Money Never Sleeps – Who Sleeps and Earns the Most



When it comes to success, we all know the stereotype: the successful don’t sleep. Whether it’s a tech CEO leading a risky new startup or a famous author working on her latest best-seller, everyone believes that earning more means working more, and working more inevitably means sleeping less. It’s a trade-off most of us expect to make eventually, if we’re not making it already.

Yet when it comes to scientific data to back up this idea, there’s often not much to be found. At Tuck, we wanted to know: how does the sleep/work trade-off really work? Is it really true—statistically true—that sleeping less means earning more? Might there be exceptions to the rule? And how do specific careers compare with one another in this regard?

Without clear answers, we decided to take scientific matters into our own hands. To get to the bottom of these questions, we went straight to one of the most authoritative sources available: the Bureau of Labor Statistics’ 2016 American Time Use Survey. Published annually since 2004, the American Time Use Survey gives analysts, journalists, and social scientists a comprehensive look at how Americans spend their days—including those huge time-takers, work and sleep.

The BLS dataset for 2016 included data from about 10,000 respondents. We used this data to run a regression analysis, which gave us the relationship between hours worked and hours slept we were looking for (read about our complete methodology below).

The results were fascinating. On the one hand, we confirmed some hunches (such as that those in legal professions would, on average, be the highest paid while working the most and sleeping the least). On the other, some results were less predictable. Scientists and architects saw quite high weekly pay, while getting close to average sleep, for instance. And teachers, who you might expect to be both low earners and low sleepers, fell almost exactly at the average in both categories. Though the rule was generally true—the more you work, the more you earn, and yes, the less you sleep—there were a few big exceptions to be found. What you’ll learn about coders will definitely surprise you.

These kinds of comparisons between professions were the real fruit of our analytical labor. Finally, we compiled them into gorgeous charts and assembled them into a handy infographic, to make reading and understanding these findings as pleasant and informative impossible. Check it out, find your job on the charts, and see how your own work and sleep numbers compare to those of other careers.

Our Findings


Data Transformations

The data used for this report was sourced from the Bureau of Labor Statistics’ (BLS) American Time Use Survey for 2016, a survey with roughly 10,000 respondents. We hope to gain some insight about American sleep patterns from the survey. To do this, data has been compiled from three sources:

1) The ATUS Respondent data file, which contains employment and wage information about respondents
2) The ATUS Roster data file, which contains respondents’ basic information such as age and gender
3) The ATUS Activity Summary data file, which contains total time slept per 24 hour period of the ‘diary day’ during which activities are recorded

Data for the linear model is reformatted and modified only to include employed respondents with basic wage and hours worked information (e.g. respondents who did not provide that information were not included) reducing the dataset to 3165 respondents, and moderately limiting the generalizability of any results to the population at large.

Data for the occupation averages is also reformatted to only include respondents with wage, hours worked, and occupation code information, and surveyed on weekdays, limiting the set to just over 1500 respondents. Differences in the the ‘employed’ vs ‘not employed’ sets may be attributable to subjective states of employment (full time / part time, contractor etc) that are not accounted for in this analysis.

With additional resources, the BLS data could be re-weighted to accommodate for generalizability but for now the report should be treated as an exploratory analysis.

Linear Model
Independent variables were added one by one (a hierarchical regression) to the model according to how well correlated they were to the dependent variable (minutes slept) and a qualitative assessment of relevance.

The order of inclusion is as listed in the table below.

At each step, variables were assessed for significance; no variables were dropped from the analysis as all showed as significant. VIF gave no indication of issues of multicollinearity at any stage in the regression.

(Intercept)649.5810511411.7120727555.463< 0.0000000000000002***
WEEKLY WAGE-0.000121700.00002939-4.1420.00003538856***
WEEKLY HOURS WORKED-0.366245400.14400680-2.5430.01103*
MONDAY-85.333334667.28848977-11.708< 0.0000000000000002***
TUESDAY-99.264892037.45254723-13.320< 0.0000000000000002***
WEDNESDAY-84.825966877.50065494-11.309< 0.0000000000000002***
THURSDAY-91.444581887.71517698-11.853< 0.0000000000000002***
FRIDAY-98.511824647.59262418-12.975< 0.0000000000000002***

The Raw Numbers:

Personal care and service occupationsPCS362.73369.5424.4719.9543.13144.36
Food preparation and serving related occupationsFPS398.17240.2330.3916.5541.76133.35
Healthcare support occupationsHCS426.47279.7131.3115.53472.57135.64
Building and grounds cleaning and maintenance occupationsBGCM430.1281.5130.5517.07495.51126.81
Farming, fishing, and forestry occupationsFFF487.68352.2638.4613.81480.3388.34
Office and administrative support occupationsOAS755.36476.5735.8414.33485100.36
Production occupationsP823.84537.5939.4814.86488.79128.29
Transportation and material moving occupationsTMM826.07638.839.416.28506.52153.35
Sales and related occupationsSR843.76765.223817.81490.97116.94
Community and social service occupationsCSS900.04546.8136.3816.57488.17111.59
Installation, maintenance, and repair occupationsIMR956.17415.3942.4611.42462.7190.04
Education, training, and library occupationsETL963.4640.5437.0717.4472.2895.52
Construction and extraction occupationsCE967.5255237.4617.05457.1188.11
Arts, design, entertainment, sports, and media occupationsADESM1046.82747.9532.7316.93434.2191.72
Protective service occupationsPS1108.41709.9841.8920.15445.31159.21
Healthcare practitioner and technical occupationsHCPT1180.9682.7837.6815.13472.12133.27
Business and financial operations occupationsBFO1364.53760.5540.812.08459.6895.66
Management OccupationsMGMT1476.97780.0643.5714.146089.68
Life, Physical, and social science occupationsLPSS1654.36810.0641.5115.88468.08140.62
Architecture and engineering occupationsAE1678.96696.0142.859.75465.7381.85
Computer and mathematical science occupationsCMS1752.05719.7542.419.99477.6287.46
Legal occupationsL1833.48817.4342.3814.67432.5693.82

Fair Use

If you appreciate what you’ve learned here about sleep and labor, please feel free to share our graphic as well as the data as you wish. We simply ask that you link back to this page to credit Tuck as the author of this content.


Published by Mohamed Ebrahim, MBA, CeMap, MLIBF, MCSI

Mohamed Ebrahim Mohamed is an author of books related to Islamic Finance, Financial Reporting, Accountancy, and related topics. Mohamed, is currently based in Birmingham, West Midlands, England, United Kingdom and is a Co-founder, CEO and Director of a Start-up Everest Fin Edu Tech Limited. He utilises his training and experience of over 25 years to find funding solutions for individuals, businesses and property buyers, investors and developers especially for the SME'S. Mohamed, is a Senior Partner with Ace Associates LLP - Certified Public Accountants & CEO of Ace Financial Advisory Limited, he is a CPA Kenya and holds an MBA from The University of Manchester (UK) and B.A (Hons) from Manchester Metropolitan University, He has worked for over 25 years with firms in Kenya -Ernst & Young – Assurance Advisory Business Service & Tax Service lines, PKF Kenya Audit Senior, and Devani –Devani & Co. United Arab Emirates -Group Financial Controller - Credo Investments FZE. Canada – Mc Tavish & Co. CPA’s. A member Institute of Directors (Kenya) and Non-Executive Directors Association (UK). He served on the ICPAK Coast Branch, Executive Council as Secretary and CPD Convener (2013-15) and from May 2016 to May 2018. Vice-Chair May 2018 to June 2020. He was commended by ICPAK in June 2015 for his services to the Accounting profession by ICPAK. Furthermore, Mohamed Ebrahim was awarded a Fellowship of the Institute of Certified Public Accountants of Kenya on.11th December 2020. Educational & Professional details. Mohamed speaks English, Gujerati, Hindi, Urdu, Swahili. Born in an Indian immigrant family from Gujerat India, settled on the Swahili Coast of East Africa for four (4) generations, Bachelor of Arts (Hons) – Sustainable Performance Management Manchester Metropolitan University Master of Business Administration The University of Manchester – Manchester Business School Certified Islamic Finance Executive (CIFE) Advanced. Certified Islamic Finance Executive in Islamic Accounting Ethica Institute of Islamic Finance, Dubai, UAE. ACMA, CGMA, Member, Chartered Institute of Management Accountants and Association of International Certified Professional Accountants, registered as a CIMA Member in Practice. CPA, Practicing member Institute of Certified Public Accountants of Kenya FCFIP, Fellow Member -International Institute of Certified Forensic Investigation Professionals FCT, Fellow Member, Fellow Chartered Treasurer FFA – Fellow of the Institute of Financial Accountants MCIArb - Chartered Institute of Arbitrators, Full Member. MCSI: Member, Chartered Institute of Securities & Investments Institute of Internal Auditors - Member Currently, a Doctoral Student at the Edinburgh Business School, completed the Coursework stage, working on the doctoral thesis Interim Award - Post Graduate Certificate in Business Research methods Short Courses and MOOC’s • The World Bank Group's MOOC on Financing for Development. • Financial Markets an online non-credit course authorized by Yale University, facilitator being Professor Robert Shiller – 2013 recipient of Nobel Prize in Economic sciences • Principles of Valuation: Time Value of Money authorized by University of Michigan • Islamic Financial & Capital Markets -101 - & Structure and Trading of Sukuk102 – by Islamic Research and Training Institute • Islamic Finance & Banking 101 & 102 – Islamic Modes of Finance - by Islamic Research and Training Institute • University Teaching MOOC on Coursera by Hong Kong University. • Oxford Brookes University Business School – Online mentoring Course • ICPAK - Training of Trainers PRESENTATIONS AND PUBLICATIONS Professional Conference paper IICFIP 2014 Global Conference “Creating a Business Culture based on ethics” MBA Dissertation Risk Management in Islamic Financial Institutions Publications in Professional Journals The Accountant – Journal of the Institute of Certified Public Accountants of Kenya • Tax Reforms 1 – Time for a Flat Tax system in Kenya – February- March 2012 issue • Tax Reforms 2 – Specific Tax Simplification Reforms – April –May 2012 Issue • Risk Management in Islamic Financial Institutions – December-January 2013 issue Africa Islamic Finance Report (Volume 1 no, 2)- April- June 2016 • A case for Islamic Sharia Compliant Real Estate Investment Trust (Islamic REITS) in Kenya Others Islamic Home Financing

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