UN/Eurostat Handbook on Rapid Estimates: Status and way forward
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1 UN/Eurostat Handbook on Rapid Estimates: Status and way forward By: Gian Luigi Mazzi - European Commission/ DG Eurostat Copenhagen, 13 September 2016 CIRET pre-conference Workshop on Rapid Estimates
2 1. Aim Providing a comprehensive view of statistical and econometric techniques to produce rapid estimates Consistently with the glossary classification Very didactical presentation of methods and techniques Advanced techniques also presented in detail Mixed frequency models Internationally recognized authors 2
3 1. Aim Facilitating the identification of best practices to produce various types of rapid estimates Focusing also on communication and dissemination aspects Targeting a large public Official statisticians Academics Researchers Students 3
4 2.Structure and content of the handbook Part I Generalities Chapter 1: Introduction: objectives, definitions, costs and benefits of rapid estimates. D. Ladiray, G.L. Mazzi Status: To be prepared at the end. Chapter 2: Rapid estimates: different products for different purposes R. Ruggeri Cannata, G.L. Mazzi Annex: Glossary of rapid estimates (Barcellan, Hecq, Mazzi, Ruggeri)
5 Chapter 3: Forecasting and nowcasting macroeconomic variables: a methodological overview J. Castle, D. Hendry, O. Kitov Chapter 4: The trade-off between timeliness and reliability: the perspective of a statistical agency. G.L. Mazzi and R. Ruggeri Cannata Status: Ongoing.
6 Part II: Statistical and econometric techniques for rapid estimates Chapter 5: An overview of modelling techniques for rapid estimates D. Ladiray, G. L. Mazzi and R. Gatto Chapter 6: A review of parametric and non-parametric techniques for variable selection D. Ladiray Chapter 7: Model selection, model specifications and a typology of rapid estimates D. Ladiray, J. Mitchell, F. Bacchini
7 PART III: Rapid estimates based on data available at different frequencies Chapter8: Multivariate Temporal Disaggregation G. L. Mazzi, T. Proietti Chapter 9: A Survey of Econometric Methods for Mixed-Frequency Data M. Marcellino, C.Foroni
8 PART IV: Rapid estimated based on factor models Chapter 10: Dynamic Factor Models: A Review of the Literature K.Barhoumi, O.Darné, L.Ferrara Status:Done. Chapter 11: Forecasting with Rich Data: Model Comparison and Evidence from European Countries G. Kapetanios, G. L. Mazzi, K. Petrova
9 PART V: Rapid estimates based on combining forecasting techniques Chapter 12: Combined Forecasting Methods and Rapid Estimates M. Marcellino Status:Done. Chapter 13: Combining forecasting techniques: some empirical considerations F. Charpin and G.L. Mazzi Chapter 14: Combined nowcasts S. Luiand J. Mitchell
10 PART VI: Aggregate versus disaggregate approaches to construct rapid estimates Chapter 15: Aggregate versus disaggregate approaches to construct rapid estimates S. Lui, G. L. Mazzi and J. Mitchell Status:Done.
11 PART VII: Constructing and evaluating rapid estimates Chapter 16: Quality assessment of rapid estimates D. Ladiray, G. L. Mazzi Chapter 17: Constructing and evaluating rapid estimates: some examples G.L. Mazzi and R. Ruggeri Cannata Status: Ongoing.
12 PART VIII: Big data and rapid estimates Chapter 18: Challenges of using big data to construct rapid estimates G. Kapetanios, M. Marcellino, G.L. Mazzi Status: Almostdone. Chapter 19: Some guidance on the use of big data for constructing rapid estimates G. Kapetanios, M. Marcellino, G.L. Mazzi Status: Almostdone.
13 PART IX: Guidelines for the construction of rapid estimates Chapter 20: Aim and scope of the guidelines G.L. Mazzi and R. Ruggeri Status: To be preparedatthe end. Chapter 21: The guidelines for the construction of rapid estimates D. Ladiray, G.L. Mazzi, R. Ruggeri Status: To be preparedatthe end.
14 3. Way forward Handbook already submitted to expert consultation with very positive feedback and comments Proposed changes under implementation Global consultation to be foreseen by end of October onwards Suggestedimprovementsimplementedas soonas they will become available Publication foreseen in the first Quarter 2017
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