Heterogeneity and Microeconometrics Modelling

Presented at the 2005 Econometric Society World Congress Plenary Session on "Modelling Heterogeneity". We survey the treatment of heterogeneity in applied microeconometrics analyses. There are three themes. First, there is usually much more heterogeneity than empirical researchers allow for. Second, the inappropriate treatment of heterogeneity can lead to serious error when estimating outcomes of interest. Finally, once we move away from the traditional linear model with a single 'fixed effect', it is very difficult to account for heterogeneity and fit the data and maintain coherence with theory structures. The latter task is one for economists: "heterogeneity is too important to be left to the statisticians". The paper concludes with a report of our own research on dynamic discrete choice models that allow for maximal heterogeneity.heterogeneity; applied microeconometrics; fixed effects; dyanamic discrete choice

Going beyond energy intensity to understand the energy metabolism of nations: The case of Argentina

The link between energy consumption and economic growth has been widely studied in the economic literature. Understanding this relationship is important from both an environmental and a socio-economic point of view, as energy consumption is crucial to economic activity and human environmental impact. This relevance is even higher for developing countries, since energy consumption per unit of output varies through the phases of development, increasing from an agricultural stage to an industrial one and then decreasing for certain service based economies. In the Argentinean case, the relevance of energy consumption to economic development seems to be particularly important. While energy intensity seems to exhibit a U-Shaped curve from 1990 to 2003 decreasing slightly after that year, total energy consumption increases along the period of analysis. Why does this happen? How can we relate this result with the sustainability debate? All these questions are very important due to Argentinean hydrocarbons dependence and due to the recent reduction in oil and natural gas reserves, which can lead to a lack of security of supply. In this paper we study Argentinean energy consumption pattern for the period 1990-2007, to discuss current and future energy and economic sustainability. To this purpose, we developed a conventional analysis, studying energy intensity, and a non conventional analysis, using the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) accounting methodology. Both methodologies show that the development process followed by Argentina has not been good enough to assure sustainability in the long term. Instead of improving energy use, energy intensity has increased. The current composition of its energy mix, and the recent economic crisis in Argentina, as well as its development path, are some of the possible explanations.Argentina, energy intensity; energy mix; economic development; societal metabolism, integrated analysis

Dynamic binary outcome models with maximal heterogeneity

Most econometric schemes to allow for heterogeneity in micro behaviour have two drawbacks: they do not fit the data and they rule out interesting economic models. In this paper we consider the time homogeneous first order Markov (HFOM) model that allows for maximal heterogeneity. That is, the modelling of the heterogeneity does not impose anything on the data (except the HFOM assumption for each agent) and it allows for any theory model (that gives a HFOM process for an individual observable variable). `Maximal' means that the joint distribution of initial values and the transition probabilities is unrestricted. We establish necessary and sufficient conditions for the point identification of our heterogeneity structure and show how it depends on the length of the panel. A feasible ML estimation procedure is developed. Tests for a variety of subsidiary hypotheses such as the assumption that marginal dynamic effects are homogeneous are developed. We apply our techniques to a long panel of Danish workers who are very homogeneous in terms of observables. We show that individual unemployment dynamics are very heterogeneous, even for such a homogeneous group. We also show that the impact of cyclical variables on individual unemployment probabilities differs widely across workers. Some workers have unemployment dynamics that are independent of the cycle whereas others are highly sensitive to macro shocks.Discrete choice, Markov processes, Nonparametric identification, Unemployment dynamics