Using Market Expectations to Test for Speculative Bubbles in the Crude Oil Market

The wide fluctuations of oil prices from 2003 to 2008 have attracted the interest of academics and policymakers. A popular view is that these fluctuations were caused by speculative bubbles due to the increased financialization of oil futures markets. This hypothesis, however, is difficult to examine since the fundamental price of oil is unobservable and, therefore, econometric evidence in favor of bubbles may actually be due to misspecified market fundamentals. In this paper, we extend two recently proposed methodologies for bubble detection that alleviate this problem by using market expectations of future prices. Both methodologies provide no evidence of speculative bubbles.     

Asymptotic confidence bands for the estimated autocovariance and autocorrelation functions of vector autoregressive models

This paper provides closed-form formulae for computing the asymptotic covariance matrices of the estimated autocovariance and autocorrelation functions of stable VAR models by means of the delta method. These covariance matrices can be used to construct asymptotic confidence bands for the estimated autocovariance and autocorrelation functions to assess the underlying estimation uncertainty. The usefulness of the formulae for empirical work is illustrated by an application to inflation and output gap data for the U.S. economy indicating the existence of a significant short-run Phillips-curve tradeoff.First version received: November 2002/Final version received: September 2003     

Breastfeeding versus infant formula: the Kenyan case

An Infant Feeding Practices Study (IFPS) in 1982 in Kenya, which included a cross-sectional survey of a weighted sample of 980 low and middle income Nairobi mothers who had given birth in the previous 18 months, found that most women breastfeed their infants for long periods, but many introduce alternate feeding, especially infant formula, in the 1st 4 months (86 and 50% of the infants were breastfed at 6 and 15 months respectively, but 50% of the 2 month-olds and 63% of the 4 month-olds were receiving substitutes, mostly formula). This is done largely out of the belief that infant formula is an additional health benefit. A workshop to discuss the findings of the IFPS and other available data, and to make policy recommendations urged the adoption of a policy of protection, support and promotion of breastfeeding. Since breastfeeding is already widely prevalent in Kenya, protection of breastfeeding should receive the 1st priority in policy related to infant feeding. Attention should be directed at at least 2 influences which help undermine breastfeeding: widespread availability and promotion of breast milk substitutes. Support for breastfeeding is viewed as the 2nd policy priority. Situations where support can play a helpful role are, women's paid employment outside the home, hospital practices, maternal morbidity, and difficulties in breastfeeding. Since promotion is the least cost effective of the 3 options, and most Kenyan women are already motivated to breastfeed, this should be the last priority. Promotion includes reeduction of mothers to make them better aware of the benefits of breastfeeding. The workshop recommended the dissemination of appropriate information, consisting of standarized messages based on clearcut guidelines, using mass media techniques.     

Estimation of a non-invertible moving average process: The case of overdifferencing

The effect of differencing all of the variables in a properly specified regression equation is examined. Excessive use of the difference transformation induces a non-invertible moving average (MA) process in the disturbances of the transformed regression. Monte Carlo techniques are used to examine the effects of overdifferencing on the efficiency of regression parameter estimates, inferences based on these estimates, and tests for overdifferenccing based on the estimator of the MA parameter for the disturbances of the differences regression. Overall, the problem of overdifferencing is not serious if careful attention is paid to the properties of the disturbances of regression equations.     

Search in cities

The aim of this paper is to expose the recent developments of urban search models which incorporate a land market into a search-matching framework. Using these models, we will be able to explain why unemployment rates vary within a city, how city structure affects workers’ labor-market outcomes, how unemployment benefits and the job-destruction rate affect the growth of cities and why workers living far away from job centers search less intensively and experience higher unemployment rates than those residing closer to jobs. We are also able to explain why, as compared to whites, black workers spend more time commuting to work but travel less miles and search for jobs over a smaller area.