of [19 U.S.C. § 1677f–1(d)(1)(B)(i)] and (ii) have been satisfied. Accordingly,

the Department has reasonably created a framework to determine how the [A-T] method may be

       28
                Statement of Administrative Action accompanying the Uruguay Round
Agreements Act (“SAA”), H.R. Doc. No. 103-316, vol. 1, at 842-43, reprinted in 1994
U.S.C.C.A.N. 4040, 4177-78. The SAA “shall be regarded as an authoritative expression by the
United States concerning the interpretation and application of the Uruguay Round Agreements
and this Act in any judicial proceeding in which a question arises concerning such interpretation
or application.” 19 U.S.C. § 3512(d).
Court No. 17-00071                                                                         Page 37

considered as an alternative to the standard [A-A] method based on the extent of the pattern of

prices that differ significantly as identified with the Cohen’s d test.”). Commerce was faced with

the task of creating a method for determining when it should use the A-T method. Stanley has

failed to show that Commerce’s method does not do what it is supposed to do. Accordingly, the

court finds that Commerce’s use of the ratio test is a reasonable interpretation of § 1677f–

1(d)(1)(B)(i).

            ii. The Meaningful Difference Test

       Under the meaningful difference test, Commerce first calculates the dumping margin that

would result by applying the A-A method to all sales, i.e., Commerce calculates a dumping

margin the same way that it would absent any targeted dumping procedures. Commerce then

calculates two additional dumping margins: (1) by applying the A-T method to all sales that

passed the Cohen’s d test and the A-A method to the remaining sales, and (2) by applying the A-

T method to all sales.29 Preliminary Analysis Memorandum at 16. Depending on the results of

the ratio test,30 Commerce then compares (1) the margin calculated under its normal method (i.e.,

       29
                While Commerce states that “the Department tests whether using an alternative
comparison method, based on the results of the Cohen’s d and ratio tests described above, yields
a meaningful difference in the weighted-average dumping margin as compared to that resulting
from the use of the [A-A] method only,” Preliminary I&D Memo at 20, the Amended Final
Results Analysis Memo shows that Commerce actually calculated three margins: (1) by applying
the A-A method to all sales; (2) by applying the A-T method to those sales that passed the
Cohen’s d test and the A-A method to all remaining sales; and (3) by applying the A-T method to
all sales. See Amended Final Results Analysis Memo at 2. The Department then, based on the
results of the ratio test, selects the appropriate A-T method and compares that margin to the
margin calculated using the A-A method. Amended Final Results Analysis Memo at 2.
       30
                As described above, the sales to which Commerce will apply the A-T method
(provided a “meaningful difference” is found) depends on the results the ratio test. If the results
of the ratio test indicate that passing sales represent 66 percent or more of a respondent’s total
sales value, Commerce will use the margin calculated by applying A-T to all sales for its
“meaningful difference” comparison. If the passing sales represent more than 33 percent and less

                                                                         (footnote continued . . . )
Court No. 17-00071                                                                                                                                             Page 38

using the A-A method), and (2) the dumping margin calculated using the A-T method, to

determine if there is a “meaningful difference” between the two. Preliminary I&D Memo at 20.

Commerce considers there to be a “meaningful difference” when the comparison demonstrates

(1) that there is a 25 percent relative change in the weighted-average dumping margin between

the A-A method and the appropriate A-T method where both margins are above the de minimis

threshold; or (2) that the A-T method generates a dumping margin that crosses the de minimis

threshold when compared to the A-A method. If a meaningful difference exists, Commerce

infers that the A-A method is unable to account for the price differences among particular

purchasers, regions, or in particular periods of time (i.e., that the A-A method would not

“unmask” observed pricing differences which evidence targeted dumping). See Apex Frozen

Foods Private Ltd. v. United States, 862 F.3d 1337, 1348 (Fed. Cir. 2017) (“Apex II”)

(“Commerce’s meaningful difference analysis—comparing the ultimate antidumping rates

resulting from the A-A methodology, without zeroing; and the A-T methodology, with zeroing—

was reasonable.”).

             Notwithstanding the Federal Circuit’s approval of Commerce’s meaningful difference

test31 (applied and explained in the same manner as Commerce has done so here), Stanley argues

that the Court has not addressed its argument, which is that the meaningful difference test is

“flawed methodologically” because Commerce performs it’s A-A and A-T comparison “based

on Stanley’s total sales even though it performed the [Cohen’s d test] based on sales of

individual CONNUMs.” Pls.’ Br. 37, 39-40 (“By separating the basis for its determination of a

than 66 percent of a respondent’s sales, then Commerce will use the margin calculated using the
A-T method on passing sales and the A-A method on remaining sales.
             31
                          Apex II, 862 F.3d at 1348.

Court No. 17-00071                                                                              Page 39

meaningful difference from the specific products that displayed significant price differences

Commerce failed to meet its statutory burden to explain why [the A-A method] could not

account for those price differences . . . .”). Therefore, Stanley claims that “the methodological

error that is fatal to the meaningful difference test was not at issue” in Apex II. Pls.’ Br. 37; see

also Pls.’ Reply Br., ECF No. 32, 12 (“While the Federal Circuit was explicit in approving

Commerce’s rationale . . . it has not addressed . . . the question Stanley has raised here

concerning whether Commerce’s specific implementation of the meaningful difference test

contravenes 19 U.S.C. § 1677f–1(d)(1)(B)(ii).”).

         For Stanley, the absence of a “reasonable nexus” between the meaningful difference test

and the Cohen’s d test not only “produce[s] distorted results,” but also represents an

unreasonable interpretation of 19 U.S.C. § 1677f–1(d)(1)(B). Pls.’ Br. 37. Stanley’s argument is

based on its reading of the “such differences” language found in § 1677f–1(d)(1)(B)(ii)’s

requirement that Commerce “explain why such differences cannot be taken into account using

[the A-A] method . . . .” 19 U.S.C. § 1677f–1(d)(1)(B)(ii) (emphasis added).32 Stanley claims

             32
                           Section 1677f–1(d)(1)(B) provides:

         [Commerce] may determine whether the subject merchandise is being sold in the
         United States at less than fair value by comparing the weighted average of the
         normal values to the export prices (or constructed export prices) of individual
         transactions for comparable merchandise, if—

                  (i)      there is a pattern of export prices (or constructed export prices) for
                           comparable merchandise that differ significantly among
                           purchasers, regions, or periods of time, and

                  (ii)     [Commerce] explains why such differences cannot be taken into
                           account using [the A-A method] . . . .

19 U.S.C. § 1677f–1(d)(1)(B) (emphasis added).

Court No. 17-00071                                                                       Page 40

that the “such differences” language references the “prices” portion of the “pattern of export

prices for comparable merchandise that differ significantly” language found in the statute. Pls.’

Br. 37 (citing 19 U.S.C. § 1677f–1(d)(1)(B)(i) (emphasis added)); Transcript of Oral Argument,

ECF No. 40 at 6-7. Thus, because Commerce found significant pricing differences using a

CONNUM-specific approach (the Cohen’s d test), Stanley argues that Commerce must also

conduct its meaningful difference test on a CONNUM-specific basis, i.e., by applying the A-A

method to sales of individual CONNUMs, rather than to Stanley’s overall sales.

       Although the Federal Circuit did not specifically address the argument raised by Stanley,

its holding nonetheless directs the court to find for the Government. As the Apex II Court noted,

“Commerce devised its meaningful difference test, in which antidumping rates—as they would

ultimately be applied for the A-A methodology versus an alternative—are compared, across all

sales,” and concluded that “there is no basis (statutory or otherwise) for demanding a distinction

between the meaningful difference analysis and the ultimate margin calculation.” Apex II, 862

F.3d at 1346, 47 (emphasis added). Thus, the Federal Circuit was fully aware of the method by

which the meaningful difference test was conducted and approved its use. Also, in “assess[ing]

whether Commerce’s reading of the statute was permissible and whether its implementation was

otherwise . . . unreasonable,” the Federal Circuit specifically found that the meaningful

difference test, that is, “comparing the ultimate antidumping rates resulting from the A-A

methodology” with the appropriate A-T method, “was reasonable.” Id. at 1348.

       Here, as Commerce states, “finding that there exists a pattern of prices that differ

significantly means only that the Department will consider whether the standard comparison

methodology can account for such differences,” i.e., whether using the A-A method as it would

ultimately be applied could account for the pattern of price differences found using the Cohen’s

Court No. 17-00071                                                                          Page 41

d test. Final I&D Memo at 15. For Commerce, “comparing the weighted-average dumping

margins calculated using the two comparison methods allows the Department to quantify the

extent to which the [A-A] method cannot take into account different pricing behaviors exhibited

by the exporter in the U.S. market.” Final I&D Memo at 13. The court agrees. The meaningful

difference test fulfills the statutory requirement that Commerce explain why the A-A method

cannot account for the perceived pattern of pricing differences. Moreover, the Federal Circuit has

noted that “[u]nder a plain reading of the statute [19 U.S.C. § 1677f–1(d)(1)(B)(ii)], the use of

‘such differences’ does not, in itself, manifest Congress’s intent to dictate how Commerce is to

make the determination whether the A-A method[] can account for potential targeted or masked

dumping.” Apex II, 862 F.3d at 1345. Thus, Commerce’s approach has been approved by the

Federal Circuit, and the court therefore finds that it was also reasonable here.

       Accordingly, the court finds the meaningful difference test, as applied, to be lawful under

19 U.S.C. § 1677f–1(d)(1)(B)(ii).

       D. Differential Pricing Does Not Contravene Congressional Intent as Expressed in
          the Legislative History

       In the Final Results, Commerce found that 77.8 percent of Stanley’s U.S. sales “passed”

the Cohen’s d test, and therefore, using the ratio test,33 applied the A-T method to all of Stanley’s

sales for the POR. Amended Final Results Analysis Memorandum at 2. Notably, Commerce

deemed sales to have “passed” the Cohen’s d test whether they passed because the test group’s

       33
                As discussed above, the ratio test provides that if the value of sales to certain
purchasers, regions, and time periods that “pass” the Cohen’s d test account for 66 percent or
more of the value of a respondent’s total sales, then Commerce considers there to be an
“identified pattern of prices that differ significantly” such that it may consider the application of
the A-T method to all sales. Preliminary I&D Memo at 20.
Court No. 17-00071                                                                           Page 42

sales were higher priced than the comparison group or lower priced than the comparison group,

with no inquiry into whether passing sales were actually dumped.34 Final I&D Memo at 16.

Stanley argues that “Commerce’s failure to limit its targeting analysis to sales that ‘pass’ the

[Cohen’s d test] with ‘low’ prices conflicts with the SAA’s express statement that ‘targeted

dumping’ comprises prices that are both dumped and below prices ‘to other customers.’” Pls.’

Br. 42 (“[T]he standard described in the SAA is prices ‘to other customers,’ not a price to ‘any

other customer,’ evidencing Congress’ intent that the possibility of targeted dumping is to be

measured in relation to prices below the general norm.”). Thus, for plaintiff, “[b]y embracing

higher than normal price sales as evidence of ‘targeting,’” the differential pricing analysis

“contravenes Congress’s intent as to what comprises the problem—targeted dumping—that

Commerce is authorized to address.” Pls.’ Br. 42. Stanley thus argues that Commerce’s approach

does not properly address targeted dumping, as it is supposed to, because Commerce considers

sales that are sold at a higher price than other sales to be evidence of targeted dumping.

       Stanley then claims that “embracing higher than normal prices as evidence of ‘targeting’

is conceptually absurd.” Pls.’ Br. 43. Stanley reasons that because “[t]he only rational reason to

‘target’ is to gain sales,” a seller cannot “successfully gain sales by charging the allegedly

‘targeted’ customer a higher price than it charges other customers for identical merchandise.”

Pls.’ Br. 43. Therefore, Stanley claims that the Final Results are unlawful because they ignore

the intent of the statute as articulated in the SAA to focus only on sales that were lower than the

norm. Pls.’ Br. 43.

       34
             That is, as long as there was a 0.8 standard deviation difference between the test
and comparison groups, Commerce considered the sales to have passed the Cohen’s d test.
Court No. 17-00071                                                                                  Page 43

        The court is not persuaded that the differential pricing analysis runs counter to

congressional intent. As an initial matter, the statute does not specify whether prices must

“differ” by being priced lower or higher than comparison sales. See 19 U.S.C. § 1677f–

1(d)(1)(B). Thus, Commerce has not violated the plain language of the statute. Moreover, as the

Department emphasized, “higher priced sales will offset lower priced sales, either implicitly

through the calculation of a weighted-average sale price for a U.S. averaging group, or explicitly

through the granting of offsets when aggregating the [A-A] comparison results, that can mask

dumping.” Final I&D Memo at 16. Therefore, when Commerce calculates the weighted-average

export price (or constructed export price) for sales included in a particular averaging group,35

higher priced sales may drive the averaging group’s export price up, potentially concealing

dumped sales within the group. In addition, when aggregating the results of the averaging groups

to determine the weighted-average dumping margin, higher priced sales could result in averaging

groups for which the weighted-average export price exceeds the weighted-average normal value,

which would offset the results of any averaging groups for which the weighted-average export

price is less than the weight-average normal value. Therefore, higher priced sales are relevant to

Commerce’s analysis. This is consistent with the SAA’s description of “concealed” targeted

dumping, which, according to the text, occurs when “an exporter may sell at a dumped price to

particular customers or regions, while selling at higher prices to other customers or regions.”

SAA at 842, 1994 U.S.C.C.A.N. at 4177-78. Thus, considering that the purpose of applying the

             35
                           An averaging group consists of “subject merchandise that is identical or virtually
identical in all physical characteristics and that is sold to the United States at the same level of
trade.” 19 C.F.R. § 351.414(d)(2).

Court No. 17-00071                                                                          Page 44

A-T method is to unmask targeted dumping, Commerce’s consideration of “higher priced” sales

(which may mask lower priced, or dumped, sales) is reasonable.

       As to Stanley’s argument that the SAA links “targeting” with “dumping,” the court is

also not convinced that the only sales relevant when determining whether prices differ

significantly are those that are lower priced than the comparison group. First, the SAA mentions

that the targeted dumping statute (19 U.S.C. § 1677f–1(d)(1)(B)) will provide a comparison

method in situations where the A-A or T-T method cannot account for a pattern of prices that

differ significantly among purchasers, regions, or time periods, i.e., “where targeted dumping

may be occurring.” SAA at 843, 1994 U.S.C.C.A.N. at 4178 (emphasis added). This statement

does not, on its face, confine Commerce’s method to solely analyzing sales at less than fair

value, nor does it require Commerce to make an affirmative finding of targeted dumping. See

Stanley Works (Langfang) Fastening Sys. Co. v. United States, 41 CIT __, __, 279 F. Supp. 3d

1172, 1191 (2017). As has been previously stated, the Cohen’s d test in no way measures

dumping—it only identifies a pattern of differing prices. In fact, every sale used to reach a

finding that there was such a pattern could be dumped or not dumped. That is, merely because a

sale is high in relation to the mean does not tell Commerce anything about whether or not it is a

sale at less than fair value (i.e., “dumped”). At the initial stage of its analysis, Commerce is only

tasked with determining whether there is a pattern of prices that differ significantly. If such a

pattern is found, Commerce will consider whether the A-A method can account for these

differences, and if it cannot, the SAA considers this to be evidence that targeted dumping may be

occurring.

       In addition, the SAA itself anticipates that targeted dumping encompasses “situations [in

which] an exporter may sell at a dumped price to particular customers or regions, while selling at

Court No. 17-00071                                                                          Page 45

higher prices to other customers or regions” and thus, explicitly considers higher priced sales to

be relevant. SAA at 842, 1994 U.S.C.C.A.N. at 4177-78 (emphasis added). Thus, not only does

the SAA contemplate considering higher prices in the targeted dumping context, but also, as the

Department states, by “considering all sales, higher priced sales and lower priced sales, the

Department is able to analyze an exporter’s pricing practice and to identify whether there is a

pattern of prices that differ significantly” by purchaser, region, or period of time. Final I&D

Memo at 16. As this Court has found, “[a]ll sales are subject to the differential pricing analysis

because its purpose is to determine to what extent a respondent’s U.S. sales are differentially

priced, not to identify dumped sales,” and therefore, “Commerce is not restricted in what type of

sales it may consider in assessing the existence of such a pattern so long as its methodological

choice enables Commerce to reasonably determine whether application of A-T is appropriate.”

Apex I, 144 F. Supp. 3d at 1330.

       In the end, plaintiff’s argument appears to conflate passing the Cohen’s d test with the

application of the A-T method and ultimately “unmasking” targeted dumping. The latter,

however, requires not only a finding of a pattern of prices that differ significantly among

purchasers, regions, or periods of time, but also an explanation as to why the A-A method cannot

account for such differences and a finding of dumping using A-T. These are separate analyses,

and a high result in the first does not necessarily determine the result of the second. Therefore,

the court finds that the differential pricing analysis is not inconsistent with congressional intent,

and Commerce reasonably considered both higher priced sales and lower priced sales in

evaluating whether there exists a pattern of export prices that differ significantly among

purchasers, regions, or periods of time.

Court No. 17-00071                                                                          Page 46

       E. Commerce’s Implementation of the Differential Pricing Analysis is Reasonable

       Next, Stanley argues that the procedure Commerce uses to form comparison groups in its

differential pricing analysis also results in high Cohen’s d test pass rates, and therefore, is an

unreasonable interpretation of the statute. According to Stanley, this is because Commerce

includes sales from test groups that “pass” the Cohen’s d test in its base (or “comparison”)

groups, thereby causing other sales to “pass” the Cohen’s d test that otherwise would not have

passed. Pls.’ Br. 44-45. Plaintiff thus argues that “when Commerce finds a sale in a test group to

pass the [Cohen’s d test], it nevertheless includes the anomalous price of that sale in the

comparison (i.e., base) group used to evaluate the prices of other test groups,” which results in

“passing” sales that would otherwise not pass. Pls.’ Br. 45. Therefore, plaintiff argues,

Commerce is double-counting irregular sales prices.

       Plaintiff then maintains that the problem is exacerbated because of Commerce’s “refusal

to consider any of the many circumstances of sale that cause net prices to vary” such as

movement costs, credit costs, or warranty costs. Pls.’ Br. 45. As a result, plaintiff argues, even if

a respondent sells products having the same CONNUM to all customers at the same gross price,

adjustments to the U.S. selling price could nonetheless cause a sale to “pass” the Cohen’s d test.

Pls.’ Br. 45-46. For Stanley, it is unreasonable for Commerce to conduct the Cohen’s d test at a

net price level because “the antidumping statute overtly recognizes the potential for different

circumstances of sale to distort the calculation of dumping margins,” and therefore, “expressly

directs Commerce to correct for such distortions by adjusting normal values.” Pls.’ Br. 46 (citing
Court No. 17-00071                                                                        Page 47

19 U.S.C. § 1677b(a)(6)(C)36). Stanley thus claims that “[i]t is unreasonable for Commerce to

account for differences in circumstances of sale when calculating dumping margins[37] but not

when determining whether such dumping was targeted.” Pls.’ Br. 46.

       The court finds that Commerce’s method is reasonable. As to plaintiff’s double-counting

theory, the court agrees with this Court’s analysis in Timken:

       The purpose of Commerce’s [differential pricing] analysis is to find a pattern of
       prices that differ significantly . . . . Under Commerce’s methodology, even if
       some sales are included in a test group and later in a comparison group, their
       value is counted only once in the numerator of the ratio [test] if they pass Cohen’s
       d.

Timken, 179 F. Supp. 3d at 1178-79. Put simply, in determining whether the total value of sales

that “pass” the Cohen’s d test is such that Commerce might consider the application of the A-T

method (i.e., whether the value of passing sales is greater than 33 percent of a respondent’s total

sales value), Commerce counts the value of any particular passing sale only once in the

numerator.

       Moreover, to remove passing sales from subsequent comparison groups because they are,

as Stanley suggests, “anomalous” would lead to inconsistent results. As Commerce stated:

       36
               Title 19 U.S.C. § 1677b(a)(6)(C) provides, in pertinent part, that the normal value
shall be

       increased or decreased by the amount of any difference (or lack thereof) between
       the export price or constructed export price and the price described in paragraph
       (1)(B) (other than a difference for which allowance is otherwise provided under
       this section) that is established to the satisfaction of [Commerce] to be wholly or
       partly due to . . . other differences in the circumstances of sale.

19 U.S.C. § 1677b(a)(6)(C)(iii).
       37
              As noted above, to calculate a dumping margin, Commerce determines the
difference between the export price (or constructed export price) and the normal value of the
product.
Court No. 17-00071                                                                              Page 48

        If the weighted-average price to purchaser A differs significantly from the
        weighted-average price to purchaser B, then the weighted-average price to
        purchaser B also differs significantly from the weighted-average price to
        purchaser A. Stanley’s suggestion, that once the Department finds that the
        weighted-average price to purchaser A differs significantly from the weighted-
        average price to purchaser B, then the sales prices to purchaser A should be
        excluded henceforth from the analysis, is illogical. This would result in no
        comparison being made for the weighted-average price to purchaser B. Further, if
        purchaser B’s sales were tested first, then purchaser A’s sales would not be tested.
        Such an approach would lead to arbitrary and unpredictable results that would
        depend upon the order in which purchasers, regions or time periods were
        examined.

Final I&D Memo at 18-19. Similarly, if sales from purchaser A to purchaser B were found not to

have passed the Cohen’s d test, then so too will the sales from purchaser B to purchaser A, and

the value of both will be included in the denominator of the ratio test. See Timken, 179 F. Supp.

3d at 1178-79. Stanley’s argument does not make Commerce’s rationale unreasonable.

        In addition, the court finds that the use of net prices in the differential pricing analysis is a

reasonable interpretation of the statute. As the Department states, its “analysis is to determine

whether the [A-A] method is appropriate to measure the amount of dumping for a respondent”

and that to “calculate a weighted-average dumping margin . . ., the Department uses net U.S.

prices . . . .” Final I&D Memo at 13. Therefore, Commerce considered the use of net prices

“consistent with the view that discounts, rebates and similar price adjustments are not expenses,

but instead form part of the price itself.” Final I&D Memo 13. This interpretation is reasonable

as it appears to implement the intent of the statute (i.e., to determine whether the A-A method is

the appropriate tool with which to measure a respondent’s dumping). Also, as Commerce

emphasized, “the use of net U.S. prices would increase the variability of the sale prices within a

group and thus require a larger difference in the weighted-average sale prices between the two

groups . . . .” Final I&D Memo at 14. Therefore, the court finds that Commerce’s use of net

prices in its differential pricing analysis is a reasonable interpretation of the statute.

Court No. 17-00071                                                                           Page 49

       At bottom, plaintiff once again appears to conflate passing the Cohen’s d test with the

application of the A-T method, and ultimately, a finding that there is targeted dumping. As

discussed above, (1) finding a pattern of prices that differ significantly among purchasers,

regions, or periods of time, and (2) explaining why the A-A method cannot account for such

differences are two separate analyses. The results of the former does not necessarily determine

the result of the latter. Accordingly, the court finds that Commerce’s differential pricing analysis

is a reasonable interpretation of 19 U.S.C. § 1677f–1(d)(1)(B).

III.   The World Trade Organization Appellate Body Decision

       Finally, Stanley argues that the World Trade Organization (“WTO”) Appellate Body

decision in United States—Anti-Dumping and Countervailing Measures on Large Residential

Washers from Korea38 demonstrates that Commerce has interpreted and applied 19 U.S.C.

§ 1677f–1(d)(1)(B) in an unreasonable manner that is inconsistent with the United States’

international obligations. Pls.’ Br. 47. Specifically, plaintiff argues that Commerce’s differential

pricing analysis violates the Agreement on Implementation of Article VI of the General

Agreement on Tariffs and Trade 1994 because (1) “Commerce did not limit its ‘pattern’ analysis

[to] sales that ‘pass’ the [Cohen’s d test] because they are lower than the comparison group

mean”; and (2) “Commerce employed a rote application of a series of mathematical formulae in

the guise of ‘tests’. . . while ignoring the nature of any factors causing price differences . . . and

             38
                           Appellate Body Report, United States—Anti-Dumping and Countervailing
Measures on Large Residential Washers from Korea, WTO Doc. WT/DS464/AB/R (adopted
Sept. 7, 2016).

Court No. 17-00071                                                                                  Page 50

thus considered only quantitative criteria.”39 Pls.’ Reply Br. 18 (citing the Appellate Body

Report, United States—Anti-Dumping and Countervailing Measures on Large Residential

Washers from Korea, ¶¶ 101, 102, WTO Doc. WT/DS464/AB/R (adopted Sept. 7, 2016)). In

other words, Stanley uses Washers from Korea to illustrate its view that Commerce’s

interpretation of what constitutes “a pattern of export prices . . . for comparable merchandise that

differ significantly among purchasers, regions, or periods of time” pursuant to 19 U.S.C.

§ 1677f–1(d)(1)(B) is unreasonable because it violates the WTO agreement. See Pls.’ Br. 47

(emphasis added).

        This argument is unconvincing. WTO decisions are irrelevant to the interpretation of

domestic U.S. law. See 19 U.S.C. § 3512(a)(1) (“Nothing in [the Uruguay Round Agreements

Act] shall be construed . . . to amend or modify any law of the United States.”); see also Corus

Staal BV v. Dep’t of Commerce, 395 F.3d 1343, 1348 (Fed. Cir. 2005) (“WTO decisions are ‘not

binding on the United States, much less this court.’” (quoting Timken Co. v. United States, 354

F.3d 1334, 1344 (Fed. Cir. 2004))); see also Corus Staal BV, 354 F.3d at 1346 (“Commerce is

not obligated to incorporate WTO procedures into its interpretation of U.S. law.”). Further, “[t]he

SAA provides that ‘[r]eports issued by . . . the Appellate Body under the [WTO Dispute

             39
                           The court notes that, in its opening brief, plaintiff argued that (1) “Commerce did
not limit its ‘pattern’ analysis to sales that ‘pass’ the [Cohen’s d test] because they are lower than
the comparison group mean”; (2) “Commerce applied the A-T comparison methodology to all of
Stanley’s sales”; (3) “Commerce employed a rote application of a series of mathematical
formulae in the guise of ‘tests’”; and (4) “Commerce used A-T with zeroing both in the
meaningful difference test and in the calculation of Stanley’s dumping margin” in contravention
of the Washers from Korea Appellate Body decision. Pls.’ Br. 47-48. In its reply brief, however,
plaintiff claims that only “[t]wo of [the Appellate Body’s] reasons [why differential pricing
violates the Agreement] support a conclusion that the Final Results are unreasonable and should
be remanded.” Pls.’ Reply Br. 18. Accordingly, the court will address only the two arguments
that remain in plaintiff’s subsequent reply brief.

Court No. 17-00071                                                                       Page 51

Settlement Understanding] have no binding effect under the law of the United States . . . [and] do

not provide legal authority for federal agencies to change their regulations or procedures.’”

Corus Staal BV v. U.S. Dep’t of Commerce, 27 CIT 388, 399, 259 F. Supp. 2d 1253, 1264 (2003)

(citing SAA at 1032, 1994 U.S.C.C.A.N. at 4318).

       Issues brought before WTO panels and the Appellate Body deal with whether a country is

complying with the terms of the WTO Agreement. See Corus Staal BV v. United States, 29 CIT

777, 786, 387 F. Supp. 2d 1291, 1300 (2005). Cases brought before the Court of International

Trade present questions dealing with domestic U.S. law. Id. (“In sum, the WTO decision-making

process operates apart from the decision-making in this court. WTO decision-making starts with

an international agreement, which may not match the domestic statute and which is interpreted

pursuant to different principles.”). Commerce’s interpretation of a statute might well be a

perfectly reasonable interpretation of U.S. law and nonetheless be found to violate the WTO

Agreement, as, for instance, was the case with zeroing. See, e.g., id. Thus, plaintiff’s argument

that the Appellate Body’s decision in Washers from Korea somehow shows that Commerce’s

interpretation and implementation of the targeted dumping statute is unreasonable under U.S. law

is far wide of the mark.
Court No. 17-00071                                                                      Page 52

                                       CONCLUSION
         For the foregoing reasons, the court finds that Commerce’s method is a reasonable one

for determining if targeted dumping may be occurring and therefore denies plaintiff’s motion for

judgment on the agency record. Commerce’s Final Results are sustained. Judgment shall be

entered accordingly.

                                                                 /s/ Richard K. Eaton
                                                                Richard K. Eaton, Judge

Dated:          "VHVTU

                New York, New York