A child health production function estimated from longitudinal data. Cebu Study Team

Collaborating researchers used a multi equation model to analyze 3080 mother-infant pairs living on the island of Cebu in the central Philippines and to estimate a child health production function. The econometric methods used eliminated obstacles such as heterogeneity and endogeneity of significant explanatory factors. They also maximized the longitudinal quality of the data. The results showed that morbidity in 1 period reduced infant weight in following periods. For example, diarrhea and febrile respiratory infection reduced growth in the time period following the illnesses. Further effects of some contributing factors were great near birth not diminished with age. For example, breast feeding promoted growth and protected against infection, especially diarrhea and febrile respiratory infection, more substantially near birth than it did later. Further, in urban areas, preventive health care positively affected growth independently of its indirect influence on reducing respiratory infection. Yet it had little effect on diarrhea. Diarrhea had a strong adverse effect on growth. Exposure of the infant to enteric pathogens had the greatest influence on production of diarrhea. In urban areas, exposure included water supply contamination, exposure to feces, a more pathogenic diet, and community crowding. In rural areas, however, exposure included community crowding and increased rainfall which presumably washed feces into the water supply. Household crowding in both urban and rural areas and irritation from smoke in urban areas only tended to bring about febrile respiratory infection.     

Conjectures, firm characteristics, and market structure : An empirical assessment

This paper makes use of a unique data set to investigate how firms in the Vancouver, British Columbia retail-gasoline market view their rivals and how consumers in turn view these firms. Own- and rival-price elasticities of demand, conjectural variations, and Lerner indices are estimated for thirteen service stations in a submarket of Vancouver. These variables are then related to firm characteristics such as type of ownership, degree of horizontal and vertical integration, and type of service. In this way, systematic patterns in seller behavior and in buyer attitudes are revealed.     

Costs of financial instability, household-sector balance sheets and consumption

Extant work on costs of financial instability focuses on fiscal costs and declines in aggregate GDP following banking crises. We estimate effects of banking and currency crises on consumption in 19 OECD countries, showing consumption plays an important role in the adjustment following a crisis, and effects are not captured solely by the impact of crises on standard consumption determinants, income and wealth. Additional effects, attributable to factors such as time-varying confidence, uncertainty and credit rationing, are aggravated by high and rising leverage, despite financial liberalisation easing liquidity constraints. High leverage implies that banking crises taking place now could have greater incidence than in the past.     

Institutional framing and perceptions of fairness

This paper's goal is to construct a positive theory of economic fairness. Using the theoretical schema developed by Hurwicz and others, the paper makes precise the notions of an “institution,” “fairness fraiming,” and “institutional framing.” Four fairness propositions yield an important corollary: the economic environment, the operative institution and history give meaning to the often used FORMAL PRINCIPLE OF DISTRIBUTIVE JUSTICE (“equals should be treated equally, and unequals unequellay, in proportion to relevant similarities and differences”). We support these four propositions and corollary by an analysis of laboratory, survey, and anecdotal evidence. Finally we describe a number of areas for future research. The authors would like to thank Allen Buchanan, James Buchanan, Joel Feinberg, Elizabeth Hoffman, David Schmitz, Linda Schnabel Stizer, Vernon Smith, Richard Wagner, the participants in the Aspen Institute's Conference on “Local Justice and Fair Allocation”, the members of the Industrial Organization Workshop of the Department of Economics at the University of Arizona, and panel participants at the Public Choice Society Meeting for their help and comments at various stages of this paper's preparation. Responsibility for errors is the authors' alone.     

Measuring Fund Strategy and Performance in Changing Economic Conditions

The use of predetermined variables to represent public information and time-variation has produced new insights about asset pricing models, but the literature on mutual fund performance has not exploited these insights. This paper advocates conditional performance evaluation in which the relevant expectations are conditioned on public information variables. We modify several classical performance measures to this end and find that the predetermined variables are both statistically and economically significant. Conditioning on public information controls for biases in traditional market timing models and makes the average performance of the mutual funds in our sample look better.     

Bayesian time series analysis of periodic behaviour and spectral structure

Analysis, model selection and forecasting in univariate time series models can be routinely carried out for models in which the model order is relatively small. Under an ARMA assumption, classical estimation, model selection and forecasting can be routinely implemented with the Box–Jenkins time domain representation. However, this approach becomes at best prohibitive and at worst impossible when the model order is high. In particular, the standard assumption of stationarity imposes constraints on the parameter space that are increasingly complex. One solution within the pure AR domain is the latent root factorization in which the characteristic polynomial of the AR model is factorized in the complex domain, and where inference questions of interest and their solution are expressed in terms of the implied (reciprocal) complex roots; by allowing for unit roots, this factorization can identify any sustained periodic components. In this paper, as an alternative to identifying periodic behaviour, we concentrate on frequency domain inference and parameterize the spectrum in terms of the reciprocal roots, and, in addition, incorporate Gegenbauer components. We discuss a Bayesian solution to the various inference problems associated with model selection involving a Markov chain Monte Carlo (MCMC) analysis. One key development presented is a new approach to forecasting that utilizes a Metropolis step to obtain predictions in the time domain even though inference is being carried out in the frequency domain. This approach provides a more complete Bayesian solution to forecasting for ARMA models than the traditional approach that truncates the infinite AR representation, and extends naturally to Gegenbauer ARMA and fractionally differenced models.