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Níl an t-ábhar seo ar fáil i nGaeilge.

Istvan Vincze

9 December 2014
STATISTICS PAPER SERIES - No. 6
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Abstract
This paper models industrial new orders across European Union (EU) Member States for various breakdowns. A common modelling framework exploits both soft data (business opinion surveys) and hard data (industrial turnover). The estimates show for about 200 cases that the model determinants significantly help in explaining monthly growth rates for new orders. An alternative estimation method, different model specifications and out-of-sample and real-time forecasting all show that the model results are robust. We present real-time outcomes of a European Central Bank (ECB) indicator on industrial new orders at an aggregated euro area level. This indicator is largely based on national new orders data and on estimates yielded by the model for those countries that no longer report new orders at the national level. Finally, we demonstrate the leading nature of the ECB indicator on euro area new orders in relation to industrial production.
JEL Code
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
Annexes
26 June 2013
OCCASIONAL PAPER SERIES - No. 149
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Abstract
Following the discontinuation of the official statistics on industrial new orders by Eurostat in mid-2012, this paper introduces the ECB indicator on euro area industrial new orders, which aims to fill the new statistical gaps for euro area total new orders as well as for various breakdowns. Despite the discontinuation of the data collection at European level, a large number of euro area countries are expected to continue with the data collection nationally. For those countries which have discontinued the collection of national data, model-estimates are used in calculating the ECB indicator on euro area industrial new orders. New orders are modelled across EU countries using "soft" data (business opinion surveys) as well as "hard" data (industrial turnover) and applying a common modelling framework. The model determinants significantly explain the monthly growth rates in new orders across approximately 200 estimated equations. Various tests show that the estimates are robust. This paper demonstrates that, besides the leading information content of industrial new orders for euro area industrial production, the monitoring of the ECB indicator on new orders is useful for cross-checking developments in industrial production in real time.
JEL Code
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles