Volume 6, Issue 2

First, the goals and process of model building, including models for learning from data, explaining the past, predicting as yet unobserved data and making policy decisions are discussed. Then attention is given to the important role of nonlinear, dynamic relations in three of my past and one of my current projects: (1) Evaluation of the world's most famous marine conservation program, (2) Assessing effects on regional growth of proposed dam construction on the Susquehanna River, (3) Consideration of the Federal Reserve-MIT-PENN model of the U.S. economy and (4) Construction and use of the new Marshallian Macroeconomic Model. Last, current work to complete the nonlinear, dynamic Marshallian Macroeconomic Model of an economy is described.

We propose information theoretic tests for serial independence and linearity in time series against nonlinear dependence on lagged variables, based on the conditional mutual information. The conditional mutual information, which is a general measure for dependence, is estimated using the correlation integral from chaos theory. The significance of the test statistics is determined by means of bootstrap methods. The size and power properties of the tests are examined by simulation and illustrated with applications to real US GNP data.

This paper proposes an empirical exploration of the possible asymmetric nature of the preferences of central bankers, with respect to inflation and output targets. The idea underlying this work lies in the widespread belief that central bankers interventions - through changes in a short-term interest rate - are influenced by the state of the current and/or expected state of the business cycle. The GMM estimates of a threshold model support the asymmetric representation of the monetary policy reaction function for recent U.S, French and German data.