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Homework’s Influence on Future Financial Success in the Age of ChatGPT Cover

Homework’s Influence on Future Financial Success in the Age of ChatGPT

International Review of Financial Consumers
Volume 11 (2026): Issue 1 (June 2026)
By: ,   and    
Open Access
|Jun 2026
Figures & tables

Figures & Tables

Education regression results

TechniqueOLS (1)OLS (1)OLS (2)OLS (2)
DatasetNLSY97CNSSNLSY97CNSS
Intercept2.064*** (0.138)4.037*** (0.212)1.874* (1.038)3.048*** (0.253)
Employed 0.396*** (0.094)0.820*** (0.107)
Homework (2)0.738*** (0.086)1.056*** (0.122)0.716*** (0.085)1.011*** (0.118)
Gender-0.430*** (0.053)0.071 (0.098)-0.427*** (0.052)-0.044 (0.096)
Age -0.010 (0.032)0.011*** (0.003)
Race0.560*** (0.054)0.200 (0.127)0.490*** (0.054)0.053 (0.124)
Born in U.S.-0.090 (0.114)-0.055 (0.161)-0.042 (0.113)-0.052 (0.156)
Marital Status 0.385*** (0.053)0.279*** (0.098)
Observations29319782931978
R20.0840.0720.1050.139

Descriptive statistics and variables from the CNSS dataset, (n=978)

VariableDescriptionScaleMeanSD
Homework (1)Response to: “How often did you complete your assigned homework in high school?”1 = Never2= Rarely3 = About half the time4 = Most of the time5 = Always4.141.04
Homework (2)Converts responses to a binary variable0 = About half the time or less1 = Most of the time or always0.800.40
EducationAttained education levelNone of grades 1–8High-school incompleteHigh-school graduate (or GED)Technical, trade, or vocational schoolSome college, no 4-year degreeCollege graduate (4-year degree)Post-graduate or professional schooling5.031.55
Homeownership 0 = Rent or rent-free1 = Own0.630.48
Income, 2016Median of the income bracket rangeLow = 0High = 190,00052,20038,200
Log-income, 2016Natural logarithm of the medianLow = 0High = 12.210.401.76
Age Low = 18High = 9547.9617.93
EmployedEmployment status0 = Not-employed1 = Employed0.660.47
Marital Status 0 = Not married1 = Married0.500.50
Born in U.S. 0 = Not U.S.-born.1 = U.S.-born0.900.30
Race 0 = Non-Caucasian1 = Caucasian0.820.38
Gender 0 = Female1 = Male0.500.50
UrbanIn Metropolitan Statistical Area0 = Rural1 = Urban0.830.38
NortheastCensus Region0 = Not in region1 = In region0.190.39
MidwestCensus Region0 = Not in region1 = in region0.230.42
SouthCensus Region0 = Not in region1 = In region0.390.49
WestCensus Region0 = Not in region1 = In region0.200.40

Log-net-worth regression results

TechniqueOLS (1)OLS (2)
DatasetNLSY97NLSY97
Intercept0.916 (3.108)4.010 (3.204)
Employed-0.424 (0.292)0.277 (0.293)
Homework (2)0.363 (0.254)0.447* (0.265)
Gender0.661*** (0.159)0.874*** (0.163)
Age0.072 (0.095)0.095 (0.099)
Race0.542*** (0.162)0.895*** (0.168)
Born in U.S.-0.749** (0.337)-0.756** (0.352)
Education-0.269*** (0.057)-0.068 (0.057)
Homeownership2.425*** (0.180)
Income0.489*** (0.072)
Marital Status0.920*** (0.167)1.713*** (0.165)
Observations27962796
R20.1410.064

Log-income regression results

TechniqueOLS (1)OLS (1)OLS (2)OLS (2)OLS (3)OLS (3)OLS (4)
NLSY97CNSSNLSY97CNSSNLSY97CNSSCNSS
Intercept6.783*** (0.783)8.385*** (0.353)7.622*** (0.407)8.492*** (0.326)7.196*** (0.815)8.925*** (0.332)8.338*** (0.420)
Employed1.139*** (0.071)0.816*** (0.144)1.139*** (0.071)0.839*** (0.147)1.226*** (0.074)0.961*** (0.141)1.175*** (0.175)
Homework (2)-0.056 (0.065)0.004 (0.159)-0.056(0.065)0.001 (0.159)0.102 (0.067)0.183 (0.155)0.368** (0.171)
Gender0.393*** (0.040)0.064 (0.125)0.393***(0.040)0.062 (0.125)0.299*** (0.041)0.057 (0.126)0.027 (0.144)
Age0.053** (0.024)0.006 (0.004) 0.050** (0.025)0.008** (0.004)0.016** (0.006)
Age2 0.001** (0.000)0.001* (0.000)
Race0.092** (0.041)0.301* (0.161)0.092** (0.041)0.296* (0.161)0.200*** (0.042)0.311 (0.163)0.312* (0.183)
Born in U.S.-0.086 (0.085)-0.009 (0.202)-0.086 (0.085)-0.013 (0.202)-0.095 (0.089)-0.018 (0.204)-0.107 (0.220)
Education0.220*** (0.014)0.177*** (0.042)0.220*** (0.014)0.177*** (0.042)
Marital Status0.151*** (0.040)0.663*** (0.128)0.151*** (0.040)0.672*** (0.126)0.236*** (0.042)0.712*** (0.128)0.675*** (0.144)
Observations293197829319782931978683
R20.1980.1110.1960.1110.1280.0950.117

Descriptive statistics and variables from the NLSY97 dataset (n=2,93l)

VariableDescriptionScaleMeanSD
Homework (1)Response to: “… About how much time did you spend per day doing homework?” (1997)Range: 0–8 hours5.757.27
Homework (2)Response to: “… Did you spend any time doing homework?” (1997)0 = No1 = Yes0.890.31
EducationResponse to: “What is the highest educational degree you have ever received?”1 = None2 = GED3 = High-school diploma4 = Associate/Junior college (AA)5 = Bachelors’ degree (BA, BS)6 = Masters’ degree (MA, MS)7 = PhD8 = Professional degree (DDS, JD, MD)2.721.49
Homeownership 0 = Rent, rent-free, or other1 = Own0.330.47
IncomeAggregated annual incomeLow = 0High = 213,00042,90033,900
Log-incomeNatural logarithm of incomeLow = 0High = 12.310.31.18
Age Low = 31High = 3332.00.82
EmployedEmployment status0 = Not employed1 = Employed0.920.28
Marital Status 0 = Not married1 = Married0.450.50
Born in U.S. 0 = Not U.S.-born1 = U.S.-born0.940.23
Race 0 = Non-Caucasian1 = Caucasian0.540.50
Gender 0 = Female1 = Male0.500.50
UrbanIn Metropolitan Statistical Area0 = Rural1 = Urban0.830.38
NortheastCensus Region0 = Not in region1 = In region0.160.37
MidwestCensus Region0 = Not in region1 = In region0.210.41
SouthCensus Region0 = Not in region1 = In region0.390.49
WestCensus Region0 = Not in region1 = In region0.230.42

Homeownership regression results

TechniqueLogistic (1)Logistic (1)Logistic (2)Logistic (2)Logistic (3)
DatasetNLSY97CNSSNLSY97CNSSCNSS
Intercept-6.394*** (1.844)-5.467*** (0.724)-6.844*** (1.840)-5.242*** (0.725)-6.564*** (0.938)
Employed-0.090 (0.181)0.537** (0.212)-0.109 (0.181)0.642*** (0.208)0.394 (0.274)
Homework (2)0.324** (0.158)0.407* (0.214)0.409*** (0.156)0.553*** (0.207)0.545** (0.253)
Gender-0.096 (0.093)-0.178 (0.176)-0.189** (0.091)-0.189 (0.175)-0.081 (0.211)
Age-0.022 (0.054)0.056*** (0.006)-0.027 (0.054)0.057*** (0.006)0.067*** (0.009)
Race0.569*** (0.096)0.648*** (0.215)0.620*** (0.095)0.647*** (0.214)0.688*** (0.251)
Born in U.S.-0.094 (0.202)0.058 (0.273)-0.085 (0.200)0.058 (0.272)0.401 (0.306)
Education0.144*** (0.033)0.144** (0.058) 0.164** (0.071)
Income0.469*** (0.063)0.116** (0.047)0.556*** (0.061)0.135*** (0.048)0.156** (0.064)
Marital Status1.335*** (0.090)1.528*** (0.175)1.364*** (0.089)1.546*** (0.174)1.534*** (0.204)
Urban-0.438*** (0.121)-0.460** (0.235)-0.382*** (0.120)-0.420* (0.234)-0.761*** (0.290)
Midwest0.753*** (0.150)0.271 (0.267)0.722*** (0.148)0.262 (0.266)0.286 (0.319)
South0.548*** (0.138)0.076 (0.231)0.513*** (0.137)0.057 (0.231)0.008 (0.269)
West0.135 (0.150)-0.369 (0.263)0.105 (0.149)-0.351 (0.261)-0.192 (0.312)
Observations28959782895978683
R20.1910.3340.1860.3300.304
DOI: https://doi.org/10.2478/irfc-2026-0004 | Journal eISSN: 2508-464X | Journal ISSN: 2508-3155
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Language: English
Page range: 49 - 64
Published on: Jun 30, 2026
Published by: International Academy of Financial Consumers
In partnership with: Paradigm Publishing Services
Keywords:
Financial security,
homework,
artificial intelligence,
educational attainment
Related subjects:
Business and economics,
Political economics,
Economic policy,
Business management,
Corporate social responsibility (CSR), compliance management, business ethics,
Industries,
Banks, financial service provider, insurers,
Law,
Commercial law,
Consumer protection

© 2026 Ken D. Shimizu, Scott D. Stewart, Jay L. Zagorsky, published by International Academy of Financial Consumers
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 11 (2026): Issue 1 (June 2026)
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