Industrial Policy: Why, What and How?

Ann Harrison

University of California, Berkeley and NBER September 2011

What do we mean by industrial policy?

….Growth was not a passive, trickle-down strategy for helping

the poor. It was an active, pull-up strategy instead. It required a government that would energetically take steps to accelerate growth, through a variety of policies including building infrastructure such as roads and ports and attracting foreign funds….

Jagdish Bhagwati, In Defense of Globalization (2004)

A Broad Vision of Industrial Policy

• Working definition: any intervention which

shifts incentives away from policy neutrality • IP spans a range of policies

– Tariffs – Tax breaks – Trade promotion – Targeted infrastructure projects (IP as sequential

decision making) – Promotion of clusters, industrial zones, EPZs

Outline

I. Why industrial policy: the rationale II. But does it work? A tour of the

literature III. Two critical issues:

– What you promote – How you promote

• Harrison and Rodriguez Clare (2010) • Cai, Harrison, and Lin (2011) • Aghion, Dewatripont, Du, Harrison and

Legros (2011)

I. Why Industrial Policy?

Why this resurgence of interest in industrial policy?

• All 13 of the successful cases identified by the Growth Commission Report used industrial policy.

• All governments “doomed to choose” • New openness to thinking about government intervention

post-2008-2009 crisis. Why? – Failed orthodox laissez faire policies associated with crisis – Perception (even at World Bank) that just relying on

investment climate not enough – Perceived success of (pro-industrial policy) China and

generally more successful performance of developing countries throughout the crisis. In US, the Central Intelligence Agency views China’s IP as a new secret weapon.

The rationale for industrial policy usually comes from a market failure, such as:

• Industry-level externalities, which mean that firms produce too

little because they do not incorporate the gains to others when they increase their own output

• Complementarity between goods production and key inputs such as infrastructure, which require public provision

• Agglomeration economies, stemming from knowledge spillovers or labor market pooling imply firms could lower costs of production if they could all locate close together

• Imperfect competition. Aghion, Dewatripont, Du, Harrison, Legros show that with two dominant firms and competitive fringe, laissez faire leads to less competition, innovation and lower welfare

• Imperfect capital markets, which make it difficult to find financing for new projects (ex: SMEs lack collateral for loans)

Implication: No government action means too little growth, innovation, or exploitation of agglomeration economies

II. But Does it Work? A Tour of the Literature

Skeptics – Krueger and Tuncer (1982)

• If IP worked, more supported sectors should grow faster. • Since they don’t in Turkey, IP involved rent-seeking and

didn’t work • Reply by Harrison (1984): in fact, promoted sectors grew

faster • Reply by Rodrik: shouldn’t expect higher growth

– Beason and Weinstein (1996) • Japan targeted wrong sectors • Protected and supported sectors did not grow faster

– Howard Pack and K. Saggi (2006) • Conclude IP doesn’t work (India and software industry)

– Josh Lerner (2009)

Optimists: What and How you promote matters: – Clemens and Williamson (2001): Target

emerging sectors – Nunn and Trefler (2006): Target skill-

intensive sectors – Rodrik (2008) suggests under-valuing the

exchange rate to promote tradeables – Easterly et al (2009): manufactured exports – Alfaro and Charlton (2010): FDI promotion,

which targets high-tech sectors, leads to higher quality FDI and growth

III. Digging Deeper: What to promote and How

Should successful IP promote emerging, not declining sectors ?

USA

Bailing out sunset industries Promoting emerging sectors

China

Insights from 3 research papers on what and how

• Harrison and Rodriguez-Clare (2010) survey of industrial policy in Handbook of Development Economics

• Cai, Harrison, and Lin (2011) on patterns of policy interventions and growth across Chinese cities

• Aghion, Dewatripont, Du, Harrison, and Legros (2011) on Industrial Policy and Competition

Harrison and Rodriguez Clare (2010) in Handbook of Development Economics promote “soft” IP

“Hard” industrial Policy: – Tariffs – Subsidies to specific

sectors – Tax breaks for foreign

investors – Domestic content

requirements

Soft” Industrial Policy: – Special Economic

Zones offering lower cost infrastructure

– Roads and ports designed to increase trade

– Special Credit for exporters (Trade Credit)

– Promoting clusters in order to export

? √

Specific Suggestions for “Soft” IP (1)

• Regulations to enforce higher quality standards • Public investment in specific infrastructure projects

when there are large investment complementarities • Attracting FDI through provision of infrastructure • Scholarships for studies abroad in areas important

for diversifying clusters but with thin markets • Technical assistance, prizes, grants for projects

proposed by organized producers and performed by local research centers

Specific Suggestions for “Soft” IP (2)

• Don’t expect governments to identify coordination failures, but invite sector and cluster organizations to come forward

• If such organizations are weak, provide support to sectors that want to initiate or improve their organizations

• In general, avoid “price interventions” to reallocate resources but use existing clusters to identify effective interventions.

• Public-private collaboration is crucial

Cai, Harrison and Lin (2011)

• Define a series of correlations within China to identify what sectors are targeted by local governments.

• Why China? (data, governance, city variation) • Building on Nunn and Trefler (2006), CHL focus on

the correlation between tariffs or tax holidays and industrial characteristics

• Focus on four types of sectors: Labor intensive (L/K): total workforce/fixed assets for production Export intensive (EXP/SALES): export procurement/industrial sales Skill intensive (S/UNSK): #skilled workers /#unskilled workers, skilled

workers are those with at least high school education R&D intensive: #high-level technicians and engineers/total workforce

Measures of Patterns of Interventions (Does “what” you promote matter?)

• Patterns of tariff policies are measured by:

• For example, the first correlation, which is between the industry-city level of initial period labor intensity and current period tariffs for sector j in city r, measures whether tariff protection is biased towards labor intensive sectors in city r in year t.

• Explore alternatively impact of tariffs and tax holidays

0 0( , / )rt jt jr jrCorr Tariff L KΩ =

0 0( , / )rt jt jr jrCorr Tariff EXP SALESω =

0 0( , / )rt jt jr jrCorr Tariff S UNSKρ =

0( , )rt jt jrCorr Tariff RDIntensityυ =

Estimation Strategy • Estimate the effect of patterns of policies on

firm performance. • Measures of performance: Total factor productivity estimated using four methods:

AW et al 2001 (AW), OLS, OLS with fixed effects, and Olley & Pakes 1996 (OP).

• Alternative measures of performance: Levels and growth of firm productivity Growth of output and exports Industry-city aggregate productivity growth “Between” measure of aggregate TFP: measures

movement into new sectors and contribution to TFP

Data • Chinese Industrial firms from NBS: annual

survey of all enterprises with more than 5 million RMB sales

• Annual data for 1998 through 2007 • Information on outputs and inputs, ownership • Tax incentives based on deviations from

statutory taxes, based on taxes paid/profits • Tariff dataset from the World Integrated

Trading Solution (WITS) • Firm-specific reporting on subsidies

Summary Statistics: What sectors are promoted in China?

Year Correlation Tariff, L/K

Correlation Tariff,

Exports

Correlation Tariff,

Skill/Unskill

Correlation Tariff, RD intensity

Correlation Tax, L/K

CorrelationTax,

Exports

Correlation Tax,

Skill/Unskl

Correlation Tax, RD intensity

1998 0.0233 0.0476 -0.0288 -0.1521 -0.0549 -0.1277 0.0395 0.0845

1999 0.0133 0.0197 -0.0123 -0.1502 -0.0418 -0.1077 0.0494 0.1061

2000 0.0050 -0.0049 -0.0045 -0.1464 -0.0489 -0.0857 0.0375 0.0794

2001 0.0342 0.0322 -0.0567 -0.1733 -0.0360 -0.0783 0.0368 0.0660

2002 0.0375 0.0313 -0.0528 -0.1754 -0.0553 -0.1332 0.0479 0.0934

2003 0.0314 0.0263 -0.0513 -0.1596 -0.0301 -0.1257 0.0242 0.0972

2004 0.0262 0.0134 -0.0379 -0.1342 -0.0405 -0.1345 -0.0003 0.1091

2005 0.0699 0.0511 -0.0523 -0.1186 -0.0290 -0.0998 0.0031 0.0919

2006 0.0449 0.0266 -0.0518 -0.1272 -0.0273 -0.0949 -0.0248 0.0718

2007 0.0306 0.0185 -0.0592 -0.1341 -0.0219 -0.0747 -0.0012 0.0859

Total 0.0345 0.0264 -0.0444 -0.1428 -0.0357 -0.1043 0.0138 0.0886

Notes: All endowments are measured by industry-city level beginning of period values (1998 for labor and export intensity, 2004 for skill intensity and RD intensity). Labor intensity is defined as the ratio of total workforce to fixed assets for production; export intensity equals export procurement d ivided by industrial sales; the ratio between skilled workers (educations equivalent to or higher than senior high school) and unskilled workers is defined as skill intensity; RD intensity is defined as the share of high level technicians and engineers in total number of employees.

Effects of Patterns of Tariffs on

Industry-City Aggregate Productivity VARIABLES Industry-City Level Aggregate lnTFP

AW OP Panel A. Effect of tariff policies biased towards labor-intensive sectors

lnTariff -0.114*** -0.111*** (0.0404) (0.0402)

Correlation(Tariff, L/K) 0.0170** 0.008 (0.00760) (0.00798)

lnTariff_input -0.281** -0.261** (0.112) (0.115)

Panel B. Effect of export-oriented biased tariff policies lnTariff -0.114*** -0.110***

(0.0413) (0.0412) Correlation (Tariff, Export/Sales) 0.0742*** 0.0531***

(0.0102) (0.0111) lnTariff_input -0.274** -0.263** (0.112) (0.115)

Panel C. Effect of skill- biased tariff policies lnTariff -0.113*** -0.112***

(0.0402) (0.0403) Correlation(Tariff, Skilled/Unskilled) -0.0360*** -0.0500***

(0.00850) (0.00782) lnTariff_input -0.275** -0.255** (0.111) (0.114)

Panel D. Effect of tariff policies targeting on R&D intensive sectors lnTariff -0.113*** -0.112***

(0.0402) (0.0403) Correlation(Tariff, RD intensity) -0.0203** -0.0524***

(0.00885) (0.0102) lnTariff_input -0.275** -0.256**

(0.111) (0.114) Observations 110,407 116,261 Industry Fixed Effects YES YES Region Dummies YES YES Year Dummies YES YES

Effects of Patterns of Tax Breaks on Industry-City Aggregate Productivity

VARIABLES Industry-City Level Aggregate lnTFP AW OP

Panel A. Effect of tax policies biased towards labor-intensive sectors lnTax -0.0287*** -0.00769**

(0.00305) (0.00325) Correlation(Tax, L/K) -0.0219*** -0.0439*** (0.00724) (0.00697)

Panel B. Effect of export-oriented biased tax policies lnTax -0.0296*** -0.00807**

(0.00306) (0.00321) Correlation (Tax, Export/Sales) -0.0158** -0.0639***

(0.00781) (0.00799) Panel C. Effect of skill- biased tax policies

lnTax -0.0287*** -0.00799** (0.00299) (0.00336)

Correlation(Tax, Skilled/Unskilled) 0.0253*** 0.00980 (0.00792) (0.00760)

Panel D. Effect of tax policies targeting on R&D intensive sectors lnTax -0.0285*** -0.00770**

(0.00299) (0.00333) Correlation(Tax, RD intensity) 0.0221*** 0.0244*** (0.00596) (0.00622) Observations 104,209 108,895 Industry Fixed Effects YES YES Region Dummies YES YES Year Dummies YES YES

Moving into higher productivity sectors: what matters?

• Can decompose Industry-city level growth into a “within” component and a “between” component which reflects structural change.

• Rodrik (2011) and McMillan and Rodrik (2010) show much of difference in Asian versus other regions’ growth is due to the between component

• Across Chinese cities, biggest determinant of between component of productivity growth is not driven by policies but by foreign investment, which encourages firms to move into high productivity sectors

Lessons from Cai, Harrison, and Lin • Net impact of tariffs negative because while

interventions skewed towards sectors where China has a comparative advantage helped (measured by higher export intensity or lower skill-intensity), the targeting was not strong enough & independent effect of tariffs<0

• Strong evidence that tax holidays led to higher growth when targeted at labor-intensive, export-oriented, and less R&D intensive sectors in China.

• Because targeting was stronger using tax holidays, and effect uniformly positive, net impact of this intervention has been positive on firm productivity growth

• Benefits highest when instrument correlated with initial exports and tax breaks used instead of tariffs

• Biggest determinant of moving into new (higher productivity) sectors was FDI

Aghion, Dewatripont, Du, Harrison, Legros: How you intervene just as important

• Over time, and particularly since the 1980s, economists have come to dislike industrial policy on two grounds: – It focuses on big incumbents (“national

champions”) – Governments are not great at “picking winners”

• Current dominant view is that industrial policy and competition policy are always contradictory

• Aghion, Dewatripont, Du, Harrison, and Legros (2011) take issue with this view. For today, we skip the theory and move straight to empirics.

The idea: combining Industrial Policy and Competition

• Why sectoral policy may complement, rather than destroy, competition: – Competition weeds out bad projects, thus reduces the

danger of picking the wrong winner – Sectoral focus preserves competition among firms that

would otherwise differentiate horizontally

• In particular, the more intense product market competition within sectors and the less concentrated are government subsidies within a sector, the more innovation-enhancing sectoral focus should be

TFP Estimation: Testing for the Impact of Interventions in China in conjunction with Competition Z=Vector of firm-level controls, including state and foreign ownership S=Vector of sector-level controls, including input and output tariffs, sectoral foreign

shares. All specifications allow for firm fixed effects and time effects. Three Approaches: OLS, OLS with fixed effects, Olley-Pakes approach to measuring TFP

in first stage

Critical question: Are productivity gains from subsidies higher with competition? If so, coefficient B5 > 0

ijttijt

jtijtjtijtijt

COMPSUBSIDYCOMPSUBSIDYSZTFP

εααβ

ββββα

++++

++++=

*

ln

5

4321

Definition of Key Variables • Subsidy: for a firm, this is the subsidy received by a firm as a share of industrial

sales. Subsidy is our measure of “targeting” • COMP: sector-level measure of competition. A value of 1 indicates perfect

competition while values below 1 suggest some degree of market power. – To calculate industry-level lerner index, we first aggregate operating

profits, capital cost, and sales at the industry-level. Lerner index = (operating profits – capital costs)/sales.

– COMP = 1-Lerner Index • InvSubsidyHerf: measures sectoral dispersion of subsidies. We construct a

Herfindahl index using the share of subsidies a firm obtains to the total subsidies awarded to one industry. InvSubsidyHerf is 1/Herf_subsidy, where

2

__ ∑∈

=

jijt

ijtjt subsidySum

SubsidysubsidyHerf

Results: Dependent Variable is log of Total Factor Productivity (TFP) calculated using Olley-Pakes

Table 1 (1) (2) (3) (4) (5) (6) VARIABLES lnTFP (based on Olley-Pakes regression) Stateshare -0.00150 -0.00144 -0.00159 -0.00152 -0.00185 -0.00179

(0.00337) (0.00331) (0.00337) (0.00331) (0.00329) (0.00326) Horizontal 0.322*** 0.335*** 0.323*** 0.335*** 0.178* 0.198*

(0.0756) (0.0793) (0.0755) (0.0793) (0.0947) (0.101) Ratio_subsidy -0.185*** -0.188*** -8.201*** -6.752*** -8.067*** -6.798***

(0.0279) (0.0276) (1.769) (1.404) (1.748) (1.392) Competition_lerner 0.512 0.482 0.427

(0.533) (0.535) (0.535) Interaction_lerner 8.212*** 6.724*** 8.074*** 6.773***

(1.818) (1.441) (1.796) (1.429) Backward 0.779*** 0.762***

(0.278) (0.273) Forward 0.112 0.0995

(0.0991) (0.0990) LnTariff -0.0382** -0.0348** -0.0380** -0.0348** -0.0335 -0.0321

(0.0162) (0.0166) (0.0162) (0.0166) (0.0214) (0.0213) LnbwTariff -0.00764 -0.00672 -0.00770 -0.00682 -0.0223 -0.0213

(0.0174) (0.0172) (0.0174) (0.0172) (0.0194) (0.0189) LnfwTariff -0.00373 -0.00422 -0.00379 -0.00424 -0.00418 -0.00406

(0.00260) (0.00278) (0.00260) (0.00278) (0.00544) (0.00537) Constant 1.726*** 1.213** 1.725*** 1.242** 1.699*** 1.274**

(0.0315) (0.534) (0.0314) (0.535) (0.0412) (0.533) Observations 1,072,034 1,072,034 1,072,034 1,072,034 1,072,034 1,072,034 R-squared 0.172 0.172 0.172 0.173 0.173 0.173 Notes: Robust clustered standard errors are shown in the parentheses. Firm fixed effect and time effect are included in each specification. To exclude foreign-invested and state-owned firms, we estimate the results based on the sample of domestic non-state-owned firms.

Results by degree of concentration • In Table 2, we keep the same specification as in Table 1. However, we divide the

sample into four groups based on the percentiles of “Herf_subsidy”. Table 2 compares the results from the second quartile and the fourth quartile (the fourth quartile refers to the most concentrated industries).

Table 2 (1) (2) (3) (4) (5) (6)

Dependent: lnTFP (based on Olley and Pakes regression) The second quartile: more dispersion in subsidies

Ratio_subsidy -0.197* -0.193** -16.25*** -12.00*** -16.49*** -11.96*** (0.0962) (0.0937) (4.884) (4.037) (4.813) (4.031)

Competition_lerner 1.818 1.763 2.001 (1.286) (1.285) (1.308)

Interaction_lerner 16.63*** 12.24*** 16.88*** 12.19*** (5.096) (4.186) (5.023) (4.178)

The fourth quartile: least dispersion in subsidies (most concentrated) ratio_subsidy -0.227*** -0.228*** -9.352** -6.169** -9.148** -6.338**

(0.0625) (0.0627) (3.615) (2.854) (3.710) (2.860) competition_lerner 1.179 1.153 1.029

(0.981) (0.982) (1.042) interaction_lerner 9.320** 6.069** 9.107** 6.238**

(3.628) (2.883) (3.727) (2.888)

Horizontal Yes Yes Yes Yes Yes Yes Forward & Backward No No No No Yes Yes Tariffs Yes Yes Yes Yes Yes Yes

Direct Impact of More Widespread Dispersion of Subsidies is Positive In Table 3, we keep everything the same as Table 1 but we replaced interaction term with the InvSubsidyHerf, which is a sector-level variable. A one standard deviation increase leads to an increase in TFP of 1.4 %.

Table 3 (1) (2) (3) (4) (5) (6)

lnTFP (based on Olley and Pakes regression) Stateshare -0.00150 -0.00106 -0.00144 -0.00106 -0.00171 -0.00133

(0.00337) (0.00322) (0.00331) (0.00322) (0.00326) (0.00317) Horizontal 0.322*** 0.343*** 0.335*** 0.343*** 0.198* 0.212**

(0.0756) (0.0785) (0.0793) (0.0785) (0.101) (0.0975) Ratio_subsidy -0.185*** -0.200*** -0.188*** -0.200*** -0.187*** -0.199***

(0.0279) (0.0320) (0.0276) (0.0320) (0.0277) (0.0318) Competition_lerner 0.448 0.512 0.448 0.457 0.399

(0.542) (0.533) (0.542) (0.534) (0.543) InvSubsidyHerf 0.000177*** 0.000177*** 0.000170**

(6.24e-05) (6.24e-05) (6.49e-05) Backward 0.762*** 0.738***

(0.273) (0.274) Forward 0.0992 0.0931

(0.0990) (0.101) LnTariff -0.0382** -0.0360** -0.0348** -0.0360** -0.0322 -0.0338*

(0.0162) (0.0155) (0.0166) (0.0155) (0.0213) (0.0202) LnbwTariff -0.00764 -0.00578 -0.00672 -0.00578 -0.0212 -0.0199

(0.0174) (0.0166) (0.0172) (0.0166) (0.0189) (0.0186) LnfwTariff -0.00373 -0.00556** -0.00422 -0.00556** -0.00402 -0.00517

(0.00260) (0.00276) (0.00278) (0.00276) (0.00537) (0.00541) Constant 1.726*** 1.311** 1.213** 1.311** 1.245** 1.337**

(0.0315) (0.539) (0.534) (0.539) (0.532) (0.537) Observations 1,072,034 1,072,034 1,072,034 1,072,034 1,072,034 1,072,034 R-squared 0.172 0.173 0.172 0.173 0.173 0.174

Summarizing Results for Aghion, Dewatripont, Du, Harrison, Legros • Targeting has more positive effects on productivity

when associated with greater competition • Targeting has more positive effects on innovation as

measured by the share of new products in sales when associated with greater competition

• Greater dispersion in allocation of subsidies results in improved performance

• Our theory shows that the gains from promoting some sectors in conjunction with competition still hold when the planner does not have perfect information

Concluding Remarks: Lessons on Using Industrial Policy

Why, what, and how to do IP? Why? • All countries engage in IP: question is not whether to

do IP, but how • Many theoretical justifications: agglomeration

economies, latent comparative advantage, need to spur innovation, spillovers

• Many practical reasons as well: promoting an attractive investment climate is not enough

• Governments are “doomed to choose”

What and How What to promote • Sectors with agglomeration economies, economies of scale,

spillovers, sectors of “latent” comparative advantage • Reason IP works when it focuses on export promotion is because

it targets these kinds of sectors • Economists generally favor foreign investment promotion; some

evidence that such IP works because it targets new or export oriented, growing sectors with externalities

How to promote • Mechanisms in place that ensure a critical private sector role:

– Industry associations, matching grants • Preserve or enhance competition by targeting competitive

sectors and spreading subsidies to many enterprises • Use instruments that enhance competition: tax cuts not tariffs

International Trade in Natural Resources: Practice and Policy Michele Ruta, World Trade Organization Anthony J. Venables, University of Oxford and CEPR IGC, September 2011

Structure of the presentation

• Natural resources trade: some stylized facts • What is (conceptually) distinctive about trade in resources? • Trade policy in resource sectors

– Exporters – Importers

• The long-run: exploration, development, depletion • Policy equilibrium • The international system

2

Some stylized facts • The long run:

– Resources trade increased in the first half of the 20th century. – The decline since 1955 was punctuated by increases coinciding with

oil shocks.

3

Some stylized facts

4

• Share in world trade: In 2009 natural resources trade was nearly 21% of world merchandise trade in dollar values

Some stylized facts

• Price volatility: The recent rise and fall of natural resources trade is mostly due to the evolution of commodity prices, particularly oil

5

Real prices of selected commodities Jan.2000 - Dec. 2010

Source: IMF, International Financial Statistics.

Some stylized facts

• Patterns of resources trade: Regions that are rich in natural resources tend to ship these goods to other regions

6

Resources exports by region and destination, 2009

Some stylized facts • Dominance in some economies:

– Countries with the highest concentration scores also have high shares of natural resources in total exports

7

0

0.2

0.4

0.6

0.8

1World

Angola

Iraq

Venezuela

Sudan

Sao Tome and Principe

Nigeria

Yemen

Libyan Arab JamahiriyaGabonBahrain

Iran

Tajikistan

Solomon Islands

Maldives

Saudi Arabia

Oman

Mali

Mauritania

concentration index share of natural resources in total export

• 9 countries where resource exports > 50% GDP

• 21 countries where resource exports > 80% all exports

• 19 countries where resource revenues > 80% fiscal revenues

• South Sudan over 95% of forex and fiscal revenue

Some stylized facts

Trade policy: why resources are different

• Trade on spot (physical market) & futures & long-term contracts • Supply:

– Immobile & inelastic supply – P > AC: Rents; often captured by government – Spatially concentrated; dominant some countries, no production in others.

• Demand:

– Inputs to production: ‘strategic’?

• Inter-temporal issues: – Long run projects / sunk costs – Depletion / exhaustibility

• Externalities:

– Open access and other environmental externalities

9

Trade policy for resource exporters • Instruments:

• Export taxes: discriminatory: domestic price < world price • Differently from tariff, export taxes are generally permitted and are not bound • Quotas are prohibited, but exceptions are allowed for “public policy” reasons • 35% of all notified export restrictions are in resource sectors.

• Domestic production taxes/ quantity controls: – Non-discriminatory: change total supply

10

Export taxes by natural resource

Trade policy for resource exporters Look at implications of policy for

– government revenue – domestic users – terms of trade (rent distribution).

I: Export taxes and government revenue: (given world price) • Transfer from producer government domestic consumers:

If resource rents already accrue to government (govt the producer) Export tax causes government revenue loss

• Generally; net revenue loss if domestic private sector net purchaser (resource revenue received by private sector < private sector purchases)

11

given world price

Trade policy for resource exporters I: Export taxes and government revenue: (continued)

Corollary: import tariffs for resource (or aid) rich economies • Suppose government only producer/consumer of resource, fixed supply. Export tax has zero effect; govt taxing itself • By Lerner symmetry, import tariff has zero real effect

• ‘Illusory revenues’: the tariff simply transfers revenue from resource account to tariff account (Collier and Venables 2010).

• Generalize:

• If some export elasticity/ other exports/ non-uniform import tariff structure then get usual deadweight welfare loss.

• Strong revenue case for resource exporters to have low export taxes and

import tariffs – but no evidence that they do.

12

Trade policy for resource exporters II: Export taxes and domestic users:

Use of export taxes to: • Promote downstream production activities

• Export resource embodied in goods rather than unprocessed • NB: transport costs and natural protection: 19th century vs 21st century • Indonesia (timber), China (rare earths).

• Reduce prices to consumers: political economy. • Reduce domestic price of fuel – benefit of resource abundance that is

visible to citizens • Reduce domestic price of food:

– Rice price spike – Wheat price spike

13

Trade policy for resource exporters III: Terms of trade and the distribution of rent

Tax/ quantity restrictions to raise world price: • ‘Optimal’ (for suppliers) output reduction: simple Hotelling model,

commit to leave some resource under ground price higher at all dates. • Time-consistent? • If cannot commit to leave undepleted resource, issue is one of inter-

temporal price profile – Iso-elastic demand curve, cartel behaviour ≡ price taking behaviour – Elasticity increasing through time, restrict quantity now.

• Cartel members: – Resource producers – Producers of substitutes

Incentives for producers to use WTO legal measures to redistribute rent.

14

Trade policy for resource importers

15

Import tariffs: • Covered by WTO

bindings • With the exception of

fisheries, tariff protection is lower than for overall trade, both for developed and developing countries

• … however

Trade policy for resource importers I: Domestic users: tariff

escalation and moving downstream production.

• Cannot move resource

production, but can move downstream activities

• Extensive tariff escalation • Higher tariffs processed than

raw • Tariff rates low but effective

protection high.

• Policy equilibrium – export taxes vs tariff escalation

16

Structure of tariff protection in developed countries, by stage of processing

Trade policy for resource importers II: Terms of trade and the distribution of rent

If no local production then import tariff ≡ domestic tax outside WTO commitments

Domestic taxes can be used to reduce the world price:

• ‘Optimal’ import tariff (consumption tax):

• If Hotelling suppliers and importer cartel, import tariff shifted entirely to suppliers: optimal import tariff drives world price down to extraction cost.

• Not in a pure Hotelling world: extensive margin of exploration and development.

• There is no explicit importer cartel …. but is high fuel tax explained entirely by externalities & Ramsey taxation…. or by potential to change terms of trade?

17

Trade policy equilibrium • Incentives for exporters to use export taxes:

• Domestic political economy • Moving downstream industry • Shifting the terms of trade

• Incentives for importers to use:

• consumption taxes: shift the terms of trade • Tariff escalation: move downstream industry • Shifting the terms of trade

• Policy equilibrium:

• Policy instruments outside WTO disciplines • Efficient location of downstream industries? • Equilibrium distribution of rent? • Supply distortion? • Consumption distortion: fuel prices vary by factor of 20:1

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Futures market & volatility • High volume futures trade

• Crude oil traded on future contracts EU, NY 1994: 1.5 x annual consumption 2009: 8.5 x annual consumption

• Traders • Producers – sell short: insurance, typically 6 months – 1 year. • Index traders – roll over long positions • Speculators – ‘price discovery’…. momentum

• Impact on volatility? • Contracts not physical commodities • Transmission future to spot: no evidence of increase in inventories • Volatility quite well explained by fundamentals, including increased

uncertainty about long run price anchor.

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Contracts: exploration and development

Biggest market failure, obstacles to exploration & development • Exploration a public good/ high levels of uncertainty (price, geology,

politics)/ asymmetric information/ sunk costs and hold up.

• Market failures include: • Risk of: renegotiation, changing fiscal terms, expropriation

– Deters investment – Inefficiently fast depletion – Losses to both parties

• Lack of transparency in award of contracts; auctions vs deals

Suggestive evidence of under-exploration/ lack of development in low- income countries An international trade/ investment issue.

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Low level policy equilibrium? What has the international system delivered?

• Consumer price of fuel varies by factor of 20:1 around world – Deadweight loss – even if inelastic supply – Implications for C02 emissions.

• Developing countries failed to develop downstream activities – Export taxes vs tariff escalation – Or just lack of comparative advantage?

• Under-exploration and development, – particularly in SSA

• Spot price not anchored on social marginal cost? – Determined by bargaining over rent

• Price volatility • Common pool problems:

– Renewables – fish – Deep sea oil – Polar regions

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Policy reform • Address asymmetries that create price gaps

• Asymmetric treatment of export taxes/ import tariffs • Asymmetric treatment of trade taxes/ domestic taxes

• Diversification and development. • Permit targeted interventions (instead of blunt export taxes)

• The allocation of resource contracts – auctions vs negotiations • MFN type principles of open competition, transparency

• Arbitration and dispute settlement • Contracts are incomplete and will be changed • Need to bound changes to be ‘reasonable’. • BITs or WTO?

• Anchor prices more firmly on long run social marginal cost…..? • No policy instruments • Changes in market structure/ geology of supply

• Global commons • Fish, poles etc

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