1.1.1 THE THEORY OF ECONOMIC GROWTH THROUGH BASIC MODELS
Within the Theory of Economic Growth, different strands have been surfaced throughout the years aspiring the explained variation in income levels across countries, or in other words, how nations grow and prosper. Solow-Swan model (1956) was a pioneering approach using aggregate production functions to study the accumulation of capital in order to improve nations’ income. Although influential, Solow’s model assumes that technical progress is exogenous. In other words, the model assumes that technological progress captured by the (unexplained by the model) Solow residual just happens. The latter is the main shortcoming of the model as in the absence of technological progress, sustained growth is questionable. Moreover, the rate of capital accumulation (i.e., change) is determined by the savings rate, the depreciation, and the rate of population growth, respectively, which are also assumed to be exogenous. In other words, in this exogenous growth model, the interest is placed on capital accumulation as this was believed to be the means for welfare and prosperity at that time, thus neglecting the role of technology in sustained growth. Nevertheless, Mankiw et al.’s model (1992) provides an estimate of the total factor productivity rate, that is, the Solow residual.
Another strand is the neoclassical growth model that explicitly determines consumer’s side by taking into consideration (or in economic terms, endogenizing) savings. The Ramsey (1928) or Cass (1965)-Koopmans model (1965) introduces household optimization assuming an infinitely living representative household. Household preferences are specified; therefore, savings can now be linked to them, along with technology and prices in the economy. The most important contribution attached to this line of models is that it paves the way for a more systematic analysis of capital accumulation, investment in human capital, and endogenous technological progress. Although it does not shed light on the causes of cross-country income differences and economic growth, it clarifies the nature of economic decisions. However, the main assumption of the model is its major shortcomings as well.
In the overlapping generation models (OLGs), such as Diamond’s model (1965), households do not live eternally, but also allow for new households in the economy over time; however, their usefulness is not limited to that. Totally different implications are derived compared to the aforementioned neoclassical model, while the dynamics of capital accumulation and consumption are closer to Solow’s rather than the neoclassical model.
The common feature of the models described so far is the focus on exogenous technological progress as the source of capital accumulation and economic growth. However, the latter was challenged by the Endogenous Growth Theory stating that technical progress occurs within the system through Research and Development (R&D) activities and is therefore endogenous. The most important representatives of this class of models are David Romer and Robert Lucas.
On the one hand, Romer (1994) assumes that generated knowledge by a firm’s research spills over to other ones, creating new knowledge for them as well. In other words, technology has spillover effects across the entire economy and constitutes the ultimate determinant of long-run growth. On the other hand, Lucas (1988) puts human capital under the spotlight. Investment in education contributes to the production of human capital boosting growth. He argues that through education, the individual worker undergoing training becomes more productive (internal effect) and that spillovers increase both the productivity of capital and that of other workers in the economy (external). It is an investment in human rather than physical capital that has spillover effects, thus increasing the level of technology.
Overall, the focus is on technological progress, without explicit explanation of the details of the investment per se. However, income differences across countries could be attributed to differences in technology levels. Thus, understanding the sources of such differences is a necessary condition to achieve economic growth.
Grossman and Helpman (1994) brought to the discussion the role of the innovation process to explain the growth by arguing that research leads to a greater variety of final goods, and income improves because households gain more utility through product proliferation. However, a country’s technological progress is solely determined by its own investment in R&D, which is questionable. Technological advancements diffuse across countries, and each country has the potential to absorb knowledge generated through the World Technology Frontier, thus making diffusion equally important to the creation of new technologies. Another limitation of these models is that they do not capture the notion of the creative destruction process; that is, although innovation creates new technologies, it also “destroys” others by making them obsolete. Last but not least, the Schumpeterian models of economic growth capture process have their own limitations that go beyond the scope of this chapter.
1.1.2 THE ROLE OF TECHNOLOGY IN PRODUCTION
A well-known fact in economic theory is that the production functions, that is, production frontiers of economies of two different countries, are not directly comparable due to differences in the level of technology they have access to. Empirically speaking, this is one of the main issues that cause inconvenience to researchers in cross-country comparisons using most of the times the gross domestic product. A production function combines inputs such as labor, capital, and energy in order to produce outputs such as gross domestic product by assuming a certain level of technology. The latter is not directly observable, and it is considered as a black box.
Recent methodological advancements acknowledge that technology is a source of productivity and prosperity differences revolutionized the way cross-nation comparisons and benchmarking are done. The pioneering work of Haymi (1969) and Hayami and Ruttan (1970) introduced the concept of the metaproduction function that envelops all the individual frontiers. Moreover, the influential contribution of O’Donnell et al. (2008) further developed the concept and notions that could be used for benchmarking purposes and performance evaluation of the decision-making units under examination.
The latter paves the way for calculating the technology gap, which is the distance between the individual frontier and the metafrontier. The metafrontier that is used as an empirical tool to account for all the possible heterogeneities among the units is under consideration, has become a growing wave, and has triggered many studies in the field of economics in terms of efficiency and productivity.
It has become apparent that growth and prosperity can be sustained through technology diffusion. Recent contributions of Tsekouras et al. (2016) and Chatzistamoulou et al. (2019) have used the metafrontier to capture knowledge flows; that is, spillover effects improve the performance of the units bringing to the forefront, and productivity differences are attributed to heterogeneities of technology.
