Trade Liberalization and Financial Leverage
Jen Baggs, School of Business, Queen’s University
James A. Brander, Faculty of Commerce, University of British Columbia
April 2003
Acknowledgements: This paper draws from and augments Chapter 3 of Jen Baggs’s unpublished
Ph.D. thesis, done at the University of British Columbia. We thank our colleagues at Queen’s
University, the University of British Columbia, and Statistics Canada’s Business and Labour
Market Analysis Division for helpful comments. We particularly thank Werner Antweiler, Keith
Head, and John Ries who, along with James Brander, formed the supervisory committee for Jen
Baggs’s Ph.D. thesis. We also owe a substantial debt to Garnett Picot of Statistics Canada and to
Statistics Canada in general. The authors are associated with the Entrepreneurship Research
Alliance and are grateful for financial support from Social Sciences and Humanities Research
Council (SSHRC) MCRI grant 412-98-0025.
Trade Liberalization and Financial Leverage
ABSTRACT:
This paper argues that trade liberalization has a potentially significant impact on financial
leverage. We compare the predictions of the trade-off model of capital structure with the pecking
order model. In the first case, we suggest that trade liberalization affects the trade-off between
the tax advantages of debt and expected bankruptcy costs. This implies that a reduction in
domestic tariffs would tend to reduce financial leverage for domestic firms, while a trading
partner’s reduced tariffs would tend to increase the level of leverage selected by domestic firms.
The pecking order model suggests an opposing scenario. By altering the profits of domestic
firms, trade liberalization moves firms along their pecking order of preferences for financing. We
suggest that declining domestic tariffs reduce the profits of domestic firms and accordingly
increase leverage, while falling foreign tariffs increase profits leading to lower leverage. Using
data on Canadian firms in the period immediately following implementation of the Canada-U.S.
Free Trade Agreement, these predictions are tested empirically and the results are broadly
consistent with the predictions of the pecking order model of capital structure.
1
1. Introduction
One of the fundamental questions of financial economics concerns the determination of
financial “leverage” - the relative importance of debt as opposed to equity in financing the firm.
In view of the substantial and increasing importance of international markets, it would be natural
to ask whether international trade policy considerations might affect financial leverage. However,
the possible effect of international trade policy events on financial leverage (and on financial
structure in general) seems to be completely unstudied by researchers in finance, international
trade, or international business.1
The principal objective of this paper is to propose and test a natural explanation of how
trade liberalization might affect financial leverage. If the linkages between trade policy and
financial decisions are significant there would be several important consequences. If, for
example, it turned out that trade liberalization tended to increase the use of debt relative to equity,
this might have implications for the likelihood of bankruptcy and for the pace and amplitude of
business cycle fluctuations.
Modigliani and Miller (1958) established that under certain conditions there is no unique
optimum for financial leverage. There has been much subsequent analysis seeking to relax one or
more of the assumptions underlying the Modigliani-Miller theorem so as to provide some
understanding of why a firm might choose a particular level of financial leverage. Perhaps the
most basic and empirically most important movement in the direction of realism involved taking
into account market “imperfections” in the form of tax advantages of debt and possible
bankruptcy costs. Specifically, there is a tradeoff between the tax advantages of debt and
expected bankruptcy costs leading, under normal circumstances, to a unique internal optimum for
the debt-equity ratio. A standard reference on this tradeoff is Kraus and Litzenberger (1973).
This tradeoff is the starting point for the theoretical analysis of this paper.
In addition to the trade-off model, this paper also considers the predictions of the pecking
order model of capital structure, developed in Myers (1984). The pecking order model suggests
1
There has been some discussion of the effects of financial markets and debt instruments on trade policy
and on the overall trade balance at a country level (as in, for example, Cole (1988) and Barai (1997), but
very little work on the effects of trade policy on firm-level financial structure.
2
that capital structure is predominately determined by the asymmetry of information between
managers and investors. This asymmetry leads firms to make their financing choices through a
pecking order – using first retained earnings, then safe debt, then riskier debt and finally, when no
other option is available, equity. The amount of financing required is largely determined by the
amount of investment undertaken, while the availability of retained earnings and lower risk debt
is a function of the firm’s profits.
Accordingly, in the pecking order model, leverage is
determined not by the costs and benefits of debt, but by the amount of investment and profits.
This paper expands the standard trade-off and pecking order models to describe how firm
leverage might respond to trade liberalization in each structure and offers an empirical test of
those predictions.
As a precursor to understanding the effect of trade liberalization on financial leverage we
note that trade liberalization has two general effects on market conditions for a domestic firm.
First, falling domestic protection (particularly tariffs) increases competition in the domestic
market as foreign firms find it easier to compete locally. Second, declining foreign protection
allows for improved access to foreign markets for domestic firms, making it possible to reach a
large pool of potential customers at reduced cost.
In terms of the trade-off model, our theoretical innovation is to observe that falling
domestic tariffs therefore
increase the probability of bankruptcy without affecting the tax
advantages of debt and, accordingly, reduce the optimal amount of leverage held by the firm. In
effect firms find it desirable to partially offset the increased bankruptcy risk.
Conversely,
increased access to the foreign market caused by declining foreign tariffs will decrease the
probability of bankruptcy without affecting the tax shield effect and will therefore increase
optimal leverage. The pecking order model suggests exactly the opposite result. The increase in
competition resulting from lower domestic tariffs reduces the profits of domestic firms forcing
them to increase their debt holdings in order to finance the same level of investment. On the
other hand, falling foreign tariffs improve the competitive position of domestic firms, increasing
their profits and allowing them to finance investment with retained earnings reducing their need
for leverage.
3
The trade-off and pecking order models both suggest that the domestic competition effect
of trade liberalization on leverage should work in the opposite direction to the foreign market
access effect, however, the two theories suggest exactly opposing directions for these effects.
This provides a potentially powerful test of the two opposing theories. Some firms are more
strongly influenced by domestic competition, whereas other firms are more strongly affected by
market access. We should therefore see leverage changing in different directions and by different
magnitudes depending on the relative importance of these two effects for the firm in question.
This structure can be estimated naturally in a regression framework.
Admittedly, we would expect the factors just described to be modest compared to other
determinants of financial structure and therefore to be hard to observe. However, we are fortunate
in having access to a unique data set constructed by Statistics Canada that tracks financial
structure in Canadian firms in the period surrounding a particularly important “natural
experiment” – the Canada-U.S. Free Trade Agreement (FTA)2 .Given the importance of the U.S.
economy to Canadian firms and given the significance of this particular trade liberalization, there
is a reasonable hope that the effects might be large enough to be observable. Our main empirical
finding is that lower Canadian tariffs are associated with higher leverage, whereas lower U.S.
tariffs are associated with lower leverage. Both of these findings are inconsistent with the tradeoff model but consistent with the pecking-order model, offering some support for this model as
representative of firm capital structure.
This paper is example of a situation in which changes in the product market environment
(induced by trade policy changes) are related to changes in financial structure. Turning to the
literature, we note that there is by now a substantial literature on the relationship between
financial leverage and product market considerations. Standard early papers making this point at a
theoretical level include Allen (1990), Brander and Lewis (1986), and Titman (1984), and an
interesting empirical application is Chevalier (1995). These papers focus mainly on the causal
link from financial structure to product market strategy, although the reciprocal direction of
influence is recognized.
2
The Canada-U.S. Free Trade Agreement went into effect as of January 1, 1989 and was extended to
Mexico, becoming the North American Free Trade Agreement (NAFTA), as of January 1, 1994.
4
There are several papers dealing primarily with this latter direction of influence: from
product markets to financial leverage. Maksimovic and Zechner (1991) indicate that firms
choosing strategies with higher risk should also choose higher debt levels, while Kovenock and
Phillips (1995) suggest that the decision to recapitalize is influenced by long run changes in
industry demand and supply conditions. The empirical findings of McKay and Phillips (2001)
point toward both smaller competitive groupings of firms within industries and the characteristics
of firms themselves influencing financial structure. We view our work as broadly consistent with
these lines of research as our paper also focuses on how variations in the product market
environment influence financial leverage. However, none of these papers or, to the best of our
knowledge, any other paper, considers how changing trade barriers or other similar exogenous
shocks to the competitive environment affect the amount of leverage a firm chooses.
In addition to this branch of literature, this paper is also related to a number of recent
empirical papers testing the trade-off theory of capital structure against the pecking order model.
The findings of Shyam-Sunder and Myers (1999), using a time series analysis of large U.S. firms,
generally support the pecking order model as the most significant predictor of capital structure.
However, Frank and Goyal (2003), find support for none of the quantitative predictions of the
pecking order model, while finding some evidence in favour of the trade-off model. Fama and
French (2002), testing the predictions of the two models for dividends paid as well as debt levels,
find some support for each hypothesis, in particular for the predictions common to both models.
In general, there is an active an unresolved debate surrounding the validity and implications of the
two models. This paper builds on this debate and adds the new dimension of how capital
structure, and the theories describing it, are affected by changes in product market competition.
We view the main contributions of the paper as arising from three sources. First, we
believe that the basic idea that trade liberalization might have an impact on financial structure is
original, interesting, and of some importance. Second, we provide what we believe is a simple but
empirically relevant comparison of theoretical structures demonstrating the impact of trade
liberalization on financial leverage. Third, the unique data set we have access to provides a
particularly good opportunity to test the opposing theories.
5
Our theoretical model is presented in section 2. Section 3 provides a description of the
data set and section 4 contains the empirical analysis. Section 5 is devoted to concluding remarks.
There is also a data appendix at the end of the paper.
2 Theoretical Framework
2.1 Trade-off Model
As noted in the introduction, we use the tax shield – bankruptcy cost tradeoff formalized
by Kraus and Litzenberger (1973) as the starting point for our analysis. We want to develop the
simplest possible model that allows incorporation of trade policy effects into the determination of
financial leverage. One simplification is that we consider only “debt” and “equity”. No explicit
allowance is made for hybrid financial instruments such as convertible debt, warrants, etc. This
simplification is forced on us by the data in any case, as the data report only “assets” and
“equity”, allowing the calculation of “debt”. In essence, all financing is either debt or equity and
no finer distinctions are available in this data set.
Another simplification is that we consider a one-period model. Debt is taken on at the
beginning of the period and must be repaid at the end. We can imagine that the “period”
represents a time horizon of appropriate length. The firm’s debt is denoted D, where D is the
amount the firm must repay to bondholders. The debt will equal the borrowed principal plus
interest payments. For a given cost of producing a target output level, we could view the principal
as paying some of that cost and therefore reducing the required residual input of equity capital.
This interpretation is not necessary, however, and the firm could just as easily be viewed as
giving the borrowed money directly to shareholders. A firm is assumed to go bankrupt if it has
insufficient net revenues, R, to pay off its debt obligations.
Our key behavioural assumption is that the firm maximizes its market value, V, (the sum
of equity value and the value of debt claims on the firm). Given the standard assumptions made
so far, it can be shown (as, for example, in Kraus and Litzenberger (1973) and in most modern
textbooks on corporate finance) that this market value can be written as follows.
V = VU + TS(D) – EB
(1)
6
The first term in expression (1), denoted VU, is the value of an otherwise equivalent unleveraged
firm (i.e. a firm without debt). The second term, denoted TS for “tax shield”, is the value of the
tax benefits associated with debt. The third term, EB, is expected bankruptcy costs. Each of these
terms requires some explanation.
To understand unleveraged value, VU, we follow Brander and Lewis (1988) and write net
revenues as R(q,τ,τ*,z) where q is the output level of the firm and z is a random variable
representing the effects of uncertain environmental conditions on the prosperity of the firm.
Variables τ and τ* are the domestic and foreign tariff rates, respectively. The marginal density of
z, denoted f(z), is defined over the interval [0,1] and we assume that high values of z represent
good states of the world while low values represent poor states of the world. For an unleveraged
firm (i.e. a firm without debt) R would be the before tax profit of the firm. However, the actual
market value would have to reflect tax obligations. Accordingly we would write VU as
1
VU = ∫ [R(q,τ,τ*,z) − T(R)]f(z)dz
(2)
0
where T(R) is the tax liability of an unleveraged firm that earns before tax profit R.
The second term in valuation expression (1), TS, is the value of tax benefits arising from
debt. As noted, this benefit arises because a firm with debt is worth more than an otherwise
equivalent all-equity firm as the returns to debt are tax-deductible whereas the returns to equity
are not. For a firm with debt, the tax shield effect, TS(D), serves to partially offset T. Thus T(R)
is what a firm that earns profit R would pay if it had no debt. A firm with debt D and operating
profit R ends up paying net taxes of T(R) – TS(D). The fact that the tax advantage of debt can,
under relatively general circumstances, be represented by an additive term in the firm’s valuation
function was first observed in Modigliani and Miller (1963). We make the standard simplifying
assumption that the tax shield effect is simply a constant t multiplied by the level of debt.
TS(D) = tD
(3)
The third term in expression (1) is expected bankruptcy costs. For a firm with debt, that
debt must be paid off if possible. There exists a critical value of z, denoted here as z , where the
firm is just able to meet its debt obligations. We assume that this critical value exists for any
feasible level of D and is defined by
7
R(q,τ,τ*, z ) – D = 0.
(4)
The value of z (the marginal or pivotal state of the world in which the firm just reaches
bankruptcy) will depend on the amount of debt the firm holds, the output level of the firm, and
foreign and domestic tariff levels. As domestic tariffs increase, the domestic industry is more
protected and we can assume that the value of z will decrease – firms will remain solvent in
otherwise worse states of the world if they have higher levels of domestic protection. Similarly,
as foreign tariffs increase, access to the foreign market becomes more costly, and a better state of
the world (higher z ) will be required in order for the firm to remain solvent. Critical state z will
also increase as D increases, as we assume firms with more debt will require sufficiently better
environmental conditions in order for profits to exceed debt obligations.
In states of the world worse than z , the firm will be unable to meet its debt obligations
and will declare bankruptcy. Bankruptcy does not necessarily cause liquidation of the firm, but
rather implies a legally defined condition in which shareholders lose their claim on the firm’s
earnings and debt holders become the residual claimants. Declaring bankruptcy both changes the
firm’s legal status, and imposes costs, including such costs as legal fees and loss of revenue from
reduced sales if either demand or production is affected. Following Brander and Lewis (1988), we
assume that the actual cost of bankruptcy is some fraction k of the shortfall between debt and net
revenues, R, available to pay off the debt.
B = k(D-R(q,τ,τ*,z))
(5)
Therefore, the expected bankruptcy costs depend on z and are given by the integral of (5) over
states of the world in which the firm is bankrupt as shown in expression (6).
z
= k [D-R(q,τ,τ*,z)]f(z)dz .
EB(z)
∫
(6)
0
We can substitute expressions (2), (3), and (6) into (1) to get a more detailed expression
for firm value.
1
z
0
0
V = ∫ [R(q,τ,τ*,z)-T(R)]f(z)dz+tD-k ∫ [D-R(q,τ,τ*,z)]f(z)dz .
(7)
8
We can see that debt enters expression (7) and therefore affect firm value in two ways,
first by way of a tax advantage and then by affecting the expected costs of bankruptcy. In this
model, debt is used only for its tax advantages, and the optimal amount of debt will equate the
marginal benefit of increased debt for tax purposes with the marginal cost of increased debt
associated with an increased probability of bankruptcy.
The optimal level of debt is obtained by maximizing equation (7) with respect to D.
Using subscripts to denote derivatives, the first order condition can be written as
dz = 0 .
VD =t-k ∫ (1)f(z)dz-k[D-R(q,τ,τ*,z)]f(z)
dD
0
z
(8)
The third term in equation (8) is zero by the definition of z in equation (1), which reduces the
first order condition to
VD = t-k[F(z)-F(0)]
= 0,
(9)
where F( z ) is the probability that bankruptcy will occur. For a maximum the second order
condition must be satisfied, as shown in expression (10).
VDD
( )  < 0
 dF z
= -k 
 dD



(10)
Note that for VDD to be negative, the derivative of the probability of bankruptcy with respect to
debt must be positive, as we would expect. Higher levels of debt would of course increase the
chance of insolvency, and this is borne out empirically.3
We now make explicit two additional conditions that that were implicit in our
introductory discussion of the effects of trade liberalization.
dF( z )/dτ < 0
(11)
dF( z )/dτ* > 0
(12)
Condition (11) states that a reduction in the domestic tariff would tend to increase the probability
3
In Baggs (2003) it is shown that the probability of survival is negatively related to leverage. Given that
bankruptcy and exit are highly correlated, as are debt and leverage, this suggests that rising debt will also
increase the probability of bankruptcy
9
of bankruptcy for any given domestic firm. The rationale for imposing this condition is that, as
noted in the introduction, a reduction in domestic trade barriers increases foreign competition in
the domestic market and therefore makes the competitive environment more difficult for domestic
firms. This condition is borne out empirically in Baggs (2003) where falling domestic tariffs
increase the probability of exit for domestic firms4. Similarly, condition (12) states that a
reduction in the foreign tariff tends to reduce the probability of bankruptcy. This result is also
confirmed empirically in Baggs (2003). The rationale for imposing this condition is that greater
access to foreign markets improves the market environment for domestic firms. Consistent with
the empirical results of Pavcnik (2002), the relative importance of the import competition effect
described in condition (11), compared to the foreign market access effect described in condition
(12), depends on the extent to which the firm is an import competing firm as opposed to an
export-oriented firm.
We can now state the main implications of our theoretical structure. From the theoretical
point of view, it is natural to view debt as the choice variable and to state the results focussing on
debt levels, as we do in parts (i) and (ii) of Proposition 1. However, empirically, it is useful to
work with leverage. Leverage sometimes is taken to refer to the debt to equity ratio and
sometimes taken to equal the debt to asset ratio, where assets equal debt plus equity. Either
measure of leverage can be used equivalently. We opt to use the debt to asset measure and state
the corresponding results in part (iii) of Proposition 1.
Proposition 1:
(i) Reductions in domestic tariffs tend to decrease the firm’s optimal debt level.
(ii) Reductions in foreign tariffs tend to increase the firm’s optimal debt level.
(iii) Statements (i) and (ii) apply equivalently to the firm’s optimal debt to asset ratio.
Proof:
(i) To determine the implications of changing domestic tariffs for the optimal level of debt chosen
by the firm, we calculate dD/dτ by totally differentiating first order condition (9) with respect to
D and τ and rearranging to obtain:
4
See also: Pavcnik (2002), Gu, Sawchuck and Whewell (2002), Lewis-Bynoe, Griffith, and Moore (2002).
10
( )
 d F(z)



k
dτ 
d2V

dD
dDdτ
 >0
=
= 
dτ
VDD
VDD
)
(
(13)
The sign of expression (13) follows from expressions (10) and (11).
(ii) The comparative static effect dD/dτ* is determined by totally differentiating first order
condition (9) with respect to D and τ* to obtain
(
2
- dV
dD
dDdτ*
=
dτ*
VDD
)
( )
 d F(z)


k
dτ* 

 < 0.
= 
VDD
(14)
The sign of expression (14) follows from (10) and (12).
(iii) In our analysis the firm chooses its productive mix optimally, including its total asset level.
The firm’s choice problem is then to choose the mix of debt and equity that comprise total assets.
Therefore, we can treat assets as predetermined and hence exogenous. It follows that the debt to
asset ratio will move in the same direction as debt in response to changes in τ and τ*.
This model predicts that trade liberalization, or falling foreign and domestic tariff rates,
will produce competing influences on the amount of debt held by domestic firms. Falling
domestic tariffs reduce protection to the domestic industry, which increases the probability of
bankruptcy. By increasing the expected marginal costs of bankruptcy, without altering the tax
benefits of debt, falling domestic tariff rates reduce the optimal level of firm debt. In the same
manner, falling foreign tariffs reduce the expected marginal costs of bankruptcy by decreasing the
probability of bankruptcy. Since this decrease is not accompanied by any change in the tax
benefits of debt, the optimal amount of debt increases. Consequently, trade liberalization gives
rise to divergent influences on the debt levels of the firm.
2.2 Pecking Order Model
In addition to the trade-off model described above, the pecking order model of capital
structure can also be used to provide predictions as to the effects of trade liberalization on the
amount of leverage held by firms. The pecking order model originates with Myers (1984) and
11
Myers and Majluf (1984), where managers are assumed to know more about the firm’s value than
do investors. Using their private information, managers choose to offer riskier securities when
they are overpriced by market forces.
Investors act rationally by taking this asymmetric
information problem into account and discounting both the firm’s new and existing risky
securities when new issues are announced. Managers also behave rationally by anticipating this
discount and selecting against offering riskier securities where other financing options are
available. In the extreme case, the pecking order model suggests that managers may in fact
forego profitable investments if the only way to finance those investments is with new, risky
securities.5
The costs of the asymmetry of information between investors and management leads
managers to prefer financing projects with those sources of funding least affected by information
asymmetry. This results in a pecking order of investment financing, with managers financing
new projects first with retained earnings, then safe debt, then risky debt, and finally, in situations
where no other alternative exists, with equity. Myers (1984) suggests that the costs of issuing
equity, or even risky debt, far outweigh the tax advantages of debt considered in the trade-off
model. Accordingly, he suggests that leverage will be determined not by a trade-off between tax
advantages and bankruptcy costs, but rather by a pecking order of alternative financing sources,
with firms only choosing to increase their leverage when no internal sources of financing are
available. This implies that firms will only increase their debt holdings when investment exceeds
retained earnings.
Accordingly, for a given level of profitability, the pecking order model
predicts that leverage will be higher for firms with more investments.
While if we hold
investment constant, leverage will be higher for less profitable firms.
In terms of trade liberalization, the pecking order model offers several predictions for the
leverage levels of domestic firms. Falling domestic tariffs increase competition in the domestic
market, and consistent with conventional economic theory and evidence we expect this increase
in competition to reduce the profits of domestic firms. This result is confirmed empirically in
Appendix A where we find falling Canadian tariffs reducing the growth of profits for Canadian
firms. Holding investment constant, according to the pecking order model, this result suggests
5
See for example: Fama and French (2002)
12
that falling domestic tariffs will act to increase the amount of leverage held by domestic firms as
their lower profits reduce the opportunities to finance projects with retained earnings.
Conversely, lower foreign tariffs effectively act to reduce the costs of domestic firms
accessing the foreign market, and holding demand constant, we would expect this lower cost to
increase the profits of domestic firms. This result is again confirmed empirically in Appendix A
where falling US tariffs increase the growth of profits for Canadian firms. This suggests that
falling foreign tariffs will act to reduce the amount of leverage held by domestic firms as their
higher profit levels improve their ability to finance projects with retained earnings.
3 Data Description
We use the T2LEAP dataset maintained by Statistics Canada. The dataset was created by
linking two underlying sources of data. One underlying data source consists of corporate income
tax information obtained from tax forms referred to as “T2” forms. The other underlying source
of data is the Longitudinal Employment Analysis Project (LEAP), which obtains its data from
firm-specific payroll information filed with Revenue Canada. Firm identifiers are removed so as
to make the data set anonymous. Even so, the data set is confidential and in order to use the data
it is necessary for the person analyzing the data to become a “deemed employee” of Statistics
Canada. The data must be analyzed at a secure site in the Ottawa office of Statistics Canada and
cannot be moved.
The T2LEAP dataset is a longitudinal dataset that provides information on every
incorporated Canadian establishment that legally hired employees (and hence filed payroll
information with Revenue Canada) and also filed an income tax return in one or more of the years
between 1984 through 1997. (Most of the data for 1998 is also available.) An “establishment” is
not necessarily equivalent to a “firm” as some large firms have more than one establishment, but
the overwhelming majority of firms are establishments and vice versa and we will use the term
“firm” to represent the units in the data set from now on.
T2LEAP provides firm level data documenting the firm’s financial status as well as its
ownership, location, industry affiliation at the 3 digit Standard Industrial Classification (SIC)
level, and number of employees. Our primary objective is to link financial variables with tariff
13
changes, so we need to link T2LEAP with tariff data. We are able to obtain Canadian and U.S.
tariffs that can be at translated, following Head and Ries (1999), to the 3 digit Standard Industrial
Classification (SIC) level for manufacturing firms. As this is possible only for manufacturing
firms, we are forced to restrict attention to the manufacturing sector.
In addition, we restrict attention to the period 1989 (when the FTA went into effect)
through 1997. The elimination of the pre-1989 period is implied by the logic of the paper.
Specifically, we would like to be able to attribute the effects to the FTA period. Another filter we
impose on the data is to eliminate very small firms – those with less than one “standardized”
employee. Many of these very small “firms” are not firms at all but exist primarily to provide tax
advantages to individuals and it makes sense to eliminate them. The other significant filter is that
firms must be in the data set for at least 4 years (including the pre-1989 period). The reason is that
we discard the first and last year of a firm’s life as the first and last years will typically be partial
years and can therefore produce misleading information. In addition we use some lagged
variables which means that we need two years of data aside from the entry and terminal years for
each firm. Accordingly, a firm that is in the data for 4 years yields one usable data point, a firm in
the data for 5 years yields two usable data points, etc. Even with these filters our data set is still
very large (with over 291,000 observations). For some purposes we consider only firms that
report positive profits. There are just over 188,000 such observations. Table 1 reports some
descriptive statistics regarding the main variables of interest.
Average leverage in our overall sample is just over 0.8, implying that the average firm
has about 80% of its assets represented by debt and about 20% represented by equity. The median
leverage level is 0.65, implying some skewness in the data. Not surprisingly, profitable firms
have lower average leverage than firms without taxable profits. As of 1989, some goods had no
tariffs and tariffs ranged up to about 20% on an ad valorem basis. Under the FTA some tariffs fell
to zero as of 1989, some fell to zero over five years (1989-93) and the remaining tariffs fell to
zero over ten years (1989-98). This implies, as shown by the table, that not all tariffs had fallen to
zero of as 1997, as the 10th and final adjustment remained for some industries.
14
Table 1 – Descriptive Statistics
All Firms
Firms with Profits
Number of Observations
291,543
188,108
Mean Leverage (debt to asset ratio)
0.8081
0.7269
Median Leverage
0.6544
0.6513
Largest Canadian Tariff in 1989
20.7%
20.7%
Largest US Tariff in 1989
18.6%
18.6%
Largest Canadian Tariff in 1997
2.3%
2.3%
Largest US Tariff in 1997
2.1%
2.1%
4. Empirical Analysis and Results
We examine how trade liberalization affected the leverage of Canadian establishments by
estimating a simple econometric specification:
∆ln(leverage t ) = α + β∆(τ it )+ λ∆ (τ*it )+ γSit-1 + ε it .
(15)
Leverage is taken to be the debt to asset ratio, and our dependent variable is the change in the
natural log of leverage from year t-1 to year t. ∆(τit) is the decrease in the Canadian tariff rate
applied to firm i from year t-1 to year t, and ∆(τit*) is the corresponding fall in the US tariff rate.
Sit-1 is the vector of “control variables” that contribute to the determination of the amount of
leverage held by firm i. The error term of course incorporates unobserved influences on leverage.
We recognize at the outset that unobserved idiosyncratic influences will be vastly more important
than changes in tariffs in the determining the leverage of any one firm. However, these effects
should in general be uncorrelated with tariff changes. We therefore have a good chance to isolate
and detect the implications tariffs have for financial structure. A data point consists of a particular
firm’s change in leverage and tariff rates relative to the previous year, and other variables in a
particular year.
There are several variables that might be chosen as control variables. One important issue
is that leverage tends to vary systematically from industry to industry. Accordingly, we might
15
want to correct for industry “fixed effects”. However, tariffs themselves only vary by industry at
the three digit level of industry classification. Therefore, it is not possible to use industry fixed
effects at the three digit level. On the other hand, to the extent that there are industry fixed effects,
they would be expected to operate at a higher level of aggregation than at the three digit level.
Accordingly, in some of our specifications we use industry fixed effects at the 2-digit SIC level.
Thus the main explanatory power of the regressions with industry fixed effects comes from
looking at a particular 2-digit industry and asking whether, within that industry, firms in subindustries with higher tariffs tend to have lower or higher leverage6. Another important source of
variation in the data might be due to business cycle effects. At some points in the cycle, debt to
asset ratios might tend to rise for all firms, for example. This can be corrected for by using year
fixed effects.
Table 2 reports the results for the most basic regression – without fixed effects, and also
shows the results of adding year fixed effects, industry fixed effects and a fixed effect
representing the existence of profits. All regressions have intercepts. These estimated intercepts
are unremarkable and are not reported. Table 2 is inconsistent with our primary theoreticallybased hypotheses concerning the trade-off model (as stated in Proposition 1). However, it is
consistent with the predictions of the pecking order model.
Specifically, Canadian tariff
reductions have a significant positive effect on leverage whereas U.S. tariff reductions have a
significant negative effect on leverage. This suggests that a firm’s choice of leverage in response
to changing product market competition is more in line with the pecking order model than the
trade-off model.
The change in the probability of bankruptcy and related costs appears to be
outweighed by the firm’s preference for financing with low risk options before high risk options.
The reduction in Canadian tariffs (corresponding to trade liberalization) is associated with a
decrease in profits, leading to firms increasing their debt-asset ratio as their ability to finance
6
There are 22 2-digit industries in the data and 121 3-digit industries. For example, one
2-digit industry is “Transportation Equipment” and it is subdivided into 8 3-digit industries,
including aircraft, motor vehicles, motor vehicle parts, truck and bus body parts, railroad rolling
stock, shipbuilding, boat building, and other.
16
projects with retained earnings diminishes. On the other hand, declining American tariffs increase
firm profits, allowing firms to use these profits for financing, reducing their leverage acquisitions.
Table 2 (all firms)
Dependent Variable = ∆ln(Leveraget)
291,543 Observations
1
2
Reduction in Canadian Tariffs
=Canadian tarifft-1- Canadian tarifft
Reduction in US Tariffs
=US tarifft-1- US tarifft
3
4
1.320*
(0.210)
1.532*
(0.126)
0.846*
(0.166)
0.726*
(0.148)
-0.462*
(0.058)
-0.529*
(0.057)
-0.304^
(0.129)
-0.102^
(0.050)
-0.072*
(0.008)
Profit dummy variable
=1 if profits reported
=0 if no profits reported
Year Fixed Effects
year dummy variables
NO
YES
YES
YES
Industry Fixed Effects
two-digit SIC dummy variables
NO
NO
YES
YES
0.000
0.004
0.004
0.006
R2
* = significant at 1% level, ^ = significant at 5% level. Standard errors are in parentheses
The tariffs effects described above are robust to the inclusion of the primary potential
control variables. The introduction of year fixed effects corrects for the marked business cycle
that occurred over the sample period. Not surprisingly, these fixed effects are collectively highly
significant and their inclusion increases the significance of the tariff variables. We take the
inclusion of year fixed effects as uncontroversial.
Including industry fixed effects (at the two-digit level of aggregation) is more
problematic. On one hand it is undoubtedly true that there are unobserved industry specific
differences that should be controlled for: some industries tend to have higher debt levels than
others for reasons not captured in our model. We should not mistakenly attribute such differences
to tariffs. On the other hand, there is substantial variation in tariffs across industries at the 2-digit
level and we run the risk of absorbing any resulting effects on leverage into the fixed effects. By
17
including industry fixed effects at the 2-digit level we are restricting measurement of crosssectional tariff effects to variation at the 3-digit level of industry aggregation within a given 2digit industry. It is therefore not surprising that the inclusion of industry fixed effects lowers both
absolute size and the statistical significance of the tariff coefficients. However, even with the
inclusion of industry fixed effects the tariff effects remain significant.
The other variable we control for is profits in the previous year. It is reasonable to expect
that the change in leverage will be affected both by the change in competition and also depend on
the previous level of profits. Accordingly, it is natural to correct for profits – and we use profits
in the previous period so that there is no question about any possible endogeneity problem with
the profit variable. We have (positive) reported profits for 188,108 observations. For the other
103,435 observations the firms reported no taxable profits. In the regression reported in Table 2
we simply code the presence or absence of positive profits using a dummy variable. The profit
variable takes on the expected sign: positive profits in the previous period lead to lower leverage
growth in the current period. This effect is highly significant and does not significantly change
coefficient estimates or significance levels for other explanatory variables.
We also have the opportunity to use more information arising from the profit variable.
One thing we can do is to use the actual level of profits as a regressor instead of just a dummy
variable for positive profits, although we are then able to use just the 188 thousand observations
that report positive profits. This allows us to make much fuller use of profit information. The
results of these regressions can be found in Table 3.
The profit variable has, as expected, a highly significant negative coefficient, implying
that larger profits are associated with lower subsequent debt to asset ratios. In addition, it is
striking that the tariff coefficients in these regressions are considerably larger in absolute value
than the tariff regressions for the full sample, and these differences are statistically significant.
Significance levels for the coefficients themselves are very similar in the two sets of regressions,
despite the considerably smaller (but still very large) sample size underlying Table 3. Overall, we
would take column 4 of Table 3 as representing the most suitable regression for drawing
inferences about the effects of trade liberalization on leverage.
18
Table 3 (Firms with positive profits)
Dependent Variable = ∆ln(Leveraget)
188,108 Observations
1
2
Reduction in Canadian Tariffs
=Canadian tarifft-1- Canadian tarifft
Reduction in US Tariffs
=US tarifft-1- US tarifft
3
4
1.427*
(.395)
1.400*
(.397)
3.091*
(.568)
2.462*
(0.567)
-1.723^
(.712)
-1.777^
(.712)
-2.942^
(1.062)
-2.548^
(1.060)
ln(Profit in Previous Year)
Year Fixed Effects
year dummy variables
NO
YES
YES
-0.007*
(.001)
YES
Industry Fixed Effects
two-digit SIC dummy variables
NO
NO
YES
YES
0.000
0.002
0.008
0.023
R2
* = significant at 1% level, ^ = significant at 5% level. Standard errors are in parentheses
Table 4 reports regression results incorporating additional lines of investigation that
might shed light on the robustness of our basic results. Table 4 shows the results of introducing
variables to identify firms that are more export or import competing. The variable “export
intensity” is defined as the share of domestic production, at the 3-digit SIC level for each
province, exported to the United States in a given year.7
Similarly, the “import intensity”
variable is defined as the share of the Canadian domestic market in a given 3-digit industry in a
given province for a given year, composed of imports from the United States. We suggest that
these variables are of interest as we would expect firms with a larger share of their production
exported to the United States to be more substantially affected by falling US tariffs, while firms
7
For example: For a data point consisting of firm operating in industry 319 in Alberta in 1993, the export
intensity variable would be the share of the total production of industry 319 in Alberta in 1993 exported to
the United States.
19
competing in industries where the domestic Canadian market features a high concentration of US
imports, to be more affected by falling Canadian tariffs.
Table 4 (Firms with positive profits)
Dependent Variable = ∆ln(Leveraget)
188,108 Observations
1
2
Reduction in Canadian Tariffs
=Canadian tarifft-1- Canadian tarifft
Reduction in US Tariffs
=US tarifft-1- US tarifft
Export Intensity
4
2.947*
(.584)
3.172*
(.703)
2.958*
(.705)
3.045*
(.704)
-3.024*
(.644)
-0.428^
(.215)
-0.261^
(.118)
-0.257^
(.129)
-0.020
(.010)
-0.009
(.011)
-0.016
(.012)
-0.016
(.012)
-6.768*
(1.833)
-5.896^
(2.871)
-6.047^
(2.867)
0.008
(.014)
0.022
(.014)
0.027
(.014)
0.211
(1.163)
1.567
(0.948)
2.038
(1.210)
-0.007*
(.001)
-0.009*
(.001)
Interaction: (Export Intensity)*(∆US Tariff)
Import Intensity
3
0.007
(.008)
Interaction: (Import Intensity)*(∆Cdn Tariff)
ln(Profit in Previous Year)
Age Fixed Effects
NO
NO
NO
YES
Year Fixed Effects
year dummy variables
YES
YES
YES
YES
Industry Fixed Effects
two-digit SIC dummy variables
YES
YES
YES
YES
R2
0.008
0.008
0.025
0.046
*= significant at 1% level, ^ = significant at 5% level. Standard errors are in parentheses
In the first column of table 4, the export and import intensity variables are insignificant,
suggesting that export or import intensity alone does not affect the firm’s acquisition of leverage.
However, in subsequent columns where we interact the intensity variables with the tariff terms,
we see that firms operating in industries where a larger share of production is exported to the
20
United States are more affected by falling US tariffs than firms in less export oriented industries.
The export intensity and US tariff interaction is negative and significant indicating that falling US
tariffs reduce leverage, and this affect is even larger for firms in more export oriented industries.
The Canadian tariff and import intensity interaction is positive, and significant at the 10% level in
columns 3 and 4, tentatively suggesting that Canadian firms in more import oriented industries
see a larger increase in leverage as a result of falling Canadian tariffs than do firms facing less
competition from US imports.
The other innovation in Table 4 is to correct for the age of the enterprise. We therefore
include age fixed effects in the third regression. The actual coefficients are not reported but we
note that the expected result that younger firms tend to have higher leverage is highly significant
in the data. The key point for our analysis here is that including age effects has very little impact
on tariff effects. More broadly, we have used (but not reported) various other control variables
and different permutations of control variables and have found that the tariff effects are and the
are relatively robust.
So far we have focused on the statistical significance of the results. It is also worth
considering the economic significance as implied by the magnitude of the coefficients so as to
determine whether the estimated effects appear reasonable. The most complete regression we
report is from column 4 of Table 4, so we use those tariff coefficients to do this calculation.
Tariffs are entered as decimals. Thus a change in the relevant tariff from, for example, 7% to 6%
would imply a change from 0.07 to 0.06 in our data. The results indicate that a 1 percentage point
decrease in the relevant Canadian tariff (from, for example 7% to 6%) would imply an increase in
the change in the natural log of the debt to asset ratio of about .0305 plus 0.0204 times the import
intensity of the firm’s industry. The mean import intensity is 28%, and at this level, a one percent
decrease in Canadian tariffs would lead to a 0.0362 change in the log of leverage. While we
would not want to take the precise estimates too seriously, this seems a very plausible magnitude.
It is large enough to matter but no so large as to suggest misspecification.
21
5. Concluding Remarks
This paper underscores the basic idea that financial structure and product market
competition are not independent of one another. However, rather than considering financial
structure as a precursor to competition in the product market, this paper suggests that changing
the competitive structure of the output market affects the amount of financial leverage chosen by
the firm. We focus in particular on the change in product market conditions arising from trade
liberalization.
In this paper, two simple theoretical models suggest diverse consequences of trade
liberalization for leverage. The first determines the effect of debt on the value of the firm using
the trade off between the benefits of debt for tax purposes and the costs of debt in increasing the
likelihood of bankruptcy and therefore increasing expected bankruptcy costs. Trade liberalization
has two distinct effects on this trade-off. Declining domestic tariffs imply an increase in
competition and a consequent increase in the likelihood of bankruptcy. Such a change would tend
to reduce the firm’s choice of leverage. Conversely, a declining foreign tariff increases a domestic
exporter’s market access and therefore reduces the probability of bankruptcy. This effect should
tend to increase the optimal leverage. The second model, based on a pecking order, suggests
exactly the opposite result. By decreasing profits, and accordingly the availability of retained
earnings and low risk debt, falling domestic tariffs move firms further down their pecking order
of preferred methods of financing, increasing their leverage. Conversely, declining foreign tariffs
increase domestic profits and allow firms to move up their pecking order of preference for
financing, and reduce leverage by increasing their use of retained earnings.
The fact that the two main components of a trade liberalization (lowered domestic
protection and increased access to foreign markets) have opposite predictions in the two models
allows, in principle, a very appealing empirical test of the two theories. In practice, however,
these trade liberalization effects are difficult to test as the effects would almost certainly be small
relative to other major influences on financial structure. Also, if aggregate data are used, the
analysis would be obscured by the problem that, for most countries, only a minority of firms are
22
engaged in either exporting or in import competition. Therefore the trade liberalization effect
might be rather dilute and hard to observe.
In our case, we have the good fortune to have a compelling "natural experiment" at our
disposal. This specific experiment was the Canada-U.S. Free Trade Agreement of 1989 that
ushered in a 10 year period of successive trade liberalization culminating in the elimination of
tariffs in the manufacturing sector for trade between these two countries. The trade liberalization
was large, well publicized, and not subsumed in a larger package of macro-economic reforms. In
addition, by focussing on Canadian manufacturing firms we have another advantage. The
Canadian manufacturing sector is very heavily integrated with the U.S. economy. During our
sample period, the manufacturing sector exported about 40% of its total production to the U.S.
(rising, over the period, from about 30% to about 50%). In addition, about 35% of manufacturing
output consumed in Canada was imported from the United States and also rose sharply over the
period. In Canada, virtually every manufacturing firm is either export-oriented or importcompeting, and many fall into both categories. Conveniently, however, there is substantial
heterogeneity across firms in the relative importance of Canadian and U.S. tariff changes. Putting
these various facts together implies that the Canada-U.S. Free Trade Agreement offers an
excellent opportunity to test our model.
We find that the implications of trade liberalization for leverage are consistent with the
pecking order model of capital structure – declines in Canadian tariffs are associated with
increasing leverage while declining U.S. tariffs are associated with decreasing leverage. Most
previous work linking financial leverage and product markets has emphasized the dependence of
competition in the product market on the firm’s choice of financing. Our work suggests a
reciprocal effect.
By altering both competition at home and access to markets in foreign
countries, trade liberalization has significant implications for the financial structure of firms.
These findings are relevant for the analysis of international trade policy and of corporate finance.
More specifically, understanding the interaction between trade policy and financial structure at
the firm level is important to enhance our appreciation of the broad and varying implications of
increasing trade liberalization as well as the financing choices of firms.
23
References
Allen, Franklin (1990) “Capital Structure and Imperfect Competition in Product Markets” in
Incentives, Organization, and Public Economics: Papers in Honour of Sir James Mirlees,
ed. Peter J. Hammond and Gareth D. Myles, pp. 281-301, (Oxford University Press:
Oxford)
Baggs, Jen (2003) “Firm Survival and Exit in Response to Trade Liberalization”, Working
Paper. Queen’s University.
Barari, Mahua (1997) “Trade Policy with Asset Markets: The Role of Financial
Structure for Time Consistency,” International Advances in Economic Research,
3(1): 18-36.
Brander, James and Tracy Lewis (1986) “Oligopoly and Financial Structure: The
Limited Liability Effect,” American Economic Review, 76(5): 956-970.
Brander, James and Tracy Lewis (1988) “Bankruptcy Costs and the Theory of
Oligopoly,” The Canadian Journal of Economics, 21(2): 221-243.
Chevalier, Judith (1995) “Capital Structure and Product-Market Competition: Empirical
Evidence from the Supermarket Industry,” American Economic Review, 85(3):
415-435.
Cole, Harold (1988) “Financial Structure and International Trade,” International
Economic Review, 29(2): 237-259.
Head, Keith and John Ries (1999) “Rationalization effects of tariff reductions,” Journal
of International Economics, 47: 295-320.
Fama, Eugene and Kenneth French (2002) “Testing Trade-Off and Pecking Order Predictions
About Dividends and Debt,” Review of Financial Studies, 15(1): 1-33.
Frank, Murray and Vidhan Goyal (2003) “Testing the Pecking Order Theory of Capital
Structure,” Journal of Financial Economics, forthcoming.
Jensen, Michael (1986) “Agency Costs of Free Cash Flow, Corporate Finance, and
Takeovers,” American Economic Review, 76: 323-329.
Jensen, Michael (1988) “Takeovers: Their Causes and Consequences,” Journal of
Economic Perspectives, 2: 21-48.
Kovenock, Dan and Gordon Phillips (1995) “Capital Structure and Product-Market
Rivalry: How Do We Reconcile Theory and Evidence?” American Economic
Review, 85(2): 403-408.
Kraus, Alan and Robert Litzenberger (1973) “A State-Preference Model of Optimal
Financial Leverage,” Journal of Finance, 28(4): 911-922.
Lester, J. and T. Morehen (1987) “New Estimates of Canadian Tariff Rates by Industry
24
and Commodity,” Canadian Department of Finance Working Paper No. 88-2.
Lewis-Bynoe, Denny, Jennifer Griffith and Winston Moore (2002) “Trade Liberalization and
the Manufacturing Sector: The Case of the Small Developing Country,” Contemporary
Economic Policy, 20(2): 272-287.
MacKay, Peter and Gordon Phillips (2001) “Is There an Optimal Industry Financial
Structure?” Working Paper.
Maksimovic, Vojislav and Josef Zechner (1991) “Debt, Agency Costs and Industry
Equilibrium,” Journal of Finance, 46: 1619-1643.
Modigliani, Franco and Merton Miller (1958) “The Cost of Capital, Corporation Finance
and the Theory of Investment,” American Economic Review, 48: 261-297.
Modigliani, Franco and Merton Miller (1963) “ Corporate Income Taxes and the Cost of Capital:
A Correction,” American Economic Review, 53 (June): 433-43.
Pavcnik, Nina (2002) “Trade Liberalization, Exit, and Productivity Improvements:
Evidence from Chilean Plants,” The Review of Economic Studies, 69: 245-76.
Shyam-Sunder, Lakshmi and Stewart Myers (1999) “Testing Static Trade-Off Against Pecking
Order Models of Capital Structure,” Journal of Financial Economics, 51: 219-244.
Titman, Sheridan (1984), “The Effect of Capital Structure on a Firm’s Liquidation Decision”
Journal of Financial Economics (March).
25
Appendix
Table A1 – Affect of changing tariffs on the change in log profits
Dependent Variable = ∆ln(Profitst)
188,108 Observations
1
2
3
Reduction in Canadian Tariffs
4
-2.996^
(1.278)
2.843^
(1.282)
-2.810^
(1.278)
-2.924^
(1.337)
6.817^
(3.159)
5.950^
(2.686)
5.683^
(2.642)
6.563^
(3.198)
Year Fixed Effects
year dummy variables
YES
YES
YES
YES
Industry Fixed Effects
two-digit SIC dummy variables
NO
YES
YES
YES
Age Fixed Effects
NO
NO
YES
YES
Size Fixed Effects
NO
NO
NO
YES
=Canadian tarifft-1- Canadian tarifft
Reduction in US Tariffs
=US tarifft-1- US tarifft
0.008
0.013
0.016
0.023
R2
* = significant at 1% level, ^ = significant at 5% level. Standard errors are in parentheses
26
Data Appendix
The data set used in this analysis reflects the merger of two data bases maintained by
Statistics Canada. The first set of data is provided by the Longitudinal Employment Analysis
Program (LEAP), which tracks every employer in Canada that registers a payroll deduction
account with the Canadian tax authority (Revenue Canada).Employers register a payroll
deduction with Revenue Canada if they hire employees. Accordingly, firms enter the LEAP data
base in the year they first hire employees, and record their last entry in the data base in the last
year they hire employees. For each year in which a firm hires employees, a measure of its annual
employment, called average labour units (ALU), is recorded in LEAP. The reported ALU for a
given firm can be interpreted as the number of “standardized employees” working for a firm
during that year. The total number of employees in LEAP is slightly less than the number of full
time equivalent workers in the Canadian economy as LEAP excludes individuals who are
self-employed.
The LEAP data set has been linked with a second file, The Corporate Tax Statistical
Universe File (T2SUF). The T2SUF tracks every incorporated firm in Canada filing a T2 form
with Revenue Canada. The linkage of these two files forms the T2LEAP data set used in this
paper. In effect, the T2LEAP data set contains every establishment in Canada that is both
incorporated and hires employees8. In this paper, we limit our sample to firms with more than
one employee. This removes the very smallest firms from the population in question, and limits
our analysis to slightly larger and more economically important firms.
The addition of the T2SUF to the LEAP adds annual measures of several financial
variables to the employment statistics. In this paper, we use the T2SUF record of each firm's
equity and assets, converted to constant Canadian dollars using a 1986 price index. In addition to
8
In the case of firms which underwent mergers, acquisitions or spin offs during that time period, the
T2LEAP record is defined by retrospective reconstruction. This means that if, for example, firm A merged
with firm B in year t, then a new firm, C, is created and given a synthetic history aggregated from the
histories of firms A and B. The individual histories of A and B disappear from the data base and firm C
represents their joint operations both before and after year t.
27
employment and financial data, each firm is classified by a 3-digit SIC code. T2LEAP contains
firm information for 15 years, from 1984 to1998. However, the first and last years are subject to
partial reporting, leaving the usable portion as 1985 to 1997 only. We use observations from
1989 forward, but we make use of lagged profits from 1988. Using 3-digit SIC codes, we are able
to match both Canadian and US tariff rates to each firm by year and industry as in Head and Ries
(1999).9
We construct a panel of survivors and exiters using the T2LEAP data as follows. The
initial population of firms we consider are those firms which existed in 1988. Since our analysis
requires data for the year t-1 that represents a full year of operation, these firms must also have
existed in 1987, although that may have been their first year in business. Firms appearing in our
sample in 1989 are those which had their first fiscal period start on or before December 31, 1987,
and whose first year with employees is 1987 or earlier. From this population of firms existing at
the outset of the FTA, we consider both which firms survive, and which exit. Our sample is
augmented in each consecutive year by removing exiting firms and adding new firms. A firm is
removed from the sample in year t if year t is the year in which the firm files its last tax return
(the T2SUF measure of exit) or if year t is the last year in which the firm hires employees (the
LEAP measure of exit). If a firm falls into either of these categories, it is counted as exiting. A
firm exiting in year t will be removed from the sample for all subsequent years.
9
US tariffs are compiled using the 93 industry classification provided in Table A2.1 of the Canada-US Free
Trade Agreement: An Economic Assessment (Government of Canada, Department of Finance, 1988).
Canadian tariffs are compiled from Lester and Morehen (1987). See Head and Ries (1999) for further
details.
28