Bridging between economy-wide activity and household-level consumption data: Matrices for European countries

This dataset represents bridging matrices between two different data classification systems: consumption by purpose (COICOP) and products by activity (CPA). While the former classification is used in household budget and expenditure surveys, the latter represents the industry sector dimension that i...

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Bibliographic Details
Main Authors: Mattia Cai, Toon Vandyck
Format: Article
Language:English
Published: Elsevier 2020-06-01
Series:Data in Brief
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340920302894
Description
Summary:This dataset represents bridging matrices between two different data classification systems: consumption by purpose (COICOP) and products by activity (CPA). While the former classification is used in household budget and expenditure surveys, the latter represents the industry sector dimension that is typically adopted in national accounts and input–output tables. We collect input data from Eurostat on total household consumption for 35 COICOP and 63 CPA categories for the year 2015. Based on these data, we construct bridging or concordance tables for 30 European countries using recently developed matrix balancing techniques. The resulting tables enable data conversion between consumption- and production-based statistics, facilitating research that integrates macroeconomics, multi-sectoral international trade and heterogeneous agents in household-level expenditure micro-data. Although they are a necessary input in several types of research, they are often constructed on an ad hoc and region-specific basis and not shared publicly. As such, making this dataset available will be useful for computable general equilibrium and input–output models and for carbon footprint and life cycle analyses that incorporate rich consumption micro-data, for instance to shed light on distributional aspects of climate and energy policies. Furthermore, by eliminating a barrier raised by differences in statistical classifications, this dataset may foster collaboration between different research teams and may facilitate soft-linking between complementary analytical tools used for policy support.
ISSN:2352-3409