Financial markets and the working class in the USA: an empirical investigation of financial stress

2019 ◽  
Vol 43 (4) ◽  
pp. 867-890 ◽  
Author(s):  
Michael J McCormack
Keyword(s):  
Working Class ◽  
Financial Markets ◽  
Financial Stress ◽  
Safety Net ◽  
Stress Index ◽  
Survey Of Consumer Finances ◽  
Consumer Finances ◽  
The Usa ◽  
Financial Stress Index ◽  
The Relationship

AbstractThis paper investigates the relationship between financial stress and the working class in the USA. Employing a financial stress index created from the Survey of Consumer Finances, I show that working class households are nearly twice as likely to be financially stressed than wealthier non-working class households from 1992 to 2016. A possible explanation of this result could be that the financial expropriation of personal income among the working class has the effect of increasing that group’s financial stress relative to wealthier classes. Working class households in the USA have struggled to afford means of subsistence in lieu of lacklustre wage growth and a tattered safety net. Financial expropriation of these households has operated in tandem with this precarity, increasing financial stress in a time of financialised capitalism.

scholarly journals The Spillover and Transmission of Chinese Financial Markets Risk

2018 ◽  
Vol 11 (8) ◽  
pp. 66
Author(s):  
Sha Zhu
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Financial Markets ◽  
Financial Market ◽  
Spillover Effect ◽  
Financial Stress ◽  
Stress Index ◽  
2008 Financial Crisis ◽  
The Us ◽  
Financial Stress Index

After the 2008 financial crisis, the whole world financial markets became more fluctuates, the same to China also. It is necessary to pay great attention to high volatility problem in Chinese market, and also the uncertainty problem, risk accumulation and spillover effect come along with it. This paper calculates stock market return and builds financial stress index to explore the risk spillover effect. Empirical results show that the Chinese financial market have higher volatility than other countries. The Chinese stock market had higher dynamic market co-movement with international financial markets after 2008 financial crisis. What’s more, this article also finds the financial risk spreads between China and US. When the US financial stress index increases, China's financial stress index experiences a larger increase. However, after the change in China's financial stress index, the US financial stress index has no obvious trend of change. So we should pay more attention to periods of Chinese financial market risk and its spillover.

The link between financial stress index and economic activity: prominent Granger causalities across frequencies in Luxembourg

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pejman Bahramian ◽  
Andisheh Saliminezhad ◽  
Şule Aker
Keyword(s):  
Granger Causality ◽  
Time Domain ◽  
Economic Activity ◽  
Financial Stress ◽  
Financial Sector ◽  
Stress Index ◽  
Content Type ◽  
Financial Stress Index ◽  
The Time Domain ◽  
The Relationship

PurposeIn spite of the certain risk imposed by financial stress on the real economy, the relationship between financial stress and economic activity is complicated and underresearched, meaning that important gaps still remain in the authors’ understanding of this critical relationship. Therefore, the current study aims to answer the significant question regarding whether a stressful financial sector has predictive power on the real sector and vice versa. Hence, the study examines the causal interrelationship between financial stress index (FSI) and economic activity in Luxembourg as a sample country.Design/methodology/approachIn this study, accompanying the time domain Granger causality framework of Hacker and Hatemi-J (2012), the authors utilize the spectral causality technique of Breitung and Candelon (2006), which is based on the study of Geweke (1982) and Hosoya (1991). This method enables the researcher to measure the degree of a particular variation in time series. Moreover, it allows considering the nonlinearities and causality cycles. The authors further apply the recent method of Farné and Montanari (2018) that is a bootstrap framework on Granger-causality spectra, which allows for disambiguation in causalities.FindingsThe time-domain approach finds evidence of bidirectional causation between the variables. However, the spectral causality results indicate the causal linkages between the series are only valid under the medium-run frequency. This study’s findings emphasize covering the frequency causality to deliver a more comprehensive picture of the interrelationship between the variables.Originality/valueThere are many studies in this area that examine the nexus between financial stress and economic activity. However, the authors believe this paper is the first study in the context of Luxemburg. The authors focus on this country since its financial sector is designated as the most important pillar for the economy. Thus, a careful and reliable examination of the relationship between the financial sector and economic activity is likely to be of considerable interest to policymakers and researchers in this field.

The Cleveland Financial Stress Index

2012 ◽  
Author(s):  
Timothy Bianco ◽  
Mikhail V. Oet ◽  
Stephen J. Ong
Keyword(s):  
Financial Stress ◽  
Stress Index ◽  
Financial Stress Index

The Risk Tolerance Measure in the 2016 Survey of Consumer Finances: New, But Is It Improved?

2021 ◽  
pp. JFCP-19-00022
Author(s):  
Kyoung Tae Kim ◽  
Sherman D. Hanna ◽  
Dongyue Ying
Keyword(s):  
Negative Relationship ◽  
Risk Tolerance ◽  
Stock Ownership ◽  
Survey Of Consumer Finances ◽  
Consumer Finances ◽  
Two Measures ◽  
Complex Patterns ◽  
Relationship Of ◽  
The Relationship ◽  
Different Levels

The Survey of Consumer Finances (SCF) has included a 4-level risk tolerance measure since 1983. In 2016, the SCF also included an 11-level risk tolerance measure. We compare the two measures, and develop suggestions for using the new measure. While the new measure is seemingly simpler than the old measure, we demonstrate that it does not have a monotonic relationship with owning stock assets, with a pattern similar to the relationship of the old measure to stock ownership. We also identify complex patterns of factors related to different levels of the new measure, for instance education has a negative relationship at one level but positive at another level. Those using the new measure should consider the complex patterns we demonstrate.

TOURISM INDUSTRY STRESS INDEX AND ITS RELATIONSHIP TO THE FINANCIAL STRESS INDEX

2021 ◽  
Vol 27 (2) ◽  
pp. 363-383
Author(s):  
Marina Malkina ◽  
Anton Ovcharov
Keyword(s):  
Interaction Design ◽  
Moving Average ◽  
Financial Stress ◽  
Principal Component ◽  
Tourism Industry ◽  
Real Effective Exchange Rate ◽  
Stress Index ◽  
Marginal Effect ◽  
Causality Test ◽  
Financial Stress Index

Purpose – development of the Tourism Industry Stress Index (TSI) and the Financial Stress Index (FSI) followed by an examination of their interaction. Design – The TSI, which aggregates tourist arrivals, overnight stays and net occupancy, was tested on data for Finland, Italy, Germany and Spain between 1993 and 2020. The FSI was composed of the S&P500 index, Brent oil futures, and the real effective exchange rate of the euro. Methodology / Approach – Both stress indices were calculated as the difference between the moving standard deviation and the moving average of the monthly growth rate of the selected indicators. We aggregated them by applying two alternative techniques: arithmetic mean and nonnormalized principal component analysis. The Granger causality test was utilised to assess the dependence between the indices. Findings – We identified periods of increased volatility in the European tourism market and described its connection to financial crises. The causality test of the FSI-TSI model showed that financial turmoil led to increased tourism market stress with an average lag of three months and a marginal effect of 0.2. Originality of the research – We recommend the Financial Stress Index as a predictor of the Tourism Industry Stress Index in the business cycle.

Disparate Recoveries: Wealth, Race, and the Working Class after the Great Recession

2021 ◽  
Vol 695 (1) ◽  
pp. 173-192
Author(s):  
Fenaba R. Addo ◽  
William A. Darity
Keyword(s):  
Middle Class ◽  
Working Class ◽  
Great Recession ◽  
Wealth Inequality ◽  
Net Worth ◽  
The Great Recession ◽  
Consumer Finances ◽  
White Working Class ◽  
Using Data ◽  
The Relationship

What does it mean to be working class in a society of extreme racial wealth inequality? Using data from the Survey of Consumer Finances, we investigate the wealth holdings of Black, Latinx, and white working-class households during the post–Great Recession (pre–COVID-19) period that spanned 2010 to 2019. We then explore the relationship between working-class and middle-class attainment using a wealth-based metric. We find that, in terms of their net worth, fewer Black working-class households benefitted from the economic recovery than white working-class households. Among white households, the working class saw the greatest increase in wealth in both absolute and relative terms. Working-class households were less likely to be middle class as defined by their wealth holdings, and Black and Latinx households were also less likely to be middle class. For Black households, racial identity is a stronger predictor of wealth attainment than occupational sector.

Measuring the Impact of Financial Crisis

2016 ◽  
pp. 274-283
Author(s):  
İsmail Yıldırım
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Financial Crisis ◽  
Global Financial Crisis ◽  
Financial Stress ◽  
Stress Index ◽  
Destructive Effect ◽  
Monthly Data ◽  
Financial Stress Index ◽  
The Impact

Crisis in 2001 and global financial crisis in 2008 effect Turk economy in a lot of ways. Financial crisis creates destructive effect especially on increasing market economies. It is not so easy to watch occurring of this financial crisis and determining of its expanding. First of all determining of crisis terms are needed to predict of financial crisis. In this part, a financial stress index is composed by using TL interest rate and monthly data of global gross reserves belongs to $/TL exchange rate between 1997:01-2014:12 terms for Turkey. Months when financial stress index raised to top level for Turkey and financial crisis are observed on, are found as February(2001) and November (2008).

scholarly journals The Financial Stress Index: Identification of Systemic Risk Conditions

Risks ◽  
2015 ◽  
Vol 3 (3) ◽  
pp. 420-444 ◽  
Author(s):  
Mikhail Oet ◽  
John Dooley ◽  
Stephen Ong
Keyword(s):  
Systemic Risk ◽  
Financial Stress ◽  
Stress Index ◽  
Financial Stress Index
Sign in / Sign up

Export Citation Format

Share Document