Publications

In recent years, awareness of social and environmental issues has been on the rise. As a result, the demand for sustainability data has grown exponentially. This has driven the Banco de España’s Statistics Department to develop a micro-database for sustainability indicators (ESG).

This document presents two papers which analyse the process developed to gather this information and the numerous limitations and difficulties found along the way when dealing with sustainability microdata. Specifically, the two topics covered by these papers are:

1. “Analysing climate change data gaps” (presented at the 11th Biennial IFC (Irving Fisher Committee) Conference on “Post-pandemic landscape for central bank statistics” held on 25-27 August 2022, Session 3.B “Environmental statistics”)
2. “Creation of a structured sustainability database from company reports: A web application prototype for information retrieval and storage” (presented at the IFC Bank of Italy workshop on “Data science in central banking” held on 14-17 February 2022, Session 4.3 “Text Mining and ML utilized in Economic Research”) (Koblents and Morales (2022))

The first paper focuses on the various limitations encountered and achievements made in the process of developing a micro-database for sustainability indicators for non-financial companies. After carefully researching current ESG standards, consulting ESG experts, analysing regulatory obligations and conducting practical research, a list of the 39 most relevant ESG indicators was selected from those normally reported by companies. Currently more than 15,000 data samples have been gathered for the period 2019-2020 using a semi-automatic search application developed in-house (presented in detail in the second paper). Numerous challenges were identified during the process, such as the use of different metrics for reporting sustainability information, a lack of information and of a downloadable digital format, comparability difficulties and regulatory restrictions.

The second paper focuses on the tool developed to create the micro-database presented in the first paper. This web application aims, through semi-automatic extraction and storage, to retrieve sustainability indicators from annual non-financial statements reported by Spanish non-financial corporations. This application aims to make it easier for users to search for sustainability indicators in large document databases and store them in a structured database. The tool developed incorporates a set of pre-defined search terms for each indicator which have been selected based on domain knowledge and artificial intelligence in subsequent developments. For each company and indicator, the tool suggests the most relevant text snippets to the user, who then identifies the correct value of the indicator and stores it in the database using the web’s user interface. This tool was created by two data scientists in three months, with the continuous support of a team of experts that helped to define the system specifications, propose refinements, collect input data and validate and test the tool. This paper describes the technical approach and the main modules of the implemented prototype, which include text extraction, indexing and search, data storage and visualization.

This statistical note presents the methodology applied to compile the supplementary statistics on foreign direct investment in Spain by ultimate investing economy, according to the directional principle and using data consistent with the balance of payments/international investment position. Also, an analysis is performed of the most notable differences between the foreign direct investment position in Spain by immediate investing economy and by ultimate investing economy.

This note presents the impact that application of International Financial Reporting Standard (IFRS) 16 has had on the financial statements of listed Spanish groups. Listed European groups are required to apply IFRS in their consolidated accounts. Specifically, IFRS 16 on the measurement and presentation of leases practically eliminates the dual model approach for finance leases and operating leases for lessees and establishes a single model for all leases. This new way of accounting for leases has a strong impact on some items in groups’ income statements and on metrics such as gross value added (GVA) and earnings before interest, taxes, depreciation and amortisation (EBITDA), as they rise as a result of lower lease expenses. The increase in the balance sheet prompted by recognising right-of-use assets and liabilities also has significant repercussions, by pushing up the ratios used to analyse debt levels. Movement in analysed variables and ratios caused by changes in an accounting standard, rather than by conduct attributable to the listed group, must therefore be taken into account by analysts.

Compiling the financial assets/liabilities of households in the balance of payments (b.o.p.) /
international investment position (i.i.p.) is commonly considered as one of the most challenging issues faced by statisticians. This is in light of the multiple limitations of this institutional sector when a direct collection system is designed in terms of complexity, coverage or accuracy. Therefore, it is necessary to find other alternatives or complementary information to enhance the estimation of these data with the aim of making them as real as possible. This is when data-sharing among institutions and countries can play an important role. 

This paper presents the Spanish experience working towards an improvement in the regular production of official external statistics regarding transactions and positions of households, not subject to the sources of information collected in first instance by the compiler but using all available sources of information and taking advantage of its complementarity. The paper will present the usefulness of mirror data sources and administrative data going through different financial instruments held/taken abroad by this sector: deposits, loans, life insurance technical reserves, securities and real estate.