NBER WORKING PAPER SERIESMISALLOCATION AND PRODUCTIVITY EFFECTS OF THE SMOOT-HAWLEYTARIFF
Eric W. Bond
Mario J. Crucini
Tristan Potter
Joel Rodrigue
Working Paper 18034
http://www.nber.org/papers/w18034

NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
May 2012

Tristan Potter acknowledges financial support through the Vanderbilt Undergraduate Summer Research
Program, 2010. The views expressed herein are those of the authors and do not necessarily reflect
the views of the National Bureau of Economic Research.
NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official
NBER publications.
© 2012 by Eric W. Bond, Mario J. Crucini, Tristan Potter, and Joel Rodrigue. All rights reserved.
Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided
that full credit, including © notice, is given to the source.

Misallocation and Productivity Effects of the Smoot-Hawley Tariff
Eric W. Bond, Mario J. Crucini, Tristan Potter, and Joel Rodrigue
NBER Working Paper No. 18034
May 2012
JEL No. E6,F1,F13
ABSTRACT
Using a newly created microeconomic archive of U.S. imports at the tariff-line level for 1930-33, weconstruct industry-level tariff wedges incorporating the input-output structure of U.S. economy andthe heterogenous role of imports across sectors of the economy. We use these wedges to show thatthe average tariff rate of 46% in 1933 substantially understated the true impact of the Smoot-Hawley(SH) tariff structure, which we estimate to be equivalent to a uniform tariff rate of 70%. We use thesewedges to calculate the impact of the Smoot Hawley tariffs on total factor productivity and welfare.
In our benchmark parameterization, we find that tariff protection reduced TFP by 1.2% relative tofree trade prior to the Smoot Hawley legislation. TFP fell by an additional 0.5% between 1930 and
1933 due to Smoot Hawley. We also conduct counterfactual policy exercises and examine the sensitivityof our results to changes in the elasticity of substitution and the import share. A doubling of the substitution
elasticities yields a TFP decline of almost 5% relative to free trade, with an additional reduction due
to SH of 0.4%.

Eric W. Bond
Vanderbilt University
Department of Economics
VU Station B #351819
2301 Vanderbilt Place
Nashville, TN 37235-1819
eric.bond@vanderbilt.edu
Mario J. Crucini
Department of Economics
Vanderbilt University
Box 1819 Station B
Nashville, TN 37235-1819
and NBER
mario.j.crucini@vanderbilt.edu

Tristan Potter
Department of Economics
Boston College
potter.tristan@gmail.com
Joel Rodrigue
Vanderbilt University
joel.b.rodrigue@vanderbilt.edu

Misallocation and Productivity E¤ects of the Smoot-Hawley
Tari¤
Eric W. Bond, Mario J. Crucini, Tristan Potter and Joel Rodrigue
This Version: April 25, 2012

Abstract
Using a newly created microeconomic archive of U.S. imports at the tari¤-line level for
1930-33, we construct industry-level tari¤ wedges incorporating the input-output structureof U.S. economy and the heterogenous role of imports across sectors of the economy. We use
these wedges to show that the average tari¤ rate of 46% in 1933 substantially understated thetrue impact of the Smoot-Hawley (SH) tari¤ structure, which we estimate to be equivalent
to a uniform tari¤ rate of 70%. We use these wedges to calculate the impact of the SmootHawley tari¤s on total factor productivity and welfare. In our benchmark parameterization,
we …nd that tari¤ protection reduced TFP by 1:2% relative to free trade prior to the SmootHawley legislation. TFP fell by an additional 0:5% between 1930 and 1933 due to SmootHawley. We also conduct counterfactual policy exercises and examine the sensitivity of ourresults to changes in the elasticity of substitution and the import share. A doubling of thesubstitution elasticities yields a TFP decline of almost 5% relative to free trade, with anadditional reduction due to SH of 0:4%.
Keywords: Hawley-Smoot Tari¤, Great Depression, commercial policy, productivity,
misallocation, macroeconomic ine¢ ciency.
JEL Codes:

1

Introduction

The Smoot-Hawley (SH) tari¤ of 1930 is the most signi…cant piece of tari¤ legislation in U.S.
history. The legislation is often mentioned for rhetorical e¤ect in the context of tari¤ debates,
perhaps most pointedly by Al Gore as he presented Ross Perot with a framed picture of Senator
Eric Bond: Department of Economics, Vanderbilt University, email: eric.bond@vanderbilt.edu; Mario J.
Crucini: NBER and Department of Economics, Vanderbilt University, email: mario.j.crucini@vanderbilt.edu;
Tristan Potter: Department of Economics, Boston College; Joel Rodrigue: Department of Economics, Vanderbilt
University, joel.rodrigue@vanderbilt.edu. We thank Cem Karayalcin, Diego Restuccia, Richard Rogerson forcomments that substantively improved our paper. We also thank conference participants at the SED 2011 heldin Ghent, Belgium and the Conference on Macroeconomics Policy, hosted by Bilgi University in Istanbul, Turkey
in 2011. We thank David Schenck for excellent research assistance.

1Smoot and Congressman Hawley on Larry King Live in 1993. This was the time at which thecontroversial North American Free Trade Agreement (NAFTA) was being debated in Congress.
Despite the theatre surrounding the Smoot-Hawley tari¤, the scope of the legislation and its
economic impact remain poorly understood. Much of what is known about the economic e¤ectsof SH and the foreign retaliation that took place comes from macroeconomic models that focus
on the impact of the average tari¤ on imports. The emerging consensus from this literatureis that the tari¤ war alone could have at most precipitated a moderate recession with a larger
impact on international trade, but the quantitative e¤ects would be trivial in comparison to
the depth and duration of the Great Depression. Far less is know about the impact of the SHtari¤s across U.S. industries, and the resulting potential for sectoral misallocation. Our goal inthis paper is to assess the extent of sectoral misallocation, and to develop a measure of theiraggregate impact.1
The most obvious reason for the lack of study on the e¤ect of sectoral misallocations resulting
from the SH tari¤s is the complexity of the tari¤ schedules themselves. The tari¤ and trade
data compiled for the quantitative analysis of this paper is the complete line item data fromthe Foreign Trade and Navigation of the United States (FTNUS) at three di¤erent points intime. The number of individual import line items (tari¤ lines) typically exceeds 4,000 withad-valorem-equivalent duties ranging from a few percentage points to almost 300. Even morechallenging is the fact that the duties themselves took one of three forms: i) pure ad-valorem,
assessed as a percentage of the foreign value imported, ii) speci…c duties, assessed in nominal
U.S. currency units per physical quantity imported or iii) a combination of the two.2 Thepractical implication of this is a high degree of dispersion of e¤ective ad valorem tari¤ rates
across sectors, and signi…cant movements in both the mean and variance of those rates overtime due to a combination of legislative changes and price-induced changes in the ad valorem
equivalent of speci…c duties.
The impact of both legislative and price-induced variation is evident even at the level of thecommonly used aggregate tari¤ index computed as the ratio of customs revenue to total dutiable
imports. Figure 1 shows this measure of the aggregate U.S. tari¤ rate annually from 1914 to1940 and identi…es the dates of three key pieces of tari¤ legislation. The …rst is the Emergency
Tari¤ Act of 1921 which was quickly followed by the Fordney-McCumber Tari¤ Act of 1922.
Combined, these two pieces of legislation led to a sharp rise in the tari¤ index from its historicaltrough in 1920. The third notation in the …gure is the date the SH tari¤ schedules went intoe¤ect, June 17, 1930. The increase relative to 1929 is evident, though smaller in percentage terms
than the increases of the early 1920s. Note, however, the aggregate tari¤ measure increases from1

Irwin (2011) provides an excellent discussion of the political process that led to the passage of the SH
legislation. Our analysis will focus on the impact of the legislation, taking the process that generated it as agiven.
2
During the period of this study, the United States did not have much in the way of preferential tari¤s, anddid not use quantitative restrictions on imports.

2

44:7% in 1930 to 59% in 1932 despite the absence of additional legislative changes. Prior researchsuggests that much of the variation in this measure during the interwar period re‡ects the e¤ectof price level changes on the ad valorem equivalent of speci…c duties. In particular, the rapidin‡ation of World War I reduced tari¤ levels substantially from 1914 to 1920 while de‡ation of
the early 1930s increased tari¤ levels substantially above the rates determined at 1930 prices. In
addition, since the tari¤ rates in Figure 1 are value-weighted averages of individual tari¤ lines,
they will be downward biased measures of the average tari¤ level in the SH schedule due toimport substitution bias while also failing to re‡ect the distribution of tari¤ levels across items.
These issues turn out to be central to our quantitative analysis because it is well recognized thatboth the mean and the dispersion of tari¤ rates play signi…cant roles in determining the welfaree¤ects of trade barriers. In particular, a high degree of dispersion in tari¤ rates across sectors canexacerbate the aggregate tari¤ distortion and worsen the allocation of resources across sectors.

FIGURE 1 –UNITED STATES AD-VALOREM EQUIVALENT TARIFF RATE
60

55

50

45

40

35

Smoot-Hawley
T ariff Act
June 17, 1930

Emergency
T ariff Act
May 27, 1921
F ordney-McCumber
T ariff Act
September 1922

30

25

20

15
1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940

Notes: The ad-valorem equivalent rate is computed as the ratio of customs revenues to U.S. dutiable imports.

Our objective in this paper is to address the role of the dispersion of tari¤ rates under the
SH legislation by developing a panel data set that traces the e¤ective ad valorem tari¤ rates
at the tari¤ line level over the period from 1930 to 1933. This panel can be used to address
the question of how the distribution of e¤ective tari¤ rates changed at the line item level as3

a result of the SH legislation and subsequent de‡ation. Combined with our structural model,
it is possible to construct tari¤ wedges, which show the variation across sectors in the price ofimported intermediates resulting from the changes in the tari¤ schedules. In particular, thesewedges identify signi…cant movements in both the mean and variance of tari¤ rates over time due
to a combination of legislative changes and price-induced changes in the ad valorem equivalentsof speci…c duties.3
We utilize these tari¤ wedges in a general equilibrium model to calculate the impact ofchanges in protection on macroeconomic variables, including employment, consumption, anddomestic price indices.4 We derive two aggregate measures of the welfare impact of tari¤s. The…rst is their e¤ect on total factor productivity, which we de…ne to be the number of units ofthe composite consumption bundle per unit of domestic productive resources. The second is theconsumption equivalent, which is the compensation needed in units of aggregate consumption to
make the representative agent indi¤erent between allocations under free trade and those underthe existing tari¤ structure. In our benchmark parameterization, we …nd that the pre-SmootHawley tari¤ legislation had the e¤ect of reducing total factor productivity relative to the free
trade level by 1:2%. The increases in tari¤s associated with the Smoot Hawley and the de‡ationfrom 1930-33 had the e¤ect of reducing TFP by an additional 0:5%. We use a counterfactual
exercise to show that if SH had not been passed, the e¤ects of de‡ation would still have reduced
TFP by 0:3% due to the widespread use of speci…c tari¤s. The consumption equivalent measureyields e¤ects of a similar magnitude for the benchmark parameterization. We also show the
impact of the dispersion in the tari¤ structure across goods in the sense that the uniform tari¤equivalent of the existing tari¤ schedule is substantially above the average tari¤ during thisperiod.
Our paper contributes to the growing literature on the e¤ect of policy distortions on aggregate
outcomes. Restuccia and Rogerson (2008) use a calibration exercise to show that distortions in
the allocation of capital and labor between …rms can lead to substantial reductions in aggregate
productivity. Hsieh and Klenow (2009) calculate the dispersion of marginal products of capitalacross …rms in India and China, and argue that reducing the dispersion in these countries to thelevel observed in the US would have the e¤ect of raising productivity by 40
30

60% in India and

50% in China. Our analysis abstracts from distortions in factor markets, and focuses on

the e¤ect of sectoral tari¤ wedges. The reduction in total factor productivity we …nd as a resultof sectoral misallocations due to tari¤ protection are of a much smaller magnitude than those3
The potential importance of using microdata to address the pattern of protection was …rst shown by Crucini(1994), who constructed annual data from 1903 to 1940 on 32 imported items to examine the variability of e¤ective
ad valorem tari¤ rates. His data show that there is substantial variability in the ad valorem rates across sectors
over time, resulting from both legislated tari¤ changes and di¤erences in the importance of speci…c tari¤s in thelegislation applying to individual items. Our analysis extends Crucini’s analysis by signi…cantly expanding therange of products covered and by developing measures to evaluate how the distortions evolved over this period.
4
Irwin (1998b) analyzes the e¤ect of the Smoot Hawley tari¤s using aggregate data and a CGE model toestimate sectoral e¤ects, but does not utilize the degree of sectoral decomposition that we do.

4

associated with factor market distortions, presumably due to the fact that trade accounted fora relatively small fraction of U.S. consumption and intermediate inputs during this period of
history. We provide counterfactual exercises to illustrate the sensitivity of our results to changes
in the import share of consumption goods and material inputs, as well as to the assumed elasticity
of substitution between imports and domestic goods. These exercises provide some perspectiveon the potential for misallocation e¤ects arising from commercial policy for other time periods
and other nations.
We proceed in the following manner. Section 2 presents the multisector general equilibrium
model and uses it to construct measures of the e¤ects of tari¤ rates on aggregate variables.
Sections 3 describes the construction of the panel data series on tari¤ rates, compares the sector
level panel data to the line item data and presents estimates of sector level tari¤ wedges. Section
4 reports the results for the aggregate e¤ects of tari¤ policy, and section 5 concludes.

2

The Model

Our goal in this section is to develop a tractable model that can be used in conjunction with
our tari¤ line panel to obtain a measure of the impact of sectoral misallocation on aggregate
variables. Our modeling choices are driven by two features of the data from this period. First,
75% of imports are intermediate goods according to the input-output tables for 1929 (Leontief(1941)). Therefore, we want a model that captures the substitution between imported materials
and domestically produced materials in the production process.

Second, there is substantial

variation across tari¤ lines in the extent to which protection was increased during this period, as
well as substantial di¤erences across sectors in the degree to which imported inputs are used in
the production process. For example, imports accounted for 75% of intermediate inputs in thesugar, glucose and starch industry, but less than 1% of intermediate inputs into the agriculturalindustry. This heterogeneity combined with the fact that sugar duties were much higher andvaried more over time than most other agricultural duties indicates the di¤erent industry-level
distortions of these respective duties. This motivates the use of a multisector model that allows
for di¤erential e¤ects of tari¤ protection across the various production sectors.

2.1

The Multisector Production Model

We consider a GE production model with NF sectors producing non-traded …nal consumption
goods and one sector representing exportable goods (sector 0). The NF …nal goods sectors
correspond to the sectors in the Leontief input-output tables. This model allows us to capture
substitution by …rms between domestic and imported material inputs, as well substitution by
consumers between domestic and imported …nal consumption goods. Our model also has a
block recursive structure that provides simple measures of the e¤ects of the tari¤ structure on
aggregate variables.
5Each of the NF + 1 production sectors produce …nal output using inputs of domestic value
added and material inputs. We assume that domestic capital and labor are used in the same
proportions in all sectors, so that value added can be treated as a composite input whose price,pV , is the same for all sectors. The technology for sector j is given by the unit cost function
1

ajV p1VF+ ajM PjM

1

1

F

F

. Here PjM is the price of material inputs in sector j, andF

is the elasticity of substitution between value added and materials in the production of …nal
goods. The material inputs for sector j consist of domestic and imported materials. Assumingthat the domestic material input is produced using value added alone and that the productionof materials is perfectly competitive, the price paid for material inputs in sector j will equal the1unit cost of the composite material input, PjM = ajd pV1M

1 M+ ajm pjm

1M

; where pjm isthe cost of a composite of line item imported inputs used in production in sector j andM isthe elasticity of substitution between domestic and imported materials.
The sector-speci…c input prices are constructed from our tari¤ line panel using the inputoutput structure of the U.S. economy (Leontief (1941)) and the existing microeconomic tari¤
structure. Letting

i be one plus the ad valorem tari¤ rate on good i and qi the world price ofthat good, the import price index for materials used by sector j will be
pjm =

X Nm
i

1

1

bji ( i qi )where Nm is the number of tari¤ lines,

1mm

j = 0; 1::; NF(1)m is the elasticity of substitution between tari¤ lines,

and the bji , are parameters that re‡ect the intensity with which good i is used as an input into
the production of sector j.5
With perfect competition in the production of materials and …nal goods, the price of a …nal
good will equal its unit cost,
pjF =ajV p1VF+ ajM ajd pV1M

1 M+ ajm pjm

1
1

F
M

!

1
1

F

, j = 0; 1::; NF(2)

We assume that the exportable good is sold on world markets at an exogenously given world
price, q0F

1. The zero pro…t condition for the exportable sector can be inverted to solve

for the return to domestic value added as a function of the price of imported goods used in
the exportable sector, pV (p0m ). This solution can then be inserted into the remaining zeropro…t conditions to solve for the prices of the NF non-traded consumption goods. We thus have
solutions for prices of domestic non-traded goods and factor inputs as a function of the vectorof tari¤s, , and world prices of the home country importables, q, that determine the pjm from5
The bij are functions of both the input-output structure of the US economy in 1929 and a base period pricevector. The details of the mapping between the two are discussed in section 3.2.

6

(1).6In the case of a small open economy, q is exogenously given and there will be complete
pass through of tari¤s to prices paid by the domestic purchasers of imports. We will treat
the US as a small open economy in our analysis below, which merits some discussion. Our
assumption ensures that all of the distorting e¤ects of the tari¤ are borne by the US, and thus
can be thought of as representing an upper bound on the aggregate productivity e¤ects of tradebarriers.7 In contrast, if US tari¤ increases have the e¤ect of reducing world prices, this will
represent a terms of trade improvement for the US that will be an o¤set against the productivity
losses that we calculate. This could be captured in our analysis by allowing for incomplete passthrough of tari¤s to domestic prices. However, there is little evidence of negative e¤ects of tari¤
rate changes on world prices in our tari¤ line data.8 The absence of a signi…cant correlation
seems consistent with the fact that US imports were only $4:4 billion in 1929, which represented
approximately 12% of world trade. Also, tari¤ retaliation by foreign countries would have thee¤ect of mitigating the terms of trade improvements that the US experienced on account of its
own tari¤ rate increases.
We conclude our discussion of the production side of the model with the production function
for domestic value added,
V = AK 1

L ;(3)

where K is the input of capital, L is the input of labor, and A is the productivity level. We will
undertake a short run analysis in which the capital stock is assumed to be …xed. The market
wage will be determined by the marginal productivity condition,
w
=A
pV

K
L

1

(4)

For a given K=L, protection will lower the wage rate because it lowers pV = pV (p0m ): The levelof labor input will be determined as part of the household decision problem, to which we now
turn.
6

Our assumption of a single export sector is made to be consistent with our assumptions of a single (composite)
domestic factor input and exogenously given world prices. The latter assumptions ensure that national income
can be maximized by specializing in the traded good that yields the highest return to the domestic factor of
production.
7
We should note however that the e¤ects could be larger in a dynamic model, where tari¤s a¤ect capital
accumulation.
8
If US tari¤s have a signi…cant e¤ect on world prices, then the world price of goods on which the US imposes
higher tari¤s should fall relative to other goods. To test this, we regressed changes in world prices on changes intari¤ rates, allowing for di¤erential coe¢ cients based on whether goods had ad valorem or speci…c tari¤s. We did
not …nd a signi…cant negative e¤ect of tari¤ changes on prices for either type of protection.

7

2.2

Household Decisions and Market Equilibrium

The preferences of households are assumed to take the following form:
L
C1 s
1 s
0
1 C
C 1
NF
1
1
X
C 1
C 1
C
where C = @acjC Cj C + acm
Cm C A
.
U

=

(5)

j=1

The intertemporal elasticity of substitution in consumption is given by 1s , and the Frisch elasticityof labor supply by

1

1 : The consumption levels Cj are demands for the …nal goods from theproduction sectors j = 1; ::; NF , Cm is the consumption of imports, andC is the elasticity of

substitution between all consumption goods, domestic and imported.
P F
The household budget constraint is N
j=1 pjF Cj + pcm Cm = wL + rK + T , where T is theamount of tari¤ revenue transferred to households. The prices pcm and pjF are the indices forimported consumption goods and each non-traded …nal good j, constructed as in equations (1)and (2), respectively. The household consumption allocation between domestic and imported
goods can be solved using two stage budgeting. The necessary conditions for choice of C and L
yield
C sL

1

where PC

w
PC
0
1 1
1
C
NF
X
1 C
1 CA
@
=
acj pjF + acm pcm

=

(6)

j=1

PC is the price index for consumption, which can be used to derive the shares of expenditure on
domestic and imported goods in aggregate consumption,j(pjF) = acj
PC

pjF
PC

m(

pcm
) = acm
PC

pcm
PC

1

C

j = 1; :::; NF
1

(7)

C

.

Letting YjF denote the output of the …nal good of sector j, the market clearing conditions fordomestic consumption goods are
pjF YjF =

j(

pjF
)PC C
PC

j = 1; ::; NF .

(8)

The market clearing condition for domestic value added requires that the sum of demands for
PNF
value added across sectors equal the supply,
j=0 jV pjF YjF = pV V , where jV (pV ; pjm ) =8

@PjF (pV ;pmj )
@pV

pV
pjF

is the share of value added (both direct and as a share of materials) insector j. This market clearing expression can be used to solve for the level of exports as afunction of aggregate value added and the output of non-traded goods,
Y0F =

PN f

pV V

j=1 jVj PC C(9)0V

In order to determine the level of tari¤ revenue, we need to derive demands for the imported
products at the tari¤ line level. The share of imports of tari¤ line i in the expenditure of@pjm qi i
qi i
ji ( pjm ) = @(qi i ) pjm

activity j on imported inputs is given by

= bji

1

qi i
pjm

m

.

Using (7),the value of imports in tari¤ line i will be the sum of the value of imports for …nal consumption,
ci m PC C, and the value of imports for intermediate use from the various production activities,

PNF

j=0

ji jm pjF YjF , where

jm

= 1

jV

is the share of imported materials in the cost of

production of good j. Using (8) and (9), we obtain an expression for tari¤ revenue as a functionof value added and aggregate consumption:T=

V pV V +C PC C

(10)
where

V

=

Nm
X

C

=

i=1

The terms

V

and

C

0m
0i

i

i=1

Nm
X

1

i

1

i
i

0
@

>0

0V
NF
X

0i 0m jV
ji jm
0V

j=1

j +

1

ci m A .

capture the e¤ect of an increase in value added and consumption ontari¤ revenue. These factors play a key role in measuring the distortions from the tari¤ structure, because they represent the …scal e¤ects of household decisions regarding labor supply andconsumption.
To interpret the coe¢ cientV , note that an increase in value added will result in an increasein production of exportable goods from (9). This increase in exports requires an increase in theimport of intermediate inputs for the exportable sector, which raises tari¤ revenue and has apositive spillover to household income. The interpretation of

C is more complicated, because

it involves a reallocation of resources between the traded and non-traded goods sectors. An
increase in aggregate consumption will raise imports of …nal consumption goods and imports ofmaterials to produce the non-traded domestic consumption goods. However, it will also resultin a reduction in production of exportables, and thus a reduction in imported material inputs tothe exportable sector. This leads to an ambiguous e¤ect of an increase in aggregate consumption
on tari¤ revenue, since tari¤ revenue could actually fall if exports are intensive in the use ofintermediate inputs relative to other production and consumption activities.

9Substituting (10) into the budget constraint yields
C
pV (1 +=T F P ( ; q) =
V
PC (1

V)

(11)

C)

The right hand side of (11) expresses the amount of the composite consumption good that canbe generated per unit of the composite factor input as a function of the tari¤ structure andthe terms of trade. This index can be interpreted as a measure of total factor productivity forthe open economy. The numerator is the social return to value added, which is the market
return plus the additional tari¤ revenue generated from an additional unit of value added. The
denominator of this expression is the social cost of consumption, which is the market cost lessthe tari¤ revenue generated by additional imports (which could be negative). The introductionof tari¤s will reduce the real return to value added, PpVC , relative to the free trade level because
protection reduces the return to value added in the exportable sector and raises the relative costof imported intermediates and …nal goods used in the consumption bundle. The adjustment
V)for tari¤ revenue, (1+(1 C ) , will be equal to unity at free trade and at autarky from (10). It

can be shown that this measure of total factor productivity is maximized at free trade in thesmall country case, since tari¤s result in deadweight losses by causing ine¢ cient substitution ofdomestic goods for imports.
In addition to its impact on the e¢ ciency of resource use, protection will also distort labor
supply and consumption decisions. Substituting (6) into (11) and using the fact that wL =pV V , we obtain a solution for the equilibrium level of employment

L( ; q) =where (s1) +> 0 for all s

pV
AK 1
PC
0 since1 s1(s 1)+(T F P ) s(12)

1. The existence of tari¤ protection will reduce

both PpVC and T F P relative to the free trade level. The former e¤ect will tend to reduce the levelof employment relative to free trade, whereas the latter e¤ect will tend to increase it. Thus,tari¤ protection will have an ambiguous e¤ect on employment relative to the free trade level.
The equilibrium level of consumption is obtained by substituting from (12) and (4) into (6),which yields
C( ; q) =

pV
PC

AK 1

(T F P )! (s 11)+.

(13)

Consumption will be increasing in PpVC and T F P , so tari¤ protection will unambiguously reduce
consumption relative to the free trade level.
The solutions to (13) and (12) can be substituted into (5) to construct the indirect utility

10

function
W ( ; q) =C( ; q)1 s
1 s

L( ; q)(14)(14) will be maximized at free trade in the small country case. To calculate the e¤ect of a given
tari¤ structure,

0 , on welfare we can calculate the level of consumption that would lead to thesame welfare as at free trade, given the distorted labor supply. This consumption equivalentvalue, which we denote C E , is the solution to
U (C E ; L( 0 ; q)) = W (1; q) .

(15)

The expressions (11) and (15) can be used to measure the aggregate e¤ects of tari¤ protection
on resource allocation and welfare. If the tari¤ structure does not a¤ect aggregate employment,
then aggregate value added will be constant and the loss in consumption due to tari¤ protection
will coincide with the reduction in TFP. When tari¤ protection reduces (raises) employment,
the loss in consumption will be smaller (larger) than the reduction in TFP.
A second question of interest is the e¤ect of the variance in the tari¤ structure on welfare.
This question can be addressed by solving for the uniform tari¤ that yields the same welfare
level as the existing tari¤ structure. Letting

0 be an initial tari¤ vector and q0 the vector ofworld prices of importable goods, the uniform tari¤ vector U that yields the same domestic

welfare will be the solution toW ( U ; q0 ) = W ( 0 ; q0 ) .
This measure corresponds to the trade restrictiveness index (TRI) constructed by Anderson and
Neary (2005).

3

The Tari¤ Line Data and Sectoral Price IndicesThree volumes of the FTNUS have been painstakingly converted from the original text source
to an electronic data archive in order to construct a panel consisting of three cross sections.
The …rst cross section records imports during the …rst six months of 1930 when the FordneyMcCumber tari¤s of 1922 were still in e¤ect, which we will refer to as the 1930A cross section.
The 1930B cross section covers the last six months of 1930 when the Smoot-Hawley tari¤s were…rst applied to U.S. imports. The third cross section covers the entire year 1933. We chose
two post Smoot Hawley cross sections to illustrate how the tari¤ structure changed as a resultof the e¤ect of price de‡ation on sectors with speci…c tari¤s. The year 1933 was chosen forthe second post SH cross section for two reasons. First, it is the trough of the U.S. businesscycle and captures the maximum change in imports resulting from the collapse in aggregate
demand over the business cycle contraction phase. Second, 1933 also coincides with the pricelevel trough. This is important for our study of the relationship between imports and tari¤s

11because many customs duties were speci…c. Thus, the price level trough also coincides with thepeak ad-valorem-equivalent rates of duty for many imported goods. As far as we know, this is
the only archive of U.S. imports and duties in existence at the line item level for the 1930s.
Table 1 provides a sense of the scope of our cross sections. The number of line items fromthe original FTNUS source document increases from 4,861 to 5,280 and then to 5,629 as we moveacross the three cross sections. The larger increase in 1930, despite the shorter time interval, islargely due to the expansion of the scope and level of detail in the tari¤ schedules themselves.
Relative to these maximums, the fraction of available data varies across the measures of value
imported, quantity imported, import price, duty collected and the ad-valorem-equivalent tari¤rate. The value imported is available for more than 95% of the line items. The quantity data
are next most abundant, available for about 90% of the line items. The price data are imputed
as unit values, taking the ratio of value imported to the physical quantity imported and thus
require availability of both measures. As such, they are available for fewer line items than either
value or quantity, 85% typically. Since some items are duty free, the duty and tari¤ columns
also have fewer entries than the value column. In sum, the cross-sections represent the complete
record of U.S. trade ‡ows at the line-item basis.

TABLE 1: SCOPE OF THE CROSS-SECTIONS (SOURCE DATA)
Number of observations

Proportion available

Pre-SH

Post-SH

1933

Pre-SH

Post-SH

1933

Tari¤ lines

4,861

5,280

5,629

1.00

1.00

1.00

Value imported

4,750

5,001

5,302

0.98

0.95

0.94

Quantity imported

4,388

4,685

5,007

0.90

0.89

0.88

Price

4,290

4,422

4,690

0.88

0.84

0.83

Duty

4,018

4,321

4,487

0.83

0.82

0.80

Ad-valorem rate

3,980

4,207

4,345

0.82

0.80

0.77

3.1

Construction of Panel Data

Conducting research in an environment with enormous heterogeneity in the products and thetari¤ levels across them poses some unique challenges. To measure the change in the quantity
imported in response to a good-speci…c tari¤ change requires careful control of the quality ofthe matches of goods across time. Attention must also be paid to the fact that tari¤ lines are
sometimes split or combined. This makes some rudimentary aggregation necessary to avoid
excluding a signi…cant number of entry-level items.
To match goods across time, we employed a text-matching algorithm to tari¤ lines in 1930A
with those in the 1930B and 1933 cross sections. Since there was both splitting and aggregationof tari¤ lines during the period, the text matching algorithm did not provide one to one matches12

in many cases. In these cases, we constructed an aggregated line item series by taking a weighted
average of the individual line items using the 1930A import values as weights. This procedure
resulted in a balanced panel of 495 line items, accounting for 18% of trade in 1930A and 25%of trade in 1933. The reduction in the number of tari¤ lines occurs for two reasons. First,
aggregation naturally reduces the number of individual tari¤ lines and due to a large degree ofre-organization between 1930A and 1930B/1933; it is common for two or more line items to bematched to the same line item in a later cross-section. Second, aggregation exacerbates missing
data issues. Any set of line items which is matched to any individual observation with missing
data have to be discarded since the aggregation cannot be performed.9
Let ~it denote one plus the legislated ad valorem tari¤ for tari¤ line i and let wit denote thelegislated speci…c tari¤ in the tari¤ schedule implemented at time s. The e¤ective ad valorem
tari¤ rate at time t is thus de…ned as
it (qit ) = ~ is +

wis
qit

(16)

where qit is the world price of good i at time t. The tari¤ rates under the Fordney-McCumber
Act were in e¤ect for the …rst 6 months of 1930, which is denoted as t = 0 (the 1930A crosssection). The Smoot Hawley tari¤s schedule was in e¤ect for the 1930 B (t = 1) and 1933 (t = 2)cross sections. The variation in e¤ective tari¤ rates between t = 1 and t = 2 will thus include
only the price level induced changes resulting from changes in import prices.10 . We will also use(16) to construct the tari¤ vector

0 (qt ) for t = 1; 2 which represents the counterfactual e¤ective

rates that would have been observed if the Smoot Hawley legislation had not been passed.
We can provide a sense of how representative our balanced panel is of the underlying crosssections by comparing their distributions and reporting key statistics. Arguably one of the mostimportant distributions is the microeconomic distribution of ad-valorem-equivalent tari¤ levels
across goods. Figure 2 plots kernel estimates of the distributions of tari¤s before Smoot-Hawley
was passed, after Smoot-Hawley was passed and in 1933. The solid line is the raw (source) microdata and the dashed line is the balanced panel data. It is quite evident that the balanced panel
is representative of the underlying line-item tari¤ data. The tari¤ levels are underestimated by
the panel, but the di¤erences are quite minor, the largest di¤erence being the pre-Smoot Hawley
panel where the median ad-valorem-equivalent rate is 0.31 compared to 0.37 in the full archive.
Table A1 of the appendix reports additional comparisons of the full cross-section and panel.
9
A detailed discussion of the quality of the matches from the text matching algorithm, as well as further
discussion of the aggregation procedure, is provided in Appendix A.
10The signi…cant role played by price level changes in the e¤ective tari¤ rate has been emphasized by Crucini(1994) and Irwin (1998). The e¤ective tari¤ rate in (16) can be decomposed into a policy component, which
evaluates the change due to legislated changes in ~ and w at given world prices, and a price level e¤ect. The
correlation between the policy e¤ects and price e¤ects is -.049.

13

FIGURE 2 –TARIFF COMPARISONS, ORIGINAL ARCHIVE AND PANEL

0 .0 60 .0 60 .0 9F u l l c r o s s - s e c tio n
F u l l c r o s s - s e c tio n

F u l l c r o s s - s e c tio n

P a n e l d a ta

P a n e l d a ta

P a n e l d a ta

0 .0 80 .0 50 .0 50 .0 70 .0 40 .0 40 .0 60 .0 50 .0 30 .0 30 .0 40 .0 20 .0 20 .0 30 .0 20 .0 10 .0 10 .0 1

0
0

0
0

0 .5

1

1 .5

0
0

0 .5

1

Note: Solid line is density estimate of original tari¤s (

0 .5

1

1 .5

1 .5

1) in the FTNUS archive,

dashed line is panel data.

A second concern about the reliability of our panel data is the extent to which we havesuccessfully matched industries over time. An important issue in our analysis is the extent towhich tari¤s vary over time, whether due to changes in trade policy or due to changes in importprices that alter the protective e¤ect of ad valorem tari¤s. If we are not matching industries
correctly over time, this will introduce a measurement error into our comparisons of tari¤ rates
over time. Since the tari¤ legislation did not change between the 1930B and 1933 samples, acrude measure of the quality of a match is the di¤erence between the tari¤ rate (whether advalorem or speci…c) for 1930B and 1933. For ad valorem tari¤ rates, 75% are within 1% of thebase period rate, 77% are within 5% of the base period rate, and 91% are within 25% of thebase period rate. The average base period (1930B) tari¤ rate was 16 percent. For speci…c tari¤
rates, 81% are within 1% of the base period duty, 84% are within 5% of the base period duty,
and 89% are within 25% of the base period duty. The average base period (1930B) speci…c duty
was 25 cents.

3.2

Construction of Sectoral Price Indices

The import price indices de…ned in (1) represent ideal price indices for the cost of imports to
the NF + 1 production sectors and …nal consumption. Our tari¤ line panel provides the values

14

of

jt and qjt required for construction of these indices, but we also need to obtain values forthe taste parameters, bji , and the elasticities of substitution,m.

The expression for the share of imports from tari¤ line i by activity j,qi iji ( pjm ) = bji

1

qi i
pjm

m

can be used to express the bij in terms of observables at time t and the elasticity of substitution,bji =Note that since thejit

qit itpjm (pt )

m

1

.

(17)

ijt are homogeneous of degree 0 in the vector of coe¢ cients bi , the system of

equations (17) determines the bij vector only up to a multiplicative constant. We can determine
unique values for a given value ofm by choosing a normalization of base period price such as

pim0 (p0 ) = 1
The tari¤ line data provide the total value of imports in the tari¤ line i, vit , but not theallocation of these imports across the …nal goods sectors as required for theable to construct a proxy for the budget shares in the base year,

jit . However, we are

ij0 , using the Leontief tables

and the tari¤ line data by making two assumptions. The …rst assumption is that …nal goodindustry i’s share of consumption of imports from tari¤ lines associated with …nal goods sector
k is equal to its share of consumption of domestically produced intermediates from …nal goods
sector k. Letting vij0 denote imports by industry i in tari¤ line j in the base year, Jk denote theindex set of tari¤ lines associated with industry k, andki the share of industry k’s output thatis sold as intermediate goods to sector i, this assumption implies thatP

vij0 =

ki

j2Jk

P

vj0 .

j2Jk

The second assumption is that the imports of …nal goods sector i from …nal goods sector j areallocated across tari¤ lines !
in proportion to their share in total imports from industry k, which
requires

Pvij

j2JK

vij =

Pvj

vj

: Together these assumptions imply that vij =j2JKki vj for all j 2 Jk ,so that the base year budget shares can be expressed as
vij0
vj0= P Pkiij0 = Pki vj0j vij0
k j2Jki = 1; ::; NC ; j = 1; ::; Nm .

(18)

The base year budget shares are calculated using Leontief’s 1929 input-output tables for thekiand the 1930 (pre HS) tari¤ line data for the vj0 .
To complete the construction of the import price indices, we calibrate the values ofm andC to match the change in imports between 1930A and 1930B in response to the changes intari¤s and world prices. Using (1) and (8) we can express the demand for imports as materials
by sector j from tari¤ line i as mji =

pjF
qi i
ji ( pjm ) jm (pV ; pjm ) j ( PC )PC C. Totally di¤erentiating

this expression and de…ning x^ = dx
x , we havem
^ ji =sji (^i + q^i ) + sVji p^V + sFji P^iF + sVji P^C + C^

15

(19)

,

where the coe¢ cients skji are functions of the elasticities of substitution, ( C ;F;

M;m ), andthe cost shares. A similar expression can be derived for m^ ci , and the model’s prediction of
the change in imports from tari¤ line i, m
^ i , will be an import share weighted sum of the m^ ji .
Assuming that

= 1;

F

m =

^V
M , and that p= p^jF = p^C = w^ are given by the rate ofchange in the GDP de‡ator, we obtain an expression for the change in imports in tari¤ line i
as a function of

C

and

m.

We choose the valuesCandm to match price and quantity

movements in the data between the 1930A and 1930B cross sections. We then compare thechange in imports between the 1930A and 1933 cross sections with the predictions based on ourcalibrated parameters as an out-of-sample check on our parameter choices. The results for the
1930B and 1933 cross-sections are displayed in the two panels of Figure 3.

FIGURE 3 –ACTUAL AND PREDICTED INDUSTRY-LEVEL CHANGES
1930A TO 1930B

1930 TO 1933

0.6

0.4

3

Model
Data

2

0.2

1

0

0

-0.2

-1

-0.4

-2

-0.6

-3

-0.8

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

-4
-15

2.5

Model
Data

-10

-5

0

5

10

Figure 3 displays the model predicted data (blue dots), the actual data (green crosses) anda quadratic regression of actual import prices changes on import quantity changes. We observethat the relationship between import price and quantity changes in 1933 is nearly linear. Further,settingm = 3:5 andC = 2:5, we …nd that the model matches the data very closely. In 1930

we observe a less linear relationship between prices and quantities. In particular, there are anumber of goods for which we observe large declines in import quantities in response to moderate
import price increases. This is arguably reasonable if the legislated tari¤ increases were foreseen
by importers, who were in turn able to increase imports in the …rst half of 1930 before the tari¤changes took e¤ect. Nonetheless, overall the model matches the data relatively well.11
11

These parameter values yield a price elasticity of import demand elasticity that averages 3.1 Our estimatesof the elasticity parameters are relatively low compared to those presented elsewhere in the trade literature. For
instance, Eaton and Kortum suggest an elasticity of substitution across imports near 8, while Simonovka andWaugh (2011) suggest that an improved estimate would be closer to 4. We note that increasing m from ourbenchmark estimate results in higher tari¤ wedges a larger role for tari¤ policy in determining trade ‡ows. In lightof our relatively conservative elasticity estimate ,we also consider a counterfactual exercise with larger elasticities.

16

15

Given our benchmark parameterization, we can use our constructed import price indices tomeasure the impact of the SH policy on the cost of imported goods across industries and overtime. Speci…cally, we calculate the tari¤ wedges for each industry in year t to be
2

PNm

pjm (pt ) 6 i= 4P
pjm (qt )
Nm
i

ji0
ji0

qit itqi0 i0
qit

1

m

1

m

qi0 i0

3
7
5

1
1

m

i = 0; ::; NF and C

given the individual tari¤ line item data, the Leontief share data and our parameterization ofm.

The results are presented in Figure 4 where we have sorted the tari¤ wedges from lowest

to highest based the 1930A, pre-SH tari¤ wedge.
FIGURE 4 –ESTIMATED TARIFF WEDGES BY INDUSTRY AND CROSS-SECTION
3
1930A
1930B
1933

2.5

2

r leat

Othe

Leat

1

her s
ho
Bras ess, etc
her p
.
rodu
cts
Coke
Auto
Sme
mob
lting
iles
and
refinin
Leat
g
her t
annin
Iron,
Chem gstee
ica
Rubb l and ele ls
ctric
er m
anufa
Stee
ctu
l and
rollin res
g mil
Indu
ls
str
Othe
r text ies n.e.s.
il
ep
Othe
r woo roducts
d pro
ducts
Agric
ulture
Print
Clo
ing a
nd pu thingbli
Manufact shing
ured
gas
Coal
Yarn
Othe
r pap and cloth
er pr
oduc
ts
Iro
Pape
r and n mining
wood
Re
pulp
Non- fined petrferro
us m oleumetaLum
ber a l min.
Slaund tim
ghter
ber
ing a
nd m
eat
Tran
sport
at
Elec
tric u ion
F
lo
u
Petro
r and tilities
leum
grist
a
mill
Toba nd naturalcco manufa gascturesNon- Construc
tion
meta
l min
erals
Liquo Blast fur
nace
rs an
s
d bev
erag
Brea
es
d
a
nd ba
Othe
kery
r foo
Butte d industrier, che
s
Cann
ese,
ing a
e
Suga nd prese tc.
rr, glucose ving, starch

1.5

Figure 4 demonstrates a striking degree of heterogeneity in the tari¤ wedge across industries
in all three cross-sections. Even before the SH policy was implemented (the blue line) we observethat tari¤ wedge ranges from a low of 1.01 (leather shoes) to a high of 1.91 (sugar, glucose, andstarch). Over time we observe that the heterogeneity increases with the onset of the SH tari¤policy and the propagation of the Great Depression. The green line in Figure 4 represents thetari¤ wedges in 1930 after the SH-policy has been passed. As expected, trade barriers rose formost industries, with many of the largest increases occurring in industries that already had largetari¤ wedges before the change in policy. By 1933 the wedges range from a low of 1.11 (leather
shoes) to a high of 2.73 (sugar, glucose and starch). These are enormous increases in tradebarriers. At the low end, the leather shoe industry experiences a 10 percent increase from the17pre-SH period, which is not small by historical standards). However, it seems minute relative
to the 82 percent increase the sugar, glucose and starch industry over the same time.
TABLE 2 –TARIFF WEDGE MOMENTS
1930A

1930B

1933

Mean

1.32

1.46

1.59

Variance

0.0486

0.124

0.116

0

0.156

0.268

Mean Absolute Deviation

Notes: The mean absolute deviation is relative to 1930A.

Table 2 shows that the mean tari¤ wedge prior to SH was equivalent to a 32% tari¤ onimported inputs. The SH legislative increase combined with de‡ation during 1930 increased thesize of the mean tari¤ wedge to 46%, and the subsequent de‡ation further increased it to 59% at
the trough of imported prices in 1933. In addition to increasing the mean of the tari¤ wedges,
the SH legislation also raised the cross-sectional variance of tari¤ rates substantially from 5%prior to SH to 12% in 1933.

4

Aggregate E¤ects of the Tari¤ Structure

The analysis of the previous section documented the wide range of sectoral distortions resulting
from the SH tari¤ legislation and subsequent de‡ation. In this section we examine the impactof these distortions on aggregate consumption, employment, and welfare using the measuresderived in Section 2.
The …rst exercise we conduct is to calculate the aggregate impact of protection using thetari¤ ratett (qt ) in time period t, which is calculated from (16) using the tari¤ schedulefrom period t and evaluating the ad valorem equivalent of the speci…c tari¤s using world prices
at time t. We thus incorporate both legislated changes in tari¤ rates and price level inducedchanges in tari¤ rates for each period, which results in an increase in the the mean tari¤ ratefrom 30.8% in 1930A to 45.7% in 1933 and an increase in the variance from 0.052 to 0.125. Inorder to abstract from terms of trade changes, we solve for the equilibrium values assuming thatprices remain constant at the 1930A levels, so that consumers and producers are assumed to befacing the tari¤ laden price vector

12
t q0 at t.

12

The cost function parameters (a0d ; a0V ; a0m ) and pV 0 are the values that satisfy the zero pro…t condition andmatch the cost shares ( 0d ; 0V ; 0m ) from the input-output tables. The (ajd ; ajV ; ajm ) are then solved to matchthe respective cost shares given pV 0 for j = 1; ::NF : A similar procedure is used to solve for the acj from the jin the data.

18

TABLE 3 –BENCHMARK CASE
Tari¤ Structure

1930A

1930B

1933

1)

30.8

38.8

45.7

Variance of Tari¤s

0.052

0.072

0.125

49.0

58.0

69.7

(qt );q0 )Value added price: pV p(V 0(1;q
0)

-1.0

-1.0

-1.3

(qt );q0 )Consumption price: PCp(V 0(1;q
0)

1.2

1.4

1.5

T F P ( 0 (qt ); q0 )

-1.2

-1.4

-1.7

0 (qt );q0 )Employment: L(L(1;q
0)

0.1

0.1

0.2

0 (qt );q0 )Consumption: C(C(1;q
0)

-1.2

-1.3

-1.6

1.2

1.4

1.7

Mean Tari¤ (Uniform Tari¤ Equivalent (1)

E);q0 )
Consumption Equivalent : CC(( 00(q(qtt);q0)

Note: Parameter values: s = 2,
M =m = 3:5,

C = 2:5,= 2:5,= :667,F = 1.

Table 3 reports the values for some of the key the aggregate variables from the model, witheach variable reported as a percentage change relative to its free trade variable Thus, the e¤ectof the pre-SH tari¤s is to reduce the return to domestic value added by about 1% relative to thefree trade level. This is due to the fact that the pre-SH tari¤s increased the price of importables
to the production of exports by about 25%, and these imports accounted for approximately 3%of the cost of the exportable good in the base period. Subsequent tari¤ increases due to SH andde‡ation had little impact on the return to value added. Similarly, the cost of the aggregate
consumption bundle was about 1:2% higher in 1930A due to the pre-SH tari¤s, and increased
an additional 0:3% due to SH. The third row in Table 3 shows that the aggregate e¤ect of tari¤
protection on TFP at the peak of tari¤s in 1933 was to reduce it by 1:7% relative to the free
trade level. Note that almost 2/3 of the e¤ect of tari¤ protection on TFP was due to the pre-SHtari¤s, with SH and the subsequent de‡ation reducing aggregate productivity by approximately
0:5% compared with the pre-SH level.
In order to calculate the e¤ects on employment and consumption, we choose the utility
function parameters s = 2 and= 2:5. These choices yield an intertemporal elasticity of

substitution of 0:5 and a Frisch elasticity of labor supply of 2=3, which are within the range ofvalues obtained from micro studies.13 With these parameter choices, tari¤ protection leads to
13

Chetty et al (2011) argue a Frisch elasticity of 0:75 is the upper bound of values that are consistent with19

a decrease in consumption of about 1:6% and an increase in employment of about 0:2%. As
noted in the discussion of (13), tari¤ protection will decrease consumption relative to free trade
because reduction in T F P and PpVC both work to reduce consumption. The e¤ects of these twochanges on employment are con‡icting, and with our chosen parameter values the net e¤ect isa small increase in employment.14 The equivalent consumption e¤ect indicates that at the peakof tari¤ protection, consumption would need to be increased by 1:7% to raise welfare to the free
trade level. This is essentially equal to the TFP e¤ect due to the minimal e¤ect of protection
on the level of employment.15
The comparison between the uniform tari¤ equivalent and the mean tari¤ shows that although the mean tari¤ was 45:7% at its peak, the e¤ect of the tari¤ structure was equivalent
to that of a uniform tari¤ of 69:7%. The increase in the variance of tari¤s thus had a signi…cant e¤ect in increasing the distortion associated with the protective structure as measured by
the uniform tari¤ equivalent. However, as already noted it had a relatively small e¤ect on theaggregate productivity and welfare measures.
How would the outcome have di¤ered if Smoot Hawley had never been passed? We canaddress this question by solving the model using the e¤ective tari¤ rates associated with the
pre-SH tari¤ legislation for all three periods of the panel,

0 (qt ).

This exercise captures thee¤ect of the decline in world prices on the e¤ective tari¤ rate for goods that had speci…c tari¤sunder the pre SH legislation. As in the benchmark case, we assume world prices remain …xed
at the initial level. The results for this counterfactual exercise on the aggregate measures arereported in Table 4. Since the pre-SH tari¤ included a number of speci…c tari¤ rates, the decline
in prices still yielded an increase in the 1930B and 1933 cross sections that was about halfthat arising from the Smoot Hawley legislation as shown by the mean tari¤ rate. Interestingly,
the variance of tari¤s in 1933 would have been comparable to that under SH. As a result, theincrease in the uniform tari¤ equivalent is almost 2/3 of that occurring with SH. The decline in
TFP in the absence of SH would have been 1:5% relative to the free trade level, and the required
consumption increase to compensate for the decline in tari¤ protection would have been 1:5% aswell. These results indicate that if Smoot Hawley had not been passed, the increase in the tari¤distortion would have been more than half of that which occurred under SH, because de‡ation
would have been responsible for a substantial increase in both the mean and dispersion of tari¤
rates.
micro. Elasiticities of intertemporal substitution in the range of 0:5 to 1 are typically obtained in studies using
household data on consumption (eg. Attanasio, Banks,and Tanner (2002)).
14
If we choose s = 1 and = 1, we obtain a small reduction in employment as a result of tari¤s. However, theconsumption equivalent is similar in this case.
15
It can be shown that the measures reported in Table 3 are independent of the parameters ; A; and K.

20

TABLE 4: NO SMOOT HAWLEY
1930A

1930B

1933

1)

30.8

33.1

38.4

Variance of Tari¤s

0.052

0.072

0.125

49.0

55.0

61.6

(qt );q0 )VA price: pV p(V 0(1;q
0)

-1.0

-1.0

-1.1

(qt );q0 )Cons price: PCp(V 0(1;q
0)

1.2

1.3

1.4

T F P ( 0 (qt ); q0 )

-1.2

-1.3

-1.5

0 (qt );q0 )Employment: L(L(1;q
0)

0.1

0.1

0.2

0 (qt );q0 )Consumption: C(C(1;q
0)

-1.2

-1.3

-1.4

1.2

1.3

1.5

Mean Tari¤ (Uniform Tari¤ Equivalent (1)

E);q0 )
Consumption Equivalent : CC(( 00(q(qtt);q0)

Notes: Parameter values same as benchmark, Table 3.
In order to test the sensitivity of these results to our assumptions regarding the elasticities
of substitution between domestic and imported goods, we also consider a case where we double
the elasticities tom =M= 7 andC= 5. The results for this exercise are reported inTable 5. TFP now declines by 4:9% relative to free trade with the pre-SH tari¤s with thehigher substitution elasticities, which is more than 4 times that in the benchmark case. A larger
elasticity of substitution leads to a substantially larger e¤ect on TFP because of the greater
substitution away from imported goods due to tari¤ protection. In addition to a larger e¤ect on
productivity, the higher elasticity also results in a substantially larger impact on employment,
which now rises by 1:4%. As a result of the increase in employment, the amount of consumption
required to reach the free trade level (5:6%) exceeds the TFP e¤ect (5:3%) in magnitude. The
subsequent SH tari¤s and de‡ation (1933) reduce TFP by an additional 0:4% relative to the free
trade level. Finally, we note that increasing the elasticity of substitution between importables
also has the e¤ect of increasing the uniform tari¤ equivalent of the tari¤ structure. The greater
substitution elasticities raise the distortion associated with variance in the tari¤ structure, andthus tends to raise the uniform tari¤ equivalent.

21

TABLE 5 –DOUBLE SUBSTITUTION ELASTICITIES
1930A

1930B

1933

56.5

62.5

68.8

-2.9

-2.7

-2.9

2.8

3.1

3.0

-4.9

-5.1

-5.3

1

1.4

1.5

1.6

1

-4.0

-5.1

-5.3

5.2

5.4

5.6

Uniform Tari¤ Equivalent (t ;q0 )VA price: ppVV((1;q0)

1t ;q0 )
Cons. price: PPCC((1;q0)

T F P ( t ; q0 )

1)

1

1

t ;q0 )
Employment: L(
L(1;q0 )t ;q0 )
Consumption: C(C(1;q0 )E

Consumption Equivalent : CC(( tt;q;q00))
Parameter values:

C = 5;m =M = 7; rest as in benchmark

FIGURE 5 –TFP EFFECTS, SENSITIVITY ANALYSIS
TFP
1.00

0.99

1930A

0.98

1933
0.97

1930B

0.96

0.95

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

σm

Note: Each line show the TFP e¤ects (relative to free trade of 1) as the elasticity of substitution
rises for each year of our panel.

22

These results suggest that the aggregate cost of tari¤ protection can be fairly sensitive to theassumptions made regarding

m and

C.

Figure 5 shows how the loss in TFP varies with thevalue of the substitution elasticities for each of the cross sections we analyze, with elasticities
( m;

M;

C ) evaluated at 1,

4/3, 5/3 and 2 times their benchmark values For each crosssection, the magnitude of the total loss from tari¤ protection relative to free trade is non-linear
in the substitution elasticity. Interestingly, however, the incremental loss moving from 1930A to1933 due to the SH tari¤s is in the 0:4

0:5% range for all of the elasticity values. Thus, theincremental impact of SH is quite robust to the elasticity assumption in this range.
TABLE 6 –DOUBLE ALL IMPORT SHARES
1930A

1930B

1933

Uniform Tari¤ Equivalent

47.4

55.7

67.7

t ;q0 )VA price: ppVV((1;q
0)

-2.6

-2.7

-3.3

t ;q0 )
Cons. price: PPCC((1;q
0)

2.2

2.6

2.6

T F P ( t ; q0 )

-2.5

-3.0

-3.6

t ;q0 )
Employment: L(
L(1;q0 )

0.1

0.2

0.5

t ;q0 )
Consumption: C(C(1;q0 )

-2.4

-2.8

-3.3

2.6

3.1

3.8

E

Consumption Equivalent : CC(( tt;q;q00))

Notes: Parameter values same as benchmark, Table 3.
As a …nal exercise, we consider the impact of a doubling of the US import share using thebenchmark elasticity assumptions. That imports were a small fraction of GDP is one factor in
explaining why the aggregate impact of tari¤ protection is relatively small in our benchmark
case. The raises the question of how large import shares must be in order to have signi…cante¤ects on aggregate productivity and welfare. Table 6 considers a counterfactual exercise of
doubling the US import share from its 1930 levels. This change has the e¤ect of doubling
the impact of tari¤s on the price of value added. The e¤ect of the pre SH tari¤s on TFP isapproximately double that in the benchmark case, since TFP now decreases by 2.5% from the
pre SH tari¤s. Doubling the import share also doubles the percentage increase in consumption
required to compensate for the e¤ect of the tari¤ structure relative to free trade. Employmente¤ects continue to be quite small in this case. Note that although the aggregate e¤ects are
increased substantially in this counterfactual, there is only a minor e¤ect on the uniform tari¤23

equivalent. This is because the uniform tari¤ equivalent captures the e¤ect of tari¤s on one
import category relative to another. Doubling the import volume increases the e¤ects on allimport categories proportionally, and thus has a minimal e¤ect on this aggregate measure.

5

Conclusions

We have constructed a panel of tari¤ lines to quantify the e¤ect of the Smoot Hawley tari¤legislation on the mean and dispersion of tari¤ rates. The panel shows that the mean e¤ectivetari¤ rate increased from 31% to 46% between 1930 and 1933, and that the variance of tari¤
rates at the tari¤ line level more than doubled over the same period. We also used this panel
to construct tari¤ wedges re‡ecting the increased price of imported materials for domestic production sectors. The mean of these wedges increased from 32% to 59%, and the variance morethan doubled. The role of dispersion on tari¤ rates was captured by the fact that the uniform
tari¤ rate equivalent exceeded the average tari¤ rate by 18% under the pre-SH tari¤s in 1930,
and this di¤erential increased to 24% by 1933. This result showed that the tari¤ structure wassubstantially more distorting than suggested by the average tari¤ rate, and the increased variance in tari¤ rates from SH raised the di¤erential between the uniform tari¤ equivalent and theaverage tari¤.
Although our tari¤ line analysis indicated the existence of substantial sectoral distortions,
our general equilibrium model indicated that the impact of these distortions at the aggregate
level was relatively modest in the benchmark parameterization. The pre-SH tari¤ protection
reduced TFP by 1:1% relative to free trade, and the SH legislation was responsible for a further
0:5% decline in TFP We also showed that if SH had not been passed, the presence of speci…ctari¤s in the existing tari¤ legislation would have reduced TFP by 0:3% between 1930 and 1933
due to declining world prices. This conclusion is consistent with previous …ndings of Crucini(1994) and Irwin (1998) that de‡ation was responsible for a signi…cant portion of the increasein e¤ective tari¤ rates that occurred following the passage of the SH legislation.
Two caveats should be kept in mind in interpreting our results on the aggregate e¤ects of
the SH tari¤s. First, the aggregate e¤ects could be larger if the true substitution elasticities arelarger than the ones used in our benchmark analysis. Our counterfactual exercise showed that adoubling of the elasticities of substitution led to a quadrupling of the e¤ect of pre-SH tari¤s on
TFP. In addition, larger elasticities resulted in more signi…cant e¤ects on labor markets. Notehowever, that the incremental e¤ect of the SH legislation and decline in world prices on TFP
from 1930-1933 was quite robust across the di¤erent elasticity assumptions. This suggests thevalue of investigating the tari¤ policies over the interwar era to better capture the aggregate
impacts of commercial policy during the Great Depression.
Second, we assume that tari¤s have no e¤ect on world prices. Such an assumption is appropriate when the country in question is a small country, or when retaliation by foreign countries24o¤sets any e¤ects of tari¤s on the terms of trade. The existence of a favorable terms of tradee¤ect for the tari¤ imposing country would reduce the magnitude of the loss in productivity, or
could even lead to a higher productivity level. However, our data did not suggest the presenceof signi…cant reductions in world prices as a result of the Smoot Hawley tari¤s.
Our analysis could also be extended to incorporate additional e¤ects of tari¤ protection. For
example, our analysis does not incorporate the e¤ects of tari¤ protection on capital accumulation.
Crucini and Kahn (1996) …nd that persistent tari¤ protection can reduce capital accumulation,
which would lead to a larger aggregate e¤ect of tari¤ protection. Finally, tari¤ protection could
lead to larger e¤ects on productivity if it leads …rms to increase markups. Such an outcome
could occur if …rms are imperfectly competitive and tari¤ protection makes …rm demand curves
less elastic, or if protection facilitates the formation of cartels. These represent areas for future
work.

25

References[1] Anderson, James and Peter Neary. 2005. Measuring the Restrictiveness of International
Trade Policy, MIT Press (Cambridge).
[2] Chetty, Raj, Adam Guren, Day Manoli and Andrea Weber, "Are Micro and Macro Labor
Elasticities Consistent? A Review of the Evidence on Intensive and Extensive Margins,"
American Economic Review Papers and Proceedings,[3] Crucini, Mario J. 1994. “Sources of Variation in Real Tari¤ Rates: The United States,
1900-1940. American Economic Review, 84(3), 732-743.
[4] Crucini, Mario J. and James Kahn. 1996. “Tari¤s and Aggregate Economic Activity:
Lessons From the Great Depression. Journal of Monetary Economics, 38(3), 427-467.
[5] Eaton, Jonathan and Samuel Kortum. 2002. "Technology, Geography, and Trade," Econometrica, 70 (5), 1741-79.
[6] Hsieh, Chiang-ti and Peter Klenow (2009), "Misallocation and Manufacturing TFP in India
and China," Quarterly Journal of Economics, 124 (4), 1403-48.
[7] Irwin, Douglas. 1998. "Changes in US Tari¤s: The Role of Import Prices and Commercial
Policy," American Economic Review, 88 (4), 1015-26.Irwin, Douglas. 1998a. "Changes in US
Tari¤s: The Role of Import Prices and Commercial Policy," American Economic Review,
88 (4), 1015-26.
[8] Irwin, Douglas. 1998b. "The Smoot Hawley Tari¤: A Quantitative Assessment," Review of
Economics and Statistics, 89, 326-34.
[9] Irwin, Douglas. 2011. Peddling Protectionism: Smoot Hawley and the Great Depression,
Princeton University Press (Princeton).
[10] Restuccia, Diego and Richard Rogerson (2008), "Policy Distortions and Aggregate Productivity with Heterogeneous Establishments," Review of Economic Dynamics, 11, 707-20.
[11] Leontief, Wassily W. 1941. The Structure of the American Economy. Oxford University
Press.
[12] Simonovska, and Michael Waugh. 2011. "The Elasticity of Trade: Evidence and Estimates,"
CESifo working paper series no. 3356.
[13] Taussig, F. W. 1931. The Tari¤ History of the United States, Putnam (New York).

26

6

Appendix A

The matching algorithm takes two arrays of text descriptions as inputs. The output is a matrixof scores in which the ijth element is a number between zero and 1 for the quality of a match
between row i from the …rst data set and row j from the second. A score of 1 means that the
text descriptions are identical and a score of zero means they have no characters in common.
Figure A.1 shows the number of matches as a function of the quality of the match. Beginningwith a minimum threshold of 0.8, the number of matches is 1,800 and fall to about 1,690 where
the match is for all intents and purposes ‘perfect.’
FIGURE A.1 –MATCHING ALGORITHM EXAMPLE, 1930

While the matching algorithm is an invaluable tool, it does not resolve the issue of eightscenarios involving line-item splitting, aggregation or reorganization across periods. For example,
our matching procedure does not rule out more than one 1930A line item being matched to thesame 1930B (or 1933) line item. We must account for this type of aggregation in the data.
To do this we collect the set all best matches which are connected to each other through one
or more line item aggregations. We then construct an aggregated line item series by creating
a weighted average of the individual line items where the 1930A import values are used asweights. After completing the construction of a balanced panel, the size of our cross-section
shrinks to 495 line items. This occurs for two reasons. First, aggregation naturally reduces thenumber of individual tari¤ lines and due to a large degree of re-organization between 1930A
and 1930B/1933; it is common for two or line items to be matched to the same line item in alater cross-section. Second, aggregation exacerbates missing data issues. Any set of line items
which is matched to any individual observation with missing data have to be discarded since theaggregation cannot be performed.

27

TABLE A1 –MOMENTS OF SOURCE DATA AND BALANCED PANEL
Pre-Smoot-Hawley
Post-Smoot-Hawley
1933
SourcePanel
SourcePanel
SourcePanel
Value imported
Mean
359
723
282
784
276
918
Median
6
47
6
22
5
29
Std. dev.
3,292
3,404
3,066
5,426
2,926
6,578
Quantity imported
MeanMedianStd. dev.

3,842
6
51,787

9,109
69
82,8353,352
747,2309,720
47
99,54575,885

10,233
67
84,489Price (Unit Value)
MeanMedianStd. dev.

23.85
0.89
367.48

2.05
0.44
9.84

40.25
0.81
833.04

1.98
0.40
10.34

19.17
0.50
323.62

1.55
0.31
8.87

28

5,437

9