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Carmen Picón Aguilar

20 March 2020
The quality of the geographical breakdown in the balance of payments and related statistics (such as international trade in goods, trade in services and foreign direct investment (FDI) statistics) can be assessed by means of comparisons with mirror data in order to assess bilateral asymmetries. Although such comparisons are performed on a regular basis, they tend to focus on pairs of countries and are not sufficient to determine which of the countries involved has better data. This paper describes three synthetic indicators that have been developed with a view to assessing whole groups of countries. In the specific context of an economic union’s external account, they allow us to assess the quality of geographical breakdowns by country and the contribution that an individual country makes to the aggregate asymmetry for that group of countries. Those indicators are applied in the context of euro area FDI statistics.
JEL Code
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
F21 : International Economics→International Factor Movements and International Business→International Investment, Long-Term Capital Movements
F23 : International Economics→International Factor Movements and International Business→Multinational Firms, International Business
11 February 2020
We explain how the external counterpart of the euro area M3 can be analysed by using the euro area balance of payments (b.o.p.). This is possible because the net external assets of the monetary financial institutions (MFIs) are present in two statistical frameworks that follow similar conventions: the balance sheet items (BSI) of MFIs and the balance of payments statistics. The first step to including external flows in the monetary analysis is to understand the nature of the flows between resident money holders and the rest of the world. This is possible thanks to the monetary presentation of the b.o.p, which provides information on the nature of external transactions and therefore guidance on the persistence of the monetary signal stemming from external flows.Over the past five years, the increase in the euro area’s external competitiveness has given rise to a sustained current account surplus that has consistently supported monetary inflows into the euro area. At the same time, portfolio transactions, which closely reflect financial and monetary policy conditions, have fluctuated significantly, increasing monetary inflows in the period from mid-2012 to mid-2014 and turning them into net outflows during the asset purchase programme (APP) period.
JEL Code
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
F45 : International Economics→Macroeconomic Aspects of International Trade and Finance
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
F43 : International Economics→Macroeconomic Aspects of International Trade and Finance→Economic Growth of Open Economies
F32 : International Economics→International Finance→Current Account Adjustment, Short-Term Capital Movements
F34 : International Economics→International Finance→International Lending and Debt Problems
17 November 2006
Quality is a subjective notion and encompasses all aspects of how well a product meets users’ needs. It is inherently a multi-faceted concept that cannot be easily defined; any chosen definition is likely to change over time as new aspects gain importance following the evolving users’ needs. The purpose of this paper is threefold; (1) to present a number of quantitative quality indicators, (2) to apply them to measure the quality of balance of payments (b.o.p.) data at the euro area level, and (3) to identify various aspects of data quality that may be enhanced, together with their interrelations with other quality dimensions. The indicators used are compatible with the IMF Data Quality Assessment Framework (DQAF), as defined for b.o.p. statistics, focusing mainly on revisions and consistency. The results obtained from such quantitative indicators may help compilers to set priorities in order to improve the quality of the euro area data still further in dimensions such as accuracy, reliability and serviceability. Additionally, this assessment may help users to understand better the quality of the data, to anticipate the possible size and direction of the forthcoming revisions, and to evaluate the impact of using different datasets in their analysis.