Tari⁄s versus Non-Tari⁄ Barriers - World...

Tari¤s versus Non-Tari¤ Barriers

Hiau Looi Kee and Cristina Neagu

Development Research Group � Trade, The World Bank

Oct 2011Work in Progress and Preliminary

Kee and Neagu (World Bank) Tari¤s versus Non-Tari¤ Barriers 10/11 1 / 22

Motivations

With the dramatic decline in tari¤s through the successive rounds ofmultilateral negotiation and unilateral liberalizations, the main tradepolicy tools could be in the form of non-tari¤ barriers (NTBs)

Examples on commonly used NTBs

Origin of materials and partsImport licence feesCustoms inspection feesTesting requirementInspection requirementDirect consignmentrequirementRequirement to pass throughspeci�ed portService chargesLabelling requirementsCerti�cation requirementProcessing historySystems Approach

Temporary geographicprohibition for SPConformity assessmentsrelated to SPSTraceability requirementCerti�cation required by theexportingStorage and transportsconditionsMicrobiological criteria on the�nal pQuarantine requirementTraceability informationrequirements

Million Dollar Question

Are tari¤s and NTBs substitutes or complements?

Scant and mixed empirical evidence:

Complements �Dean, Ludema, Signoret, Feinberg and Ferrantino(2009) based on cross country evidence of NTBsSubstitutes �Kee, Nicita and Olarreaga (2009); Bown and Crowley(2009) based on time series evidence on the use of antidumping dutiesin India

Complements �Dean, Ludema, Signoret, Feinberg and Ferrantino(2009) based on cross country evidence of NTBs

Substitutes �Kee, Nicita and Olarreaga (2009); Bown and Crowley(2009) based on time series evidence on the use of antidumping dutiesin India

What we plan to do

Exploit a newly collected dataset of NTBs by the WB on a group ofdeveloping countries

Estimate bilateral AVEs at detailed product level as rigorously aspossible

Study the factors that in�uence the level of AVEs such as countrysizes, stage of development, and bilateral distance

Relate the estimated AVEs to bilateral tari¤s

Allow the degree of substitutability or complementarity betweenNTBs and tari¤s to be in�uenced by the characteristics of thebilateral country pair

What we plan to do

TheoriesOptimal level of protection

Countries may use trade policies to in�uence their terms of trade andtransfer rents from their trading partners

Level of protection depends on tari¤s and the ad valorem equivalent(AVE) of NTBs

tnij + AVEnij = T̄nij

Lowering tari¤s due to multilateral negotiation or unilateralliberalizations implies that NTBs will be increased to keep protectionat its optimal level ==> tari¤s and NTBs could be substitutes

TheoriesProtection for sale

Trade policies can be in�uenced by interests parties through lobbiesand governments care about social welfare as well as campaigncontributions

Level of protection depends on tari¤s and NTBs

tnij + AVEnij = Tnij

which increases with lobby contributions ==> tari¤s and NTBscould be complements

TheoriesProtection for sale

Trade policies can be in�uenced by interests parties through lobbiesand governments care about social welfare as well as campaigncontributions

Level of protection depends on tari¤s and NTBs

tnij + AVEnij = Tnij

which increases with lobby contributions ==> tari¤s and NTBscould be complements

Other factors that may in�uence government�s policychoices

Tari¤s are more transparent while NTBs are harder to implements,subject to corruptions

Some NTBs such as rules of origin requirement may a¤ect multipleindustries while tari¤s are more targeted

Tari¤s are under more scrutinized while NTBs are harder to monitored

Unlike NTBs, tari¤s generate revenues which could be important forsmall developing countries

Data on NTBs

Up to now the main data source is from TRAIN, which has not beenupdated since 2006

In 2010, World Bank collected detailed NTB data from about 20developing countries

Table 1 presents the share of products of each country that aresubjected NTBs and positive tari¤s

At sample mean, 41% of products face NTBs while 68% of productsface positive tari¤s

No clear correlation between the shares of products a¤ected by NTBsvs the shares of products a¤ected by positive tari¤s

Data on NTBs

Table: Percentage of Products A¤ected by NTBs and Positive Tari¤s

Code NTB Tari¤s Code NTB Tari¤s

ARG 87.2 80.8 NAM 49.8 40.7BOL 6.1 85.5 PER 6.4 51.8COL 7.1 88.6 PHL 20.3 91.4ECU 43.3 73.8 PRY 25.1 88.1EGY 91.7 77.2 SYR 86.9 86.4IDN 42.0 73.9 TUN 22.2 68.5JPN 37.5 28.2 TZA 5.5 59.1KEN 83.1 56.0 UGA 94.0 59.1LBN 12.4 55.5 URY 6.8 80.0MEX 55.4 69.4 VEN 43.4 89.4MUS 41.6 15.8 MEAN 41.3 67.6Notes: Products are de�ned by HS6-exporter pair;

There are all together 1,234,555 products.

Figure: Share of products a¤ected by NTBs vs Tari¤s

MUSJPN

PERLBN

ECUIDN

.6 .4 .2 0 .2e( postariffshare | X )

coef = .04772611, se = .34338015, t = .14

Estimating AVE of NTBs

Modify the framework of Kee, Nicita and Olarreaga (2009) toestimate bilateral AVEs

Gravity model at product level: Country i 0s import of product n fromcountry j (Mnij ) , depends on GDP of the two countries (Yi ,Yj ),distance in kilometers (Dij ), border (Bij ), tari¤s (tnij ) and thepresence of NTB (NTBni )

lnMnij = βn + β1 lnYi + β2 lnYj + β3 lnDij + β4Bij +

β5 ln (1+ tnij ) + βnijNTBni

While NTBs are importer-product speci�c, the e¤ect of NTBs onbilateral trade may depend on the characteristics of the importer andthe exporter, proxied by the total imports of product n in country ifrom the rest of the world (MniROW ) and the total exports of productn from country j to the rest of the world (EnROWj )

βnij = � exp (γn + γ1 lnMniROW + γ2 lnEnROWj )

Modify the framework of Kee, Nicita and Olarreaga (2009) toestimate bilateral AVEsGravity model at product level: Country i 0s import of product n fromcountry j (Mnij ) , depends on GDP of the two countries (Yi ,Yj ),distance in kilometers (Dij ), border (Bij ), tari¤s (tnij ) and thepresence of NTB (NTBni )

By construction βnij varies by product, importer and exporter

Negativity constraint on βnij so that NTB always decrease trade

Negativity constraint on β5 when necessary

Estimated with non-linear LS

The resulting AVE estimate is

AVEnij =

(exp(βnij)�1

εnij, if NTB = 1

0, if NTB = 0,

where εnij is the country i 0s import demand elasticity of product nfrom country j (from Kee, Neagu and Nicita, ReStat, forthcoming)

If Mnij = 0, then use εni from Kee, Nicita and Olarreaga (ReStat,2008)

AVEnij =

(exp(βnij)�1

εnij, if NTB = 1

0, if NTB = 0,

AVEnij =

(exp(βnij)�1

εnij, if NTB = 1

0, if NTB = 0,

AVEnij =

(exp(βnij)�1

εnij, if NTB = 1

0, if NTB = 0,

AVEnij =

(exp(βnij)�1

εnij, if NTB = 1

0, if NTB = 0,

AVEnij =

(exp(βnij)�1

εnij, if NTB = 1

0, if NTB = 0,

Caveats

Zero�s in trade:

we add 1 to all the trade variables before taking logs ==> not idealtried Poisson estimations but cannot introduce negativity constraints(nearly half of the estimated βnij�s are positive)tried non-linear LS in level but very di¢ cult to reach convergence

Mnij = Yβ1i Y

β2j D

β3ij exp

�β4Bij

� �1+ tnij

�β5 exp�

βnijNTBni�

Endogeneity of NTB:

not as bad as it seems since the dependent variables and regressionerrors vary by product-importer-exporter, while NTBs only vary byproduct-importercould instrument for NTBs using a Heckman�s selection equation

Caveats

Zero�s in trade:

we add 1 to all the trade variables before taking logs ==> not ideal

tried Poisson estimations but cannot introduce negativity constraints(nearly half of the estimated βnij�s are positive)tried non-linear LS in level but very di¢ cult to reach convergence

Mnij = Yβ1i Y

β2j D

β3ij exp

�β4Bij

� �1+ tnij

�β5 exp�

βnijNTBni�

Endogeneity of NTB:

Caveats

Zero�s in trade:

we add 1 to all the trade variables before taking logs ==> not idealtried Poisson estimations but cannot introduce negativity constraints(nearly half of the estimated βnij�s are positive)

tried non-linear LS in level but very di¢ cult to reach convergence

Mnij = Yβ1i Y

β2j D

β3ij exp

�β4Bij

� �1+ tnij

�β5 exp�

βnijNTBni�

Endogeneity of NTB:

Caveats

Zero�s in trade:

Mnij = Yβ1i Y

β2j D

β3ij exp

�β4Bij

� �1+ tnij

�β5 exp�

βnijNTBni�

Endogeneity of NTB:

Caveats

Zero�s in trade:

Mnij = Yβ1i Y

β2j D

β3ij exp

�β4Bij

� �1+ tnij

�β5 exp�

βnijNTBni�

Endogeneity of NTB:

Caveats

Zero�s in trade:

Mnij = Yβ1i Y

β2j D

β3ij exp

�β4Bij

� �1+ tnij

�β5 exp�

βnijNTBni�

Endogeneity of NTB:

not as bad as it seems since the dependent variables and regressionerrors vary by product-importer-exporter, while NTBs only vary byproduct-importer

could instrument for NTBs using a Heckman�s selection equation

Caveats

Zero�s in trade:

Mnij = Yβ1i Y

β2j D

β3ij exp

�β4Bij

� �1+ tnij

�β5 exp�

βnijNTBni�

Endogeneity of NTB:

AVE Estimates

Nearly 26 millions AVEs of NTBs are estimated (21 importers � 245exporters � 5039 HS 6)

The average AVE and tari¤ is 11% and 10%

The average AVE when AVE is positive is 28%; it is 15% for tari¤

Only about 870 thousands observations have positive trade

Among the observations with positive trade, the average AVE andtari¤ is 6.5% and 9.4%

If only focus on observations with NTBs, the average AVE is 15%;the average tari¤ is 14% among observation with positive tari¤s

AVE Estimates

AVE Estimates Assessment

Despite the large number of AVE being estimated, the results lookreasonable

AVEs of NTBs look comparable with tari¤s in terms of size on average

When NTBs are binding, AVE is almost twice as large as tari¤

Both AVE and tari¤ are lower among trading partners

AVE is lower than tari¤ among trading partners

Figure: Distribtion of AVEs for Traded Products with NTBs

0 .2 .4 .6 .8 1ave_core_nl

kernel = epanechnikov, bandwidth = 0.0072

Kernel density estimate

Table: Average Estimated AVEs of NTBs and Tari¤s

Code AVEs of NTBs Tari¤sAll > 0 Traded All > 0 Traded

ARG 24.9 30.3 12 12.0 13.8 11.1BOL 1.6 25.6 0.5 8.0 8.7 6.2COL 2.0 28.2 0.6 11.9 12.5 10.7ECU 5.9 14.1 3.1 11.0 14.0 9.7EGY 23.0 26.8 12.8 14.5 17.5 12.7IDN 11.2 27.4 3.3 6.7 8.5 5.6JPN 18.7 49.4 6.9 4.0 13.4 4KEN 34.4 44.3 13 11.8 19.6 12.1LBN 2.0 17.0 1.6 6.4 10.7 8.3MEX 16.5 31.1 5.6 10.5 14.1 6.1MUS 5.3 13.1 3.5 3.4 20.0 5.7

Table: Average Estimated AVEs of NTBs and Tari¤s

Code AVEs of NTBs Tari¤sAll > 0 Traded All > 0 Traded

NAM 8.1 17.8 7.6 7.4 17.0 6.3PER 2.3 34.3 1.1 6.0 10.7 6.7PHL 4.4 25.5 2 6.2 6.4 6PRY 14.9 61.6 2.1 11.4 12.0 9.4SYR 19.8 22.7 17.8 13.2 14.3 6.4TUN 6.2 28.3 2.6 21.5 27.0 21.9TZA 1.2 21.9 0.4 12.5 19.8 13.1UGA 16.1 18.2 34.6 12.0 18.9 12.2URY 2.6 36.7 0.6 10.3 12.0 9.6VEN 9.2 22.6 4.6 12.8 13.3 12.3

MEAN 11.0 28.4 6.5 10.2 14.5 9.4

Figure: Partial Correlations by Importers at Sample Mean

IDNPHL

JPNNAM

SYRMEX

EGYURYECUPRY

VENTUN

.05 0 .05 .1e( tariff | X )

coef = .07952134, se = .54985548, t = .14

URYNAM

EGYMEX

IDNCOL

3 2 1 0 1e( lGDPi | X )

coef = .01474484, se = .01579062, t = .93

PHLBOL

EGYSYR

MEXECU

VENNAMJPN

TUNLBN

2 1 0 1 2e( lGDPpci | X )

coef = .03308281, se = .02140866, t = 1.55

MEXLBNIDN

KENJPN

TUNPHL

EGYNAM

ECUCOLBOL

VENPRY

SYR PER

.4 .2 0 .2 .4e( lGDPj | X )

coef = .00840381, se = .10611599, t = .08

VENPRY

MEXEGYJPN

PHLTUN

.2 .1 0 .1 .2e( lGDPpcj | X )

coef = .19126077, se = .22355714, t = .86

LBNTUN

NAMPERJPN

KENMUS

COLPRY

MEXURY

.6 .4 .2 0 .2 .4e( lkm1 | X )

coef = .0553735, se = .06877168, t = .81

Figure: Dependent variable: ln�1+ AVEnij

�(1) (2) (3) (4) (5) (6) (7) (8)

Tariffs 0.006*** 0.020*** 0.024*** 0.181*** 0.050 0.039*** 0.101 0.060(0.002) (0.002) (0.002) (0.030) (0.042) (0.004) (0.074) (0.085)

Tariff*GDPi 0.004*** 0.016*** 0.003* 0.006***(0.001) (0.002) (0.002) (0.002)

Tariff*GDPj 0.014*** 0.003*** 0.007*** 0.006**(0.001) (0.001) (0.002) (0.003)

Tariff*GDPPCi 0.014*** 0.060*** 0.009*** 0.004(0.003) (0.003) (0.003) (0.004)

Tariff*GDPPCj 0.000 0.002* 0.002 0.005*(0.000) (0.001) (0.003) (0.003)

Tariff*Distanceij 0.005*** 0.001 0.001 0.000(0.001) (0.001) (0.005) (0.004)

GDPi 0.008***(0.000)

GDPj 0.002***(0.000)

GDPPCi 0.012***(0.000)

GDPPCj 0.000***(0.000)

Distanceij 0.003***(0.000)

Elasticity 0.000*** 0.000*** 0.000*** 0.000***(0.000) (0.000) (0.000) (0.000)

Product FE Yes Yes No Yes No NoImporter FE Yes No No No No NoExporter FE Yes No No No No NoImporterProduct FE No No Yes Yes Yes No NoImporterExporterFE No No No No No Yes YesTariffs at sample mean 0.025*** 0.039***

(0.002) (0.003)Observations 850640 826563 850640 826563 826563 850640 826563 826563

Preliminary Conclusions

Tari¤s and NTBs could be substitutes within importer-HS6 products,comparing across exporters

Preferential tari¤s often come with rules of origin requirements

Tari¤s and NTBs could be complements within importer-exporterpair, comparing across products

Products that have low tari¤ barriers often have lower NTBs

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