In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

http://www.long-memory.com/volatility/Baillie1996.pdf

Long memory processes and fractional integration in econometrics

Econometric policy evaluation: A critique

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Likelihood Based Inference In Cointegrated Vector Autoregressive Models

An exact form of the local Whittle likelihood is studied with the intent of developing a general purpose estimation procedure for the memory parameter (d) that applies throughout the stationary and nonstationary regions of d and which does not rely on tapering or differencing prefilters. The resulting exact local Whittle estimator is shown to be consistent and to have the same N(0,1/4) limit distribution for all values of d.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID311511_code020531590.pdf?abstractid=311511

Exact Local Whittle Estimation of Fractional Integration

We examine monthly inflation rates of five industrial countries. The application of tests against stationarity as well as tests against a unit root yield contradictory results. Thus fractional integration allowing for long memory is a plausible model. We discuss and apply the periodogram regression to estimate the difference parameters. For all countries we find estimates significantly different from 1 as well as from 0. This is evidence in favor of long memory. Specification tests and maximum likelihood estimates support the fitted models. Finally, we relate our empirical results to the construction of the data.

Long Memory in Inflation Rates: International Evidence

On the power of unit root tests against fractional alternatives

An error correction model for the demand for real M3 money is constructed for the period of 1976–1994 with real GNP, the GNP deflator, as well as a short-term and a long-term interest rate as explanatory variables. Quarterly, seasonally unadjusted data are used in estimating the model. It is found that there is a clear structural break due to the German unification in 1990. On the other hand, once this structural break is accounted for, a stable relation is found which resists a series of specification tests. These include a number of recent tests of parameter constancy and linearity. Our specification is at variance with findings reported by some other researchers, notably the Deutsche Bundesbank.

https://www.jstor.org/stable/info/2646748

Modeling the Demand for M3 in the Unified Germany

A growing body of literature argues that the financial cycle is considerably longer in duration and larger in amplitude than the business cycle and that its distinguishing features became more pronounced over time. This paper proposes an empirical approach suitable to test these hypotheses. We parametrically estimate the whole spectrum of financial and real variables to obtain a complete picture of their cyclical properties. We provide strong statistical evidence for the US and slightly weaker evidence for the UK validating the hypothesized features of the financial cycle. In Germany, however, the financial cycle is, if at all, much less visible.

/pdf/characterizing-the-financial-cycle-evidence-from-a-frequency-2biflvy3aq.pdf

Characterizing the Financial Cycle: Evidence from a Frequency Domain Analysis

Using Swiss data from 1983 to 2008, this paper investigates whether growth rates of the different measures of the quantity of money and or excess money can be used to forecast inflation. After a preliminary data analysis, money demand relations are specified, estimated and tested. Then, employing error correction models, measures of excess money are derived. Using recursive estimates, indicator properties of monetary aggregates for inflation are assessed for the period from 2000 onwards, with time horizons of one, two, and three years. In these calculations, M2 and M3 clearly outperform M1, and excess money is generally a better predictor than the quantity of money. Taking into account also the most (available) recent observations that represent the first three quarters of the economic crisis, the money demand function of M3 remains stable while the one for M2 is strongly influenced by these three observations. While in both cases forecasts for 2010 show inflation rates inside the target zone between zero and two percent, and the same holds for forecasts based on M3 for 2011, forecasts based on M2 provide evidence that the upper limit of this zone might be violated in 2011.

https://link.springer.com/content/pdf/10.1007%2FBF03399304.pdf

Jürgen Wolters

Papers

Long Memory in Inflation Rates: International Evidence

On the power of unit root tests against fractional alternatives

Modeling the Demand for M3 in the Unified Germany

Characterizing the Financial Cycle: Evidence from a Frequency Domain Analysis

The role of monetary aggregates in the policy analysis of the swiss national bank