An Alternative Approach to Measuring Consumption Gains from Trade
Rosmy Jean Louis1
November, 2014
Abstract
International trade theory postulates that it pays for countries to trade with each other because of mutual gains to be had.
Theoretically, these gains are differences between autarky and free trade levels of consumption and production. Empirically,
however, computing these gains presents quite a challenge since autarky is not observable and data are not readily available. A
potential solution to this problem is to rather focus on the relative degree of trade openness over time, which is in line with the
natural progression of trade between nations. Evidently, the world has transitioned from a period of lesser trade (Pre-GATT) to
a period of freer trade (Post-GATT), whether countries have undertaken higher level of economic integration or not. Using a
new methodology, this paper builds upon this distinction to provide estimates of consumption gain from trade for EU-15 and
NAFTA member countries.
JEL Codes: C32, E52, F02, F42, F47
Keywords: consumption gains, trade openness, structural vector autoregression, dynamic forecasts.
Note: Please do not quote! This is the very first draft of the paper and is perhaps full of typos and grammatical errors. More recent
contributions to the literature are not incorporated yet. Time is needed to clean this paper properly.
Section 1
1
Introduction
Contact Person: Professor and Chair, Department of Economics and Finance, Vancouver Island University, Nanaimo, BC, Canada V9R 5S5, Phone: 250-753-3245 Local 2233,
Fax: 250-753-6551 [email protected].
It is at times difficult to argue that international trade is not beneficial to all, whether it is electronic gadgets, software, surgical
procedures, stocks and bonds swaps, or real estate, with the advent of technology consumers with the click of a mouse can
purchase or make arrangement to purchase what they want to satisfy their needs from suppliers at fair market value. The same
goes for businesses. The theory of international trade theory is built on the tenet that trades promote welfare and all stand to
benefit from it.
International transactions among countries are of three types (Krugman, Obstfeld, and Melitz, 2012, p. 587-8); goods for goods,
goods for assets, and assets for assets. Gain from the first type is straightforward; free trade allows countries to specialize in the
goods they are most efficient at producing and export a portion of their output in payment for goods they need but do not
produce. In the second type of transactions, domestic countries borrow from international capital market in present time against
proceeds of future exports, the so-called intertemporal trade. In the third type, preferences for portfolio diversifications lead to
assets exchange (e.g., real estate, bonds, and stocks)
Gains from trade accrue to consumers in three important ways when we combine traditional and modern trade theories, namely,
David Ricardo’s comparative advantage and Heckscher-Ohlin’s factor endowment and factor price equalization, Krugman’s
2
(1979, 1980, 1981), Helpman’s (1981), Lancaster’s (1980), Eaton and Kortum’s (2002), and Melitz’s (2003) models of
international trade and monopolistic competition, among others. The first is price reduction that is to materialize due to trade
liberalization as firms reap the benefits of specialization through economies of scale and are able to pass on these gains to
consumers. The second is the availability of product varieties that enables consumers to purchase more to increase their welfare.
The third is the self-selection of firms. As the argument goes, once trade liberalization takes place the most efficient firms
survive and the least efficient ones exit the industry due to their inability to compete. The surviving firms now have access to
both domestic and foreign markets, and with the removal of tariffs and non-tariff barriers, the industry experiences higher
productivity, hence higher wages accrue to workers and lower prices of goods for consumers in general. Empirical research on
these possibilities of gains from trade has produced mixed results as evidence from the works of Harris (1984a&b); Head and
Ries (1999, 2001), Trefler (2004), Tybout et al. (1991, 1995), Smith and Venables (1988, 1991), Badinger (2006); Baldwin
(2006 a&b), Feenstra (1994), Broda and Weinstein (2006), among others.
The risk sharing literature developed since Mundell (1973a&b) that has found empirical impetus following the publication of
Asdrubali et al. (1996) postulates that international portfolio diversification and access to international credit markets work as
insurance for bad times in smoothing income and consumption. The gains from risk sharing reported vary considerably across
studies (e.g. less than 0.5% in Backus, Kehoe, and Kydland, 1992; Cole and Obstfeld, 1991; Mendoza, 1994; Obstfeld, 1994a;
3
and around 30% on average in van Wincoop 1994, 1996; Lewis, 1996; Stephano et al., 2001; Obstfeld, 1994a, 1995; Kose,
1995).
Despite discrepancy in the size of the estimates, conceptually both strands of the literature have therefore established that
consumption per capita matters if one wants to observe the benefits of trade and capital market liberalization. In this paper, we
posit that irrespective of the channel through which international trade benefits consumers, the gain is ought to be reflected in
the consumption of households per capita. To this end, we propose a new methodology to measure the gains from trade. We
postulate that trade liberalization takes the form of a structural break in a country’s degree of openness to trade, in that prior to
GATT or the signing of any formal agreement the degree of openness is low and for the period thereafter it is supposed to be
much higher as barriers to trade are removed. We hypothesize that consumption per capita influenced by the pre-GATT degree
of openness of countries would follow a path that is different than consumption per capita tributary to the post-GATT’s degree
of openness if trade barriers did not get overhauled. We formulate the gains from trade as the difference between the forecast of
Pre-GATT consumption per capita over the post-GATT period and the fitted value of the post-GATT period. Using quarterly
data for the period 1970-2011 and bivariate structural vector autoregression techniques with consumption per capita growth and
trade intensity/import intensity as endogenous variables, we provide estimates of consumption gains/losses from trade for 18
OECD countries (EU-15 and NAFTA) over the period 1994 – 2011. Contrary to expectations, preliminary results show that the
4
smaller developed countries gain from trade whereas the largest economies but France and Italy suffer consumption losses due
to globalization. The gain for Canada is 0.02% over the 18-year period when import intensity is used as measure of openness.
All NAFTA countries report losses under trade intensity. The rest of the paper is organized as follow. Section 2 presents the
underpinning theoretical framework and the methodology for empirical estimation. Section 3 analyses the data and discuss the
results, and Section 4 concludes the paper.
Section 2
Theory and Methodology
Although the gains from trade have been proven theoretically, there are still some bottlenecks empirically in that autarky in real
life is difficult to establish. For it is difficult to gather data on autarky for countries. Autarky is not observable. What really
makes sense is a transition from a period of lesser trade (Pre-GATT) to a period of freer trade (Post-GATT). Our contention is
that even under free trade agreements, some commodities are still subjected to tariffs, explicitly or implicitly. Therefore, it is the
degree of openness that matters rather than the distinction between autarky and free-trade for an economy.
Consider a world economy with two countries: home and foreign, each one takes the form of a representative consumer with
objective to maximize their utility subject to a budget constraint. The two composite commodities consumed, x1 and x2 are
classified as export and import goods, respectively. It does not matter whether we assume there is complete or partial
5
specialization for the arguments that the degree of openness to have an effect on utility. For simplicity, the home country
produces, consumes and exports x1 while imports and consumes x2. The converse holds for the foreign country. In few words,
there is trade between the two nations. We will now focus on the home country only and assume that x1 is produced with local
inputs. The representative consumer faces price p1 for x1 and the world price p2 plus a penalty of (τ =1/δ) that accounts for the
tariff and non-tariff barriers for x2. δ is the degree of openness of the economy that lies in the interval ]0, ∞[. The higher the
degree of openness, the lower the tariff rate (τ) hence the lower the burden on the consumer of the imported good. δ can also be
seen as a reflection of the differential in tariffs between restricted trade and freer trade/globalization states of the economy. δ
converging to 0 is a case of autarky where the increment in price is similar to that of a black market. δ being large or
approaching ∞ is for an economy with no distortions under free trade and is not too realistic.2 In light of these, it is fair to
assume that each country derives satisfaction from a minimum level of consumption of both goods consistent with the lowest
level of trade openness. This consumption rises as τ falls due to increase in δ.
Consequently, we assume that the objective of the representative consumer is to maximize utility subject to the usual budget
constraints where preferences take the constant elasticity of substitution (CES) calibrated share form3:
2
Even under NAFTA, Canadians cannot cross the border with merchandises from the US in excess of certain values unless they pay taxes or smuggle them through. Hence, the
concept of free trade without tariff is not too realistic.
3
As Rutherford (2009) states, it takes quite a bit of algebra to show that when the CES utility function is scaled such that the utility level is equal to one at the reference point, the
objective function takes the form described in Equation (1). Visit http://www.gamsworld.eu/mpsge/debreu/ces.pdf. Accessed January 5, 2012.
6
𝜌
𝑥
1⁄𝜌
𝑥2 (𝛿) 𝜌
𝑢̃(𝑥1 , 𝑥2 ) = (𝜃1 ( 1 ) + 𝜃2 (
𝑥̅
𝑥̅ 2
1
) )
(1)
Subject to
𝑀
̅
𝑀
=
𝑝1 𝑥1
𝑝̅1 𝑥̅1
+
(𝑝2 +𝜏)𝑥2 (𝛿)
(2)
(𝑝̅2 +τ̅ )𝑥̅2
Where M, ̅̅̅
𝑀, 𝑝
̅̅̅̅
𝑝2 , ̅̅̅̅
𝑥1 , 𝑎𝑛𝑑 ̅̅̅
𝑥2 are respectively actual levels of total expenditures, and benchmark expenditures, prices, and
1 , ̅̅̅̅
consumption levels. θ is the share parameter and ρ the elasticity of substitution between the two goods. By definition, θ1+ θ2=1.
Solving the maximization problem in its current form may be quite tedious due to the algebra involved. A way out is to
redefine the variables:
̅ ; y = x1/𝑥̅1 ; z = x2/𝑥̅2 ; py = p1/𝑝̅1 , and pz = (𝑝2 + 𝜏)/(𝑝̅2 + 𝜏̅)
Let I = M/𝑀
Replacing these variables in the objective function and the budget constraint, the problem of the consumer then resumes to
maximizing the Lagrangian:
1/𝜌
ℒ = (𝜃𝑦 𝑦 𝜌 + 𝜃𝑧 𝑧 𝜌 )
+ 𝜆(𝐼 − 𝑝𝑦 𝑦 − 𝑝𝑧 𝑧)
(3)
Under the assumption that second-order conditions are satisfied, the first-order conditions require that the derivatives of the
Lagrangian with respect to its arguments equal zero to satisfy the tangency condition:
7
𝑀𝑅𝑆𝑦
𝑀𝑅𝑆𝑧
=
𝜃𝑦 𝑦 𝜌−1
𝜃𝑧
=
𝑧 𝜌−1
𝑝𝑦
(4)
𝑝𝑧
Solving for z as a function of y, we obtain:
𝑧 = 𝑦(
𝜃𝑦 𝑝𝑧
𝜃2 𝑝𝑦
𝜎
)
(5)
Solving for y from the budget constraint and substituting in (5), we have:
𝑧∗ = (
𝐼
𝑀⁄
̅
𝑀
𝜎) =
𝜃𝑧 𝑝𝑦
)
𝜃𝑦 𝑝𝑧
𝑝𝑧 +𝑝𝑦 (
(
𝑝1 𝜎
𝜃2 𝑝
(𝑝2 +𝜏)
̅
𝑝1
( ̅ ̅ )+( ̅ ) ( 𝑝12 )
𝑝2 +𝜏
𝑝1
𝜃1 ̅
𝑝2
=
𝑥2
𝑥̅ 2
(6)
)
Similarly, solving for z as function of y from the budget constraint and substituting in (5) or plugging z* back in (5), the
consumption of good y is derived. Since our objective is to estimate the consumption gains from trade under the era of freer
trade using the pre-GATT period or the signing of formal trade agreements among countries as benchmark or reference, our
focus is on the actual demand for the goods. To that end, we replace z* and its arguments with the variables defined above. As
can be gleaned, a direct relationship exists between the demand for both x1 and x2 and the degree of openness beyond the
benchmark embodied in τ. An increase in δ beyond the reference point reduces τ and lowers the price of imports. At the
8
optimum, demand for both goods depends on the degree of openness for two reasons: (1) substitutability or complementarity
between the goods; and (2) good x1 is an export good for the home country. Equation (6) is quite bulky even after log-linearizing
for estimation purposes. The situation becomes more complicated in deriving the sensitivity of, say, x2 to δ. Further
manipulation of Equation (6) lead to the same demand function derived directly from the maximization of the scaled utility
function:
𝜎
𝑥2
𝑥̅2
𝑐
𝑀
= ( 𝑝2+𝜏 ) ( ̅ )
𝑐𝑀
(7)
̅ 2 +𝜏̅
𝑝
where c is the cost of living index4
1⁄(1−𝜎)
𝑝1 1−𝜎
𝑝2 + 𝜏 1−𝜎
𝑐 = (𝜃1 ( )
+ (1 − 𝜃2 ) (
) )
𝑝1
̅̅̅
𝑝̅2 + 𝜏̅
The associated money metric utility is given by:
𝜐̃(𝑝1 , 𝑝2 , 𝑀, 𝛿, 𝜏) =
𝑀
̅
𝑀𝑐(𝑝1 ,𝑝2 +𝜏)
(8)
Using a before-after approach, the welfare effect can be analyzed by comparing the maximum utility derived by consumers
under different levels of trade openness. The calibrated share form is used here only to contextualize the research question at
4
See Rutherford, Thomas F. (2009). Constant Elasticity of Substitution Preferences: Utility, Demand, Indirect Utility, and Expenditures Functions. ETH Zϋrich, November 2.
http://www.cepe.ethz.ch/education/IntermediateMicro/duality.pdf . Accessed January 5, 2012
9
hand. To estimate the gains from trade, however, we rely on statistical estimation, though calibrating the demand functions
using different values of 𝛿 is quite appealing. Replacing τ with 1/ δ and log linearizing Equation (7):
1
1
̅
ln(𝑥2 ) = ln(𝑥̅2 ) − 𝜎 ln (𝑝2 + ) + ln (𝑝̅2 + ̅ ) + 𝑙𝑛𝑀 − ln(𝑐) − 𝑙𝑛𝑀
𝛿
𝛿
(9)
Holding all other variables constant but the degree of openness, we use bivariate structural vector autoregression (SVAR)
technique to estimate the predicted values of consumption per capita, 𝐶 = 𝑥1 +𝑥2 . Our justification for using SVAR relates to
the possible endogeneity of the two variables. The openness of a country brings variety that induces consumption and the need
to satisfy domestic consumers propels countries to look passed their frontiers. The infinite moving average representation of the
typical SVAR model can be represented as follows:
[
𝑎11,𝑖
Δ𝐶
𝑖
] = ∑∞
𝑖=0 𝐿 [𝑎21,𝑖
𝛿
𝑎12,𝑖 𝑒 𝐶
𝑎22,𝑖 ] [𝑒 𝛿 ]
(10)
Where 𝑒 𝑥2 and 𝑒 𝛿 are respectively structural shocks to consumption and to trade openness, and L is the lag operator. The model
is identified with short-run restrictions, 𝑎12,0 = 0, in line with the natural time lag that exists from the time of placing an import
order to the time of actually receiving the products for consumption. In fewer words, it takes some time before changes in the
degree of trade openness of a country could have real effects on consumption. We consider a quarter to be that period on
average, amalgamating purchases from e-Bay or other online outlets that can take up to 2 weeks maximum and purchases by
large importers that can take much longer.
10
We estimate Equation (10) for two sample periods: Pre-GATT (1970q1- 1993q4) and Post GATT (1994q1 – 2011q4) to obtain
the predicted values of consumption, 𝐶̂70_93 𝑎𝑛𝑑 𝐶̂94_11 , respectively. To arrive at the consumption gains due to openness for
94_11
̃70_93
each country, we compute the dynamic forecast of 𝐶̂70_93 , namely 𝐶𝐹
(the benchmark), over the second sample period.
This forecast traces the path consumption would have taken, had there been no GATT or formal signing of economic
integration agreements among countries. 𝐶̂94_11 is the actual path of consumption after the signing of these agreements until
2011. The consumption gains from trade (𝐶̃𝐺 ) is given by the following equation:
94_11
̃70_93
𝐶̃𝐺 = 𝐶̂94_11 − 𝐶𝐹
(11)
As Equation (11) is a difference between two terms, 𝐶̃𝐺 can either be positive (gain), negative (loss), or zero (breakeven) for
each point in time. The total and the average consumption gains over T periods are given by:
𝑇𝐶𝐺
𝑇𝐶𝐺 = ∑𝑇𝑡=1 𝐶̃𝐺,𝑡 and 𝐴𝐶𝐺 =
𝑇
(12)
It is quite important to note that any suitable forecasting method or the average of the forecasts produced by different methods
should do the trick. Also, the cut-off point or benchmark date need not be 1994, it could be any date a major event has occurred.
11
The drawback however, the closer we are to present time, the smaller the sample size of the second period forecast. Apart from
that, the methodology is quite easy to implement empirically.
Theoretically, the problem of the producer is no different than that of the consumer. It suffices to replace the goods with factors
of production and assume that one factor is supplied locally (labor) and the other is imported (capital). Using the calibrated
share form of a CES technology, we can follow the same step to highlight the link between output and the degree of openness,
and calculate the production gains from trade. At this stage, we solely focus on the estimation of the consumption gains and
leave the estimation of the production gains for the future.
Section 3
Data Analysis and Estimation Results
The quarterly data on output, exports, imports, and consumption for the paper come from OECD-iLibrary and span over the
period 1970 – 2011. Data on yearly population estimates were taken from the United Nations Statistical Database and were
extrapolated to quarterly data. Consumption per capita and three measures of trade openness were calculated: (1) trade intensity
defined as the ratio of exports plus imports to output; (2) import intensity defined as the ratio of imports to output; and (3)
12
exports intensity as a ratio of exports to output. Thus far, we have focused on the first two measures of openness. The data
series were tested for unit roots; the openness variable was found to be stationary while the natural log of consumption per
capita was found to be non-stationary or integrated of order 1, consequently the first difference of consumption per capita enters
the VAR. Motivated by the signing of the European Union (EU) on November 1, 1993 and the North American Free Trade
Agreements (NAFTA) in 1994, we focus on 15 EU members, of which 12 were the original signatories, and the 3 NAFTA
member countries (Canada, US, Mexico). All 18 countries are also members of the OECD and account for approximately 60 %
of world output, and three-quarters of world trade. The European countries or EU-15 are: Austria (AT), Belgium (BE),
Denmark (DK), Finland (FI), France (FR), Germany (DE), Greece (EL), Portugal (PT), Ireland (IE), Italy (IT), Luxembourg
(LU), Netherlands (NL), Spain (ES), Sweden (SE), and United Kingdom (UK).
We illustrate in Figures 1, 2, and 3 the path of natural log consumption and the two measures of openness (total trade and
import intensities) over time. While for most countries consumption per capita display a smooth progression, for few countries
there is evidence of structural break in the data at the end of the 1990s entering the 2000s decade. This feature of the data
deserves careful attention, which will be given in due course.5 The data on openness by contrast display a synchronized
5
We plan to deal with the structural break issue by splitting the sample period for the countries displaying such feature right where we observe the jump in consumption per capita
to separate out the benchmark period from the period of wider openness for the countries. This arbitrary way of dealing with structural break should have no effect on the results
since we do not link the countries explicitly in computing the gains from trade.
13
fluctuation. The measures of openness are highly correlated, above 90 % in most cases. As per Table 1, The correlation of
consumption per capita ranges from a low of 74.9 % for Sweden and Greece to a max of 99.92 % for Portugal and Spain.
Except for Mexico’s linkages with Canada (93.66 %) and the US (94.09 %), these statistics are by no means a surprise since
high income countries tend to share similar tastes and mostly trade with each other. We find similar associations across the two
sample periods.
Given that consumption gain is directly linked to trade, we compute on a country-by-country basis the pairwise correlation
between consumption per capita and each measure of openness for each sample period. Table 2 shows that: (a) the correlation is
statistically significant at the 5 % level for all countries but Italy in the case of import intensity, and Canada on accounts of both
total trade and import intensities; (b) for most countries but Canada, Greece, Ireland, and Portugal, the Post-GATT period
shows greater association of the variables than the Pre-GATT period; (3) oddly enough, for Canada, this association is negative,
which seems to suggest that consumption per capita and globalization move in opposite direction; and (4) The reverse pattern is
observed for the US; negative and positive correlation in the Pre- and Post- GATT periods, respectively. In sum, the data does
not display a uniform pattern of consumption per capita and openness despite their presumed affinities.
To gauge the consumption gains from trade we estimated bivariate SVARs with four lags for each country as per the
14
methodology above and distinguish between the periods 1994-1999 (6 years after the signing of NAFTA, EU, and GATT),
2000-2007 (8 years preceding the recent financial crisis), and 2008-2011 (financial crisis wave and recovery). Table 3 presents
the results for each measure of openness.6 We find consumption per capita loss for Denmark, Germany, Mexico, Sweden, UK
(except for 1994-1999), and USA for all sub-periods. Contrary to expectations, consumption loss for Canada is mostly present
when total trade intensity is used, about 0.13 % in total. For Mexico and the US, the maximum loss is respectively 0.90 % and
0.50 %. Irrespective of the openness measure used, NAFTA countries have mostly suffered losses. The maximum gain based on
import intensity is 0.02 % for Canada for the full period, and around 0.14 % for Mexico during the crisis period. The winners
based on the average of the total gains from the two trade openness measures are Austria (1.62%; 1.62%), Belgium (3.01%,
3.02%), Finland (1.35%; 1.45%), France (1.01%; 1.09%), Greece (5.72%; 5.69%), Ireland (-0.35%, 6.69%), Italy (6.77%,
0.13%), Luxembourg (2.88%, 2.84%), Netherlands (4.72%; -0.04%), Portugal (-0.12%, 4.56%), and Spain (4.65%, 4.78%). The
year-to-year path of consumption per capita gains is reported in Figures 4 and 5. As evident, Greece has recorded the largest
gain on average, and with some few exceptions, the data capture the economic downturn of 2008.
The holistic view that trade is beneficial to all does not seem to hold here, though for some countries, the results are sensitive to
the measure of openness used (e.g., Ireland and Portugal). However, there is a clear pattern that consumers in the largest
6
The unrestricted VAR results showing the effects of openness on consumption per capita growth, the response coefficient matrix, the impulse responses, and the variance
decompositions are available upon request. The same goes for correlation of openness measures discussed in the text not presented as a table.
15
economies (USA, Canada, UK, and Germany) have all lost due to globalization. This finding may provide some justification to
the anti-globalization movement.
While the methodology proposed to arrive at the gains from trade is quite intriguing, it is worth noting that the results thus far
are not robust since only 4 lags were included in the estimation. It is quite possible that the results are sensitive to the number of
lags. To address this issue, we will experiment with 2 and 6 lags and also focus on the export intensity measure of openness.
The results only indicate that some countries have gained while others have lost due to trade liberalization, we cannot firmly
establish against or to which countries gains or losses are materialized. To address this shortcoming, we will use bilateral trade
data from the IMF’s Directions of Trade Statistics in calculating the degree of openness. With this, we will then be able to tell
with our methodology whether the signing of NAFTA or EU has been beneficial for consumers. As a word of caution, care
must be exercised in drawing any firm conclusion from the current results.
Section 4
Conclusion
In this paper, we have proposed an alternative way of estimating consumption per capita gains from trade. We conjecture that
for whatever purpose countries trade with each other, consumption per capita shall reflect any gains. As the risk sharing
16
literature has established, international portfolio diversification and access to foreign credit markets give rise to income and
consumption smoothing. Three mains sources of gains from trade exist when we combine traditional and modern trade theories.
The first is price reduction that is to materialize due to trade liberalization as firms reap the benefits of specialization through
economies of scale and are able to pass on these gains to consumers. The second is the availability of product varieties that
enables consumers to purchase more to increase their welfare. The third is the self-selection of firms. As the argument goes,
once trade liberalization takes place the most efficient firms survive and the least efficient ones exit the industry due to their
inability to compete. The surviving firms have access to both domestic and foreign markets, and with the removal of tariffs and
non-tariff barriers, the industry experiences higher productivity, hence higher wages accrue to workers and lower prices of
goods for consumers in general. This literature has therefore established that consumption per capita matters if we want to see
the benefits of trade. We have built our measure of gains from trade on that premise.
We postulate that trade liberalization takes the form of a structural break in a country’s degree of openness to trade, in that prior
to GATT or the signing of any formal agreement the degree of openness is low and for the period after it is supposed to be
much higher as barriers to trade are removed. We hypothesize that consumption per capita influenced by the Pre-Gatt degree of
openness of countries would follow a path that is different than consumption per capita tributary to the Post-Gatt degree of
openness. We formulate the gains from trade as the difference between the forecast of Pre-GATT consumption per capita over
17
the post-GATT period and the fitted value of the post-GATT period. We find, contrary to the predictions of the underlying trade
theories, that consumers in Canada, Denmark, Germany, Mexico, Sweden, US, and UK have all lost due trade openness,
regardless of the measure of trade openness used; total trade intensity or import intensity. To the best of our knowledge, this is a
novel approach in computing consumption gains from trade.
18
References (INCOMPLE AND INADEQUATE)
Asdrubali, P., Sorensen, B.E., & Yosha, O. ( 1996). Channels of interstate risk sharing: UnitedStates 1963-90. Quarterly Journal
of Economics 111, 1081–1110.
Backus, D., Kehoe, P. J., & Kydland, F. E. (1992). Dynamics of the trade balance and the terms of trade: The S-curve (No.
w4242). National Bureau of Economic Research.
Backus, D. K., Kehoe, P. J., & Kydland, F. E. (1992). Relative price movements in dynamic general equilibrium models of
international trade (No. w4243). National Bureau of Economic Research.
Broda, C., & Weinstein E. D. (2006). Globalization and the Gains from Variety. Quarterly Journal of Economics, 121(2), 54185.
Cole, H. L., & Obstfeld, M. (1991). Commodity trade and international risk sharing: How much do financial markets matter?
Journal of Monetary Economics, 28(1), 3-24.
Eaton, J., & Kortum, S. (2002). Technology, geography, and trade. Econometrica, 70(5), 1741-1779.
Feenstra, R. C. (1994). New product varieties and the measurement of international prices. The American Economic Review,
157-177.
Harris, R. (1984a) “Applied General Equilibrium Analysis of Small Open Economies with Scale Economies and Imperfect
Competition,” American Economic Review, 74(5), December, 1016-32.
Harris, R. (1984b) Trade, Industrial Policy, and Canadian Manufacturing. Toronto: Ontario Economic Council.
Head, K., & Ries, J. (1999). Rationalization effects of tariff reductions. Journal of International Economics, 47(2), 295-320.
Head, K., & Ries, J. (2001). Increasing returns versus national product differentiation as an explanation for the pattern of USCanada trade. American Economic Review, 858-876.
Heckscher, E. F., & Ohlin, B. G. (1991). Heckscher-Ohlin trade theory. The MIT Press.
19
Helpman, E. International Trade in the Presence of Product Differ-entiation, Economies of Scale and Monopolistic
Competition: A Chamberlin-Heckscher-Ohlin Approach. J. Internat. Econ. 11 (August 1981), 305- 40.
Krugman, P. R., Obstfeld, M., & Melitz, M. J. (2012): International Economics: Theory and Policy. Ninth Edition. Boston etc.:
Pearson.
Krugman, P. R. (1979). Increasing returns, monopolistic competition and international trade,
Economics 9, 469-79
Journal of International
Krugman, P. R. (1980). Scale economies, product differentiation, and the pattern of trade, American
950-9
Economic Review 70,
Krugman, P. R. (1981). Intra-industry specialization and the gains from trade, Journal of Political Economy 89, 959-73.
Lancaster, K. (1980). Intra-industry trade under perfect monopolistic competition. Journal of international Economics, 10(2),
151-175.
Lewis, A. S. (1996). Derivatives of spectral functions. Mathematics of Operations Research, 21(3), 576-588.
Melitz, M. J. (2003). The impact of trade on intra‐industry reallocations and aggregate industry productivity. Econometrica,
71(6), 1695-1725.
Mundell, R. A. (1973). Uncommon arguments for common currencies. The economics of common currencies, 114-132.
Mundell (1973a&b
Obstfeld, M. (1994). Risk-taking, global diversification, and growth. American Economic Review 84, 1310-1329.
Obstfeld, M. (1994). The logic of currency crises, Cahiers Economiques et Monetaires 43.
Obstfeld, M. (1995). The logic of currency crises (pp. 62-90). Springer Berlin Heidelberg.
Obstfeld, M. (1995). Risk-taking, global diversification, and growth (No. w4093). National Bureau of Economic Research.
Ricardo, D. (1951–73). The Works and Correspondence of David Ricardo. 11 vols. Edited by Piero Sraffa and M. Dobbs.
Cambridge: Cambridge University Press.
20
Rutherford, T. F. (2002, November). Lecture Notes no Constant Elasticity. Gamesworld.eu. Retrieved January 5, 2012, from
http://www.gamsworld.eu/mpsge/debreu/ces.pdf. (2009, November 2nd). Constant Elasticity of Substitution Preferences:
Utility, Demand, Indirect Utility, and Expenditures Functions. ETH Zϋrich. Retrieved January 5, 2012 from
Austria
Belgium
Denmark
Finland
France
Germany
Greece
Ireland
Italy
Luxembourg
Netherlands
Portugal
Spain
Sweden
UK
USA
Canada
Mexico
http://www.cepe.ethz.ch/education/IntermediateMicro/duality.pdf.
Shiller, R. J., & Athanasoulis, S. (1995). World income components: measuring and exploiting international risk sharing
opportunities (No. w5095). National Bureau of Economic Research.
Smith, A., & Venables, A. J. (1988). Completing the internal market in the European Community: Some industry simulations.
European economic review, 32(7), 1501-1525.
Smith, A., & Venables, A. J. (1991). Economic integration and market access. European Economic Review, 35(2), 388-395.
Stefano G. Athanasoulis & Robert J. Shiller, (2001). "World Income Components: Measuring and Exploiting Risk-Sharing
Opportunities," American Economic Review, American Economic Association, vol. 91(4), pages 1031-1054, September.
Trefler, D. (2004). The Long and Short of the Canada–U.S. Free Trade Agreement, American Economic Review 94, 870–895.
Tybout, J.R., J. de Melo and V. Corbo (1991). The effects of trade reforms on scale and technical efficiency: New evidence
from Chile, Journal of International Economics 31, 231-250.
Wincoop, E. V. (1994). Welfare gains from international risk sharing. Journal of Monetary Economics, 34(2), 175-200.
Wincoop, E. V. (1996). A multi-country real business cycle model with heterogeneous agents. The Scandinavian Journal of
Economics, 233-251.
21
Austria
1.0000
Belgium
0.9938
1.0000
Denmark
0.8794
0.8241
1.0000
Finland
0.9954
0.9828
0.9029
1.0000
France
0.9989
0.9891
0.8966
0.9974
1.0000
Germany
0.9590
0.9230
0.9765
0.9691
0.9684
1.0000
Greece
0.9177
0.9261
0.7594
0.9137
0.9169
0.8468
1.0000
Ireland
0.9022
0.8517
0.9902
0.9232
0.9179
0.9824
0.7992
1.0000
Italy
0.9787
0.9944
0.7644
0.9633
0.9703
0.8811
0.9199
0.8003
1.0000
Luxembourg
0.9943
0.9998
0.8262
0.9833
0.9896
0.9247
0.9259
0.8548
0.9943
1.0000
Netherlands
0.9796
0.9542
0.9538
0.9851
0.9862
0.9941
0.8834
0.9630
0.9189
0.9548
1.0000
Portugal
0.9856
0.9973
0.7908
0.9708
0.9786
0.9001
0.9244
0.8236
0.9981
0.9976
0.9343
1.0000
Spain
0.9885
0.9988
0.8002
0.9760
0.9824
0.9066
0.9267
0.8316
0.9979
0.9987
0.9405
0.9992
1.0000
Sweden
0.8722
0.8169
0.9938
0.9007
0.8907
0.9699
0.7494
0.9860
0.7581
0.8189
0.9461
0.7837
0.7943
1.0000
UK
0.9119
0.8630
0.9812
0.9310
0.9254
0.9832
0.7914
0.9951
0.8162
0.8665
0.9646
0.8371
0.8447
0.9799
1.0000
USA
0.9128
0.8630
0.9737
0.9315
0.9237
0.9781
0.7892
0.9856
0.8188
0.8668
0.9592
0.8376
0.8447
0.9669
0.9903
1.0000
Canada
0.9028
0.8532
0.9790
0.9303
0.9173
0.9727
0.8011
0.9819
0.8046
0.8553
0.9551
0.8247
0.8343
0.9810
0.9773
0.9822
1.0000
Mexico
0.9252
0.8958
0.9218
0.9337
0.9357
0.9553
0.8407
0.9407
0.8572
0.8968
0.9542
0.8762
0.8826
0.9250
0.9449
0.9366
0.9409
Table 1
The Correlation of Consumption per Capita across the 18 OECD Countries
22
1.0000
23
Table 2
Pairwise correlation between consumption and measure of trade openness
1970Q1 - 1993Q4
Trade
Export
Import
Intensity
Intensity
Intensity
Austria
0.8545*
0.8459*
0.8344*
Belgium
0.6874*
0.6959*
0.6610*
Canada
0.7743*
0.7428*
0.7785*
Denmark
0.3891*
0.6701*
-0.0978
Finland
0.4078*
0.5050*
0.1502
France
0.6895*
0.7493*
0.6108*
Germany
0.7789*
0.8455*
0.6505*
Greece
0.5909*
0.5346*
0.6304*
Ireland
0.8957*
0.9241*
0.6643*
Italy
0.2962*
0.4249*
0.1238
Luxembourg 0.6640*
0.5747*
0.6293*
Mexico
0.5712*
0.4060*
0.6777*
Netherlands 0.5198*
0.5609*
0.4289*
Portugal
0.5431*
0.5036*
0.4842*
Spain
0.7468*
0.6656*
0.7623*
Sweden
0.5555*
0.5891*
0.4649*
UK
0.2181*
0.1941
0.2103*
USA
-0.7499*
0.7199*
-0.8570*
* denotes significance at the 5% level.
1994Q1 - 2011Q4
Trade
Export
Intensity
Intensity
0.8657*
0.8736*
0.7206*
0.7624*
-0.1939
-0.2532*
0.7109*
0.7204*
0.7454*
0.6672*
0.7005*
0.5083*
0.8627*
0.8813*
0.3879*
0.4454*
0.4494*
0.4625*
0.7423*
0.6579*
0.8689*
0.8695*
0.7965*
0.7691*
0.7016*
0.7355*
0.3186*
0.2656*
0.7621*
0.6324*
0.6603*
0.6558*
0.3887*
0.2324*
0.8527*
0.6676*
24
Import Intensity
0.8487*
0.6687*
-0.1044
0.6860*
0.7678*
0.7585*
0.8286*
0.3237*
0.4229*
0.7712*
0.8579*
0.8108*
0.6547*
0.3191*
0.8186*
0.6522*
0.5160*
0.6504*
Table 3
Austria
Belgium
Denmark
Finland
France
Germany
Greece
Ireland
Italy
Luxembourg
Netherlands
Portugal
Spain
Sweden
UK
USA
Canada
Mexico
Consumption per Capita Gains from Trade Openness
Based on Import Intensity
19942000 1994 - 2011
1999
2007
2008 - 2011
Average Total
Total
0.02
1.62
1.27
0.23
0.12
0.04
3.01
2.11
0.87
0.03
-0.01
-0.80
-0.29
-0.38
-0.14
0.02
1.35
1.05
0.26
0.05
0.01
1.01
0.65
0.23
0.13
-0.01
-0.50
-0.03
-0.30
-0.18
0.08
5.72
-2.72
6.03
2.40
0.00
-0.35
0.13
-0.25
-0.23
0.09
6.77
4.29
1.96
0.52
0.04
2.88
1.50
1.05
0.33
0.07
4.72
1.96
1.61
1.15
0.00
-0.12
0.13
-0.05
-0.20
0.06
4.65
1.27
2.16
1.22
-0.01
-0.43
-0.07
-0.21
-0.14
-0.01
-0.87
-0.14
-0.30
-0.42
-0.01
-0.43
-0.10
-0.18
-0.15
0.00
0.02
0.00
0.02
0.00
-0.01
-0.77
-0.69
-0.22
0.14
25
Based on Total Trade Intensity
19942000 2008 1994 - 2011
1999
2007
2011
Average Total
Total
0.02
1.62
1.31
0.19
0.12
0.04
3.02
2.18
0.74
0.10
-0.01
-0.78
-0.31
-0.36
-0.11
0.02
1.45
0.98
0.16
0.31
0.02
1.09
0.38
0.40
0.31
-0.01
-0.38
0.06
-0.30
-0.14
0.08
5.69
-2.54
6.11
2.11
0.09
6.69
4.15
1.92
0.62
0.00
0.13
0.25
0.02
-0.14
0.04
2.84
1.70
0.94
0.20
0.00
-0.04
0.24
-0.07
-0.21
0.06
4.56
1.67
2.03
0.86
0.07
4.78
1.49
2.02
1.27
-0.01
-0.38
-0.03
-0.21
-0.14
-0.01
-0.87
-0.19
-0.27
-0.41
-0.01
-0.49
-0.10
-0.20
-0.19
0.00
-0.13
-0.07
-0.04
-0.02
-0.01
-0.90
-0.73
-0.31
0.13
Figure 1
The Path of Consumption per Capita
AUSTRIA_NCNSPC
BELGIUM_NCNSPC
12
CANADA_NCNSPC
12
11
10
10
9
9
8
8
FINLAND_NCNSPC
11
10
10
10
DENMARK_NCNSPC
11
9
8
8
8
6
7
6
4
4
6
2
70
75
80
85
90
95
00
05
10
7
70
75
80
FRANCE_NCNSPC
85
90
95
00
05
10
7
70
75
80
GERMANY_NCNSPC
11
10
85
90
95
00
05
10
5
70
75
80
GREECE_NCNSPC
11
12
10
10
9
85
90
95
00
05
10
70
75
80
IRELAND_NCNSPC
85
90
95
00
05
10
00
05
10
00
05
10
ITALY_NCNSPC
11
12
10
8
9
4
8
9
8
6
8
7
4
7
6
5
75
80
85
90
95
00
05
10
0
7
-4
2
6
70
8
0
70
75
80
LUXEMBOURG_NCNSPC
85
90
95
00
05
10
70
75
MEXICO_NCNSPC
80
85
90
95
00
05
10
70
75
80
NETHERLANDS_NCNSPC
85
90
95
00
05
10
70
9.0
11
10
12
10
8.5
10
8
10
9
6
8
4
7
2
8.0
7.5
7.0
6.0
80
85
90
95
00
05
10
6
70
75
80
SWEDEN_NCNSPC
85
90
95
00
05
10
75
80
85
90
95
00
05
10
00
05
10
0
70
US_NCNSPC
11
10.5
10.0
10.0
10
9.6
2
0
70
UK_NCNSPC
10.4
9.5
9.2
9
8.8
9.0
8.4
8
8.5
8.0
7.6
7
70
75
80
85
90
95
00
05
10
95
4
6.5
75
90
6
6
70
85
8
8
2
80
SPAIN_NCNSPC
12
4
75
PORTUGAL_NCNSPC
8.0
70
75
80
85
90
95
00
05
10
70
75
80
85
90
95
26
75
80
85
90
95
00
05
10
70
75
80
85
90
95
Figure 2
A_OPEN
Degree of Openness based on Trade Intensity
B_OPEN
1.2
1.0
CAN_O PEN
1.8
.9
1.6
.8
1.4
.7
D_OPEN
0.8
1.2
0.6
.5
0.8
70
75
80
85
90
95
00
05
10
1.0
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.6
.4
70
75
80
85
FR_O PEN
90
95
00
05
10
0.5
0.5
70
75
80
G _OPEN
.6
1.0
.6
1.0
0.4
F_OPEN
1.1
85
90
95
00
05
10
0.4
70
75
80
85
GR_OPEN
1.0
95
00
05
10
70
75
80
85
IR_OPEN
.7
90
95
00
05
10
00
05
10
00
05
10
IT_O PEN
2.0
.6
0.8
90
.6
1.6
.5
.5
.5
0.6
1.2
.4
.4
.4
0.4
.3
0.2
70
75
80
85
90
95
00
05
10
0.8
.3
.2
70
75
80
L_O PEN
85
90
95
00
05
10
0.4
70
75
80
85
MEX_OPEN
3.5
90
95
00
05
10
75
80
85
N_O PEN
.7
90
95
00
05
10
70
75
80
85
P_OPEN
1.6
.6
3.0
.3
70
1.4
90
95
SP_O PEN
.8
.7
.7
.6
.6
.5
.5
.4
.4
.3
.5
2.5
.4
1.2
2.0
.3
1.0
1.5
.2
1.0
.1
70
75
80
85
90
95
00
05
10
0.8
70
75
80
85
SW _OPEN
90
95
00
05
10
70
.7
.32
.6
.28
0.8
.5
.24
0.6
.4
.20
0.4
.3
80
85
90
95
80
85
00
05
10
90
95
00
05
10
00
05
10
.2
70
US_OPEN
1.0
75
75
UK_OPEN
1.2
70
.3
.16
70
75
80
85
90
95
00
05
10
70
75
80
85
90
95
27
75
80
85
90
95
00
05
10
70
75
80
85
90
95
Figure 3
Degree of Openness based on Import Intensity
A_MOPEN
B_MO PEN
.6
CAN_MOPEN
.9
.8
.5
D_MOPEN
.45
.55
.40
.50
.35
.45
.30
.40
.25
.35
.20
.30
F_MOPEN
.45
.40
.7
.35
.4
.6
.3
.30
.5
.2
.4
70
75
80
85
90
95
00
05
10
.15
70
75
80
FR_MOPEN
85
90
95
00
05
10
75
80
G_MOPEN
.32
85
90
95
00
05
10
.20
70
75
80
GR_MOPEN
.5
.28
.25
.25
70
85
90
95
00
05
10
70
75
80
IR_MO PEN
.40
.9
.35
.8
.30
.7
.25
.6
.20
.5
.15
.4
.10
.3
85
90
95
00
05
10
00
05
10
00
05
10
IT_MO PEN
.32
.28
.4
.24
.24
.3
.20
.20
.2
.16
.12
.1
70
75
80
85
90
95
00
05
10
70
75
80
L_MO PEN
85
90
95
00
05
10
70
75
80
MEX_MO PEN
1.6
85
90
95
00
05
10
.16
.12
70
75
80
N_MOPEN
85
90
95
00
05
10
70
75
80
P_MOPEN
.4
.8
.5
.3
.7
.4
.2
.6
.3
.1
.5
.2
.0
.4
.1
85
90
95
SP_MOPEN
.35
1.4
.30
1.2
.25
1.0
.20
0.8
.15
0.6
0.4
70
75
80
85
90
95
00
05
10
70
75
80
SW _MOPEN
85
90
95
00
05
10
70
75
80
UK_MOPEN
.5
.35
.4
.30
.3
.25
.2
.20
85
90
95
00
05
10
00
05
10
.10
70
US_MO PEN
.24
.20
.16
.12
70
75
80
85
90
95
00
05
10
.08
70
75
80
85
90
95
00
05
10
70
75
80
85
90
95
28
75
80
85
90
95
00
05
10
70
75
80
85
90
95
Figure 4
Consumption Gains from Trade based on Trade Intensity Measure of Openness
0.7
Austria gains
0.6
belgium1_gains
denmark_gains
0.5
finland_gains
france_gains
0.4
germany_gains
0.3
greece_gains
italy_gains
0.2
ireland_gains
0.1
lux_gains
netherlands_gains
-0.1
1994q1
1994q4
1995q3
1996q2
1997q1
1997q4
1998q3
1999q2
2000q1
2000q4
2001q3
2002q2
2003q1
2003q4
2004q3
2005q2
2006q1
2006q4
2007q3
2008q2
2009q1
2009q4
2010q3
2011q2
0
port_gains
spain_gains
sweden_gains
-0.2
uk_gains
us_gains
-0.3
canada_gains
-0.4
29
Figure 5
Consumption Gains from Trade based on Import Intensity Measure of Openness
0.7
austria_mgains
0.6
belgium_mgains
denmark_mgains
0.5
finland_mgains
france_mgains
0.4
germany_mgains
0.3
greece_mgains
ireland_mgains
0.2
italy_mgains
0.1
luxembourg_mgains
spain_mgains
-0.1
1994Q1
1994Q4
1995Q3
1996Q2
1997Q1
1997Q4
1998Q3
1999Q2
2000Q1
2000Q4
2001Q3
2002Q2
2003Q1
2003Q4
2004Q3
2005Q2
2006Q1
2006Q4
2007Q3
2008Q2
2009Q1
2009Q4
2010Q3
2011Q2
0
netherlands_mgains
portugal_mgains
sweden_mgains
-0.2
uk_mgains
us_mgains
-0.3
canada_mgains
-0.4
30