Research Database

The paper discusses a new, fully recursive approach to the adaptive modeling, forecasting and seasonal adjustment of nonstationary economic time-series. The procedure is based around a time variable parameter (TVP) version of the well known “component” or “structural” model. It employs a novel method of sequential spectral decomposition (SSD), based on recursive state-space smoothing, to decompose the series into a number of quasi-orthogonal components. This SSD procedure can be considered as a complete approach to the problem of model identification and estimation, or it can be used as a first step in maximum likelihood estimation. Finally, the paper illustrates the overall adaptive approach by considering a practical example of a UK unemployment series which exhibits marked nonstationarity caused by various economic factors.

This article argues that fiat money’s only technological role in an economy is to act as societal memory: money allows people to credibly record some aspects of their transactions and make that record accessible to other people. This record-keeping role is demonstrated in the three standard paradigms of fiat money: the overlapping generations, turnpike, and search models. In these models, if a new economy is created by removing the money and replacing it only with a historical record of all transactions, known to everyone in the economy, then the original monetary allocation is still achievable as an equilibrium.

A version of the Diamond-Dybvig model of banking is used to evaluate the narrow banking proposal, the idea that banks should be required to back demand deposits entirely by safe short-term assets. It is shown that the mere existence of an amount of safe short-term assets outside the banking system that exceeds banking system liabilities does not make the proposal either innocuous or desirable. In fact, despite such existence, using narrow banking to cope with banking system illiquidity eliminates the role of the banking system.