1. Industrial Policy: Why, What and
How?
Ann Harrison
University of California, Berkeley and NBER
September 2011

2. 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)

3. 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

4. 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

5. I. Why Industrial Policy?

6. 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.

7. 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

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

9. 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)

10. 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

11. III. Digging Deeper: What to
promote and How

12. Should successful IP promote
emerging, not declining sectors ?
USA China
Bailing out sunset industries Promoting emerging sectors

13. 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

14. Harrison and Rodriguez Clare (2010) in Handbook of
Development Economics promote “soft” IP
“Hard” industrial Policy: Soft” Industrial Policy:
√
– Tariffs – Special Economic
– Subsidies to specific Zones offering lower
?sectors cost infrastructure
– Tax breaks for foreign – Roads and ports
investors designed to increase
– Domestic content trade
requirements – Special Credit for
exporters (Trade
Credit)
– Promoting clusters in
order to export

15. 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

16. 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

17. 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

18. Measures of Patterns of Interventions
(Does “what” you promote matter?)
• Patterns of tariff policies are measured by:
Ωrt =Corr (Tariff jt , L jr 0 / K jr 0 )
ωrt = Corr (Tariff jt , EXPjr 0 / SALES jr 0 )
ρ rt = Corr (Tariff jt , S jr 0 / UNSK jr 0 )
υrt = Corr (Tariff jt , RDIntensity jr 0 )
• 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

19. 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

20. 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

21. Summary Statistics:
What sectors are promoted in China?
Correlation Correlation Correlation Correlation Correlation Correlation
Correlation Tariff, Tariff, Tariff, RD Correlation Tax, Tax, Tax, RD
Year Tariff, L/K Exports Skill/Unskill intensity Tax, L/K Exports Skill/Unskl 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 wo rkers is defined as skill intensity; RD intensity is defined as the
share of high level technicians and engineers in total number of employees.

22. 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

23. 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

24. 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

25. 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

26. 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.

27. 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

28. TFP Estimation: Testing for the Impact of
Interventions in China in conjunction with
Competition
ln TFPijt = α + β1Z ijt + β 2 S jt + β 3 SUBSIDYijt + β 4COMPjt
+ β 5 SUBSIDY * COMPjt + α i + α t + ε ijt
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

29. 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
 Subsidyijt 
Herf _ subsidy jt = ∑i∈ j  
 Sum _ subsidy 
 jt 

30. 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.

31. 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

32. 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

33. 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

34. 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”

35. 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

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

37. 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

38. 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

39. Some stylized facts
• Share in world trade: In 2009 natural resources trade was
nearly 21% of world merchandise trade in dollar values
4

40. 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
Real prices of selected commodities Jan.2000 - Dec. 2010
Source: IMF, International Financial Statistics.
5

41. Some stylized facts
• Patterns of resources trade: Regions that are rich in natural
resources tend to ship these goods to other regions
Resources exports by region and destination, 2009
6

42. Some stylized facts
• Dominance in some economies:
– Countries with the highest concentration scores also have high
shares of natural resources in total exports
World
Mauritania 1 Angola
Mali 0.8 Iraq
Oman 0.6 Venezuela
0.4
Saudi Arabia Sudan
0.2
0
Maldives Sao Tome and Principe
Solomon Islands Nigeria
Tajikistan Yemen
Iran Libyan Arab Jamahiriya
Bahrain Gabon
concentration index share of natural resources in total export
7

43. Some stylized facts
• 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

44. 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

45. 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
Export taxes by natural
resource
10

46. Trade policy for resource exporters
Look at implications of policy for
–
–
government revenue
domestic users } given world price
– 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

47. 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.
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48. 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
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49. 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.
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50. Trade policy for resource importers
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
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51. Trade policy for resource importers
I: Domestic users: tariff
escalation and moving
downstream production.
Structure of tariff protection in developed
countries, by stage of processing
• 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
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52. 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?
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53. 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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54. 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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55. 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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56. 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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57. 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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