Empirical Testing of the Permanent Income Hypothesis Using Data on France

This article tests the permanent income hypothesis (PIH) against contemporary (2006–2019) quarterly data on household income and consumer spending in France. The methodology follows the approaches developed by J. Campbell and N. Mankiw, as well as J. Shea. Specifically, the econometric analysis employs the two-stage least squares (2SLS) method, using predicted values of income and interest rates generated by a set of instruments that include lagged values of the relevant variables. The analysis does not support the permanent income hypothesis using data on France. To explore potential explanations for this result, the article tests additional hypotheses, namely the presence of liquidity constraints and consumer myopia. However, neither of these factors appears to account for the failure of the PIH. French household consumption is more responsive to falling income than to rising income. This phenomenon, that is, consumption’s stronger reaction to income losses than to gains, is sometimes referred to as perverse asymmetry. It may reflect a precautionary saving motive: consumers prioritize maintaining a buffer of savings to guard against future financial instability, rather than maximizing consumption in the present. This behavior aligns with Christopher Carroll’s buffer-stock saving theory. These results are consistent with those from similar studies conducted on data from other countries, including the United States, Russia, and Japan.

Authors

Publication Details

Journal
AlterEconomics
Published
2025-01-01
DOI
https://doi.org/10.31063/altereconomics/2025.22-2.7
Primary Topic
Regional Development and Policy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Empirical Testing of the Permanent Income Hypothesis Using Data on France

Ivan V. Rozmainsky, I. V. Malinovskaya, S. R. Khassenova
AlterEconomics
Regional Development and Policy
article

Empirical Testing of the Permanent Income Hypothesis Using Data on France

Ivan V. Rozmainsky, I. V. Malinovskaya, S. R. Khassenova
article en

Abstract

This article tests the permanent income hypothesis (PIH) against contemporary (2006–2019) quarterly data on household income and consumer spending in France. The methodology follows the approaches developed by J. Campbell and N. Mankiw, as well as J. Shea. Specifically, the econometric analysis employs the two-stage least squares (2SLS) method, using predicted values of income and interest rates generated by a set of instruments that include lagged values of the relevant variables. The analysis does not support the permanent income hypothesis using data on France. To explore potential explanations for this result, the article tests additional hypotheses, namely the presence of liquidity constraints and consumer myopia. However, neither of these factors appears to account for the failure of the PIH. French household consumption is more responsive to falling income than to rising income. This phenomenon, that is, consumption’s stronger reaction to income losses than to gains, is sometimes referred to as perverse asymmetry. It may reflect a precautionary saving motive: consumers prioritize maintaining a buffer of savings to guard against future financial instability, rather than maximizing consumption in the present. This behavior aligns with Christopher Carroll’s buffer-stock saving theory. These results are consistent with those from similar studies conducted on data from other countries, including the United States, Russia, and Japan.

AlterEconomicsVol. 22(2)
Openalex Percentile: Top 81%
Regional Development and Policy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.