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Emmanouil Pantelidis

29 November 2018
STATISTICS PAPER SERIES - No. 30
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Abstract
Big data” is becoming an increasingly important aspect of our daily lives as the digital sources of information and intelligence that it encompasses become more structured and more publicly available. These sources may enable the generation of new datasets providing high-frequency and timely insights into unconscious digital behaviour and the consequent actions of economic agents, which may, in turn, assist in the generation of early indicators of economic and financial trends and activities. This paper examines the usefulness of Google search data in nowcasting euro area car sales, as a leading macroeconomic indicator, and considers the quality requirements for using these new data sources as a toolkit for sound decision and policy making. The paper finds that, while Google data may have predictive capabilities for nowcasting euro area car sales, further quality improvements in the data source are needed in order to move beyond experimental statistics. If these quality requirements can be met, the resulting advances in theory and knowledge around interpreting big data can be expected to significantly re-shape how we think about and explain both behaviour and complex socio-economic phenomena.
JEL Code
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E71 : Macroeconomics and Monetary Economics