Konferenzbeitrag

Empirical Simultaneous Confidence Regions for Path-Forecasts

A probabilistic assessment about the set of possible trajectories that a random variable may follow over time is summarized by the simultaneous confidence region generated from its forecast generating distribution. However, if the null model is only approximative or altogether unavailable, one cannot derive analytic expressions for this confidence region. Moreover, the high-dimensional nature of the forecast generating distribution in such cases makes non-parametric estimation impractical given commonly available predictive samples. Instead, this paper derives the approximate rectangular confidence regions that control false discovery rate error, which are a function of the predictive sample covariance matrix and the empirical distribution of the Mahalanobis distance of the path-forecast errors. These rectangular regions are simple to construct and appear to work well in a variety of cases explored empirically and by simulation.

Language
Englisch

Bibliographic citation
Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie - Session: Advances in Time Series Analysis ; No. B6-V1

Classification
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Model Evaluation, Validation, and Selection
Forecasting Models; Simulation Methods
Subject
path forecast
forecast uncertainty
simultaneous confidence region
Scheffé's S-method
Mahalanobis distance
false discovery rate

Event
Geistige Schöpfung
(who)
Knüppel, Malte
Jordà, Òscar
Marcellino, Massimiliano
Event
Veröffentlichung
(who)
Verein für Socialpolitik
(where)
Frankfurt a. M.
(when)
2010

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Konferenzbeitrag

Associated

  • Knüppel, Malte
  • Jordà, Òscar
  • Marcellino, Massimiliano
  • Verein für Socialpolitik

Time of origin

  • 2010

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