BUSCADOR RECOLECTA

National accounting matrices (NAM) perfectly describe the economic structure of a national economy, summarizing the whole process of generation of primary income and its distribution among the different institutional sectors of the economy. It is not just a way to represent the main economic statistics of an economy, but it also serves as the basis for most macroeconomic modelling efforts. The business accounting matrix (BAM) presents the most relevant information for the firm in a similar way, adapted to the descriptive potential of financial accounting, what we believe can be useful both for economic modellers and for decision makers at the firm level. This spreadsheet helps to trace how each of the cells of the BAM are calculated. It includes a table in which the cells of the BAM incorporate a description of their content. It also contains the example of a complete BAM (SBAM) that can be used the simulation of changes in demand and other input-output related models. This material allows researchers having the financial accounts of a firm available, to immediately calculate a BAM. They can also easily adapt our proposal to their convenience.

This database contains electricity bills related to energy consumption in Spanish households. The contents of bills are automatically generated following some statistics from official bodies. The main purpose of the dataset is for training machine learning algorithms, especially for designing new methods for extracting information from invoices. There are 86 different labels, which are related to several topics, such as the customer and marketer, the contract, energy consumption, or billing. The total number of invoices is 75.000. The files are organized in two directories: a training directory, with six subdirectories, each containing 5.000 invoices in PDF format and the corresponding labels in JSON files; and a test directory, with nine subdirectories, each containing 5.000 invoices in PDF format. There are two main zip files that contain the test and training sets (test.zip and training.zip). In addition, we have included separate files with a subset of the directories in each set, so it can be downloaded by parts. There is also a reduced version of the dataset with 100 invoices per directory, which is interesting for users who want to preview the content of the dataset before downloading it. IDSEM is an acronym for "an Invoices Database for the Spanish Electricity Market". More information can be found at https://idsem.ulpgc.es/ and in the following article: [1] Javier Sánchez, Agustín Salgado, Alejandro García, and Nelson Monzón, "IDSEM, an invoices database of the Spanish electricity market", Sci. Data, (2022).