Volume 1
Issue 1
University of Toronto
Economic Review
Spring 2015
University of Toronto Economic Review
Volume 1, Issue 1
Spring 2015
University of Toronto Economic Review
Volume 1, Issue 1
University of Toronto Economic Review
Editors-in-Chief
Michael Boutros
David Cheng
Quan Le
Editors
Brianne Chan
Matthew Hong
Pujan Modi
Katherine Wang
Ian Weaver
The University of Toronto Economic Review gratefully acknowledges support from the
Department of Economics and the Economics Students’ Association at the University of
Toronto. The Review also appreciates advice from Professor Dwayne Benjamin in the
early days of this project and members of the faculty who supported us in completing
this issue. We are especially indebted to the teaching staff who assigned and graded
these written works.
The Department of Economics at the University of Toronto is located at 150 St. George
Street, Toronto, Ontario M5S 3G7, Canada.
All correspondence with the Review can be sent to [email protected].
ii
Front Matter
Spring 2015
Contents
Front Matter
iv
The Solow Growth Model in the 21st Century
Michael Boutros
1
Dollar General and Family Dollar Merger:
An Economic Analysis of Anticompetitive Effects
Rebecca Hensman
33
The Collapse of Bretton Woods System from the
Perspective of Gold
Yuchen Wu
43
An Insight on the Rationale of Using Expansionary
Monetary Policy during the Great Recession
Chifei Ma
58
On Valuing Life: Ecuador’s Yasunı́-ITT Initiative
and Payments for Ecological Services
Francesca Hannan
63
Contributors’ Spotlight
69
Editors’ Spotlight
70
iii
University of Toronto Economic Review
Volume 1, Issue 1
Mission Statement
Every semester, undergraduate students in the University of Toronto’s
rigorous undergraduate economics program produce original, creative, and
thoughtful works for a variety of courses. Students spend weeks carefully collecting data, discovering patterns, presenting results, and invoking thoughtful discussion. At the end of all this hard work, their labour of love is only
ever appreciated by one or two graders.
This certainly seems like a waste. Undergraduates are capable of producing high quality work that can be discussed and appreciated by other
undergraduates. Indeed, in drafting papers for advanced courses, it is not
uncommon to find students within the class discussing their papers and receiving valuable feedback. Undergraduates may have a more primitive toolbox of research tools than more seasoned economists, but we are still thirsty
for knowledge and eager to share our work with others.
The University of Toronto Economic Review provides a means through
which quality undergraduate papers can be shared with the entire academic
community. We are excited to present this inaugural edition as a first taste
of the University’s undergraduate quality, and we hope you find interesting
the selection of articles included.
Michael Boutros
Editor-in-Chief
iv
Front Matter
Spring 2015
Note from the Economics Students’ Association
Dear Readers,
The Economic Students’ Association, like its name embodies, is a club
by the students and for the students. Our mission has always been to enrich
the undergraduate experience and to provide students with a platform for
success.
This journal is an integral part of that platform. For the students, it is
a medium through which they can be recognized outside the lecture hall.
For everyone else, it is a curated collection that showcases the best from a
world-class economics program.
We are tremendously excited to launch this inaugural edition. We hope
it lays the foundation for years to come.
David Cheng
Editor-in-Chief
President of the Economics Students’ Association
v
University of Toronto Economic Review
Volume 1, Issue 1
Dear Readers,
In October 2014, Michael, David and I had our first meeting of the Review’s editorial team. We agreed that our top challenge was to immediately
establish the project’s academic credentials as a rigorous review of quality
work by the university’s undergraduates. Furthermore, we had to ensure
that this project was sustainable in the upcoming years. We were very lucky
to be joined by five highly committed editors sharing our goals.
As a team we quickly learned that publishing a complete journal issue is
not easy work. Our submission window opened in December 2014, accepting
coursework carried out in the previous calendar year. The selection process
was done throughout February 2015 where we faced many difficult choices.
Editing and finally publishing required careful thoughts and communication
among the editorial team. Naturally, there is no particular reason that a
work compiled by a team of eight should represent a consensus on content
or style. This issue is the final product of many hours of deliberation.
We start with Michael’s own work on estimating Mankiw, Romer, and
Weil (1993)’s standard and augmented Solow models, making his own contribution to the empirics of macroeconomic growth. The decision to make
this work the headlining piece was made by the rest of the team and treated
with due process. We then present Rebecca Hensman’s excellent case study
written for her fourth-year course Mergers and Competition Policy. For our
third paper, Yuchen Wu looks at the collapse of Bretton Woods system.
Another economic history piece is then featured with Chi-Fei Ma’s analysis on expansionary monetary ideology during the Great Recession. Last
but not least, Francesca Hannan’s essay applies economic theory to critique
Ecuador’s abandonment of a national park protection scheme.
The discipline of economics grows each day by the sharing of ideas. Thus
by adding to this conversation, we hope to make our however modest contribution to its welfare. With that in mind, I am proud to present the inaugural
issue of the Review, the first ever economics journal published by undergraduates at the University of Toronto.
Quan Le
Editor-in-Chief
vi
The Solow Growth Model in the 21st Century
Michael Boutros
1
Introduction
The Solow growth model (1956) was first empirically tested by Gregory N.
Mankiw, David Romer and David N. Weil (hereafter MRW) in 1993. They
estimate the Solow model by manipulating its key equations into a linear
function that is well suited for econometric analysis.1 Given the construction of this linear function, estimates for the explanatory variables can be
used to predict values for the shares of income for capital and labour. They
show that the model proposed by Solow fit data from 97 countries over the
period 1960 – 1985 with an R2 value of 0.59. MRW use constrained regressions to predict shares of income for capital and labour of approximately
and
1
,
3
2
3
respectively. These predictions are extremely inconsistent with other
empirical works, and MRW discard the standard model as economically insignificant.
MRW extend the model to include human capital as a third input of
production. They reason that this explanatory variable entered the error
term in their first regression, biasing the estimates and predicting inaccurate
shares of income. Again using data from 1960 - 1985, they estimate the
augmented Solow model and find significant results. The new estimation has
both a higher R2 of 0.78 and shares of income of approximately
1
3
for each
input (physical capital, human capital, and labour). These estimates are in
line with other empirical estimates. Estimations of the augmented model
are both statistically and economically significant. MRW conclude that the
Solow model with the addition of human capital is relevant in empirical
growth economics.
But the dataset used by MRW encompassed 1960 – 1985 and is now
1
The linear function has a constant term, several measurable variables, and an unobservable error term.
1
University of Toronto Economic Review
Volume 1, Issue 1
almost 30 years old. Using more recent data, we aim to determine if either
version of the Solow model still caries any statistical or economic significance.
Is physical capital accumulation still a relevant factor in economic growth?
Is human capital accumulation still a relevant factor in economic growth?
Reestimating the model is important because if physical and human capital
accumulation are no longer drivers of economic growth, then where will
future economic growth come from? This paper does not aim to answer this
question, but rather determines if the question even needs an answer for the
time being.
Section 3 reviews related literature. In section 4, I fit the standard Solow
model to cross sectional data constructed using data from 1970 to 2010 for 52
countries. Given only labour and capital, the model provides a strong fit for
the data, explaining almost two thirds of all variation. As with MRW, the
model is economically insignificant because its predictions regarding inputs’
shares of income are inconsistent with other empirical estimates. In section
5, I estimate the augmented Solow model using data from 1970 to 2010 for
49 countries. First, I use a superior measure to proxy for the savings rate of
human capital and include country-specific depreciation rates. I find similar
results as MRW but with a very significant difference: without enforcing any
constraints on the regression, the relationship between parameters predicted
by the model is observed. The unconstrained regression predicts values for
the inputs’ shares of income that are consistent with MRW and other empirical estimations. We see that the augmented Solow model is still very
significant and that economic growth can still largely be attributed to the
three basic inputs highlighted by Solow and MRW.
Next, I manipulate the augmented model’s key equations to use the level
of human capital versus its savings rate. Although this measure increases the
model’s fit, the predicted shares of income are very inconsistent with other
estimations and violate the basic assumptions of the model. The strong
fit implies that the level of human capital is a good explanatory variable
for GDP per capita, but current measures of this level are unsuitable for
estimating the Solow model. In section 6, I more carefully analyze the regression’s specification issues and discuss why OLS may still be appropriate.
Section 7 concludes.
2
Solow Growth Model in the 21st Century
2
Michael Boutros
Literature Review
The seminal work by MRW inspired two streams of related literature: works
critiquing their methods and results, and works attempting to address those
critiques. Temple (1999) and Islam (1995) are two of many papers giving
fair but ominous overviews of the econometric problems prevalent in MRW’s
estimation. These issues are discussed in detail in section 6. MRW’s estimations have two key issues: endogeneity and measurement error. The more
significant of these is endogeneity; by using simple OLS, they completely
ignore endogeneity in the explanatory variables, biasing their results.
One way to deal with endogeneity is by using instrumental variable regressions. Unfortunately, finding instruments for the explanatory variables
in our regression is notoriously difficult (Temple, 1999). Instead, economists
use panel data with the lagged dependent variable as an instrument. Many,
many authors have gone this route: Das (2013) and Arnold, Bassanini and
Scarpetta (2007) use panel data for the OECD countries, Hoeffler (2002) uses
time series data for Africa, Knight and Ding (2009) use time series data for
China, Kalaitzidakis and Korniotis (2000) use panel data for the G7 and G3
countries, and Klemp (2011) uses panel data for the G7 countries, Denmark,
Norway and Sweden. Each paper uses these limited samples and various
advanced econometric techniques to estimate both the standard and augmented Solow model, and each paper finds results for shares of income that
are in line with MRW’s. They also find that the direction and relative magnitude of each estimated coefficient is the same as in MRW’s results.2 Others
have taken more creative approaches to dealing with endogeneity. DeLong
(1996) incorporates endogeneity directly into his model by constructing the
evolution of human capital to incorporate the level of GDP and other relevant variables. Although this significantly complicates the model and makes
regression analysis more difficult, this alternative approach allows treatment
of endogeneity with more traditional data.
Measurement error is of concern in MRW, but fault does not lie with
the authors. They construct their variables given what data was available
2
As we see in sections 4 and 5, shares of income are estimated using the savings
rates of both physical and human capital. If shares of income are similar across different
regressions, then the relationship between the two savings rates must also be similar, at
least proportionally.
3
University of Toronto Economic Review
Volume 1, Issue 1
at the time. Only recently has there been reliable data on variables such as
educational enrollment or the depreciation rate. All of the papers mentioned
above implement more reliable measures of the savings rate of human capital
using some education-related indicator as a proxy. Additionally, these papers
all hold the depreciation rate constant between countries. Although this
may seem trivial, our results show that varying the depreciation rate adds
significance to the model. As data collection techniques improve and more
countries are included in freely available datasets, the Solow growth model
can be more rigorously tested, and measurement error becomes less of an
issue.
The key takeaway from the related literature is that when endogeneity
and measurement are rigorously treated in a variety of ways, MRW’s results
are confirmed. It is important to address these issues but even when they are
not treated, there is no significant benefit as the results are not significantly
different. The cost, however, is that samples are much more restrictive.
Detailed panel data is not widely available for a large amount of countries,
forcing single-country analysis. This single-country analysis is important for
explaining within-country growth but gives no indication as to global trends.
Additionally, single-country analysis can introduce new issues. For example,
yearly data for secondary school enrollment is exclusive to countries with
high GDP, presenting selection bias as a possible issue with these restrictive
samples.
This paper seeks to fill a void in the current literature by reestimating
MRW’s exact specification using similarly-constructed data gathered in the
time since their paper was published. Although some significance is lost by
ignoring endogeneity, the benefit is that we can include many more countries
in our analysis, which is important for answering our main research questions
as outlined in 1.
3
Data
Most data is sourced from version 8 of the Penn World Table (Feenstra,
Inklaar and Timmer, 2013a). The dependent variable, GDP per capita, is
calculated using total GDP and the size of the labour force in 2010. The
population growth rate is averaged from the year-over-year growth rates of
4
Solow Growth Model in the 21st Century
Michael Boutros
the labour force from 1970 to 2010. The depreciation rate is averaged for
each country using yearly rates from 1970 to 2010.
A key variable used in our analysis is human capital. Some authors,
such as Temple (1998), manually construct a measure of human capital by
multiplying the labour force by the average years of schooling. In the same
spirit, the Penn World Table combines data on average years of schooling
from Barro and Lee (2010) and the rate of return from a given amount of
schooling from Psacharopoulos (1994). Naturally, human capital is increasing in both. An exhaustive search finds that only the Penn World Table
provides enough data on human capital to support a cross-country analysis. The level of human capital has no natural interpretation and is used
mainly to compare across time and between countries. One issue with this
measure of human capital is that differences in ability are not fully captured
by differences in durations of schooling (Hanushek and Woessmann, 2012).
Recognizing this, we still use the World Table’s measure of human capital
as no superior alternatives exist.
The major caveat with this measure of human capital is that it focuses
only on education, completely ignoring health and other factors that are
certainly relevant. It is already difficult to quantify the effect of education
on human capital, and this problem is even more significant with the health
portion of human capital. This problem is endemic to all measures of human
capital: most indicators cannot be directly observed (Liu and Fraumeni,
2014). Because of this, we must instead use intermediate variables that can
be observed, and hope that these intermediate variables are good proxies for
the real value.
Similar problems exist for the savings rate of human capital. Intuitively,
the rate should capture the proportion of total wealth directed towards improving one’s own capital. There is no clear measure of this intuitive savings
rate and thus we look to use a proxy. Any proxy used must be at least proportionally related to the real value of the savings rate. If this is true, then
the estimated coefficients in our OLS regression with the proxy will be equal
to the estimated coefficients in an OLS regression with the true value of this
savings rate,3 with the difference in proportion entering only the constant
term.
3
This result is proved in appendix B.1.
5
University of Toronto Economic Review
Volume 1, Issue 1
Ignoring investment in health, a natural candidate for the savings rate of
human capital is the proportion of GDP dedicated to educational spending.
Surprisingly, we find that this figure and GDP per capita are negatively
correlated with correlation coefficient −0.238. A report by the OECD (2011)
finds that for a panel of 29 countries, only 17 matched increases in GDP
between 2000 and 2008 with increases in the proportion of GDP devoted
to education, implying that although the two are related, there is no clear
direct relationship. Fernandez and Rogerson (1997) examine panel data for
US states over the period 1950 to 1990 and find strong evidence that the share
of personal income devoted to education is unaffected by growth in income.
Instead, McLendon, Hearn and Mokher (2009) find strong empirical evidence
that other factors, such as politics and demographics, play a significant role
in determining educational spending. These findings discard the proportion
of GDP dedicated to educational spending as a good proxy for the savings
rate of human capital.
Instead, most related literature uses some measure of youth participation
in the education system as a proxy for the savings rate of human capital. For
example, Das (2013) uses the percentage of population aged 15-64 who have
secondary schooling years. MRW construct a proxy that measures approximately the percentage of the working-age population that is in secondary
school. Both authors concede that these measures are far from perfect. The
measure used by MRW is especially crude: they divide the number of students eligible for school (aged 12 to 17) into the number of youth in the
workforce (aged 15 to 24). MRW were limited in 1993 by a lack of data
regarding educational enrollment. Today, however, this type of data is much
more readily available. In this paper, secondary school net enrollment rates
from UNESCO are used to proxy the savings rate of human capital. This is
the same measure used by MRW except properly constructed using balanced
data.
Only countries which have data for every single year between 1970 and
2010 are included. In total, data from 52 countries is used in our analysis.
For three of these countries (China, India, and Brazil), there is insufficient
data for the savings rate of human capital. Given the already small sample
size, these countries are included when analyzing the standard model and
augmented model with the level human capital, but excluded from analysis
6
Solow Growth Model in the 21st Century
Michael Boutros
when estimating the augmented model with the savings rate of human capital. Summary statistics for key variables are available in table 5 in appendix
A.2. A full list of the countries used in our analysis is found in appendix
A.1.
4
The Standard Solow Growth Model
The standard Solow model uses a standard Cobb-Douglas production function with two inputs:
Yt = F (Kt , Lt ) = Ktα (At Lt )1−α
(1)
where K is capital, L is labour, A represents technology, and α ∈ (0, 1).
This particular form of the production function defines α as capital’s share
of total income, leaving (1 − α) as labour’s share of total income.
Together, technology and labour form the effective labour force. In contrast to MRW, we consider a discrete version of the model since this is more
in line with our discrete dataset. We divide both sides of the equation by the
effective labour force to arrive at output per effective unit of labour, denoted
in the lower-case glyph of its aggregate counterpart:
yt = ktα
(2)
Labour and technology grow linearly at rates n and g, respectively:
Lt+1 = (1 + n)Lt
(3)
At+1 = (1 + g)At
(4)
The evolution of capital is governed by:
Kt+1 = (1 − δ)Kt + sYt
(5)
where δ is the depreciation rate and s denotes the the savings rate. The
evolution of capital can also be expressed per effective unit of labour:
kt+1 =
syt + (1 − δ)kt
(1 + n)(1 + g)
7
(6)
University of Toronto Economic Review
Volume 1, Issue 1
The economy is in steady-state equilibrium when capital per effective
unit of labour remains constant between periods, or k∗ = kt = kt+1 .
Inserting this identity into (6), we find the exact level of capital, and then
income, at which the economy reaches steady state:4
k∗ =
y∗ =
s
n+g+δ
s
n+g+δ
1
1−α
(7)
α
1−α
(8)
This result is formally derived in appendix B.2. In any given year of equilibrium, yt = y ∗ . Recall that yt is defined in terms of effective units per labour,
but for our analysis, we are interested in GDP per capita:
α
1−α
Yt
s
= At
Lt
n+g+δ
(9)
Given that technology grows linearly, we have that At = (1 + g)t A0 . Using
this equation and taking logs yields the following:
ln
Yt
α
α
= ln A0 + t ln (1 + g) +
ln s −
ln (n + g + δ)
Lt
1−α
1−α
(10)
For any given country, technology consists of two parts. The first, ω, captures
the world level of technology, and is constant for all countires. The second, ,
captures any country-specific advantage in technology. Combining this with
(10) at equilibrium time t = 0 (for simplicity) provides a basic econometric
model:
ln
Y
L
=ω+
α
α
ln s −
ln (n + g + δ) + 1−α
1−α
(11)
In our estimations, we use data from 2010 as the steady-state year. Therefore, for any country i, we have:
Y2010,i
α
α
ln
=ω+
ln si −
ln (ni + g + δi ) + i
L2010,i
1−α
1−α
(12)
We estimate this model twice. In both estimations, we hold g constant to
4
The denominators of these equations contain another term, ng, conventionally omitted since it is approximately zero.
8
Solow Growth Model in the 21st Century
Michael Boutros
2%. In the first estimation, we hold δi constant to 3% for all i. Footnote 7 of
MRW discusses these choices of δ and g. Essentially, these figures are chosen
to match aggregate US data constructed by the authors. Slight variations
do not significantly affect regression results. In the second estimation, we
deviate from MRW and all existing literature by using country specific values
for δi .
4.1
Evaluating the Standard Model
As with most regressions, the estimated parameters’ first purpose is to determine a cause and effect relationship between the dependent and independent
variables. In evaluating the model’s overall significance and the significance
of each estimate, we look at the R2 value, the F -statistic, and t-statistics.
These form the basis of evaluating an estimation’s statistical significance.
Each estimation also has a second and more important purpose. Given
that we are estimating a model that carries its own assumptions, the results
from the estimation are used primarily to determine the validity of the model.
There are two model-specific tests that together test the validity of our
assumptions. If the conditions imposed by these two tests are not satisfied,
the model’s assumptions are invalid and thus the model is itself invalid.
The main assumption we make in deriving our estimated equation from
the Solow growth model is that each country is at its steady-state level
of output per capita. Given this, the model predicts that the parameters
for s and n + g + d are opposite in sign and equal in magnitude. Even
if the parameters do not naturally meet this restriction, we can explicitly
constrain the regression and test the statistical significance of the constrained
regression using traditional methods. This is the first test.
Additionally, we see in (12) that each estimated coefficient is a function of
α. If the two estimates are opposite in sign and equal in magnitude (either
naturally or via the constrained regression), we can determine an implied
value of α. Consensus amongst economics (see the related literature in 2)
is that for a standard Cobb-Douglas production function with only capital
and labour, α = 13 . Our estimation must predict a similar value for α. This
is the second test.
Together, the two tests determine the economic significance of the model.
Even if the estimation is very statistically significant, it can be economically
9
University of Toronto Economic Review
Volume 1, Issue 1
insignificant. In this case, the model is discarded as invalid, and we must
look to a different model to explain and predict economic growth.
4.2
Estimation Results
The standard model is estimated using ordinary least-square regression. Results are presented in table 1. In column (1), the model is fitted where
g + δ = 5%, as in MRW and related works. In column (2), g = 2% and δ
varies between countries. In columns (3) and (4), the the regressions in (1)
and (2) are replicated but with the expected relationship between parameters
(as in (12)) is explicitly enforced via a constrained regression.5
Table 1: Regression Results for Standard Solow Model
ln s
ln (n + g + δ)
Constant
R2
F
Implied value of α
N
Unconstrained Reg.
(1)
(2)
0.903∗
1.091∗∗
(0.379)
(0.402)
Constrained Reg.
(3)
(4)
1.564∗∗∗
1.479∗∗∗
(0.236)
(0.246)
-3.508∗∗∗
(0.769)
-2.573∗∗∗
(0.696)
-1.564∗∗∗
(0.236)
-1.479∗∗∗
(0.246)
14.28∗∗∗
(2.394)
0.557
37.15
–
52
12.26∗∗∗
(2.358)
0.459
24.22
–
52
8.506∗∗∗
(0.318)
0.475
43.73
0.61
52
8.808∗∗∗
(0.291)
0.431
36.11
0.60
52
Standard errors in parentheses.
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
The estimation in (1) with fixed δ provides a very strong fit for the
data. Astoundingly, this simple model of only capital and labour accounts
for almost 56% of variation between countries. All estimates are statistically
significant and the F -statistic indicates the model as a whole is statistically
significant.
The two tests for economic significance are both failed. The coefficients
are opposite in sign but differ greatly in magnitude. Although the constrained regression in (3) is statistically significant, the values imply an α
5
See appendix B.4 for a discussion of constrained regressions.
10
Solow Growth Model in the 21st Century
of almost
2
,
3
much higher than the expected
Michael Boutros
1
.
3
While the model with fixed
δ is statistically significant, it is economically insignificant, and therefore
inadequate for discussing economic growth.
The simple model with varying δ performs only slightly better. Again,
the high R2 of approximately 0.46 and F -statistic show that the estimation
in column (2) is statistically significant, although less so than the first estimation. The implied value of α in column (4) is still far too high, discarding
the model as economically insignificant. However, it is important to note
that the coefficients in (4) are slightly closer in magnitude than those in (3).
This is the condition of the first test for economic significance. The standard
literature often assumes that δ is constant across countries, but this result
shows that varying δ has a material impact on the regression results and
brings them closer in line with the model’s predictions.
This slight increase in economic significance outweighs the loss in statistical significance, and so we focus on interpreting the estimates in column
(2). The results estimate that a 1% increase in the savings rate will increase
GDP per capita by approximately 1.09%. A 1% increase in the growth rate
of technology, population growth rate, or depreciation rate will decrease
GDP per capita by approximately 2.57%. Clearly, both of these estimates
are far too high, and indicate further that the regression is not economically
significant.
5
The Augmented Solow Model
The augmented model presented by MRW adds as an additional input to
the production function:
Yt = F (Kt , Ht , Lt ) = Ktα Htβ (At Lt )1−α−β
(13)
where K is physical capital, H is human capital, L is labour, A represents
technology. α is physical capital’s share of income, β is human capital’s
share of income, and (1 − α − β) is labour’s share of income. MRW impose
three restrictions on α and β: α ∈ (0, 1), β ∈ (0, 1), and α + β ∈ (0, 1).
These technical restrictions are a product of two intuitive restrictions that
economists generally agree on: firstly, the production function demonstrates
decreasing returns to scale, and secondly, the individual inputs (K, H, and
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University of Toronto Economic Review
Volume 1, Issue 1
L) are all decreasing in marginal product.
Dividing both sides by zL again yields output per effective unit of labour:
yt = ktα hβt
(14)
Labour and technology grow as in equations (3) and (4). In this model, both
physical and human capital evolve in the same way, except with different
saving rates:
Kt+1 = (1 − δ)Kt + sk Yt
(15)
Ht+1 = (1 − δ)Ht + sh Yt
(16)
For simplicity, we assume both types of capital depreciate at the same rate.
The evolution of capital can be expressed per unit of effective labour:
sk yt + (1 − δ)kt
(1 + n)(1 + g)
sh yt + (1 − δ)kt
=
(1 + n)(1 + g)
kt+1 =
(17)
ht+1
(18)
In steady state, we require both physical and human capital per effective
unit of labour to remain constant between periods: k∗ = kt = kt+1 and
h∗ = ht = ht+1 . The steady state levels are derived by substituting these
equalities into (17) and (18):
∗
k =
"
sβh s1−β
k
n+g+δ
s1−α
sα
k
h
h =
n+g+δ
∗
#
1
1−α−β
1
1−α−β
(19)
(20)
These equations are formally derived in appendix B.3. Substituting these
equations into the production function, converting to per capita units, expanding the technology term, and taking logs gives as an econometric model
12
Solow Growth Model in the 21st Century
Michael Boutros
similar to (12), again at t = 0 for convenience:
ln
Y
L
=ω−
α+β
α
ln (n + g + δ) +
ln sk
1−α−β
1−α−β
β
+
ln sh + 1−α−β
(21)
In our estimations, we use data from 2010 as the steady-state year. Therefore, for any country i, we have:
ln
Y2010,i
L2010,i
=ω−
α+β
α
ln (ni + g + δi ) +
ln (sk )i
1−α−β
1−α−β
β
+
ln (sh )i + is (22)
1−α−β
Additionally, we can combine the steady-state level of human capital in
(20) with (22) to form a model that incorporates the level of human capital
instead of its savings rate:
ln
Y2010,i
L2010,i
=ω−
α
α
ln (ni + g + δi ) +
ln (sk )i
1−α
1−α
β
+
ln (h2 010) + 1−α
(23)
This result is also formally derived in appendix B.3. As MRW point out, the
augmented model in (23) is almost exactly identical to the simple model in
(12). The explicit human capital term in the augmented model is captured
in the simple model’s error term, biasing the other terms in the simple regression and skewing the prediction of α. A regression including the human
capital term should extract a less biased estimate for the coefficients on the
other terms and a more realistic prediction for α.
Again, we estimate each model twice. In all estimations, we hold g
constant to 2%. In the first estimation of each model, we hold δi constant
to 3% for all i, and in the second, we use country specific values for δi .
5.1
Evaluating the Augmented Model
As with the standard Solow model, evaluating the augmented model goes
beyond considering only its statistical significance. The augmented model
also provides two tests which determine the economic significance of the
13
University of Toronto Economic Review
Volume 1, Issue 1
model. Without economic significance, the augmented model is invalidated.
Again, the main assumption in the augmented model is that each country
is in steady-state equilibrium. Given this, the model predicts a specific relationship between the parameters in (22), forming the first test for economic
significance. The relationship between the estimates is slightly more complicated than in the standard model, but can still be used to derive implied
values for α and β, forming the second test for economic significance.
We first consider the augmented model with the savings rate of human
capital. In the following, let each term represent the coefficient on that term
as in (22). Then:
ln (n + g + δ) = −( ln sk + ln sh )
(24)
When the model is estimated, we are left with a system of two unknowns
and three equations, guaranteeing a unique implied value for both α and β.
In the augmented model with the level of human capital, the only equality
implied in the parameters is that the coefficients on sk and ln (n + g + δ)
are opposite in sign and equal in magnitude; this is the exact same as in the
standard model. This is the first test of economic significance.
When the model is estimated, an implied value of α is obtained. Then,
from (23), we see that the estimate for the final parameter h is a function of
both α and β. We solve for β using the estimated parameter for h and the
implied value of α. As with the standard model, we should expect to see a
value for α of around
1
.
3
MRW suggest that β should be between
1
2
and
2
3
given the following definition:
In the United States the minimum wage—roughly the return
to labour without human capital—has averaged about 30 to 50
percent of the average wage in manufacturing. This fact suggests
that 50 to 70 percent of total labour income represents the return
to human capital, or that β is between one third and one half.
However, in their own empirical tests of the model, they find that β is approximately 0.28. The works cited in the literature review section of this paper
all found similar values for β. Additionally, later work by other economists
explicitly estimating β found similar results. Acemoglu (2009) used data
from 100 countries over the period 1960 to 2000 and found β = 0.26. Steffen
14
Solow Growth Model in the 21st Century
Michael Boutros
(2013) used panel data for Germany from 1976 to 2000 and also estimated
β = 0.26. Overall, these estimates point to an approximate value of β = 13 ,
and this is the value which we use in our second test of economic significance.
5.2
Estimation Results with the Savings Rate of Human
Capital
Table 2 reports results from estimating the augmented version of the model
with the savings rate of human capital. In columns (1) and (3), g + δ = 5%,
while in columns (2) and (4), g = 2% and δ varies across countries.
Table 2: Regression Results for Augmented Solow Model
(Savings Rate of Human Capital)
Unconstrained Reg.
(1)
(2)
0.415
0.510
(0.329)
(0.355)
ln sk
Constrained Reg.
(3)
(4)
0.616∗
0.533
(0.335)
(0.358)
ln (n + g + δ)
-2.240∗∗∗
(0.565)
-1.379∗
(0.547)
-1.350∗∗∗
(0.211)
-1.279∗∗∗
(0.233)
ln sh
0.661∗∗∗
(0.186)
0.738∗∗
(0.216)
0.733∗∗∗
(0.191)
0.746∗∗∗
(0.201)
10.77∗∗∗
(1.625)
0.712
33.54
–
–
49
8.714∗∗∗
(1.534)
0.662
22.10
–
–
49
8.157∗∗∗
(0.273)
0.697
44.21
0.26
0.31
49
8.407∗∗∗
(0.280)
0.661
32.96
0.23
0.33
49
constant
R2
F
implied value of α
implied value of β
N
Standard errors in parentheses
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
The augmented model with the savings rate of human capital fits the data
very well, accounting for 71% of variation when g and δ are held constant.
The estimates for ln (n + g + δ) and ln sh are significant at the 1% level,
and the F-statistic shows that the model statistically significant.
The coefficients on ln sk and ln sh sum to 1.076, although the model
15
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Volume 1, Issue 1
predicts they should sum to 2.240, the magnitude of the coefficient on ln (n+
g +δ). When the OLS regression is restricted to enforce this equality, column
(3) shows that the implied α and β are both within the acceptable range of
what we expect to find for these two values. The restricted OLS regression
is statistically significant for all estimates and again has a high R2 and F statistic. Both tests of economic significance are passed, although the first
test is reliant on a constrained regression. These findings strongly indicate
that the augmented Solow model does a much better job of aligning theory
with data versus the simple model. Not only has statistical significance
increased, but the implied values for α and β indicate that the model is
economically significant.
These findings are corroborated in column (2) when δ is allowed to vary.
Although R2 decreases slightly, the model is still a very strong fit and the
F statistic implies the model is overall significant. The most valuable result
from (2) is that the expected relationship between parameters is observed
without enforcing any constraint: the sum of the estimates on ln sk and
ln sh is 1.248, just shy of 1.379, the model’s prediction. The implied α of
0.23 is slightly smaller than other estimates,6 but still very plausible. The
implied β of 0.33 falls in line with previous predictions. By varying δ, the
economic significance of the estimation increases significantly. Unlike the
standard model or even the augmented model with a constant δ, the patterns
naturally observed in the data are those predicted by the model. Both tests
of economic significance are passed, and this is the only regression where
we find both statistical and economic significance without any constrained
regression.
For this reason, the estimates in column (2) are used for interpretation.
Although the estimate for sk is statistically insignificant on its own, it is
economically significant as it fits the model’s predictions when combined with
the other estimates. The model predicts than a 1% increase in the savings
rate of capital increases GDP per capita by 0.51%. A 1% increase in the
savings rate of human capital has a larger effect, increasing GDP per capita
by 0.74%. A 1% increase in the growth rate of technology, population growth
rate, or depreciation rate will decrease GDP per capita by approximately
6
It is likely the case that this very small redistribution of income shares is due to
measurement differences, not an underlying trend in the data.
16
Solow Growth Model in the 21st Century
Michael Boutros
1.34%. These estimates are still fairly large, but clearly an improvement
in realism over the estimates from the standard model. Again, we are more
concerned with the direction and relative magnitude of each coefficient versus
its absolute level. These results predict that physical capital accumulation is
important but human capital accumulation is more important. This falls in
line with the results predicted by other recent estimates (Das, 2013; Koutun
and Karabona, 2013; Knight and Ding, 2009).
5.3
Estimation Results with the Level of Human Capital
Table 3: Regression Results for Augmented Solow Model
(Level of Human Capital)
Unconstrained Reg.
(1)
(2)
0.443
0.522
(0.260)
(0.283)
Constrained Reg.
(3)
(4)
0.783∗∗∗
0.695∗∗
(0.221)
(0.214)
ln (n + g + δ)
-2.026∗∗∗
(0.414)
-1.258∗∗
(0.414)
-0.783∗∗∗
(0.221)
-0.695∗∗
(0.214)
ln h2010
3.083∗∗∗
(0.373)
3.395∗∗∗
(0.386)
3.345∗∗∗
(0.408)
3.481∗∗∗
(0.391)
constant
9.718∗∗∗
(1.435)
0.772
–
–
58.51
52
7.857∗∗∗
(1.455)
0.736
–
–
46.12
52
6.016∗∗∗
(0.374)
0.744
0.44
1.87
70.77
52
6.075∗∗∗
(0.373)
0.729
0.41
2.05
68.97
52
ln sk
R2
implied value of α
implied value of β
F
N
Standard errors in parentheses.
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 3 reports results from estimating the augmented version of the
model with the level of human capital. In columns (1) and (3), g + δ = 5%,
while in columns (2) and (4), g = 2% and δ varies between countries.
This third version of the model provides the most superior fit for the data,
accounting for 77% of variation between countries when g + δ is held fixed.
Two of three estimates are statistically significant, and the F -statistic indi17
University of Toronto Economic Review
Volume 1, Issue 1
cates the model is significant. When δ is varied, the data accounts for 74%
of variation between countries, again the strongest fit of the three models.
In columns (3) and (4), the regressions are constrained such that α and β
can be estimated. In these regressions we find that the model is completely
economically insignificant. The results do not come even close to matching
the model’s predicted relationship between estimates, failing the first test
of economic significance. When the regressions are constrained, the implied
values for α are higher than expected, but still plausible. The values for β
are extremely high and far outside the range predicted by previous empirical
works, failing the second test of economic significance.
Even worse, the implied values of α and β violate the model’s basic
assumptions. The value for β is greater than 1, violating the assumption
that human capital is decreasing in marginal product. The sum of these
two estimates violates the assumption that α + β < 1 and implies that
the economy has more than quadrupling returns to scale. These flagrant
violations of the model’s core assumptions render the estimations even more
economically insignificant, and interpreting the estimates is worthless.
Given that the augmented model is both statistically and economically
significant when sh is used, we attribute this version of the model’s poor
economic significance to the way h is measured. Recall that educational
enrollment was used as a proxy for the savings rate of human capital with
the justification that if the proxy was at least proportionally related to the
true value, the estimates would be the same. In this case, we can conclude
that this measure of h is not even proportionally related to the true value
of h, likely due to the construction of h and its shortcomings discussed in
section 3. Although the idea of using the level of human capital seemed
promising, and the data for h is significant in explaining variation, this
particular construction of h is not suitable for this model.
6
Specification Issues with the Solow Model
The specification used by MRW is no stranger to criticism. Temple (1999)
and Islam (1995) discuss a variety of specification errors in great detail.
Four of these issues are highlighted below and analyzed with respect to the
estimations in this paper.
The first issue is parameter heterogeneity. Durluaf, Kourtellos and Minkin
18
Solow Growth Model in the 21st Century
Michael Boutros
(2001) discusses that while the Solow model may be relevant for individual
countries, it is implausible that the estimated parameter regarding the savings rate of capital can be equally relevant for two very different countries.
It is important to remember that the parameter represents an “average”
affect amongst all countries in the sample. Our purpose is not to make
predictions for specific countries, but rather to make a general statement regarding, for example, the effect of the savings rate of capital on the growth of
GDP per capita. To this end, the only test for parameter relevance is model
significance. We find that the model is both statistically and economically
significant, with more than two thirds of all parameter estimates also significant. Although we cannot speak to parameters for individual countries, we
are confident in our estimates for capturing global trends and validating the
model in general.
The second issue is measurement error. This was a much larger issue 10
– 15 years ago when demand for growth empirics was high while supply for
clean, consistent data was low. In the time since, many reliable resources
have been created to meet this demand, and finding good data is no longer
as difficult as it once was. This is evident even in this paper, where the
net enrollment ratio for secondary school was acquired for all countries in
the sample from a single source. In contrast to the crude construction of
this variable by MRW, it is clear that datasets today are much more robust
than they were in the past. Of course, there will always be some error when
measuring macro variables such as GDP and labour force participation, but
these are unavoidable and should not deter us from performing analysis on
what data we do have.
The third issue is endogeneity. Clearly, human capital affects GDP per
capita, but it is equally clear that GDP per capita also affects human capital.
For example, in an economic boom that increases GDP per capita, people
may be able to afford better health care, increasing their human capital. Instrumental variables are the tool of choice for dealing with endogeneity, but
finding a good instrumental variable for which data for many countries and
many years is available is a very difficult task. Several papers using panel
data with lagged instrumental variables were discussed in section 2. As time
passes and more panel data is collected, endogeneity can be better treated.
Similar to the issue with measurement data, supply for good data is increas19
University of Toronto Economic Review
Volume 1, Issue 1
ingly meeting demand, and future work will benefit from this better data.
At the same time, however, an empirical work ignoring endogeneity should
not be automatically invalidated. Recent literature highlighted in section 2
shows that treating endogeneity does not significantly change MRW’s result.
Therefore, in this paper, we make no attempt at dealing with endogeneity,
allowing us to include a wider selection of countries in our dataset.
The last issue with our data is heteroskedasticity. There is simply no
claim to be made for homoskedasticity as it is intuitively clear that the variances of error terms are grouped together by some factor(s). The most obvious of these is location, and indeed “it is often the case that regional dummies add substantially to a growth regression’s explanatory power.” (Temple,
1999; DeLong and Summers, 1991). We test for homoskedasticity using the
Breusch-Pagan test discussed in Wooldrige (2013, p. 277). The BP test regresses the squared OLS residuals on the explanatory variables and tests for
the model’s significance. If the model is significant, then the error term is
dependent on the explanatory variables, and the data is not homoskedastic.
In the BP test, H0 = homoskedasticity and HA = heteroskedasticity. Table
6 in appendix A.3 reports the p-values from the test for each regression. The
null hypothesis is rejected in all six cases at the 15% significance level, with
four rejections at the 5% level. Given that the p-values are not significantly
large, we use heteroskedasticity-robust standard errors in all regressions instead of performing more drastic manipulations of the dataset.
In hindsight, the use of OLS regression produces results that match our
theory, indicating that the regression technique does a fairly good job regardless of any specification problem.7 In an OLS regression, when n is not
large and we cannot rely on the asymptotic properties of estimates, then
we assume ex ante that error terms are normally distributed, allowing us
to use t-statistics to test for significance. Although error terms are unobservable, we can observe the post ante residuals from our regression, and
these too must be normally distributed in order to use t-statistics to test for
significance. Figures 1 - 6 in appendix A.4 show that the residuals from all
12 regressions are roughly normally distributed, and therefore our tests for
significance are appropriate.
7
This is assuming that our assumptions are not extremely flawed to the point where
an extremely flawed regression validates them.
20
Solow Growth Model in the 21st Century
7
Michael Boutros
Conclusion
In this paper, we extend MRW’s work by fitting their exact specification of
both the standard and augmented Solow models to data from 1970 to 2010.
We find almost identical results in both the constrained and unconstrained
estimations of the standard model. The standard model is statistically significant but economically insignificant due to unreasonable estimates for shares
of income for capital and labour. The augmented model is both statistically
and economically significant because the shares of these three inputs are
consistent with those found by estimating the Solow model (such MRW and
Das (2013)) and those explicitly estimating the shares (such as Acemoglu
(2009) and Steffen (2013)).
We contribute to the literature in two ways. Firstly, we show that by
including country-specific depreciation rates from the Penn World Table, we
obtain the same shares of inputs without constrained regressions. The depreciation rate is a small but important part of the model, and the assumption
by related literate that this rate is constant across countries is unfounded.
Given the freely available data on depreciation rates from the Penn World
Table, other researches should include this variable in their analysis.
Secondly, we reiterate that even in today’s high-tech world, the basic
inputs highlighted by Solow and MRW so many years ago are still very relevant. Growth can still come from these basic inputs. Increasing education
and health will lead to increased human capital and higher GDP per capita.
Increasing an economy’s investment via the savings rate will lead to more
capital and more GDP per capita. Technological advancement is of course
extremely important, but the fundamental inputs of neoclassical growth economics are not to be discarded.
In our final regression, we estimate the augmented model using the level
of human capital instead of its savings rate. Although we find that this
regression produces the highest degree of fit, the estimates imply values for
the shares of inputs that are incongruent with all previous literature. More
importantly, they violate the basic assumptions of the model. The level of
human capital can play an important role in future research, but current
data is not suited for estimating this particular model.
21
University of Toronto Economic Review
Volume 1, Issue 1
References
Acemoglu, Daron. 2009. Introduction to Modern Economic Growth. Princeton
University Press, Princeton, NJ, USA.
Arnold, Jens, Andrea Bassanini, and Stefano Scarpetta. 2007. “Solow
or Lucas?: Testing Growth Models Using Panel Data from OECD Countries.”
OECD Economics Department Working Papers.
Barro, Robert J., and Jong-Wha Lee. 2010. “A new data set of educational
attainment in the world, 1950-2010.” NBER Working Papers.
Das, Debasish Kumar. 2013. “Empirical Estimation of the Solow Growth Model:
A Panel Approach.” Master’s diss. School of Economics and Management, Lund
University.
DeLong, James Bradford. 1996. “Cross-Country Variations in National Economic Growth Rates: the Role of ’Technology’.” Federal Reserve Bank of Boston
Conference Series, 40: 127–172.
DeLong, James Bradford, and Lawrence H. Summers. 1991. “Equipment Investment and Economic Growth.” Quarterly Journal of Economics,
106(2): 445–502.
Durluaf, Steven N., Andros Kourtellos, and Artur Minkin. 2001. “The
Local Solow Growth Model.” European Economic Review, 45: 928–940.
Feenstra, Robert C., Robert Inklaar, and Marcel P. Timmer. 2013a. “The
Next Generation of the Penn World Table.”
Feenstra, Robert C., Robert Inklaar, and Marcel Timmer. 2013b. “PWT
8.0 – a user guide.”
Fernandez, Raquel, and Richard Rogerson. 1997. “The Determinants of Public Education Expenditures: Evidence from the States, 1950-1990.” NBER Working Papers.
Hanushek, Eric A., and Ludger Woessmann. 2012. “Do better schools lead
to more growth? Cognitive skills, economic outcomes, and causation.” Journal
of Economic Growth, 17(4): 267–321.
Hoeffler, Anke E. 2002. “The Augmented Solow Model and the African Growth
Debate.” Oxford Bulletin of Economics and Statistics.
Islam, Nazrul. 1995. “Growth Empirics: A Panel Data Approach.” The Quarterly
Journal of Economics, 110(4): 1127–1170.
Kalaitzidakis, Pantelis, and George Korniotis. 2000. “The Solow growth
model: vector autoregression (VAR) and cross-section time-series analysis.” Applied Economics, 32(6): 739–747.
Klemp, Marc P. B. 2011. “Time-Series Analysis of the Solow Growth Model
(First Draft).”
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Solow Growth Model in the 21st Century
Michael Boutros
Knight, John, and Sai Ding. 2009. “Can the Augmented Solow Model Explain
China’s Economic Growth? A Cross-Country Panel Data Analysis.” Journal of
Comparative Economics, 37: 432–452.
Koutun, Alina, and Patrick Karabona. 2013. “An Empirical Study of the
Solow Growth Model.” Master’s diss. School of Business, Society and Engineering, Malardalen University Sweden.
Liu, Gang, and Barbara M. Fraumeni. 2014. “Human capital measurement:
country experiences and international initiatives.”
Mankiw, Gregory N., David Romer, and David N. Weil. 1993. “A Contribution to the Empirics of Economic Growth.” The Quarterly Journal of Economics, Vol. 107(2): 407–437.
McLendon, Michael K., James C. Hearn, and Christine G. Mokher.
2009. “Partisans, Professionals, and Power: The Role of Political Factors in State
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OECD. 2011. “Education at a Glance: What portion of national wealth is spent
on education?” 224 – 231.
Psacharopoulos, George. 1994. “Returns to investment in education: A global
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Temple, Jonathan. 1998. “Equipment Investment and the Solow Model.” Oxford
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Temple, Jonathan. 1999. “The New Growth Evidence.” Journal of Economic
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Wooldrige, Jeffrey M. 2013. Introductory Econometrics: A Modern Approach,
5e. Mason, OH, USA:South-Western CENGAGE Learning.
23
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A
A.1
Volume 1, Issue 1
Figures and Tables
Countries Used in Analysis
Table 4: List of Countries Used in Analysis
Argentina
Barbados
Cameroon
China
Denmark
Egypt
Greece
India
Jamaica
Kenya
Malta
New Zealand
Panama
Philippines
Spain
Switzerland
Tunisia
Zimbabwe
Australia
Belgium
Canada
Costa Rica
Dominican Republic
Finland
Guatemala
Ireland
Japan
Luxembourg
Mexico
Niger
Paraguay
Portugal
Sri Lanka
Thailand
Turkey
Austria
Brazil
Chile
Cyprus
Ecuador
France
Honduras
Israel
Jordan
Malaysia
Netherlands
Norway
Peru
Senegal
Sweden
Trinidad and Tobago
Uruguay
* not included in analysis with the savings rate of human capital.
24
Summary Statistics for Key Variables
Table 5: Summary statistics
25
Variable
GDP (2010) (000 000, $US (2005))
Labour (2010) (0000)
GDP per Capita (2010) ($US (2005))
Human Capital (2010)
Population Growth Rate (%)
Savings Rate of Physical Capital (%)
Savings Rate of Human Capital (%)
Depreciation Rate (%)
Y2010
L2010
y2010
h2010
n
sk
sh
δ
Obs.
52
52
52
52
52
52
49
52
Mean
6889.74
35.51
38,772.71
2.75
2.05
21.74
58.55
4.08
Std. Dev.
17,512.33
125.46
27,772.59
0.44
1.06
6.56
27.71
0.70
Min.
68.33
0.13
1706.15
1.28
0.29
9.47
6.00
2.48
Max.
115,042.93
781.38
104,882.95
3.52
3.81
35.86
99.36
5.56
Solow Growth Model in the 21st Century
A.2
Michael Boutros
University of Toronto Economic Review
A.3
Volume 1, Issue 1
Homoskedasticity Test Results
Table 6: Results from Breusch-Pagan Test for Heteroskedasticity
g + δ = 5%
0.023
g = 2%, δ varies
0.107
Augmented Model (sh )
0.151
0.031
Augmented Model (h)
0.025
0.038
Standard Model
p-values from BP test on independent variables.
A.4
A.4.1
Residuals from OLS Regressions
Residuals from Standard Solow Model Regressions
(a) g + δ = 5%
(b) g = 2%, δ varies
Figure 1: Unconstrained Regressions
(a) g + δ = 5%
(b) g = 2%, δ varies
Figure 2: Constrained Regressions
26
Solow Growth Model in the 21st Century
A.4.2
Michael Boutros
Residuals from Augmented Solow Model (Savings
Rate of Human Capital) Regressions
(a) g + δ = 5%
(b) g = 2%, δ varies
Figure 3: Unconstrained Regressions
(a) g + δ = 5%
(b) g = 2%, δ varies
Figure 4: Constrained Regressions
27
University of Toronto Economic Review
A.4.3
Volume 1, Issue 1
Residuals from Augmented Solow Model (Level of
Human Capital) Regressions
(a) g + δ = 5%
(b) g = 2%, δ varies
Figure 5: Unconstrained Regressions
(a) g + δ = 5%
(b) g = 2%, δ varies
Figure 6: Constrained Regressions
28
Solow Growth Model in the 21st Century
B
B.1
Michael Boutros
Proofs and Derivations
Consistency of OLS Estimates With Proportional
Proxies
Proposition 1. Suppose x̃ = ρx and y = β0 + β1 ln x. When y is regressed on
ˆ
x, suppose βˆ1 is the estimate for β1 . When y is regressed on x̃, suppose β˜1 is the
ˆ
ˆ
˜
estimate for β1 . Then β1 = β1 .
Proof. We use the standard equation for determining β1 in single variable OLS:
P
(ln x̃ − ln x̃)(y − ȳ)
ˆ
β˜1 =
(25)
P
(ln x̃ − ln x̃)2
P
(ln ρx − ln ρx)(y − ȳ)
=
(26)
P
(ln ρx − ln ρx)2
P
(ln ρ + ln x − ln ρ − ln x)(y − ȳ)
=
(27)
P
(ln ρ + ln x − ln ρ − ln x)2
P
(ln x − ln x)(y − ȳ)
(28)
=
P
(ln x − ln x)2
= βˆ1
(29)
Moving from (26) to (27) is possible because:
ln ρx1 + ln ρx2 + · · · + ln ρxn
n
(ln ρ + ln x1 ) + (ln ρ + ln x2 ) + · · · + (ln ρ + ln xn )
=
n
n · ln ρ + (ln x1 + ln x2 + · · · + ln xn )
=
n
= ln ρ · ln x = ln ρ + ln x
ln ρx =
29
University of Toronto Economic Review
B.2
Volume 1, Issue 1
Steady State Equilibrium in the Standard Solow Model
Given equation (6) and the equilibrium condition k∗ = kt = kt+1 :
k∗ =
sk∗α + (1 − δ)k∗
(1 + n)(1 + g)
k∗ (1 + n)(1 + g) − k∗ (1 − δ) = sk∗α
k∗ (1 + g + n + ng − 1 + δ) = sk∗α
(n + g + ng + δ)k∗
=s
k∗ α
∗
k
s
=
k∗ α
n + g + ng + δ
s
(k∗ )1−α =
n + g + ng + δ
1
1−α
s
k∗ =
n + g + ng + δ
Since both n and g are small, ng ≈ 0, and:
k∗ =
s
n+g+δ
30
1
1−α
Solow Growth Model in the 21st Century
B.3
Michael Boutros
Steady State Equilibrium in the Augmented Solow Model
Given equations (17), (18), and the two equilibrium conditions k∗ = kt = kt+1 and
h∗ = ht = ht+1 , we begin by isolating for k∗ and h∗ :
k∗ =
h∗ =
sk (h∗ )β
n+g+δ
sh (k∗ )α
n+g+δ
1
1−α
(30)
1
1−β
(31)
We proceed to solve for k∗ by substituting (31) into (30):
∗
k =
sk
n+g+δ
αβ
k∗ = (k∗ ) (1−α)(1−β)
1−α−β
(k∗ ) (1−α)(1−β) =
k∗ =
k∗ =
"
sh
n+g+δ
sh
n+g+δ
1−β
sβ
h sk
n+g+δ
#

1
1−α

sh (k∗ )α
n+g+δ
sh
n+g+δ
β
β
1−β


1
1−α
β
(1−α)(1−β)
(32)
sk
n+g+δ
1
1−α
sk
n+g+δ
1−β
1−α−β
sk
n+g+δ
1
1−α
(1−α)(1−β)
β
1−α−β
1
1−α−β
(33)
(34)
(35)
(36)
Since the intermediate quations for h∗ and k∗ are largely symmetric, substituting
(30) into (31) and following the same procedure yields a similar expression for h∗ :
h∗ =
"
s1−α
sα
k
h
n+g+δ
#
1
1−α−β
(37)
To produce the augmented model’s steady-state equilibrium with the level of human
capital, we begin by isolating (37) for sh :
sh =
ln sh =
"
(h∗ )1−α−β (n + g + δ)
sα
k
#
1
1−α
1−α−β
1
α
ln h∗ +
ln (n + g + δ) −
ln sk
1−α
1−α
1−α
Substituting (39) into (22) and grouping like terms yields (23).
31
(38)
(39)
University of Toronto Economic Review
B.4
Volume 1, Issue 1
Restricting OLS Regressions
Although statistical packages such as Stata have built-in tools to constrain OLS
regressions, and these tools are used in this report, it is also very simple to manually
constrain a regression. Consider the augmented Solow model with the savings rate
of human capital; (22) can be expressed as:
ln
Y
= β0 + β1 ln sk + β2 ln (n + g + d) + β3 ln sh + L
(40)
α+β
β
α
, β2 = −
, and β3 =
.
1−α−β
1−α−β
1−α−β
Noticing that β2 = −(β1 + β3 ), we substitute this expression into (40):
where β0 = ω, β1 =
Y
= β0 + β1 ln sk + (−β1 − β3 ) ln (n + g + d) + β3 ln sh + (41)
L
Y
= β0 + β1 (ln (sk ) − ln (n + g + d)) + β3 (ln (sh ) − ln (n + g + d)) (42)
ln
L
ln
This equation is estimated using standard OLS. The estimates for β1 and β3 are
used to calculate an estimate for β2 , and standard errors for all three are calculated
as normal. A similar method is used to constrain the other regressions.
32
Dollar General and Family Dollar Merger:
An Economic Analysis of Anticompetitive Effects
Rebecca Hensman
1
Merger Proposal and Industry Overview
On August 18, 2014 Dollar General bid to acquire Family Dollar (Dol-
lar General, 2014). Family Dollar is currently entertaining bids from both
Dollar General and Dollar Tree and is undergoing a second request from the
Federal Trade Commission (FTC) regarding both mergers (Family Dollar,
2014b). The dollar store industry includes three main players: Dollar General Corporation, Family Dollar Stores Incorporated and Dollar Tree Stores
Incorporated. These stores comprise over 60% of the dollar and variety
store industry within the United States with Dollar General having 30% of
the market share (11,000 locations) and Family Dollar having 17% of the
market share (7,800 locations); the remainder of the industry is composed
of many small firms, each with a small market share (Haider, 2014).
The two chains combined sell products in four main categories including
consumable items, seasonal and variety goods, apparel and home products
(Marketline, 2014a,c). Dollar Tree, however, only offers consumable, variety
and seasonal products (Marketline, 2014b). This industry fits a differentiated
goods Bertrand model since firms primarily compete on price, as depicted
by the firms’ distinctive pricing strategies. For example, Dollar General and
Family Dollar offer a wide variety of products at a price of less than $10
per product whereas Dollar Tree specializes in products that are sold at a
$1 price point (Marketline, 2014a,c,b). Through an examination of both the
theories of harm and the potential entry and efficiencies of the merger, this
paper will argue that the merger between Dollar General and Family Dollar
will substantially lessen competition and have anticompetitive effects at the
detriment of consumers.
33
University of Toronto Economic Review
2
Volume 1, Issue 1
Defining the Relevant Antitrust Market
The hypothetical monopolist test is used to determine the relevant an-
titrust market. This test states that the relevant market is one in which
a monopolist of that market is able to make a small but significant nontransitory increase in price of at least 5%.
Pre-merger pricing strategies are able to provide a real-life application
of the hypothetical monopolist test, as demonstrated in the Staples-Office
Depot merger (Dalkir and Warren-Boulton, 2004). A press release by Family
Dollar alludes to the fact that Family Dollar and Dollar General engage in
zone pricing, which suggests that prices are lower in areas where the two firms
co-exist (Family Dollar, 2014a). This implies that a reduction in competition
provides an incentive for the lone firm to raise prices. By comparing prices
in markets with only one firm to prices in markets with both Dollar General
and Family Dollar, it is possible to deduce if it is profitable for a monopolist
of this industry to raise prices. The ability of a lone firm to profitably set
higher prices in areas lacking the competing firm reflects the ability of a
hypothetical monopolist to raise prices due to reduced competition.
This same scenario was also observed when analyzing the Staples-Office
Depot merger. In this case, it was found that prices in areas where the two
firms co-existed were 11.6% lower than in areas with only Staples (Dalkir
and Warren-Boulton, 2004). This suggested that common ownership of these
two firms would remove Office Depot competition and allow a hypothetical
monopolist to profitably raise prices. Using this same logic, if the prices
in areas where Dollar General and Family Dollar co-exist, are significantly
lower than the prices in areas where they exist individually, then it is likely
that monopoly ownership of the two entities would allow for a profitable
price increase.
One major point of contention when developing the relevant market is
whether supermarket retailers such as Wal-Mart and Target should be included. Although these retailers offer many of the products that are sold
in dollar stores at a similar price point, dollar stores are targeting a specific
group of consumers. To demonstrate this, consider the following two pieces
of evidence that depict that dollar stores target lower income households and
focus on convenience shopping.
34
Dollar General and Family Dollar Merger
Rebecca Hensman
First, a survey by Kantar Retail collected data on Dollar General, Family
Dollar, Wal-Mart and Target consumers and showed that Dollar General and
Family Dollar have a greater proportion of consumers with yearly incomes
less than $25,000 compared to Wal-Mart and Target (Peterson, 2014); this
suggests that dollar stores target lower income households. Not only does
the type of consumer differ between dollar stores and retailers, but the type
of shopping differs as well. The average Dollar General customer spends
$9.70 per visit compared to the average Wal-Mart consumer who spends between $50-60 per visit; additionally, 36% of dollar store customers state that
they shop at dollar stores to save time (Agriculture and Agri-Food Canada,
2011; Fox, 2013). This shows that customers tend to use dollar stores for
small purchase convenience shopping whereas customers use large retailers
for more substantial shopping trips. Therefore, dollar stores represent a separate market since the consumer base for supermarket retailers is different
than that of dollar stores.
Second, a comparable distinction was made in the Whole Foods - Wild
Oats merger, where the addition of supermarket retailers into the relevant
market was disputed (Federal Trade Commission, 2007). The FTC argued
that supermarket retailers should not be included in the relevant market
because Whole Foods and Wild Oats represent a separate specialized market.
These stores are distinct from supermarkets because they target wealthier
consumers, offer a unique set of organic products and create a lifestyle/brand
that regular supermarkets lack. Following this same logic, retailers such as
Wal-Mart and Target should not be included in the relevant market since
dollar stores target a unique type of consumer and are specific to a certain
type of shopping.
Considering the aforementioned points, the relevant antitrust market is
the dollar and variety store market, which includes the top three firms:
Dollar General, Family Dollar and Dollar Tree.
3
Market Concentration
The dollar and variety store industry is moderately concentrated based
on the Horizontal Merger Guidelines.
The Herfindahl-Hirschman Index
(HHI) of the industry is 1490, which is just under the 1500 benchmark that
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University of Toronto Economic Review
Volume 1, Issue 1
constitutes a moderately concentrated market (Haider, 2014). Using a simplistic approach, it is possible to calculate an estimate of the post merger
HHI by assuming that the market share of the merged firm will be the sum
of the market shares of the two individual firms. Doing so, the HHI post
merger will be 2529, which represents close to a two-fold increase. This significant increase creates a highly concentrated industry and raises concerns
regarding anticompetitive effects.
There are two limitations of this analysis. Firstly, this calculation of
HHI is purely an estimate as it is unlikely that the initial assumption will
hold in reality. For example, if the merged firm raises prices, consumers will
substitute away from the firm and the market share of the merged firm will
be less than the sum of the two individual firms. Secondly, the importance
of HHI in this industry is limited because increased market concentration
does not translate into enhanced market power since this market does not
fit a homogenous goods Cournot model. In a homogenous goods industry,
an increase in HHI allows the merged firm to increase prices due to reduced
competition. HHI does not capture the proportion of consumers that substitute away from the merged firms good as prices rise, which is a concern in a
differentiated goods industry (Federal Trade Commission & U.S Department
Of Justice, 2010). The FTC guidelines suggest that a diversion ratio would
be a better predictor of a potential price increase post merger for a differentiated goods market (Federal Trade Commission & U.S Department Of
Justice, 2010). Thus, although a change in HHI is unrelated to the market
power of the merged firm, it does depict that the merger will likely result in
a highly concentrated market.
4
Theories of Harm
The primary anticompetitive mechanism of this merger is through uni-
lateral effects. The unilateral theory of harm proposes that post merger the
reduction in competition will permit the merged entity to raise prices. The
consequences of these unilateral effects are heightened since the two merging firms are close substitutes. Three key pieces of information suggest that
these two stores are highly substitutable. Firstly, both firms offer products in
the same four categories: consumable products, seasonal and variety goods,
36
Dollar General and Family Dollar Merger
Rebecca Hensman
home products and apparel. Secondly, the two firms have similar pricing
strategies, where both firms sell products for less than $10. As well, both
stores offer 25% of their products at a $1 price point and approximately
70% of both stores sales are in consumable goods (Marketline, 2014a,c).
Lastly, the stores have extensive geographic overlap as 73% of Family Dollar
stores are within a 3-mile radius to a Dollar General store (Family Dollar,
2014a). Therefore, due to similar product offerings, price points and geographic locations, these two stores are very close substitutes for one another.
Additionally, the two firms are closer substitutes to each other than to their
competitor Dollar Tree, since Dollar Tree only offers consumable, variety
and seasonal goods, and only offers products that can be sold at a $1 price
point (Marketline, 2014b). Thus, it is fair to argue that Dollar General and
Family Dollar are each others closest competitors.
The 2010 FTC Horizontal Merger Guidelines (Federal Trade Commission
& U.S Department Of Justice, 2010) suggest that in a differentiated goods
market, mergers between firms selling close substitutes allow the merged
firm to make a larger profitable price increase. Since the two goods are close
substitutes, the merging firm will have an incentive to raise the price of at
least one good since it is able to capture a proportion of the lost sales by
consumers substituting away to the product sold by the other merging party.
The more substitutable the two products are, the greater the proportion of
lost sales the merged firm can capture after a price increase, and thus the
greater the risk of post merger unilateral price effects. Given that Dollar
General and Family Dollar appear to be fairly close substitutes, the threat
of merger induced unilateral effects is immense.
The pricing differences across geographic markets pre-merger illustrate
the potential unilateral effects. As previously discussed, there is evidence
that prices tend to be lower in areas where Dollar General and Family Dollar
co-exist and thus higher in areas where only one firm exists. This occurrence
demonstrates that removal of the firms major competitor provides an incentive for the lone firm to profitably raise prices. The effects of the merger will
be greatest in areas where Dollar General and Family Dollar currently coexist, as these regions will directly experience the reduction in competition.
This union will negatively affect a substantial number of markets. Dollar
General currently overlaps with over 6000 Family Dollar locations and even
37
University of Toronto Economic Review
Volume 1, Issue 1
though they are offering to divest 1500 locations (Family Dollar, 2014a), such
a divestment would not be sufficient to cover all the overlapping, high-risk
regions.
A coordinated effects theory of harm suggests that the merger will encourage price coordination between the merged firm and other firms in the
relevant antitrust market. These effects are unlikely to occur in this scenario because Dollar Tree, the only other major competitor remaining post
merger, has a unique pricing strategy. As previously mentioned, Dollar Tree
is based on a brand where every product sold is priced at $1. Thus, it is
unlikely that Dollar Tree would raise its prices along with the merged entity
because it would violate their branding and marketing.
Overall, the major theory of harm to consider with regards to this merger
is a unilateral effects theory of harm, which will pose a significant threat since
the stores are close substitutes.
5
Potential Post-Merger Entry
In order for entry of new firms to offset the anticompetitive effects of
this merger, entry must be likely, timely and sufficient. Entry into the dollar
store industry by new firms not currently operating in the retail industry
is unlikely due to large barriers to entry. One of the primary barriers to
entry is the economies of scale advantage that existing firms encompass.
Established dollar stores, such as Dollar General and Family Dollar, are
able to exploit economies of scale that a new entrant would not be able to
obtain. These economies of scale have been observed in many industries.
For example, David Davis presents an econometric analysis of economies of
scale within supermarkets (Davis, 2010). The regression model examines
the effect of economies of scale on prices by using the share of national
supermarket sales as a proxy for economies of scale. The results show a
negative relationship between the share of national supermarket sales and
prices, which could be explained by the fact that firms with greater sales are
able to obtain lower input prices from their suppliers which allows them to
charge lower prices. New entrants are at a disadvantage because they cannot
achieve the same level of economies of scale as the existing firms and thus
cannot set competitive prices. Furthermore, the current existing firms may
38
Dollar General and Family Dollar Merger
Rebecca Hensman
have strategic relationships with their suppliers, such as exclusive contracts,
which impede new entrants from buying inventory. For these reasons, entry
of new firms who do not already exist in the retail industry is unlikely.
Although entry of new stores into the retail industry is unlikely, it is possible that larger retail stores may enter the dollar and variety store industry
by creating smaller size stores. For instance, Wal-Mart has already begun
to introduce its new line of Neighbourhood Markets and Wal-Mart Express
Stores. One of the main differentiating factors between dollar stores and
large retailers is that dollar stores focus on convenience and small purchase
shopping. The new line of Wal-Mart stores has a smaller store design similar
to dollar stores, which is more conducive to small purchases. Entry of large
retailers into the dollar and variety store market would be timely since it
has already started. Wal-Mart opened its first express store in 2011 and is
expecting to open 300 new stores in 2014 (Walmart, 2014). Whether or not
the entrance of Wal-Mart will be sufficient to curb the merged firm’s price
increase is debatable. At this point in time, it is not feasible to assume that
Wal-Mart will be able to prevent the merged firm from raising prices, primarily because Wal-Mart Express and Neighbourhood stores are not numerous
enough. Dollar General and Family Dollar overlap in over 6000 regions and
these regions are the most threatened by the merger (Family Dollar, 2014a).
Even given Wal-Mart’s aggressive expansion of Neighbourhood Markets and
Express Stores, they only have around 700 locations (Walmart, 2014), which
is not sufficient to prevent price increases in 6000 threatened areas.
Thus, although entry of large retailers into the dollar and variety industry
may be likely and timely, it will not be sufficient to prevent the merged firm
from profitably raising prices.
6
Merger Induced Efficiencies
As previously mentioned, Dollar General and Family Dollar have over
6000 locations within 3 miles of one another. Post merger the firms would be
able to shut down the overlapping stores, which creates a possible efficiency
gain. Rent and utilities account for 5.9% of industry costs and wages account for 9.5% of costs (Haider, 2014), thus closing down redundant stores
would alleviate these costs. Since these savings cannot be achieved with39
University of Toronto Economic Review
Volume 1, Issue 1
out the merger, they are viable efficiencies to consider. If a proportion of
these savings were passed to consumers, they may be sufficient to offset the
expected price increase. Although one store may not be large enough to
contain the consumer traffic experienced by two neighbouring stores, Dollar General is already planning store expansions to increase square footage
(Dollar General, 2013).
While shutting down stores does provide efficiency savings, it may reduce
product variety. Even though the two firms tend to offer similar products
since they sell in the same four product categories, each stores selection has
some variation. Thus, closing down stores would decrease the variety of
products available to consumers. This phenomenon was observed during the
Whole Foods - Wild Oats merger previously discussed. Since the product
offerings of these two stores greatly overlaps, Whole Foods stated that they
would close down stores that were located within one mile of one another
(Mackey, 2007). While the two firms had similar product offerings, these
closures reduced product variety, as there was some differentiation between
items sold at nearby locations.
Therefore, although the merged entity may save the cost of redundant
store locations, this comes at a cost to consumers due to the reduced product
variety. Since this potential efficiency causes a detriment to consumers, it is
not appropriate to presume that these efficiencies would offset the harm of
this merger.
7
Conclusion
This paper investigated the anticompetitive effects of a merger between
Dollar General and Family Dollar. Using the hypothetical monopolist test,
the relevant market was defined as the dollar and variety store market. This
paper proposes a unilateral effects theory of harm, which suggests that the
merged entity would have an incentive to increase prices post merger due
to the reduction in competition. This effect is anticipated to be significant
due to the high substitutability of the two stores. The potential of entry
was considered but deemed insufficient to offset the price increases resulting
from this merger. Moreover, plausible efficiency savings were examined, but
due to the reduction in product variety resulting from the efficiencies, they
40
Dollar General and Family Dollar Merger
Rebecca Hensman
were not considered sufficient to offset the negative effects of the merger.
Given the arguments analyzed in this paper, it is appropriate to anticipate
that the union between Dollar General and Family Dollar will substantially
lessen competition.
References
Agriculture and Agri-Food Canada. 2011. “Overview of the Retail Dollar Store
Market in the United States: Opportunities for Canadian Agri-Food Exporters.”
Dalkir, S., and F. Warren-Boulton. 2004. “Prices, Market definition, and the
Effects of the merger: Staples- Office Depot (1997).” In The Antitrust Revolution: Economics, Competition and Policy. . 4th edition ed., , ed. Jr. John
E. Kwoka and Lawrence J. White, 52–72. Oxford University Press.
Davis, David E. 2010. “Prices, Promotions and Supermarket Mergers.” Journal
of Agricultural and Food Industrial Organization, 8(8): 1–25.
Dollar
General.
2013.
“Dollar
General
Corporation
Reports
Record Third Quarter 2013 Financial Results.” Retrieved from
http://newscenter.dollargeneral.com/news/dollar-general-corporation-reportsrecord-third-quarter-2013-financial-results.htm.
Dollar
General. 2014. “Dollar General Makes Proposal to Acquire
Family
Dollar
for
78.50
Per
Share.”
Retrieved
from
http://newscenter.dollargeneral.com/news/dollar-general-makes-proposalto-acquire-family-dollar-for-7850-per-share.htm.
Family Dollar. 2014a. “Family Dollar board of directors rejects revised
proposal from Dollar General based on antitrust issues.” Retrieved from
http://investor.familydollar.com/investors-relations/news-releases/PressRelease-Details/2014/Family-Dollar-Board-of-Directors-Rejects-RevisedProposal-from- Dollar-General-Based-on-Antitrust-Issues/default.aspx.
Family
Dollar.
2014b.
“Family
Dollar
Certifies
Substantial
Compliance
with
FTC’s
Second
Requests.”
Retrieved
from
http://investor.familydollar.com/investors-relations/news-releases/PressRelease-Details/2014/Family-Dollar-Certifies-Substantial-Compliance-WithFTCS-Second-Requests/default.aspx.
Federal Trade Commission. 2007. “Federal Trade Commission v. Whole Foods
Market, Inc. and Wild Oats Markets Inc: Complaint for the temporary restraining order and preliminary injunction pursuant to section 13(b) of the Federal
Trade Commission Act.”
Federal Trade Commission & U.S Department Of Justice. 2010. “Horizontal Merger Guidelines.”
Fox, Emily Jane. 2013. “Wal-Mart: The $200 billion grocer.” CNN Money,
Retrieved from http://money.cnn.com/2013/01/31/news/companies/walmartgrocery/.
41
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Volume 1, Issue 1
Haider, Zeeshan. 2014. “IBISWorld Industry Report 45299. Dollar & Variety
Stores in the US.” Retrieved from IBISWorld database.
Mackey, John. 2007. “Whole Foods Market, Wild Oats and The Federal
Trade Commission.” Retrieved from http://www.wholefoodsmarket.com/
blog/john-mackeys-blog/whole-foods-market-wild-oats-and-federaltrade%C2%A0commission.
Marketline. 2014a. “Company Profile Dollar General Corporation.” Retrieved
from Marketline database.
Marketline. 2014b. “Company Profile Dollar Tree, Inc.” Retrieved from Marketline database.
Marketline. 2014c. “Company Profile Family Dollar Stores, Inc.” Retrieved from
Marketline database.
Peterson, Hayley. 2014. “Meet the average Wal-Mart shopper.” Business Insider, Retrieved from http://www.businessinsider.com/meet-the-average-walmart-shopper-2014-9.
Walmart. 2014. “Walmart U.S accelerates small store growth: Expansion program doubles initial forecast.” Retrieved from http://news.walmart.com/newsarchive/2014/02/20/walmart-us-accelerates-small-store-growth.
42
The Collapse of Bretton Woods System
From the Perspective of Gold
Yuchen Wu
1
Introduction
The collapse of Bretton Woods system has always been one of the most
influential events in the 20th century history. It was the first fully negotiated
monetary agreement among most of the developed countries and its end
marks the ending of gold being the world reserve currency over thousands
of years in our civilization. The consequences of the collapse of Bretton
Woods are long lasting and still shape the financial reality today. Therefore,
to better understand our current system as well as to explore our future
options, it is important for us to understand the reasons behind this event,
that is, what really caused the collapse of the system?
Historically, scholars have been focusing their research mainly on two
approaches. The first approach is to looking for the fundamental flaws of
the Bretton Woods system internally, such as the famous Triffin Dilemma.
The second approach is to looking at the external changing international
environment, such as the U.S. trade deficit problem. Some researching has
been done to combine both the approaches and it provides compelling logic
for the event. However, these researches tend to over emphasize on the
U.S. dollars and in contrast ignores the role of gold played, which in turn,
probably provides a more compelling logic for the real intentions behind the
collapse of Bretton Woods system.
This paper will argue that the purposefully designed roles gold played
in the Bretton Woods system makes the system a fake gold standard and
inevitably led the system to collapse so that the U.S. dollar could replace
the gold as the world reserve currency. This conclusion was supported by six
individual arguments such as the none-effective gold reserve requirement for
43
University of Toronto Economic Review
Volume 1, Issue 1
issuing U.S. dollars and the use of U.S. dollar solely as the mean of trading
settlement.
2
Background
Bretton Woods system was a monetary agreement designed to establish
the rules and regulations for financial and commercial relations among 44
countries. It was officially established in July 1944 before the Second World
War come to an end and ended in August 1971 after U.S. President Richard
Nixon announced the new economic policy to terminate the convertibility
between gold and dollar. The Bretton Woods system had several major features, including the fixed exchange rate regime, U.S. dollars convertibility to
gold, other countries currencies pegged to U.S. dollar and the establishment
of the International Monetary Fund and World Bank.
The collapse of the Bretton Woods system is actually the collapse of
gold and the takeover of the U.S. dollar. In my opinion, before any further
investigation about the collapse of Bretton Woods system need to be done,
we must first understand the definition of the word collapse used here. That
is, what exactly do we mean by the collapse of Bretton Woods system, what
part of it was changed by the collapse of this system?
To answer this question, there are mainly two parts that was fundamentally changed as the result of this famous financial event. First, the final link
between gold and dollar was cut off; U.S. dollar was no longer pegged to gold.
Second, the fixed exchange rate regime was replaced by floating exchange
rate regime; foreign currencies were no longer pegged to U.S. dollar.
The relationship between these two points looks independent but is in fact
cause and effect. For the second point, we knew that the portion of the gold
each unit of currency represents calculated the fixed exchange rates between
currencies. As the gold dollar exchange commitment was the link to let dollar
being pegged to gold, the default of the gold dollar exchanges commitment
directly caused the collapse of fixed exchange rate regime. Therefore the
first point caused the second point and both the first and second points
listed above were the results of the disconnection between gold and dollar.
We can conclude that the collapse of Bretton Woods system was in fact the
collapse of gold dollar exchange commitment and this is what we should be
44
Collapse of the Bretton Woods System
Yuchen Wu
focusing on while studying this event.
As we knew, when it comes to the topic about the collapse of gold dollar exchange commitment, scholars usually focused on the roles U.S. dollar
played in the world such as the Triffin Dilemma the U.S. trade deficits and the
monetary expansion (Ravenhill (2005), Conte and Karr (2001)). Although
people knew that the collapse of the Bretton Woods system was caused directly by the termination of the convertibility between gold and U.S. dollar
as we discussed above. There has not been much research done about the
roles gold played in the Bretton Woods system as there should be. As a
matter of fact, understanding the roles gold played in the Bretton Woods
system is crucial to the understanding of the collapse of system. In the next
section, we will discuss how the U.S. government purposefully designs the
Bretton Woods system so that it looks like gold standard but is as a matter
of fact a fiat currency system. As well as the inevitably collapse it would
lead to so that U.S. dollar could replace gold as world reserve currency.
3
Analysis
At a glimpse, gold was supposed to be the foundation of the U.S. dol-
lar in Bretton Woods system and this is what makes U.S. dollar publicly
accepted by the other 43 countries as the international reserve currency.
People considered dollar as good as gold and its convertibility commitment
made by the U.S. government made people believe that the Bretton Woods
system was based on gold standard, which has been used before and can
be trusted. However, what has not been told is that Bretton Woods system
was fundamentally different from the other two kinds of gold standard which
has been used before mainly in six ways and these differences not only made
Bretton Woods system a fake gold standard but also inevitably caused the
gold dollar exchange commitment to fail by allowing the U.S. dollar to act
as an unconstrained fiat currency.
3.1
The fake gold reserve requirement, in the name of law
First of all, the requirement for dollar to be backed up by gold does
not put any real constrains to the issue of U.S. dollar since the amount of
dollar issued was far below the theoretical ceiling in 1944 and was always
45
University of Toronto Economic Review
Volume 1, Issue 1
kept this way by intentionally changing the law afterward. Therefore, as we
look back, this gold reserve requirement has no effect on the issue of U.S.
dollar as it was advertised.
Unlike the gold specie standard and gold exchange standard which people
use gold as currency or currency is fully backed by gold. The Bretton Woods
version of gold standard only requires 40% of the dollar issued being backed
up by gold from 1913 to 1945, and this requirement was further lowered to
25% at 1945 and was eventually repealed by United States Congress in 1968
(, n.d.). These acts did not just happened randomly but for a reason, as the
requirement went lower, the government could literally create more wealth
simply by print more dollar.
Even though the existence of dollar back up requirement was the essential condition that Bretton Woods system could be advertised as basing on
gold standard, it severely constrained the governments ability to print excess amount of money for its benefit, so after the agreement was signed in
1944, a series of actions were gradually taken to ensure this dollar back up
requirement did not stand in the way whenever more dollar is wanted.
The first step was taken right at the Bretton Woods conference when
U.S. set up the gold price at 35 dollars per ounce, by calculating the price
of gold as if the total amount of dollar in circulation was totally backed up
by gold automatically gives the U.S. government the right to issue as much
as another 1.5 times the existing amount of dollar issued. The second step
was taken in 1945, only one year after the Bretton Woods agreement was
signed, even though there was absolutely no worry about the ceiling since
the U.S. government did not print too much money compared to 1944 as
we can see from figure 1, the Congress still reduced the ratio from 40% to
25%. This action did not only increase the possible theoretical amount of
U.S. dollar issued by 60%, but also clearly showed the U.S. governments
long-term intention (strategy) to unchain the U.S. dollar from gold after the
U.S. dollar officially become the international reserve currency. In another
word, the U.S. government was able and willing to weaken the already weak
gold foundation of U.S. dollar for its own benefit even at a cost of destroying
the gold dollar exchange commitment therefore the Bretton Woods system.
The final act was completed in 1968 when United States Congress repeal
the requirement for dollar to be 25% backed up by gold even though the
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Collapse of the Bretton Woods System
Yuchen Wu
theoretical ceiling was still far from being reach. The U.S. dollar was finally
a fiat currency as it. Base on the history, the dollar back up requirement
never put any constrains on the issue of U.S. dollar throughout the lifetime
of Bretton Woods system. Technically speaking, by constantly changing the
law, the U.S. dollar from 1944 to 1968 was only nominally based on gold
standard, but in fact a fiat currency. The U.S. government successfully used
the name of gold standard to fulfill its purpose to promote U.S. dollar as the
international reserve currency but at the same time avoided the constrains it
has to bring. It seems that the only functional connection between gold and
dollar was through the gold dollar exchange commitment, but by performing
an unethical word trick, the U.S. government also avoided the constrains it
should hold for dollar.
3.2
Gold dollar exchange commitment, a tiny yet lethal
trick
The gold dollar exchange commitment had no influence on the issue of
U.S. dollar since it was only a commitment for exchange, but not a commitment for availability to exchange.
Let us not be confused, although it looks like the credibility of U.S. dollar
was constrained by this gold dollar exchange commitment in the expectation
that the price of gold in terms of dollar should remain fixed, U.S. government
in fact only had a commitment that foreign central banks could exchange
one ounce of gold for every 35 dollars, but not a commitment that all dollars
held by foreign central banks could be exchanged to gold at a rate of 35
dollars per ounce. Although these two notions above looks similar, but
they are fundamentally very different. The first one does not require U.S.
government to limit the amount of dollar being issued as long as it could
keep the gold dollar exchange commitment when other central bank asks for
exchange while the second one does require U.S. government to limit the
amount of dollar being issued in order to keep the absolute convertibility
between gold and dollar at the fixed rate. By choosing the first notion,
the gold dollar exchange commitment would hold as long as the current
buyers demands were satisfied, even though the potential demand could be
dangerously overwhelming. In another words, what U.S. government was
doing is like the supermarket having a heavy discounts promotion towards
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a certain kind of product without indicating, Limited quantity available or
When supply last. The consumers would be led to misunderstanding the
situation as one could always purchase the amount he or she want but only
to find out that there is nothing left for the late comers.
Consequently, by promoting the idea that the gold dollar commitment
was designed to last long, the U.S. government successfully made an illusion
to let others believe that this gold dollar exchange commitment was the key
to peg dollar to gold while it actually has no influence on the issue of dollar
at all. As long as the foreign demands for U.S. gold could be kept under
control by various ways such as political intervention, military threat and
financial aid, it really did not matter how much dollar was out there in the
hands of foreigners. Therefore, the gold dollar exchange commitment only
served as a special offer made by the U.S. government for foreign dollars
to be exchanged for gold at a fixed rate, but not a guarantee that all the
foreign dollars could be changed to gold. This made the gold dollar exchange
commitment powerless against the excess issue of dollar.
We knew that the gold does not have any control over the issue of dollar
and this makes Bretton Woods system a fake gold standard. But beside this,
what roles did gold played in the system?
3.3
Gold, a king without his country
The answer to the previous question was pretty straightforward; gold
did not play any important roles in Bretton Woods system rather than the
minor and temporary roles such as to set the initial exchange rates among
currencies and to be used as the last way to settle international trade imbalance. Besides, not only the gold is meaningless in Bretton Woods system,
but also the monetary price for gold($35/once) set by the U.S. government
was meaningless since it does not represent the real value of gold and will
only cause the real price for gold to soar as more and more dollar were
printed.
The gold was not in the Bretton Woods system at the first place as all the
commodities and trades are settled in U.S. dollars. As we knew, U.S. dollar
was pegged to gold and all other currencies and commodities were pegged
to dollar, this combination looks like everything was eventually pegged to
gold, but what beneath the surface is that gold was purposefully isolated
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Yuchen Wu
from the real world, changing the value of dollar in terms of gold would
have almost zero impact on the world since everything was pegged to dollar
instead of gold. Therefore, the U.S. dollar and only the U.S. dollar can do
everything and thus completely replace the roles gold used to play as the
reserve currency. Let us look at the roles gold played in this way, if we
change the price of gold from 35 dollars per ounce to 45 dollars per ounce
under Bretton Woods system, what would happen? Apparently whoever
has the gold would be richer in terms of dollar, but other than that, nothing
serious would happen. The fixed exchange rate among different currencies
would not be affected since the foreign currencies are calculated based on
the reserve currency after the initial set up. The international trade would
not be affected since all the product and service are priced in dollar. The
price of commodity such as crude oil would not be affected since it is priced
in dollar as well. Therefore, except for the price of gold itself, the changing
of the price of gold does not have any real effect on the world at all.
As a matter of fact, if gold is essential to dollar (as gold standard should
be), then after the gold was forced to break up with the dollar in 1971, the
dollar should be far worse off. But the reality points to the exact opposite
direction as the roles dollar played in the world were not affected at all.
This was not because U.S. government managed to avoid the shockwave but
because there is no shockwave towards dollar. The gold was designed not to
play any useful or real roles in Bretton Woods system therefore could not
affect the issue or circulation of U.S. dollar at all at the time of government
default.
The gold dollar exchange commitment could only be more unstable as
more dollars were printed. We knew that $35 per ounce is just the price
to match the gold reserves U.S. holds in terms of dollar at a ratio of 1:1
in 1944, but the point is that 35 dollars for one ounce of gold was just the
price at that specific moment, as we can see from figure 1, the total amount
of circulating dollar quickly overpasses the total value of gold reserves after
1944 and therefore makes the price of 35 dollars outdated and troublesome.
As the price for gold in the open market became significant higher than the
monetary gold price set by the Bretton Woods conference, this would create
a market for speculators to arbitrage between open and official market and
gradually drain up the gold reserves.
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Therefore, we could see that the U.S. government announced this $35
per ounce benchmark just because it would create an illusion for the others
to believe that dollar will always be as good as gold as it is in 1944. And
the system was purposefully designed in a way that when the relationship
between gold and dollar come to an end, the relationships between dollar
and the rest of the world would not be affected at all.
3.4
U.S. dollar, the free lunch
The different costs to obtain U.S. dollar for U.S. and the rest of world
would eventually cause the dollar to flood and lead the Bretton Woods system to collapse in long term.
The partial requirement for the gold to back up dollar allows U.S. dollar
to be mainly based on faith rather than gold. Each dollar issued at 1944
when the Bretton Woods conference was only required to hold 0.4 dollar
worth of gold by the government. But as we can see from figure 1, the
famous gold price of 35 dollars per ounce was based on the real price of
gold at that time by a ratio of roughly 1:1. This means that at the time of
Bretton Woods conference, U.S. government could afford to fully back up
the amount of dollar issued by gold at the price of 35 dollar per ounce even
though it was only required by 40%. In other words, the U.S. government
was calculating the price of gold in terms of dollar as if it was fully backed up
by gold while it was only 40%. If the U.S. government was to calculate the
price of gold in terms of dollar based on faith and gold as it is, then the price
of gold in terms of dollar would be increased by 52.5 to 87.5 dollar per ounce
since each dollar is actually 0.4 dollar based on gold. But by doing this, the
fact that U.S. dollar was 60% based on faith would be obvious to others and
this would cause overall suspicions towards Bretton Woods system under the
name of gold standard, therefore the U.S. government choose to promote the
idea that the U.S. dollar was as good as gold rather than the fact that it was
actually 40% as good as gold.
This trick would inevitably cause the problem of inequity for the value
of dollar in terms of gold. The same dollar had different values towards
U.S. and other countries since each dollar was worth 1/87.5 ounce of gold
to U.S. but 1/35 to other countries. In another word, the cost for U.S. to
get 1 dollar is 0.4 dollar in terms of gold, but it would take other countries
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Collapse of the Bretton Woods System
Yuchen Wu
1 dollar in terms of gold to got 1 dollar. Therefore, from U.S. governments
perspective, whenever foreign central banks exchanged one dollar for gold,
U.S. government was only receiving 0.4 dollar but in return gave out 1 dollar
worth of gold. We may also look at this problem in an extreme view in order
to understand this fundamental flaw of Bretton Woods agreement. Let us
suppose that the U.S. government issued 100 dollar in total with 40-dollar
worth of gold as back up under the law in 1944. If 40 out of this 100 dollars
were held by foreign central banks. Then when foreigners exchanged their
dollar for gold from U.S., the U.S. gold reserves would be completely drained
out. From this point, all the dollar in circulation would be based 100% on the
faith and the law would be broken. This revels us the fact that the gold dollar
commitment was not sustainable since the trade is unfair to other countries
and the effect of this would show up in the long term as the rate of money
supply increase overpass the rate of gold reserve increase. Since U.S. dollar
is only 40% percent backed up by gold reserves, as other countries starts to
use and hold dollar, the amount of dollar holding by other countries would
eventually exceed the amount of gold being hold by U.S. and this would
ultimately lead the gold dollar exchange commitment to collapse.
This problem could be avoided if U.S. government fully back up the
dollar with gold and therefore set the price for gold at 87.5 dollar per ounce
at first place, but as discussed, this would lead U.S. to lose its prestige to
print the money at a cost of only 40% of its face value and therefore lose the
main point of Bretton Woods system. In a nutshell, The U.S. government
purposefully designed the Bretton Woods system this way to benefit itself
at a cost of sacrificing the stability of the gold dollar exchange commitment
in the long term, but this systematic flaw would make perfect sense for
the benefit of U.S. as it would eventually lead the system to collapse and
therefore completely unchain the U.S. dollar from gold.
3.5
The disguise: U.S. dollars secret identity as an unconstrained fiat currency
The Bretton Woods system was considered to be based on gold stan-
dard but was in fact a system of fiat currency since gold does not have any
ability to influence the issue of dollar. Neither through the dollar backs up
requirement or the gold dollar exchange commitment. However, from the
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economic point of view, this trap was hard to be fully noticed in the short
term mainly because of three factors, the political pressures, the intervention
of gold market and the dollar shortage.
Besides the numerous political pressures U.S. government had given to
its allies and enemies to keep them from holding the dollars instead of gold
(Gavin, 2003). The U.S. government also set up the London Gold Pool in
1961 in an attempt to keep the price of gold in open market down to around
$35 per ounce even though U.S. knows it was not meant to last long as
more dollars are being printed. The London Gold Pool did not only failed in
1968 but also dragged other seven countries which together established the
London Gold Pool down, as the gold being sold at the market was only 50%
provide by the U.S. government. The main function of London Gold Pool
was not to provide the gold needed, but the confidence needed. By supply
the gold at the monetary fixed price, other countries would not see the needs
to exchange dollars into gold since this trade could always be done whenever
it is needed. Besides, holding dollar would also gain interest while holding
gold would cost a maintenance fee.
Another important reason to keep other countries from exchanging dollar
for gold was because of the global dollar shortage after the Second World
War. As the war destroyed most of the countries industrial ability to produce
goods it needs for its rebuild, these countries (mainly European countries)
desperately need dollars to buy goods imported from the States and other
countries. This process would take years until the rest of the world regains
its ability to produce enough goods for themselves and export. Therefore at
a time of dollar shortage, no one would have motivation to exchange useless
gold with precious dollars.
These economic factors discussed above together with the political factors
ensures the stability of the gold dollar exchange commitment therefore the
Bretton Woods system, But it would only work in the short term since it was
achieved through severe government interventions that aimed to maintain
the illusion that gold dollar exchange commitment was to last long. In
the long term, as the supply of U.S. dollar soared (more specifically, when
the foreigners hold more dollar than the U.S. gold reserves), other countries
would sooner or later realized the terrifying truth that there were not enough
gold for everyone anymore, and if they dont hurry, there will be no gold left
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Yuchen Wu
for them to exchange.
3.6
Gold does not have a name on it, but dollar does
There is one more factor that was usually ignored by economists but
is really important, the ability to change the law towards ones own favor
without any penalty. The U.S. dollar would not be able to act as a fiat
currency if the United States Congress did not perform the series of actions
to unchain the dollar from gold. Also, the U.S. government would have little
interest to default the gold dollar exchange commitment if there was severe
penalty associated.
The fundamental difference between gold standard and dollar standard
is that gold is controlled by the country that owns it, but dollar was only
controlled by the U.S. government no matter who owns it. By changing
the law about the dollar, the U.S. government had the ability to rewrite
the rules of game according to its own will such as to print excess amount
of dollar and default the gold dollar exchange commitment without any
compensation. After all, the world reserve currency was not named Bancor
or Unita as proposed by the British government during the Bretton Woods
conference, it was named the U.S. Dollar (Mikesell, 1994).
4
Conclusion and Its Implication
By summing these points up and have a look at the big picture of the
Bretton Woods system. We can see that the U.S. dollar is in fact a fiat
currency under Bretton Woods system rather than equal to the gold standard it claimed to be. And the collapse of gold dollar exchange agreement
is fundamentally inevitable as U.S. government abusing its privileges and
therefore leading the gold being replaced by U.S. dollar as world reserve currency. Within the different approaches scholar took to study the collapse of
Bretton Woods system. This approach focusing on the gold clearly showed
a compelling logic flow to explain this event. The Bretton Woods system
was advertised as a system of gold standard by U.S. government in order to
gain other countries trust. But gold did not play any important roles in the
system as the whole system was built up on U.S. dollar instead of gold. By
playing an unethical word trick and changing the law at its own will, U.S.
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dollar was unchained from gold and became a de facto fiat currency and at
the same time gold was completely isolated from the real world. By printing
excess amount of dollar towards its own benefit, the U.S. government inevitably led the gold dollar exchange commitment to collapse. And by using
the political and financial interventions, the U.S. governments real intention
to gradually destroy the gold dollar exchange commitment was covered until it is too late for other countries to do anything but to accept the fact
that dollar is no longer tied to gold. By destroying the gold dollar exchange
commitment in 1971, the U.S. dollar finally became the international reserve
currency with no constrains.
With the U.S. dollar being the world reserve currency, the U.S. government had a strong incentive to maximize the benefits from its dollar domination such as economic exploration and unlimited debt. In this case, printing
more dollars in the means of government debt literally means creating wealth
by oneself rather than working hard to earn wealth from others since U.S.
dollar was always guaranteed to be accepted as a result of Bretton Woods
system. And we could also see the benefit of this U.S. dollars exorbitant
privileges with the famous quote from French economist Jacques Rueff: ”If
I had an agreement with my tailor that whatever money I pay him returns to
me the very same day as a loan, I would have no objection at all to ordering
more suits from him.” (Dooley, Folkerts-Landau and Garber, 2004).
Therefore, we could see that the core of Bretton Woods system was not
the double pegged system or the setup of International Monterey Fund and
World Bank, it was the use of U.S. dollar as the worldwide reserve currency.
All others were just the path towards it. The collapse of Bretton Woods
system in 1971 was actually the collapse of gold dollar exchange standard.
This historical collapse did not hurt the U.S. dollars privilege but in the
opposite strength it as gold was officially driven out of the stage. The reason
that dollar was advertised as good as gold is because the simple fact that it
never is, but the worst of all, is what as the famous British economist Keynes
commented it is exactly the opposite of gold standard. (Stephey, 2008).
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Collapse of the Bretton Woods System
5
Yuchen Wu
Answer to the Question
By taking the approach to understand the role gold played in the Bretton
Woods system, we can see that the Bretton Woods system apparently played
a temporary but very important role in the development of our financial and
economic world. Its birth served its purpose of setting the U.S. dollar as the
index currency. Its life served its purpose of getting the world used to dollar.
Its death served its purpose of setting the dollar completely free. With these
understandings in our head, we could finally answer the question raised at
the beginning of this paper and explain what exactly caused the collapse of
the Bretton Woods system. And the angle to answer this question should not
be limited in one direction, but actually three directions. That is Economic,
politics and philosophy.
Economical speaking, the collapse of Bretton Woods system was caused
by the over-issue of U.S. dollar towards U.S.s own benefit. And this could
not be done without the fact that the U.S. dollar is an unconstrained fiat
currency, which is in turn achieved by purposefully design the Bretton Woods
system by U.S. government in order to let U.S. dollar replacing the gold as
the world reserve currency.
Political speaking, the collapse of Bretton Woods system was inevitable
as it serves as the final step to unchain the U.S. dollar. Gold was just a
tool used by US government to convince other countries to accept Bretton
Woods system, gold is neither essential nor important to the existence or
usage of dollar. After Bretton Woods system finished its historical duty to
make the world transfer from gold standard to dollar standard, it would be
abundant by the US government sooner or later. Because only when the last
connections between dollar and gold were terminated, the dollar can finally
shows its true power, as what it is today.
Philosophical speaking, the collapse of Bretton Woods system was due to
the conflict of interest. In other words, the fact that Bretton Woods system
was built solely focusing on the benefit of U.S. is the reason to cause its own
failure in the long term. A currency completely owned by one country could
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never serve both the interests for its owner as well as the rest of the world
since the owner of the currency would always uses it towards its own benefit
at the cost of others. That is also why we see the emerging of Euros and
other currencies in an attempt to end the U.S. dollars monopolistic position.
In short, any international monetary system built on one single currency
owned by one single country would eventually collapse, by definition.
It is usually helpful to find the truth by looking back to the history and
see what happened afterward. In 1996, Paul Krugman summarized the postNixon Shock era as follows: The current world monetary system assigns no
special role to gold; indeed, the Federal Reserve is not obliged to tie the dollar
to anything. It can print as much or as little money as it deems appropriate.
There are owerful advantages to such an unconstrained system. Above all,
the Fed is free to respond to actual or threatened recessions by pumping
in money. It is very clear that the collapse of Bretton Woods system has
done much more good than harm to the U.S. government by have U.S. dollar
successfully replacing the gold. And perhaps that is the fundamental reason
why the Bretton Woods system would have to collapse. Therefore, the year
1971 was not the year Bretton Woods system fell but as a matter of fact the
year it finally stood up.
References
Conte, Christopher, and Al Karr. 2001. Outline of the U.S. Economy. U.S.
Dept. of State, Office of International Information Programs.
Dooley, Michael P., David Folkerts-Landau, and Peter Garber. 2004. “The
Revived Bretton Woods System.” International Journal of Finance and Economics, 9: 307–313.
Gavin, Francis J. 2003. Gold, Dollars, and Power - The Politics of International
Monetary Relations, 1958-1971. The University of North Carolina Press.
Mikesell, Raymond F. 1994. “The Bretton Woods Debates: A Memoir.” Prince
University Department of Economics: Essays in International University, ,
(192).
Ravenhill, John, ed. 2005. Global Political Economy. Oxford University Press.
Stephey, M.J. 2008. “A Brief History of Bretton Woods System.” Times Magazine.
56
Collapse of the Bretton Woods System
Yuchen Wu
United States Congress, Public Law 90-269, 1968-03-18. n.d..
A
Appendix
Figure 1
57
An Insight on the Rationale of Using Expansionary
Monetary Policy during the Great Recession
Chi-Fei Ma
Shortly after the end of WWII, the United States became the largest
economy in the world. As Europe was recovering from the aftermath of the
War, the US seized the opportunity and became the only country which had
the ability to re-shape the global monetary order. The US dollar became the
major currency of international trade and thus the US dollars depreciation or
appreciation began to have severe impacts for economies around the world.
The Great Recession is a global economic decline that began in 2007. It
started with the US subprime mortgage crisis and other high-risk financial
activities. The bursting of the US real-estate bubbles, caused by the easy and
aggressive credit conditions prior to 2008, also contributed to the Recession.
The economic decline has since then expanded from a US financial crisis to
a global recession, which resulted in a severe slump in international trade,
soaring unemployment rate and high level of household debt.
Nearly 5 years after the Great Recession began, the US economy is now
recovering slowly, and has been stimulated by both conventional and unconventional monetary policy conducted by the United States Federal Reserve
Bank and its counterparts, including the European Central Bank, the Bank
of England and the Bank of Japan.
A central bank is the sole conductor of modern monetary policy. In Will
Robsons article (Robson, 2008), he described central banks as “not only fast
and powerful, but [their] operational independence and place at the core of
national payments systems mean they can act even-handedly among sectors
and regions.”
Theoretically speaking, standard expansionary monetary policy includes
the Federal Reserve (central bank) buying government bonds in order to
lower interest rates as to improve the current account and eventually increase
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Expansionary Monetary Policy during the Great Recession
Chi-Fei Ma
the equilibrium income in the short run, caused by the increase in the money
supply.
Prior to the outbreak of the recession in 2007, the money market, the
goods market, and the external sector were in equilibrium. The outburst of
the subprime loan losses and US housing bubbles in 2006 caused the initial
wave of the financial crisis including the plummeting of securities and the
failure of Lehman Brothers. Following that, high default rates on subprime
mortgages and low-quality mortgages started to deteriorate the financial
system.
If this was a regular economic downturn or if the short term nominal
interest rate was not close to zero, the Federal Reserve would have decided
to initiate expansionary monetary policy by increasing the nominal supply
of money through an increased amount of open market operation. In the
IS-LM-BP diagram, this action shifts the LM curve rightward and rate of
interest would then decrease. The decrease in the interest rate causes the
balance of the capital account to deteriorate and the gradual deterioration
of the capital account causes the US dollar to depreciate.
Normally, this would create excess demand in the US goods market as
US exports become more competitive in the international market. In order
to eliminate the excess demand of US products, output starts to rise and the
demand for money is also raised, and so the rate of interest starts to increase.
At the end of the process, LM, BP and IS curves all intersect at a new point
again. The equilibrium income increases and equilibrium rate of interest
decreases as a result of the increase in the money supply. This standard
monetary policy was a common practice by central banks around the world
when responding to economic downturns, prior to the Great Recession.
However, during the Great Recession, when the risk-free short term nominal interest rate was close to zero, standard monetary policy became ineffective to stimulate the economy as it could no longer lower the rate of interest.
Since the federal fund rate (short-term nominal interest rate) targeted by the
Federal Reserve (Reis, 2010, p 120) dropped consistently from 5% in mid2007 to 0.25% in late-2008, the standard expansionary policy implemented
by the Fed in 2007 was not very effective in accelerating the US economic
recovery. This is the moment when the Fed considered the possibility of
initiating Plan B - Quantitative easing QE1, QE2 and QE3.
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Quantitative easing, which almost no one had heard of five years ago, is
described by The Economist as the great new discovery in macroeconomics
and policymakers put their faith in it as the engine of recovery. It was first
used by the Bank of Japan (Roach, 2012) in 2001 to counter domestic deflation. The Federal Reserve was contemplating the execution of quantitative
easing by buying financial assets from commercial banks and other private
institutions in an attempt to increase the monetary base.
Up until July 2013, the Federal Reserve initiated three series of Quantitative Easing and each of these QEs differed from another. In QE1, the Fed
bought $600 billion worth of mortgage-backed securities. This large amount
of asset purchase was aimed at increasing the asset portion of the national
balance sheet in order to support economic activity. According to the ISLM-BP model, when money supply increases it also increases the liquidity
of the private sector, which in turn provided support to the functioning of
the credit market.
In QE2, the Fed announced to purchase $600 billion worth of Treasury
securities with the intention of supporting US economic activity. According
to the IS-LM-BP model, increasing the US money supply depreciates the
dollar against other currencies. This depreciation could benefit domestic
exporters but could also harm creditors and importers. In 2012, the Fed
decided to initiate QE3, which was a bailout plan of $85 billion per month
to purchase mortgage-backed securities. The result of QE1 and QE2 is foreseeable. Adjusted reserves has soared to 6.8% (Svensson, 2012) of GDP in
2009 (from 0.8%, 2007), while the monetary base was equal to 14% of GDP
in 2009 (from 6%, 2007).
Since the US economy is the largest economy in the world, the Recession
itself has grown from a US domestic problem to a world economic recession (except in some countries such as China and South Korea who just
experienced slow economic growth instead of severe recession). In 2009, the
European Central Bank (Galbraith, 2006) launched a purchase plan of
e60
billion covered bonds. ECBs counterpart, the Bank of England launched a
similar quantitative easing plan worth £375 billion.
In Asian countries other than China and South Korea, (Wan, 2010) who
avoided the Recession, Japan has been seriously affected by a bleak US
economy, together with the weak domestic economic situation since 1999.
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As a pioneer of Quantitative Easing, Japan spent U55 trillion in 2011 in
order to expand its national balance sheet and money supply to tackle the
Great Recession. Additionally, the Bank of Japan decided to add $1.4 trillion
during 2013 and 2014 in order to bring Japan out of deflation, a policy known
as Abenomics.
The effectiveness of QE is open to debate (Beckworth, 2011). Theoretically speaking, according to the IS-LM-BP model, the aim of quantitative
easing is to influence the quantity of bank reserves to influence the price
and rate of interest. Statistics proved that US monetary base did increase
sharply, stock price is increasing and is accompanied with decreasing unemployment rate.
However, in 2012, the Bank of England reported that quantitative easing
increased stocks and shares value by 26%, but 40% of these capital gains was
received by the richest 5% British households. In addition, according to the
IS-LM-BP model, if the amount of easing launched was over-estimated or
too much money supply was created by the purchase of liquid assets, then
there could be a risk that quantitative easing caused higher inflation than
favoured.
Some economists argue that in addition to monetary policy, fiscal policy
can be effective when tackling economic downturn. In William Robsons paper, he noted, Most things governments can do speedily are, in fact, unlikely
to help much. His statement has been proven to be correct during the peak
of the Great Recession. Quick one-offs such as cutting sales tax, which the
Canadian government adopted in 2008, and sending cheques to households,
which the US government adopted, have not been very effective. On the
other hand, traditional fiscal policy such as increasing government spending on building new infrastructure can effectively stimulate the economy.
However, the drawback is it takes too much time for these projects to be
designed and executed. In conclusion, monetary policy such as quantitative
easing is capable to boost the equilibrium income in the short run and is
ideal for government leaders who want quick and instant results (for political reasons). However, for the benefit of the domestic and global economy,
the appropriate fiscal policy is also a must as it can continuously stimulate
the economy in the long run. As a result, although there are drawbacks
to quantitative easing, the best scenario would nonetheless be a responsi61
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ble government initiating expansionary fiscal policy and an effective central
bank initiating quantitative easing, at least until the economy has reached
the 2% inflation target.
References
Beckworth, David. 2011. “Brad DeLong, Jim Grant, and Milton Friedman.”
Macro and Other Market Musings.
Galbraith, James K. 2006. “Endogenous Doctrine, or, Why Is Monetary Policy in America so Much Better than in Europe?” Journal of Post Keynesian
Economics, 28(3): pp. 423–432.
Reis, Ricardo. 2010. “Interpreting the unconventional US monetary policy of
2007-09.” National Bureau of Economic Research.
Roach, Stephen S. 2012. “Shinzo Abe’s Monetary Policy Delusions.” Project
Syndicate.
Robson, William. 2008. “This is a job for the Bank of Canada.” The Globe And
Mail.
Svensson, Lars EO. 2012. “Practical monetary policy: Examples from Sweden
and the United States.” National Bureau of Economic Research.
Wan, Ming. 2010. “The great recession and China’s policy toward Asian regionalism.”
62
On Valuing Life: Ecuador’s Yasunı́-ITT Initiative and
Payments for Ecological Services
Francesca Hannan
In August 2013, Ecuador’s president Rafael Correa announced the cancellation of the Yasunı́-ITT initiative. This 2007 proposal would have exempted the ITT (Ishpingo-Tambococha-Tiputini) concession in the Amazon
rainforest from oil extraction, foregoing approximately $7 billion in revenues
on the condition that world governments and private donors compensate
Ecuador for half of the foregone revenues over a period of ten years (Larrea
and Warnars, 2009). Although it should be noted that the initiative was
highly politicized (Arsel and Angel, 2012; Rival, 2011), the scope of this
paper is the economics behind Yasunı́-ITT and why it did not attract the
participation necessary to delegitimize the sudden cancellation de la Repblica del Ecuador.
The ITT concession is located in Yasunı́ National Park - a region that
is valuable by any definition of the word. Besides the presence of oil, it
is the site of important ecological activity. Old-growth rainforest, a pillar
of Earth’s ecosystem, plays an indispensable role in global carbon and water cycling. Furthermore, Yasunı́ is held by biologists to be easily among
the most biodiverse places on the planet Larrea and Warnars (2009). The
practical importance of biodiversity to humans is well-established, and far
too manifold to be elaborated here. In short, as living things, we use the
rainforest’s services on a daily basis.
Importantly, people do not pay for the usage of these services as they
have been available to us through no agency of our own since before money
was invented. By contrast, oil is a tangible commodity. Though its existence
is a geological accident, its provision as something to be bought and used
requires human agency and human labour, necessitating compensation. The
quantification of its value in money not only can, but must be determined
in a market in order for its use-value to be accessible. The coexistence
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of different types of values by one which is pecuniarily quantifiable and one
which is not creates an economic case-study as fascinating as the forest itself.
To explain, while Ecuador’s government formally acknowledges and celebrates the value of Yasunı́ to humanity’s well-being, it is mostly through oil
extraction that the rainforest has produced actual financial revenues for the
country. An important tension arises: the economic value of Yasunı́ oil cannot be realized without the forest’s ecological value being compromised, as oil
extraction necessitates deforestation and contributes to global warming. As
the country requires funds for development, it faces the incentive to destroy
ecological value in the realization of financial value. It is no revelation that
such incentives can bring about market failure. In exploiting its oil reserves,
Ecuador trades off a public benefit for a private one. As the environmental
impacts of such decisions have been increasingly sorely felt, many scholars
have stressed the importance of finding ways to explicitly place economic
value on ecosystems in order to incentivize conservation.
The concept of Payments for Ecosystem Services (PES) has thus gained
increasing prominence in environmental-economic discourse, but still involves many ‘unresolved difficulties’ (Salles, 2011). As mentioned, ecosystems unlike commodities are not available because humans want them or
because humans made them. Their existence is prior to the existence of a
market of producers and consumers, which we normally rely on to determine something’s price. A somewhat arbitrary valuation must therefore be
decided upon the question of how remains controversial. Approaches often
involve determining willingness-to-pay for preservation of ecosystem services
as a proxy for their value. Problematically, this in turn cannot be objectively
determined in a way that likely reflects the true value of the services. Due
to the complexity of evolved natural systems, we often do not know which
particular natural features are indispensable or what degree of degradation
can be allowed before we compromise our own survival. As such, we are very
prone to under-valuing or (much less likely) over-valuing a particular ‘unit’
of ecosystem.
That is, we would be, if we consumed ecosystem services in identifiable
units. However, use of ecosystems does not involve a specific act of consumption at all; we consume them by way of being alive. On rainforest and
the water cycle, for instance, biologist Pete Oxford writes:
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On Valuing Life
Francesca Hannan
”Every glass of water. . . you drink contains water
molecules that. . . [have] been sucked up from the forest floor by the roots of a tree in the Amazon, pumped
into the atmosphere by that tree during respiration
and transpiration, and converted to rain to fall somewhere, to be drunk by you. Your very blood contains
molecules of Amazonian water!” - Oxford (2012)
Our consumption of ecosystem services so permeates our lives that we are
normally altogether unconscious of it, creating the paradox that we cannot
conceptualize our willingness-to-pay for something not only valuable, but
indispensable.
Currently, formalized PES schemes for forest carbon sequestration attempt to overcome this problem as payments are simply those necessary
to compensate action taken to create or preserve carbon sinks. The United
Nations’ Clean Development Mechanism (CDM), for instance, only funds afforestation or reforestation projects (United Nations Framework Convention
on Climate Change), and not deforestation prevention, while Reducing Emissions from Deforestation and Forest Degradation (UN-REDD) requires developing countries’ active participation in creating forest management plans
and assisting those who must abandon deforestation-based livelihoods (Programme). The carbon market does not yet incorporate projects like Yasunı́ITT, which do not require restoring forest or changing how it is used, but
simply leaving it untouched. Such a scheme appears to require more so a
valuation of the forest’s existence itself.
However, the reasoning behind the initiative was grounded in the fact
that a decision to refrain from extraction constituted an exercise of human
agency that would make ecological services more available than otherwise.
This scenario of alternatives contingent on a decision created the potential for economic valuation based on an ordinal utility approach; should the
global community prefer rainforest preservation to oil extraction in this instance, the ecological value of Yasunı́ could be economically realized as the
compensatory payment to Ecuador necessary to bring about the decision not
to extract.
Notably, the problem of quantifying the forest’s value was side-stepped,
and instead this was proxied by Ecuador’s opportunity cost of not develop65
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ing the oil field as the ‘price’ it would pay for preserving ecosystem services.
Ecuador announced its willingness to pay half of this price, and essentially
asked that its fellow consumers pitch in the remaining cost of the services all
would use. While still arbitrary, this method of valuing preserved rainforest
was admirably objective; Ecuador isolated a ‘unit’ of ecosystem, identified
a ‘cost’ associated with making its services available, and asked that it be
compensated for this cost by the community for whose benefit it was incurred.
Then, the willingness-to-pay of agents the world over and thus their
contributions to Yasunı́-ITT were left to be determined by their perception
of whether they would benefit more from the preservation of ITT or the
exploitation of the oil reserves. Unfortunately, in this case a standard costbenefit comparison could convince an economic decision maker that there
was little incentive to pay for preservation. The amount of rainforest which
would be lost if drilling occurred in ITT is very small compared to the world’s
total. It is quite possible that the marginal deforestation caused would not
affect our ability to survive on the planet, or directly and wholly cause any
species extinctions. It is also unlikely that the ten days of world oil consumption to which the ITT reserves are equivalent would itself bring about
catastrophic climate change. It appears that the failure to meet fundraising
targets and the initiative’s cancellation formalized an overall consensus that
the economic activity produced by said oil consumption is truly more valuable than one preserved concession as CDM and REDD projects, after all,
offer alternative destinations for funding that do not require such a sacrifice.
The difficulty, therefore, lay in the fact what was at stake with Yasunı́ITT was only an increment of ecosystem. Ecuador succeeded in coming up
with a price for one unit of ecosystem services, but this did not solve the
valuation problem since so many other units’every other hectare of rainforested national park in the world’ remained available for free. That is,
Ecuador offered at a positive cost services whose ‘market’ price is zero.
This being the case, it is difficult to answer why Yasunı́-ITT made
economic sense without asking further questions. What if the cost-benefit
reasoning outlined above were applied to every patch of rainforest destroyed
for oil, agriculture or settlement? Or to every oil reserve in the world which
will remain underground, given that most of them must if climate impacts
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On Valuing Life
Francesca Hannan
deemed unacceptable by the international community are to be avoided?
(Initiative, 2012) If we always contemplate the preservation-extraction tradeoff only at the margin, the so-called rational price of ecosystem services will
remain zero until we recognize that ecosystems have become so degraded that
the marginal importance of preservation justifies foregoing other economic
benefits. Our inherent difficulty with valuing ecosystem services casts doubt
on whether this will occur before our individual ’‘rational’ decisions produce
an aggregate effect of devastation.
Success of Yasunı́-ITT would have required a conscious choice not to
take this chance. The initiative formalized an unorthodox approach to economic decision-making by which a single choice is considered in the context
of aggregate effects. Unorthodox, experimental, and imperfect, certainly;
but there will likely never be any solutions to global warming or biodiversity
collapse which do not involve a calculated break in orthodox economic reasoning. Such reasoning, along with ecological ignorance, caused these problems. However, we are no longer ignorant, nor are we the simplified marginal
cost-benefit analyzers portrayed by elementary Economics textbooks. There
is no shortage of profound, informed economic thought focusing on environmental crises. Hopefully, international policy will begin to reflect such
thought before it is too late.
References
Arsel, Murat, and Natalia Avila Angel. 2012. “”Stating” Nature’s role in
Ecuadorian development: civil society and the Yasun-ITT Initiative.” Journal
of Developing Societies, 28(2): 203–227.
de la Repblica del Ecuador, Presidencia. n.d.. “Presidente Rafael Correa,
Cadena Nacional sobre iniciativa Yasun Itt (English subtitles).” Retrieved from
https://www.youtube.com/watch?v=315v8QPAqQg.
Initiative, Carbon Tracker. 2012. “”Unburnable Carbon:
Are the
world’s financial markets carrying a carbon bubble?”.” Retrieved
from
http://www.carbontracker.org/wp-content/uploads/2014/09/
Unburnable-Carbon-Full-rev2-1.pdf.
Larrea, Carlos, and Lavinia Warnars. 2009. Ecuador’s Yasuni-ITT Initiative:
Avoiding emissions by keeping petroleum underground. Vol. 13.
Oxford, P. et al. 2012. Yasun, Tiputini and the Web of Life. Quito: Ingwe Press.
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University of Toronto Economic Review
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Programme, UN-REDD. n.d.. Retrieved from http://www.un-redd.org/
AboutUN-REDDProgramme/tabid/102613/Default.aspx.
Rival, Laura. 2011. Chapter ”Planning development futures in the Ecuadorian
Amazon: the expanding oil frontier and the Yasuni-ITT Initiative”. London:
Routledge.
Salles, Jean-Michel. 2011. “Valuing biodiversity and ecosystem services: Why
put economic values on Nature?” Comptes Rendus Biologies, 334: 469–482.
United Nations Framework Convention on Climate Change. n.d.. “Clean
Development Mechanism: Methodologies.” Retrieved from http://cdm.unfccc.
int/methodologies/index.html.
68
Front Matter
Spring 2015
Contributors
Rebecca Hensman is a graduating student completing a double major in
Economics and Human Biology: Genes, Genetics and Biotechnology. She is
interested in pharmaceutical market research.
Chi-Fei Ma is a 4th year Finance student at the Rotman School of Management. He has been obsessed with game theory and political economy ever
since he was old enough to attend university.
Yuchen Wu is a graduating student at Rotman Commerce specialized in
Finance and Economics.
Francesca Hannan is a third year student double-majoring in Economics and
Environmental Studies. She is interested in researching the structural and
behavioural changes necessary for sustainable development.
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University of Toronto Economic Review
Volume 1, Issue 1
Editors-in-Chief
Michael Boutros is a graduating student interested in how to apply economic
theory in explaining empirical phenomena. He is especially interested in
macroeconomics and new ways of approaching old problems.
David Cheng is a fourth-year student in Economics and Political Science.
He is interested in fields of public economics and economic history. David is
also the President of the Economic Students’ Association for 2014-2015.
Quan Le is a third year student at the university. He studies Mathematics
and Economics with a focus on development, urban and cultural economics.
Editors
Brianne Chan is a third year student double majoring in actuarial science
and economics. She is interested in the study of environmental economics
and the impacts of green policies and projects.
Matthew Hong is a second year student in economics. He is interested in
financial economics and macroeconomic policy.
Pujan Modi is a graduating student in Economics and Ethics, Society &
Law. His interests lie in the potential of using empirical microeconomics to
achieve the public good.
Katherine Wang is a student of economics and applied math (with a minor
in political science) at the university.
Ian Weaver is a fourth year student at the university. He is a double major in
mathematics and economics with interests in sports analytics and education
economics.
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