race to nowhere: the political economy of foreign direct
TRANSCRIPT
Race to Nowhere: The Political Economy of Foreign Direct Investment Restrictions in the 1990s
Sonal S. Pandya Department of Politics University of Virginia
@virginia.edu
1
1. Introduction
It is hard to overstate the importance of foreign direct investment (FDI) to
international economic integration. FDI is the single largest source of global capital, in
some years worth more than all other forms of capital flows combined.1 Intrafirm trade –
trade between subsidiaries of a multinational firm – comprises one-third of total world
trade.2 Additionally, FDI can foster economic development by creating jobs and
introducing new technologies.3 Despite FDI’s prominence we know little about how
countries regulate it. Existing scholarship on the political economy of FDI focuses on
how political risk influences FDI flows. 4
The politics of FDI are about more than political risk. Governments make explicit
choices about FDI, regulating it in much the same way they do trade and other forms of
This work shows that countries receive more
FDI when their governments can credibly safeguard foreign investments. The politics of
FDI, it follows, are about governments’ willingness and capacity to protect foreign
investors’ property rights. This framing obscures an enduring fact: governments restrict
FDI inflows.
1 World Bank 2003.
2 Hummels et al 2001, Yi 2003.
3 Romer 1993, Borzenstein et al 1998, Alfaro et al 2004.
4 Henisz 2002, Jensen 2003, Li and Resnick 2003, Pinto and Pinto 2008. An earlier
generation of FDI research also emphasized political risk but typically assumed an
antagonistic relationship between investors and host governments. See Vernon 1971,
Kobrin 1987. Kang 1997 and Crystal 2003 consider the relative absence of FDI
regulation in the US.
2
capital flows. Even during the 1990s, a decade marked by explosive growth in FDI
flows, restrictions on foreign ownership were common. Table 1 describes patterns in
foreign ownership restrictions in the 1990s. These restrictions limit the percent equity
foreigners can hold in a local firm, in some cases outright banning foreign participation.
The first three rows classify country-industry restrictions by three broad sector categories.
It shows that the percent of total observations restriction are similar across primary,
manufacturing, and service industries but that more countries outright ban investment
into service industries than manufacturing industries. The remaining rows disaggregate
country-industry restrictions by region of the world. Here too there is considerable
variation in incidence and severity of ownership limits. Of particular note is the relative
absence of regulation in Latin America.
A compelling explanation for these patterns requires a richer account of FDI’s
political economy, one that can explain variation in the degree of FDI regulation across
industries and countries. To develop this account I draw on established analytical
traditions in international political economy. First, I derive voters’ policy preferences
from the expected effect of FDI on income. FDI inflows redistribute income; precise
patterns vary with firms’ underlying motive for investment. Vertical FDI, investment for
export-oriented production, redistributes income from local capital owners to labor,
whereas horizontal FDI, production for sale in local product markets, is more likely to
reduce the income of both local capital and labor employed in the recipient industry.
Governments supply FDI restrictions when doing so benefits politically salient
constituencies; the configuration of these constituencies follows directly from FDI’s
distributional effects. Governments led by left parties are less likely to limit vertical FDI
3
because these investments benefit labor. Regulation of horizontal FDI is more likely
where electoral systems privilege narrow special interests over aggregate welfare. The
interaction of these economic and political dynamics explains variation in the incidence
of FDI regulation across industries and countries.
A central feature of this paper is an original dataset of country-industry foreign
ownership regulations in the 1990s. These data are of unprecedented breadth and detail,
covering thirty-nine industries each in over ninety countries. I test theoretical claims
using these data. Among the key findings are that countries are more likely to limit FDI
into industries that tend to receive horizontal FDI. Industries that receive purely
horizontal FDI are eight percentage points more likely to have a limit on foreign
ownership than industries dominated by vertical FDI. Candidate-centered electoral
systems are more likely to impose FDI restrictions; countries with highly candidate-
centered systems are ten percentage points more likely to limit FDI than countries with
party-centered electoral systems. There is some evidence that countries led by left
governments are less likely to regulate industries that receive vertical investments.
The remainder of this paper consists of three main sections. Section 2 lays out a
theory of FDI regulation comprised of a model of FDI’s distributional effects, and the
national political characteristics that explain the supply of FDI regulation. Section 3
reviews the empirical strategy – data sources, tests – and results. Section 4 concludes by
considering the broader implications of this work to the political economy of
international economic integration.
2. A Theory of FDI Regulation
4
FDI distinguishes itself from other forms of international capital flows by its firm-
specific nature. The capital assets at stake in FDI include proprietary production
technologies, managerial and organizational practices, and trademarked brands.
Multinational corporations (MNCs) arise to overcome the inefficiencies of directly
selling or licensing these assets. These include the incompleteness of contracts,
misaligned incentives of contracting firms, and difficulties in monitoring licensees. FDI
expands firms across borders, enabling them to realize firm-level scale economies while
keeping assets within the firm.5 Due to the high costs of establishing and maintaining
foreign affiliates, only the world’s most productive firms can profitably undertake FDI.6
Helpman, Melitz, and Yeaple find that MNCs are fifteen percent more productive than
purely domestic, exporting firms.7
5 Hymer 1976, Antràs 2003. MNCs resolve incomplete contracting problems by
allocating residual rights of control, those rights which are not ex ante contractable, to the
parent firm (Grossman and Hart 1986).
6 MNCs enter host countries through the establishment of new production facilities,
greenfield investment, or by acquiring existing firms, mergers and acquisitions (M&As).
For simplicity’s sake, I assume all FDI is of the former variety. Most of the same
conclusions apply to FDI through M&As but the predictions regarding capital’s
preferences are somewhat complicated by the presence of a local capital beneficiary of
FDI. In some instances, MNCs will face local firms who are themselves MNCs in which
case the productivity gap is narrower.
7 Helpman et al 2004.
5
Since owners of firm-specific capital face incomplete contracting problems, they
do not seek returns to their assets in arms-length capital markets. Rather, FDI yields
returns to these assets in product markets. MNCs use FDI to either exploit lower
production costs, vertical FDI, or enter new product markets, horizontal FDI. 8 These
two types of FDI correspond to different ways of organizing multinational production.
Firms that pursue vertical FDI fragment the production process. They retain headquarter
functions like research and marketing in the home country and relocate production in
countries abundant in necessary factors of production, typically labor.9 Horizontal FDI
replicates production facilities in multiple host countries to produce goods and services
for sale in that market.10
8 Although there are finer-grained distinctions between types of FDI (see Feenstra 1999,
Eckholm et al 2003) the salient distinction here is between export and local market-
oriented FDI. I collapse all investments that export out of the host country into the
vertical category and all market-oriented investments in the horizontal category.
9 Helpman 1984. FDI in the primary sector is sited near resource deposits. Due to the
unique features of FDI into this sector – exceptionally large economies of scale and very
capital intensive – the distributional implications presented here are less likely to hold.
10 Markusen 1984.
Firms pursue this strategy when trade barriers or transport costs
make cross-border trade prohibitive. Both types of investment increase the supply of
productive capital in host countries but differ in their effect on local product market
competition - the production output of vertical FDI is for export while firms sell
horizontal FDI’s output in the local market. This difference drives variation in FDI’s
distributional effects.
6
2.1. Distributional Effects of FDI Inflows
I derive FDI’s effect on local factor returns using Jones’ canonical specific factors
model.11 The model features a three factor, two product economy consisting of two types
of sector-specific capital and mobile labor.12 Each sector produces one product using a
combination of one form of specific capital and labor. This is an appropriate model as
FDI inflows “transmit equity capital, entrepreneurship, and technological or other
productive knowledge in an industry-specific package.”13
11 Jones 1971. See appendix for a formal discussion of this model.
12 Although FDI is firm-specific capital, firms compete in sector-defined product
markets. Accordingly, sector-specificity of capital is the most appropriate assumption in
examining FDI’s distributional effects. Relaxing the mobile labor assumption magnifies
the factor supply effects detailed below. See Grossman and Helpman 1996 and Batra and
Ramachandran 1980.
13 Caves 1971, 3. Absent from this theoretical framework is FDI’s potential to generate
growth through technology spillovers. Although these are a commonly cited as a benefit
of FDI, findings are inconclusive (see footnote 3). At best, whether such spillovers
obtain depends on several preconditions for growth having been. Also absent are FDI’s
effects, if any, on balances of payment as these depend on several detailed aspects on
investment including financing and sourcing of inputs. The export orientation of vertical
FDI suggests that it is more likely than horizontal FDI to contribute to positive payment
balances.
7
Vertical FDI increases the supply of one type of specific capital. This raises the
marginal revenue product of labor in the recipient sector – the income generated by each
additional worker employed. In equilibrium, firms hire workers until the marginal
revenue product equals the market wage. An increase in sector-specific capital raises the
marginal product of labor employed in the sector as additional capital raises the
productivity of the marginal worker. 14
There is considerable empirical support for the positive effects of FDI inflows on
wages.
To maximize productivity gains the sector
receiving FDI expands production, drawing in workers from the other sector. Since labor
is mobile higher labor productivity in one sector drives up the market wage. Higher
wages come at the expense of capital income. As product prices are fixed, these are
changes in real income.
15
14 The Jones model assumes technology is the same across all firms. Relaxing the
assumption of uniform production technologies across firms within each sector - to allow
for the observed fact that MNCs are more productive than local firms - raises the
possibility that FDI reduces overall labor demand. In horizontal FDI this is a possibility
only when product demand is sufficiently price inelastic that demand remains constant
following a prince reduction. In vertical FDI this result can only obtain if MNCs
systematically underinvest given that production is for export. A possible exception is
the natural resources sector in which the difference in capital intensity of local and
foreign-owned firms’ production technologies can be exceptionally large.
15 See Lipsey 2002 for a comprehensive summary of empirical findings.
Görg and Greenway find that local firms increase wages after the entry of
8
foreign-owned firms despite constant or even decreasing total factor productivity.16 In
one of the few studies of FDI’s localized wage impact, Blonigen and Figlio examine the
effects of FDI on wages in South Carolina.17 They conclude that the entry of a single,
average-sized, foreign-owned plant, employing about 190 workers, increases by 2.3
percent the real wage of all workers employed in the same industry and county as the
foreign-owned plant. This wage increase, they argue, is so large that it must reflect an
overall increase in labor demand. There is also evidence to confirm FDI’s negative
effect on capital’s returns. Demonstrating the losses to local capital owners due to FDI
inflows elsewhere in the economy, Hiscox finds that US manufacturing industries that are
not active in FDI are more likely to engage in political lobbying and file grievances with
the International Trade Commission.18
The income effects of horizontal FDI operate through both an increase in sector-
specific capital and a drop in the price of the product produced by that sector. The
decline in product prices reflects the market access motive of horizontal FDI. Firms
make horizontal investments when other, less costly, forms of market entry are
unavailable. Capital owners’ real income declines with horizontal FDI into their sector
similar to the vertical case. The implications for real wages, however, are ambiguous.
There are three variables that determine horizontal’s net effect on wages: an increase in
16Görg and Greenway 2001. This result also demonstrates that increased returns to labor
are not due to the propensity of foreign investors to acquire firms that were more
productive ex ante.
17 Blonigen and Figlio 2000. 18 Hiscox 2004.
9
labor demand (identical to vertical FDI), a drop in sector returns due to price competition,
and labor’s consumption preferences. Under some circumstances there will be a drop in
real wages, suggesting that labor will unite with capital owners in their sector to lobby
against horizontal FDI inflows.
Sector-specific rents provide an additional, independent motivation for labor and
capital to unite against horizontal FDI into their industry. Horizontal FDI indicates the
existence of market entry barriers that can give rise to rents.19 To the extent that labor
shares in these rents they are more likely to oppose horizontal FDI. A growing body of
empirical research documents how FDI reduces returns to local firms. The market
competition introduced by FDI reduces returns to existing local firms. Sembenelli and
Siotis find that the profit margins of non-R&D intensive Spanish firms declined with FDI
inflows into their industry.20 Blonigen, Tomlin, and Wilson show that US firms register,
on average, a three percent increase in their stock market value after filing an anti-
dumping petition. FDI into the firms’ US market reduces these abnormal returns by fifty
percent, and are not statistical significance.21
19 Specific rents can also arise from product differentiation but these rents are generally
less likely to be threatened by FDI because product varieties in the same industry are not
perfect substitutes. Schmalansee 1989. To the extent that varieties introduced by FDI are
substitutes for existing products horizontal FDI can increases average total costs in
industries with increasing returns to scale.
20 Sembenelli and Siotis 2002. 21 Blonigen, Tomlin, and Wilson 2004.
Chari and Gupta examine the effects of
India’s partial FDI liberalization in 1991 on firm profitability and find that in all
10
liberalized sectors local firms’ market share declined following FDI.22
A complete account of FDI policy formation requires a link between policy
preferences and outcomes. Political institutions establish this link through their influence
on the costs of collective political action, and politicians’ policy choices. I assume that
politicians are singularly interested in retaining political office and this informs their
response to constituents’ conflicting preferences.
This threat to
rents posed by horizontal FDI makes is more likely that labor and capital owners will
oppose horizontal FDI into their industry.
2.2. Domestic Politics of FDI Regulation
23
Collective action refers to the willingness and ability of groups to mobilize in
support of a goal. As Olsen famously observed, the difficulty of collective action
The opposing preferences that
vertical and horizontal FDI each create pose tradeoffs that politicians must negotiate.
Vertical FDI pits the interests of capital owners against those of labor. Horizontal FDI
poses a tradeoff between the preservation of rents and consumer welfare. The salient
aspects of the political environment vary with the structure of voters’ preferences. Two
dimensions are particularly relevant: the propensity of factor and sector groups to engage
in collective action and the size of politicians’ constituencies for reelection.
22 Chari and Gupta 2008. 23 This assumption excludes politicians engaging in personal rent-seeking, for example by
accepting illegal payments from potential foreign investors. Such rent-seeking almost
certainly exists but my claim is that it does not systematically figure into the calculations
of the elected politicians who set FDI policies.
11
towards a common goal increases where public goods are at stake.24 Alt and Gilligan
conjecture that collective action is easier in small groups because an individual has a
greater incentive to contribute; their contribution is more likely to be decisive.25
The politics of vertical FDI feature broad factor groups. Political parties
introduce factor groups’ preferences into the policy-making process. Parties organize
voters and politicians according to a stable set of policy orientations. Partisanship
informs how politicians resolve the tradeoff between capital and labor’s preferred
policies; politicians will support their constituents’ preferred policies because they weight
the welfare of their corresponding factor group more than that of the other factor.
Accordingly, countries with left governments are more likely to liberalize FDI into
industries receiving vertical investments, in accordance with labor’s predicted support for
such investment. Dutt and Mitra demonstrate this relationship in the trade policy
context.
Group
size can also matter when the marginal cost of expanding the group is fixed or monitoring
of others’ activities is necessary to ensure contribution. Politicians’ responses to these
lobbying efforts derive from the institutional setting. The institutional environment
indicates on whom the politician is dependent for re-election; the procedure for securing
elected office elevates the interests some voters over others.
26
24 Olson 1965. 25 Alt and Gilligan 1994. 26 Dutt and Mitra 2005.
They find that tariff levels vary systematically with relative factor
endowments and party control: left governments in capital-abundant countries are more
protectionist than right governments of capital-rich countries or Left governments of
12
labor-abundant economies. These results demonstrate how political parties respond
directly to their corresponding factor group’s preferences.27 Hiscox also identifies a
partisan cast to US trade policy but clarifies that partisanship is salient only when
distributional effects are felt along factor lines.28
A tradeoff between sector returns, whether they be factor returns or rents, and
consumer welfare defines the politics of horizontal FDI. The Stigler-Peltzman model of
regulation captures the essential tradeoff: concentrated costs versus diffuse gains.
When sector type exercises a larger
influence on factor incomes trade policy is only weakly related to partisanship. This is
why partisanship is only relevant to explaining vertical FDI policies; preferences for
horizontal FDI do not neatly coincide with partisan ideology.
29 The
reelection-minded politician views this tradeoff as one between campaign contributions
from sectoral interests and votes from consumers; contributions are useful for earning
additional votes. This politician jointly maximizes contributions and votes such that a
marginal increase in contributions is equal to the loss in votes due to untapped consumer
welfare.30
27 Unlike this result, however, the distributional effects of FDI are not contingent on the
relative factor endowments of host countries.
28 Hiscox 2002. 29 Stigler 1971, Peltzman 1976. 30 More precisely, the marginal increment of contributions is equal to the number of votes
that increment of contribution generates. Untapped consumer welfare refers to the
deadweight loss created by regulation.
For each politician, the relative importance of small groups of contributors
and the broader electorate varies based on electoral institutions; the more politicians are
13
rewarded for delivering broadly-distributed welfare gains, the less likely they are to limit
horizontal FDI. Evidence on trade policy outcomes demonstrates this logic. Mitra,
Thomakos, and Ulubaşoģlu find that Turkish politicians weighed consumer welfare more
as the country democratized.31 Milner and Kubota conclude that democratization
contributed to trade liberalization developing countries. 32
3. Empirics
This account of the political process through which FDI policy is made shows
how FDI’s distributional effects interact with features of the domestic political
environment. It demonstrates the importance of disaggregating FDI inflows: vertical and
horizontal FDI have different distributional effects. From these different alignments over
FDI policies emerge distinct political models of FDI policy-making. Vertical FDI pits
large factor groups against each other, making the politics of vertical FDI about factor
groups’ influence on the policy process. The politics of horizontal FDI embodies a
tradeoff between concentrated costs of local industries and diffuse gains to consumers
due to price competition. Those industries capable of lobbying are more likely to secure
limits on horizontal FDI. Politicians attentive to the general welfare of the electorate are
less likely to restrict horizontal FDI.
The primary challenge of empirical research on FDI regulation is the
measurement of key concepts. The measurement of two variables in particular, FDI
31 Mitra et al 2002. 32 Milner and Kubota 2005.
14
regulation and the horizontal and vertical motives for FDI into a given industry, shape the
overall empirical strategy.
FDI Barrier, the dependent variable, is a three category variable measured at the
country-industry level (e.g. Argentina-Chemicals). It is equal to “2” for a complete ban
on foreign ownership; “1” for limits on the amount of equity that foreigners can hold or a
discretionary screening of investment proposals; and “0” for no formal ownership limit.33
Foreign ownership regulations capture countries’ explicit effort to limit FDI inflows.
Local ownership and joint venture requirements deter investment because they require
firms share profits with local partners and can result in leakage of firm-specific
technologies. 34
These data are a tremendous innovation in the study of FDI. They measure the
existence and degree of restrictions across industries within countries. By contrast, the
standard proxies for FDI openness use political risk measures, summary indicators of
national investment climate that do not identify formal policies or vary across industries.
Given that the hypotheses presented here emphasize country and industry, rather than
temporal, variation I work around the absence of data for every unit of observation in the
1990s by calculating the median level of entry barrier for each country-industry between
Similarly, broad screening mandates can have a chilling effect by
creating uncertainty and costs for investors.
33 See appendix for detailed information on data sources and measurement.
34 Gomes-Casseres 1990 and Wei 2000 demonstrate this effect empirically.
15
1990 and 2000 using observed data.35 The sample spans 39 industries each in 94
countries.36
Horizontal FDI and Vertical FDI measure the proportion of total industry FDI
flows that are horizontal and vertical, respectively. These measures aggregate affiliate
sales of U.S.-based MNCs across all host countries, taking the sales patterns of US firms
to be representative of MNCs worldwide.
Of the 3666 country-industries in this cross-section, 2597, or approximately
seventy percent of observations have some form of entry barrier. 2485 country-
industries, about sixty-seven percent of the sample have regulation on the amount of
foreign ownership while the remaining three percent (112 country-industries) completely
ban foreign ownership.
37
35 To standardize interpretation all but one of the variables in the estimated models are
median values for the same time period. The data on MNCs sales, described below, is for
1999, the only year for which complete data for this set of industries in available.
36 The use of BEA data (described below) dictated the use of these 39 industries. See
appendix for industries and countries in the sample.
37 Data are from the U.S. Bureau of Economic Analysis 1999 Survey of Direct
Investment Abroad, a comprehensive firm-level survey of U.S.-based MNCs. Firms are
legally required to provide detailed operations and financial data, with the guarantee that
firm-level data remain confidential. The publicly available aggregated data is the most
detailed and comprehensive data source on the activities of multinational firms in any
country. See Table A2 for a list of industries and their associated Horizontal FDI values.
Horizontal FDI is the ratio of total affiliate
sales in an industry made in host countries. Vertical FDI is the proportion of total
16
affiliate sales made via exports out of host countries. These measures vary only across
industry.
The relative proportion of vertical and horizontal FDI into an industry is a proxy
for the distributional effects of FDI in the industry. Recall the theoretical argument from
the previous section: horizontal FDI creates product market competition, making it more
likely that both capital and labor experience a net loss in income. Under these
circumstances labor and capital are more likely to be united in their opposition to FDI in
their industry. By contrast, vertical FDI, production for sale outside the host country,
divides factor groups because the income effects of vertical FDI are common to factor
groups rather than industries.
Sales-based measures of horizontal and vertical FDI constructed with US data are
standard in empirical research on FDI.38
38 Brainard 1997, Carr et al 2001, Blonigen et al 2003, Hanson et al 2003, Yeaple 2003. I
assume that US affiliates’ sales patterns are representative of MNCs worldwide.
There may be concern that these measures are,
to some degree, endogenous to FDI restrictions. For this to be true two conditions must
hold: restrictions deter one type of investment more than another such that the overall
distribution of sales between exports and local sales is altered; and this effect is
sufficiently robust to appear at the worldwide industry level, aggregating across that
industry’s FDI in all countries. The first condition could hold but the second one is quite
unlikely given that the choice of investment strategy is causally prior to the choice of host
country. An MNC faced with an entry barrier will seek a market with a more liberal FDI
17
regime rather than fundamentally change its investment strategy in order to invest in a
country with restrictions.39
Partisanship measures derive from the World Bank’s Database of Political
Institutions’ (DPI) data on the partisan orientation regarding economic policy.
40 Right
parties are those that prefer less government involvement, left parties are those whose
“names reveal them to be communist, socialist, or social democratic” while centrist
parties are those evincing a mix of left and right elements, for example pro-business
regulation coupled with support for redistributive policies.41 I generate a measure of
partisanship, Left Party, which takes the value 1 if the largest party in government is left
and not nationalist as defined by the DPI.42
39 There are few alternative measures to try as robustness checks due largely to the
absence of industry-level data on service industries.
40 See Beck et al 2001 for a detailed description of these data.
41 Beck et al 2001, 15 42 For countries with presidential systems, this variable represents the party orientation of
the executive and for parliamentary systems the orientation of the party with the largest
representation in government. See below for further discussion of nationalist parties.
The inclusion of democracy measures,
discussed below, facilitates a more precise interpretation of Left Party given that there are
countries in the sample for which there are not electoral institutions as conceived of here.
With both covariates in the model, Left Party can be interpreted as the estimated
probability of a foreign ownership limit when the government is led by a left party
18
relative to the same probability under a right or centrist-led government.43
The politics of horizontal FDI, recall, derive from the relative weight that
politicians place on narrow (sector) versus broad (consumer) interests. I capture this
concept with an indicator of political particularism, the degree to which politicians have
an incentive to cultivate a personal vote. Aspects of electoral rules govern how votes
translate into seats. These include the extent of party control over seat allocation and
district magnitude.
The
theoretical prediction is that left parties are less likely to restrict vertical FDI due to its
positive effects on local wages. I use these partisanship data based on the assumption
that left parties, as defined here, consistently represent the interests of urban labor – the
segment of the labor market most likely to benefit from an increase in vertical FDI. My
expectation is that Left Party is negatively associated with the probability of limits on
investment and that this effect is more likely to obtain in industries dominated by vertical
FDI.
44
43 I have also estimated a model of vertical FDI regulation in which I include a direct
measure of whether a county is defined as having no political parties in place of Polity
Score. Substantive conclusions are unchanged.
44 Carey and Shugart 1995 describe the basic logic of the measure. Johnson and Wallack
(2008) adapt the Carey and Shugart measure to describe, at the national level, politicians’
incentives to cultivate a personal vote.
Where politicians have a greater incentive to cultivate support
among narrow groups, they are more likely to privilege the narrow protectionist interests
of industries over the welfare gains to consumers. This measure, Personal Vote, ranks
countries on a scale of 1 to 13 by the extent to which politicians have an incentive to
19
provide narrow, particularistic policies rather than policies oriented towards maximizing
aggregate welfare; higher values correspond to a greater incentive to cultivate smaller
constituencies.45
As a robustness check, I measure the extent of democratic accountability using
the Polity IV combined measure of regime type.
The interpretation of this measure is that in countries in which
politicians are relatively more concerned with providing benefits to narrow constituencies
we are, on average, more likely to see FDI regulation in a given industry.
46
Nationalism and national security concerns are two prominent alternate
explanations for FDI regulation. Nationalist explanations hold that countries oppose
foreign ownership as foreign ownership violates a conception of national identity based,
at least in part, on assets remaining in the hands of those with an enduring connection to
the host country. National security explanations build on concerns that foreign
ownership compromise national security through various mechanisms including greater
potential for espionage by foreign governments via subsidiaries and foreign ownership of
assets vital to national security. Both considerations have the potential to vary across
industries - some industries probably matter more to national identity and national
Polity Score summarizes a variety of
institutional features to generate a measure that ranges from -10 to 10 with higher values
representing more robust democracies. All else equal, more democratic countries are
less likely to restrict to FDI inflows because politicians in these countries have electoral
incentives to place a higher weight on aggregate welfare of voters than the rent income of
specific industries.
45 “dom_rank” variable from Johnson and Wallack 2008.
46 Jaggers et al 2004.
20
security than others - but in the absence of theoretically-driven criteria to establish the
nationalist or national security salience of industries I look to sources of country-level
variation in the resonance of nationalist and national security concerns in the policy-
making process.
I control for possible nationalist motives for FDI regulation by testing whether the
nationalist orientation of the largest party in government is associated with a higher
probability of restriction. Nationalism is a binary variable that takes the value 1 if the
largest political party in government has as a central tenet of its platform “the creation or
defense of a national or ethnic identity.” This measure is from the DPI. Countries in the
sample led by nationalist parties include Apartheid-era South Africa, Greek Cyprus, and
Lebanon.47
I measure countries’ propensity to regulate FDI based on national security
concerns by whether the chief executive is a military officer. Military is a binary
measure from the DPI. Examples include Argentina, 1977-1983, Fiji from the late 1980s
onwards, and South Korea from 1975 (the first year covered by the DPI), through 1992.
In using this measure I assume that a chief executive who is also a military officer places
greater importance on national security concerns than would her civilian counterpart. If
national security concerns do factor into FDI regulation, countries with military chief
To the extent that there are nationalist concerns that drive FDI policy-
making, governments led by nationalist parties should be more likely to restrict FDI
inflows in order to preserve national identity. Given the generality of this claim I include
it as a control in models for both vertical and horizontal FDI.
47 Approximately a third of the countries in the sample are nationalist by this measure for
at least one year in the 1990s.
21
executives should be more likely restrict FDI than countries with civilian leaders. I
acknowledge that a concern for national security may imply different approaches to FDI
regulation; in some countries it implies restricting entry while in others it can dictate a
particular openness to FDI, perhaps in a bid to develop industrial capacity. Again, given
the generality of this explanation I include it in both models.
Additionally, I examine external influence on FDI policies, another alternate
explanation. I construct a binary variable, ‘80s IMF Loan that indicates whether a
country received concessional International Monetary Fund (IMF) funding in the 1980s.
Concessional IMF loans carry a below market interest rate and are conditional on
borrowing countries adopting policy reforms recommended by the IMF. Although there
is little indication that FDI liberalization is an explicit criterion other common
requirements, particularly privatization, may indirectly require liberalization of foreign
ownership. I use data for the 1980s to allow for a lag between the initial imposition of
IMF conditionality and observable policy changes. I calculate the median net flow of
concessional IMF funding to each country between 1980 and 1989.48 The variable is
binary, equal to 1 for countries that received or repaid concessional IMF loans in the
1980 and 0 otherwise.49
48 These data are from the World Bank’s World Development Indicators
49 Although this specification eliminates information by collapsing down net flow data to
binary variable, there are no theoretical reasons to expect that the amount of IMF funding
is systematically related to countries’ propensity to restrict FDI inflows.
Given the conditionality mechanism I expect that countries that
received IMF loans in the 1980s are less likely to restrict FDI inflows in the 1990s.
22
Finally, I include three controls for conditions that may influence outcomes.
First, industries with government ownership have a unique distributional dynamic -- the
state itself is potentially on the losing end of FDI inflows. Labor employed in state-
owned firms often enjoy perks including high wages and job security and the state,
analogous to a local capital owner, has exceptional influence over FDI regulation. In
order to parse out this effect, I include in both models Government Ownership, a binary
measure of whether there is government ownership in a given country-industry.50 My
expectation is that industries with government ownership are more likely to be regulated
in order to protect rents accruing to the state and public employees. The second control
variable is GDP Growth, a measure of annual GDP growth.51 The rationale for this
control is that voters in countries experiencing high levels of growth may be, at the
margins, less sensitive to the negative distributional effects of FDI inflows and therefore
will not lobby for protection. Accordingly, I expect this variable to have a negative
influence on the probability of FDI regulation. Finally, in some specifications I include a
measure of tariffs to test whether the politics of FDI regulation are distinctive for
industries in which there is also cross-border trade in goods. Tariff is the trade-weighted
tariff for the given country-industry.52
50 These data were collected along with the FDI entry barrier data. See the appendix for
more detail on sources.
51 These data are from the World Bank’s World Development Indicators
52 These data were obtained through UNCTAD’s TRAINS database.
The sample of traded industries provides insight
into the relative importance of vertical and horizontal incentives for FDI in
manufacturing industries, the one sector in which both motives for investment are
23
prominent. To the extent that there is cross-border trade, firms have less of an incentive
to engage in horizontal FDI, as trade is more efficient, but a greater incentive to engage in
vertical FDI because transaction costs are lower. For a given industry among the subset
of tradeables tariff levels indicate whether vertical or horizontal motives are more likely
to dominate.53
I estimate two sets of models, one each for the regulation of vertical and
horizontal FDI. Given that the FDI Barrier is a three category ordered variable I use
ordered probit models with multiple imputation for missing data.
I expect that higher tariffs are associated with a higher probability of
regulation in industries receiving horizontal FDI and lower probability of limits in
industries that tend to receive vertical FDI.
54 The substantive
results are robust to a binary recoding of the dependent variable and estimation with
binary logit and probit specifications.55
Table 2 summarizes the results of baseline models of vertical FDI regulation and
estimates using primary, manufacturing, and service industry subsamples. Model 1 is
the baseline specification that includes the interaction of Vertical FDI and Left Party. As
the latter variable is binary, the coefficient on Vertical FDI represents the mean effect of
the proportion of FDI that is vertical when there is not a left government. The inclusion
of Polity Score controls for countries with no meaningful systems of political
representation, so this can be thought of as the effect of right or centrist party leadership.
The result shows that industries that receive vertical FDI have a negative and statistically
significant probability of restriction in the absence of left party leadership. This is
53 Amiti and Waeklin 2003 demonstrates this pattern empirically 54 Results are robust to list-wise deletion in place of multiple imputation. 55 See appendix for further details on the estimation techniques used.
24
somewhat unexpected but may simply reflect the pooling of right and centrist parties, the
latter having ambiguous bases of political support. The coefficient on Left Party is
positive and statistically significant, indicating that for industries receiving no vertical
FDI, industries into which FDI is exclusively host market-oriented, left parties are more
likely to limit FDI inflows. The model does not offer a clear prediction on the
preferences of left parties for horizontal FDI since this type of FDI is does not have
uniform effects on returns to labor. The main prediction of the theory is that countries
led by left government are less likely, all else equal, to regulate industries receiving
vertical FDI. The interaction of Left Party and Vertical FDI tests for this joint effect.
The sign on this coefficient is negative, as predicted, but it is not statistically different
from zero. Given the ambiguity in the coding of Left Party, I re-estimate the model for
sector and region subsamples of data. Though this is less efficient because the sample
sizes are smaller, I can bring to bear more precise predictions about the distributional
effects of FDI for the sector subsamples and permit variation in what construes a left
party to the extent the support bases of parties vary systematically by region.
In Models 3-6 I re-estimate the baseline model for subsets of the data from which
we can make more precise conclusions about the composition of interests. Models 3-5
are based on subsamples for three sectors: primary, manufacturing, and services,
respectively. Interestingly, Vertical FDI and Left Party cease to be significant in all three
of these models, though the direction of these effects is the same as the baseline model.
For the sake of completeness, I include primary sector but given that there are relatively
few observations these estimates are not very precise. Model 4 shows that among
manufacturing industries the amount of vertical FDI is not a significant predictor of
25
restrictions in into an industry, while the presence of a left party is more likely to be
associated with restrictions, even within a sample of industries that is likely to have the
most vertical FDI. This effect is more precise for service industries but given that most
FDI into these industries is horizontal there is little scope for an increase in labor demand.
Again, it seems that on average, groups negatively influenced by horizontal FDI belong
to the support base of left parties. Finally, Model 5 is a sample of industries for which
there can also exist cross-border trade. Recall that vertical FDI and trade are
complements, so the wage-increasing effects of vertical FDI are the most likely to obtain
in this sample of industries. Indeed, the sign on Vertical FDI flips to negative though
without achieving conventional levels of statistical significance. These preliminary
results suggest re-estimating Model 5 with more disaggregated, industry-level data.
Table 3 summarizes the model estimates across region subsamples. Recall that
the partisanship argument refers to parties that represent the interests of urban workers.
In the absence of more precise data on representation, I split the sample up into regional
groupings on the assumption that the organization of political parties is somewhat similar
within regions. The findings for Latin America show the predicted interaction effect.
Based on the coefficients in Model 7, Latin American countries lead by left parties are
sixteen percentage points less likely limit FDI into industries receiving vertical FDI than
Latin American countries lead by right or center parties. This result suggests that left
parties in Latin American may more accurately reflect the interests of urban workers.
More detailed study of the support bases of political parties is needed.
26
Of the alternate explanations, two are consistently significant across these
samples.56
Table 4 summarizes the estimates of the baseline model of horizontal FDI
regulation. Models 12 and13 confirm the basic insight that countries are more likely to
regulate FDI into those industries in which FDI creates product market competition.
Horizontal FDI has a positive and statistically significant effect on the probability of FDI
entry barriers. Table 5 provides a substantive interpretation of this effect. It shows the
expected probability of an entry limit (FDI Barrier = 1) and a complete ban on FDI (FDI
Barrier = 2) for six of the thirty-nine industries represented in the sample. These selected
industries span the range of observed values of Horizontal FDI. The computers industry
is the least locally-oriented industry in the sample as over sixty percent of its sales are
made outside of host countries. For this industry the expected probability of an entry
limit is .516 and the probability of a complete ban on investment is a low .033. Moving
from left to right, industries are more oriented towards horizontal investment as indicated
by the percent sold locally. Telecommunications, the industry in the rightmost column, is
Recipients of concessional IMF loans have a 5.5 percentage point lower
expected probability of a local ownership requirements and a 1.6 percentage point lower
probability of a complete FDI ban. Leadership by a nationalist party increases the
expected probability that FDI Barrier =1 by 6.2 percentage points and the expected
probability of that FDI Barrier =2 by 2.7 percentage points. For Latin America,
however, there is a negative and significant effect of nationalist parties. This curious
finding suggests further study of Latin America’s party system and its influence on FDI
policies.
56 Expected probabilities calculated with Zelig using coefficients for Model 2 and have p-value no greater than .05 (Imai et al 2007).
27
purely horizontal given the inability to trade basic domestic telecommunications services
across national borders. Accordingly, the expected probabilities of regulation, .60 for an
entry barrier and .06 of a complete ban, are the highest in the sample. Overall, there is an
approximately nine percentage point difference in the expected probability of an entry
limit and a three percentage point difference in the same probability of an FDI ban
between the highest and lowest observed Horizontal FDI values.
Figures 1a and 1b show graphically the effect of political institutions on the
expected probability of FDI regulation. Figure 1a plots the marginal change in the
probability of FDI regulations across different values of Personal Vote when Horizontal
FDI is fixed at its mean. The left panel shows that between the least and most
particularistic regimes there is approximately a ten percentage point increase in the
expected probability that FDI Barrier = 1. The right panels shows that across this same
range there is a three percentage point increase in the expected probability of a ban on
FDI (FDI Barrier =2). These findings are consistent with the theoretical claim that
countries with candidate-centered political systems are more likely to regulate FDI owing
to politicians’ incentives to privilege special interests.
As a robustness check I graph the expected probabilities of regulation across the
range of Polity Score, a general measure of democracy. Democracy and Personal Vote
appear to capture different aspects of political institutions as the correlation between them
is -.168. The left panel of Figure 1b shows the expected probability that FDI Barrier =1
across the range of Polity Score values. The expected probability of an entry limit at the
lowest observed level of Polity Score, -10, is .62 and this probability at the highest value
of Polity Score, 10, is .515, creating a roughly ten percentage point reduction in the
28
expected probability across the range of possible values. As the confidence intervals
show, however, estimates at the lowest level of polity are less precise because few
countries in the sample have such low levels of democracy.57
Of the five control variables in the model, three are significant across Models 12
and 13. GDP Growth has the expected negative effect on the probability of FDI
regulation; countries experiencing growth may be, at the margins, less likely to limit
horizontal investments, either because local producers would not see a reduction in
market share or consumers would be less sensitive to price changes. There is a 4.7
percentage point decrease in the expected probability of FDI Barrier = 1 between the
GDP Growth evaluated at two standard deviations below and above its mean.
The difference in expected
probabilities between the highest and median values of Polity Score is a more modest two
percentage points, though still statistically different from zero. As shown in the right
panel there is a difference of about four percentage points between Polity Score’s highest
and mean (3.65) values.
58
57 There are only two sample countries each for each value in the range Polity Score =-10- -8: -10: Saudi Arabia, and Qatar; -9: Bahrain, Oman; -8: Syria, United Arab Emirates. 58 All first difference estimates reported for control variables are significant at the ninety-five percent level and are generated with coefficients and errors from Model 13.
There is
a 1.3 percentage point change in the same probability that FDI Barrier = 2. Nationalism
is positive and significant, indicating that countries with governments led by nationalist
parties are more likely to regulate FDI inflows. There is a four percentage point higher
expected probability of FDI Barrier = 1 in the presence of a nationalist government and a
1.8 percentage point higher probability that FDI Barrier = 2. IMF Conditionality has
opposite effects in Models 12 and 13. In Model 12 the variable is unexpectedly positive,
suggesting that countries with previous experience with concessional IMF lending are
29
more likely to regulate FDI. In Model 13 the same variable has a negative and
significant effect on the probability of FDI regulation indicating that countries that
received concessional IMF lending in the 1980s were, all else equal, less likely to limit
FDI. Specifically, the expected probability of FDI Barrier = 1 is 5.6 percentage points
less for IMF loan recipients, and same probability that FDI Barrier = 2 is 1.6 percentage
points less. These different findings suggest that acceptance of IMF loans is related to
some larger aspect of democracy. Models 14 and 15 disaggregate the sample into
manufacturing and service industries. Notably, the statistically significant effect of
Horizontal FDI disappears when the sample is disaggregated by sector. These findings
demonstrate that range of variation in the full sample drives the significant results based
on the full sample. The mean value of Horizontal FDI industries is .64 for manufacturing
industries but .92 for service industries.
4. Conclusion
This paper highlights a new dimension to the political economy of FDI, the
politics of FDI regulation. Existing research suggests that countries uniformly seek to
maximize FDI inflows. In practice, countries routinely restrict foreign ownership. In this
paper I explain variation in these restrictions as a function of FDI’s redistributive effects
on income and politicians’ incentives to supply regulation. Empirical tests feature a
unique and comprehensive dataset of foreign ownership restrictions in the 1990s,
disaggregated by country and industry. Countries are more likely to limit FDI into
industries that receive horizontal, market-seeking FDI than those industries in which
vertical, cost-reducing FDI dominates. Countries with constituent-centered political
30
systems are, all else equal, more likely to regulate horizontal FDI inflows due to
politicians incentives to privilege narrower, producer interests. There is also some
evidence that countries with left governments are less likely to regulate industries that
receive vertical FDI. These findings are robust to controls for alternate explanations
include nationalism, national security concerns, and the mandates of international
financial institutions.
These findings contribute to a more nuanced account of FDI’s politics. They help
to make sense of prominent yet contradictory stylized facts about FDI: the concerted
efforts of many countries to attract FDI inflows juxtaposed with frequent attempts to
block other investments. Variation in FDI’s distributional effects across industries can
help to explain this contradiction. It is likely that countries target their investment
promotion efforts towards vertical investments while blocking investments that would
threaten returns to existing producers.
These findings also reveal underexplored facets of international economic
integration. FDI places a richer set of industries and economic activities into an open
economy context. FDI pushes integration past physical limitations like transport costs
towards more far-reaching global market integration. For example, horizontal FDI
introduces foreign competition into markets for nontradeables, likes services. This
insight is particularly important in light of the growing emphasis in world trade
negotiations on market access into service industries. The extent to which FDI’s market-
integrating potential is realized depends on individual countries’ choices to accept the
costs – competition from the world’s most productive firms. The theory and data
presented here are the foundations of a new research program on the political economy of
31
FDI regulation. This research program provides a nuanced and versatile framework in
which to understand a central driver of global economic integration.
32
Appendix: Derivation of Hypotheses Using Jones (1971) Specific Factors Model
I derive FDI’s effect on local factor returns using Jones’ canonical specific factors
model.59
1K
The model features a three factor – two product economy, consisting of two
types of sector-specific capital, and 2K , and labor, L which is mobile across sectors.
Two products, 1X and 2X , are produced each with a combination of one type of specific
capital and labor. This is an appropriate model as FDI inflows “transmit equity capital,
entrepreneurship, and technological or other productive knowledge in an industry-
specific package.”60
ija
Let refer to the amount of factor i necessary to produce a single unit of
product j ; iR represents the return to one unit of factor i , i = 1,2 ; and jp the price of
product j, j = 1,2. In the competitive equilibrium there is full employment of all factors.
The following equations describe factor endowments and commodity prices:
1111 KXaK = (1)
2222 KXaK = (2)
LXaXa LL =+ 2211 (3)
111111 pRaRa LLKK =+ (4)
59 Jones 1971. This neoclassical model could be extended to incorporate common
characteristics of MNCs and the markets in which they operate including scale
economies, product differentiation, and firm-level variation in productivity. See
Helpman and Krugman 1985 and Melitz 2003.
60 Caves 1971, 3.
33
222222 pRaRa LKK =+ (5)
The competitive market assumption implies that firms minimize unit costs. Firms
optimize by selecting a mix of inputs based on the ratio of factor prices of the two factors
used in industry j :
)(Kij
Lijij R
Raa = (6)
From these equations the effect of changes in factor endowments and product prices on
returns to both forms of capital and labor is derived through total differentiation:
)7]}(ˆˆˆ[ˆˆ]1{[1ˆ2211
11
12
22
22
11
11
22
22
1111
111 KKLppR LL
K
L
KL
K
L
KL
KKLK λλ
θθ
θσ
λθθ
θσ
λθθ
σλ −−+−+
∆=
)8]}(ˆˆˆ[ˆˆ]1{[1ˆ1122
22
21
11
11
22
22
11
12
2222
222 KKLppR LL
K
L
KL
K
L
KL
KKLK λλ
θθ
θσ
λθθ
θσ
λθθ
σλ −−+−+
∆=
]}ˆˆˆ[ˆˆ{1ˆ22112
11
221
11
11 LKKppR LL
KL
KNL −+++
∆= λλ
θσλ
θσλ (9)
where
22
22
11
11
KL
KL θ
σλθσλ +=∆ (10)
Ljλ is the fraction of the total labor force employed in the production of commodity j; ijθ
is the proportion of total factor inputs accounted for by factor i in the production of
commodity j; jσ is the elasticity of substitution between the two factor inputs used in the
production of commodity j; and “^” indicates the relative change in a variable.
Vertical FDI increases the host country’s supply of 1K . In equations 7 and 8,
which specify returns to sector 1 and sector 2 capital owners respectively, 1K̂ has a
34
negative coefficient. This indicates that an increase in 1K reduces returns to capital
owners in both sectors. Equation 9, which describes returns to labor, shows that an
increase in 1K raises wages.61
1K
In equilibrium, firms hire workers until the marginal
revenue product equals the market wage. An increase in raises the marginal product
of labor employed in the sector as the additional capital makes the marginal worker more
productive. To maximize marginal revenue product the sector receiving FDI expands
production, drawing in workers from the other sector. This increase in labor demand
drives up the market wage. As prices are fixed these are changes in factors’ real income.
Horizontal FDI redistributes income through an additional channel: product
market competition. I treat this effect in the context of the model as a drop in 1p , the
price of the commodity produced by the sector receiving horizontal FDI.62
61 In all three equations the magnitude of change is conditional on
This
1Lλ , the proportion of
the total labor supply employed in the sector receiving FDI. The magnitude of capital’s
losses also depends on its sector’s ratio of labor to capital inputs,Kij
Lj
θθ
. This ratio
indicates the labor-intensity of the i-th sector’s production technology. Intuitively, the
more labor-intensive a sector is, the more income is redistributed from capital to labor.
Accordingly, capital owners in the relatively labor-intensive sector experience a greater
decline in income than capital owners in the other sector.
62 This captures the common case in which 1X is a nontraded commodity such that 1p is
set locally.
35
assumption is reasonable given the consistently higher productivity of foreign-owned
firms. 63
1X
Horizontal FDI is more likely to reduce the income of local labor than vertical
FDI. With a drop in price, the marginal revenue products of both factors employed in
decline but 11KR falls by a greater percentage than does 1p while LR declines by less
than 1p . Equation 9 shows that returns to labor are the weighted sum of labor used in
both sectors which cushions wages against the drop in 1p . The net income effect of
horizontal FDI for labor depends on labor’s consumption preferences; wages may
increase in terms of 1X but drop in terms of 2X . The model shows industry
characteristics that are more likely to result in a net drop in labor income. The first term
within the curly braces in Equation 9 shows the magnitude of a drop in 1p on wages
depends on 1Nλ , the percent of the total labor supply used in Industry 1 and, 11
1
Kθσ , the
elasticity of the marginal product curve of labor of industry 1. The elasticity of the
marginal product curve describes how easily labor can be substituted for capital in
industry 1’s production function. The more easily this can happen, the greater the decline
in labor’s income.
63 This assumption precludes anti-competitive behavior by MNCs such that product
prices would increase following horizontal FDI. The precise effect of horizontal FDI on
commodity prices depends on the elasticity of substitution between existing commodities
and those introduced through FDI.
36
Data Appendix
Measure of FDI Entry Barriers
Foreign ownership data were coded from Overseas Business Reports, a US
Commerce Department publication series that provides detailed summaries of individual
countries’ economic policies and market profiles to assist Americans contemplating
commercial activities abroad.
Each observation is at the industry-country-year level. Industry designations are
according to the International Standard Industrial Classification (ISIC) Revision 3.1.64
64 Due to the ISIC scheme it is sometimes necessary to classify restrictions at a higher
level of aggregation than would be preferred. For example, countries often subject
investment in domestic air transport to a different set of regulations than international air
transport. The air transportation category (ISIC 6200), however, is only divided into two
sub-categories: “scheduled air transport” (ISIC 6210) and “non-scheduled air transport”
(ISIC 6220). In this case, an FDI restriction in domestic air transport is coded at the more
aggregate (ISIC 6200) level.
The raw data were collected at the most appropriate industrial classification, ranging
from one to four-digit aggregations. For example, a ban on foreign ownership in
transportation is coded as a ban on foreign ownership in three two-digit categories: land
transport (ISIC 6000), water transport (ISIC 6100), and air transport (ISIC 6200). By
contrast, a ban on foreign ownership in railroads is coded as a restriction in the three-digit
37
subcategory of land transportation for railroads (ISIC 6010 – rail transport). This dataset
encompasses fifty-seven two-digit ISIC categories and their associated subcategories.65
Foreign ownership restrictions refer to formal limits on equity ownership by non-
citizens. Typically, countries set these regulations by industry and set explicit limits on
foreign equity participation. In some cases there are mandatory joint venture
requirements that require the foreign investor to split ownership with a local partner firm.
FDI Regulation takes the value “2” for those country-industries into which no foreign
ownership is allowed; “1” for country-industries a regulation limiting foreign equity
(most often limited to forty-nine percent), or a mandatory joint venture requirement (such
that ownership is evenly split between a foreign firm and a local partner).
For analysis purposes. in this paper I aggregated all industry-level data to the 2-digit level
according to the rule that if a constituent sub-category has a restriction then the associated
2-digit category is coded as restricted.
66
65 There are four additional two-digit categories in ISIC Rev. 3.1 that are not included in
this dataset because, by definition, they cannot receive FDI. These include ISIC 95, 96,
97, all subsets of “Activities of private households as employers and undifferentiated
production activities of private households” and ISIC 99 - “Extraterritorial organizations
and bodies.”
66 Although there is a legal difference between a majority ownership requirement and a
joint venture regulation, in practice these terms are often used interchangeably.
The
remaining observations take the value “0” if any of the three variables has an observed
38
absence of any of the three restrictions. All graphics generated with binary versions of
this variable collapse observations equal to 1 and 2 into a single category.
There 3666 total observations in the sample. The sample consists of, for a given
year, all industries in the countries for which there is information on FDI regulations for
at least one industry in that year from which I calculate the median value at the country-
industry-level for the period 1990-2000. Given that all possible types of industrial
activity are not likely to be present in all country-years, I identify nonexistent
manufacturing industries as industries in which both employment and output are zero for
a given country-year. I identify these industries in the United Nations Industrial
Development Organization (UNIDO) Industrial Statistics Database.67
Approximately forty percent of the data on the dependent variable is not
observed. In order to increase the efficiency and reduce bias of estimates I perform
multiple imputations prior to analysis using the software package MICE (Van Buuren and
Oudshoorn 2007) to generate ten imputed datasets, each comprised of ten iterations. The
imputation model includes thirty-one variables: those variables used in the analysis, a
The use of data for
manufactured goods reflects the option of importing goods rather than producing them
locally. Most countries have few substitutes for locally-produced services owing to the
difficultly of trading most services. Therefore I assume that all service sectors exist in all
countries in the sample. I also assume that country-year descriptions are based on a
positive-list for industries, that those industries which are not specifically mentioned as
having some form of entry barrier do not have restricted entry.
67 UNIDO classifies data by the ISIC Revision 2. I converted these data to ISIC Rev. 3
using the United Nation’s correspondence.
39
variety of industry-level measures taken from the BEA, and country-level measures of
economic growth, external debt, and political indicators, all taken from data sources
described in this appendix. The results presented here represent averages of the
variations of each estimates plus the variation across estimates to accurately represent the
additional uncertainty introduced through imputation (Rubin and Little 2002). As a
robustness check, I re-estimate models 1 and 12 using list-wise deletion (eliminating
2619 observations). The only substantive change is that Government Ownership is
negative and highly significant. Results are available upon request.
Industry-Level FDI Measures
All industry-level explanatory variables are from the Bureau of Economic
Analysis’ (BEA) 1999 Survey of Direct Investment Abroad. Any data suppressed for
privacy reasons are designated as missing (indicated by “(D)” in the original dataset).
Data for which values are close to zero, noted as varying between -US$500,000 and
US$500,000 (indicated by “(*)” in the original dataset) are set at their maximum value.
In order to use these data, industry designations have to be aggregated up from the ISIC
Rev. 3 into the BEA’s classifications scheme.68
68 Data on ownership restrictions were originally classified by the International Standard
Industrial Classification Revision 3 (ISIC Rev.3), standardized to the two-digit
aggregation. I construct a correspondence between ISIC Rev.3 and the BEA’s industrial
classification for international surveys to use the BEA’s industry-level sales data. This
correspondence is available upon request.
In some instances aggregation required
summing across categories that include suppressed data, creating measures that are lower
40
than their true values. Table A2 provides an overview of all observed values of horizontal
FDI.
All financial data are standardized to constant year 2000 millions of U.S. dollars using
the U.S. Bureau of Labor Statistics All-Urban Consumer Price Index.
41
Table A1: Summary Statistics
Mean Stnd Deviation
Minimum Maximum Predicted Sign
FDI Barrier 0.67 0.58 0 2 Horizontal FDI 0.744 0.19 0.383 1 Positive
Vertical FDI 0.259 0.181 0 0.61 Negative Personal Vote 6.7 4.29 1 13 Positive Polity Score 3.65 6.78 -10 10 Negative Left Party 0.316 0.44 0 1 Negative Military 0.146 0.34 0 1 Positive Nationalism 0.116 0.344 0 1 Positive 80s IMF Loan 0.387 .499 0 1 Negative
Tariff 13.1 17.25 0 314.92 Negative
Government Ownership 0.66 0.48 0 1 Positive
GDP Growth 4.35 2.79 -7.02 25.7 Negative
Means and standard deviations are means of the means and standard deviations of ten multiply-imputed datasets.
42
Table A2: Proportion of Total Sales by US-based MNCs in Host Countries Industries Proportion of MNC Sales Administration, support, and waste management (S) 0.94 Agriculture, forestry, fishing, and hunting (P) 0.45 Beverages and tobacco products (M) 0.667 Chemicals (M) 0.638 Communications & audio and visual equipment (M) * Computers (M) 0.38 Construction (S) 1 Fabricated metal products (M) 0.737 Food (M) 0.745 Furniture and related products; Misc. Manufacturing (M) 0.643 Health care and social assistance (S) 0.997 Hotels & Restaurants (S) * Information services and data processing services (S) 0.896 Instruments (M) 0.483 Insurance carriers and related activities (S) 0.825 Machinery (M) 0.6 Miscellaneous services (S) 1 Motion picture and sound recording industries & broadcasting (S)
*
Motor vehicles, bodies and trailers, and parts (M) 0.476 Nonmetallic mineral products (M) 0.774 Oil and gas extraction (P) 0.529 Other-Mining (P) 0.532 Other-Transportation Equipment (M) 0.482 Other finance, except depository institutions & securities (S) 0.713 Paper (M) 0.756 Petroleum and coal products (M) 0.835 Plastics and rubber products (M) 0.673 Primary metals (P) 0.522 Printing & publishing industries (M) 0.88 Professional services; Management (S) 0.826 Real estate (S) 1 Rental and leasing (except real estate) (S) 1 Retail trade (S) 0.985 Telecommunications (S) 1 Textiles, apparel, and leather products (M) 0.57 Transportation and warehousing (S) 0.853 Utilities (S) 0.99 Wholesale Trade (S) 0.6997 Wood products (M) 0.47 Industry categories are based on the 1997 Bureau of Economic Analysis International Survey classifications. To facilitate merging industry-level data across different classifications some industries list here are aggregations of multiple BEA categories. (*) indicates that no estimate could be derived due to suppressed survey data. P = primary sector, M = manufacturing, S = services.
43
Table A3: Countries in Sample
Africa Algeria Angola Benin Botswana Côte d'Ivoire Cameroon Cape Verde Algeria Ethiopia Gabon Ghana Guinea-Bissau Kenya Liberia Morocco Madagascar Mozambique Mauritania Niger Nigeria Senegal Seychelles Tunisia Tanzania Uganda South Africa Congo, Dem. Rep. Of/Zaire Zambia Zimbabwe Asia Australia Bangladesh China, P.R: Mainland Indonesia India Japan Korea Sri Lanka Malaysia New Zealand Pakistan Philippines Papua New Guinea Singapore Taiwan Thailand
Canada Latin America Argentina Bahamas, The Bolivia Brazil Chile Colombia Costa Rica Dominican Republic Ecuador Guatemala Haiti Mexico Panama Peru Paraguay Uruguay Venezuela Middle East Bahrain, Kingdom of Egypt Israel Jordan Kuwait Lebanon Oman Qatar Saudi Arabia Syrian Arab Republic Turkey United Arab Emirates Yemen, Republic of Western Europe Austria Belgium Switzerland Cyprus Germany Denmark Spain Finland France United Kingdom Greece Ireland
Table 1: Distribution of 1990s Foreign Ownership Restrictions FDI Barrier = 0 1 2 % of total
restricted Primary 85 136 4 60 Manufacturing 429 536 28 62 Services 344 570 74 56 Africa 108 351 27 77 Asia 189 270 24 60 Latin America 413 141 32 29 Middle East 71 249 10 78 Western Europe
77 193 12 73
This table summarizes the dependent variable in this paper, FDI Barrier, a three category dependent variable equal to 0 if there is no limit on foreign ownership in a country-industry, equal to 1 if a there is a specified percentage of equity that must be held by a local partner (typically fifty-one percent), and equal to 2 if no foreign ownership is allowed. See Table A2 for sector classifications and Table A3 for region classifications.
45
Table 2: Sources of Vertical FDI Regulation, Full Sample and Sector Subsamples
(1) (2) (3) (4) (5) (6) Vertical FDI -0.426***
(0.166) -0.473*** (0.141)
-1.596 (2.985)
-0.407 (0.368)
-0.016 (0.425)
-0.297 (0.422)
Left Party 0.188**
(0.089) 0.147** (0.057)
1.85 (2.554)
0.192 (0.252)
0.18** (0.106)
-0.082 (0.295)
Polity Score -0.022***
(0.004) -0.022*** (0.004)
-0.022+ (0.014)
-0.027*** (0.007)
-0.017*** (0.006)
-0.021** (0.011)
Nationalism 0.007***
(0.078) 0.243*** (0.078)
0.223 (0.254)
0.288** (0.122)
0.204** (0.104)
0.655*** (0.148)
Military 0.034
(0.096) 0.033 (0.096)
0.107 (0.243)
0.119 (0.125)
-0.049 (0.129)
0.549*** (0.202)
80s IMF Loan -0.187**
(0.076) -0.187** (0.076)
-0.357* (0.206)
-0.283*** (0.1)
-0.0698 (0.096)
-0.372* (0.154)
Government Ownership
-0.016 (0.133)
-0.016 (0.133)
-0.221 (0.239)
-0.161 (0.16)
0.137 (0.133)
-0.291 (0.242)
GDP Growth -0.023***
(0.007) -0.023*** (0.007)
-0.045 + (0.027)
-0.03*** (0.01)
-0.013 (0.011)
-0.088*** (0.028)
Vertical FDI x Left Party
-0.165 (0.276)
-3.376 (5.218)
-.182 (.683)
-0.292 (0.762)
0.243 (0.706)
Tariff 0.002
(0.003)
N 3666 3666 376 1692 1598 782 Primary
Industries Manufacturing Services Tradables
***>.01, **>.05, *>.10, +>.15. Standard errors in parentheses. Ancillary parameters omitted. This table summarizes ordered probit estimates. The dependent variable is FDI Barrier, a three category dependent variable equal to 0 if there is no limit on foreign ownership in a country-industry, equal to 1 if a there is a specified percentage of equity that must be held by a local partner (typically fifty-one percent), and equal to 2 if no foreign ownership is allowed. See Table A2 for sector classifications.
46
Table 3: Sources of Vertical FDI Regulation, By Region
(7) (8) (9) (10) (11) Vertical FDI -0.91**
(0.373) -0.673** (0.324)
-0.45** (0.25)
0.099 (0.452)
-0.453 (0.463)
Left Party 0.96***
(0.238) -0.398* (0.205)
0.076 (0.198)
0.132 (0.184)
Polity Score 0.07***
(0.018) 0.119*** (0.026)
-0.005 (0.01)
-0.047 (0.188)
-0.103*** (-0.014)
Nationalism 0.832***
(0.165) -1.75*** (0.446)
0.415** (0.166)
0.528 ** (0.224)
1.914*** (0.398)
Military 2.418***
(0.294) 0.147
(0.161) -2.672***
(0.435)
80s IMF Loan -0.036
(0.125) -1.57*** (0.28)
-0.166 (0.144)
0.32 (0.352)
Government Ownership
0.022 (0.202)
0.281 (0.219)
-0.091 (0.205)
0.38* (0.19)
0.029 (0.278)
GDP Growth -0.116***
(0.035) -0.045 (0.037)
-0.004 (0.01)
-0.09*** (0.03)
0.078 (0.06)
Vertical FDI x Left Party
-0.131 (0.659)
-1.013 + (0.685)
0.205 (0.55)
0.535 (0.58)
N 624 663 1092 741 507 Asia Latin
America Africa Western
Europe Middle East
***>.01, **>.05, *>.10, +>.15. Standard errors in parentheses. Ancillary parameters omitted. This table summarizes ordered probit estimates. The dependent variable is FDI Barrier, a three category dependent variable equal to 0 if there is no limit on foreign ownership in a country-industry, equal to 1 if a there is a specified percentage of equity that must be held by a local partner (typically fifty-one percent), and equal to 2 if no foreign ownership is allowed. See Table A3 for region classification.
47
Table 4: Sources of Horizontal FDI Regulation
(12) (13) (14) (15) Horizontal FDI
0.66** (0.32)
0.414*** (0.125)
0.281 (0.503)
0.349 (0.883)
Personal Vote
0.05* (0.03)
0.046 (0.39)
0.064 (0.094)
Horizontal FDI * Personal Vote
-0.029 (0.039)
-0.019 (0.064)
-0.044 (0.101)
Polity Score -0.023* (0.014)
Horizontal FDI * Polity Score
0.005 (0.018)
Nationalism
0.577*** (0.089)
0.167* (0.087)
0.556*** (0.099)
0.54*** (0.156)
Military -0.463*** (0.11)
-0.007 (0.085)
-0.494*** (0.142)
-0.521*** (0.172)
80s IMF Loan
0.234** (0.084)
-0.187*** (0.058)
0.218** (0.1)
0.228* (0.116)
Government Ownership
0.295* (0.142)
0.017 (0.1)
0.284 ** (0.111)
0.387*** (0.135)
GDP Growth -0.021 +
(0.014) -0.022*** (0.008)
-0.022+ (0.014)
-0.028* (0.015)
N
3666 3666
1692 Manufacturing
1598 Services
***>.01, **>.05, *>.10, +>.15. Standard errors in parentheses. Ancillary parameters omitted. This table summarizes ordered probit estimates. The dependent variable is FDI Barrier, a three category dependent variable equal to 0 if there is no limit on foreign ownership in a country-industry, equal to 1 if a there is a specified percentage of equity that must be held by a local partner (typically fifty-one percent), and equal to 2 if no foreign ownership is allowed. See Table A2 for sector classifications.
Table 5: Expected Probability of Foreign Ownership Restrictions, Selected Industries
( Percentage Sales in Host Market )
Computers ( 38% )
Motor Vehicles ( 47% )
Chemicals ( 63% )
Non - Metallic Mineral Products ( 77% )
Transport /Warehousing ( 85% )
Telecoms ( 100% )
Minimum Local Ownership
.52 (.016 )
.53 (.013 )
.55 (.011 )
.57 (.01 )
.58 (.01 )
.60 (.012 )
Foreign Ownership Ban
.03 2 (.005 )
.033 (.006 )
. 04 1 (.005 )
.046 (.005)
.05 (.004 )
.056 (.006)
Standard errors in parentheses. Estimates calculated using Zelig (Imai, King, Lau 2007) based on Model 12 estimates. All other variables set at mean or median values. The industries shown here represent the range of observed values of Horizontal FDI.
.
Figure 1a: Probability of FDI Regulation Across Personal Vote
2 4 6 8 10 12
0.00.1
0.20.3
0.40.5
Incentives to Cultivate
Chan
ge in
P(Y
=1)
2 4 6 8 10 12
0.00.1
0.20.3
0.40.5
Incentives to Cultivate
Chan
ge in
P(Y
=2)
50
References
Alfaro, Laura, Areendam Chanda, Sebnem Kalemli-Ozcan, and Selin Sayek. 2004. "FDI
and Economic Growth: The Role of Local Financial Markets." Journal of
International Economics 64, no. 1: 89-112.
Alt, James E., and Michael J. Gilligan. 1994. "The Political Economy of Trading States."
Journal of Political Philosophy 2, no. 2: 165-92.
Amiti, Mary, and Katherine Wakelin. 2003. "Investment Liberalization and International
Trade." Journal of International Economics 61: 101-26.
Antràs, Pol. 2003. "Firms, Contracts, and Trade Structure." Quarterly Journal of
Economics 118, no. 4: 1375-418.
Barry, Frank G. 2004. "FDI and the Host Economy: A Case Study of Ireland." In
Multinational Firms in the World Economy, edited by Giorgio Barba Navaretti
and Anthony J. Venables. Princeton: Princeton University Press.
Batra, Raveendra N., and Rama Ramachandran. 1980. "Multinational Firms and the
Theory of International Trade and Investment." American Economic Review 70,
no. 3: 278-90.
Beck, Thorsten, George Clarke, Alberto Groff, Philip Keefer, and Patrick Walsh. 2001.
"New Tools in Comparative Political Economy: The Database of Political
Institutions." World Bank Economic Review 15, no. 1: 165-76.
Blonigen, Bruce A., Ronald B. Davies, and Keith Head. 2003. "Estimating the
Knowledge-Capital Model of the Multinational Enterprise: Comment." American
Economic Review 93, no. 3: 980-1001.
Blonigen, Bruce A., and David M. Figlio. 2000. "The Effects of Foreign Direct
Investment on Local Communities." Journal of Urban Economics 48: 338-63.
51
Blonigen, Bruce A., KaSaundra Tomlin, and Wesley W. Wilson. 2004. "Tariff-Jumping
FDI and Domestic Firms' Profits." Canadian Journal of Economics 37: 656-77.
Branstetter, Lee G., and Robert C. Feenstra. 2002. "Trade and Foreign Direct Investment
in China: A Political Economy Approach." Journal of International Economics
58: 335-58.
Brainard, S. Lael. 1997. "An Empirical Assessment of the Proximity-Concentration
Trade-Off between Multinational Sales and Trade." American Economic Review
87, no. 4: 520-44.
Borensztein, Eduardo, Jose De Gregorio, and Jong-Wha Lee. 1998. "How Does Foreign
Direct Investment Affect Economic Growth?" Journal of International
Economics 45, no. 1: 115-35.
Carr, David L., James R. Markusen, and Keith E. Maskus. 2001. "Estimating the
Knowledge-Captial Model of the Multinational Enterprise." American Economic
Review 91, no. 3: 693-708.
Carey, John M. and Matthew Soberg Shugart. 1995. " Incentives to cultivate a personal
vote: A rank ordering of electoral formulas." Electoral Studies 14, no.4: 417-439.
Caves, Richard E. 1971. "International Corporations: The Industrial Economics of
Foreign Investment." Economica 38: 1-27.
Chari, Anusha, and Nandani Gupta. 2008. "Incumbents and Protectionism: The Political
Economy of Foreign Entry Liberalization." Journal of Financial Economics 88,
no.3: 633-656.
Crystal, Jonathan. 2003. Unwanted Company: Foreign Investments in American
Industries. Ithaca: Cornell University Press.
52
Dutt, Pushan, and Devashish Mitra. 2005. "Political Ideology and Endogenous Trade
Policy." Review of Economic Studies 87, no. 1: 59-72.
Eckholm, Karolina, Rikard Forslid, and James R. Markusen. 2003. "Export-Platform
Foreign Direct Investment." NBER Working Paper, no. 9517.
Feenstra, Robert C. 1999. "Facts and Fallacies about Foreign Direct Investment." in
Martin Feldstein, ed. International Capital Flows, University of Chicago Press
and NBER, 331-350.
Feenstra, Robert C., and Gordon H. Hanson. 1996. "Foreign Investment, Outsourcing,
and Relative Wages." In The Political Economy of Trade Policy: Papers in Honor
of Jagdish Bhagwati, edited by Robert C. Feenstra, Gene M. Grossman and
Douglas A. Irwin. Cambridge, MA: MIT Press.
Feenstra, Robert C., and Gordon H. Hanson. 1997. "Foreign Direct Investment and
Relative Wages: Evidence from Mexico's Maquiladoras." Journal of International
Economics 42: 371-93.
Gomes-Casseres, Benjamin. 1990. "Firm Ownership Preferences and Host Government
Restrictions: An Integrated Approach." Journal of International Business Studies
First Quarter: 1-22.
Görg, Holger, and David Greenway. 2001. "Foreign Direct Investment and Intra-Industry
Spillovers: A Review of the Literature." Globalisation and Labour Markets
Programme, University of Nottingham 2001/37.
Grossman, Sanford J., and Oliver D. Hart. 1986. "The Costs and Benefits of Ownership:
A Theory of Vertical and Lateral Integration." Journal of Political Economy 94,
no. 4: 691-719.
53
Grossman, Gene M., and Elhanan Helpman. 1996. "Foreign Investment and Endogenous
Protection." In The Political Economy of Trade Policy: Papers in Honor of
Jagdish Bhagwati, edited by Robert C. Feenstra, Gene M. Grossman and Douglas
A. Irwin. Cambridge, MA: MIT Press.
———. 1994. "Protection for Sale." American Economic Review 84, no. 4: 833-50.
Hanson, Gordon H., Raymond J. Mataloni, and Matthew J. Slaughter. 2003. "Vertical
Production Networks in Multinational Firms." NBER Working Paper 9723, May
Helpman, Elhanan. 1984. "A Simple Theory of Multinational Corporations." Journal of
Political Economy 92: 451-71.
Helpman, Elhanan, Marc J. Melitz, and Stephen R. Yeaple. 2004. "Export Versus FDI
with Heterogeneous Firms." American Economic Review 94: 300-16.
Henisz, Withold. 2002. Politics and International Investment: Measuring Risks and
Protecting Profits. Cheltham, UK: Edward Elgar.
Hiscox, Michael J. 2004. "International Capital Mobility and Trade Politics: Capital
Flows, Political Coalitions, and Lobbying." Economics and Politics 16, no. 3:
253-85.
———. 2002. "Commerce, Coalitions, and Factor Mobility: Evidence from
Congressional Votes on Trade Legislation." American Political Science Review
96, no.3: 593-608.
Hummels, David, Jun Ishii, and Kei-Mu Yi. 2001. "The Nature and Growth of Vertical
Specialization in World Trade." Journal of International Economics 54: 75-96.
Hymer, Stephen. 1976. The International Operations of National Firms. Cambridge,
MA: MIT Press.
54
Imai, Kosuke, Gary King, and Olivia Lau, 2007. “Zelig: Everyone’s Statistical
Software,” http://GKing.Harvard.Edu/zelig.
Marshall, Monty G., Keith Jaggers, and Ted Robert Gurr. 2006, “Polity IV Project,
Political Regime Characteristics and Transitions, 1800–2004,” Maryland: Center
for International Development and Conflict Management, University of
Maryland, College Park).
Jensen, Nathan M. 2003. "Democratic Governance and Multinational Corporations:
Political Regimes and Inflows of Foreign Direct Investment." International
Organization 57, no. 3: 587-616.
Jones, Ronald W. 1971. "A Three-Factor Model in Theory, Trade, and History." In
Trade, Balance of Payments, and Growth, edited by Jagdish N. Bhagwati, Ronald
W. Jones, Robert A. Mundell, and Jaroslav Vanek. New York: American Elsevier
Publishing Company.
Johnson, Joel W. and Jessica S.Wallack. 2008. Electoral Systems and the Personal Vote
[Dataset] http://dss.ucsd.edu/~jwjohnso/espv.htm
Kang, CS Elliot. 1997. "US Politics and Greater Regulation of Inward Foreign Direct
Investment." International Organization 51, no. 2: 301-333.
Kobrin, Stephen J. 1987. " Testing the bargaining hypothesis in the manufacturing
sector in developing countries." International Organization 41, no.4: 609-638.
Li, Quan, and Adam Resnick. 2003. "Reversal of Fortunes: Democracy, Property Rights
and Foreign Direct Investment Inflows to Developing Countries." International
Organization 57, no. 1: 175-211.
55
Markusen, James R. 1984. "Mulitnationals, Multi-Plant Economies, and the Gains from
Trade." Journal of International Economics 16: 205-26.
Melitz, Marc J. 2003. "The Impact of Trade on Intra-Industry Reallocations and
Aggregate Industry Productivity." Econometrica 71: 1695-725.
Milner, Helen V., and Keiko Kubota. 2005. "Why the Move to Free Trade? Democracy
and Trade Policy in the Developing Countries." International Organization 59,
no. 1: 107-43.
Mitra, Devashish, Dimitrios D. Thomakos, and Mehmet A. Ulubasogflu. 2002.
"'Protection for Sale' in a Developing Country: Democracy Versus Dictatorship."
Review of Economics and Statistics 84, no. 3: 497-508.
Olson, Mancur. 1965. The Logic of Collective Action. Cambridge, MA: Harvard UP.
Peltzman, Sam. 1976. "Towards a More General Theory of Regulation." Journal of Law
and Economics 19, no. 2: 211-40.
Pinto, Pablo M. and Santiago M. Pinto. 2008. "The Politics of Investment: Partisanship
and the Sectoral Allocation of Foreign Direct Investment" Economics & Politics
20, no. 2: 216-254.
Romer, Paul. 1993. "Idea Gaps and Object Gaps in Economic Development." Journal of
Monetary Economics 32: 543-73.
Schmalensee, Richard. 1989. "Inter-Industry Studies of Structure and Performance." In
Handbook of Industrial Organization, Volume 2, edited by Richard Schmalensee
and Robert D. Willig. Amsterdam: Elsevier.
56
Sembenelli, Alessandro, and Georges Siotis. 2002. "Foreign Direct Investment,
Competitive Press and Spillovers: An Empirical Analysis on Spanish Firm Level
Data." Working Paper, November.
Stigler, George J. 1971. "The Theory of Economic Regulation." The Bell Journal of
Economics and Management Science 2, no. 1: 3-21.
van Buuren, S. and C.G.M. Oudshoorn. 2002. Multivariate Imputation by Chained
Equations. TNO Report PG/VGZ/00.038
Vernon, Raymond. 1971. Sovereignty at Bay: The Multinational Spread of US
Enterprises. New York: Basic Books.
Wei, Shang-Jin. 2000. "Local Corruption and Global Capital Flows." Brookings Papers
on Economic Activity 2: 303-54.
World Bank. 2003. Global Development Finance, Volume 1. Washington DC: World
Bank.
UNCTAD. 2004. World Investment Report. Geneva: United Nations.
Yeaple, Stephen R. 2003. "The Role of Skill Endowments in the Structure of US
Outward Foreign Direct Investment." Review of Economics and Statistics 85, no.
3: 726-34.
Yi, Kei-Mu. 2003. “Can Vertical Specialization Explain the Growth of World Trade?”
Journal of Political Economy 111, no.1: 52-102.