Motivation for the Research
Economies at early stages of the development process are often shaken by abrupt changes in growth rates. In an earlier paper, the authors quantified the contribution of various factors at different stages of development, finding that the high volatility in poor countries is due to (1) higher levels of sectoral concentration, (2) higher levels of sectoral risk (that is, poor countries not only specialize in few sectors, but those sectors also tend to bear particularly high risk), and (3) higher country-specific macroeconomic risk.
A volatility accounting exercise carried out by the authors indicates that approximately 50 percent of the differences in volatility between rich and poor countries can be accounted for by differences in the sectoral composition of the economy (higher concentration and sectoral risk), whereas the other 50 percent is due to country-specific risk.
These characteristics of the development process are inconsistent with previous theoretical explanations of the dynamics of volatility and development. In this paper, the authors provide an alternative theory that is in line with the empirical evidence.
The authors develop an endogenous growth model of technological diversification. In the model, the number of varieties evolves endogenously in response to profit incentives. The consequent change in volatility associated with changes in the number of varieties feeds back into the investment and savings decisions of producers.
The key idea of the model is that firms using a larger variety of inputs can mitigate the impact of shocks affecting the productivity of individual inputs. In order to explore why poorer countries specialize in less sophisticated sectors, the authors extend the model to allow for international mobility of goods and for cross-country differences in endowments.
The model leads to a set of predictions concerning the relationships among productivity, volatility, and technological diversification. The authors discuss these predictions in the light of empirical evidence and then conduct robustness checks.
- Technological complexity both increases average productivity and reduces the volatility of productivity. The expansion of varieties of inputs leads to lower volatility of production via two channels. First, as each individual input matters less in production, productivity becomes less volatile by the law of large numbers. Second, whenever a shock hits a particular input, firms can adjust the use of the other inputs to partially offset the shock.
- More complex sectors are both more productive and less volatile; there is no evidence of a mean-variance frontier. As countries develop, they use more sophisticated technologies, which leads to both higher productivity and lower variance.
- In the multi-sector version of the model, two channels explain the negative association of volatility with development: first, a within-sector channel, whereby a given sector exhibits higher technological complexity in more-developed countries, and, second, a compositional channel, whereby poor countries specialize in relatively less complex sectors.
- Within a sector, in addition to decreasing with increasing technological complexity, volatility also decreases with increasing skill intensity and the size of the sector.
- Countries with high profit rates and low investment costs will develop faster, implying both a faster growth of output and a faster fall in volatility.
- An alternative explanation for the decline of volatility with development is that high-income countries specialize in differentiated products, which are subject to idiosyncratic demand and supply shocks. The authors' findings suggest that "output diversification" does not contribute significantly to the decline of volatility.
The fact that the predictions of the model developed in this paper fit the empirical data better than previous theories suggests that the model may have captured the essential channels whereby increasing technological complexity leads to increasing productivity and decreasing volatility.