Trade and investment patterns

1. Trade and investment patterns
Lecture for the course STV4284B
Carl Henrik Knutsen
Department of Political Science, UiO
8/4-2008

2. Important questions
• Which firms import and export, and why?
• Which firms invest, and why?
• What characterizes FDI flows and stocks?
• What are the factors influencing allocation of
FDI?
• How does trade relate to FDI?

3. Actors
• Firms invest
• However, we are often interested in aggregate
patterns at the national level, even if
individual investment decisions are taken by
firms (and even individuals within the firm).
– Structural factors, political economic systems
– Generalization

4. The profit-maximizing firm in neo-
classical economics
• Invest or not?
– Invest if: p*f(x) – w*x – c > δ
– A wide interpretation of c: plant investment, administrative
costs, corruption, reputation effects etc..
• Uncertainty and risk-averse firms
• Are investors rational? Other important factors more or less
compatible with rational choice theory:
– knowledge and learning; bounded rationality
– external effects on other activities
– market power (mergers and acquisitions)
– maximizing profits or size?
• Parsimony: Benefits and drawbacks.

5. Empirical studies
• Aggregate vs firm level data
• Firm level data are only available for a certain
number of countries, and this limits the number
of studies
• Secrecy
• Short time series
• Comparability across nations; data at the national
level
• Definitions and comparability. OECD.

6. Norwegian FDI
• Data from the Statistics Norway (SSB)
• Data on investment projects
• 1998-2005
• Based on survey
• Reporting, bias and lack of data
• Availability and secrecy

7. Project on Norwegian FDI
• Hveem et al (2008a and 2008b) are first
outputs from this projects.
• Aggregate studies on FDI-patterns.
Descriptions and causal analysis.
• Forthcoming: State-owned enterprises and FDI
• Need for nuance: Sector studies and firm
studies. Studies on particular host countries?
• A very good opportunity for writing MA-
thesis!

8. ”The Latecomer Investor”
• Large-scale outward FDI from Norway is a relatively novel
phenomenon, with some exceptions (e.g. shipping)
• Historically, Norway has been a net importer of FDI
• But this has changed! In 2005: Outward = 2x Inward FDI
– Economic growth and growth of firms (large firms are much
more likely to engage in FDI)
– Capital accumulation
– Business culture changes, even in state-owned enterprises?
• According to UNCTAD statistics, Norwegian outward FDI-
stock in 1980 was only 0,4% of that in 2006, and in 1990 it
was 9,0% of that in 2006.

9. Some numbers
• Total outward FDI stock:
– 1998: 238 864 million NOK
– 2005: 665 349 million NOK
– Annual growth rate of 15,8% from 1998 to 2005. The growth rate from
1980 to 1998 was 25,1%, starting from a very low level!
– The growth rate in global FDI-stocks over the period from 1998 to
2005 was 10,9%. The growth rate from 1980 to 1998 was 11,6%.
• Norwegian outward FDI as a share of global FDI went up from
0,09% in 1980 to 1,04% in 2005. The Norwegian population
accounts for about 0,08% of the world’s population.
• Total outward FDI stock in oil and gas production:
– 1998: 87 408 million NOK
– 2005: 216 755 million NOK
– Annual growth rate of 13,9%

10. Norwegian FDI from 1980-2006
0
20000
40000
60000
80000
100000
120000
140000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
Series1

11. Geographical dispersion Norwegian
FDI
1969 1979 1989 1996 1999 2002 2005
Western
Europe
73,3 67,2 68,3 65,5 72,4 61,9 51,3
Eastern
Europe/
former Soviet
Union
0 0 0 6,7 1,8 3,2 7,4
Middle
East/North
Africa
n.a. n.a. n.a n.a. 0.6 0,6 2,2
Africa South
of the Sahara
n.a. n.a. n.a. n.a 2,9 2,9 3,6
North
America
16,7 15.5 19,6 14,4 15,3 16,9 19,9
Central and
South
America
n.a. n.a n.a. n.a. 3,2 3,7 3,2
Asian and
Oceania
} 6,7 } 10,3 } 9,5 } 10,6
2,5
0,3
4,8
3,0
8,2
1,9
Caribia n.a. n.a. n.a. n.a. 1,0 3,1 2,4

12. Some claims from the paper
• Norwegian FDI has had a dramatic increase in later years, outgrowing even the
global trend
• Norwegian FDI has been and still is very concentrated geographically, but the trend
is deconcentration, as Norwegian investors have increasingly turned to for
example Africa and Asia
• The largest ”receivers” of FDI in 2005: Sweden, USA, Belgium, Canada,
Netherlands, Singapore, Denmark, Great Britain, Germany, Angola, Azerbaijan
• Norwegian oil and gas investments are a substantial part of the story, but not the
whole story. Other sectors: Telecom, aluminium, mechanical industries, shipping
• Norwegian FDI has grown because of 1) New investments in existing projects, 2a)
Mergers and acquistions, 2b) Greenfield investments
• In addition to FDI, Norway’s state owned petroleum/pension fund is a very large
global investor in stocks and bonds.
• Not in paper: State owned companies are important: 30,3% of 2005 FDI, when
applying a 50% ownership criterion.

13. ”Blue-eyed investors”
• Underlying premise: A very wide range of host-
country characteristics can affect the allocation of
Norwegian FDI.
• Economic, geographic, political and social factors.
• Earlier studies have tended to focus on economic
factors
• No existing coherent model is able to capture
these diverse factors A need for theoretical
eclecticism and an explorative strategy,
empirically.

14. Some methodology
• A regression-based framework, but applied on a panel data
set  OLS does not suffice
• Pooled Cross Section Time Series analysis: OLS with panel
corrected standard errors. Takes into account heterogenous
standard errors across panels, autocorrelation and
contemporaneous correlation
• Time series from 1998-2005. Country-years are units.
• Data from several sources: SSB, WDI, FHI, WGI, ILO, CEPII….
• Regression equation:
Y = α + β1Xi1 + β2Xi2 + …. + βnXin + εi
• Interpretation of coefficients (Controlled for all other factors!)

15. Methodological pitfalls
• Data: Measurement errors from survey. Lacking data classified as 0
underreporting
– Systematic biases if FDI in some particular countries are systematically
underreported (tax-havens?)
• Transit countries and final investment location: Belgium and
Singapore!!
• Bi-directional causality: Only affects some variables in this study
• Omitted variable bias
• Controlling away indirect effects
• Multi-colinearity and uncertainty
• All these points imply that the results from the article have to be
interpreted with care. Nevertheless, these are the best estimates
we can get!

16. The main empirical results
• These factors seem to significantly increase Norwegian FDI:
– Large market
– Small geographical distance
– EU-membership
– Being Nordic
– High tertiary school enrollment rate
– Low capital density
– Energy-resources
– Low corruption
– Stricter labour standards
• These factors show diverging results or are insignificant in most analyses:
– Wages
– Democracy
– Rule of law
– Trade-taxes
– Bilateral investment treaties
– Tax-haven status
– Primary school enrollment rate

17. Economic factors
• The ”gravity model” in studies of trade. Works
quite well here as well.
– The role of a big market and well developed factor
markets
– Distance and FDI. Vertical vs horizontal FDI and
theoretical predictions
• Factors of production
– Type of education and sectors
– The role of wages
– Investment and two theoretical predictions (Solow vs
Krugman)

18. Economic policy and trade
• Bilateral investment treaties and tax-havens:
Why such weak results?
• Trade taxes and alternative explanations of
the negative relationship with FDI
• EU/Nordic
• Trade and FDI: The issue of causal direction
and interpretation of regression results

19. Political structures
• High correlation between political structures.
Institutional structures that tend to og
togetherMulti-colinearity and the difficulty
of determining relative effects.
• But: Political structures clearly matter!
– Rational investors and cost of doing business
– Rational investors and uncertainty
– Business leaders and norms
– Reputation effects

20. Specifications
• The choice of functional form: Logarithmic
transformations and interpretation of coefficients
• Alternative operationalization and robustness of
results
• The largest problem however is choosing the
most suitable model-specification
• Remember that we are only dealing with model-
contingent estimates: The most important thing
is not the numbers, but ”sign” of coefficients and
statistical significance.

21. How to read a regression table
Variables Model X
Constant 1257963
5,82*
GDP, 2000 $ 4,41E-06
13,53*
Weighted distance -72,78349
-5,97*
GDP per capita, 2000 $ -49,398
-1,40
R-squared 0,5123
Countries 175
Observations 1020

22. Interpretation and nuance
• Estimates are estimates
• We are dealing with aggregate data: way of
generalizing, does not strictly say anything
about factors moving decisions in concrete,
singular instances
• Nuancing the aggregate data: Sectors and
diversity!

23. Bernard et al. (2007)
• Firms and trade in the US.
• What are the characteristics of trading firms, and
how do they perform?
• Data from 1993-2000: Notice the short time
interval when interpreting trends
• Trends versus levels, shares versus growth
• Links customs data with data on firms
• Paper is mostly descriptive, and does not conduct
any rigorous analysis. Correlation and causation.

24. Main findings
• Importing and exporting are correlated activities (omitted variables? Size?)
• Trade is very concentrated: Top 1% trading firms account for 81% of trade, and
concentration increases over time.
• Only a small number of firms engage in trade, but the number is growing (entry
and exit mechanisms)
• But these firms are in general big!
• Greates share of trading firms are ”wholesale and retail trade” firms, but the
largest volume of trade takes place in the goods sector
• Most of the trade is with other OECD countries, and the average number of trading
partners is low (approx 3), but growing.
• Trading firms have better performances (employment growth and exit). Causal
interpretation: Learning and spill-overs as well as profits from trade AND/OR self-
selection into trade by most successful firms: Trade as symptom (Dani Rodrik)
• ”Most Globally Engaged Firms” are firms that both import and export with related
parties. These account for 80% of US exports and imports and are more likely to
trade with less developed countries
• Intra-firm trade is on the rise in MGEs, and in general, these firms also have higher
growth rates in exports and imports than other firms.

25. Hummels et al. (2001)
• Point of departure: Production processes increasingly
involve sequential, vertical trading along the value
chain. Import of inputs - production - export of good
(alternatively used as new input in receiving country)
• (International) Vertical specialization: Use of imported
goods that are used in producing goods that are later
exported
• More formally:
– Good is produced in two or more stages
– Two or more countries provide value added to good
– At least one country must use imported inputs and export
some of the production

26. Data and main findings
• Uses input-output tables from OECD database for
10 OECD countries, plus separate data from
Ireland, Korea, Taiwan and Mexico (These
countries account for more than 60% of world
exports).
• Vertical Specialization as share of trade for these
countries: From 0,165 in 1970 to 0,21 in 1990. A
30% growth.
• Vertical Specialization accounts for 30% of the
growth in total exports over the period.

27. Other findings
• Heterogeneity: Small countries have a higher
share of VS/export, and the US in particular has a
low share.
• VS/export has grown in most countries, but some
countries experienced a slow-down in the 1980’s.
VS was particularly important in increasing export
growth rates in Mexico and Taiwan.
• The VS share has mainly grown because there has
been an increasing VS share within sectors, and
not because countries have changed their
sectoral composition

28. Causes
• Countries are able to reap benefits from
Ricardian ”comparative advantages” not only in
trading ”home-grown” final goods, but also by
trading inputs: gains from trade.
• Why has this become increasingly possible?
– Technological change
– Transport costs
– Lowering of tariffs
– The transnational corporation and intra-firm trade
(organizational change)

29. Feenstra
• Increase in trade, and economic integration (mainly focusing on the US).
• ”The skeptic”: Pre WWI trade levels were high!
– Feenstra: Sectoral composition has changed as GDP has increased. Less trade
in services than in goods: Merchandise trade/production is much higher today
(1998)
• Economic integration goes together with disintegration of production
process (”outsourcing”). Relate to Hummels et al and vertical
specialization
• US trade in goods and long-run developments: From agriculture and raw
materials to manufactured consumer goods and particularly capital goods
• Capital goods, but also manufacturing are increasingly done abroad, but
often by affiliates belonging to US TNCs or by firms engaged in different
types of long-run contractual relations (licensing etc.)
• ”Low skill” production undertaken abroad, and ”high skill” production at
home (a simplified model). Advertising, marketing and product
development remains in the US. The logic of comparative advantage

30. The political debate and the academic
debate
• The political debate, especially in the US, has focused on the negative effects of
globalization and outsourcing on real wage decline or at least stagnation for low-
skilled workers and uneployment
• Economists, with a basis in empirical studies, have argued that technological
change, which has reduced demand for low-skilled workers, is largely to blame for
declining real wages (US) and high unemployment (Europe)
• Feenstra argues that one cannot separate easily between effects from
technological change and the effects from trade, and that these economists have
based their studies on trade in final goods. According to Feenstra, the picture
changes if we take into account vertical specialization and trade in inputs.
• In addition, increased mobility of capital has increased the relative bargaining
power of capital owners over laborers. Often, the threat to move the factory is
enough to reduce wages, and we do not need to see outsourcing for the threat of
outsourcing to have an effect on wages.
• Feenstra’s point is well taken, but in my view, the public debate has one-sidedly
focused on economic integration as a cause for these economic ills, and has not
taken into account the role of technological change. Both factors have probably
been at work.

31. Policy-remedies
• Trade policy: From altering and using the ”escape clauses”
in WTO to outright unilateral protectionism: Efficiency
issues!
• Subsidize the losers, but let the economy restructure:
Norman and Dixit’s subsidies and taxes
• Rodrik and the need for a strong welfare state in a
globalized economy
• Labour-market policies: Retrain and reeducate the
unempolyed industrial workers
• Technological development and new sectors: Find your new
comparative advantage!
• Provide a well-functioning and broad educational system.