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11.17 Focusing on the Fundamental Causes of Growth

The research of economists shows that successful economies are those with

high rates of accumulation of human and physical capital together with

sustained technological progress. But this conclusion then raises the crucial

question: why do some nations successfully achieve this outcome while

others fail? Olson (1996) has highlighted the fact that high rates of growth

seem to occur in a subset of poor countries rather than in all low-income

countries as the transitional dynamics of the Solow neoclassical growth model

imply. Given that capital and technology can migrate across political boundaries,

the persistence of significant differences in the level of output per

worker suggests the presence of persistent barriers to growth and development

(Parente and Prescott, 2000). An obvious deterrent to the free flow of

capital from rich to poor countries arises from the greater risk involved in

investing in countries characterized by macroeconomic instability, trade barriers,

inadequate infrastructure, poor education, ethnic diversity, widespread

corruption, political instability, disadvantageous geography and frequent policy

reversals. To understand why some countries have performed so much better

than others with respect to growth it is therefore necessary to go beyond the

proximate causes of growth and delve into the wider fundamental determinants.

This implies that we cannot hope to find the key determinants of

economic growth by using narrow economic analysis alone. To explain growth

‘miracles’ and ‘disasters’ requires an understanding of the history of the

countries being investigated as well as how policy choices are made within an

institutional structure involving political distortions.

Dani Rodrik (2003) has provided a useful framework for highlighting the

distinction between the proximate and fundamental determinants of eco634

Figure 11.8 Proximate and fundamental sources of growth

GDP = Yt

Factor endowments

= Kt + Nt + Lt


= At





= St

Geography =


resources +

climate +

topography +



Partly endogenous


nomic growth. Figure 11.8, adapted from Rodrik, captures the main factors

that determine the size and growth of any economy. Referring back to equation

(11.4), in the upper part of Figure 11.8 we can see the influence of the

proximate determinants of growth, with output being directly influenced by

an economy’s endowments of labour (Lt), physical capital (Kt), natural resources

(Nt) and the productivity of these resources (At). The impact of both

technical and allocative efficiency is captured within the productivity variable.

In the lower portion of Figure 11.8 we observe the major fundamental

determinants of economic growth, including social capability (St). Rodrik

provides a threefold taxonomy of the fundamental determinants of growth,

namely geography, integration and institutions. These categories highlight

three major research areas, within a voluminous and rapidly expanding literature,

that have dominated growth analysis in recent years. Many social scientists

would argue forcefully that the influence of culture should be added to the list

of important deeper determinants of economic performance. It is certainly the

case that economic historians have given much greater consideration to culture

as a determinant of economic performance than economists. For example,

David Landes argues that ‘Culture Makes Almost All the Difference’ (Harrison

and Huntington, 2000). For other interesting discussions of the influence of

culture on economic growth and development the reader should consult

Huntington, 1996; Temin, 1997; Landes, 1998; Lal, 1999; Dasgupta and

Serageldin, 2000; Barro and McCleary, 2003; Grief, 2003.

As Rodrik points out, the central question in growth analysis is: which of

the causal relationships in Figure 11.8 matters most? However, Rodrik also

notes that geography is the only exogenous factor in his threefold taxonomy,

with integration and institutions ‘co-evolving with economic performance’.

The causal interrelationships between the variables in Figure 11.8, indicated

by the two-way direction of some of the arrows, suggest that there are

complex feedback effects at work. Therefore empirical work, in the form of

endless cross-country regressions, that attempts to establish clear lines of

causality must be treated with ‘extreme care’.