Understanding and forecasting aggregate and disaggregate price dynamics
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- Colin Bermingham & Antonello D’Agostino, 2014. "Understanding and forecasting aggregate and disaggregate price dynamics," Empirical Economics, Springer, vol. 46(2), pages 765-788, March.
- D'Agostino, Antonello & Bermingham, Colin, 2010. "Understanding and Forecasting Aggregate and Disaggregate Price Dynamics," Research Technical Papers 8/RT/10, Central Bank of Ireland.
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Citations
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Cited by:
- Edward N. Gamber & Julie K. Smith, 2016. "Time-series measures of core inflation," Working Papers 2016-008, The George Washington University, Department of Economics, Research Program on Forecasting.
- Marco Huwiler & Daniel Kaufmann, 2013. "Combining disaggregate forecasts for inflation: The SNB's ARIMA model," Economic Studies 2013-07, Swiss National Bank.
- repec:erc:cypepr:v:12:y:2018:i:2:p:24-66 is not listed on IDEAS
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting,
Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
- Katarzyna Maciejowska & Rafał Weron, 2015.
"Forecasting of daily electricity prices with factor models: utilizing intra-day and inter-zone relationships,"
Computational Statistics,
Springer, vol. 30(3), pages 805-819, September.
- Katarzyna Maciejowska & Rafal Weron, 2013. "Forecasting of daily electricity prices with factor models: Utilizing intra-day and inter-zone relationships," HSC Research Reports HSC/13/11, Hugo Steinhaus Center, Wroclaw University of Technology.
- Mossfeldt, Marcus & Stockhammar, Pär, 2016. "Forecasting Goods and Services Inflation in Sweden," Working Papers 146, National Institute of Economic Research.
- Mario Marcel & Carlos Medel & Jessica Mena, 2017. "Determinantes de la Inflación de Servicios en Chile," Working Papers Central Bank of Chile 803, Central Bank of Chile.
- Katarzyna Maciejowska & Rafal Weron, 2013. "Forecasting of daily electricity spot prices by incorporating intra-day relationships: Evidence form the UK power market," HSC Research Reports HSC/13/01, Hugo Steinhaus Center, Wroclaw University of Technology, revised 15 Apr 2013.
- Itai Areili & Yakov Babichenko & Rann Smorodinsky, 2017. "Robust Forecast Aggregation," Papers 1710.02838, arXiv.org, revised Feb 2018.
- repec:mbr:jmonec:v:8:y:2013:i:4:p:1-17 is not listed on IDEAS
- Huddleston, Samuel H. & Porter, John H. & Brown, Donald E., 2015. "Improving forecasts for noisy geographic time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1810-1818.
- Tallman, Ellis W. & Zaman, Saeed, 2017.
"Forecasting inflation: Phillips curve effects on services price measures,"
International Journal of Forecasting,
Elsevier, vol. 33(2), pages 442-457.
- Tallman, Ellis W. & Zaman, Saeed, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
- Mihaela SIMIONESCU, 2014. "Improving The Inflation Rate Forecasts Of Romanian Experts Using A Fixed-Effects Models Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 13, pages 87-102, June.
- Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, Elsevier.
- Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
- repec:eee:spacre:v:20:y:2017:i:1:p:95-106 is not listed on IDEAS
- Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers CWP41/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
More about this item
Keywords
aggregation; forecasting; inflation;JEL classification:
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ALL-2011-08-09 (All new papers)
- NEP-CBA-2011-08-09 (Central Banking)
- NEP-ETS-2011-08-09 (Econometric Time Series)
- NEP-FOR-2011-08-09 (Forecasting)
- NEP-MON-2011-08-09 (Monetary Economics)
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