Volatility and Development

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.volatility, specialization, diversification, development, economic fluctuations.

Wage Setting Patterns and Monetary Policy: International Evidence

Systematic differences in the timing of wage setting decisions among industrialized countries provide an ideal framework to study the importance of wage rigidity in the transmission of monetary policy. The Japanese Shunto presents the most well-known case of bunching in wage setting decisions: From February to May, most firms set wages that remain in place until the following year; wage rigidity, thus, is relatively higher immediately after the Shunto. Similarly, in the United States, a large fraction of firms adjust wages in the last quarter of the calendar year. In contrast, wage agreements in Germany are well-spread within the year, implying a relatively uniform degree of rigidity. We exploit variation in the timing of wagesetting decisions within the year in Japan, the United States, Germany, the United Kingdom, and France to investigate the effects of monetary policy under different degrees of effective wage rigidity. Our findings lend support to the long-held, though scarcely tested, view that wage-rigidity plays a key role in the transmission of monetary policy.monetary policy, wage rigidity, seasonality

Technological diversification

Economies at early stages of development are often shaken by abrupt changes in growth rates, whereas in advanced economies growth rates tend to be relatively stable. To explain this pattern, we propose a theory of technological diversification. Production makes use of different input varieties, which are subject to imperfectly correlated shocks. Technological progress takes the form of an increase in the number of varieties, raising average productivity. In addition, the expansion in the number of varieties in our model provides diversification benefits against variety-specific shocks and it can hence lower the volatility of output growth. Technological complexity evolves endogenously in response to profit incentives. The decline in volatility thus arises as a by-product of firms’ incentives to increase profits and is hence a likely outcome of the development process. We quantitatively asses the predictions of the model in light of the empirical evidence and find that for reasonable parameter values, the model can generate a decline in volatility with the level of development comparable to that in the data.

Is Poland the Next Spain?

We revisit Western Europe's record with labor-productivity convergence, and tentatively extrapolate its implications for the future path of Eastern Europe. The poorer Western European countries caught up with the richer ones through both higher rates of physical capital accumulation and greater total factor productivity gains. These (relatively) high rates of capital accumulation and TFP growth reflect convergence along two margins. One margin (between industry) is a massive reallocation of labor from agriculture to manufacturing and services, which have higher capital intensity and use resources more efficiently. The other margin (within industry) reflects capital deepening and technology catch-up at the industry level. In Eastern Europe the employment share of agriculture is typically quite large, and agriculture is particularly unproductive. Hence, there are potential gains from sectoral reallocation. However, quantitatively the between-industry component of the East's income gap is quite small. Hence, the East seems to have only one real margin to exploit: the within-industry one. Coupled with the fact that within-industry productivity gaps are enormous, this suggests that convergence will take a long time. On the positive side, however, Eastern Europe already has levels of human capital similar to those of Western Europe. This is good news because human capital gaps have proved very persistent in Western Europe's experience. Hence, Eastern Europe does start out without the handicap that is harder to overcome.

Technological diversification

Why is GDP so much more volatile in poor countries than in rich ones? To answer this question, we propose a theory of technological diversification. Production makes use of different input varieties, which are subject to imperfectly correlated shocks. As in endogenous growth models, technological progress increases the number of varieties, raising average productivity. In our model, the expansion in the number of varieties provides diversification benefits against variety-specific shocks and it hence lowers the volatility of output. Technological complexity evolves endogenously in response to profit incentives. Complexity (and hence output stability) is positively related with the development of the country, the comparative advantage of the sector, and the sector’s skill and technology intensity. Using sector-level data for a broad sample of countries, we provide extensive empirical evidence confirming the cross-country and cross-sectoral predictions of the model. JEL Classification: O11, O14, O41, E32diversification, economic fluctuations, specialization, technology choice

Is Poland the Next Spain?

We revisit Western Europe's record with labor-productivity convergence, and tentatively extrapolate its implications for the future path of Eastern Europe. The poorer Western European countries caught up with the richer ones through both higher rates of physical capital accumulation and greater total factor productivity gains. These (relatively) high rates of capital accumulation and TFP growth reflect convergence along two margins. One margin (between industry) is a massive reallocation of labor from agriculture to manufacturing and services, which have higher capital intensity and use resources more efficiently. The other margin (within industry) reflects capital deepening and technology catchup at the industry level. In Eastern Europe the employment share of agriculture is typically quite large, and agriculture is particularly unproductive. Hence, there are potential gains from sectoral reallocation. However, quantitatively the between-industry component of the East's income gap is quite small. Hence, the East seems to have only one real margin to exploit: the within industry one. Coupled with the fact that within-industry productivity gaps are enormous, this suggests that convergence will take a long time. On the positive side, however, Eastern Europe already has levels of human capital similar to those of Western Europe. This is good news because human capital gaps have proved very persistent in Western Europe's experience. Hence, Eastern Europe does start out without the handicap that is harder to overcome.Economic integration, economic growth, labor, technology, productivity gaps, Europe

The timing of monetary policy shocks

A vast empirical literature has documented delayed and persistent effects of monetary policy shocks on output. We show that this finding results from the aggregation of output impulse responses that differ sharply depending on the timing of the shock: When the monetary policy shock takes place in the first two quarters of the year, the response of output is quick, sizable, and dies out at a relatively fast pace. In contrast, output responds very little when the shock takes place in the third or fourth quarter. We propose a potential explanation for the differential responses based on uneven staggering of wage contracts across quarters. Using a stylized dynamic general equilibrium model, we show that a very modest amount of uneven staggering can generate differences in output responses similar to those found in the data.Monetary policy

In brief: Hot and cold seasons in the housing market

The difference in the price you pay for the same house in the summer and in the winter is huge, according to Rachel Ngai and Silvana Tenreyro.

Further simulation evidence on the performance of the Poisson pseudo-maximum likelihood estimator

We extend the simulation results given in Santos Silva and Tenreyro (2006, �The log of gravity,� The Review of Economics and Statistics, 88, 641-658) by considering data generated as a finite mixture of gamma variates. Data generated in this way can naturally have a large proportion of zeros and is fully compatible with constant elasticity models such as the gravity equation. Our results confirm that the Poisson pseudo maximum likelihood estimator is generally well behaved.