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Structural Adjustment during Canada’s Wheat Boom: 1900-1913*
Emma Stephens
Graduate Student, Department of Economics
Cornell University
Ithaca, NY, USA
DRAFT - NOT FOR CITATION
Abstract
Using a theoretical model borrowed from the literature on adjustment to booming
tradable sectors, I find that the observed exponential growth in Canada’s agricultural,
manufacturing and non-tradable sectors and wage and price trends between the turn of
the century and the First World War are consistent with a model of tariff protection of the
manufacturing sector from any negative consequences of the agriculture sector boom
during this period. The model implies that without tariff protection, the manufacturing
sector might not have developed as rapidly due to the increase in equilibrium real wages
and reallocation of the labor supply brought about by the boom in agriculture, as in a
‘Dutch Disease’ scenario. To effectively control for the effects of the increasing
immigration, land settlement and capital inflow rates while examining the adjustment of
the manufacturing sector to the Wheat Boom, a simple system dynamics model of the
agricultural and manufacturing sectors is developed. The system dynamics model is then
used to illustrate the divergent growth paths of Canada’s manufacturing and agricultural
sectors and overall economic performance under different hypothetical trade policies with
modern implications for domestic trade policy in developing nations.
*
I wish to thank Asaf Zussman, Charles Nicholson, Chris Barrett, Paul Hayes, Talia Bar, Nancy Chau, Francesca Molinari
and the participants in Cornell’s Third Year Research Seminar for valuable feedback on this paper. All errors are my own.
1. Introduction
At the beginning of the 20th century, the Canadian economy was rapidly changing in a
number of different dimensions. The Canadian government was determined to unify the
country and promote ‘east-west’ economic interactions and pursued a number of key
programs, like the completion of the transcontinental railway in 1885 and an aggressive
recruitment campaign to promote immigration to the country, starting in 1896 (Skelton,
1914).
As well, massive movements of international capital from abroad and
technological advances in many of Canada’s industries simultaneously exerted pressure
on the economy at the turn of the century.
The two largest components of GNP for Canada during this period were agriculture and
manufacturing. Between 1870 and 1910, the two combined accounted for between 39
and 56 percent of gross domestic product, with agriculture’s share as the slightly larger
part until 1911 (Table 1). Canada produced a wide variety of agricultural products and
manufactured goods many of which were either destined for the export sector or subject
to substantial international competition.
In addition, both sectors saw phenomenal
growth, particularly after 1900. A clear turning point in the time series for both sectors is
observable around 1900. (Figure 1).
Several theories exist about the interactions between growing sectors in an economy.
One particular strand of the literature concerns the impact of a growing tradable sector on
other tradable sectors that are subject to international prices (Corden & Neary, 1982,
Corden, 1984). This literature was developed to explain the behavior of the Dutch and
British economies after the discovery of new oil reserves in the 1980’s. Both economies
suffered a contraction in manufacturing that was theorized to be partly due to the boom in
2
the oil industry spurred by adjustment to the discovery of the new tradable natural
resource. This effect is known as the ‘Dutch Disease’. This theory of the adjustment
process is also applicable in the case of price shocks for internationally traded goods, as
well as a natural resource discovery.
The Dutch Disease model of adjustment between a booming and a lagging tradable sector
can be used to study the response of an economy to a great many different types of
shocks, such as positive technological improvements and improved terms of trade. It has
also been recently applied to historical events, such as the effect of the importation of
American treasure on Spanish industry in the 16th century (Forsyth & Nicholas, 1983)
and increases in overseas investment income for the U. K. between 1870-1913 (Rowthorn
& Solomou, 1991).
The period of rapid growth in the agriculture sector in Canada between 1900-1913 is
known as the Wheat Boom era in the literature on Canadian economic history. Many
economic historians have attempted to analyze the impact of the boom in the agriculture
sector on Canada’s overall level of economic growth and many believe that the two
trends are highly correlated (Bertram, 1963, Lewis, 1975, Altman, 1987, Inwood &
Stengos, 1991).
The Wheat Boom has been attributed to many different factors including technological
improvements, and increased demand for Canadian agricultural output, (particularly
wheat) on the international market (Dick, 1980, Ward, 1994). Some of these changes
thus have qualities that should allow successful application of the Dutch Disease model
to Canada during this period. However, the manufacturing sector in Canada was also
3
growing during the same period, which is in direct conflict with some of the predictions
of the basic theoretical model.
Thus far in the literature on Canada’s historical economic development, the growth of
overall GNP per capita in Canada during this period has generally been attributed to the
boom in the agriculture sector, although the exact degree is still in dispute (Chambers &
Gordon, 1966, Dales, McManus & Watkins, 1967, Lewis, 1975, Inwood & Stengos,
1991) and has been used in the past as evidence to support the idea of export-led growth
(also known as the Staples Hypothesis (Vickery, 1974, Ankli, 1980)) as a policy that
should be promoted in many developing countries today.
The Staples Hypothesis focuses on forward and backward linkages from agriculture to
manufacturing to account for the observed positive levels of growth in both sectors
between the turn of the 20th century and the beginning of WWI, and have concluded that
these linkages promoted economic growth overall1. However, this is a longer view of the
behavior of the agriculture and manufacturing sectors and the actual interactions between
the two in the medium run might be better represented by the Dutch Disease model.
The clear divergence between the predictions of these two models of economic
adjustment is cause for concern, because the policy implications for each are completely
different. On the one hand, if one believes that a booming export sector could be
responsible for the decline of another important part of the economy, even if it is just in
the medium run, then perhaps measures can be undertaken to lessen the impact of the
shock.
On the other, if exports are believed to lead to economic growth, then the
booming export sector should be promoted to the highest possible degree, despite interim
1
For example, Caves (1971) examines such linkages as the relationship between the rate of export
expansion and savings rates, international migration patterns, and import-competing manufacturing growth.
4
adjustments between the different exporting sectors. The Dutch Disease model should
apply in the Canadian case.
However the predicted result of a decline in the
manufacturing sector did not occur. It is important to determine why, if the Canadian
experience of economic growth at the turn of the 20th century is to be used as a model for
other countries to follow in the future.
One limitation of the Dutch Disease model in its most basic form is that it models
adjustment in the medium run and relies partly on assuming that important state variables
such as labor or land or financial capital are held fixed. The turn of the century in
Canada was a time of rapid expansion of the area of farmland and the country
aggressively attracted immigrants to settle the Western Provinces (Dick, 1980, Urquhart,
1986). As well, inflows of foreign capital due to overseas investment also boomed in the
period under study (Dick & Floyd, 1992).
Therefore, following the theoretical
discussion, I present a simple system dynamics model of the Canadian economy that
allows for variable stocks of labor and land and foreign capital inflows. Some sample
simulations under different structural assumptions are presented and their impact on
important variables like output in both the agricultural and manufacturing sectors, as well
as prices and wages is discussed. As can be demonstrated with the simulations, the
adjustment of the different sectors of the economy both to the boom in agriculture as well
as to the many other changes that occurred in this period is still consistent with the
variant of the Dutch Disease model used in the theoretical discussion within certain
parameter ranges. Furthermore, the model reveals that particular assumptions about trade
policy need to be made in order to generate a scenario that most closely matches the
trends observed in the Canadian economy during this era. These simulations allow for a
5
discussion of trade policy in developing countries and the assumptions necessary for
economic growth for small open economies that are subject to various shocks.
2. The Dutch Disease Model of Adjustment and the Canadian Economy
This description of the Dutch disease model comes from Corden and Neary (1982). An
economy is supposed to consist of multiple tradable and non-tradable sectors that
generally share one or more factors of production. In the simplest version, the economy
is modeled to have two tradable and one non-tradable sector. All three sectors have a
particular factor of production, which is unique to that sector, as well as one shared
factor, which is assumed to be labor. The mobility of the shared factor between each
sector allows the shock to the booming tradable sector to be transmitted to the other
sectors in the economy.
Figure 2 shows one of the main implications of the Dutch Disease model. The labor
demand functions for the tradable sector (i.e. booming plus lagging sectors), the lagging
sector and the non-traded sectors are given by LT, LL and LNT respectively, with the wage
rate measured in terms of the lagging sector on the vertical axis. With an increase either
in productivity in the booming sector or some other increase in labor demand (an output
market price increase, for example), the tradable sector labor demand curve LT shifts
outwards (in this diagram, this is to the left). This results in an increase in the wages for
all sectors, as labor is assumed to be completely mobile and in equilibrium, the same
wage rate will prevail. The increase in wages draws labor from the lagging and nontraded sectors into the booming sector, as shown by the increase in labor from point A to
point B on the graph and the decrease in labor in the lagging sector from M to M’ (labor
6
in the traded sectors is measured from the right origin OT). This is known as the
‘resource movement effect’.
However, the internal adjustment to the booming sector then continues in the economy.
Due to the small open economy assumption, the price of both the booming and lagging
tradable sector output cannot change as it is determined in the international market. The
increase in wages leads to increased demand for all goods. Therefore, the price of nontraded goods relative to traded goods increases and the labor demand curve for the nontraded sector shifts outwards as prices rise, which draws labor from both the booming and
lagging tradable sectors into the non-traded sector (shown by the change in labor from
point B to point G). This is the ‘spending effect’.
The final result, in this particular formulation of the Dutch Disease model, is that labor
moves unambiguously out of the lagging sector, while the results for final labor
distribution in the booming and non-traded sectors are determined by the dominance of
either the resource movement effect, in which labor increases in the booming sector, or
the spending effect, in which labor increases in the non-traded sector. As well, nontradables prices relative to tradables prices have increased and the exchange rate
experiences a real appreciation.
Is the Dutch Disease model of adjustment appropriate for the Canadian economy during
the Wheat Boom period? The two primary components of GDP in the period were
agriculture and manufacturing (Urquhart, 1986). Real agricultural output was composed
of dairy products, meat, wheat and other field crops, with meat products dominating
production until about 1916 (Innis, 1986). Between 1900 and 1910, the rate of growth of
the agriculture sector increased, with yearly (compounded) growth averaging between 2
7
and 3% per annum from 1870-1900 and up to 4% in 1910. This growth has been
attributed to a number of factors, including rapid settlement of the Canadian prairies
(Innis, 1986), technological labor-saving improvements in farm equipment (Ward, 1994),
the development of better varieties of wheat (Urquhart, 1986) and the increased demand
for Canadian wheat for bread making (Dick, 1980).
In addition to production, increased numbers of people were involved in agricultural
production over this same period. Table 2 shows the numbers of individuals engaged in
agriculture according to the Canadian Census and the annualized growth rates of numbers
of workers in agriculture. The numbers of individuals engaged in agriculture increased
more than 165% between 1871 and 1911. In addition, the annualized growth rates
indicate that the number of workers grew fairly steadily at around 1% per year until 1901,
and between 1901 and 1911, the numbers grew by almost 3%. Therefore, there appears
to have been a great increase in both the number of those employed in the agriculture
sector and the overall output of this sector around the turn of the century that might be
analyzable using the Dutch Disease model.
However, determining the lagging sector may be difficult if the Dutch Disease model is
to be used. This model developed out of concern that booming sectors, especially those
in the natural resources, may negatively impact a country’s manufacturing sector, via the
drain on labor out of the lagging manufacturing sector. But in Canada, the manufacturing
sector overall displayed growth trends in output and workers quite similar to those of the
agriculture sector. Annualized growth rates of output average around 3% per year until
1900 and then jump to 5.2%.
Table 3 summarizes the available manufacturing
employment data. The numbers of individuals in manufacturing also grew, but at a
8
decreasing rate, as opposed to the agriculture sector, with employment growth rates
declining from between 3 and 4% per year to between 1 and 2%.
The changes in both agriculture and manufacturing overall mask changes in individual
sub sectors of each industry. In agriculture, meat made up the primary component of
agriculture until around 1910, when wheat began to dominate. In manufacturing, wood
products comprised 42% of all manufacturing output in 1870 but steadily declined as a
proportion of total manufacturing output to approximately 17% in 1910, while iron and
steel products grew from 5% to approximately 18% (Altman, 1987). So the interaction
between the agriculture and manufacturing sectors of the Canadian economy around the
turn of the century may be a complicated mix of changes in many different sub sectors.
For this study, I will focus on the agriculture and manufacturing sectors overall, but it is
important to keep in mind that much variation exists in the sub-components of both.
One final symptom of the Dutch Disease at work in an economy is a real appreciation in
the country’s exchange rate. Therefore the ratio of non-traded to traded prices should
increase if a booming sector is applying some pressure to domestic resources and is
changing incomes in an economy.
Figure 3 shows the overall ratio of non-traded to traded prices for Canada from 18701913. Between 1895 and 1905 it appears that the ratio of prices sustained an upward
movement, with a flattening out thereafter. This is also in line with the Dutch Disease
hypothesis that a boom will cause this ratio to rise because of the spending effect.
3. Reconciliation of the Dutch Disease model with Canadian Experience
There are many variations on the ‘Dutch Disease’ model, or more generally, the medium
run analysis of resource allocation in an economy with both tradable and non-tradable
9
sectors. The prediction of ‘de-industrialization’ generated by a boom in a country’s
tradable sector can only be assured in a very simplistic case where the tradable and nontradable sectors share only one common factor of production.
However, if more
complicated interactions between the three sectors are introduced that incorporate
different kinds of trade policy or two or more mobile factors, then the effects of a boom
in a tradable sector become more ambiguous.
In Corden and Neary (1982), three possible scenarios are presented where the booming
tradable sector might actually lead to an increase the output of the lagging sector. In the
first case, even in the simplest model with one shared factor of production, if the lagging
sector is not entirely for export, then the prediction of de-industrialization of the entire
lagging sector is not assured, as the movement of labor out of the lagging sector due to
the resource movement effect is counteracted with the increased output in the nontradable sector due to the spending effect. In the traditional model, the lagging sector is
assumed to be the country’s entire manufacturing industry, hence the fear of deindustrialization if the manufacturing sector is strictly for export. But if a portion of the
manufacturing sector can be considered as non-tradable, for example through the
imposition of tariffs, then at least some portions of the manufacturing industry may
benefit from the effects of the booming tradable sector, due to the increase in demand and
the spending effect’s promotion of output in the non-tradable sector.
Canada at the turn of the century had in place a protectionist tariff policy known as the
‘National Policy’ that was designed to insulate the domestic manufacturing industry from
competition from abroad (primarily from the United States) (Annis, 1936). Therefore, it
is possible that the sectors most protected by the National Policy should be better
10
analyzed as part of the non-tradable sector and the boom in agriculture, in that it raised
national income, could be said to increase demand for and the prices and output of at
least some of the manufacturing sector overall output, thereby eliminating the deindustrialization effect.
A second model presented by Corden and Neary incorporates both labor and capital. In
this expanded model, labor is assumed to be mobile between all three sectors, but the
booming sector employs a specific factor (in our case, land), and the lagging tradable
sector and the non-tradable sector are assumed to share both labor and capital and do not
have any other specific factors. The intensity of usage of labor and capital in the lagging
and non-tradable sectors therefore becomes the determining factor on whether the
booming sector causes output in the lagging sector (and the non-tradable sector) to go up
or down. If the lagging sector is more capital intensive than the non-tradable sector, then
the resource movement effect of the boom limits the amount of labor available to the
lagging and non-tradable sectors. Accordingly, the output of the capital intensive lagging
sector will rise, as the increase in the wage caused by the resource movement effect
causes the output in the relatively labor intensive non-tradable sector to fall. However,
the spending effect tends to increase demand for services, which raises output of the nontradable sector, and squeezes the output of the lagging trading sector, thereby
counteracting the resource movement effect. But, the result on the lagging sector’s
output is ambiguous and if the resource movement effect dominates, then the lagging
sector will experience an increase in output, because the pressure applied to the shared
factor of production (labor) more negatively affects the labor-intensive industry, which in
this scenario is the non-tradable sector. This is in contrast to the simplest model, with
11
only labor shared between all sectors, in which both the resource movement effect and
the spending effect squeezed the output in the lagging sector.
The third model assumes that two factors of production (labor and capital) are completely
mobile between all sectors of the economy. In this case, if the lagging sector is more
capital intensive than the booming sector and also the non-tradable sector2, then the boom
in the least capital intensive sector raises the relative wage with respect to the return on
capital, as well as the price of services, and can imply an increase in the output of both
the booming and lagging tradable sectors under certain conditions.
4. Statistical Evidence
The three versions of the Dutch Disease model presented above that allow for a
simultaneous increase in both the booming and lagging tradables sectors will now be
compared to data available for Canada at the turn of the century. In order to analyze the
Canadian case, it remains to decide which of the possible three models presented above
might best represent the behavior of the Canadian economy at the turn of the century.
4.a Labor Mobility Model with Protective Tariffs
If the only mobile factor of production is assumed to be labor, as in the first modified
version of the Dutch Disease model described in section 3 then the economy should
adjust to a boom in one of the tradables sectors by:
1. Reduced production of non-protected manufactures (i.e. manufactures is the
lagging sector.
2. Increased real wage (in terms of non-protected manufactures)
3. Increase in the ratio of non-tradable to tradables prices.
2
No assumptions are made on the relative capital intensities of the booming and non-tradables sectors.
12
Over the period between 1879-1913, much of the manufacturing industry in Canada was
protected by substantial import tariffs.
The Canadian government launched a
protectionist campaign with the institution of what was called the National Policy in
1879, which was designed to promote the development of sectors of the economy that
were facing competition from foreign imports. Table 4 summarizes the tariff rates on
different Canadian products in different years between 1879, when the National Policy
was first introduced, and 1907. Many manufacturing products (and also agricultural
products) were protected during this period. The tariffs on agricultural output declined
over this period but a vocal manufacturing sector in Canada managed to convince the
government that tariffs on almost all manufactures were necessary for Canada’s
economic development (Kilgour, 1988). This was also in spite of the fact that these
tariffs, especially on agricultural implements and other manufactured goods crucial to the
agricultural industry hurt farmers in the Western part of the country and were loudly
denounced by members of the agricultural sector (Annis, 1936).
One notable exception within the tariff policy appears to be the wood products sub sector
in manufacturing output. As mentioned previously, wood products declined from 42% to
17% of total manufacturing output between 1870 and 1910. This reduction has mostly
been attributed to the loss of markets for wood products brought on by the decline in
wooden shipbuilding at the end of the 19th century (Urquhart, 1986). However, the
various tariff programs listed in Table 4 do not specifically target the wood products
industry. It may have been subjected to an overall tariff that covered all untargeted
imports, however the relative lack of protection given to this sector, in light of the
implications of the Dutch Disease model that non-protected lagging sectors should
13
decline, might give some evidence that the booms in agriculture and protected
manufacturing sectors might have also contributed to the decline of the wood products
sector.
Therefore, even though overall manufacturing output increased during the Wheat Boom
era, some sub sectors that may have been better protected by tariffs (like iron and steel
products) seem to account for most of this growth, and extreme decline in non-protected
sectors like wood products is also observed. As well, as has already been noted, the ratio
of non-tradables to tradables prices did increase during this period. Finally, Mackinnon
(1996) finds that Canadian Pacific Railway (C. P. R.) real wages in both unskilled and
skilled positions grew between 1901 and 1913 (Table 5).
The national railways
employed up to 10% of the non-agricultural labor force in Canada before WWI and can
thus be seen as a partial proxy for manufacturing industry wages overall in the country.
Interestingly, in the Mackinnon wage study, there is also an observed differential between
nominal C. P. R. wage rates offered in the western provinces of British Columbia, and the
prairie provinces, over those offered in Ontario and Quebec. The Prairie Provinces were
the center of the agriculture boom and if C. P. R. wages can proxy for overall nonagriculture wages, then these wages were higher than wages offered in Ontario and
Quebec.
This might be further evidence that the booming agriculture sector raised
wages, because the effect of this boom would be felt the strongest in the provinces where
agriculture was most practiced.
Therefore, these three trends seem to match the modified Dutch Disease model described
above, with mobile labor but some parts of the manufacturing sector protected and not for
export. Demand from the booming agricultural sector for many manufactured goods
14
must have increased but due to the protective tariff, this demand was not satisfied by
increased importation from outside of Canada and may have led to the observed overall
increase in the output of the manufacturing sector, despite the opposite prediction of the
Dutch Disease model.
4. b Labor and Capital Mobility in the lagging and non-tradable sector plus labor
mobility between the agriculture and other sectors.
Taking now the Canadian economy as in the second model of section 3, assume again
that the manufacturing industry is completely tradable and the tariffs did not significantly
impact the level of competition. If agriculture (as the booming sector) has some specific
factors of production and only shares labor with the rest of the economy, then, if it is
assumed that the manufacturing sector is more capital intensive than the non-tradable
sector, manufacturing output can increase along with a booming agricultural sector only
if the overall output of the non-tradable sector decreases. This is because the resource
movement effect tends to boost production of the manufacturing sector as it is more
capital intensive than the services sector3. The boom in agriculture reduces the amount of
labor available to both manufacturing and the non-tradable sector, and the resultant
reallocation of labor and capital between these two sectors increases manufacturing
sector output. However, the spending effect that results from an overall increase in
national income due to the boom in the agriculture sector will increase demand for nontradable goods and this pressure will again draw labor out of manufacturing and back into
the non-tradable sector. So, the resource movement effect and the spending effect again
counteract each other, and the only way that this model could be applied to the Canadian
case, knowing that the overall production of the manufacturing industry rose during the
3
This is given as an application of the Rybcszynski Theorem.
15
period under consideration, would be if there was an observed decrease of output in the
non-tradable sector. The ratio of non-tradable to tradable prices should also increase in
this model, therefore without the further implication for the output of the non-tradable
sector, it would be difficult to distinguish this model from the model described in section
4. a.
The non-tradable sector essentially represents the provision of services to the Canadian
population. The non-tradables price series for Canada is composed of information about
housing construction and rent, plus other services like fuel and light (Dick & Floyd,
1992). Table 6 gives nominal GNP data on the total income received in construction,
transportation, electric light and power, residential rents and communications for selected
years. Using these sectors as representative of the non-tradable sector of the Canadian
economy, this income data was deflated using the non-tradable price series of Dick and
Floyd to get a rough estimate of real output in the non-tradable sector.
As can be seen in Figure 4, even by this arguably imprecise measurement of output in the
non-tradables sector, this version of the Dutch Disease model does not seem to match the
evidence available on the non-tradables sector.
Given the assumptions about the
manufacturing sector being more capital intensive than the non-tradables sector,
expansion in manufacturing, given a boom in agriculture, can only come at the expense
of output in the non-tradables sector. But the evidence seems to suggest that the nontradable sector,
as represented
by
various industries like construction and
communications, was also expanding, and experienced a sharp increase after 1895,
similar to the increases observed for both manufacturing and agriculture at this time.
Even if we consider only residential rents, which are arguably closest to the terms used to
16
create the non-tradable price index, there is still an observed increase in rents, although it
is much less pronounced than the overall increase in output in the non-tradables sector,
using the sub-sectors listed as proxies for the entire sector. Therefore, the simultaneous
increase observed in the Canadian economy in agriculture, manufacturing and the nontradables sector is not consistent with the assumptions of this model of structural
adjustment.
4.c Fully Mobile Labor and Capital between all sectors
If labor and capital are fully mobile between all sectors, as in the third modified Dutch
Disease model of section 3, then the results for the output of each sector and the real
wage, in terms of the lagging manufacturing sector, are ambiguous. Table 7 summarizes
the possible relative capital intensity combinations between the booming, lagging and
non-tradable sectors and the subsequent implication for prices and wages in each sector
of the boom. (i.e. kj is the capital intensity ratio for sector j (j=B, L, NT for Booming,
Lagging and Non-Tradables sector, respectively) and pNT is the price of output in the
non-tradable sector. w is the wage, in terms of lagging manufactures).
In looking at the Canadian economy, we know that prices in the non-tradables sector
unambiguously increased over the given time period, so we can restrict our attention to
the scenarios where pNT is shown to increase. As well, with the C. P. R. wages of
Mackinnon (1996), we might imagine that wages also rose. In the Corden and Neary
model, however, it is not possible to observe a simultaneous increase in lagging sector
output along with an increase in non-tradables prices and an increase in wages4.
4
This is because with increasing prices and wages, as in section 4. b, any increase in the manufacturing
sector output must come at the expense of output in the non-tradables sector, which was not observed in
Canada in the time being considered.
17
Therefore, the model with capital and labor fully mobile over all three sectors is not
consistent with Canadian data.
5. Simulation Model of the Turn of the Century Canadian Economy
In order to further support the notion that the correct model of adjustment for the
agriculture and manufacturing sectors is one in which the manufacturing sector is partly
protected from rising real wages by trade tariffs, I develop a simple system dynamics
model of the agriculture, manufacturing and non-tradables sectors that allows both for
analysis of the adjustment of the manufacturing and non-tradable sectors to the Wheat
Boom, while simultaneously taking into account the concurrent growth in the labor force,
area of farm land and foreign capital flows during the same period. The model tracks the
stocks of labor, real output, land and uses these stocks to calculate output, wage, labor
allocation and price trends as they adjust to changes due to the Wheat Boom.
A simplified diagram that shows the primary causal relationships between the stocks in
the model is shown in Figure 55. As can be seen in Figure 5, the simulation model is
simply a dynamic version of the Corden and Neary model that allows for variation in the
levels of the key state variables. Three important feedback loops that dominate the
behavior of the simplified model over time have been labeled. The first, shown with
green arrows, is the resource effect that leads to a reduction in manufacturing output in
response to an increased demand for agricultural output, due either to an increase in the
world price or due to a change in the level of agricultural production6. The shock to
demand drives up real wages, which reduces the amount of labor supplied to the
5
Full information on the model structure is available from the author upon request.
I also assume for simplicity that increased land area for farming leads to an increased demand for
agricultural sector labor and that increased capital inflows leads to an increase in the demand for
manufacturing sector labor and have not specified exact production functions in either sector.
6
18
manufacturing sector, as the increased demand draws workers from manufacturing and
the non-tradable sector into agriculture. The second loop, which runs around the outside
of the entire diagram, is the spending effect mentioned in earlier sections of the paper.
The increase in real GDP leads to an increase in demand for all outputs, which are
assumed to be normal goods. However, it is only in the non-tradables sector that this
increase in demand leads to an increase in real wages, as output prices in agriculture and
manufacturing are fixed by the international market. This increase in wages again leads
to a reduction in manufacturing output. The third loop is shown in blue (labeled “Real
Appreciation”) and represents the overall increase in non-tradables prices that are a direct
result of the boom in the tradable sector (in this case agriculture).
In the causal loop diagram, the primary stocks have been placed inside the boxes. By
identifying these elements as stocks and developing appropriate rate equations, the
diagram shown becomes a full-fledged stock and flow structure in the system dynamics
model of the interaction between agriculture, manufacturing and the non-tradables sector.
It is the ability to describe the flows into and out of the labor and output pools for the
three sectors under consideration, both due to the boom in agriculture but also due to
other inflows and outflows like immigration, emigration and land settlement, that allows
for the analysis of the Canadian economy using the Dutch Disease framework, while
simultaneously controlling for the dynamic processes that were important during the
period between the turn of the century and the First World War.
5.a Simulation Results
The model simulates for thirty years. The simulation starts in approximately 1890, which
is a few years before the observable upward trends in the different production sectors
19
takes place and is a year that has a large amount of data available. The initial values for
key stocks and flow rates, like labor force, immigration/emigration rates, output for each
sector, etc. were collected from Dick (1980) and Urquhart (1986) wherever possible to
initialize the model. It is important to note that much other data on dynamic variables
like appropriate adjustment times that govern many of the first order adjustment rate
equations in the model are not known and were given very rough estimates.
The
dynamics described by the different simulation runs are therefore primarily qualitative
rather than precise quantitative predictions.
5.b.1. Simulation of the ‘baseline’ Corden and Neary model
Figure 6 shows the result of simulating the most restrictive form of the model, under
circumstances that most closely match the original Corden and Neary (1982) theoretical
framework. In this simulation, the total labor force is held constant and world prices for
agricultural and manufacturing output are assumed to be fixed. However, the price for
non-tradable output is calculated within the model in response to the changing
distribution of labor between the three sectors. An increase in farmland area drives the
‘boom’ and increases the demand for labor in the agricultural sector. Using the fact that
the labor force is fixed as well as an approximate elasticity of labor demand response to
increases in farming land, the final medium run changes in supply curves for labor in the
manufacturing and non-tradables sector that result from the boom in labor demand in
agriculture are calculated and the stocks of labor in the two ‘lagging sectors’ gradually
shift, with both manufacturing and the non-tradable sector experiencing an initial
decrease due to the ‘resource effect’ (this is analogous to the movement from point A to
B in Figure 2).
The shifts in the demand and supply curves are then used to
20
endogenously determine the new equilibrium wage that should be common across all
three sectors, under the assumption of perfect mobility of labor.
As soon as wages start to increase in response to the agriculture boom, the ‘spending
effect’ that results from the real appreciation begins to operate, and the labor force shifts
again, this time out of manufacturing and agriculture and into the non-tradable sector
(this is movement from B to G in Figure 2). The price of non-tradable output is also
determined endogenously through the changing labor supply and demand curves as well
as the changing demand for non-tradable output brought about by the ‘spending effect’.
Finally, the changes in labor lead to changes in output, with the manufacturing sector
experiencing an overall decrease in the amount of final output, which is the hypothesis of
the ‘Dutch Disease’.
As can be seen in Figure 6, most variables demonstrate the behavior described above.
Output in agriculture initially increases in response to the movement of labor from the
other sectors into agriculture, but gradually experiences a decline as the ‘spending effect’
draws labor out of agriculture and into the non-tradable sector. Also, output in the nontradable sector has increased while manufacturing has decreased, which is as expected.
Wages climb almost continuously during the simulation period time but non-tradable
prices and GDP first increase and then decrease. This is due to the relative productivity
of labor in each sector and the changes in labor allocation. Figure 7 shows the resultant
trends in this allocation, with the left panel representing the changes in labor between
agriculture and the total ‘lagging’ sector, composed of manufacturing and non-tradables
combined, and the right panel showing how the labor supply adjusts in the manufacturing
and non-tradable sectors specifically. As can be seen, although the total lagging sector
21
labor does not change too much, labor moves unambiguously out of the manufacturing
sector and into the non-tradable sector.
5.b.2 Model simulation with changing land area as well as a variable labor force
Figure 8 shows the results from allowing labor force as well as land area to change7.
Now, due to the steady increase in labor supply (the net immigration rate was
approximately 0.5% per year (Urquhart, 1986)), output eventually increases, but both
wages and sectoral output remain level for most of the simulation, as the increasing
amount of labor available puts downward pressure on wages, and the effects of labor
shifting between the different sectors on the trends in output are dampened. However,
the effect of the boom on the price of non-tradables as well as the overall trend in GDP
are more similar to the actual data for the Canadian economy presented in Figures 1 and
3, and support the fairly intuitive notion that changes in the stock of available labor may
have made important contributions to the output and price dynamics in Canada in the
period under consideration. Finally, the graphs in the bottom panels of Figure 8 that
show the changes in the labor allocation between the sectors have some similarity with
the data presented in Tables 2 and 3, with a decrease in the growth rate in the agricultural
labor force actually observed around 1901. Although this is very circumstantial and there
are many other reasons possible for such a change, it could also be interpreted as some
friction in the adjustment of the labor force between the agricultural and
manufacturing/non-tradable sectors that are represented both in the theoretical and
simulation model described here.
5. b. 3. Model sensitivity analysis of different degrees of tradability
7
Other changes between the baseline model and the model in section 5.b.2 include pressure from increases
in demand for manufacturing output brought on by an increase in capital to reduce labor in non-tradables.
22
In section 4, the possibility that trends in wages, output and prices observed in Canada
between around 1900 and 1913 were consistent with the presence of a protective tariff,
was presented, as the output in the non-tradable sector was observed to increase rather
than decrease over this time period. Figure 8 goes some way to further supporting this
idea and shows the response of key variables when subjected to a range of elasticities that
correspond to the impact of real GDP on manufacturing sector labor demand. Recall that
in the non-tradable sector, labor demand will increase as a result of increases in real GDP
due to the spending effect.
A similar effect may be assumed for industries in the
manufacturing sector that may have been more closely protected from import competition
by the presence of a tariff, with increases in real GDP brought about by the boom in
agriculture leading to increases in the demand for labor in those industries. To test the
response of the model, the ‘real GDP elasticity of demand for labor in manufacturing’
was varied between a value of 0, which indicates no additional ‘spending effect’ on the
economy, at 10 which may represent a high level of response8,9. The sensitivity analysis
is compared to the ‘baseline’ model, shown by the red line (labeled ‘Corden Neary’ on
the graphs).
The results of the sensitivity analysis are tentative but suggestive. The wage rate is
highly sensitive, both numerically and behaviorally, to the elasticity parameter, indicating
possible model misspecification, however wage increase is more steep and rapid with the
most protected manufacturing sector possible in the model (represented by the upper
contour of the colored distribution). As well, manufacturing sector output grows with
tariff protection rather than eventually falling as in the unprotected case (while still lying
8
The model is highly sensitive to the effects of real appreciation and tests of elasticities greater than 10
resulted in model errors.
9
The sensitivity analysis was conducted using Monte Carlo simulations, with 200 repetitions.
23
above the level suggested in the Corden Neary model). This more closely matches the
observed trends in manufacturing sector output at the turn of the 20th century.
Interestingly, agricultural output rises farther and falls less under a protected
manufacturing sector than would otherwise be the case, although again the behavioral
sensitivity shown between the upper and lower contours of the distribution is cause for
caution in further interpretation. However, the protected manufacturing sector distributes
labor more evenly throughout the economy, possibly leading to greater overall output
(due to the different productivity levels and prices) and a smaller loss from the
agricultural sector than in the unprotected case, which may explain the trends observed
for agriculture. Finally, non-tradable prices rise higher in the protected case rather than
falling in the unprotected case. As this more closely matches the Canadian experience
(see Figure 3), it also suggests that the tariff may have played an important role not only
in the manufacturing sector, but in all other parts of the economy as well.
6. Conclusion
The Canadian economy experienced rapid growth in almost all sectors between the turn
of the 20th century and WWI. Although some models of structural adjustment predict
that booms in certain sectors may lead to negative effects on other areas of the economy,
under some assumptions on factor mobility and intensity, these models may also be
useful in examining the Canadian economy, which did not experience a marked decline
in its non-booming sectors. The Dutch Disease model of structural adjustment is one
such tool.
If some sectors of Canadian manufacturing are assumed to have been
effectively protected via tariffs, then the observed trends in agricultural and
manufacturing output along with the ratio of non-tradable to tradable goods prices and
24
real wages seem to fit with a picture of primarily mobile labor between different sectors
of the economy combined with some protection from international competition. Other
modifications of the Dutch Disease model that allow for simultaneous increases in output
in multiple tradable sectors do not seem to be supported by the data available. As well, a
simple system dynamics model of the three production sectors in question further
supports the idea that a tariff protecting the manufacturing sector may also partly explain
the upward trends in both manufacturing and agriculture during this period, even under
conditions where labor and land inputs to production are changing over time.
These results may have implications for current trade policy, in that the observed benefits
of a leading export sector cannot be simply explained and the impact of booming export
sector will only be complimentary to other sectors under certain conditions (in the case of
Canada, it appears that these conditions were tariff protection and non-mobility of most
factors of production except labor). Understanding the medium run adjustment of these
sectors should help to create better trade policy, which may have been focused
historically on the long run picture.
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25
Annis, C. A.
(1936).
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Chambers, E. J. & Gordon, D. F. (1966). Primary products and economic growth: An
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Dick, T. J. O. & Floyd, J. E. (1992). Canada and the gold standard: balance of
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28
Table 1 Real Agriculture, Manufacturing and Total GNP, Selected Years, ($000)
(1900=100)
Year
1871
1881
1891
1896
1901
1911
1913
Agriculture
111,184
175,912
170,881
168,375
246,703
348,753
388,359
Manufacturing
80,421
120,651
172,503
156,859
206,353
418,651
444,750
Total GNP
345,454
529,788
666,670
649,313
996,284
1,849,412
2,138,683
Source: Altman (1992), Tables 1 & 2. Altman’s variant A GNP estimates are used for column (3). The
components of the agriculture sector include dairy products, other animal products, wheat, other field crops
and other outputs. The components of manufacturing are food & beverages, tobacco & products, rubber
products, leather products, textile products, clothing, wood products, paper, printing & publishing, iron &
steel products, transportation equipment, non-ferrous metal products, electrical apparatus & supplies, nonmetallic mineral products, petroleum & coal products, chemical products and other miscellaneous
industries.
29
Figure 1. Real Agricultural and Manufacturing Output, 1871-1913
500,000
450,000
400,000
350,000
$ (x1,000)
300,000
Agriculture
Manufacturing
250,000
200,000
150,000
100,000
50,000
0
1865
1870
1875
1880
1885
1890
1895
1900
1905
1910
1915
1920
Year
Figure 2. Tradable, Lagging and Non-tradable Labor Demand Curves
LNT’
Wage
LT’
LNT
LL
LT
G
w
B
w’
w
A
ONT
M
M’
M’’
OT
Source: Corden & Neary (1982), Figure 1.
30
Table 2. Employment and Employment in Agriculture, 1871-1911 (thousands of persons).
Year
1871
1881
1891
1901
1911
Total Gainfully
Occupied
Total Engaged in
Agriculture
1130
1378
1606
1783
2724
579
667
744
717
958
Proportion
Engaged in
Agriculture
Annualized labor
growth rates in
agriculture
0.51
0.48
0.46
0.40
0.35
1.4
1.1
-0.4
2.9
Source:Urquhart (1986), Table 2.7.
Table 3. Employment in Manufacturing, 1870-1910 (thousands of persons)
Year
1870
1880
1890
1900
1910
Total Manufacturing Employment
182
248
353
414
500
Annualized labor growth rates in
manufacturing
3.1
3.6
1.6
1.9
Source:Altman (1987), Table 7, (in the footnote). Altman’s Urquhart adjusted figures are used for column
(2).
31
Figure 3. Price Series - Canada 1870-1913
150
140
130
Price Index
120
Non-tradables to Tradables Ratio
110
Overall Prices
100
90
80
70
1865
1870
1875
1880
1885
1890
1895
1900
1905
1910
1915
1920
Year
Source: Dick & Floyd (1992), Table B. 2.
32
Table 4. Tariff Rates in Canada, selected sectors, 1879-1913
Sector
Wheat
Meat
pre-1879
none
--
1879
$0.15/bushel
--
1887
$0.15/bushel
--
1894
$0.12/bushel
--
1907-1913
$0.12/bushel
$0.02
$0.03/lb.
-$1.08/100 lb.
Butter
Sugar
(refined)
Coal
$0.04/lb.
25%
$0.04/lb
35%
---
---
none
$0.50/ton
--
--
Agr.
implements
Pig iron
Slabs,
blooms,
loops
or
billets
Stoves and
castings
Iron
wire
nails
Bolts, rivets,
nuts
Cotton (grey
or
unbleached)
Wool
(blankets
etc.)
Clothing
(wool)
Boots
and
shoes
All
other
goods
not
otherwise
specified
17.5%
25%
20-35%
20%-25%
$0.00
$0.53/ton
17.5%-20%
none
5%
$2.00/ton
12.5%
$4.00/ton
$9.00/ton
27.5%
$5.00/ton
$2.50/ton
$2.50/ton
17.5%
25%
30%
27.5%
$7.00/ton
--
30%
30%
27.5%
30%
--
30%
30%
27.5%
30%
17.5%
$0.01/sq. yd 22%-30%
and 15%
22%-30%
25%-32.5%
17.5%
$0.075/lb
and 20%
20%-27.5%
20%-30%
30%-35%
17.5%
25%
25%
30%
35%
17.5%
25%
--
--
30%
17.5%
20%
20%
20%
--
Source: Annis (1936). Canada instituted a preferential tariff in 1907, with an lower rate for British imports
than for imports from other countries. The higher, general tariff is listed in column (5) as Canada imported
most of their goods from the U.S. at this time. The symbol ‘—‘ means data was not available.
33
Table 5. C. P. R. Real (hourly) Wage Rates for different skill levels, 1901-1913 (1913=100)
Year
1901
1913
Machinists
labor)
71.5
100.0
(Skilled Helpers
labor)
79.7
100.0
(Semi-skilled Laborers
labor)
86.4
100.0
(Unskilled
Source: Mackinnon (1996), Table 5.
Table 6. GNP in selected non-tradable sectors, 1870-1910
Sector
Construction
Transportation
Electric Light and Power
Communications
Residential Rent
TOTAL
Non-tradable Prices (1890=100)
Real Non-tradable output
Real Rent
1871
1880
21000
20400
22609
25001
----21959
27275
65568
72676
118
111
55566.1 65473.9
18609.32 24572.1
Year
1890
1900
1910
30100
32500
158500
40460
62083
153591
936
1700
9503
745
1818
10401
37493
60453
132764
109734
158554
464759
100
99
135
109734
160156
344266
37493 61063.6 98343.7
Source: Urquhart (1986), Table 2.1. Non-tradables prices are from Dick & Floyd (1992), Table B.2.
34
Figure 4. Real Non-tradable Output
500000
450000
Real Output (x $1000) (1890=100)
400000
350000
300000
250000
Real Nontradable
Output
Real rent
.
200000
150000
100000
50000
0
1865
1870
1875
1880
1885
1890
1895
1900
1905
1910
1915
1920
Year
Table 7. Relative Capital Intensities and price and wage movements
kL > kNT
kL < kNT
kL > k B
pNT ↑, w ↑
pNT ↓, w ↑
kL < k B
pNT ↓, w ↓
pNT ↑, w ↓
35
Figure 5. Causal Relationships between the three economic sectors, wages and prices
Increase in
Productivity due
to technology
+
Supply of
Manufacturing
Sector Labor
Manufacturing
Sector Output
-
+
Demand for
Agricultural Sector
Labor
+
World Price
Increase for
Agricultural
Output
+
Resource Effect
Agricultural
Output
+
+
Real GDP
+
Real Wages
+
Demand for
Non Tradable
Output
+
+
Spending Effect
+
Non Tradable
Sector Output
+
Non Tradables Prices
Real Appreciation
Demand for Non
Tradable Sector Labor
+
36
Figure 6. Response to increased farmland areas – various indicators. (farm land area
growth rate=8% per year).
Wages - Agriculture (Booming) vs. Manufacturing+ Non Tradable Sector (Lagging)
Real Output by Sector
4
20 M
3.25
15 M
2.5
10 M
1.75
5M
1
0
0
2
4
6
8
10
12
14
16
Time (year)
18
20
22
24
26
28
Total Canadian Agricultural Output : Corden Neary
Total Canadian MF Output : Corden Neary
Total Canadian NT Output : Corden Neary
30
tonnes
tonnes
tonnes
0
2
4
6
8
10
12
14
16
Time (year)
18
20
22
24
26
Booming Sector Wages : Corden Neary
Lagging Sector Wages : Corden Neary
28
30
dollars/hour
dollars/hour
Relative Non Tradable to Tradable Price Levels (1890=100)
Nominal and Real GDP (1890=100)
200
600 M
170
500 M
400 M
140
300 M
110
200 M
80
0
0
2
4
6
Non Tradable to Tradable Price Index : Corden Neary
8
10
12
14
16
Time (year)
18
20
22
24
26
28
2
30
Dmnl
4
6
8
10
12
14
16
Time (year)
18
20
22
Real GDP : Corden Neary
Nominal GDP : Corden Neary
24
26
28
30
dollars
dollars
37
Figure 7. Labor supply response to increasing farmland areas (farmland area growth
rate=8% per year).
Agriculture (Booming) and Manufacturing+Non-Tradable Sector (Lagging) Labor Supply
Lagging Sector Labor Distribution
2M
600,000
1.5 M
450,000
1M
300,000
500,000
150,000
0
0
0
2
4
6
Booming Sector Labor Supply : Corden Neary
Lagging Sector Labor Supply : Corden Neary
8
10
12
14
16
Time (year)
18
20
22
24
26
28
30
people
people
0
2
4
6
8
10
12
14
16
Time (year)
18
20
22
Manufacturing Sector Labor Supply : Corden Neary
Non Tradable Sector Labor Supply : Corden Neary
24
26
28
30
people
people
38
Figure 8. Response to increased farmland areas with variable labor (farmland area growth
rate=8% per year, immigration rate=2% per year, emigration rate=1.5% per year).
Wages - Agriculture (Booming) vs. Manufacturing+ Non Tradable Sector (Lagging)
Real Output by Sector
8
60 M
6
45 M
4
30 M
2
15 M
0
0
0
2
4
6
8
10
12
14
16
Time (year)
18
20
22
24
26
28
Total Canadian Agricultural Output : FullModel
Total Canadian MF Output : FullModel
Total Canadian NT Output : FullModel
30
tonnes
tonnes
tonnes
0
2
4
6
8
10
12
14
16
Time (year)
18
20
22
24
26
Booming Sector Wages : FullModel
Lagging Sector Wages : FullModel
28
30
dollars/hour
dollars/hour
Relative Non Tradable to Tradable Price Levels (1890=100)
Nominal and Real GDP (1890=100)
200
2B
170
1.5 B
1B
140
500 M
110
0
80
0
0
2
4
6
8
10
12
14
16
Time (year)
18
20
22
24
26
28
Non Tradable to Tradable Price Index : FullModel
2
4
6
8
10
12
30
Dmnl
14
16
Time (year)
18
20
22
24
26
28
Real GDP : FullModel
Nominal GDP : FullModel
30
dollars
dollars
Agriculture (Booming) and Manufacturing+Non-Tradable Sector (Lagging) Labor Supply
Lagging Sector Labor Distribution
2M
2M
1.5 M
1.5 M
1M
1M
500,000
500,000
0
0
0
2
4
Booming Sector Labor Supply : FullModel
Lagging Sector Labor Supply : FullModel
6
8
10
12
14
16
Time (year)
18
20
22
24
26
28
30
people
people
0
2
4
6
8
10
12
14
16
Time (year)
18
20
22
Manufacturing Sector Labor Supply : FullModel
Non Tradable Sector Labor Supply : FullModel
24
26
28
30
people
people
39
Figure 9. Sensitivity analysis of wages, output and non-tradable prices to the degree of
manufacturing sector tradability
Parameter and Range Tested: Elasticity of manufacturing sector labor demand to real GDP, 0-10.
Note that an elasticity of 0 represents complete tradability.
ElasticitySensitivity
Corden Neary
50%
75%
95%
Booming Sector Wages
6
100%
4.5
Wages
3
1.5
0
0
ElasticitySensitivity
Corden Neary
50%
75%
95%
Total Canadian MF Output
20 M
7.5
15
Time (year)
22.5
30
7.5
15
Time (year)
22.5
30
7.5
15
Time (year)
22.5
30
100%
15 M
Manufacturing
Output
10 M
5M
0
0
ElasticitySensitivity
Corden Neary
50%
75%
95%
100%
Total Canadian Agricultural Output
20 M
15 M
Agricultural
Output
10 M
5M
0
0
40
ElasticitySensitivity
Corden Neary
50%
75%
95%
100%
Non Tradable to Tradable Price Index
200
170
Non Tradable
Price Index
140
110
80
0
7.5
15
Time (year)
22.5
30
41
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