The impact of financial stress on consumer confidence: evidence from survey data
Thoughts
Connects with: @cardarelli2011 @hakkio2009 @hollo2012 @illing2006
Annotations
rooj2025 - p. 118
Increased FS can result in reduced access to financing for firms and households as the economic outlook worsens and asset prices fall (Tng and Kwek, 2015). It can also lead to a decline in output and disruptions in the labor market (Wang and Su, 2024). Therefore, such FS can impact household expectations, such as job and income loss, which can impact consumer confidence (CC).
rooj2025 - p. 119
The asymmetries in response to FSI on CC indicate that households may react more strongly to bad news than to good news, which is consistent with the idea that households display reference-dependent preferences; this manifests into loss aversion, where people react more strongly to losses than to gains (Kahneman and Tversky, 1979). Dimmock and Kouwenberg (2010) found that loss aversion affects households’ equity market participation and household portfolio choice.
rooj2025 - p. 120
We combine the household-level information on CC from the CCS conducted by the RBI with the FSI index, which is an initiative to collect data on CC from 2010. Initially focused on six cities, the CCS was later expanded to 19 cities [2], capturing insights from approximately 5,000 households in each round, including information regarding households’ confidence in general economic conditions compared to a year ago and their expectations a year ahead. Our sample covers data from March 2015 (round 23) to July 2023 (round 73).
rooj2025 - p. 121
FS is defined as episodes with large shifts in asset prices, unexpected rises in risk or uncertainty, a rise in the financial system’s illiquidity and apprehensions in the banking sector’s health (Balakrishnan et al., 2011). The FSI index is a composite index based on stress in the four major domains of financial markets, such as banking, equity markets, debt and foreign exchange (Park and Mercado, 2014).
rooj2025 - p. 121
The final FSI is then constructed by aggregating the five individual measures using the variance-equal weights and principal component analysis (Park and Mercado, 2014)
rooj2025 - p. 123
3.2.1 Heterogeneous effect based on household income. Household income is a prime determinant of how families cope with FS. Therefore, we explore the impact of the FSI on household confidence based on their income categories. The evaluated coefficient of the interaction term (INCOMEG*LFSI) shows a negative impact across all income groups for GECPER (Table A2 [1]).
rooj2025 - p. 123
3.2.2 Heterogeneous effect based on education level. To explore heterogeneity across different education levels, Table A3 [1] shows our regression estimates. GECPER, the estimated interaction term coefficients (EDUG*LFSI), are negative and statistically significant across all the education categories, barred for the respondents with primary and matriculation levels. Further, for GECOTL, respondents with primary education, followed by undergraduates, are most pessimistic about their expectations for the future economy. Education is correlated with employment and income.