Age, Wealth, and the MPC in Europe - A Supervised Machine Learning Approach

42 Pages Posted: 15 Feb 2023

See all articles by Satyajit Dutt

Satyajit Dutt

Independent

Jan Wedigo Radermacher

Leibniz Institute for Financial Research SAFE

Date Written: February 13, 2023

Abstract

We investigate consumption patterns in Europe with supervised machine learning methods and reveal differences in age and wealth impact across countries. Using data from the third wave (2017) of the Eurosystem’s Household Finance and Consumption Survey (HFCS), we assess how age and (liquid) wealth affect the marginal propensity to consume (MPC) in the Netherlands, Germany, France, and Italy. Our regression analysis takes the specification by Christelis et al. (2019) as a starting point. Decision trees are used to suggest alternative variable splits to create categorical variables for customized regression specifications. The results suggest an impact of differing wealth distributions and retirement systems across the studied Eurozone members and are relevant to European policy makers due to joint Eurozone monetary policy and increasing supranational fiscal authority of the EU. The analysis is further substantiated by a supervised machine learning analysis using a random forest and XGBoost algorithm.

Suggested Citation

Dutt, Satyajit and Radermacher, Jan Wedigo, Age, Wealth, and the MPC in Europe - A Supervised Machine Learning Approach (February 13, 2023). SAFE Working Paper No. 383, Available at SSRN: https://ssrn.com/abstract=4360002 or http://dx.doi.org/10.2139/ssrn.4360002

Satyajit Dutt

Independent

Jan Wedigo Radermacher (Contact Author)

Leibniz Institute for Financial Research SAFE ( email )

House of Finance
Theodor-W.-Adorno-Platz 3
Frankfurt, 60323
Germany

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