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Keywords:Missing data 

Working Paper
Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting

Interest in regional economic issues coupled with advances in administrative data is driving the creation of new regional economic data. Many of these data series could be useful for nowcasting regional economic activity, but they suffer from a short (albeit constantly expanding) time series which makes incorporating them into nowcasting models problematic. Regional nowcasting is already challenging because the release delay on regional data tends to be greater than that at the national level, and "short" data imply a "ragged edge" at both the beginning and the end of regional data sets, ...
Working Papers , Paper 23-09

Working Paper
Missing Data Substitution for Enhanced Robust Filtering and Forecasting in Linear State-Space Models

Replacing faulty measurements with missing values can suppress outlier-induced distortions in state-space inference. We therefore put forward two complementary methods for enhanced outlier-robust filtering and forecasting: supervised missing data substitution (MD) upon exceeding a Huber threshold, and unsupervised missing data substitution via exogenous randomization (RMDX).Our supervised method, MD, is designed to improve performance of existing Huber-based linear filters known to lose optimality when outliers of the same sign are clustered in time rather than arriving independently. The ...
Finance and Economics Discussion Series , Paper 2025-001

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Dobrev, Dobrislav 1 items

Koop, Gary 1 items

McIntyre, Stuart 1 items

Mitchell, James 1 items

Poon, Aubrey 1 items

Szerszen, Pawel J. 1 items

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