Marmen Inc., Marmen Energie Inc., Marmen Energy Co. v. United States, Wind Tower Trade Coalition

United States Court of Appeals
for the Federal Circuit
______________________
MARMEN INC., MARMEN ENERGIE INC.,
MARMEN ENERGY CO.,
Plaintiffs-Appellants
v.
UNITED STATES, WIND TOWER TRADE
COALITION,
Defendants-Appellees
______________________
2023-1877
______________________
Appeal from the United States Court of International
Trade in No. 1:20-cv-00169-JCG, Judge Jennifer Choe-
Groves.
______________________
Decided: April 22, 2025
______________________
J AY CHARLES C AMPBELL, White & Case LLP, Washing-
ton, DC, argued for plaintiffs-appellants. Also represented
by R ON KENDLER , A LLISON KEPKAY.
R OBERT R. KIEPURA , Commercial Litigation Branch,
Civil Division, United States Department of Justice, Wash-
ington, DC, argued for defendant-appellee United States.
Also represented by R EGINALD T HOMAS B LADES, JR ., B RIAN
M. B OYNTON, P ATRICIA M. MCCARTHY; J ESUS N IEVES
SAENZ , Office of the Chief Counsel for Trade Enforcement
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MARMEN INC. v. US 2
and Compliance, United States Department of Commerce,
Washington, DC.
MAUREEN E. THORSON, Wiley Rein, LLP, Washington,
DC, argued for defendant-appellee Wind Tower Trade Co-
alition. Also represented by T HEODORE PAUL B RACKEMYRE ,
T ESSA V. CAPELOTO, R OBERT E. DEF RANCESCO, III, LAURA
E L-SABAAWI, DERICK HOLT, ELIZABETH S. LEE , A LAN H.
P RICE , J OHN A LLEN R IGGINS .
______________________
Before P ROST, TARANTO, and CHEN, Circuit Judges.
P ROST, Circuit Judge.
Marmen Inc., Marmen Énergie Inc., and Marmen En-
ergy Co. (collectively, “Marmen”) appeal the U.S. Court of
International Trade’s (“CIT”) decision sustaining the U.S.
Department of Commerce’s (“Commerce”) final determina-
tion that calculated a 4.94% dumping margin for utility-
scale wind towers from Canada. See Marmen Inc. v. United
States, 545 F. Supp. 3d 1305 (Ct. Int’l Trade 2021) (“Mar-
men I”); Marmen Inc. v. United States, 627 F. Supp. 3d 1312
(Ct. Int’l Trade 2023) (“Marmen II”). We vacate and re-
mand for further proceedings consistent with this opinion.
B ACKGROUND
Wind towers “are a component of utility scale wind tur-
bine electrical power generating units used to convert the
energy from wind to electrical energy.” J.A. 49. “Wind tow-
ers are tubular steel structures upon which the other major
wind turbine components i.e., rotor blades and nacelles are
mounted.” J.A. 49. “Wind towers have three types of sec-
tions: the base section, one or more mid-sections, and the
top section.” Marmen’s Br. 5 (citing J.A. 74). “[S]teel plate
is the primary input for wind towers,” and “the quantity
and thickness of steel plate consumed in a particular tower
can vary significantly depending on the specification.”
J.A. 78.
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MARMEN INC. v. US 3
In July 2019, Commerce initiated an antidumping
(“AD”) investigation of wind towers from Canada in re-
sponse to an AD petition filed by the Wind Tower Trade
Coalition (“WTTC”). Marmen Inc. and Marmen Énergie
Inc. were selected as mandatory respondents. In February
2020, Commerce issued a preliminary AD determination,
assigning Marmen a 5.04% dumping margin, and in June
2020, Commerce issued its final AD determination, assign-
ing Marmen a 4.94% dumping margin.
Marmen appealed to the CIT, making three arguments
that are relevant here: Commerce erred by (1) determining
that Marmen’s steel plate costs did not reasonably reflect
the costs associated with the production and sale of the
products, and thus it was error for Commerce to weight-
average (or smooth) the reported steel plate costs; (2) re-
jecting a supplemental cost-reconciliation item that was in-
tended to correct certain purchase information that had not
been properly converted from U.S. dollars (“USD”) to Ca-
nadian dollars (“CAD”); and (3) using the average-to-trans-
action (“A-to-T”) methodology, instead of the ordinary
average-to-average (“A-to-A”) methodology, to calculate
Marmen’s dumping margin based on a misapplication of
Cohen’s d test.
The CIT affirmed the weight-averaging of Marmen’s
steel plate costs, Marmen I, 545 F. Supp. 3d at 1315, but
remanded the case to Commerce on the other two issues.
For the USD-to-CAD cost reconciliation, Commerce ini-
tially rejected the submission because it “constituted un-
timely and unsolicited new information.” Id. The CIT
explained that “Commerce has a duty ‘to determine dump-
ing margins as accurately as possible,’” id. at 1316 (quoting
NTN Bearing Corp. v. United States, 74 F.3d 1204, 1208
(Fed. Cir. 1995)), and concluded that it was an abuse of dis-
cretion to deny the currency-conversion correction solely on
the basis that it was untimely, id. at 1316–17.
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MARMEN INC. v. US 4
As to the appropriate A-to-A or A-to-T methodology,
Commerce first decides whether “a pattern of export prices
(or constructed export prices) for comparable merchandise
. . . differ significantly among purchasers, regions, or peri-
ods of time.” Id. at 1318 (quoting 19 U.S.C.
§ 1677f-1(d)(1)(B)(i)). If such a pattern exists, then Com-
merce “explains why such differences cannot be taken into
account using [the A-to-A method].” § 1677f-1(d)(1)(B)(ii).
If the A-to-A methodology cannot account for these differ-
ences, then Commerce may apply the A-to-T methodology
instead to calculate a dumping margin. In Marmen I, Mar-
men argued that there was no significant difference among
purchasers, regions, or periods of time, and thus Commerce
should have used the A-to-A method to calculate the dump-
ing margin. According to Marmen, Commerce erroneously
found a significant price difference based on a misapplica-
tion of Cohen’s d test—a statistical test which can be used
in certain circumstances to determine differences between
the mean averages of two data sets. This, according to
Marmen, led Commerce to incorrectly use the A-to-T meth-
odology for calculating the dumping margin. Marmen I,
545 F. Supp. 3d at 1319. While Marmen I was pending be-
fore the CIT, our court issued Stupp Corp. v. United States,
which called into question the appropriateness of Com-
merce’s use of Cohen’s d test. 5 F.4th 1341, 1357 (Fed. Cir.
2021) (“[T]here are significant concerns relating to Com-
merce’s application of the Cohen’s d test . . . in adjudica-
tions in which the data groups being compared are small,
are not normally distributed, and have disparate vari-
ances.”). Based on Stupp, the CIT remanded “the issue of
Commerce’s use of the Cohen’s d test for Commerce to ex-
plain further whether the limits on the use of the Cohen’s
d test were satisfied.” Marmen I, 545 F. Supp. 3d at 1320.
On remand from Marmen I, Commerce again rejected
the USD-to-CAD cost reconciliation because it allegedly
would double count an exchange-rate adjustment already
reflected in the cost of goods sold and reported cost of
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MARMEN INC. v. US 5
production. See Marmen II, 627 F. Supp. 3d at 1316–20.
As to Commerce’s application of Cohen’s d test, and despite
concerns with its use expressed by our court in Stupp, Com-
merce determined that “‘the assumptions of normality and
roughly equivalent variances’ are not relevant to Com-
merce’s application of the Cohen’s d test” because Com-
merce’s use of the test is based on an entire population of
data and not a sample. See id. at 1320–22. The CIT, in
Marmen II, agreed with Commerce on both issues and sus-
tained Commerce’s determination of a 4.94% dumping
margin.
Marmen timely appeals. We have jurisdiction under
28 U.S.C. § 1295(a)(5).
DISCUSSION
“While we recognize the [CIT] has unique and special-
ized expertise in trade law, its decision is reviewed de novo,
applying anew the same standard used by that court in its
consideration of Commerce’s determination.” Union Steel
v. United States, 713 F.3d 1101, 1106 (Fed. Cir. 2013). “Ac-
cordingly, Commerce’s antidumping determination will be
upheld unless it is ‘unsupported by substantial evidence on
the record, or otherwise not in accordance with law.’” Id.
(quoting 19 U.S.C. § 1516a(b)(1)(B)(i)). Substantial evi-
dence is “such relevant evidence as a reasonable mind
might accept as adequate to support a conclusion.” Consol.
Edison Co. v. NLRB, 305 U.S. 197, 229 (1938). “[T]he rel-
evant standard for reviewing Commerce’s selection of sta-
tistical tests and numerical cutoffs is reasonableness, not
substantial evidence.” Stupp, 5 F.4th at 1353.
Marmen presents three main arguments on appeal:
that (1) Commerce’s determination to weight-average (or
smooth) Marmen’s steel plate costs was not supported by
substantial evidence or otherwise in accordance with the
law; (2) Commerce erred by rejecting Marmen’s USD-to-
CAD cost reconciliation; and (3) Commerce’s use of the A-
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MARMEN INC. v. US 6
to-T methodology based on Cohen’s d test was unreasona-
ble. We address each argument in turn.
I
Before calculating a dumping margin, Commerce must
“determin[e] . . . whether subject merchandise is being, or
is likely to be, sold at less than fair value.” 19 U.S.C.
§ 1677b(a). To do so, a comparison is made “between the
export price or constructed export price and normal value,”
id., where the export price or constructed export price is
the price at which subject merchandise is sold in the U.S.
market and normal value is the price of a “foreign like prod-
uct” sold in the producer’s home market or in a comparable
third-country market. “If the price of an item in the home
market (normal value) is higher than the price for the same
item in the United States (export price), then the compari-
son produces a positive number, indicating that dumping
has occurred.” Thai Plastic Bags Indus. Co. v. United
States, 746 F.3d 1358, 1360 (Fed. Cir. 2014) (citing 19
U.S.C. § 1677(35)(A)). If a “foreign like product” is not
identical to the merchandise sold in the U.S. market, then
a “model match” methodology is used to sort merchandise
into groups to be compared based on a hierarchy of similar
characteristics. See § 1677(16). Each group is assigned a
control number (“CONNUM”).
Here, Commerce compared the price of Marmen’s wind
towers sold in the U.S. with those sold in its home market
of Canada. There were no identical products, so the mer-
chandise was sorted into groups based on similar charac-
teristics. “In making product comparisons, [Commerce]
matched foreign like products based on the physical char-
acteristics reported by [Marmen] in the following order of
importance: type (tower or section), weight of tower/sec-
tion, height of tower/section, total sections, type of paint or
coating, metalizing, electrical conduit – bus bars, electrical
conduit – power cable, elevators, number of platforms, and
other internal components.” J.A. 2466; see also Marmen I,
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MARMEN INC. v. US 7
545 F. Supp. 3d at 1313. “Commerce determined that the
most significant physical characteristics in differentiating
costs of steel plate were type, thickness, weight, width, and
height.” Marmen I, 545 F. Supp. 3d at 1314.
Once sorted into CONNUMs, the export price and the
normal value may be compared. Under § 1677b, a compar-
ison of the subject merchandise is based in part on the ex-
porter’s cost of production. “Costs shall normally be
calculated based on the records of the exporter or producer
of the merchandise, if such records are kept in accordance
with the generally accepted accounting principles of the ex-
porting country (or the producing country, where appropri-
ate) and reasonably reflect the costs associated with the
production and sale of the merchandise.” § 1677b(f)(1)(A)
(emphasis added). But when the reported costs do not re-
flect the production costs, then “it is Commerce’s normal
practice to adjust costs to address distortions when such
cost differences are attributable to factors beyond differ-
ences in the physical characteristics of such products.”
J.A. 3858; Thai Plastic Bags, 746 F.3d at 1368 (“It is cus-
tomary for Commerce to adjust a company’s reported allo-
cation methodology to reflect costs based solely on physical
characteristics.” (cleaned up)). In such circumstances,
Commerce has “averaged” or “smoothed” certain
CONNUM-specific costs across multiple CONNUMs.
That is what happened here—Commerce determined
that the reported steel costs did not reasonably reflect the
cost of production because “Marmen’s suppliers did not
charge different prices for plates of different grade, thick-
ness, width, or length,” and therefore, “there should be lit-
tle difference in plate costs for different dimensions and
grade based on record evidence on a per-unit weight basis.”
Marmen I, 545 F. Supp. 3d at 1314. But Commerce did find
differences unrelated to physical characteristics, such as
the timing of production. Id. As a result, Commerce
“weight-averaged the reported steel plate costs for all re-
ported CONNUMs, except the CONNUM for the thickest
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MARMEN INC. v. US 8
plate.” Id.1 Marmen argues that this weight-averaging (or
cost-smoothing) was improper. We disagree.
A
Marmen first argues that Commerce arbitrarily disre-
garded its standard test for when weight-averaging may be
used—“Commerce’s consistent test for determining
whether to average a respondent’s reported product-spe-
cific costs across multiple CONNUMs was to examine:
(1) whether the respondent reported significantly different
costs for ‘nearly identical’ or ‘similar’ CONNUMs and, if so,
(2) whether such differences in cost were unrelated to the
products’ physical characteristics.” Marmen’s Br. 8; see
also id. at 34–35. Commerce responds that its “cost-
smoothing practice is not limited solely to instances in
which the products are ‘identical’ or ‘very similar.’” U.S.
Br. 19. Instead, according to Commerce, “the key factor is
whether a respondent’s reported cost differences properly
reflect production differences associated with physical
characteristics, as distinguished from other unrelated fac-
tors.” Id. The difference between these two positions, as
relevant here, is whether Commerce may apply cost-
smoothing practices only when the finished product (i.e.,
the subject merchandise) is nearly identical or similar, or
whether Commerce may apply cost-smoothing practices
when the input (e.g., raw materials) to the subject mer-
chandise is nearly identical or similar. See Marmen’s
Br. 34–35; U.S. Br. 19.
Commerce did not arbitrarily disregard its standard
practice. Commerce’s statutory requirement is to
1 “Commerce excluded the CONNUM for the thick-
est plates because the record indicated that there was a
surcharge applied to high thickness plates that was not ap-
plied to lower thickness plates.” Marmen I, 545 F. Supp.
3d at 1314.
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MARMEN INC. v. US 9
determine if the cost reporting “reasonably reflect[s] the
costs associated with the production and sale of the mer-
chandise.” § 1677b(f)(1)(A). Commerce has historically
made that determination based on finished products in
some cases and individual inputs in other cases. Indeed, in
another antidumping case involving wind towers (de-
scribed by Marmen as a companion case, Marmen’s Reply
Br. 4 n.1), Commerce found that the per-unit weight cost of
the steel plate input was “virtually the same regardless of
the grade, thickness, width, or height.” See Dongkuk S&C
Co. v. United States, No. 23-1419, slip op. at 12 (Fed. Cir.
Apr. 21, 2025) (citation omitted). “Accordingly, Commerce
concluded that ‘the overwhelming factor that caused the
differences in the steel plate costs [for the final CON-
NUMs] was the timing of the steel plate purchases.’” Id.
(alteration in original) (citations omitted). Based on these
facts and findings (which are nearly identical to those be-
fore us), Commerce smoothed the respondent’s steel plate
input costs. Id. at 7. We affirmed, concluding that “Com-
merce’s analysis did not have to focus on comparing the
costs of finished wind towers sharing the same physical
characteristics,” id. at 14, and “Commerce was not required
to rely upon . . . distortive records and had the authority to
adjust steel plate input costs to more accurately approxi-
mate [respondent’s] costs of production during the period
of investigation,” id. at 11.
The same is true here. “It was reasonable for Com-
merce to analyze whether or not [respondent’s] costs were
attributable to some relationship between raw material in-
puts and CONNUM physical characteristics.” Id. at 13.
Therefore, as we did in Dongkuk, we conclude that Com-
merce did not act arbitrarily or inconsistently with its
standard practice.
B
Marmen also argues that Commerce’s factual findings
are not supported by substantial evidence. Specifically,
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MARMEN INC. v. US 10
Marmen argues that “Commerce wrongly concluded that
[Marmen’s] steel suppliers do not charge different prices
for plates of different grade, thickness, width, or length, ex-
cept for high thickness range plates (i.e., greater than
50.8mm),” and “Commerce assumed, contrary to the record
evidence and its own findings, that differences in timing
explained observed differences in Marmen’s reported
CONNUM-specific plate costs.” Marmen’s Br. 36 (cleaned
up). We agree with the CIT that Commerce’s factual find-
ings are supported by substantial evidence.
As to Commerce’s determination that Marmen’s sup-
pliers do not charge different prices for plates of different
grade, thickness, width, or length, except for high thick-
ness range plates, it was Marmen who first argued that
“[t]hickness, in particular, affects steel plate cost.”
J.A. 3709. Marmen also stated that multiple suppliers re-
quired upcharges for plates of the greatest thickness.
J.A. 3709–10. Commerce, therefore, “excluded the
CONNUM for the thickest plates because the record indi-
cated that there was a surcharge applied to high thickness
plates that was not applied to lower thickness plates.”
Marmen I, 545 F. Supp. 3d at 1314. Marmen did not iden-
tify surcharges for the smaller thicknesses nor did Marmen
identify surcharges or provide evidence of cost differences
based on other physical characteristics. J.A. 3709–10. For
example, despite stating that steel grade could cause dif-
ferences in costs, Marmen confirmed that the grades from
its suppliers were “roughly equivalent.” J.A. 3710. Based
on Marmen’s own evidence, Commerce explained that
“[u]nder Marmen’s theory, one would expect the thicker
plates . . . to cost more per ton, and those that are thinner
to cost less per ton.” U.S. Br. 26. But this was not the case.
See Marmen’s Br. 37; U.S. Br. 26. Indeed, when Commerce
compared the plate costs on a per-unit weight basis, it
found a significant variance in the per-unit plate costs.
Having found that thickness, grade, and weight did not
solely drive the cost, Commerce looked to other factors.
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MARMEN INC. v. US 11
And in further analyzing the data, “Commerce found a pat-
tern indicating that most of the CONNUMs with higher
plate costs were sold early in the investigation period,
whereas those with lower plate costs were sold later.” U.S.
Br. 28 (citing J.A. 3874, 3879–80). On this record, we agree
with the CIT that Commerce’s findings are supported by
substantial evidence.
II
Next, Marmen argues that substantial evidence does
not support Commerce’s decision to reject a minor correc-
tion to the cost-reconciliation worksheet to account for an
exchange rate. On this question, we agree with Marmen.
The period of interest for the investigation was July 1,
2018, to June 30, 2019. During 2018, Marmen did not ac-
count for the exchange rate of USD-to-CAD for its “USD-
denominated purchases.” Marmen’s Br. 12. During 2019,
however, Marmen did convert its USD purchases to CAD
in its financial records. Apparently relying on these finan-
cial records, when Marmen initially reported its costs of
production in response to Section D of the AD Question-
naire, it inadvertently omitted the conversion from USD-
to-CAD in the cost-reconciliation worksheet for Item L (“Af-
filiated purchase of wind sections from Marmen Énergie”)
for the first half of the period of interest, i.e., July to De-
cember 2018. To correct this error, Marmen added a new
line, Item L1, to adjust for the exchange rate from USD-to-
CAD and submitted a Second Supplemental D Question-
naire on February 7, 2020. J.A. 3641. On February 25,
2020, Commerce rejected the correction as “untimely filed
new factual information.” J.A. 3706–07; see also J.A. 3861.
In Marmen I, the CIT held that “Commerce abused its
discretion by failing to consider Marmen’s corrective sub-
mission.” 545 F. Supp. 3d at 1317. On remand, however,
Commerce again rejected the exchange-rate correction—
this time alleging that the correction “would duplicate an
adjustment amount that was already reflected in its
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MARMEN INC. v. US 12
revised audited financial statements.” J.A. 4827. Marmen
again appealed, and this time, the CIT accepted Com-
merce’s rejection of the exchange-rate conversion as sup-
ported by substantial evidence. On appeal here, Commerce
makes two main arguments for why it rejected the ex-
change rate: (1) the exchange-rate conversion would be du-
plicative of other adjustments, U.S. Br. 40–41, and
(2) Marmen’s specific exchange rate is unreliable, id. at 46.
Neither argument has merit.
A
Commerce’s double-counting argument is unpersua-
sive. In a generous read of Commerce’s argument, its dou-
ble-counting argument appears to be based on
representations from Marmen’s auditors that the cost rec-
onciliation was complete and allegations that line items P,
Q, and R from Marmen’s cost-reconciliation worksheet al-
ready accounted for the exchange-rate conversion. But the
statements from Marmen’s auditors were primarily made
prior to the discovery of the omitted exchange-rate conver-
sion. See U.S. Br. 40 (citing J.A. 1006–07; J.A. 4855–58 (al-
most entirely relying on evidence from before Marmen
submitted the supplemental questionnaire)).
Equally unpersuasive is Commerce’s argument that
“the cost reconciliation Item L, which is the figure that
Marmen claims requires adjustment to account for U.S.
dollar purchases from its French-Canadian affiliate, did
not change based on the auditor’s adjustment to Marmen’s
financial statement, indicating that the auditor did not be-
lieve any correction to that figure was necessary.” U.S.
Br. 41 (citing J.A. 3905). We disagree. In Marmen’s Feb-
ruary 7, 2020, submission, Marmen added Item L1, labeled
“Exchange Rate Variance on July to Dec 2018 Affiliated
Purchases of Wind Sections from Energie,” to adjust for the
USD-to-CAD exchange rate. J.A. 3641 (“Version Two”).
On February 25, Commerce rejected this submission as un-
timely and directed Marmen to “remove the entire” Item
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MARMEN INC. v. US 13
L1. J.A. 3707. On February 28, 2020, Marmen complied
and removed the line item. J.A. 3753 (“Version Three”).
After Marmen I, Marmen submitted “Version Four” of the
cost-reconciliation worksheet, again including Item L1 to
adjust for the exchange rate. See J.A. 3904. In none of
these versions did Marmen change Item L. Instead, it
made the adjustment by adding the new Item L1. So the
fact that Item L did not change does not indicate that Mar-
men did not make adjustments in the cost-reconciliation
worksheet for Item L; Marmen just made the adjustment
in a separate line item and labeled it accordingly. See
J.A. 3904.
Commerce’s next argument is also unconvincing.
Turning to line items P, Q, and R, Commerce admits that
each of these line items are for exchange-rate conversions
covering the first half of 2018. See J.A. 3905. We fail to
see how adjustments for the first half of 2018 have any rel-
evance to the proposed adjustments for the second half of
2018. Nor is there any explanation of how these exchange
rates could be duplicative if they do not cover the same pe-
riods in time.
B
As to the alleged lack of reliability, Commerce first ar-
gues that it is unclear what transactions actually occurred
in USD and which occurred in CAD. Commerce explains
that when it reviewed the underlying invoices for the sales
of the entire period of interest “almost every invoice listed
in the document . . . is designated as a USD-denominated
sale.” U.S. Br. 42 (citing J.A. 4858–59, J.A. 3907–13). But
it then points to Marmen’s statements that the January to
June 2019 purchases from Marmen Énergie were in CAD
but not designated as such in the document listing the in-
voices. Id. Commerce’s argument appears to be that it can-
not tell which sales are in USD and which are in CAD with
any reliability. But this is an unnecessarily complicated
view of the record. The records that Marmen relied on were
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MARMEN INC. v. US 14
intended to show that the 2018 sales were recorded in USD
and should be converted to CAD. That is what these rec-
ords show. See J.A. 3907–09. Any other interpretation of
the data amounts to a question of the veracity of Marmen’s
representations—not its reliability. Commerce has not
made an allegation that Marmen misrepresented its finan-
cial records nor are we aware of any records to support such
a claim.
WTTC (the party who originally requested the AD in-
vestigation and also an appellee here) makes another at-
tempt at a reliability argument—i.e., that Marmen
provided no support for the average exchange rate for the
relevant period. WTTC Br. 40–44. For example, WTTC
argues that Marmen has confused which exchange-rate pe-
riod should actually apply by pointing to Marmen’s asser-
tion that the disputed exchange rate should apply for the
second half of 2018 but then also stating that the exchange
rate was “based on its exchange rate contracts in place dur-
ing the POI [period of investigation].” WTTC Br. 40 (em-
phasis in original) (quoting Marmen’s Br. 15). WTTC’s
reliance on this statement to confuse the period for the ex-
change rate is not consistent with the record as a whole.
Marmen has been clear that the exchange rate it seeks to
apply is for the second half of 2018, both in its record evi-
dence and briefs. See Marmen’s Br. 12–18; J.A. 3904;
J.A. 3907–09. Marmen’s statement that the requested ex-
change rate is based on exchange rate contracts in place
during the POI does not undermine this, particularly be-
cause the second half of 2018 was during the POI.
Commerce and WTTC present additional arguments
regarding the reliability of the proposed exchange rate, but
we find these arguments equally unpersuasive. Thus, we
conclude that Commerce’s determination that the ex-
change rate would double count records or is unreliable is
not supported by substantial evidence. On this record, sub-
stantial evidence does not support Commerce’s rejection of
the exchange rate.
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MARMEN INC. v. US 15
III
Finally, we turn to Commerce’s use of Cohen’s d test.
We begin with a discussion of how Cohen’s d test is used in
the process of calculating a dumping margin, and then turn
to why normal distributions, equal variability, and equally
and sufficiently numerous data are necessary to achieving
a meaningful Cohen’s d coefficient.
A
Our recent opinion in Stupp provides a thorough expla-
nation of Cohen’s d test and its relevance to calculating a
dumping margin. 5 F.4th at 1344–48, 1357–60. The same
statutory and regulatory background applies here. There-
fore, we do not repeat all of this background information
and instead only include a summary of Cohen’s d test for
the purposes of evaluating the arguments raised here. Ad-
ditionally, Stupp involved a similar question regarding the
appropriateness of using Cohen’s d test in the context of
calculating a dumping margin. The summary below in-
cludes the relevant conclusions from Stupp about Co-
hen’s d test that led us to Commerce’s arguments raised in
the present case.
“When calculating a weighted average dumping mar-
gin, Commerce typically uses the average-to-average com-
parison method. 19 C.F.R. § 351.414(c)(1); see also 19
U.S.C. § 1677f-1(d)(1).” Stupp, 5 F.4th at 1345. But when
“(i) there is a pattern of export prices (or constructed export
prices) for comparable merchandise that differ signifi-
cantly among purchasers, regions, or periods of time, and
(ii) [Commerce] explains why such differences cannot be
taken into account using [the A-to-A method],”
§ 1677f-1(d)(1)(B), Commerce may then use the A-to-T
method. Stupp, 5 F.4th at 1345; see also U.S. Br. 48–49.
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MARMEN INC. v. US 16
Cohen’s d test is used as the first step in the differential
pricing analysis to calculate the dumping margin.2 First,
Cohen’s d test is used “to measure whether the United
States prices to a particular purchaser, region, or time pe-
riod differ significantly from the prices for all other pur-
chasers, regions, and time periods.” U.S. Br. 49–50 (citing
Stupp, 5 F.4th at 1346). “If the Cohen’s d value is equal to
or greater than 0.8 for any test group, the observations
within that group are said to have ‘passed’ the Cohen’s d
test, i.e., Commerce deems the sales prices in the test group
to be significantly different from the sales prices in the
comparison group.” Stupp, 5 F.4th at 1347. “Commerce
applies Cohen’s d test to each test group within the re-
gional, purchaser, and time-period categories.” Id.
“Second, the ratio test calculates the proportion of re-
spondent’s United States sales, by value, that ‘pass’ the Co-
hen’s d test, to determine whether a ‘pattern’ exists.” U.S.
Br. 50 (citing Stupp, 5 F.4th at 1347). Together, steps one
and two determine, in accordance with the statute,
whether “a pattern of export prices (or constructed export
prices) for comparable merchandise that differ signifi-
cantly among purchasers, regions, or periods of time.”
§ 1677f-1(d)(1)(B)(i). Based on the outcome of these tests,
Commerce selects which dumping margin calculation to
use—either the A-to-A method or the A-to-T method (or
some hybrid of the two).3 See U.S. Br. 47–52.
2 “The differential pricing analysis involves three
tests to address the statutory requirements of section
1677f-1(d)(1)(B),” U.S. Br. 49: (1) Cohen’s d test, (2) the ra-
tio test, and (3) the meaningful difference test. See id.
at 49–51; Stupp, 5 F.4th at 1346–48.
3 The selection of the A-to-A method or A-to-T
method is also subject to the meaningful difference test,
but for the sake of simplicity, we do not discuss that test in
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MARMEN INC. v. US 17
In Stupp, the appellant argued that “Commerce mis-
used the Cohen’s d test in its differential pricing analysis.”
5 F.4th at 1357. We agreed with the appellant “that there
are significant concerns relating to Commerce’s application
of the Cohen’s d test in [that] case, and more generally, in
adjudications in which the data groups being compared are
small, are not normally distributed, and have disparate
variances.” Id. “Our first concern is a general one: Com-
merce’s application of the Cohen’s d test to data that do not
satisfy the assumptions on which the test is based may un-
dermine the usefulness of the interpretive cutoffs.” Id. We
explained that “[t]here is extensive literature describing
the problems associated with applying the Cohen’s d test
to data that are not normally distributed or that are lack-
ing equal variances.” Id. at 1358; see also id. at 1358–59
(reviewing literature that investigated Cohen’s d when the
assumptions are not met); id. at 1358 (applying Cohen’s d
to non-normally distributed data sets and concluding “that
applying Cohen’s d to such data caused serious flaws in in-
terpreting the resulting parameter” (emphasis added)); id.
(“conclud[ing] that Cohen’s d ‘was found to be inaccurate
when the normality and homogeneity-of-variances assump-
tions were violated in this study, thereby severely affecting
the accuracy of d in evaluating the true [effect size] in the
research literature” (emphasis added) (second alteration in
original)). Another “concern arises from test groups con-
taining sales prices that hover around the same value” be-
cause it “tend[s] to artificially inflate the dumping margins
for a set of export sales prices that has minimal variance.”
this opinion. See U.S. Br. 50; Stupp, 5 F.4th at 1347. Com-
merce did not use a meaningful difference test in a way
that was independent of the first two steps, both of which
depend on the use of Cohen’s d test. If the use of Cohen’s d
test at the first and second steps is unsupported here, then
we have no basis to find that error was harmless by use of
the meaningful difference test. See also infra at 20.
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MARMEN INC. v. US 18
Id. at 1359 (explaining mathematically how this artificial
inflation of Cohen’s d coefficient may occur).
We concluded, “[i]n sum, the evidence and arguments
before us call into question whether Commerce’s applica-
tion of the Cohen’s d test to the data in this case violated
the assumptions of normality, sufficient observation size,
and roughly equal variances associated with that test.” Id.
at 1360.4 But we did not reverse; rather we remanded the
case to Commerce giving it an opportunity to address the
following question:
We therefore remand to give Commerce an oppor-
tunity to explain whether the limits on the use of
the Cohen’s d test prescribed by Professor Cohen
and other authorities were satisfied in this case or
whether those limits need not be observed when
Commerce uses the Cohen’s d test in less-than-fair-
value adjudications. In that regard, we invite Com-
merce to clarify its argument that having the entire
universe of data rather than a sample makes it
4 Stupp addressed concerns with all three of Co-
hen’s d test’s required assumptions—normal distributions,
equal variability, and equally and sufficiently numerous
data—and concluded that the academic literature sur-
rounding Cohen’s d test did not support the use of Co-
hen’s d test when these assumptions are not met. 5 F.4th
at 1357–60. We do not repeat all of the reasons for the se-
rious concerns with the use of Cohen’s d when these as-
sumptions are not met but reaffirm those concerns are
equally applicable to the facts before us. The opinion here
instead focuses primarily on the question of whether using
a population instead of a sample can assuage these con-
cerns. (It does not.) We demonstrate this conclusion by
focusing on the assumption of normal distribution because
Commerce’s justification for using Cohen’s d test is largely
based on reasoning regarding that assumption.
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MARMEN INC. v. US 19
permissible to disregard the otherwise-applicable
limitations on the use of the Cohen’s d test.
Id.
B
This case begins where Stupp ended—Was it unreason-
able for Commerce to use Cohen’s d test as part of its dif-
ferential pricing analysis when the test is applied to data
sets that do not satisfy the statistical assumptions (normal
distribution, equal variability, and equally and sufficiently
numerous data)? It was.
Commerce makes two arguments to justify its use of
Cohen’s d test: (1) “[T]he assumptions discussed in Stupp
are unnecessary when Commerce uses a full population of
prices in each of the test and comparison groups in its Co-
hen’s d test, rather than sampling the sales prices,” U.S.
Br. 53 (emphasis added); and (2) “Commerce does not rely
on the Cohen’s d test to calculate the respondent’s
weighted-average dumping margin, but only to determine
whether prices differ significantly as one component of its
analysis to determine whether it is appropriate to use an
alternative comparison method instead of the A-to-A
method in calculating the dumping margin,” U.S. Br. 55.
This second argument apparently suggests that it does not
matter if the calculated Cohen’s d coefficient is accurate or
not because it is not actually used in the calculation of the
dumping margin. See id.; WTTC Br. 51–52.
We begin by rejecting Commerce’s second argument.
As explained above, Cohen’s d test is used as the first step
in the differential pricing analysis. While we recognize
that Cohen’s d coefficient is not a direct input into calculat-
ing the dumping margin, its value is a basis for determin-
ing which methodology to use to calculate the dumping
margin. If the output of Cohen’s d test is incorrect, then
the flawed output becomes a flawed input to the ratio test.
That flawed input to the ratio test leads to a flawed output,
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MARMEN INC. v. US 20
and that flawed output will be used to determine whether
a pattern of significant price differences exists. And if the
ratio test determines there is a pattern when there is not,
Commerce has then selected the wrong weight-averaged
methodology as required under § 1677f-1(d)(1)(A)(i). We
decline to conclude that a flawed output in step one of a
calculation can be transformed into meaningful data by
further manipulating it.
As to Commerce’s first argument regarding samples
versus populations, Commerce’s argument strains credu-
lity. First, Professor Cohen, who first established Cohen’s
d test, expressly discussed the effect size in terms of a pop-
ulation:
If we maintain the assumption that the populations
being compared are normal and with equal varia-
bility, and conceive them further as equally numer-
ous, it is possible to define measures of nonoverlap
(U) associated with d which are intuitively compel-
ling and meaningful.
JACOB COHEN, STATISTICAL POWER A NALYSIS FOR THE
B EHAVIORAL SCIENCES 21 (2d ed. 1988) (italics added; bold
in original) (“Statistical Power Analysis”).
LARGE EFFECT SIZE: d = .8. When our two pop-
ulations are so separated as to make d = .8, almost
half (U1 = 47.4%) of their areas are not overlapped.
U2 = 65.5%, i.e., the highest 65.5% of the B popula-
tion exceeds the lowest 65.5% of the A population.
As a third measure, the mean or upper half of the
B population exceeds the lower 78.8% (= U3) of the
A population.
Id. at 26 (italics added; bold in original).
Second, whether the data comes from a sample or a
population is irrelevant to producing an accurate Cohen’s d
coefficient. “Cohen’s d coefficient is a measure of ‘effect
size’ that gauges the extent of the difference between the
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MARMEN INC. v. US 21
means of two groups.” U.S. Br. 50; see also Stupp, 5 F.4th
at 1346–47; Canada Amicus Br. 11. “Effect size measures
the ‘effect’ that being in one group rather than the other
has on the observed value and expresses that measurement
in units of standard deviation.” Canada Amicus Br. 11.
For example, Cohen’s d coefficient could be used to meas-
ure the effect (i.e., the “effect size”) on test scores (i.e., ob-
served or measured value) from being placed in two
different classes. See id. For the effect size to have mean-
ing, it is necessary to “maintain the assumption that the
populations being compared are normal and with equal
variability, and conceive them further as equally numer-
ous.” Statistical Power Analysis, at 21. Then, “it is possible
to define measures of nonoverlap (U) associated with d
which are intuitively compelling and meaningful.” Id. (em-
phasis in original). Essentially, each d value corresponds
to a set of U values (U 1 , U 2 , and U 3 ), which describe how
much of the two compared groups overlap with each other.
For example, U1 describes the percentage of all observa-
tions in the two groups that do not overlap (the gray areas
in the image below).
Canada Amicus Br. 13.
Continuing with this example, when Cohen’s d = 0.8,
that means U 1 = 47.4% (i.e., almost half the areas of the
groups do not overlap). But the relationship between d val-
ues and U values is based on the assumption that the data
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MARMEN INC. v. US 22
sets being compared have normal distributions. Statistical
Power Analysis, at 23 (“[The U values] are simply related
to d and each other through the cumulative normal distri-
bution.” (emphasis in original)). This is so because normal
distributions are defined by their mean and standard devi-
ations. Definitionally, in a normal distribution, approxi-
mately 68% of data falls within one standard deviation and
approximately 95% of data falls within two standard devi-
ations. Thus, whether in a population or a sample, where
two groups of data are not normally distributed, the rela-
tionships between standard deviation, normal distribu-
tions, d values, and U values fall apart. See Canada
Amicus Br. 17–19 (demonstrating the flawed outcome in
calculating a d coefficient for groups of data that are not
normally distributed). In other words, when the data sets
do not satisfy the normal assumptions, the Cohen’s d value
no longer represents the effect size of the two groups being
compared, i.e., how significant is the difference between be-
ing in one group and being in the other, specifically regard-
ing the groups’ means.
Commerce offers two main arguments to suggest that
the academic literature favors its position. We are not per-
suaded. First, Commerce argues that because it relies on
the entire universe of data (and not a sample), “Commerce
uses the Cohen’s d test to measure the practical signifi-
cance of differences in real-world pricing, rather than the
statistical significance (which arises when one seeks to de-
termine the likelihood that a result observed based on es-
timation through sampling is a result of chance, or
represents the actual parameters of the full populations).”
U.S. Br. 54 (emphasis in original) (citing J.A. 4835–37).
But the portion of the appendix that Commerce relies on
for support is based on a totally different premise—i.e.,
that a different test, called the “t-test,” tests for statistical
significance, while Cohen’s d test, which measures an effect
size, measures for a practical significance. See
J.A. 4835–37. That there are two different tests for
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MARMEN INC. v. US 23
analyzing whether the means of two sets of data are differ-
ent says nothing about why the assumptions for Cohen’s d
test need not be satisfied when relying on a population in-
stead of a sample.
Next, Commerce argues that “unlike with a sample of
data for which the estimated parameters will change with
each sample selected from a population, each time these
parameters are calculated as part of Commerce’s Cohen’s d
test the exact same results will [be] obtain[ed] because the
calculated parameters are the actual values of the param-
eters of the entire population and not estimated values of
the parameters based on a sample.” U.S. Br. 54–55. This
argument misses the point. Even if you calculate the same
mean, standard deviation, and d value with population
data (whereas there might be minor variations based on
estimated values of sampled data), the d value while con-
sistent could still be unsound as a gauge of group differ-
ence. Repeatedly calculating an incorrect d value does not
transform it into a “compelling and meaningful” d value.
Statistical Power Analysis, at 21.
For the reasons above, and those explained in Stupp,
we conclude that it was unreasonable to rely on Cohen’s d
test to determine whether prices differ significantly when
the underlying data is not normally distributed, equally
variable, and equally and sufficiently numerous. Because
there is no dispute that Marmen’s data does not satisfy
these assumptions, Cohen’s d test cannot be used here to
determine “a pattern of export prices (or constructed export
prices) for comparable merchandise that differ signifi-
cantly among purchasers, regions, or periods of time.”
§ 1677f-1(d)(1)(B). We therefore vacate Commerce’s calcu-
lated dumping margin based on the unreasonable use of
Cohen’s d test to justify the A-to-T methodology. On re-
mand, Commerce may re-perform a differential pricing
analysis, and that analysis may not rely on Cohen’s d test
for data sets like those here. This conclusion, of course,
does not preclude Commerce from fashioning and
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MARMEN INC. v. US 24
justifying a statistical analysis that uses some of the ideas
underlying Cohen’s analysis of group differences as long as
the resulting analysis is itself justified as sound for gaug-
ing differences in the data sets at issue.
C ONCLUSION
We have considered the parties’ remaining arguments
and find them unpersuasive. For the reasons above, we
vacate and remand for Commerce to recalculate Marmen’s
dumping margin consistent with this opinion.
VACATED AND REMANDED
C OSTS
No costs.
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