The Stanley Works (Langfang) Fastening Sys. Co. v. United States , 333 F. Supp. 3d 1329 ( 2018 )

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).
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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).

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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 . . . )

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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.

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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.

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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
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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”).

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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