Friday, March 13, 2015

15 years of new growth economics: what have we learnt?

I want to highlight a few passages from Xavier Sala-i-Martin's paper titled "15 years of new growth economics: what have we learnt?" 

Paul Romer’s paper Increasing Returns and Long Run Growth, now 15 years old, led to resurgence in the research on economic growth. Since then, growth literature has expanded dramatically and has shifted the research focus of many generations of macroeconomists. The new line of work has emphasized the role of human capital, social and political variables, as well as the importance of institutions as driving forces of long-run economic growth. This paper presents an insight into the theoretical and empirical literature of the past fifteen years, highlighting the most significant contributions for our understanding of economics."

A good part of the paper discusses the technicalities of economic data modeling. While interesting, they are not the key teachings I wanted to bring out in this blog entry. 
I only quoted the parts which are my key takeaways...

First quote:
   "The cross-country regression literature is enormous: a large number of papers have
claimed to have found one or more variables that are partially correlated with the growth rate: from human capital to investment in R&D, to policy variables such as inflation or the fiscal deficit, to the degree of openness, financial variables or measures of political instability. In fact, the number of variables claimed to be correlated with growth is so large that the question arises as to which of these variables is actually robust.
Some important lessons from this literature are:

  1. There is no simple determinant of growth
  2. The initial level of income is the most important and robust variable (so conditional convergence is the most robust empirical fact in the data)
  3. The size of the government does not appear to matter much. What is important is the “quality of government” (governments that produce hyperinflations, distortions in foreign exchange markets, extreme deficits, inefficient bureaucracies, etc., are governments that are detrimental to an economy)
  4. The relation between most measures of human capital and growth is weak. Some measures of health, however, (such as life expectancy) are robustly correlated with growth
  5. Institutions (such as free markets, property rights and the rule of law) are important for growth
  6. More open economies tend to grow faster"
Second quote:
   "Notice that since technology is non-rival, it must be produced only once (once it is

produced, many people can use it over and over). This suggests that there is a large fixed cost in its production (the R&D cost), which leads to the notion of increasing returns. The average cost of producing technology is always larger than the marginal cost. Hence, under perfect price competition (a competition that leads to the equalization of prices with marginal costs), the producers of technology who pay the fixed R&D costs will always lose money. The implication is that in a perfectly competitive environment, no firm will engage in research. Put another way, if we want to model technological progress endogenously, we need to abandon the perfectly-competitive-pareto-optimal world that is the foundation of neoclassical theory and allow for imperfect competition. And this is another contribution of the literature: unlike the neoclassical researchers of the 1960s, today’s economists deal with models that are not Pareto optimal."

Third quote:
   "The new growth models of technological progress have clarified some important issues
when it comes to R&D policies. Perhaps the most important one being that, despite market
failures (because of imperfect competition, externalities, and increasing returns), it is not at all obvious whether the government should intervene, what this potential intervention should look like and, in particular, whether it should introduce R&D subsidies. This is important because there is a widespread popular notion that countries tend to underinvest in technology and that the government should do something about it. The models of R&D highlight a number of distortions, but it is not clear that the best way to deal with them is to subsidize R&D. For example, the one distortion that is common across models is the one that arises from imperfect competition: prices tend to be above marginal cost and the quantity of ideas generated tend to be below optimal. The optimal policy to offset this distortion, however, is not an R&D subsidy but a subsidy to the purchases of the overpriced goods.

The main point I wish to highlight is that, although the new generation of growth models
are based on strong departures from the old pareto-optimal neoclassical world, it is not obvious that they call for strong government intervention and, when they do, it is not obvious that the intervention recommended coincides with the popular view that R&D needs to be subsidized."

Fourth quote:
   "Another important lesson we have learned from the new economic growth literature is
that “institutions” are important empirically and that they can be modeled. By “institutions” I
mean various aspects of law enforcement (property rights, the rule of law, legal systems, peace), the functioning of markets (market structures, competition policy, openness to foreign markets, capital and technology), inequality and social conflicts (the relation between inequality and growth has been widely studied)13, political institutions (democracy, political freedom, political disruption, political stability), the health system (as previously stated, life expectancy is one of the variables most robustly correlated with growth), financial institutions (like an efficient banking system or a good stock market) as well as government institutions (the size of bureaucracy and red tape, government corruption).

   Institutions affect the “efficiency” of an economy much in the same way as technology
does: an economy with bad institutions is more inefficient in the sense that it takes more inputs to produce the same amount of output. In addition, bad institutions lower incentives to invest (in physical and human capital as well as technology) and to work and produce.
   Although the new economic growth literature has quantified the importance of having the
right institutions, it is still at its early stages when it comes to understanding how to promote
them in practice. For example, the empirical “level of income” literature mentioned above has demonstrated that the “institutions” left behind in the colonies directly affect the level of income enjoyed by the country one half century later: colonies in which the colonizers introduced institutions that helped them live a better life in the colony, tend to have more income today than colonies in which colonizers introduce predatory institutions. This seems to be a robust empirical phenomenon. However, it is not clear what the lessons are for the future. In other words, can we undo the harm done by the “colonial predators” and, if so, what can we do and how can we do so.
Although these are important questions currently being dealt with in the literature, the answers are still unclear.

   Indeed, we are still in the early stages when it comes to incorporating institutions to our
growth theories. Empirically, it is becoming increasingly clear that institutions are an important
determinant of growth."

Working Paper #172, Central Bank of Chile, July 2012
Xavier Sala-i-Martin, Columbia University and Universitat Pompeu Fabra