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DRAFT - NOT FOR CITATION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.

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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

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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

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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.

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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

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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 non-

traded 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

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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 non-

traded goods relative to traded goods increases and the labor demand curve for the non-

traded 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, non-

tradables 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

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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

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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 1870-

1913. 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

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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 non-

tradable 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 non-

tradable 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 de-

industrialization 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

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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 de-

industrialization 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 non-

tradable 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

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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.

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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

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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 non-

agriculture 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

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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 non-

tradable 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.

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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 non-

tradable 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

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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 non-

tradables 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.

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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. 6 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.

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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

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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

21

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 non-

tradable 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

22

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.

23

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.

24

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

25

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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29

Table 1 Real Agriculture, Manufacturing and Total GNP, Selected Years, ($000) (1900=100) Year Agriculture Manufacturing Total GNP 1871 111,184 80,421 345,454 1881 175,912 120,651 529,788 1891 170,881 172,503 666,670 1896 168,375 156,859 649,313 1901 246,703 206,353 996,284 1911 348,753 418,651 1,849,412 1913 388,359 444,750 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, non-metallic mineral products, petroleum & coal products, chemical products and other miscellaneous industries.

30

Figure 2. Tradable, Lagging and Non-tradable Labor Demand Curves

Source: Corden & Neary (1982), Figure 1.

w

B

Figure 1. Real Agricultural and Manufacturing Output, 1871-1913

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

1865 1870 1875 1880 1885 1890 1895 1900 1905 1910 1915 1920

Year

$ (

x1

,00

0)

Agriculture

Manufacturing

LL

LT’

LT

G

A

w’

w

ONT OT

Wage

LNT

LNT’

M’ M M’’

31

Table 2. Employment and Employment in Agriculture, 1871-1911 (thousands of persons).

Year Total Gainfully Occupied

Total Engaged in Agriculture

Proportion Engaged in Agriculture

Annualized labor growth rates in agriculture

1871 1130 579 0.51 1881 1378 667 0.48 1.4 1891 1606 744 0.46 1.1 1901 1783 717 0.40 -0.4 1911 2724 958 0.35 2.9

Source:Urquhart (1986), Table 2.7.

Table 3. Employment in Manufacturing, 1870-1910 (thousands of persons)

Year Total Manufacturing Employment Annualized labor growth rates in manufacturing

1870 182 1880 248 3.1 1890 353 3.6 1900 414 1.6 1910 500 1.9

Source:Altman (1987), Table 7, (in the footnote). Altman’s Urquhart adjusted figures are used for column (2).

32

Source: Dick & Floyd (1992), Table B. 2.

Figure 3. Price Series - Canada 1870-1913

70

80

90

100

110

120

130

140

150

1865 1870 1875 1880 1885 1890 1895 1900 1905 1910 1915 1920

Year

Pri

ce In

dex

Non-tradables to Tradables Ratio

Overall Prices

33

Table 4. Tariff Rates in Canada, selected sectors, 1879-1913

Sector pre-1879 1879 1887 1894 1907-1913 Wheat none $0.15/bushel $0.15/bushel $0.12/bushel $0.12/bushel Meat -- -- -- -- $0.02 -

$0.03/lb. Butter $0.04/lb. $0.04/lb -- -- -- Sugar (refined)

25% 35% -- -- $1.08/100 lb.

Coal none $0.50/ton -- -- $0.00 - $0.53/ton

Agr. implements

17.5% 25% 20-35% 20%-25% 17.5%-20%

Pig iron none $2.00/ton $4.00/ton 27.5% $2.50/ton Slabs, blooms, loops or billets

5% 12.5% $9.00/ton

$5.00/ton $2.50/ton

Stoves and castings

17.5% 25% 30% 27.5% $7.00/ton

Iron wire nails

-- 30% 30% 27.5% 30%

Bolts, rivets, nuts

-- 30% 30% 27.5% 30%

Cotton (grey or unbleached)

17.5% $0.01/sq. yd and 15%

22%-30% 22%-30% 25%-32.5%

Wool (blankets etc.)

17.5% $0.075/lb and 20%

20%-27.5% 20%-30% 30%-35%

Clothing (wool)

17.5% 25% 25% 30% 35%

Boots and shoes

17.5% 25% -- -- 30%

All other goods not otherwise specified

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.

34

Table 5. C. P. R. Real (hourly) Wage Rates for different skill levels, 1901-1913 (1913=100)

Year Machinists (Skilled labor)

Helpers (Semi-skilled labor)

Laborers (Unskilled labor)

1901 71.5 79.7 86.4 1913 100.0 100.0 100.0 Source: Mackinnon (1996), Table 5.

Table 6. GNP in selected non-tradable sectors, 1870-1910

Year Sector 1871 1880 1890 1900 1910 Construction 21000 20400 30100 32500 158500 Transportation 22609 25001 40460 62083 153591 Electric Light and Power -- -- 936 1700 9503 Communications -- -- 745 1818 10401 Residential Rent 21959 27275 37493 60453 132764 TOTAL 65568 72676 109734 158554 464759 Non-tradable Prices (1890=100) 118 111 100 99 135 Real Non-tradable output 55566.1 65473.9 109734 160156 344266 Real Rent 18609.32 24572.1 37493 61063.6 98343.7 Source: Urquhart (1986), Table 2.1. Non-tradables prices are from Dick & Floyd (1992), Table B.2.

35

Table 7. Relative Capital Intensities and price and wage movements

kL > kNT kL < kNT

kL > kB pNT ↑, w ↑ pNT ↓, w ↑

kL < kB pNT ↓, w ↓ pNT ↑, w ↓

Figure 4. Real Non-tradable Output

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

500000

1865 1870 1875 1880 1885 1890 1895 1900 1905 1910 1915 1920

Year

Real

Ou

tpu

t (x

$1000)

(1890=

100)

Real Non-tradable

OutputReal rent

.

36

Figure 5. Causal Relationships between the three economic sectors, wages and prices

AgriculturalOutput

Non TradableSector Output

Supply ofManufacturingSector Labor

ManufacturingSector Output

World PriceIncrease forAgricultural

Output

Increase inProductivity due

to technology

Real Wages

Non Tradables Prices

Real GDP

Demand forNon Tradable

Output

+

+

+

-

+

+ +

Real Appreciation

Demand for NonTradable Sector Labor

+

+

+

+

Resource Effect

Spending Effect

Demand forAgricultural Sector

Labor

+

+

+

37

Figure 6. Response to increased farmland areas – various indicators. (farm land area growth rate=8% per year).

Real Output by Sector

20 M

15 M

10 M

5 M

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Total Canadian Agricultural Output : Corden Neary tonnes

Total Canadian MF Output : Corden Neary tonnes

Total Canadian NT Output : Corden Neary tonnes

Wages - Agriculture (Booming) vs. Manufacturing+ Non Tradable Sector (Lagging)

4

3.25

2.5

1.75

1

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Booming Sector Wages : Corden Neary dollars/hour

Lagging Sector Wages : Corden Neary dollars/hour

Relative Non Tradable to Tradable Price Levels (1890=100)

200

170

140

110

80

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Non Tradable to Tradable Price Index : Corden Neary Dmnl

Nominal and Real GDP (1890=100)

600 M

500 M

400 M

300 M

200 M

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Real GDP : Corden Neary dollars

Nominal GDP : Corden Neary dollars

38

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

2 M

1.5 M

1 M

500,000

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Booming Sector Labor Supply : Corden Neary people

Lagging Sector Labor Supply : Corden Neary people

Lagging Sector Labor Distribution

600,000

450,000

300,000

150,000

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Manufacturing Sector Labor Supply : Corden Neary people

Non Tradable Sector Labor Supply : Corden Neary people

39

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).

Real Output by Sector

60 M

45 M

30 M

15 M

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Total Canadian Agricultural Output : FullModel tonnes

Total Canadian MF Output : FullModel tonnes

Total Canadian NT Output : FullModel tonnes

Wages - Agriculture (Booming) vs. Manufacturing+ Non Tradable Sector (Lagging)

8

6

4

2

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Booming Sector Wages : FullModel dollars/hour

Lagging Sector Wages : FullModel dollars/hour

Relative Non Tradable to Tradable Price Levels (1890=100)

200

170

140

110

80

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Non Tradable to Tradable Price Index : FullModel Dmnl

Nominal and Real GDP (1890=100)

2 B

1.5 B

1 B

500 M

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Real GDP : FullModel dollars

Nominal GDP : FullModel dollars Agriculture (Booming) and Manufacturing+Non-Tradable Sector (Lagging) Labor Supply

2 M

1.5 M

1 M

500,000

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Booming Sector Labor Supply : FullModel people

Lagging Sector Labor Supply : FullModel people

Lagging Sector Labor Distribution

2 M

1.5 M

1 M

500,000

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Time (year)

Manufacturing Sector Labor Supply : FullModel people

Non Tradable Sector Labor Supply : FullModel people

40

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.

Wages

ElasticitySensitivity

Corden Neary

50% 75% 95% 100%

Booming Sector Wages

6

4.5

3

1.5

00 7.5 15 22.5 30

Time (year)

Manufacturing Output

ElasticitySensitivity

Corden Neary

50% 75% 95% 100%

Total Canadian MF Output

20 M

15 M

10 M

5 M

00 7.5 15 22.5 30

Time (year)

Agricultural Output

ElasticitySensitivity

Corden Neary

50% 75% 95% 100%

Total Canadian Agricultural Output

20 M

15 M

10 M

5 M

00 7.5 15 22.5 30

Time (year)

41

Non Tradable Price Index

ElasticitySensitivity

Corden Neary

50% 75% 95% 100%

Non Tradable to Tradable Price Index

200

170

140

110

800 7.5 15 22.5 30

Time (year)