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10.16 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 finance

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

Figure 10.6 How inequality may adversely affect growth

Credit market

imperfections: the

poor forego

investment in

human capital

Inequality

promotes

redistribution:

tax distortions

reduce work

effort and

entrepreneurship

Inequality

promotes rent

seeking, crime

and political

instability

‘Big Push’

theory:

industrialization

requires a large

domestic market

and inequality

represents an

obstacle

Reduced

economic

growth

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).