Computational methods to gauge investor sentiment from commonly used online data sources that rely on machine learning classifiers and lexicons have shown considerable promise, but suffer from measurement and classification errors. In our work, we develop a simple, direct and unambiguous...

This report summarises the methodologies used in the first wave of the Eurosystem Household Finance and Consumption Survey, which provides household-level data collected in a harmonised way in 15 euro area countries for a sample of more than 62,000 households. The report presents the...

This report summarises key stylised facts from the first wave of the Eurosystem Household Finance and Consumption Survey, which provides household-level data collected in a harmonised way in 15 euro area countries for a sample of more than 62,000 households. The report presents results on...

In this paper, we estimate consumption in the first wave of the Eurosystem Household Finance and Consumption Survey for a subset of countries that account for around 85% of the aggregate final consumption expenditure of households in the euro area. For this purpose we use the methodology...

The Expert Group on Linking Macro and Micro Data for the household sector (EG-LMM) was established in December 2015 within the European System of Central Banks (ESCB) with the aim of comparing and bridging macro data (i.e. National Accounts/Financial Accounts) and micro data (i.e. the Household...

This report summarises the methodologies used in the fourth wave of the Eurosystem Household Finance and Consumption Survey, which provides household-level data collected in a harmonised way in all 19 euro area countries, as well as in the Czech Republic, Croatia and Hungary. The total sample...

This report summarises the stylized facts from the fourth wave of the Eurosystem Household Finance and Consumption Survey, which provides household-level data collected in a harmonised way in all 19 euro area countries, as well as in the Czech Republic, Croatia and Hungary for a sample of more...