Volatility and Development
By Miklós Koren, Silvana Tenreyro. 2007
629 citations recorded by the source corpus.
Why is GDP growth so much more volatile in poor countries than in rich ones? We identify four possible reasons: (i) poor countries specialize in more volatile sectors; (ii) poor countries specialize in fewer sectors; (iii) poor countries experience more frequent and more severe aggregate shocks (e.g. from macroeconomic policy); and (iv) poor countries' macroeconomic fluctuations are more highly correlated with the shocks of the sectors they specialize in. We show how to decompose volatility into these four sources, quantify their contribution to aggregate volatility, and study how they relate to the stage of development. We document the following regularities. First, as countries develop, their productive structure moves from more volatile to less volatile sectors. Second, the level of specialization declines with development at early stages, and slowly increases at later stages of development. Third, the volatility of country-specific macroeconomic shocks falls with development. Fourth, the covariance between sector-specific and country-specific shocks does not vary systematically with the level of development. We argue that many theories linking volatility and development are not consistent with these findings and suggest new directions for future theoretical work.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/49b4dcf7e814cecd560c6510965e81f2707583d7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Eduardo A. Cavallo
- Olivier Cadot
- Scott R. Baker
- J.M.C. Santos Silva
- I. Mihov
- Antonio Fatás
- Silvana Tenreyro
- Céline Carrère
In Finance
- J.M.C. Santos Silva
- I. Mihov
- Antonio Fatás
- Olivier Cadot
- Céline Carrère
- Vanessa Strauss-Kahn
- Nicholas Bloom
- Eduardo A. Cavallo
Citations in the corpus
- Currency unions in prospect and retrospect (2010, positive): “Because more developed and bigger economies tend to be more diversified (Koren & Tenreyro, 2007), Kenen (1969)'s OCA criterion points to a completely different set of ideal candidates for unification than McKinnon (1963)'s. Put differently, the list of countries that do not satisfy either of these…”
- The Geography of Output Volatility (2009, neutral): “[64] Koren, M.”
- Large Capital Inflows, Sectoral Allocation and Economic Performance (2015, background): “Presumably this pattern reflects the fact that 11Since industry-level deflators are not available for a broad set of countries, the alternate approach taken by Koren and Tenreyro (2007) is to use US industry-level deflators.”
- Trade Diversification, Income, and Growth: What Do We Know? (2013, positive): “Using different data, Koren and Tenreyro (2007) confirmed the existence of a U-shaped relationship between the concentration of production and the level of development.”
- Does Uncertainty Reduce Growth? Using Disasters as Natural Experiments (2013, background): “Other related growth papers include Barro (1991) who finds a negative relationship between growth and political instability, Koren and Tenreyro (2007) who find strongly negative correlations between growth and the volatility of country level macro shocks, and Engel and Rangel (2008) who show a…”
- Policy Volatility, Institutions, and Economic Growth (2013, methodology): “Woo (2009) presents evidence suggesting that countries that run a more procyclical fiscal 26 Koren and Tenreyro (2007) also document that the volatility of countryspecific shocks, which they interpret as policy shocks or political stability, is more important for the overall macroeconomic…”
- Output Volatility and Openness to Trade: A Reassessment (2009, background): “In particular, Koren and Tenreyro (2005) show that the correlation of sectoral shocks between low-trade and high-trade countries is very high, suggesting that more open economies do not face different exposure.”
- Firms, Destinations, and Aggregate Fluctuations (2014, neutral): “…using quintile dummies, since that allows for greater (non-parametric) flexibility in the estimation. where wjnt−1 is the share of sector j’s sales to market n in total sales of French firms to all sectors and destinations, and wfnt−1 is the share of firm f ’s sales to destination n in total sales.”