Although economists have long been aware of Jensen's inequality, many econometric applications have neglected an important implication of it: under heteroskedasticity, the parameters of log-linearized models estimated by OLS lead to biased estimates of the true elasticities. We explain why this problem arises and propose an appropriate estimator. Our criticism of conventional practices and the proposed solution extend to a broad range of applications where log-linearized equations are estimated. We develop the argument using one particular illustration, the gravity equation for trade. We find significant differences between estimates obtained with the proposed estimator and those obtained with the traditional method. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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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.

We estimate the impulse response of key US macro series to the monetary policy shocks identified by Romer and Romer (2004), allowing the response to depend flexibly on the state of the business cycle. We find strong evidence that the effects of monetary policy on real and nominal variables are more powerful in expansions than in recessions. The magnitude of the difference is particularly large in durables expenditure and business investment. The effect is not attributable to differences in the response of fiscal variables or the external finance premium. We find some evidence that contractionary policy shocks have more powerful effects than expansionary shocks. But contractionary shocks have not been more common in booms, so this asymmetry cannot explain our main finding. JEL classifications: E52, E32Keywords: asymmetric effects of monetary policy, transmission mechanism, recession, durable goods, local projection methods.

We extend the simulation results given in Santos-Silva and Tenreyro (2006, 'The Log of Gravity', The Review of Economics and Statistics, 88, 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 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means without the prior permission in writing of the publisher nor be issued to the public or circulated in any form other than that in which it is published.Requests for permission to reproduce any article or part of the Working Paper should be sent to the editor at the above address.

What is the effect of nominal exchange rate variability on trade? I argue that the methods conventionally used to answer this perennial question are plagued by a variety of sources of systematic bias. I propose a novel approach that simultaneously addresses all of these biases, and present new estimates from a broad sample of countries from 1970 to 1997. The answer to the question is "Zero:" Nominal exchange rate variabibily has no impact on trade flows.

Every year housing markets in the United Kingdom and the United States experience systematic above-trend increases in both prices and transactions during the second and third quarters (the "hot season") and below-trend falls during the fourth and …rst quarters (the "cold season"). House price seasonality poses a challenge to existing models of the housing market. To explain seasonal patterns, this paper develops a matching model that emphasizes the role of match-speci…c quality between the buyer and the house and the presence of thickmarket e¤ects in housing markets. It shows that a small, deterministic driver of seasonality can be ampli…ed and revealed as deterministic seasonality in transactions and prices, quantitatively mimicking the seasonal ‡uctuations in transactions and prices observed in the United Kingdom and the United States.

Emerging economies, particularly those dependent on commodity exports, are prone to highly disruptive economic cycles. This paper proposes a small open economy model for a net commodity exporter to quantitatively study the triggers of these cycles. The economy consists of two sectors, one of which produces commodities with prices subject to exogenous international fluctuations. These fluctuations affect both the competitiveness of the economy and its borrowing terms, as higher commodity prices are associated with lower spreads between the country's borrowing rate and world interest rates. Both effects jointly result in strongly positive effects of commodity price increases on GDP, consumption and investment, and a negative effect on the total trade balance. Furthermore, they generate excess volatility of consumption over output and a large volatility of investment. The model structure nests various candidate sources of shocks proposed in previous work on emerging economy business cycles. Estimating the model on Argentine data, we find that the contribution of commodity price shocks to fluctuations in post-1950 output growth is in the order of 38%. In addition, commodity prices account for around 42% and 61% of the variation in consumption and investment growth, respectively. We find transitory productivity shocks to be an important driver of output fluctuations, exceeding the contribution of shocks to the trend, which is smaller, although not negligible.