✦ LIBER ✦

Municipal budget forecasting with multivariate ARMA models

✍ Scribed by G. W. Downs; D. M. Rocke

Publisher: John Wiley and Sons
Year: 1983
Tongue: English
Weight: 755 KB
Volume: 2
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.3980020407

No coin nor oath required. For personal study only.

✦ Synopsis

In this paper multivariate ARMA models are applied to the problem of forecasting city budget variables. Unlike univariate time-series methods, multivariate models can use relationships among budget variables as well as relationships with economic and demographic indicators. Although available budget series are shorter than what is usually believed necessary for multivariate ARMA modelling, the forecasts seem to be of higher quality than those from univariate models.

📜 SIMILAR VOLUMES

Forecasting the federal budget with time

Forecasting the federal budget with time-series models

✍ Hamid Baghestani; Robert McNown 📂 Article 📅 1992 🏛 John Wiley and Sons 🌐 English ⚖ 768 KB

The stochastic properties of conventionally defined federal expenditures and revenues are examined, and cointegration is found. Alternative timeseries models-univariate ARIMA models, vector autoregressions in levels and differences, and an error correction model-are specified and estimated using qua

Forecasting large datasets with Bayesian

Forecasting large datasets with Bayesian reduced rank multivariate models

✍ Andrea Carriero; George Kapetanios; Massimiliano Marcellino 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 208 KB

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and compare their predictive performance for US time series with the most promising existing alternatives, namely, factor model

Forecasting with balanced state space re

Forecasting with balanced state space representations of multivariate distributed lag models

✍ Stefan Mittnik 📂 Article 📅 1990 🏛 John Wiley and Sons 🌐 English ⚖ 681 KB

A procedure for estimating state space models for multivariate distributed lag processes is described. It involves singular value decomposition techniques and yields an internally balanced state space representation which has attractive properties. Following the specifications of a forecasting compe

Forecasting multivariate time series wit

Forecasting multivariate time series with linear restrictions using constrained structural state-space models

✍ Gurupdesh S. Pandher 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 280 KB 👁 1 views

## Abstract This paper presents a methodology for modelling and forecasting multivariate time series with linear restrictions using the constrained structural state‐space framework. The model has natural applications to forecasting time series of macroeconomic/financial identities and accounts. The