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Sona Muzikarova

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
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
1 December 2017
OCCASIONAL PAPER SERIES - No. 203
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Abstract
In the euro area, there is mixed evidence that the GDP per capita of lower-income economies has been catching up with that of higher-income economies since the start of monetary union. The significant real convergence performance of some of the most recent members contrasts with that of the economies of southern Europe, which have not met expectations. However, attributing all the blame for this outcome to the introduction of the single currency simply misses the point. By taking a “long view” and reviewing the evidence since the 1960s, this paper shows that certain member countries began to face a “non-convergence trap” long before the euro years. We also provide stylised facts on: (i) the central role of total factor productivity in driving real convergence in the euro area over time, alongside other factors; and (ii) the crucial interaction of real convergence with “Maastricht convergence” and institutional quality, the other two key components of sustainable economic convergence. We conclude that it is critical that the euro area countries facing convergence challenges enhance the resilience of their economic structures by improving the relevant institutions and governance.
JEL Code
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
F15 : International Economics→Trade→Economic Integration
J11 : Labor and Demographic Economics→Demographic Economics→Demographic Trends, Macroeconomic Effects, and Forecasts
O11 : Economic Development, Technological Change, and Growth→Economic Development→Macroeconomic Analyses of Economic Development
O43 : Economic Development, Technological Change, and Growth→Economic Growth and Aggregate Productivity→Institutions and Growth
O47 : Economic Development, Technological Change, and Growth→Economic Growth and Aggregate Productivity→Measurement of Economic Growth, Aggregate Productivity, Cross-Country Output Convergence
O52 : Economic Development, Technological Change, and Growth→Economywide Country Studies→Europe
O57 : Economic Development, Technological Change, and Growth→Economywide Country Studies→Comparative Studies of Countries