Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates
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DOI: 10.26509/frbc-wp-202206
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References listed on IDEAS
- Rossi, Barbara & Sekhposyan, Tatevik, 2019.
"Alternative tests for correct specification of conditional predictive densities,"
Journal of Econometrics, Elsevier, vol. 208(2), pages 638-657.
- Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative tests for correct specification of conditional predictive densities," Economics Working Papers 1416, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2017.
- Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
- Di Fonzo, Tommaso, 1990. "The Estimation of M Disaggregate Time Series When Contemporaneous and Temporal Aggregates Are Known," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 178-182, February.
- Panagiotelis, Anastasios & Athanasopoulos, George & Gamakumara, Puwasala & Hyndman, Rob J., 2021.
"Forecast reconciliation: A geometric view with new insights on bias correction,"
International Journal of Forecasting, Elsevier, vol. 37(1), pages 343-359.
- Anastasios Panagiotelis & Puwasala Gamakumara & George Athanasopoulos & Rob J Hyndman, 2019. "Forecast Reconciliation: A geometric View with New Insights on Bias Correction," Monash Econometrics and Business Statistics Working Papers 18/19, Monash University, Department of Econometrics and Business Statistics.
- Anastasios Panagiotelis & Puwasala Gamakumara & George Athanasopoulos & Rob J Hyndman, 2020. "Forecast Reconciliation: A geometric View with New Insights on Bias Correction," Monash Econometrics and Business Statistics Working Papers 23/20, Monash University, Department of Econometrics and Business Statistics.
- Gefang, Deborah, 2014. "Bayesian doubly adaptive elastic-net Lasso for VAR shrinkage," International Journal of Forecasting, Elsevier, vol. 30(1), pages 1-11.
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Cited by:
- George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Anastasios Panagiotelis, 2023. "Forecast Reconciliation: A Review," Monash Econometrics and Business Statistics Working Papers 8/23, Monash University, Department of Econometrics and Business Statistics.
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More about this item
Keywords
Regional data; Mixed frequency; Nowcasting; Bayesian methods; Real-time data; Vector autoregressions;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2022-04-04 (Econometrics)
- NEP-ETS-2022-04-04 (Econometric Time Series)
- NEP-GEO-2022-04-04 (Economic Geography)
- NEP-MAC-2022-04-04 (Macroeconomics)
- NEP-ORE-2022-04-04 (Operations Research)
- NEP-URE-2022-04-04 (Urban and Real Estate Economics)
Statistics
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