Municipal Budget Forecasting with Multivariate ARMA Models

Article Abstract:

Forecasting city budget variables with multivariate ARMA models means that relationships of budget variables and links of economic and demographic indicators can be figured in, which was not possible to do with univariate approaches. While some of the budget series are not as lengthy as those usually demanded by ARMA modeling, forecasting accuracy is greater than univariate modeling. Two uses of budget forecasting are the impact of revenue changes and the development of a counter-factual forecast for situations where policy changes are evident. The supply of municipal budget data is poor, but data was extracted for both San Diego and Pittsburgh. The sensitivity of highly aggregated models can be greater than disaggregated models as to officials' behavior. Tables of parametric data for both cities are included.

Finance, Municipal government

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Updating ARMA predictions for temporal aggregates

Article Abstract:

A comparison of the performance of two predictors for temporally aggregated series, one based on ARMA Models using aggregated data and the other based on prediction on aggregations based on disaggregated data are presented.

United States

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Average conditional correlation and tree structures for multivariate GARCH models

Article Abstract:

The application of the model confidence set approach, for the comparative analysis of the dynamic conditional correlations and tree structures of multivariate GARCH models, is described.

Switzerland, Usage, Measurement, Economics, Correlation (Statistics), Economic theory

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