Download The Big Push: what does it mean, and does it make sense for

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PED401. Applications and Cases in International Development
Teaching Notes 1
The Big Push: what does it mean,
and does it make sense for Ethiopia?
The idea of the Big Push is one of the earliest in development economics, coined by
Rosenstein-Rodan over 60 years ago in the context of a classic work on “the problem of
industrialization of eastern and south-eastern Europe”. The core argument is that
coordination problems, in the context of increasing returns, create the possibility of
multiple equilibria. A poor country can be caught in a low-equilibrium “poverty trap”,
government intervention can potentially solve the coordination problem, and “push” the
economic into the better equilibrium allowing a “take-off” into sustained growth.
The Big Push idea has returned to the center of development policy in the recent past.
William Easterly (2006) described 2005 as the Year of the Big Push. It has done so in
particular in the context of debates over Africa: the compelling normative case to
transform development possibilities of Africans, has been associated with renewed
emphasis on the positive case for a Big Push. This has been linked to the case for a major
expansion in aid, notably in the work of the Commission for Africa and the Millennium
Development Goals; Jeffrey Sachs has been a vigorous exponent of this linkage.
This case concerns the analytics of the Big Push, the evidence and its applicability to a
poor African country. It bridges issues of growth (from macro) and general equilibrium
(from micro). There are three parts. The first outlines the analytics: it uses the prism of
the Solow growth model to look at three possible cases for multiple equilibria, and
focuses on the coordination problem as one account. The second looks at approaches to
evidence from cross-country patterns, and from country experiences. The third poses the
question of Big Push ideas are applicable to Ethiopia.
Analytics of the Big Push
Poverty traps try to explain, within a growth model, why some countries exhibit stagnant
growth at low levels of income per capita while others race ahead. In the 1940s, scholars
conjectured that underdeveloped countries might be caught in a “poverty trap”, a vicious
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These notes were prepared by Alexander Culiuc and Michael Walton and are solely for teaching purposes.
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circle of low savings and unattractive investment opportunities. How can this be
explained?
We’ll answer this question within the framework of the Solow model, using three
“classical” sources of poverty traps discussed by Easterly (2006): low savings at low
income levels, non-convexities in the production function, and a Malthusian trap. All
three involve multiple equilibria, driven, respectively, by the shape of the savings
function, the production function and the depreciation schedule.
Low savings at very low incomes
In this story, poverty traps are due to low saving rates among poor people, so that
physical capital accumulation fails to keep up with depreciation and population growth.
Similar stories could apply to human capital, but we lump the two forms of capital into
one for simplicity. This may be due to a subsistence constraint—below a certain level of
income, people have to consume almost all of their income simply to stay alive. The
savings of the poor in this case are just big enough to make sure the same subsistence
constraint is met in future periods also. 2 So the Solow model breaks in this model at the
low end of capital.
Output cannot go below some level that covers both subsistence consumption cmin +
“subsistence” savings smin, i.e. f(0) is not defined. Instead, we have f(kmin), where kmin is
the amount of capital required to maintain the household at this subsistence level of
consumption. As output increases, this constraint will be relaxed, and we are back in the
standard Solow world, where savings represent a constant share of output. See Figure 1.
As shown in the graph, there are three steady state equilibria: k*low, k*mid and k*high. Of
these, only the extreme ones are stable equilibria. However, the k*mid defines the critical
threshold. If the economy is located below this point, it will converge to the low capitallow-output equilibrium k*low. If it is above this threshold – it will converge to the “good”
equilibrium k*high.
2
PED-101 inspired example: an Indian farmer does not consume all of his crop, a small portion of output
being “invested” in (fed to) the bullock, to ensure that the animal can work the land next year.
3
Figure 1. A poverty trap in an economy with a subsistence constraint
Poverty trap
Output
Savings
f(k)
A world w/o poverty
(n+δ)k
Savings
f(kmin)
cmin
smin
kmin
k*low
k*mid
k*high
k
In this context, aid that is fully invested in new capital will raise the savings curve and
will temporarily remove the low equilibrium, as shown in Figure 2: the depreciation line
(n+δ)k no longer touches the savings schedule at the lower end of the k axis. To escape
the poverty trap, what is needed is to supply sufficient aid for long enough until the
economy passes the k*mid threshold, after which aid can be discontinued.
Figure 2. The effect of aid on savings
Poverty trap
Output
Savings
f(k)
A world w/o poverty
Savings + Aid
(n+δ)k
Savings
f(kmin)
Aid
k*mid
k*high
k
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Production function non-convexities
The same general result can be achieved by assuming a different shape of the production
function. The key is increasing returns to scale, at least for a range of capital-labor ratios.
Let us revert to the assumption of a constant savings rate. However, assume that the
production function does not satisfy the Inada conditions, but instead has the following
properties:
f (0) = 0
⎧< 0 0 < k < k a
⎪
f ' ' ( k ) = ⎨> 0 k a < k < k b
⎪< 0
k > kb
⎩
f '> 0
The conditions imposed on the 2nd derivative is what makes this function non-convex.3 In
this case the Solow graph will look as follows (inflexion points ka and kb are omitted):
Figure 3. Poverty trap
Poverty trap
Savings
f(k)
A world w/o poverty
(n+δ)k
Savings = s .f(k)
k*min
k*mid
k*high
k
Again, we obtain two stable equilibria, k*low and k*high, and the non-stable “threshold”
equilibrium k*mid. Foreign aid has the same impact on the economy as in the “poor save
too little” story: it will temporarily raise the savings schedule so that the economy can
pass the threshold. The Murphy-Shleifer-Vishny account (discussed below) provides the
underpinnings for increasing returns.
3
The terminology is somewhat confusing in this case. When we talk about a non-convex production
function, we actually mean that it has convex regions where f''>0. A well-behaved production function is
concave.
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A basic version of the Malthusian trap
The third obvious modification to the Solow model that can create multiple equilibria is
the assumption of an abnormal depreciation schedule. Instead of assuming a constant
population growth, we make n a function of output. For low levels of income, the system
behaves like a Malthusian economy, in which all increases in productivity are offset by
increases in population. Only when returns to human capital become high enough do
people shift from making more babies to investing more in their children, which results in
the escape from the poverty trap.
Figure 4 Malthusian poverty trap in the Solow model
Output
Savings
Poverty trap
A world w/o poverty
y=f(k)
(n(y)+δ)k
s.f(k)
k*low
k*mid
k*high
k
We will return to this type of poverty trap and its implications in a future session.
The Big Push in a general equilibrium setting
When discussing the poverty trap due to a non-convex production function, we simply
assume that such a production function can exist. Murphy, Shleifer, Vishny (1989)
develop several models that explain why such non-convexities arise in the real world.
The basic idea of their approach is that demand for a manufacturing activity depends on
whether other manufacturing activities are already in place. These demand spillovers can
result in lack of industrialization in the absence of investment coordination (a “Big
Push”). It requires increasing returns to scale interacting with other features of the
economy, in particular pecuniary externalities between firms.
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Demand spillovers and a factory wage premium
The economy produces a continuum of goods over the unit interval. Each good is
produced by a firm. The only factor of production is labor, with L being the
representative worker’s endowment. Any good can be produced either with a traditional
or a modern technology, with n being the fraction of firms using modern technology.
Firms using traditional technology transform one unit of labor into one unit of output
(CRS). If we normalize the wage (price of a unit of labor) to 1, we obtain that the price of
any good is also 1. The wage is spent by the worker/consumer equally among all the
goods, with y being the per-good spending. Since the total number of goods is 1, the
output of each good in a purely traditional economy (n=0) is:
yn=0= L
“Modernization” makes the firm more productive, i.e. one unit of output requires only
1/α units of labor (α>1). However, modernization entails two costs:
Higher wages (1 + ν), where ν is the factory premium. 4
„ A sunk cost of F units of labor in order to upgrade the technology. Notice that the
labor used in the modernization of the firm is of the productive type, but it also has
to be paid the high wage, so the cost of the upgrade is F(1+ ν)
„
Total output if all firms modernize is:
yn=1= α(L – F)
Modernization is welfare improving if α(L – F) > L.
The presence of a sunk cost leads to increasing returns to scale, since average cost will be
decreasing as output increases (the sunk cost is spread among more units of output).
Clearly, if 1+ν>α then modernization will not happen regardless of the sunk cost – the
marginal cost under new technology will be higher than under the traditional one, so we
only consider 1+ν<α. The modernized firm will sell its goods at the same price as the
traditional ones 5 , which means that it charges a per-unit markup (1–1/α). However, the
existence of a markup does not make modernization necessarily a profitable investment
from the point of view of the firm, since we need to subtract the upgrade cost. The profit
from modernization is:
⎛
⎝
π = ⎜1 −
1 +ν ⎞
⎟ y − F (1 + ν )
α ⎠
If no other firms have yet modernized, the profit of a “pioneer” from modernization is:
4
Authors argue that modern firms (factories) have to pay higher wages, whether to offset harder working
and living conditions in the city (pollution, long commute, etc.), or on efficiency wage grounds. The
urban-rural wage gap is empirically robust, even when accounting for differences in productivity.
5
This stems from the particular form of the utility function assumed by the authors.
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⎛
⎝
π n =0 = ⎜1 −
1 +ν ⎞
⎟ L − F (1 + ν )
α ⎠
If all other firms have already modernized, the profit of a “late-comer” from
modernization is:
⎛
⎝
π n=1 = ⎜1 −
1 +ν ⎞
⎟α (L − F ) − F (1 + ν )
α ⎠
So under our assumptions it may be possible that π n=0 < 0 and π n=0 > 0 . In such a
situation, there must be a threshold fraction of firms n* that need to modernize before
modernization becomes profitable for subsequent firm.
Figure 5. Multiple equilibria in the presence of a factory wage premium
The intuition: if nobody has yet modernized, total income in the economy is low, so the
first firm to modernize might not reach the scale where average cost is low enough
(remember average cost goes down with output) and its profits will be negative. The
“late-comer” benefits from the fact that everyone has already modernized, so that the
income in the economy is high enough to drive average costs below unit price. However,
this n* cannot be reached, since no firm will want to be the first to modernize. And the
market economy offers no mechanism for firms to coordinate their efforts. Therefore,
there is a role for the state to step in and make all (or at least n*) firms modernize at the
same time.
Infrastructure investment
Let’s now assume that the wage in the modern sector is the same as in the traditional one
(so ν=0) and explore a different source of coordination failures. Modern
technologies/activities require an investment in infrastructure (“railroad”), with sunk cost
R and zero maintenance costs. Now industrialization is welfare-enhancing if:
α(L – F – R) > L
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Since the firm operating the infrastructure is a monopolist, it will be able to extract from
modern firms a share λ of the profits from modernization by charging a non-zero price for
using the infrastructure. Since ν=0, profits from modernization are now:
⎛
⎝
π = ⎜1 −
1⎞
1⎞
⎛
⎟ y − F = ⎜1 − ⎟α (L − F − R ) − F
α⎠
⎝ α⎠
Profits from undertaking the infrastructure investment depend on whether goods are
produced with modern technology or not:
Π n =0 = − R
1⎞
⎛
Π n=1 = λ ⎜1 − ⎟α (L − F − R ) − F
⎝ α⎠
If λ is sufficiently high, we have multiple equilibria (industrialization and noindustrialization).
Figure 6. Profits of the infrastructure owner as a function of the modernization level
of the economy
Unless the investor is guaranteed at least n* modern activities, the infrastructure
investment will not take place. And unless the infrastructure is expected to be in place, no
entrepreneurs will choose to operate with modern technology. The state can step in by
financing the infrastructure, with modernization following on its own.
Some empirical evidence
Cross-country patterns
The logical sequence stemming from the aggregate models is the following:
Poverty traps exist
„ A “big push” can move the economy into a good equilibrium
„ Aid can finance the big push
„
This is what Easterly (2006) calls the classic narrative, and he looks at evidence for this
from cross-country patterns. His findings are as follows:
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„
„
„
„
„
„
Malthusian poverty traps clearly exist, as shown by the historical experience of
Western countries, that experience long periods in which increased national income
was translated into increased population, and not rising income per capita, until the
transition to modern growth. However, escaping such traps is a prolonged process.
There is no macro-level evidence supporting low savings rate at low levels of
income.
Africa has indeed experienced near-zero growth rates since the mid-1980s, but it
was growing over the period if 1950-1985 at around 1% a year (Europe was
growing at this rate in mid-nineteen century), and such slowdowns are hard to
motivate in the framework of poverty traps.
There is less than ten cases throughout history that fit the story of a big push, in
which countries jump from near-zero to sustained, significant positive growth levels
(>1.5% a year). Growth rates in the West picked up gradually, so there was no big
push in the sense advocated by Sachs and others. Japan and Korea are the clearest
examples.
There appears to be no relationship between success stories of rapid sustained
growth and aid, although the number of cases fitting the big push story is too small
to draw any statistical conclusions on this.
There appears to be a much more robust correlation between the quality of
institutions and growth than between aid and growth. This would suggest that
development is primarily a political economy problem, not a coordination failure,
as argued by Sachs.
What would Jeff Sachs respond to all this evidence? One possible argument against
Easterly’s findings can be read off the graph in Figure 2. Notice that if aid is small, the
savings schedule will not be lifted up sufficiently to push the economy above the
depreciation line. Or, if the aid is short lived, the economy might not reach k*mid by the
time aid is discontinued and the economy rolls back to the original state. In other words,
all the aid to date was either not sufficiently large or was not sustained at high enough
levels for a sufficiently long time. But that is still inconsistent with earlier experiences of
steady growth in poor (African or other) countries.
Country narratives
Easterly’s cross-country analysis is a test of an aggregate, systematic relationship at the
country level—of the classic narrative. His rejection of this is consistent with his vision
of successful development, that has at its core a much more decentralized, experimental
approach. But he does not directly test for the specific mechanisms described in Murphy,
Shleifer and Vishny. As discussed in PED101, there is a plausible case to be made that
some of the East Asian countries did actively intervene in ways that helped solve
coordination problems across industries. (This is perhaps most compelling for Japan,
Korea and Taiwan—and Murphy, Shleifer and Vishny speculate that the Korean
experience exemplifies their models.) More broadly, a central feature of East Asian
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development has been a high priority to large-scale infrastructure development, with this
often leading, rather than, lagging, productive demand. Unfortunately, there are also
classic failures in government attempts to coordinate industrial policy or use big
infrastructure to foster development. Table 1 provides a heuristic summary.
Table 1 Coordination: stylized implications and good and bad examples
Models
Implications for
development policy
Pecuniary
“Coordinate”
externalities through Subsidize industry
demand linkages
Infrastructure and
industry profits
Finance big
infrastructure
Coordinate with
industrial or other
users
Heuristic/stylized
example
Japanese, Korean
and Taiwanese
industrial policy
Negative examples
Soviet
industrialization;
industrial policy in
Latin American and
India
Chinese
“White elephant”
infrastructure policy dams and other
(put infrastructure in major projects
place, get demand
later)
So the world seems more demanding. At a minimum there are countervailing factors to
offset the coordination gains implied by Murphy, Shleifer and Vishny. How do we
interpret this? One prism is through the nature and relative importance of market failures
versus “government failures”. By the latter we mean that governments either lack the
capacities or the incentives to undertake the coordinatory role implied by the models.
They may lack the information, or be driven by rent-seeking, corruption and clientelism
rather than the maximization of social welfare. More subtly, coordination of industrial
investment or big infrastructure depends on the credibility of the investment environment,
at macro and micro levels—if investors do not believe the government will sustain its
policies it will not invest. This is an issue we’ll discuss later in the semester.
With respect to East Asia, some scholars have sought to interpret not only what they did,
but how this related to the underlying political and institutional context. A seminal
example is the work of Peter Evans (1995). He argues that Korea indeed did have a
developmental state, that was effective in promoting industrial transformation, but that
this involved a combination of coherent internal organization, and close links to society
that he called “embedded autonomy”, that in turn had historical roots in processes of
social and political evolution. The strength, and partial independence, of the Korean and
Japanese bureaucracies is a manifestation of this. The strategic choice to make exporting
a central performance criterion was critical, but this had to be complemented by the
capacity of the state to respond to failures (as emphasized in PED101.)
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Does a Big Push make sense for Ethiopia?
I believe in a strong developmental state and developmental states do not intervene in the market in a
wanton fashion. They intervene in the market to address pervasive market failures and let the markets work
where they work well. So it is a combination of market instruments and non-market instruments to optimise
the outcome. That’s been the model lets say in Korea, and Taiwan.
...while the neo-liberal model was right in identifying the central problem in Africa as being pervasive rent
seeking on the part of the state, its solution was to remove the state from the economic equation. The neoliberal reforms did not transform the rent-seeking state into a non-rent seeking one. It has no capacity to do
it. All it did was reduce the influence of the state without changing its nature and therefore was inherently
incapable of generating the type of growth it sought.
Meles Zenawi, Prime Minister of Ethiopia, Interview with the Financial Times. 6th February,
2007.
Clearly, the Prime Minister believes in an active role for the Ethiopian state, inspired by
Korea and Taiwan. As discussed in the introductory case in the first semester, Ethiopia is
extraordinarily poor with respect to income per capita, social outcomes, human capital,
and physical capital. Figure 7 superficially looks like a poverty trap—Ethiopia’s income
has, to first order, stagnated, while other very poor countries have taken off. As the
Tables at the end of these notes indicate, Ethiopia has a very low level of
industrialization, and very low levels of manufactures in her exports.
Figure 7. Ethiopia’s income in comparative perspective
GDP Per Capita (PPP)
6000
5000
4000
3000
2000
Ethiopia
Indonesia
China
Vietnam
1000
19
7
19 5
77
19
7
19 9
81
19
8
19 3
85
19
8
19 7
8
19 9
9
19 1
93
19
9
19 5
97
19
9
20 9
01
20
03
0
There is thus a compelling ethical case for a big push—but is this intellectually coherent
and politically and administrative feasible? We should be cautious about the growth
numbers being evidence for a poverty trap—as indicated in Easterly’s analysis. But it is
highly plausible that issues of coordination are salient: that complementarities between
infrastructure and other investment matter and that inter-industry linkages will be central
to any growth process. We don’t have the information for a rigorous test of the Murphy,
Shleifer and Vishny models, and so a policy assessment and proposal would have to be
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undertaken based on incomplete information and a judgment of what kind of policy
process makes sense. In particular, even if it could be shown that the models applied,
there remains the question of government capability to undertake the interventions to
effect the coordination.
So this case is to think through the applicability of coordination issues based on what you
know about Ethiopia. These notes also summarize some of the conclusions from recent
World Bank analysis—that itself is a synthesis of a range of existing work.
Industrial policy
The World Bank’s diagnosis of constraints for private sector industrial (and agroindustrial) growth falls loosely within the growth diagnostics framework (Hausmann,
Rodrik and Velasco, 2005). With respect to the focus of this case, there are two
categories of constraint identified:
Constraints associated with general costs of doing business (e.g. land registration
costs) and determinants of expected profits, influenced by uncertainties over
government behavior.
„ Problems of constructing functioning value chains, whether for domestic or export
production.
„
The concept of a value chain is a version of inter-industry pecuniary externalities—the
profits of any firm along the chain will be a function of the level of capital (physical and
organizational) in other parts of the chain. The analysis does not assess the relative
importance of the two categories of constraint, but argues that government policy needs
to work on both fronts.
Two contrasting examples of value chains are given. The first is the case of rose
production for export. This has taken off in recent years (Table 2). It started with an
investment by a foreign producer with experience in Kenya to explore if rose production
was profitable in Ethiopia. There followed a process of “discovery”, organization, and
tackling of obstacles. Ethiopia is climatically well-suited, and has low cost labor suitable
for horticulture. However, there are number of steps in the value chain from production
to delivery in Europe—sharing of information on growing practices, internal transport,
refrigeration, shipping in air cargo. Logistics account for three-quarters of the delivered
costs of flowers. Obstacles have been partially resolved, including in land zoning and use
of cargo, and incentives provided, including tax-exempt fertilizers and pesticides, dutyfree privileges on technology and government funding of projects. Two factors
facilitated resolution. First, there was the creation of an effective private sector
organization with an unusual level or trust and cooperation—the Horticulture Association
(that set up the EthioHorticulture Share Company to negotiate with other parts of the
chain). This helped solve the collective action problem. Second, the government was
quite responsive to the demands, adapting policies and regulations to the specific
conditions of the sector.
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Table 2 A success: Ethiopia's Flower Exports (US$)
Year
2001
2002
2003
2004
2005 (August)
Flower Export
Revenue
660,038
1,212,968
2,904,000
5,050,000
12,645,000
Year-on-Year
Growth
N/A
84%
139%
74%
>150%
Source: Ethiopian Customs Authority
A contrasting example is that of leather, traditionally much larger than horticulture
(Figure 8). Here however there has been a failure to solve the organizational and
processing problems in the sector. The quality premium that Ethiopian leather used to
hold has effectively gone. A small fraction of the total slaughter is undertaken in
commercial abattoirs, there is enormous waste and damage (some 90 percent of total
production ends with a low grade), there is no system for tracing higher quality final
products back through the value chain to provide incentives for better production and
processing. Overall, neither government nor producer associations have been able to
solve the coordination problems in an area of significant potential comparative
advantage. The result has been stagnation of export revenues and of producer and agroprocessing incomes. In this case there is a much more dispersed initial producer base—
and so a larger initial collective action problem, weak producer organization, and the
government has not found interventions to solve the problems along the value chain.
Figure 8. A failure in upgrading: the value chain for leather
Abattoir
1% of total slaughter
Slaughter
10.2 million
off take/
year
(40% of
sheep
population)
Sheep
Population
25.5 million
Live Animal
Export:
0.03 million
(18% of sheep
population)
Urban Dweller
7.52-million/year
(74% of off take)
Rural Farmer
2.68-million/year
(26% of off take)
Waste & Damage
0.8 million pieces due to
quality problems and
traditional use as seat cover
(30% of raw skin from
farmer)
Waste & Damage
89.5% downgraded to
below Grade III quality
Collector
9.4 million/
year
Merchant
9.4 million/
year
Local Market
2.68 million/year
(30% of processed
finished skin)
Tannery
9.4 million/
year
Waste & Damage
Pre-process rejection: 0.47%
In-process damage: 5.0%
Export Market
6.25 million/year
(70% of processed
skin):
ƒ Pickled= 84.6%
ƒ Wet blue= 5.3%
ƒ Crust = 2.7%
ƒ Finished= 7.4%
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Infrastructure
There is almost universal agreement that Ethiopia has a massive infrastructure deficit.
This is illustrated in Table 3, while Table 4 gives some indicators of the complementary
effects on factors affecting firm profitability. There are deficits in almost every area.
Two illustrate: the poor quality of the rail to the principal port, in Djibouti (See Map);
and the contrast between the great potential in water, and the tiny fraction of irrigable
land actually under irrigation
Table 3 Indicators of Ethiopia’s infrastructure deficit
(unless otherwise indicated; 2000, latest available for Ethiopia)
Access to safe water source
Access to improved sanitation water
Fixed and mobile telephones (per 1,000 population)
Within 2 km of an all-season road (rural population)
Access to electricity (%households)
Rely on solid fuels (%households)
Low income
average
78
40
64
55
78
Africa
Ethiopia
54
44
58
40
24
90
24
15
8
27
6
95
Source: IDA 14 Results Measurement System, World Bank, 2004 and Estache (2005) for roads;
Ethiopia sources: World Bank (2004c) for water and sanitation; WDI for telephones; Estache
(2005) for roads and MDG NA for electricity; ESMAP for solid fuels
Table 4 The impact of unreliable infrastructure services on firms
Africa
Developing
Country
Average
Ethiopia
2002
Electricity
Delay in obtaining electricity connection
57.4
32.2
115.8
(days)
Value of lost output due to electrical outages
6.1
4.2
5.4
(% turnover)
Firms that share/own generator (% of total)
47.9
33.9
17.1
Telecom
Delay in obtaining telephone line (days)
73.6
37.2
154.9
Source: World Bank Investment Climate Assessment Database, latest available survey
(years vary).
Note: Data for Africa is average from 9 countries; developing country average for 45 countries.
There has been substantial growth in spending on infrastructure since the early 1990s,
with investment accounting for over 4 percent of GDP (of which almost 3 percent in
roads).
For infrastructure that supports productive activities, this has the structure of the last
model in Murphy, Shleifer and Vishny. Profits from transport, dams, irrigation etc.
depend on other firms investing. Given the low incomes and uncertain growth prospects
15
of Ethiopia, private firms are highly unlikely to invest in infrastructure outside areas that
have a well-defined markets, for which telecoms is the clearest example. (There is a
more complex story around private infrastructure finance with partial guarantees that we
return to later in the semester.) For major transport and water development, there is a
prima facie case for public funding, that also means donor finance. About 20 percent of
ODA already goes to finance infrastructure. However, this does not resolve the
coordination problem, for there are further rounds of organizational and inter-firm
challenges on the production side. Either smallholder or commercial farm production in
major irrigation sites will require solving a series of other constraints, including health
related (in the lowlands), organization of water management, and input and marketing
services. Even more challenging is solving the international coordination problems under
the Nile Basin Initiative, if Ethiopia is to undertake major water development and export
electricity from hydropower to the Sudan and Egypt.
A note on Dutch Disease
Since large scale infrastructure will require upfront government spending—with
significant donor finance—there is also a risk of Dutch Disease, that is a reduction in the
relative price of tradables as an equilibrating mechanism for the relative expansion of
demand for nontradable goods (in fact a further example of a general equilibrium
interaction.) This will tend to reduce profits in tradable goods production, and this needs
to be balanced against the increased profits from scale, infrastructure and inter-firm
linkages do not offset this.
Politics and government capability
Even if there is a prima facie case for government intervention, there is a question of
government capabilities. Here there are a number of factors to consider.
While the Ethiopian administration is relatively effective—especially for its income
level—it is far from independent. It has also been developed more to effect
political control than to coordinate and respond—whether across small-scale
producers (leather, smallholders that would produce in irrigated areas) or firms.
„ The society is emerging from a history of hierarchical control and conflict. The
recent elections displayed continuing underlying polarization. There is significant
mistrust between the private sector and the government.
„ Both state enterprises and party-controlled enterprises dominate the large-scale firm
sector. This raises questions of whether the playing field will be level for other
private firms, or new entrants. It is also likely to make it more difficult for the state
to impose hard performance constraints (that were important to the East Asian
experience.)
„
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The policy question
The question concerns policy design, but you have a choice of vantage point.
You are a newly appointed World Bank country director for Ethiopia. In your previous
experience, mainly outside the World Bank, you developed a rich understanding of the
industrialization dynamics in East Asia, focusing especially on the experiences of Japan
and Korea. There is tremendous interest in the question of how Ethiopia can take off into
rapid growth, and the government is interested in following what they interpret as an East
Asia path, of government playing a leading role in the coordination of industrialization
and big infrastructure investment. The donors took fright after the 2005 elections, but
there is now rising interest in coming back in—the donors are desperate for an African
success, and, in geopolitical terms, Ethiopia is increasingly seen as an island of stability
in a volatile neighborhood. But you are worried that conditions in Ethiopia are very
different from the East Asia exemplars: the political and social situation is polarized,
there is widespread concern over political biases in support of party-affiliated firms, and
the bureaucracy, while reasonably effective for its income level, is hardly independent.
You have a strategic planning meeting with the decision group in the World Bank’s Vice
Presidency for Africa. What do you recommend?
You are an economic advisor in the Prime Minister’s Office in Ethiopia. The
government faces a major policy challenge. Even before the 2005 elections, the
government had a clear vision of effecting an economic transformation of the country,
subject to the constraint of maintaining political control. After the elections, there is an
overwhelming political imperative—rapid, medium-term growth is seen as essential to
manage the current unpopularity of the government and indeed to hold the nation
together. With donors (including China) showing renewed interest, the government
wants to effect a Big Push. You have been asked to lead the team designing the strategy.
You have had study tours of East Asia, and see both economic and political parallels.
But you are also aware that a country such as Korea had important checks on
performance, including a powerful bureaucracy and the export drive. It is not clear that
these are politically and practically feasible for Ethiopia. You have to sketch your
approach to the Prime Minister. What do you recommend?
References
Easterly, William. 2006. “Reliving the 1950s: the Big Push, Poverty Traps, and Takeoffs
in Economic Development.” Forthcoming, Journal of Economic Growth.
Evans, Peter. 1995. Embedded Autonomy: States and Industrial Transformation.
Princeton University Press.
Hausmann, Ricardo, Dani Rodrik, and Andres Velasco. 2005. “Growth Diagnostics.”
Harvard University. Cambridge, Mass.: Processed.
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Murphy, Kevin, Andrei Shleifer, and Robert Vishny. 1989. “Industrialization and the
Big Push.” The Journal of Political Economy, 97,5.
Rodrik, Dani. 2006. Lecture notes on industrialization, PED101.
Rosenstein-Rodan, P. 1943. “The problem of industrialization of eastern and southeastern Europe.” Economic Journal, 53, 202-211.
Sachs, Jeffrey. The End of Poverty: Economic Possibilities for Our Time. New York:
the Penguin Press.
The Commission for Africa. Our Common Interest. Penguin Books.
World Bank. 2006. Draft country economic memorandum on Ethiopia.
Map of Ethiopia
Figure 7
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