The Impact of Mutual Recognition Agreements on Foreign Direct Investment andExportYong Joon Jang
Oct. 11, 2010

In this paper, I will attempt to analyze how MRAs affect “horizontal” FDI relative to therelationship with exports: there exists the trade-off between horizontal FDI and exports, i.e.,tariff jumping strategy vs. economies of scale. Recently the decision of how to serve foreign
markets by Multinationals (MNEs) is becoming one of interesting issues in International
Trade. MNEs can serve foreign markets by constructing production facilities overseas toavoid variable trade costs such as tariffs and transportation costs or they can have all
production facilities in their home countries to realize economies of scale and choose toexport their products to foreign countries. As a result, when trade costs decrease from MRAs,
MNEs may concentrate their activities on one country and develop trade flows rather thanopen a plant in a foreign member country. As MNEs derive more benefits from economies ofscale than tariff jumping strategies after conclusion of MRAs, the relative exports tohorizontal FDI sales might increase.
To test this hypothesis, I have developed the theoretical framework which analyzes therelationship between exports and horizontal FDI sales in response to MRA as well as variable
trade costs and wage difference between two countries, based on the work by Helpman,
Melitz and Yeaple (HMY, 2004). From a consumer’s CES preferences over a continuum ofdifferentiated goods and the monopolistically competitive market in which each firm1

produces a different variety, the relative values of export to FDI in the foreign market isdefined as follows:

whereandare the values of export and FDI, respectively,substitution across goods,

is a per-unit iceberg cost for exporting such astransportation costs, insurance fees and tariffs,respectively, and,andis the elasticity ofandare fixed costs for export and FDI,

represent other industry or country characteristics.

As in Beller (2007) and Hogan & Hartson (2003), an MRA will be modeled as a drop in
fixed costs of exporting,implies. Hence the expression for the relative values of export to FDI, implying that when a domestic country concludes an MRA with a foreigncountry, its relative values of export to FDI will increase.
I have empirically tested the theoretical results with U.S. multinationals’ affiliate sales andexports in 8 countries and 7 manufacturing sectors during the period 1999-2006. Foureconometric specifications were set up for this treatise: the fixed effects model, the constanttreatment effects model and two specifications of the time-varying treatment effects model.
Both constant treatment effects and the time-varying treatment effects models are in thegroup of the Difference-in-Difference (DID) estimator.
The fixed effects model is defined as follows:2

i, j, t refer to foreign countries, industries and years, respectively.

is the dependent

variable, which represents the log of the relative values of U.S. exports to U.S. multinational
affiliate sales for industry j in country i at year t.
t.

is the log of country i’s GDP at year

is the log of per capita GDP difference between the U.S. and country i atyear t.

is the log of country i’s aggregate costs which consist of all freight,insurance and other charges for industry j in the U.S. at year t.
is the log of the weighted tariff rate for industry j in country i at year t.
is the log of the estimated duty of goods imported into the U.S. for industry j fromcountry i at year t. To estimate the effects of various sector-level tariff rates on the dependent
variable I have replaced
The key variable,

within some regressions.

, is a dummy variable which is 1 after an MRA is entered into

force with country i in industry j at year t; and 0 otherwise.

,anddenote country-fixed effects, industry-fixed effects and year-fixed effects, respectively. Finally,is anunobserved error term.
Based on theoretical results, I expect

to have positive effects on.

One important concern about the fixed effects model is the endogenous problem. To solve
this the DID estimation is a useful instrument for isolating the effects of a treatment (i.e.,MRA) from those of other unobservable characteristics on the dependent variable. It is basedon a comparison of outcomes in the treated group with those in the control group before andafter the treatment. Hence there are two differences at the same time: the first one is whether
it is treated or not (cross sectional variation), and the second one is whether it is pre- or posttreatment (time series variation).
For the first difference, I divided all industries into two groups: the treated group and thecontrol group. The treated group consists of U.S. industries which signed an MRA during the3sample period, 1999-2006. The control group consists of industries which signed an MRA
before 1999 or never signed any MRA during the sample period. Second, since the U.S. hasnot signed an MRA with other countries in the same year, it is impossible to define withcertainty whether the second difference represents pre- or post-treatment. To solve thisproblem, Giavazzi and Tabellini (2005)’s methods were used as benchmarks, placing the DID
estimator within the framework of the panel analysis.
Therefore, the constant treatment effects model of the DID estimator is:

As before,

anddenote the log of the relative values of U.S. exports to U.S.

multinational affiliate sales and an unobserved error term, respectively.

is adummy variable which is 1 in years after the entry into force of the MRA in the treated groupand 0 otherwise. Therefore, both the treated group before the entry into force of an MRA andthe control group have zero values ofin the regression.

Also included here is a set of other control variables,
and, and three dummies,,

to control unobserved heterogeneity affecting the dependent variable of the treatedgroup and the control group differently.
effects model excluding

consists of explanatory variables in the fixed.

is expected to be a positive sign, which implies that the treatment affects positively therelative values of U.S. exports to U.S. multinational affiliate sales in the treated group afterthe entry into force of the MRA compared with those in the control group over the same time
period.
In some cases, it would take some years for an MRA to influence the relative values of U.S.
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exports to U.S. multinational affiliate sales. In other cases, there would be ex ante effects ofMRA on the relative values of U.S. exports to U.S. multinational affiliate sales, as firms
anticipate change. To control these timed effects of the treatment, estimates were derived
using the first time-varying treatment effects model of the DID estimator, following Giavazzi
and Tabellini (2005):

(29)

,,,,

and

are the same as in (28).

is a dummy

variable which is 1 in the three preceding years before the entry into force of the MRA and 0
otherwise.

is a dummy variable which is 1 in the year of the entry into

force of the MRA and two following years.

is a dummy variable which is 1

from the third year onward after the entry into force of the MRA. Hence,
represents ex ante effects of MRA on the dependent variable, while bothandrepresent ex post effects of the MRA on the dependent variable.

Following Laporte and Windmeijer (2005), the second time-varying treatment effects
model of the DID estimator is:

�(30)

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,,,,,and

are the same as before.

is adummy variable which is 1 in the k-th year before the entry of the MRA into force and 0otherwise (k=1,2,…,4).

is a dummy variable which is 1 in the d-th year

after the entry of MRA into force and 0 otherwise (d=1,2,…,8).

is a dummy

variable which is 1 in the year of the entry of the MRA into force. Therefore,
andrepresent ex ante effects and ex post effectsof MRA on the dependent variable, respectively.
The key fact found and established by these empirical tests is that MRAs have positiveeffects on the relative U.S. exports to horizontal FDI, while trade variable costs have negativeeffects. The results are robust for another specification of industry-fixed effects, that is, theindustry-specific time trends, and standard errors which are clustered by industry, country andyear-level. Hence, the empirical results are consistent with those from the theoretical model.

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