Farmers versus Financiers: Logrolling and the Political Economy
of Exchange Rate Overvaluation in Developing Countries
David A. Steinberg
Department of Political Science
Northwestern University
[email protected]
COMMENTS WELCOME!
January 18, 2007
Abstract: This paper aims to explain why overvalued currencies are so common in
developing countries. Overvaluation is a puzzling outcome: it contradicts the common
assumption that states want to maximize net exports; and it has harmful economic effects,
such as low growth and financial crises. The sectoral logrolling theory developed in the
paper argues that overvaluation is common because pivotal actors benefit from the sideeffects of overvaluation, such as currency stability and high government spending.
Sectors that favor undervaluation are unable to offer side-payments to potential coalition
partners. Overvaluation is common because logrolling creates support for overvaluation
among actors that care little about currency valuation. The likelihood of logrolling, and
thus overvaluation, depends on whether policy promises are credible or not. Logrolling
is subject to credibility problems, which are easier to solve when there are multiple veto
points in the political system. I predict that the interaction of two factors determines
currency valuation: the political influence of individual sectors, which affects the power
of coalitions; and veto points, which affect sectors’ ability to sustain politically effective
coalitions. The statistical tests, based on a panel data set of developing countries, support
these hypotheses.
The majority of developing states have used their policy instruments to keep their real
exchange rates above market value. The median currency in the developing world was
overvalued by 16% in the post-Bretton Woods period.1 The typical Latin American and
sub-Saharan Africa country’s currency was 44% above market value. Why, despite their
myriad differences, have so many developing countries converged on this policy choice?
Currency overvaluation is a puzzling outcome, whose popularity is poorly
explained by existing theories. The most prominent approach to exchange rate politics,
developed by Jeffry Frieden, argues that currency valuation pits nontradables producers
against tradables producers, with the latter opposed to overvaluation.2 Why are tradables
producers so prone to losing battles on currency valuation? This remains a mystery. The
assumption that undervaluation is universally desired remains dominant.3 It is
unimaginable from most political economy perspectives that a government would
unilaterally reduce its tariffs on all products for all countries and concurrently request all
foreign governments to raise tariffs on all of its products4, yet overvaluation has
equivalent effects, acting simultaneously as an export tax and a subsidy on imports.5 The
history of the International Monetary Fund (IMF) illustrates this gap between theory and
reality: created to prevent currency devaluation, it has spent the last generation
encouraging depreciation. This paper develops and tests a new theory that helps explain
the unanticipated prevalence of overvaluation.
One potential explanation for the predominance of overvaluation in developing
countries is that its beneficiaries are more politically powerful than its opponents. Some
1
The data refer to the Dollar Index, described below.
Frieden 1991.
3
Henning 1994; Destler and Henning 1989: 118; Stein 1982: 308; Milner 1997: 57; Gilpin 2001: 90.
4
Alt et al 1996.
5
Broz and Frieden 2001: 333.
2
1
conjecture that overvaluation is adopted in poor unequal societies as a means to improve
the purchasing power of the poor.6 Robert Bates also sees overvaluation as a means to
transfer income to urban consumers, though he puts greater emphasis on rent-seeking,
and structural political advantages of this group.7 The financial sector, which favors
overvaluation, is also thought to have structural advantages.8 These arguments suggest
that overvaluation occurs because it is in the interests of a particular segment of society
that has political advantages over their opponents.
The conventional explanations face difficulties reconciling exchange rate
“disprotection”9 and trade protection. If an actor is powerful enough to implement
overvaluation to improve purchasing power, it is hard to understand why protectionist
trade policies, which reduce purchasing power in a way that directly contradict the effects
of overvaluation, are also so common and frequently coincide with overvaluation.
More problematic, this theory cannot explain why overvaluation often harms its
supposed proponents. While it is likely that consumers and nontraded producers are
opposed to undervalued exchange rates, currencies are often so excessively misaligned
that even these actors suffer. Extreme levels of overvaluation contribute to a host of
injurious outcomes: low economic growth10, capital flight11, speculative attacks12, and
currency crisis.13 Incredibly, exchange rates are more than double their market value
12% of the time. Urban consumers and workers that desire increases in their purchasing
power should not advocate policies that consistently lead to slow growth and the
6
Huizinga 1997; Sachs 1989.
Bates 1981.
8
Bates and Lien 1985; Winters 1994.
9
Crystal 1994, 142.
10
Dollar 1992; Easterly 2001b; Acemoglu et al 2003.
11
Crystal 1994.
12
Leblang 2002.
13
Golfajn and Valdes 1999; Kaminsky et al 1997.
7
2
accompanied unemployment. It is equally hard to imagine that financiers would create
conditions favoring currency crises, given that such crises have “devastating effects” on
the financial sector.14 While these groups benefit from mildly overvalued currencies,
everyone loses with extreme overvaluation. Existing theories cannot explain why
overvaluation is so common, or why currencies are often damagingly misaligned.
The inability of previous arguments to explain the contradictory features of
currency policy suggests that these theories are, at best, incomplete. The theory of
sectoral logrolling developed in this paper takes these inconsistencies seriously, and in
doing so provides a more satisfactory theory of exchange rate politics. I argue that
overvaluation is common not necessarily because important groups benefit from
overvaluation itself, but rather because pivotal actors benefit from the side-effects of
overvaluation. Since overvaluation tends to be associated with currency stability and
high government spending, and most groups prefer these outcomes to unstable currencies
and low spending, overvaluation advocates are able to buy the support of swing groups
by offering them these policies. Few groups will be enticed by currency instability and
low spending, which are often necessary for undervaluation. Actors who prefer
undervalued currencies are unable to offer attractive side-payments to their coalition
partners, and hence have a hard time winning political battles. Overvalued currencies are
so common because actors that care little about currency valuation will commonly
support overvaluation. Logrolling increases the political influence of the proovervaluation coalition relative to the pro-undervaluation coalition.
Logrolling is subject to credibility problems, and requires political institutions
that constrain opportunism. When there are few veto points, actors can easily change
14
Corden 2001: 43.
3
policies in the future, so policy promises lack credibility. Logrolling is unlikely to occur,
and the pro-overvaluation coalition will become internally divided. Multiple veto points
help actor’s block transgressions. This makes commitments credible, enabling a large
logrolled coalition to form. These diverse groups trade favors, generating currency
appreciation. I hypothesize that overvaluation is least likely when two conditions
coincide: there are few veto points; and agricultural exporters, the group most strongly
opposed to overvaluation, are politically influential. Multiple veto points make it less
likely that agricultural exporters will succeed politically, and increase the likelihood that
the finance sector, the strongest advocate of overvaluation, will find their attempts to
implement overvaluation successful.
To test the theory I use more direct measures of currency valuation than used by
previous researchers. The results support the logrolling theory’s hypotheses: currency
valuation is affected by the interaction of sector size and veto points. Agricultural
exporters reduce overvaluation when there are few veto points, but have no effect on
currency valuation when there are many checks and balances. The international financial
sector is associated with overvaluation when there are several veto points, but when there
are few veto points, it has no effect. Before proceeding to the theory, it is necessary to
explain how governments manipulate their exchange rates.
I. Understanding Currency Valuation
The nominal exchange rate is the number of units of domestic currency required
to purchase one unit of foreign currency. Here we are primarily concerned with the real
exchange rate, which incorporates both the nominal exchange rate and differences in
4
prices across countries. Overvaluation refers to situations where the real exchange rate is
above market value: when a given bundle of domestic goods can purchase a larger
quantity of foreign goods than with a market-determined exchange rate.15 Overvaluation
increases the domestic price of nontradables relative to tradables goods. Analogously,
depreciation lowers the international price of domestic traded products relative to other
countries’ goods.16
The real exchange rate is a “policy variable” that is within the control of
policymakers.17 Governments do not set the real exchange rate directly, but affect it by
manipulating other policy instruments—most importantly, macroeconomic policy and the
choice of exchange rate regime. Controls on international capital movements, and sales
and purchases of foreign exchange reserves also affect the real exchange rate, but are less
significant, and are not discussed here for reasons of space and simplicity.
The currency regime refers to whether a currency’s nominal value is fixed to
another currency or whether it fluctuates independently. Fixed exchange rates are more
likely to be overvalued than floating ones.18 First, the abandonment of a fixed currency
peg typically implies devaluation. Second, inflation in developing countries almost
always exceeds inflation in the anchor currency country. Combining a fixed nominal
currency with domestic price increases that exceed those of foreign prices implies real
exchange rate appreciation. This has led recent researchers to suggest that the decision
15
Although currency valuation is a continuous concept, I often treat it as a dichotomous outcome for the
sake of simplicity. Although economists do not agree on the appropriate method for measuring the market
value of the exchange rate, I address this issue in the empirical section by using multiple measures of
overvaluation.
16
Frieden 1991.
17
Government policies have strong effects on the direction of movement of the real exchange rate for time
horizons between one and five years. Acemoglu et al 2003: 57; Easterly and Levine 1997: 1209; Broz and
Frieden 2001; Frieden and Stein 2001; Krugman and Obstfeld 2003, esp. 349; Edwards 1989.
18
Schamis and Way 2003; Frieden and Stein 2001; Blomberg et al 2005.
5
about the exchange rate regime is the decision about the exchange rate level, and that the
two issues are virtually inseparable.19
Although fixed exchange rates are often more appreciated, the relationship
between the currency regime and currency level is weak and indirect. Fixed exchange
rates are neither necessary nor sufficient for overvaluation. China is one prominent
example of a country with a pegged but undervalued currency. Similarly, some countries
have overvalued exchange rates even when they do not peg—Brazil, for example.
Shambaugh points out that fixed currencies are only estimated to be 8 to 13% more
appreciated on average than floating ones, and thus “there is no necessary link between
fixed exchange rates and overvalued real exchange rates”.20 In the dataset used in this
study, the correlation between a fixed exchange rate dummy and more direct measures of
the exchange rate level is positive, but not particularly high: 0.37 for the Dollar Index and
0.04 for the Black Market Premium (see section IV). The reality thus lies somewhere
between early claims that these are separate dimensions of currency policy21 and recent
analyses that view them as deeply connected and inseparable. The exchange regime
affects and constrains the exchange rate level, but since there is extensive variation in real
exchange rate levels within a given exchange rate regime, it imperative to treat these as
distinct policy choices.
Beyond the exchange rate regime, macroeconomic policy is the most important
tool that governments have to affect the real exchange rate. Expansionary
19
Frieden and Stein 2001; Pasco-Font and Ghezzi 2001, 250.
Shambaugh 2004, 284.
21
Frieden 1991, 1994.
20
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macroeconomic policy—i.e. more government spending—increases inflation.22 Inflation
raises nontradable good prices, but has less effect on the prices of traded goods, which
are set in world markets.23 This relative price change is, by definition, real appreciation.
The correlation between log(inflation) and currency valuation is 0.10 for the Dollar Index
and 0.06 for the Black Market Premium.
Both pegs and inflationary spending individually make overvaluation somewhat
more likely, though their effects are not particularly strong on their own. It is possible for
a state to have either high spending or a peg without the other, but use other policy
instruments to maintain an undervalued currency. However, when a country’s exchange
rate is fixed in value and macroeconomic policies are expansive, overvaluation becomes
virtually unavoidable.24 This policy mix generates more extreme overvaluation than any
other. Inflation’s correlation with both measures of currency valuation is above 0.85
when exchange rates are fixed. The combination of expansionary macroeconomic policy
with fixed exchange rates negates governments’ ability to maintain an undervalued
currency. The incompatibility of these three policies—expansionary macroeconomic
policy, fixed exchange rates and undervaluation—plays an important role in currency
politics because actors are forced to choose among conflicting objectives.25
22
Fiscal expansion is typically financed by monetary expansion in developing countries, which leads to
inflation. This occurs because these countries’ domestic bond markets are underdeveloped. McKinnon and
Schnabl 2004; Krugman and Obstfeld 2003.
23
However, since overvalued currencies makes imports cheaper this slows down inflation to some extent.
Although the relationship between inflation and currency valuation is multi-faceted, on the whole, high
levels of government spending tends to lead to currency appreciation.
24
Bordo and Schwartz 1996; Edwards 1989; Krugman and Obstfeld 2003.
25
The logic of this incompatibility is similar to the logic of the “unholy trinity”, which asserts that
independent monetary policy, pegs and capital mobility are mutually incompatible. The reason the unholy
trinity policies are incompatible is that combining currency pegs and expansionary monetary policy leads to
overvaluation, which is unsustainable because it will lead to capital flight and force one of these policies to
be abandoned. Capital controls are relevant to the unholy trinity because they affect governments’ ability
to maintain an overvalued peg. It is less relevant here because pegs combined with high spending will lead
to overvaluation regardless of whether or not capital controls are in place. Edwards 1989.
7
II. Preferences
Conventional wisdom holds that social divisions over currency valuation pit
tradables industries against nontradables sectors.26 This is a reasonable depiction of
exchange rate level preferences, and would hold true if currency valuation was chosen
independently from other policies. This is not the case. Currency valuation is controlled
through policy instruments—the exchange rate regime and macroeconomic policy—that
influence other economic indicators as well. In addition to their effects on currency
valuation, the exchange rate regime also affects currency volatility, and macroeconomic
policy influences national business conditions. Thus, manipulating exchange rates
inevitably affects actors in a multitude of ways. When choosing whether or not to
support or oppose overvaluation, actors must take into consideration not just the effects
of currency valuation on their income, but also whether they will be able to receive their
preferred currency regime and macroeconomic policies. Understanding coalitions in
exchange rate politics requires combining Frieden’s insights with more explicit
consideration of the intensity of actor’s preferences across these three policies.
Preferences are defined as intense when profits are strongly and directly tied to
that policy and no other policies can have similar effects on that group’s income; when a
policy has limited impact on a sector’s income, that impact is indirect, or other policies
can achieve similar effects with less political effort, preferences are considered weak. In
the following discussion, sectoral preferences on the exchange regime and
macroeconomic policy refer to preferences on these policy tools in terms of their effects
on factors other than the currency’s value. The relevant trade-off for the currency regime
26
Frieden 1991, 1994.
8
decision is currency stability versus national policy autonomy.27 For macroeconomic
policy, the issue is whether the industry values greater domestic demand and fiscal
assistance more or less than low inflation.
The tradables-nontradables division will not always characterize currency
valuation preferences. Rather, tradables producers will often support policy packages
that involve overvaluation even though they prefer undervaluation since the desirable
side-benefits from overvaluation often exceed the benefits of undervaluation.
Overvaluation often comes with currency stability and/or fiscal expansion, and
undervaluation is typically associated with unstable exchange rates and/or contractionary
macroeconomic policy.28 The desire to reduce currency volatility or to receive fiscal
assistance is often stronger than the desire for currency undervaluation, so those who
prefer undervaluation may end up advocating currency appreciation. I show this by
considering five sector’s preferences across these various issues, which is summarized in
Table 1.
[Table 1 around here]
Import-competing sectors desire currency depreciation to improve their ability to
compete in the national economy. However, their preference for undervaluation is weak
because tariff protection has the same effects and can be achieved with less cost.29
Import-competing groups should prefer floating currencies since this reduces
international trade, but because this effect is indirect, their preference is weak.30 They
should strongly prefer high government spending: import-competing industries will profit
27
Frieden 1991; Leblang 1999; Broz 2002.
The relevant actors likely recognize this fact as well.
29
Gowa 1988.
30
Broz and Frieden 2001, 326; Frieden 1991, 445.
28
9
from the resulting increase in domestic demand, and their ability to successfully compete
against cheap foreign imports will directly improve with fiscal assistance, such as
subsidies. The costs of overvaluation to this group are smaller than the benefits of high
spending. When overvaluation is combined with high spending, but the competing policy
program packages undervalued currencies with low spending, import-competing sectors
are likely to support overvalued exchange rates.
While exporters also stand to benefit from undervaluation, only agricultural
exporters are likely to have a strong preference for this outcome. Manufacturing
exporters rely more heavily on imported inputs into production, making their preference
for undervaluation more ambiguous.31 Most manufactured products are relatively
specialized and price increases of such goods can be easily passed-through onto the
consumer, reducing sensitivity to the exchange rate level. Since agriculture products are
more standardized, they compete primarily on price. Agricultural exporters’ preference
for undervaluation should be an intense one, while manufactured exporters should hold
only a weak preference for this outcome.32 Exporters of specialized products are more
sensitive to currency volatility than exporters of agricultural commodities and thus even
though both groups should prefer fixed exchange rates, only manufacturing exporters
should hold this preference intensely.33 Both farmers and manufacturers have an intense
preference for high government spending because they directly benefit from improved
business conditions, as well subsidies and other government investments in their industry,
which lower their production costs and increase their profits.
31
Frieden et al 2001, 34.
Broz and Frieden 2001; Shambaugh 2004; Helleiner 2005.
33
Broz and Frieden 2001.
32
10
Manufacturing exporters will often become supporters of overvaluation to enjoy
its concomitant features: currency stability, and high government spending. The benefits
of these policies exceed the losses that overvaluation brings. Agricultural exporters
strongly prefer currency depreciation, and are the only actor expected to strongly and
consistently advocate for undervaluation.
Nontradables producers weakly prefer flexible exchange rates because this
enhances monetary autonomy, though the exchange rate regime has only indirect effects
on this group.34 Nontradables producers are “dependent upon domestic business
conditions” and strongly prefer high to low government spending since this boosts
demand for their products.35 They benefit from overvalued currencies, which lower the
price of imported inputs and reduce their costs. This preference is relatively weak: those
that purchase few foreign goods have limited interest in the exchange rate’s value, and
even those that do benefit in an equivalent manner from government subsidies.
The financial sector prefers low government spending since they benefit little
from fiscal assistance, are relatively unaffected by macroeconomic conditions, and prefer
low inflation.36 However, since financial actors are able to adjust their activities in ways
that allow them to continue to reap high profits in a hyper-inflationary environment, their
preference for low spending should be relatively weak.37 Bankers intensely prefer fixed
exchange rates: “though bankers dislike inflation, they dislike instability even more”,
notes Crystal.38 Pegs improve banks’ ability to attract commercial lending from abroad39,
34
Frieden 1991, 445.
Frieden 1994, 85.
36
Posen 1995; Broz 2002; Frieden 1991, 225.
37
Posen 1995.
38
1994, 145.
39
Shambaugh 2004.
35
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and reduce the risk of international transactions.40 Delegating macroeconomic policy to
foreign governments by pegging the exchange rate also improves credibility with
international investors.41 Overvaluation also provides huge benefits to the financial
sector. Financiers benefit from overvaluation because this enables them to purchase
more assets from abroad.42 More importantly, it is common for financial institutions in
developing countries to have debt denominated in foreign currencies. Depreciation
destroys the value of these assets, increases their debt burden, and in turn contributes to
banking failures.43 The international financial sector is likely to be staunchest advocate
of overvalued exchange rates, as it strongly benefits from both overvaluation and pegs.
Although finance and nontradables benefit from overvaluation, more
overvaluation is not always better, even for them. It is unlikely that they, or any other
sector, benefit from grossly misaligned currencies. Extreme levels of overvaluation,
which typically result from the coupling of high spending and fixed exchange rates,
generate economic problems that hurt these groups. The ideal outcome for these sectors
is mild overvaluation associated with either expansive macro policies or currency pegs—
not both. Nontraded producers prefer floating exchange rates, and oppose extreme
overvaluation because it reduces economic growth and thus their sales. Financiers oppose
high spending, and fear the speculative attacks and forced devaluations that frequently
come with extreme overvaluation.
There are several reasons why tradable-nontradable cleavage will not always
accurately describe the politics of currency valuation. Among tradable producers, only
40
Frieden 1991, 444.
Broz 2002.
42
Frieden 1991.
43
Shambaugh 2004; Woodruff 2005; Walter 2006; Helleiner 2005, 27.
41
12
agricultural exporters are likely to consistently favor undervaluation. Even though other
tradables producers prefer currency depreciation, they will commonly support policy
packages involving overvaluation. These sectors benefit more from overvaluation’s sideeffects than they lose from currency appreciation. The financial and nontraded goods
industries are opposed to undervalued exchange rates, but also wish to avoid extreme
overvaluation. Next, I explore some implications of this argument, seeking to explain
why overvaluation is so common, and why despite its harmful economic effects,
currencies are occasionally greatly overvalued.
III. The Sectoral Logrolling Theory
A. Why is Overvaluation so Common?
Logrolling is defined as acting contrary to one’s preferences on a given policy in
order to get someone else to do the same on a different issue.44 Logrolling has two
requirements: two actors must have opposing preferences on two policies (i.e. actor I
supports X, opposes Y; actor II opposes X, supports Y); and the policy issue which one
cares most about must be the one that the other cares less about (actor I’s priority is X;
actor II’s is Y). Logrolling is best known for its application to legislative behavior: for
example, a legislator from the industrial heartland may support wheat subsidies so that
the rural legislator will return the favor and vote for steel tariffs. Although formal trading
of votes in a legislature is the clearest manifestation of logrolling, whenever these two
conditions are met, there is an incentive for logrolling. Going against one’s immediate
interest on the less-important policy in order to receive the other actor’s support on the
high-salience policy will improve each actor’s welfare. The benefit received by
44
This paragraph borrows heavily from Riker and Brams 1973.
13
implementing the policy that you care more about will exceed the cost from going against
your interests on the lower-salience policy.
Currency politics is likely affected by logrolling because different sectors disagree
about whether an overvalued or undervalued currency is desired, and the intensity with
which that preference is held varies across sectors. Thus, currency valuation outcomes
are not necessarily the result of actors’ interest in that outcome itself. Many cases of
overvaluation are likely to be the result of its attractive side-benefits. It is easier to attract
supporters by offering them subsidies and government investments than by proclaiming
fiscal prudence. Similarly, few groups prefer unstable currencies to stable ones.45
Proponents of overvaluation are able to offer both high spending and currency stability
simultaneously, enabling them to logroll with tradables producers. For example,
manufacturing exporters may support overvaluation against its preference in return for
the financial sector’s support of high spending, which it opposes. Doing so allows each
to forego a lower-salience policy and implement an intensely preferred policy, with net
gains for each. The positive externalities of overvaluation lead actors that would
otherwise be indifferent on this issue to join the pro-overvaluation coalition. These sidepayments increase support for overvaluation, making it more likely that the coalition
favoring overvaluation will be powerful enough to succeed in implementing this policy.46
Part of the reason why undervaluation is less common than overvaluation is that
the former requires one of either a floating exchange rate or fiscal prudence (see Section
I). This inability to use both currency stability and high spending is a serious political
45
Those that do prefer currency instability or low spending tend to do so only weakly.
Others have pointed out that policies, such as tariffs, can reduce opposition to overvaluation. Woodruff
2005; Frieden et al 2001; Gowa 1988. The focus here, on policies that unavoidably influence currency
valuation, is slightly different. These policies do more than reduce opposition—they actually create
support for overvaluation among actors who would otherwise oppose it.
46
14
liability. Nontraded sectors are typically unenthused with the side-effects of undervalued
currencies. Hence, they will rarely be willing to support undervaluation. It is nearly
impossible for proponents of undervaluation to enlarge their coalition through logrolling.
The side-effects of currency policies increase political support for overvaluation.
Many cases of overvaluation would not exist without the support of actors that do not
benefit from overvaluation. If the prediction that logrolling helps account for much
overvaluation is correct, then currency outcomes will depend crucially on the credibility
of commitments.
B. The Credibility Problem
Logrolling will not occur automatically in exchange rate politics. Sectors must
worry about their partners’ ability to defect because there is a time-inconsistency
problem. Actors that favor overvaluation have an incentive to ex post renege on ex ante
promises. It is possible for finance or nontradables to implement overvaluation with
others’ initial consent but then either reduce spending or exit the fixed regime.47 The
financial industry is opposed to high spending, so they might promise expansive fiscal
policy, but renege on this promise after-the-fact since they will be better off with low
spending. The same holds with nontradables producers: their opposition to fixed
exchange rates means that others must consider whether they will offer fixed rates and
then not implement it.
Logrolling will not occur if sectors that prefer undervaluation have reason to
expect that high spending or fixed currencies will not be supplied. Sectors that favor
undervaluation will only support overvaluation when they expect their coalition partners
47
Overvaluation likely requires either a fixed currency or high government spending, but not both. Thus,
overvaluation can be maintained even if the currency floats or if macroeconomic policy is contractionary.
15
to uphold their part of the agreement—pegs and high spending. If their coalition partners
do not uphold their part of the agreement, the logrollers will incur the costs of
overvaluation without receiving the desired side-benefits. In such a case, logrolling
would make these actors worse off than if they supported their true interest,
undervaluation. Tradables producers will only logroll when they believe that their
coalition partners lack the ability to renege on their promises. Support for overvaluation
rises as commitments become more credible.
This logic can best be illustrated by comparing actors’ expected utility from a
policy combination of overvaluation, high spending and pegs to their expected utility
from undervaluation.48 Figure 1a displays the expected utility gains from overvaluation
for the five sectors, showing that it depends on their expected probability that their
partner will comply. In this case, it is the financial sector whose credibility is at stake,
and sectors must evaluate whether it will renege on its commitment to supply high
spending.49 To create this figure, intense and weak preferences were given utility values
of 3 and 1 units, respectively, though the main implications hold across a wide range of
values, including the extreme case where all policies are weighted equally.50
[Figure 1 around here]
Most sectors’ slopes are positive. The figure supports the intuition that agriculture
always prefers undervaluation to overvaluation. Manufactured exporters, import48
The latter is defined as an actor’s average utility from three feasible undervaluation policies:
undervaluation with fixed currency, high spending, and neither.
49
The financial sector was chosen because it is the strongest advocate of overvaluation, and thus more
likely to be involved in logrolls in such a capacity than other nontraded producers. The main conclusions
hold when the issue is the nontraded sector’s credibility to supply a fixed regime.
50
To illustrate, when compliance is 95% probable, the import-competing sectors’ utility from this
overvaluation combination is their intense benefit from high spending (3) multiplied by that probability, for
a total of 2.85. Their expected utility from undervaluation is the weak benefit received from three cases of
undervaluation (1), two instances of floating exchange rates (1), and one case of high spending (3), divided
by three (2.67). The net gain is 0.18
16
competing and nontradables sectors all strongly prefer overvaluation to undervaluation
when they expect finance to comply. By contrast, the latter two prefer undervaluation to
overvaluation when they expect finance to not implement high spending, and
manufacturing is indifferent. The financial sector will not attract support for
overvaluation unless they credibly commit to high spending. When they cannot do so,
these swing groups are more likely to favor undervaluation. The negative slope for the
financial industry results from the utility gain they receive from withholding promised
spending. Support for overvaluation rises with the expected probability of compliance.
C. The Rational Harm of Overvaluation
The discussion thus far has left aside the fact that combining high spending and
fixed exchange rates typically generates extreme levels of overvaluation that compromise
economic performance. Currencies are often so overvalued that they are harmful to even
the original proponents of high currencies. If no major actor want extreme overvaluation,
why does it occur? Logrolling seems particularly well-suited to explain outcomes that
seem irrational from the perspective of a single decision-maker.51 This seems an instance
of the general “paradox of logrolling”: “each [vote] trade is individually advantageous to
the traders, [but] the sum of the trades is disadvantageous to everybody, including the
traders themselves”.52 Currencies are often more overvalued than any group wants
because each group needs to support the policies of other groups. Doing so requires
increasing spending and fixed currencies beyond the ideal level for any sector, which
leads to more highly valued currencies than any single actor wants.
51
52
Snyder 1991, esp. 43-49.
Riker and Brams 1973, 1236.
17
Taking these costs seriously, Figure 1b adds a term reflecting the disutility from
extreme overvaluation (pegs combined with high spending) to the previous figure. This
private cost to each actor is assumed to be large: two-thirds the value of an intense
preference. This lowers each actor’s net benefits from extreme overvaluation. But three
actors—finance, nontradables, and manufacturing—still prefer overvaluation to
undervaluation. The result that credibility increases support for overvaluation among
swing groups continues to hold, though this effect weakens. 53 On the other hand, finance
gains more than before from reneging, reflecting the fact that it is much better off with
mild overvaluation than with extreme overvaluation, once the costs of the latter are taken
into account.
Consistent with the intuition that logrolling is bad for society as a whole, the total
utility from extreme overvaluation is less than total utility from undervaluation in this
example. Even though overvaluation is harmful to society as a whole, a majority of
sectors still prefer this outcome to the alternatives, because of its attractive side-benefits.
Putting these pieces together, the following conclusion emerges: no one wants extreme
overvaluation, but this outcome still enhances the utility of actors that logroll. Logrolling
can explain why currencies are often excessively overvalued.
D. Veto Points
According to the logrolling argument, sectors’ ability to make credible
commitments to one another is a key determinant of social support for overvalued
currencies. National political institutions are likely to be an important determinant of
53
This is true so long as the utility from an intense preference exceeds the private costs of overvaluation.
For all such values, it is also the case that finance and manufacturing gain from overvaluation.
18
actors’ ability to break policy promises, and thus their credibility.54 The institutionalist
literature points to several specific institutional arrangements that promote credibility and
logrolling: legislative committees with veto power55; cartelized regimes56; separation of
powers57; federalism and decentralization58; consensus institutions.59 All these disparate
institutional forms share a common element: multiple veto points. The number of veto
points should affect logrolling by shaping the likelihood of logrolling.
Veto players are actors whose consent is required to implement and change
policies.60 George Tsebelis and others have suggested that as the number of veto players
rises, policy change becomes less likely because the number of actors that are capable of
preventing policy changes is greater.61 Policies can change quickly when there are few
checks and balances, so there is little reason to expect an actor to continue implementing
a policy that they oppose. Multiple veto reduce actors’ ability to renege by providing
more opportunities to block unfavorable adjustments. Thus, commitments are more
credible when there are many veto points than when there are few.62 When actors know
that they can prevent others from defecting, forming stable coalitions with diverse actors
becomes easier.63
As the number of veto points rises, it is more likely that a sector that disagrees
with the attempted changes in macroeconomic or currency policies will control a veto
54
Weingast and Marshall 1988.
Weingast and Marshall 1988.
56
Snyder 1991.
57
Cowhey 1993; Martin 2000.
58
Weingast 1998; Mansfield and Snyder 2002.
59
Gourevitch and Shinn 2005.
60
Their ability to veto may result either because of constitutionally-given power or because they are
empowered by the political game, such as when there are coalition governments. Tsebelis 2002.
61
Tsebelis 2002; Kastner and Rector 2003; Spruyt 2005.
62
Henisz 2000; North and Weingast 1989, 829; Tsebelis 2002, 7, 207-208.
63
Gourevitch and Shinn 2005.
55
19
point. Advocates of overvaluation become increasingly likely to comply with their
promises when the number of institutional checks rises. For example, with many veto
points, import-competing groups can be more confident that finance lacks the ability to
cut spending. By contrast, when only a single veto point exists, finance will have more
leeway to do as it pleases in the future, regardless of what it promised others in the past.
Assuming constant incentives for opportunistic behavior, multiple veto points make
commitments more credible by reducing the ability to change policies unilaterally. Since
credible commitments imply greater incentives for logrolling, multiple veto points
broaden support for overvaluation.
E. Hypotheses
Comparing the explanatory power of the logrolling theory with alternative
approaches to currency politics requires clarifying each theory’s predictions. Bates’ rentseeking argument suggested that autocratic regimes choose overvaluation to appease poor
urban consumers. It predicts that overvaluation is most likely in counties with autocratic
regimes, large urban populations and economic inequality.64
Frieden’s sectoral theory, which serves as the foundation of the sectoral logrolling
theory, posits that overvaluation becomes more likely as the political influence of the
finance and nontradables sectors rises, and becomes less likely when tradables sectors are
politically influential. The logrolling theory does not disagree: currency valuation should
indeed reflect powerful actors’ currency valuation preferences. The power of farmers
and financiers should be particularly important, due to their intense preferences.
However, individual sectors do not usually dictate policy alone. They typically rely on
the support of others. The need to build coalitions with other sectors means that two
64
Bates 1981; Easterly 2001a; Oatley 2003.
20
factors together determine the probability of overvaluation: the political influence of
individual sectors, which affects the power of coalitions; and political institutions, which
affect sectors’ ability to sustain politically effective coalitions. Whether farmers or
financiers win the contest over exchange rate policy depends on their respective political
influence, but also on whether political institutions make them attractive coalition
partners.
Undervalued exchange rates are more likely when the agricultural export sector,
the only actor to unambiguously prefer undervaluation, is politically influential than
when it is not. A powerful agriculture sector is not likely to be sufficient for
overvaluation, however. Agricultural exporters will often face great difficulties
convincing others to forego the side-benefits of overvaluation. When it’s political
opponents can credibly commit to logrolling, agriculture will be the only sector to
support undervaluation. When there are many veto points, a broad logrolled proovervaluation coalition is likely to form, and it is unlikely that agriculture will be capable
of competing against them.
Agriculture’s inability to offer side-benefits will be a much less severe handicap
when the policy promises of their opponents lack credibility. Other tradable producers,
and even some nontraded sectors, may favor undervaluation currencies when, because of
few veto points, commitments lack credibility. A political system with few checks and
balances will exacerbate divisions within the overvaluation coalition, and make
agriculture a more attractive coalition partner. Currency valuation is affected by the
interaction of agricultural influence and the number of veto points. Agricultural
21
influence will have limited impact on currency valuation when there are many veto
players, but its effect will be stronger when there are few veto points.
Hypothesis 1: Overvaluation is least likely when the agricultural export sector is
politically influential and there are few veto points.
Multiple veto points have paradoxical effects on the financial sector, increasing
their ability to avoid their least desired outcome, undervaluation, while at the same time
making it less likely that they will receive their most favored outcome, mild
overvaluation. The financial sector’s attempt to avoid undervaluation is most likely to fail
when there are few veto points. Bankers are more likely to gain industry’s political
support when such opportunism can be blocked. Finance becomes more likely to succeed
at implementing overvaluation when there are many veto points.
However, with multiple veto points, the financial sector is likely to be associated
with currencies that are more overvalued than they desire. A strong financial sector in a
system with few checks and balances has less need to pay off other actors, and can
implement its preferred outcome: mildly overvalued exchange rates. Commitment
devices raise the extent to which finance supplies policies that they oppose. This higherthan-desired spending leads to excessive overvaluation. In order to avoid the worst-case
scenario, undervaluation, the finance sector will spend more than they themselves desire
when there are several veto points, and this logrolling will lead currencies to become
more highly valued than they would choose alone. Extreme overvaluation is most likely
when finance is strong, and when it logrolls with other sectors.
Hypothesis 2: Overvaluation is most likely when the financial sector is politically
influential and there are many veto points.
22
The logrolling theory predicts that political institutions and credible commitments
mediates the relationship between sectoral influence and currency valuation.
IV. Methodology
To test these hypotheses about the determinants of currency valuation, I use data
for all developing countries since 1973 for which data was available. 1973 was selected
as the starting date since this was when the current international monetary (non-)regime
came into being. 1995 was the most recent year with data on all relevant variables.
A. Dependent Variables
Much political science research uses the exchange rate regime as a proxy for currency
valuation.65 This is problematic because currency valuation and the exchange rate regime
are distinct concepts that are far from perfectly correlated. I use two different variables
that have so far been employed mainly in Economics.
The first measure of the dependent variable is the black market exchange rate
premium (BMP). This is defined as the percentage difference between the official
exchange rate and the exchange rate that is used in black market transactions. With real
overvaluation, imports become more attractive to purchase on the black market than at
the less appreciated official rate, which typically leads to large BMPs. Second, the Dollar
Index (DI)66 is the ratio of a country’s actual price level and the price level that is
statistically predicted based on national economic characteristics, such as income levels.
Higher-than-predicted price levels means that nontraded good prices are high relative to
65
For example, Frieden et al 2001. Those hypothesizing that currency level interests influence currency
regime decisions also use currency regime data. Schamis and Way 2003; Blomberg et al 2005; Shambaugh
2004.
66
Dollar 1992.
23
traded goods prices—real overvaluation, by definition. Since policies that contribute to
real appreciation (depreciation) raise (lower) both the BMP and the DI, economists have
used both the DI and BMP as measures of currency overvaluation.67 These are more
valid measures of exchange rate valuation than those previously used in IPE.68
One important difference is that the DI captures variation in exchange rates from
extreme overvaluation to extreme undervaluation while the BMP ranges from extreme
overvaluation to market value. The BMP does not differentiate market-valued exchange
rates from undervalued ones since no one would pay more for currency on the black
market in situations of undervaluation. Using both variables will facilitate assessing
robustness. It will also allow us to ascertain whether, as predicted, some sectors prefer
mild overvaluation to both undervaluation and extreme overvaluation. A variable that is
positively associated with the DI but negatively associated with the BMP would be
evidence for a preference for currencies at market value or slightly above market value.
Following Easterly, I will use the logged values of the DI and BMP.69
B. Independent Variables
Sectoral political influence is measured as the sector’s share of national income.
More wealth implies more political power: advocates of certain policies should be
politically stronger and more numerous when the share of national income that comes
from that sector is larger.70 These measures, though imperfect, are the most sensible and
67
See Acemoglu et al 2003; Dornbusch et al 1983; Easterly 2001b; Easterly and Levine 1997, 2003;
Edwards 1989; Rodrik and Rodriguez 1999; Kiguel and O’Connell 1995.
68
Another option would be to use the change in the nominal exchange rate, as in Frieden’s 2002 study of
European monetary relations. Unlike European countries, not all developing countries have the same
anchor currency. For this reason, and because there are important cross-national differences in
overvaluation at the initial period, Frieden’s measure is inapplicable in this context.
69
Easterly 2001b. Both variables were obtained from Easterly 2001a.
70
Rogowski 1989.
24
commonly used measures available.71 Using these measures will also facilitate
comparison between the logrolling theory and alternative sectoral arguments. To reduce
potential endogeneity problems, the independent variables are lagged one year.
The influence of the agriculture export sector is measured as agriculture raw
material exports/GDP. I use services/GDP to proxy the effects of the nontraded sector
because the service industry is the paradigmatic example of nontradable production. For
finance, I use Leblang’s measure of the size of the international financial sector—the
yearly total of international borrowing of bonds and loans—and divide this by GDP.72 I
will use imports/GDP as one measure of the influence of import-competing sectors. This
variable must be evaluated with caution because many imports do not compete with
domestically-produced products, and may instead be used as inputs into production. I
also include manufacturing/GDP since this industry produces tradable goods that
typically compete with imports. Since the manufacturing sector also has an interest in
exporting, that variable, as well as non-agricultural exports/GDP, are used to evaluate the
effects of exporting interests on policy.73 Following common practice, checks is the log
of the number of veto points from the Database of Political Institutions.74
Several control variables are used in the analysis. To test the rent-seeking
hypotheses, I use the Deniger-Squire gini inequality index, the Polity democracy score,
and the share of the population living in urban areas. I control for national income, and
the terms of trade to address the effects of economic size and changes in economic
71
See Broz and Frieden 2001; Frieden 2002.
Leblang 1999.
73
These variables are taken from the World Bank’s World Development Indicators.
74
Keefer and Stasavage 2003.
72
25
fundamentals.75 As the IMF typically makes currency depreciation a condition for a loan,
I include an IMF dummy that signifies that a country is under an IMF program.76 I also
control for the level of capital controls, using Quinn’s measure of financial openness
(financial open).77 A time trend variable and decade dummies were included to prevent
spurious regression, which may occur since time is correlated both with independent and
dependent variables.78 Table 2 displays the summary statistics for all the variables.
C. Method
Given the structure of that data, it is most appropriate to use ordinary leastsquares regression with panel-corrected standard errors (PCSEs) to correct for panel
heteroskedasticity and first-order autorcorrelation (AR1). For data with twenty or more
time-periods, PCSEs are more accurate than alternative panel data models, such as
feasible generalized least squares (FGLS). PCSEs are also better able to cope with issues
of contemporaneous correlation, which is likely to be an important issue here, as
economic shocks at individual time periods should affect many countries’ exchange
rates.79 The next section presents the results using these estimation techniques.80
[Table 2 around here]
V. Results
The results presented in the following tables and graphs confirm the expectations
of the sectoral logrolling theory. The first two models of Table 3 estimate the effects of
75
Data were obtained from Easterly 2001a.
From Vreeland 2003.
77
Quinn 1997.
78
Several of the variables were obtained from Milner and Kubota 2005.
79
Beck and Katz 1995 & 2004.
80
A multivariate-augmented Dickey Fuller test—a panel version of the Dickey Fuller test for unit roots—
revealed that non-stationarity is not likely to be a concern.
76
26
sector size on currency valuation. As expected, agricultural exports and non-agricultural
exports each significantly reduce both the log(BMP) and log(DI). Increasing agricultural
exports/GDP by 10% reduces the expected value of the DI by nearly one point, and
reduces the BMP by over three percent. Manufacturing significantly reduces the DI,
though its effect on the BMP is not significant. Surprisingly, more imports are associated
with higher values of the DI. Since not all imports compete with domestic products, this
result likely reflects producers’ desire to buy cheap inputs, rather than the effect of
foreign competition. Services and finance both have positive but insignificant
coefficients for the DI. For the BMP, services is significant and negative, while finance
is negative, and approaching significance (p=0.14). The claim that these sectors have
unconditional preferences for overvaluation seems inaccurate. Their positive association
with the DI indicates they probably oppose undervaluation, but their negative relation to
the BMP suggests hostility to extreme overvaluation.
[Tables 3-4 & Figure 2 around here]
To test the hypotheses that veto players condition the relationship between
sectoral influence and overvaluation, models 3 and 4 add checks and its interactions with
agriculture and finance to the original model. The significant negative coefficients on
agriculture in the two models suggest that agriculture reduces overvaluation when there
are few veto points. The interaction between agriculture and checks is significantly
positive in model 3. Thus, the negative effect of agriculture on the DI weakens as checks
increases. Figure 2a displays the 95% confidence intervals for the marginal effects of
27
agriculture on log(DI) at the different levels of checks.81 That graph shows that
agriculture significantly reduces log(DI) when there are very few veto points, but ceases
to have any significant effect when there are multiple veto points. With a large
agricultural sector (90th percentile), moving from the minimum to maximum of checks is
predicted to reduce the DI by 18 points. Agriculture significantly reduces log(BMP) for
most values of veto points, and although the interaction term is not significantly positive,
Figure 2b shows that the marginal effect of agriculture on log(BMP) becomes
insignificant at very high levels of checks. The following can be concluded: when there
are very few veto points, the agricultural export sector successfully promotes
undervaluation (reduces the DI and BMP); when there are an intermediate number of
veto points, agriculture helps move the exchange rate from overvalued to market value
(reducing the BMP); agriculture has no effect on currency policy whatsoever when there
are many checks and balances.
Models 3 and 4 demonstrate that the international financial sector promotes
overvaluation only when there are multiple veto points. The insignificance of finance in
model 3 suggests that this sector has no significant effect on log(DI) when there are few
veto points, but the positive and significant interaction term implies that the marginal
effect of finance grows as there are more checks and balances. Figure 2c shows that this
sector has a significant effect on currency policy only when there are more than two
checks and balances in the political system (checks = 1). Model 4 shows that finance
actually reduces log(BMP) when there are few veto points. The positive significant
interaction term means that this sector becomes increasingly associated with higher
81
These figures were created in STATA using the commands suggested by Brambor et al 2006, which
retrieve information from the variance-covariance matrix to calculate conditional standard errors. A
marginal effect is significant when the entire confidence interval is above zero.
28
values of log(BMP) as checks rises. Although the confidence intervals are quite large,
Figure 2d shows that the marginal effect of finance goes from negative to positive rather
strikingly. When there is only a single veto point (checks = 0), a standard deviation
increase in finance is predicted to reduce the BMP by about 2 points, yet with six veto
points (checks = 1.8), increasing finance by a standard deviation is predicted to increase
BMP 2 points. These results suggest that the financial sector does not promote
overvaluation when there are few checks and balances, and may even be associated with
undervaluation, yet this industry is a force for currency appreciation when there are
several veto points.
A number of sensitivity checks were performed in Table 4, and these indicated
that the findings are quite robust. Models 5 and 6 add regional dummies to the previous
models to address potential region-specific effects. The next two models use panelspecific AR1, allowing each country to have its own autoregression coefficient. In both
cases, the DI results are, if anything, stronger, though the BMP results are weaker.82 The
results are identical using FGLS rather than the PCSE procedure, as models 9-10 show.
In additional robustness checks, I added controls for the exchange rate regime and
inflation, and the results did not change.83 The results were also similar when using
Henisz’s alternative veto points measure.84 The main finding—that the association
between finance and agriculture and exchange rate levels is affected by the number of
veto points—holds across numerous robustness checks.
82
The results were identical to the original models when the AR1 term is dropped altogether. Doing so
reduces the R-squared of the DI model to 0.46, suggesting that the extremely high R-squared is due to the
strong effects of previous shocks, captured by the AR term. Although it is rare, the BMP may have
negative values if a currency is in equilibrium or undervalued, reflecting the risk of illegal transactions.
These values are dropped when using the log transformation, but setting these to zero prior to doing so
preserves these observations. This had no effect on the results.
83
These results that are not displayed for reasons of space are available from the author upon request.
84
Henisz 2000.
29
Several control variables influence these measures of currency valuation. Terms
of trade shocks seem important, and the results also indicate that countries with more
GDP and more financially open economies tend to have lower valued exchange rates.
Countries under IMF agreements tend to have lower values of log(DI). The results
provide little support for the argument that rent-seeking is an important source of
overvaluation. Autocratic states and those with large urban populations are no more
likely to have overvalued currencies than democracies or those with largely rural
populations. That inequality tends to raise overvaluation provides some support for the
rent-seeking argument, however, whether this result is due to rent-seeking or to attempts
at poverty reduction is not clear. Elite rent-seeking seems a less important determinant of
currency policy than sectoral interests.
However, the results point to two flaws of conventional sectoral approaches.
First, nontradables sectors do not always prefer more overvaluation. Both nontraded
sectors seem to reduce overvaluation, at least in certain circumstances. Second, currency
valuation depends the interaction of interests and institutions. The significance of the
coefficients for veto players*finance and veto players*agriculture supports the claim that
this institutional attribute affects currency policy. Taken together, the results suggest that
the sectoral logrolling theory has greater explanatory power than alternative political
explanations of exchange rate valuation.
VI. Discussion and Conclusions
This paper aimed to improve our understanding of the political causes of
exchange rate valuation—an area where limited research has been performed thus far.
30
Clearly, more research on these issues is required. Case-studies are needed to shed light
on what are likely complex causal mechanisms linking societal preferences to currency
valuation. Additional empirical research using these and other measures of currency
valuation would also be beneficial. A better understanding of currency politics is needed
to provide policymakers with useful information about how to avoid self-destructive
overvaluation in the future. Analysis of this issue also opens up new theoretical puzzles
that can contribute to theory development in IPE.
The puzzle that motivated this paper was the fact that the majority of developing
countries have spent most of the last few decades with overvalued exchange rates. The
logrolling theory developed here argued that achieving a certain exchange rate outcome is
more likely when doing so has positive externalities on third parties. My explanation for
overvaluation centered on the fact that sectors with weak currency preferences are likely
to support overvaluation because of its indirect benefits. Logrolling to receive
overvaluation’s attractive side-benefits helps accounts for why this outcome has been the
norm in developing countries in recent decades. I also aimed to explain why a
considerable number of states have grossly misaligned currencies, arguing that this
results from actors trading policy favors with one another such that the end result is more
overvaluation than any actor wants. Since the costs of this policy are not fully
internalized by the winning coalition, logrolling is in these groups’ private interest.
The empirical support for a variety of the theory’s hypotheses provides indirect
but suggestive support for this paper’s main argument that logrolling is an important
cause of overvaluation. The statistical evidence indicates that currency valuation reflects
the preference of influential sectors when political institutions also favor these sectors. I
31
argued that multiple veto points are anathema to advocates of undervaluation because
they help the diverse coalition opposing them overcome time-inconsistency problems and
hence unite against them and succeed politically. The results confirmed that
undervaluation is most likely when agricultural exporters are politically influential and
political institutions have few veto points. Overvaluation is most likely when bankers are
powerful and there are several veto points.
China’s recent conversion to undervaluation seems consistent with the theory, as
China’s rising export-dependence has coincided with continued centralization. A number
of other important cases seem to fit the theory’s predictions, including several rare cases
of undervaluation in Africa and Latin America, such as Ethiopia, South Africa, the
authoritarian regimes of Chile and Uruguay. Perhaps Asia has been the only developing
region where undervaluation has been typical because many of the “developmental
states” in that region combined few veto points with a sizable agricultural export sector.
India, Nigeria’s brief democratic period, and Brazil are examples of countries that
experienced extreme overvaluation during periods with multiple veto points and large
international financial industries.
The sectoral logrolling is in many ways complementary to the main alternative
explanations of overvaluation. Nonetheless, I believe that it holds several advantages
over the other theories. This theory can explain both why overvaluation is so common
and which countries it is most severe in. It remains unclear how a purely sectoral theory
could explain the general tendency for overvaluation. The results suggest that proxies for
rent-seeking do not succeed in accounting for variation in outcomes. These other theories
also lack an explanation for excessive overvaluation—the existence of currencies that are
32
so overvalued that they harmful even the proponents of high currencies. Although the
theory put forth here did not directly address the coexistence of tariffs and overvaluation,
this does not confound this theory: despite the fact that these policies have opposing
effects, their coexistence could be accounted for as a result of logrolling between actors
that care deeply about tariffs (import-sensitive industries, for example) and those that
prefer overvaluation and have only a weak opposition to tariffs (such as finance). The
logrolling theory put forth seems to provide a helpful explanation for why overvaluation
is so common, why currencies are more overvalued in some countries than others, and for
the existence of counter-productively high exchange rates.
Logrolling and issue-linkages can strengthen the “societal coalition” paradigm in
two ways. First, it provides a rationale for using this approach in an area, such as
currency policy, where critics suggest preferences are indeterminate. This analysis
partially concurs with critics of the sectoral approach who argue that preferences over
exchange rate outcomes are often more ambiguous than Frieden’s initial formulation
suggested. However, the existence of indeterminate preferences is not nearly as
problematic for interest-based arguments as these critics85 have suggested. Since
currency valuation is inextricably linked with other issues over which actors do have
intense preferences, ambiguous exchange rate level preferences does not justify
abandoning interest-based approaches.
Second, it provides a way of overcoming what are more serious shortcomings of
existing coalition arguments. Few existing models have proven capable of
simultaneously explaining preferences and policy outcomes.86 Most coalition approaches
85
86
McNamara 1998; Helleiner 2005.
Frieden 1999.
33
either explain societal cleavages without addressing power and policy outcomes87, or they
explain policy choices while ignoring the cause of coalition formation.88 Examining
preference intensities and side-payments enables the analyst to predict which coalitions
are likely to emerge, and which coalition is likely to be more powerful, and hence what
policy will be implemented.
Taking seriously the intricate relations between exchange rate valuation and other
policies seems essential. Most IPE scholars focus only on a single issue-area, such as
trade, immigration, money, etc. To do so likely misses important interrelationships
across policy issues, inappropriately reduces the role of actors that are not directly
affected by any given policy, and underestimates the importance of logrolling.
Consideration of the broader context within which a given policy takes place and the
inter-relationships among policy issues will likely improve our understanding of the
evolution of the global political economy.
87
88
Rogowski 1989; Frieden 1991.
Gourevitch 1986; Gourevitch and Shinn 2005.
34
Table 1: Sectoral Policy Preferences
Exchange Rate
Exchange Rate
Government
Valuation
Regime
Spending
Undervalued
Floating
High
Import-Competing
(Weak)
(Weak)
(Intense)
Sectors
Undervalued
Fixed
High
Manufacturing
(Weak)
(Intense)
(Intense)
Exporters
Undervalued
Fixed
High
Agricultural
(Intense)
(Weak)
(Intense)
Exporters
Overvalued
Fixed
Low
Finance
(Intense)
(Intense)
(Weak)
Overvalued
Floating
High
Nontradables
(Weak)
(Weak)
(Intense)
NOTE: Adapted from Frieden (1991, 1994), Frieden and Stein (2001), Broz and Frieden
(2001)
35
Table 2: Summary Statistics
Variable
Observations
Log(BMP)
1953
Log(DI)
1993
Manufacturing
2840
Agriculture
2070
Finance
1453
Services
3094
Export
2070
Import
3238
Checks
2991
Inequality
1686
Terms of
2522
Trade
IMF
3612
GDP
2733
Financial
2770
Open
Democracy
3001
Urban
4368
Mean
2.83
4.65
14.29
1.89
5.1E-05
47.11
32.21
41.52
0.47
40.49
Std. Dev.
1.93
0.46
8.02
3.08
0.0000868
12.81
22.22
24.20
0.62
5.55
Minimum
-4.61
2.96
0.21
0
2.4E-07
4.14
0.94
1.05
0.00
28.17
Maximum
12.93
8.62
46.00
24.04
0.0009505
85.10
143.10
173.00
2.89
45.42
109.47
33.06
40.28
353.34
0.36
6.6E+10
0.48
2.1E+11
0
6.3E+07
1
3.8E+12
6.80
2.11
2.50
12.50
-2.08
44.81
6.99
23.19
-10
2.88
10
100
36
Table 3: OLS Regression w/ PCSEs
(1)
LOG(DI)
-0.013**
(0.006)
(2)
LOG(BMP)
-0.119***
(0.034)
(3)
LOG(DI)
-0.018**
(0.009)
(4)
LOG(BMP)
-0.122**
(0.051)
Finance
502.082
(570.286)
-7028.751
(4723.652)
212.665
(636.416)
-8731.661*
(4734.613)
Manufacturing
-0.013***
(0.005)
-0.005
(0.021)
-0.013***
(0.005)
-0.013
(0.021)
Services
0.001
(0.003)
-0.030***
(0.012)
0.001
(0.003)
-0.037***
(0.012)
Export
-0.003*
(0.002)
-0.021*
(0.011)
-0.003*
(0.002)
-0.025**
(0.012)
Import
0.003**
(0.002)
0.003
(0.010)
0.003**
(0.002)
0.003
(0.011)
Veto Points
-0.020
(0.036)
0.149
(0.203)
Veto Points* Agriculture
0.014*
(0.008)
-0.014
(0.043)
Veto Points*Finance
1379.312**
(656.970)
9076.345*
(5208.084)
Agriculture
Inequality
0.033***
(0.006)
0.067***
(0.022)
0.036***
(0.006)
0.069***
(0.023)
Terms of Trade
0.001**
(0.000)
0.004
(0.002)
0.001***
(0.000)
0.004***
(0.002)
IMF
-0.063***
(0.020)
-0.037
(0.140)
-0.061***
(0.022)
-0.023
(0.136)
GDP
-5.6e-14
(10e-14)
-1.7e-12***
(6.1e-13)
2.7e-14
(1.0e-13)
-1.5e-12*
(6.4e-13)
Financial Open
-0.030
(0.019)
-0.184***
(0.049)
-0.036*
(0.019)
-0.170***
(0.057)
Democracy
-0.001
(0.003)
0.023
(0.014)
-0.004
(0.004)
-0.001
(0.018)
Urban
0.001
(0.001)
0.001
(0.006)
0.001
(0.001)
0.004
(0.006)
Constant
3.933***
(0.256)
1.897
(1.290)
3.844***
(0.239)
1.992
(1.282)
N
601
557
584
541
R-Squared
0.95
0.18
0.95
0.20
NOTE: *p< .1 **p< .05 ***p< .01. PCSEs are in parentheses
37
Table 4: Robustness Checks
(5)
LOG(DI)
-0.010
(0.009)
(6)
LOG(BMP)
-0.094*
(0.050)
(7)
LOG(DI)
-0.020**
(0.009)
(8)
LOG(BMP)
-0.128***
(0.030)
(9)
LOG(DI)
-0.018**
(0.007)
(10)
LOG(BMP)
-0.110**
(0.043)
Finance
442.262
(577.20)
-8648.793*
(4714.28)
231.693
(803.866)
-7084.26***
(2740.169)
934.081*
(509.773)
-6724.736**
(3395.354)
Manufacturing
-0.010**
(0.005)
-0.007
(0.021)
-0.016***
(0.005)
-0.029
(0.019)
-0.005**
(0.002)
-0.026**
(0.012)
Services
0.001
(0.003)
-0.047***
(0.012)
0.004
(0.003)
-0.018*
(0.010)
0.001
(0.002)
-0.024**
(0.010)
Export
-0.004*
(0.002)
-0.020
(0.012)
-0.003
(0.002)
-0.020**
(0.009)
-0.002
(0.001)
-0.012
(0.008)
Import
0.002
(0.001)
-0.005
(0.014)
-.001
(0.001)
-0.002
(0.009)
0.003***
(0.001)
-0.012
(0.008)
Checks
-0.008
(0.035)
0.191
(0.199)
-0.043
(0.035)
0.294
(0.181)
-0.033
(0.021)
0.203
(0.150)
Checks*
Agriculture
0.015*
(0.008)
-0.001
(0.040)
0.024***
(0.009)
-0.022
(0.034)
0.016***
(0.006)
0.007
(0.039)
Checks*
Finance
1341.308**
(682.01)
6672.925
(5274,70)
1512.834**
(712.518)
4696.27
(2740.169)
855.315**
(399.885)
7171.227**
(3313.292)
Inequality
0.005
(0.011)
0.103***
(0.028)
0.027***
(0.007)
0.062**
(0.024)
0.028***
(0.004)
0.069***
(0.021)
Terms of
Trade
0.001**
(0.0004)
0.004***
(0.002)
0.001**
(0.001)
0.005**
(0.001)
0.0005
(0.0004)
-0.005***
(0.002)
IMF
0.060***
(0.022)
0.001
(0.134)
-0.069***
(0.020)
0.037
(0.124)
-0.050***
(0.013)
0.062
(0.098)
GDP
1.9e-13**
(9.4e-14)
-9.8e-13*
(5.5e-13)
4.5e-14
(2.5e-13)
-1.1e-12**
(5.4e-13)
-8.0e-14
(7.9e-14)
-1.4e-12***
(4.5e-13)
Financial Open
-0.020
(0.018)
-0.168***
(0.060)
-0.051**
(0.025)
-0.034
(0.050)
-0.027***
(0.010)
-0.232***
(0.058)
Democracy
-0.003
(0.003)
-0.003
(0.017)
-0.004
(0.003)
0.019
(0.015)
-0.002
(0.002)
-0.005
(0.012)
Urban
-0.001
(0.002)
-0.005
(0.008)
-0.001)
(0.001)
0.002
(0.007)
-0.00003
(0.001)
0.005
(0.004)
Constant
5.340***
(0.467)
2.058
(1.320)
4.370***
(0.284)
0.532
(1.217)
3.968***
(0.168)
2.176**
(0.982)
N
584
541
584
541
581
540
R-Squared
0.95
0.23
0.99
0.38
Agriculture
NOTE: *p< .1 **p< .05 ***p< .01. Standard Errors in parentheses.
38
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