The Political Economy of Economic Growth
One of the most important adverse effects of political instability is its negative
impact on economic growth. In Chapter 11 we discuss several strands in
the new growth literature that focus on the deeper determinants of growth,
including politics and institutions. Drazen (2000a) argues that the political
economy of growth literature is a natural extension of the research on the
political economy of income redistribution and in this chapter we review
some recent research into the links between inequality, economic growth,
dictatorship and democracy (see Alesina and Perotti, 1994; Alesina and Rodrik,
1994; Persson and Tabellini, 1994; Alesina and Perotti, 1996c; Benabou,
1996; Deininger and Squire, 1996; Aghion et al., 1999; Barro, 2000; Forbes,
2000; Lundberg and Squire, 2003).
In exploring the connection between inequality and economic growth we
first of all need to distinguish between the ‘old’ view and the ‘new’ view. The
old view dominated thinking in development economics throughout the 1960s
and 1970s and is captured in the work of economists such as Arthur Lewis
(1954) and Richard Nelson (1956). The old view is dominated by ‘capital
fundamentalism’; that is, capital accumulation is the key to economic growth.
Capital fundamentalism is associated in particular with the wide acceptance
and use of the Harrod–Domar growth model within the development literature
and development institutions such as the World Bank (see Easterly, 1999,
2001a, and Chapter 11). In order to foster high rates of accumulation, in the
absence of substantial inflows of foreign capital, a country must generate the
necessary resources through high rates of domestic saving. It was assumed
that inequality of income would produce this result since the rich were
assumed to have a higher propensity to save than the poor (see Kaldor, 1955).
This view is encapsulated in the following statement by Harry Johnson (1958):
There is likely to be a conflict between rapid growth and an equitable distribution
of income; and a poor country anxious to develop would be probably well advised
not to worry too much about the distribution of income.
Another reason why inequality may lead to faster growth is linked to the idea
of investment indivisibilities, that is, the setting up of new industries frequently
involves very large sunk costs. Meeting these costs in poorly developed
countries with inadequate financial markets requires the concentration of
wealth. Finally, it was also argued that without adequate incentives, investment
rates would remain insufficient to generate sustained growth
That there was a trade-off between growth and equity dominated early post-
Second World War development thinking. In addition, the ‘Kuznets hypothesis’
suggested that as countries develop, inequality will initially increase before
declining (see Kuznets, 1955). Hence the relationship between inequality and
GDP per capita shows up in both time series and cross-sectional data as an
inverted U-shaped relationship. Barro’s (2000) empirical results confirm that
the Kuznets curve remains a ‘clear empirical regularity’.
As economic development spread across the world during the latter half of
the twentieth century it became clear that there was an increasing number of
successful development stories where outstanding rates of economic growth
were achieved without those countries exhibiting high degrees of income
inequality, namely the Asian Tigers. In addition many countries, for example
in Latin America, with high inequality had a poor record of economic growth.
Hence, during the last decade there has been a change in thinking on this
issue. Several economists have begun to emphasize the potential adverse
impact of inequality on growth, an idea that had already been propounded by
Gunnar Myrdal (1973). Aghion et al. (1999) conclude that the old view that
inequality is necessary for capital accumulation and that redistribution damages
growth ‘is at odds with the empirical evidence’.
Various mechanisms have been suggested as possible causes of a negative
association between inequality and subsequent growth performance (see Alesina
and Perotti, 1994). The credit market channel highlights the limited access to
finance that the poor have in order to invest in human capital formation. Since
in this environment most people have to rely on their own resources to financ
education, a reduction in inequality could increase the rate of human capital
formation and economic growth. A second ‘fiscal’ channel highlights the distortions
and disincentive effects of taxation introduced under political pressure
to reduce high inequality. Redistribution of income, by raising the tax burden
on potential investors, reduces investment and consequently economic growth
(Alesina and Rodrik, 1994; Persson and Tabellini, 1994). A third channel
suggests that high inequality leads to a larger number of agents engaging in
rent seeking, corruption and criminal activities. These activities threaten property
rights and the incentive to invest. Glaeser et al. (2003) develop a model
where inequality adversely influences economic outcomes by threatening property
rights due to the subversion of legal, political and regulatory institutions by
a rich, powerful élite. The answer to this problem is not to replace ‘King John
redistribution’ with ‘Robin Hood distribution’, that is, not to replace an old
corrupt oligarchy with a bureaucratic socialist oligarchy. Rather, the solution
lies in institutional reform. According to Olson (2000), there are two key
requirements for any society to prosper: first, the establishment of secure and
well-defined individual rights with respect to private property and impartial
enforcement of contracts, as capitalism is first and foremost a legal system; and
second, the ‘absence of predation of any kind’. The empirical evidence suggests
that there ‘is no society in the post-war world that has fully met the two
foregoing conditions’. But clearly some economies have come much closer to
the ideal than others and this is generally reflected in their long-term economic
performance (Olson, 1996). Gyimah-Brempong’s (2002) empirical analysis of
corruption, economic growth and inequality in Africa finds that corruption is
positively related to income inequality and hurts the poor more than the rich. To
understand the political roots of economic success is a crucial research area for
social scientists because, as Table 10.5 indicates, sub-Saharan Africa’s ‘Subjective
indictors of governance’ make depressing reading. Fajnzylber et al. (2002)
have also shown that violent crime is positively correlated to inequality and
their results are robust after controlling for the overall level of poverty. Furthermore,
Alesina and Perotti (1996c) show that inequality promotes social and
political unrest and the threat of violence and revolution reduces growthenhancing
activities. These conclusions are empirically ‘quite solid’ (see also
Alesina et al., 1996).
Albert Hirschman (1973) also drew attention to the impact of inequality on
growth via what he labelled ‘the tunnel effect’, which consists of the following
basic propositions:
1. in the early stages of development and growth there is a high tolerance
for growing inequalities;
2. this tolerance erodes through time if the low income groups fail to
benefit from the growth process;
Table 10.5 Selected indicators of governance: 20 sub-Saharan African
countriesa
Country Voice and Rule of lawc Government Corruption
and year of accountabilityc –2.5–2.5 effectivenessc indexc
independenceb –2.5–2.5 –2.5–2.5 –2.5–2.5
Angola 1975 –1.26 –1.49 –1.31 –1.14
Burkino Faso 1960 –0.26 –0.79 –0.02 –0.93
Cameroon 1960 –0.82 –0.40 2.0 –1.11
Côte d’Ivoire 1960 –1.19 –0.54 –0.81 –0.71
Ethiopia 1941 –0.85 –0.24 –1.01 –0.40
Ghana 1957 0.02 –0.08 –0.06 –0.28
Kenya 1963 –0.68 –1.21 –0.76 –1.11
Madagascar 1960 0.28 –0.68 –0.35 –0.93
Malawi 1964 –0.14 –0.36 –0.77 0.10
Mali 1960 0.32 –0.66 –1.44 –0.41
Mozambique 1975 –0.22 –0.32 –0.49 0.10
Niger 1960 0.11 –1.17 –1.16 –1.09
Nigeria 1960 –0.44 –1.13 –1.00 –1.05
Senegal 1960 0.12 –0.13 0.16 –0.39
South Africa 1934 1.17 –0.05 0.25 0.35
Sudan 1956 –1.53 –1.04 –1.34 –1.24
Tanzania 1961 –0.07 0.16 –0.43 –0.92
Uganda 1962 –0.79 –0.65 –0.32 –0.92
Zaire 1960 –1.70 –2.09 –1.38 –1.24
Zimbabwe 1965 –0.90 –0.94 –1.03 –1.08
Notes:
a UNDP, Human Development Report, 2002.
b Chambers Political Systems of the World, Edinburgh: Chambers.
c UNDP (2002). In the scoring range –2.5–2.5, higher is better. The highest scores for each
category are:
Switzerland for Voice and accountability (1.73);
Switzerland for Rule of law (1.91);
Singapore for Government effectiveness (2.16);
Finland for the Corruption index (2.25).
The UK scores 1.46, 1.61, 1.77 and 1.86 respectively for each category.
3. in the long run persistent and growing inequalities in a developing country
are likely to lead to ‘development disasters’ as internal tensions,
fuelled by inequality, lead to political instability.
Hirschman argues that individuals assess their individual welfare in relative
terms, that is, by comparing their own income with that of others. Even if the
poor make some modest gains in terms of real income, the fact that other
groups make spectacular progress will lead to feelings of relative deprivation.
Hirschman uses the analogy of motorists stuck in a traffic jam in a two-lane
tunnel, both lanes heading in the same direction. If the traffic is stationary in
both lanes, drivers will initially show patience in the hope that soon the
blockage will be removed. If the one lane of traffic then begins to move,
those who are not yet moving initially have their hopes raised. Soon they to
expect to be on their way. So initially the ‘tunnel effect’ is strong and the
drivers who are not moving wait patiently for their turn to move. But if one
lane of traffic continues to move, and at an ever-increasing pace, while the
other lane remains blocked, very soon the drivers in the static lane will
become furious at the injustice they are being subjected to and they will be
prepared to engage in ‘foul play’, dangerous acts of driving and maybe even
in severe violence (road rage) towards the drivers in the unblocked lane. In
other words, as long as the ‘tunnel effect’ lasts, everyone feels better off even
though it involves increased inequality. But once the ‘tunnel effect’ wears off
there is potential for revolution and demand for political change. That change
may take place with or without violent disruption. This seems to be an
accurate description of the experience of several developing countries.
A fourth channel is one that derives from Murphy et al.’s (1989b)
reinvigorated version of the ‘Big Push’ theory. Here the idea is that successful
industrialization requires a large market in terms of domestic demand in
order to make increasing-returns technologies profitable. A high degree of
income inequality, by suppressing domestic demand, inhibits the development
of an economic environment conducive to facilitating a ‘Big Push’ on
economic development.
The various mechanisms whereby inequality impacts on economic growth
are illustrated in Figure 10.6. As Alesina and Perotti (1996c) recognize, some
of these channels work in opposing directions. The distortionary effect of
taxes on the incentive to invest operating through the fiscal channel will tend
to reduce growth, but at the same time may also reduce social tensions and
thereby reduce the threat of political instability. ‘Therefore the net effect of
redistributive policies on growth has to weigh the costs of distortionary
taxation against the benefits of reduced social tensions’.
Is there any way of linking the old view to the new view of the impact of
inequality on growth? In an interview Acemoglu suggests the following
possibility (see Snowdon, 2004c):
One way of linking the ‘old inequality is good for growth’ story with the newer
stories that ‘inequality is bad for growth’ is as follows. Think of a model where in
the early stages of development, by giving resources and political power to the
same group, this leads to higher rates of investment. But suppose also, that in a
dynamic world these people who are rich and powerful are no longer the ones
who can take advantage of the changing economic opportunities. The entrenched
groups with political power become an unproductive oligarchy resistant to change.
They utilise their economic and political power to block the entry of new more
dynamic groups of people. This reverses the relationship between inequality and
growth. The high inequality countries are those that begin to stagnate. Of course
this is conjecture squared [laughter]. But it is a story that is consistent with the
history of the Caribbean economy.
It is becoming increasingly clear from economists’ research that institutional
failures frequently prevent a country from adopting the most productive
technologies. Some economists have suggested an ‘economic losers’ hypothesis’
whereby powerful interest groups resist the adoption of new technology
in order to protect their economic rents (Parente and Prescott, 2000). In
contrast, Daron Acemoglu and James Robinson in a series of papers advocate
a ‘political losers’ hypothesis’ as an alternative and more plausible explanation
of why there emerge institutional barriers to development (see, for
example, Acemoglu and Robinson, 2000a).
One of the most important adverse effects of political instability is its negative
impact on economic growth. In Chapter 11 we discuss several strands in
the new growth literature that focus on the deeper determinants of growth,
including politics and institutions. Drazen (2000a) argues that the political
economy of growth literature is a natural extension of the research on the
political economy of income redistribution and in this chapter we review
some recent research into the links between inequality, economic growth,
dictatorship and democracy (see Alesina and Perotti, 1994; Alesina and Rodrik,
1994; Persson and Tabellini, 1994; Alesina and Perotti, 1996c; Benabou,
1996; Deininger and Squire, 1996; Aghion et al., 1999; Barro, 2000; Forbes,
2000; Lundberg and Squire, 2003).
In exploring the connection between inequality and economic growth we
first of all need to distinguish between the ‘old’ view and the ‘new’ view. The
old view dominated thinking in development economics throughout the 1960s
and 1970s and is captured in the work of economists such as Arthur Lewis
(1954) and Richard Nelson (1956). The old view is dominated by ‘capital
fundamentalism’; that is, capital accumulation is the key to economic growth.
Capital fundamentalism is associated in particular with the wide acceptance
and use of the Harrod–Domar growth model within the development literature
and development institutions such as the World Bank (see Easterly, 1999,
2001a, and Chapter 11). In order to foster high rates of accumulation, in the
absence of substantial inflows of foreign capital, a country must generate the
necessary resources through high rates of domestic saving. It was assumed
that inequality of income would produce this result since the rich were
assumed to have a higher propensity to save than the poor (see Kaldor, 1955).
This view is encapsulated in the following statement by Harry Johnson (1958):
There is likely to be a conflict between rapid growth and an equitable distribution
of income; and a poor country anxious to develop would be probably well advised
not to worry too much about the distribution of income.
Another reason why inequality may lead to faster growth is linked to the idea
of investment indivisibilities, that is, the setting up of new industries frequently
involves very large sunk costs. Meeting these costs in poorly developed
countries with inadequate financial markets requires the concentration of
wealth. Finally, it was also argued that without adequate incentives, investment
rates would remain insufficient to generate sustained growth
That there was a trade-off between growth and equity dominated early post-
Second World War development thinking. In addition, the ‘Kuznets hypothesis’
suggested that as countries develop, inequality will initially increase before
declining (see Kuznets, 1955). Hence the relationship between inequality and
GDP per capita shows up in both time series and cross-sectional data as an
inverted U-shaped relationship. Barro’s (2000) empirical results confirm that
the Kuznets curve remains a ‘clear empirical regularity’.
As economic development spread across the world during the latter half of
the twentieth century it became clear that there was an increasing number of
successful development stories where outstanding rates of economic growth
were achieved without those countries exhibiting high degrees of income
inequality, namely the Asian Tigers. In addition many countries, for example
in Latin America, with high inequality had a poor record of economic growth.
Hence, during the last decade there has been a change in thinking on this
issue. Several economists have begun to emphasize the potential adverse
impact of inequality on growth, an idea that had already been propounded by
Gunnar Myrdal (1973). Aghion et al. (1999) conclude that the old view that
inequality is necessary for capital accumulation and that redistribution damages
growth ‘is at odds with the empirical evidence’.
Various mechanisms have been suggested as possible causes of a negative
association between inequality and subsequent growth performance (see Alesina
and Perotti, 1994). The credit market channel highlights the limited access to
finance that the poor have in order to invest in human capital formation. Since
in this environment most people have to rely on their own resources to financ
education, a reduction in inequality could increase the rate of human capital
formation and economic growth. A second ‘fiscal’ channel highlights the distortions
and disincentive effects of taxation introduced under political pressure
to reduce high inequality. Redistribution of income, by raising the tax burden
on potential investors, reduces investment and consequently economic growth
(Alesina and Rodrik, 1994; Persson and Tabellini, 1994). A third channel
suggests that high inequality leads to a larger number of agents engaging in
rent seeking, corruption and criminal activities. These activities threaten property
rights and the incentive to invest. Glaeser et al. (2003) develop a model
where inequality adversely influences economic outcomes by threatening property
rights due to the subversion of legal, political and regulatory institutions by
a rich, powerful élite. The answer to this problem is not to replace ‘King John
redistribution’ with ‘Robin Hood distribution’, that is, not to replace an old
corrupt oligarchy with a bureaucratic socialist oligarchy. Rather, the solution
lies in institutional reform. According to Olson (2000), there are two key
requirements for any society to prosper: first, the establishment of secure and
well-defined individual rights with respect to private property and impartial
enforcement of contracts, as capitalism is first and foremost a legal system; and
second, the ‘absence of predation of any kind’. The empirical evidence suggests
that there ‘is no society in the post-war world that has fully met the two
foregoing conditions’. But clearly some economies have come much closer to
the ideal than others and this is generally reflected in their long-term economic
performance (Olson, 1996). Gyimah-Brempong’s (2002) empirical analysis of
corruption, economic growth and inequality in Africa finds that corruption is
positively related to income inequality and hurts the poor more than the rich. To
understand the political roots of economic success is a crucial research area for
social scientists because, as Table 10.5 indicates, sub-Saharan Africa’s ‘Subjective
indictors of governance’ make depressing reading. Fajnzylber et al. (2002)
have also shown that violent crime is positively correlated to inequality and
their results are robust after controlling for the overall level of poverty. Furthermore,
Alesina and Perotti (1996c) show that inequality promotes social and
political unrest and the threat of violence and revolution reduces growthenhancing
activities. These conclusions are empirically ‘quite solid’ (see also
Alesina et al., 1996).
Albert Hirschman (1973) also drew attention to the impact of inequality on
growth via what he labelled ‘the tunnel effect’, which consists of the following
basic propositions:
1. in the early stages of development and growth there is a high tolerance
for growing inequalities;
2. this tolerance erodes through time if the low income groups fail to
benefit from the growth process;
Table 10.5 Selected indicators of governance: 20 sub-Saharan African
countriesa
Country Voice and Rule of lawc Government Corruption
and year of accountabilityc –2.5–2.5 effectivenessc indexc
independenceb –2.5–2.5 –2.5–2.5 –2.5–2.5
Angola 1975 –1.26 –1.49 –1.31 –1.14
Burkino Faso 1960 –0.26 –0.79 –0.02 –0.93
Cameroon 1960 –0.82 –0.40 2.0 –1.11
Côte d’Ivoire 1960 –1.19 –0.54 –0.81 –0.71
Ethiopia 1941 –0.85 –0.24 –1.01 –0.40
Ghana 1957 0.02 –0.08 –0.06 –0.28
Kenya 1963 –0.68 –1.21 –0.76 –1.11
Madagascar 1960 0.28 –0.68 –0.35 –0.93
Malawi 1964 –0.14 –0.36 –0.77 0.10
Mali 1960 0.32 –0.66 –1.44 –0.41
Mozambique 1975 –0.22 –0.32 –0.49 0.10
Niger 1960 0.11 –1.17 –1.16 –1.09
Nigeria 1960 –0.44 –1.13 –1.00 –1.05
Senegal 1960 0.12 –0.13 0.16 –0.39
South Africa 1934 1.17 –0.05 0.25 0.35
Sudan 1956 –1.53 –1.04 –1.34 –1.24
Tanzania 1961 –0.07 0.16 –0.43 –0.92
Uganda 1962 –0.79 –0.65 –0.32 –0.92
Zaire 1960 –1.70 –2.09 –1.38 –1.24
Zimbabwe 1965 –0.90 –0.94 –1.03 –1.08
Notes:
a UNDP, Human Development Report, 2002.
b Chambers Political Systems of the World, Edinburgh: Chambers.
c UNDP (2002). In the scoring range –2.5–2.5, higher is better. The highest scores for each
category are:
Switzerland for Voice and accountability (1.73);
Switzerland for Rule of law (1.91);
Singapore for Government effectiveness (2.16);
Finland for the Corruption index (2.25).
The UK scores 1.46, 1.61, 1.77 and 1.86 respectively for each category.
3. in the long run persistent and growing inequalities in a developing country
are likely to lead to ‘development disasters’ as internal tensions,
fuelled by inequality, lead to political instability.
Hirschman argues that individuals assess their individual welfare in relative
terms, that is, by comparing their own income with that of others. Even if the
poor make some modest gains in terms of real income, the fact that other
groups make spectacular progress will lead to feelings of relative deprivation.
Hirschman uses the analogy of motorists stuck in a traffic jam in a two-lane
tunnel, both lanes heading in the same direction. If the traffic is stationary in
both lanes, drivers will initially show patience in the hope that soon the
blockage will be removed. If the one lane of traffic then begins to move,
those who are not yet moving initially have their hopes raised. Soon they to
expect to be on their way. So initially the ‘tunnel effect’ is strong and the
drivers who are not moving wait patiently for their turn to move. But if one
lane of traffic continues to move, and at an ever-increasing pace, while the
other lane remains blocked, very soon the drivers in the static lane will
become furious at the injustice they are being subjected to and they will be
prepared to engage in ‘foul play’, dangerous acts of driving and maybe even
in severe violence (road rage) towards the drivers in the unblocked lane. In
other words, as long as the ‘tunnel effect’ lasts, everyone feels better off even
though it involves increased inequality. But once the ‘tunnel effect’ wears off
there is potential for revolution and demand for political change. That change
may take place with or without violent disruption. This seems to be an
accurate description of the experience of several developing countries.
A fourth channel is one that derives from Murphy et al.’s (1989b)
reinvigorated version of the ‘Big Push’ theory. Here the idea is that successful
industrialization requires a large market in terms of domestic demand in
order to make increasing-returns technologies profitable. A high degree of
income inequality, by suppressing domestic demand, inhibits the development
of an economic environment conducive to facilitating a ‘Big Push’ on
economic development.
The various mechanisms whereby inequality impacts on economic growth
are illustrated in Figure 10.6. As Alesina and Perotti (1996c) recognize, some
of these channels work in opposing directions. The distortionary effect of
taxes on the incentive to invest operating through the fiscal channel will tend
to reduce growth, but at the same time may also reduce social tensions and
thereby reduce the threat of political instability. ‘Therefore the net effect of
redistributive policies on growth has to weigh the costs of distortionary
taxation against the benefits of reduced social tensions’.
Is there any way of linking the old view to the new view of the impact of
inequality on growth? In an interview Acemoglu suggests the following
possibility (see Snowdon, 2004c):
One way of linking the ‘old inequality is good for growth’ story with the newer
stories that ‘inequality is bad for growth’ is as follows. Think of a model where in
the early stages of development, by giving resources and political power to the
same group, this leads to higher rates of investment. But suppose also, that in a
dynamic world these people who are rich and powerful are no longer the ones
who can take advantage of the changing economic opportunities. The entrenched
groups with political power become an unproductive oligarchy resistant to change.
They utilise their economic and political power to block the entry of new more
dynamic groups of people. This reverses the relationship between inequality and
growth. The high inequality countries are those that begin to stagnate. Of course
this is conjecture squared [laughter]. But it is a story that is consistent with the
history of the Caribbean economy.
It is becoming increasingly clear from economists’ research that institutional
failures frequently prevent a country from adopting the most productive
technologies. Some economists have suggested an ‘economic losers’ hypothesis’
whereby powerful interest groups resist the adoption of new technology
in order to protect their economic rents (Parente and Prescott, 2000). In
contrast, Daron Acemoglu and James Robinson in a series of papers advocate
a ‘political losers’ hypothesis’ as an alternative and more plausible explanation
of why there emerge institutional barriers to development (see, for
example, Acemoglu and Robinson, 2000a).
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