106591 20230519145348.0 doi 10.1080/02664763.2020.1796933 sideral 119611 ART-2021-119611 eng López-Laborda, Julio Universidad de Zaragoza (orcid)0000-0002-1539-8483 Estimating Engel curves: a new way to improve the SILC-HBS matching process using GLM methods 2021 Access copy available to the general public Unrestricted Microdata are required to evaluate the distributive impact of the taxation system as a whole (direct and indirect taxes) on individuals or households. However, in European Union countries this information is usually distributed into two separate surveys: the Household Budget Surveys (HBS), including total household expenditure and its composition, and EU Statistics on Income and Living Conditions (EU-SILC), including detailed information about households'' income and direct (but not indirect) taxes paid. We present a parametric statistical matching procedure to merge both surveys. For the first stage of matching, we propose estimating total household expenditure in HBS (Engel curves) using a GLM estimator, instead of the traditionally used OLS method. It is a better alternative, insofar as it can deal with the heteroskedasticity problem of the OLS estimates, while making it unnecessary to retransform the regressors estimated in logarithms. To evaluate these advantages of the GLM estimator, we conducted a computational Monte Carlo simulation. In addition, when an error term is added to the deterministic imputation of expenditure in the EU-SILC, we propose replacing the usual Normal distribution of the error with a Chi-square type, which allows a better approximation to the original expenditures variance in the HBS. An empirical analysis is provided using Spanish surveys for years 2012–2016. In addition, we extend the empirical analysis to the rest of the European Union countries, using the surveys provided by Eurostat (EU-SILC, 2011; HBS, 2010). info:eu-repo/grantAgreement/ES/DGA-ERDF/Public Economics Research Group info:eu-repo/grantAgreement/ES/MINECO/ECO2016-76506-C4-3-R info:eu-repo/grantAgreement/ES/MINECO/ECO2017-87862-P info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 1.416 2021 STATISTICS & PROBABILITY 73 / 125 = 0.584 2021 Q3 T2 0.507 2021 Statistics, Probability and Uncertainty 2021 Q3 Statistics and Probability 2021 Q3 2.5 2021 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Marín-González, Carmen Onrubia-Fernández, Jorge 4014 225 Universidad de Zaragoza Dpto. Economía Aplicada Área Economía Aplicada 48, 16 (2021), 3233-3250 J. appl. stat. JOURNAL OF APPLIED STATISTICS 0266-4763 399005 http://zaguan.unizar.es/record/106591/files/texto_completo.pdf Postprint 1981432 http://zaguan.unizar.es/record/106591/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:106591 articulos driver 2023-05-18-13:23:15 ARTICLE