Growth Economics and Reality

This paper questions current empirical practice in the study of growth. We argue that much of the modern empirical growth literature is based on assumptions concerning regressors, residuals, and parameters which are implausible both from the perspective of economic theory as well as from the perspective of the historical experiences of the countries under study. A number of these problems are argued to be forms of violations of an exchangeability assumption which underlies standard growth exercises. We show that relaxation of these implausible assumptions can be done by allowing for uncertainty in model specification. Model uncertainty consists of two types: theory uncertainty, which relates to which growth determinants should be included in a model, and heterogeneity uncertainty, which relates to which observations in a data set comprise draws from the same statistical model. We propose ways to account for both theory and heterogeneity uncertainty. Finally, using an explicit decision-theoretic framework, we describe how one can engage in policy-relevant empirical analysis.

Elements of a Theory of Design Limits to Optimal Policy

This paper presents a framework for understanding the limits that exist in optimal policy design in dynamic contexts. We consider the design of policies in the context of dynamic linear models. Fundamental design limits exist for policy rules in such environments in the sense that any policy rule embodies tradeoffs between the magnitudes of different frequency-specific components of the variance. Hence policies that are effective in eliminating low frequency variance components of a state variable can only do so at the cost of exacerbating high frequency variance components, and vice versa. Examples of the implications of such tradeoffs are considered.

Discrete Choice with Social Interactions I: Theory

This paper provides an analysis of aggregate behavioral outcomes when individual utility exhibits social interaction effects. We study generalized logistic models of individual choice which incorporate terms reflecting the desire of individuals to conform to the behavior of others in an environment of noncooperative decisionmaking. Laws of large numbers are generated in such environments. Multiplicity of equilibria in these models, which are equivalent to the existence of multiple self-consistent means for average choice behavior, will exist when the social interactions exceed a particular threshold. Local stability of these multiple equilibria is also studied. The properties of the noncooperative economy are contrasted with the properties of an economy in which a social planner determines the set of individual choices. The model is additionally shown to be well suited to explaining a number of empirical phenomena, such as threshold effects in individual behavior, ethnic group fixed effects of income equations, and large cross-group differences in binary choice behavior.

A Dynamic Structural Model for Stock Return Volatility and Trading Volume

This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process itself. Returns and volume data argue, in the context of our model, that persistent volatility is caused by traders experimenting with different beliefs based upon past profit experience and their estimates of future profit experience. A major theme of our paper is to introduce adaptive agents in the spirit of Sargent (1993) but have them adapt their strategies on a time scale that is slower than the time scale on which the trading process takes place. This will lead to positive autocorrelation in volatility and volume on the time scale of the trading process which generates returns and volume data. Positive autocorrelation of volatility and volume is caused by persistence of strategy patterns that are associated with high volatility and high volume. Thee following features seen in the data: (i) The autocorrelation function of a measure of volatility such as squared returns or absolute value of returns is positive with a slowly decaying tail. (ii) The autocorrelation function of a measure of trading activity such as volume or turnover is positive with a slowly decaying tail. (iii) The cross correlation function of a measure of volatility such as squared returns is about zero for squared returns with past and future volumes and is positive for squared returns with current volumes. (iv) Abrupt changes in prices and returns occur which are hard to attach to 'news.' The last feature is obtained by a version of the model where the Law of Large Numbers fails in the large economy limit.

The Kindergarten Rule of Sustainable Growth

The relationship between economic growth and the environment is not well understood: we have only limited understanding of the basic science involved and very limited data. Because of these difficulties it is especially important to develop a series of relatively simple theoretical models that generate stark predictions. This paper presents one such model where societies implement the Kindergarten rule of sustainable growth.' Following the Kindergarten rule means implementing zero emission technologies in either finite time or asymptotically. The underlying simplicity of the model allows us to provide new predictions linking the path of environmental quality to pollutant characteristics (stocks vs. flows; toxics vs. irritants) and primitives of the economic system. It also provides a novel Environmental Catch-up Hypothesis.

Economic Growth and the Environment: A Review of Theory and Empirics

This paper reviews both theory and empirical work on economic growth and the environment. We develop four simple growth models to help us identify key features generating sustainable growth. We show how some combination of technological progress in abatement, intensified abatement, shifts in the composition of national output and induced innovation are necessary for sustainable growth, and then demonstrate how growth models employing any one of these mechanisms generate other potentially refutable predictions on abatement costs, pollution levels, or emission intensities.

Multinomial Choice with Social Interactions

This paper develops a model of individual decisionmaking in the presence of social interactions when the number of available choices is finite. We show how a multinomial logit model framework may be used to model such decisions in a way that permits a tight integration of theory and econometrics. Conditions are given under which aggregate choice behavior in a population exhibits multiple self-consistent equilibria. An econometric version of the model is shown to be identified under relatively weka conditions. That analysis is extended to allow for general error distributions and some preliminary ways to account for the endogeneity of group memberships are developed.

Pathways to randomness in the economy: Emergent nonlinearity and chaos in economics and finance

This paper: (1) Gives a general argument why research on nonlinear science in general and chaos in particular is important in economics and finance. (2) Puts forth two definitions of stochastic nonlinearity (IID-Linearity and MDS-Linearity) for nonlinear time series analysis and argues for their usefulness as organizing concepts not only for discussion of nonlinearity testinf but also for building a new class of structural asset pricing models. (3) Shows how to use ideas from interacting particle systems theory to build structural asset pricing models that turn IID-Linear or MDS-Linear earnings processes into non MDS-Linear equilibrium returns processes.

Model Uncertainty and Policy Evaluation: Some Theory and Empirics

This paper explores ways to integrate model uncertainty into policy evaluation. We first describe a general framework for the incorporation of model uncertainty into standard econometric calculations. This framework employs Bayesian model averaging methods that have begun to appear in a range of economic studies. Second, we illustrate these general ideas in the context of assessment of simple monetary policy rules for some standard New Keynesian specifications. The specifications vary in their treatment of expectations as well as in the dynamics of output and inflation. We conclude that the Taylor rule has good robustness properties, but may reasonably be challenged in overall quality with respect to stabilization by alternative simple rules that also condition on lagged interest rates, even though these rules employ parameters that are set without accounting for model uncertainty.