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    <title>EconStor Collection:</title>
    <link>https://hdl.handle.net/10419/152433</link>
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        <rdf:li rdf:resource="https://hdl.handle.net/10419/322031" />
        <rdf:li rdf:resource="https://hdl.handle.net/10419/322088" />
        <rdf:li rdf:resource="https://hdl.handle.net/10419/299573" />
        <rdf:li rdf:resource="https://hdl.handle.net/10419/299571" />
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    <dc:date>2026-04-03T20:29:39Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/322031">
    <title>Filling the gap: The geographical allocation of euro area portfolio investment liabilities and related income</title>
    <link>https://hdl.handle.net/10419/322031</link>
    <description>Title: Filling the gap: The geographical allocation of euro area portfolio investment liabilities and related income
Authors: Bosetti, Isabella; Incardona, Rocco; Rodríguez Caloca, Antonio
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.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/322088">
    <title>On the collection of MiFIR transparency data: An application to the ECB eligible marketable assets</title>
    <link>https://hdl.handle.net/10419/322088</link>
    <description>Title: On the collection of MiFIR transparency data: An application to the ECB eligible marketable assets
Authors: Camba-Méndez, Gonzalo; Darecki, Jan Jerzy; Manzanares, Andrés; Metra, Matteo; Vergnano, Riccardo
Abstract: One of the main goals of launching the EU's second Markets in Financial Instruments Directive (MiFID II) and the respective Markets in Financial Instruments Regulation (MiFIR) was to increase the transparency of transactions in financial markets. Prior to MiFID II, transparency requirements in financial markets were limited mostly to equities traded in regulated markets. Following MiFID II, transactions now need to be publicly reported for a broader range of financial assets. Furthermore, disclosures on financial transactions are not restricted to those transactions executed in regulated markets but apply also to those executed over the counter. Importantly, this information should be made available free of charge, ensuring non-discriminatory access, within the 15 minutes following the transaction. The published information should also be machine-readable. The purpose of this paper is to show how a relatively simple IT tool may be devised that gathers data on market prices and transacted volumes published in compliance with MiFID II. We steer our simple IT tool towards retrieving data on those financial assets that are eligible for use as collateral in Eurosystem credit operations. This includes those assets eligible for outright purchase under the various monetary policy programmes launched by the Eurosystem. In view of the importance of UK financial markets when it comes to trading in Eurosystem eligible marketable assets, our tool also covers transactions and quotes reported by UK trading venues and investment firms in compliance with UK MiFIR. Apart from the merits and potential of our IT tool, this paper documents some of the tool's shortcomings related to processing the posted MiFID II and UK MiFIR raw data. It also covers some of the deficiencies associated with the data. Increased market transparency contributes to deeper and more integrated financial markets, potentially supporting economic growth. ECB access to these rich financial market data is very important for the conduct of its monetary policy. This is the case not only from the perspective of gathering all information relevant for monitoring financing conditions in euro area financial markets. It is also the case that the availability of pre-trade and post-trade data published in compliance with MiFIR could be a useful day-to-day tool for central bank monetary implementation and risk mitigation. The data collected provide a rich description of the price, liquidity and depth of various types of ECB eligible marketable assets.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/299573">
    <title>Climate change-related statistical indicators</title>
    <link>https://hdl.handle.net/10419/299573</link>
    <description>Title: Climate change-related statistical indicators
Abstract: Climate change entails risks to the global economy and impacts financial stability. Beyond managing related risks, the financial sector can also contribute to the transition toward a net-zero economy. Guided by the ECB's climate and nature plan1 , this paper discusses the methodology and key findings of statistical indicators developed in three areas: sustainable finance, carbon emissions, and physical risk. Our work aims to enhance data transparency in climate change analysis, while informing monetary policy, financial stability and banking supervision. The indicators we have developed focus on the euro area financial sector and are built from harmonised granular datasets. They also utilise climate information from public sources to the extent possible. The sustainable finance metrics are built on well-established securities statistics and are at a more mature stage of development when compared with the other two climate risk indicators. While there are several data gaps that need to be addressed, the proposed statistical methodology offers a valuable framework for assessing climate risks in the European context, ensuring comparability across countries, time frames and under various climate scenarios. Meanwhile, the sustainable finance indicators track issuances and holdings of sustainable debt securities in the euro area, thus providing insights on funds for sustainable projects and reflecting progress in the transition towards a net-zero economy. The carbon emission indicators study the financial sector's exposure to counterparties with carbon-intensive business models and the carbon intensity of the securities and loans portfolio. They are useful to assist in evaluating the sector's contribution to financing the transition to a net-zero economy and the associated risks. Several methodological improvements are detailed in this paper to make it easier to interpret the indicators over time and understand the trends: imputation strategies for emission and financial data, a novel balancing algorithm that accounts for changes in the composition of the underlying non-financial corporations over time, adjustments for inflation and exchange rates, and a time series decomposition. Meanwhile, the physical risk indicators evaluate the impact of climate changeinduced natural hazards on the performance of financial institutions' loan and securities portfolio. The metrics cover a range of acute and chronic hazards, presenting risk scores and expected losses, enabling historical baselines to be benchmarked with climate scenarios where data permit. From the financial side, the framework we present accounts for maturities of the loan portfolios and the collateral pledged, as well as national insurance practices, thus providing a comprehensive risk assessment. This paper discusses the methodology, underlying data, and findings for each set of indicators, while also flagging possible constraints and opportunities for future development.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/299571">
    <title>Owner-occupied housing and inflation measurement</title>
    <link>https://hdl.handle.net/10419/299571</link>
    <description>Title: Owner-occupied housing and inflation measurement
Authors: Eiglsperger, Martin; Ganoulis, Ioannis; Goldhammer, Bernhard; Kouvavas, Omiros; Roma, Moreno; Vlad, Aurelian
Abstract: The Harmonised Index of Consumer Prices (HICP) currently only includes rentals for housing (paid by tenants) and auxiliary housing expenditures (paid by both tenants and owners). The inclusion of an item for owner-occupied housing (OOH) would be desirable for both representativeness and cross-country comparability. This paper reviews the potential options for including OOH in the HICP to derive a new inflation index. We discuss the conceptual and measurement issues involved. Additionally, we present our analytical calculations on the impact and economic properties of this index as compared to the HICP. We show that since 2011 the estimated impact of including OOH in HICP annual inflation, based on either the "net acquisition" approach or the "rental equivalence" approach, would have been within a band of between -1.2 and +0.4 percentage points. The net acquisition approach could result in bigger differences in future, should the fluctuations in the housing market cycles in the euro area be more pronounced and synchronised. The results should be interpreted keeping in mind that the period of observation is relatively short in relation to housing market cycles. In general, the empirical evidence suggests that including OOH based on the rental equivalence approach decreases the cyclicality of the new inflation index, while the net acquisition approach implies a small amplification of its cyclical properties compared to the HICP.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
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