Estimating the underlying change in unemployment in the UK

By Andrew S. Harvey, Chia-Hui Chung. 2000

139 citations recorded by the source corpus.

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Citations in the corpus

Causal Discovery from Temporally Aggregated Time Series (2017, background): “…disaggregation of low resolution time series has been extensively studied in the econometric and statistical literature (Boot et al., 1967; Stram & Wei, 1986; Harvey & Chung, 2000; Moauro & Savio, 2005; Proietti, 2006), which is clearly an even harder problem than discovering causal relations.”
Temporal Disaggregation By State Space Methods: Dynamic Regression Methods Revisited (2006, unknown): “Finally, there are excellent papers covering other methodologies, among which we mention Harvey and Chung (2000) and Moauro and Savio (2002).”
AN INDICATOR OF MONTHLY GDP AND AN EARLY ESTIMATE OF QUARTERLY GDP GROWTH (2005, unknown): “Appendix B sets up the interpolation problem described above in state-space form for comparison purposes with the approach suggested by Harvey and Pierse (1984) and Harvey (1989).”
Temporal Disaggregation Using Multivariate Structural Time Series Models (2005, unknown): “The literature has recently proposed a number of tests for the form of the trend component and for the existence of common factors (see Nyblom and Harvey 2000, 2001).”
Discovering Temporal Causal Relations from Subsampled Data (2015, background): “There has been plenty of work in economics for temporal disaggregation of the low-resolution time series, with or without the side information from related indicators observed at the desired high frequency (Harvey & Chung, 2000; Moauro & Savio, 2005; Proietti, 2006).”