Antonio Rodríguez Caloca
- 24 March 2025
- STATISTICS PAPER SERIES - No. 50Details
- Abstract
- This paper presents the estimation method used to break down the euro area portfolio investment liabilities in the international investment position (i.i.p.) and their corresponding income debits in the balance of payments (b.o.p.), by main geographical counterpart. Identifying non-resident investors in euro area portfolio investment liabilities (i.e. equity and debt securities issued by euro area residents) is a complex task, as securities are regularly traded in secondary markets and held via custodians and other financial intermediaries. Consequently, identifying the actual holders of euro area securities may be hampered by so-called “first-known counterparty” and/or “custodial” biases if statisticians cannot look through the chain of intermediaries. Owing to these difficulties, the geographical counterpart allocation of euro area portfolio investment liabilities cannot generally be directly collected from reporting agents (i.e. the issuers of euro area securities) but instead needs to be estimated. The estimation method presented in this document relies on a comprehensive set of so-called “mirror” datasets (i.e. information on the holders of euro area securities) supported by temporal disaggregation and econometric techniques. The results provide robust estimates of portfolio investment liabilities and income debits by geographical counterpart.
- 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
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
- 19 June 2023
- STATISTICS PAPER SERIES - No. 44Details
- Abstract
- This paper contributes to the ongoing efforts by the European authorities to reduce the reporting burden for banks by assessing the statistical methods currently used to compile data on financial transactions related to securities holdings. Based on statistical information collected from the Banca d’Italia, we compare data on purchases of securities net of sales and redemptions reported by banks with transaction estimates based on indirect (balance sheet) methods that are permitted within the methodological framework of datasets compiled by the European System of Central Banks (ESCB). Although the direct method of collecting data on transactions is more costly for reporting agents, it produces results which are fully aligned with current statistical methodological standards (European System of Accounts 2010, ESA 2010). By contrast, the indirect method is a simplified and less costly approach. The recent development of high-quality data sources such as the ESCB integrated system for the market prices of securities – the Centralised Securities Database – has boosted the attractiveness of indirect methods since they have the potential to deliver accurate and reliable estimates. The significance of the differences between direct collection and indirect compilation of these data is analysed in detail for listed ISIN securities that are actively traded on exchanges, by also considering the impact of price volatility and trading activity. From an aggregated perspective, all indirect methods produce results which are comparable and consistent with the ESA 2010 methodology for all instrument types. There are some minor differences for equity instruments, due to the higher price volatility and trading activity associated with these instruments, but the overall aggregated dynamics are also well captured by indirect methods in these cases. [...]
- JEL Code
- C18 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Methodological Issues: General
C81 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access
G15 : Financial Economics→General Financial Markets→International Financial Markets
- 23 May 2018
- STATISTICS PAPER SERIES - No. 28Details
- Abstract
- This paper presents a detailed set of new, quantity-based indicators of financial integration in the euro area. The indicators are based on granular data from securities holdings statistics and help us disentangle the main drivers of the portfolio changes observed since the financial crisis. Three key developments since the crisis stand out. First, we find that financial integration in equity is less than that in the debt market, although the equity market was the main contributor to the partial recovery in financial integration observed since mid-2012. Second, we observe a gradual shift in cross-border investment activity from the banking sector towards other non-bank financial entities. In particular, our results show that euro area banks significantly decreased their investment in debt securities issued by banks in other euro area countries and that this decrease explains around 55% of the decline in financial integration in the debt market observed since the crisis. Finally, we find that the sharp decrease in financial integration between 2009 and 2012 was mainly driven by foreign investor flight from government debt securities, a trend that has since reversed.
- JEL Code
- F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G1 : Financial Economics→General Financial Markets
G10 : Financial Economics→General Financial Markets→General
G15 : Financial Economics→General Financial Markets→International Financial Markets