Mamma Mia! Revealing Hidden Heterogeneity by PCA-Biplot - MPC Puzzle for Italy’s Elderly Poor

37 Pages Posted: 15 Feb 2023

See all articles by Jan Wedigo Radermacher

Jan Wedigo Radermacher

Leibniz Institute for Financial Research SAFE

Date Written: February 13, 2023

Abstract

I investigate consumption patterns in Italy and use a PCA-biplot to discover a consumption puzzle for the elderly poor. Data from the third wave (2017) of the Eurosystem’s Household Finance and Consumption Survey (HFCS) indicate that Italian poor old-aged households boast lower levels of the marginal propensity to consume (MPC) than suggested by the dominant consumption models. A customized regression analysis exhibits group differences with richer peers to be only half as large as prescribed by a traditional linear regression model. This analysis has benefited from a visualization technique for high-dimensional matrices related to the unsupervised machine learning literature. I demonstrate that PCA-biplots are a useful tool to reveal hidden relations and to help researchers to formulate simple research questions. The method is presented in detail and suggestions on incorporating it in the econometric modeling pipeline are given.

Suggested Citation

Radermacher, Jan Wedigo, Mamma Mia! Revealing Hidden Heterogeneity by PCA-Biplot - MPC Puzzle for Italy’s Elderly Poor (February 13, 2023). SAFE Working Paper No. 382, Available at SSRN: https://ssrn.com/abstract=4359979 or http://dx.doi.org/10.2139/ssrn.4359979

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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