Economic Development Theory

The theory of economic development is essentially growth theory as applied to the world as a whole, consisting of nearly 200 countries ranging in population from China to nearly unpopulated islands like Nauru or tiny city-states like Liechtenstein, Monaco, San Marino or Andorra. The range of political and economic circumstances is nearly as great. To explain the developmental behavior of such a diverse group is obviously a daunting task. However, the task has attracted, and continues to attract, considerable attention from economists. Attempts to explain economic development have a long history. Early theories were more theoretically than empirically based. By the middle of the 19th century, growth was an obvious fact of economic life. At that time, it was attributed to labor force (that is, population) growth and capital accumulation. The latter was attributed to 'surplus' (profits) or savings.

The most influential models of the 1930s and 1940s were based on a formula attributed to Fel'dman (1928, 1964), equating the rate of growth of the economy to the savings rate divided by the capital-output ratio, or (equivalently) the ratio of annual savings to capital stock. The formula was rediscovered (independently) by Harrod and Domar (Harrod 1939; Domar 1946). These models, which emphasized the role of central planning (a relic of academic Marxism), dominated early postwar thinking about development economics.2 For instance, a well-known 1950s-era text on the subject by Arthur Lewis states, without qualification, that 'the central fact of development is rapid capital accumulation' (including knowledge and skills with capital) (Lewis 1955).

An influential theory of development known as the 'stage theory' was introduced in 1960 (Rostow 1960). Rostow's idea was, in brief, that economic growth 'takes off only when a certain level of capital investment has been achieved, along with other conditions. In effect, the rate of growth depends upon the level of current income, using a relationship - based on a scatter chart - that is very difficult, if not impossible, to quantify sufficiently for forecasting purposes. As a consequence, the exact model specification is essentially arbitrary, since both the theoretical and empirical bases are weak. However, the characteristic growth trajectory in the Rostow theory would be a sort of elongated S-curve, characterized by rapid growth after 'takeoff', followed by progressively slower growth thereafter, that is, 'the poor get richer and the rich slow down'.

Actually the Solow-Swan theory has a built-in tendency for declining productivity due to declining returns to capital investment (Solow 1956, 1957; Swan 1956). This feature of the Solow model implies that countries with a small capital stock should grow faster than countries with a large capital stock. The same feature also predicts a gradual convergence between poor and rich countries. In the late 1980s and early 1990s there was considerable interest in the theory of convergence, supported by a wide variety of examples, mostly regional. In fact, for a time, it appeared that a new regularity in empirical economics had been discovered, namely the existence of a common underlying convergence rate within 'convergence clubs' at the rate of 2 percent per annum (Baumol 1986; Baumol et al. 1989; Ben-David 1994; Barro and Sala-i-Martin 1992, 1995).

However, as the voluminous econometric evidence was digested, it emerged that the apparent statistical uniformity might be misleading. There is some evidence for convergence in East Asia, but not in Africa or Latin America. However, while 'convergence clubs' apparently exist at both ends of the economic spectrum, the rich clubs and the poor clubs are polarized and diverging from each other. This large-scale divergence dominates the apparent 2 percent convergence that had been accepted as conventional wisdom (Quah 1996). Others have confirmed this conclusion. The results of our work, presented below, can be regarded as supportive of the 'diverging convergence clubs' notion, although we have arrived at our results (discussed later) by a completely different route.

In any case, economic growth in the industrialized countries has not slowed down to the degree suggested by the Solow theory, while most developing countries (with some notable exceptions, as noted hereafter) have not been catching up (Barro and Sala-i-Martin 1995). The failure of the rich countries to slow down as the model implied was one of the reasons for widespread interest in 'endogenous growth theory' that emerged in the late 1980s (Romer 1986, 1990; Lucas 1988).

In response to this perceived difficulty, some theorists have suggested that capital and labor augmentation in the sense of quality improvements might enable the Solow-Swan model to account for the observed facts. For instance, education and training make the labor force more productive. Moreover, knowledge and skills presumably do not depreciate. Similarly, capital goods have become more productive as more advanced technology is embodied in more recent machines, thus compensating for depreciation. Augmentation of labor and capital are, in some degree, an observable and quantifiable fact. Allowing for it, a number of cross-sectional econometric studies were carried out in the 1990s to test this idea. Indeed, some of them seemed, at first, to provide empirical support for the idea that exogenous technological progress (TFP) can be eliminated from the theory and that factor accumulation alone adjusted for augmentation could, after all, explain the observed facts of economic development (Mankiw et al. 1992; Mankiw 1995; Young 1995; Barro and Sala-i-Martin 1995).

However more recent research has also undermined that tentative conclusion, based as it was on statistical analysis of imperfect data. Later results have essentially reinstated the original Solow view that factor accumulation is not the central feature of economic growth after all (Easterly and Levine 2001). Easterly and his colleagues, having extensively reviewed the published literature of economic development studies, argue - as Solow did - that 'something else' accounts for most of the observable differences between growth experiences in different countries. Easterly et al. adopt the standard convention of referring to this 'something else' as TFP.

The standard theory up to now also shares a significant and even bizarre feature: it does not consider natural resource consumption and use to have any role in the growth process. Yet, though most economic historians date the beginning of the industrial revolution to the innovations in textile spinning, carding and weaving, it is evident that later developments depended on the works of James Watt and the 'age of steam'. Similarly, most non-economists immediately grasp the historical importance of the substitution of machines driven by the combustion of fossil fuels for human and animal labor. It seems to follow, of course, that the availability - or nonavailability - of ever-cheaper fuels and sources of power will inevitably have a crucial impact on future economic growth.

Contemporary concerns about the price of petroleum are by no means irrelevant. It is simply not plausible that resource consumption is determined only by growth but not vice versa, or that GDP growth will continue indefinitely at a constant rate like manna from heaven. The rising price of petroleum will have very different effects on the growth trajectories of developing countries, depending on whether they are exporters or importers of oil, gas and coal. The failure of contemporary economic theory to recognize this 'disconnect' (as we see it) says more about the mind-set of contemporary economic theorists than it does about the real world.

Undoubtedly technological change, investment (and thus savings), capital accumulation, labor (workers and hours worked) and population growth are key driving forces of economic growth. These factors certainly differ widely across countries, and consistent long-term data series for some of the variables - especially technological change - are scarce or nonexistent. We therefore seek a proxy for the latter variable.

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