1. Eurostat – Unit D1 Key indicators for the European policies Euro-indicators Working Group Luxembourg, 4 th & 5 th December 2008

2. Eurostat – Unit D1 Key indicators for the European policies Item 10.1 of the Agenda General Overview of Eurotrend Activities By Filippo Moauro Doc 248/08

3. Eurostat – Unit D1 Key indicators for the European policies Eurotrend activities of 2007 quality indicators for quality assessment and improvements of PEEIs multivariate temporal disaggregation of time series back-calculation of PEEIs structural VAR models for output gap estimates real time estimates of potential output, output gap NAIRU and the Phillips curve

4. Eurostat – Unit D1 Key indicators for the European policies Quality indicators for quality assessment and improvements of PEEIs Definition of a set of synthetic quality indicators Sophisticated statistical techniques (principal component analysis, cluster analysis, …) The aim is to summarize the main quality aspects of the Euro-IND database A paper on this work has been presented at the European Conference on Quality in Official Statistics held in Rome last June

5. Eurostat – Unit D1 Key indicators for the European policies Multivariate temporal disaggregation of time series The problem deals with the historical reconstruction and nowcasting of economic variables subject to: - a temporal aggregation constraint and - contemporaneous aggregation constraint The problem is approached into a state-space framework

6. Eurostat – Unit D1 Key indicators for the European policies Back-calculation of PEEIs Definition of common guidelines for back-calculation Strategy for:- production - maintenance - validation - quality analysis Elementary and aggregated series treated through a systematic tool Particular focus on: - Labour Cost Index - National Accounts Definition of the strategy to handle the imminent change of the NACE classification

7. Eurostat – Unit D1 Key indicators for the European policies Structural VAR models for output gap estimates SVAR models combine together a robust statistical framework with the ability of integrating alternative economic constraints Economic interpretation within the DSGE models Comparative analysis between results provided by UC models, HP filter, SVAR models under different constraints specifications A paper on this issue presented last June at the international Symposium of Forecasting held in Nice

8. Eurostat – Unit D1 Key indicators for the European policies Real time estimates of potential output, output gap, NAIRU and the Phillips curve Theoretical and empirical methodological assessment of 3 alternative estimation methods: - structural approach - reduced approach assuming the Okun’s law and a VAR model The work proposes an estimation strategy for Eurostat A toolbox documentation Paper presented at the workshop on Computational and and Financial Econometrics Neuchatel last June And at 5-th Eurostat Colloquium last September

9. Eurostat – Unit D1 Key indicators for the European policies Ongoing activities Data mining and nonlinear techniques Multivariate space time benchmarking techniques Combined forecasting methods Non-linear time series models for business cycle analysis

10. Eurostat – Unit D1 Key indicators for the European policies Data mining and nonlinear techniques General overview to the problem of Time Series Data Mining (TSDM) Definition Definition: any algorithms that enumerates patterns from data or fits models on data. Single step of a larger process of knowledge discovery in database (KDD) KDD includes data warehousing, target data selection, data cleaning, pre-processing, transformation, … TSDM in last decades overcomes the traditional view TSDM looks at complex dynamics, outliers, non-linearity Univariate methods employed in TRAMO and TERROR Multivariate methods which looks at common patterns (Dynamic Factor Analysis, GETS and Cluster Analysis)

11. Eurostat – Unit D1 Key indicators for the European policies Multivariate space time benchmarking Methods to handle situations when disaggregation is both temporal and spatial Main focus is the imposition of economically motivated restrictions on the benchmarking method A New Keynesian Phillips Curve (NKPC) is identified through a system of time series including quarterly GDP, monthly inflation and monthly industrial production The aim is to examine whether imposing economically motivated restrictions delivers a gain in the real time estimates of monthly GDP

12. Eurostat – Unit D1 Key indicators for the European policies Combined forecasting methods Two parallel lines of investigation 1)Survey on the theory of forecast combination: - biased/unbiased forecasts assumptions - further extensions (regression and factor framework) - applications on monthly IPI and quarterly GDP 2)General overview of the following issues: - linear methods - estimation of combining weights - large N forecast combining methods - time-variability of weights - non-linear combination methods - application on the Euro-area GDP growth

13. Eurostat – Unit D1 Key indicators for the European policies Nonlinear time series models for business cycle analysis Three relevant issues 1)Forecasting performances of time-varying parameter models: - univatiate methods - estimation, model specification and forecasting - multivariate extension 2)nonlinear models for business cycle analysis: - properties of univariate models - Thresholds, STAR, Logit/Probit and ARCH/GARCH models - multivariate extension 3)Markov-Switching methods - univariate/multivariate approaches - state and parameter inference