mit phd in economics and statistics

Doctoral Degrees

A doctoral degree requires the satisfactory completion of an approved program of advanced study and original research of high quality..

Please note that the Doctor of Philosophy (PhD) and Doctor of Science (ScD) degrees are awarded interchangeably by all departments in the School of Engineering and the School of Science, except in the fields of biology, cognitive science, neuroscience, medical engineering, and medical physics. This means that, excepting the departments outlined above, the coursework and expectations to earn a Doctor of Philosophy and for a Doctor of Science degree from these schools are generally the same. Doctoral students may choose which degree they wish to complete.

Applicants interested in graduate education should apply to the department or graduate program conducting research in the area of interest. Some departments require a doctoral candidate to take a “minor” program outside of the student’s principal field of study; if you wish to apply to one of these departments, please consider additional fields you may like to pursue.

Below is a list of programs and departments that offer doctoral-level degrees.

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Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.

A rigorous, hands-on program that prepares adaptive problem solvers for premier finance careers.

A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.

Earn your MBA and SM in engineering with this transformative two-year program.

Combine an international MBA with a deep dive into management science. A special opportunity for partner and affiliate schools only.

A doctoral program that produces outstanding scholars who are leading in their fields of research.

Bring a business perspective to your technical and quantitative expertise with a bachelor’s degree in management, business analytics, or finance.

A joint program for mid-career professionals that integrates engineering and systems thinking. Earn your master’s degree in engineering and management.

An interdisciplinary program that combines engineering, management, and design, leading to a master’s degree in engineering and management.

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A full-time MBA program for mid-career leaders eager to dedicate one year of discovery for a lifetime of impact.

This 20-month MBA program equips experienced executives to enhance their impact on their organizations and the world.

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PhD Students

PhD students in the Finance Group benefit from the teaching, research, and mentorship of MIT Sloan’s world-renowned faculty. Students in MIT Sloan's finance programs will graduate prepared to tackle the challenges of today’s complex global economy—and to teach the business leaders of tomorrow.

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B.A. Economics and Mathematics/Statistics

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B.S. Industrial Engineering and Economics

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B.A. Economics and Finance; M.A. Economics

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B.A. Music and Economics

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B.S. Finance, M.A. Economics

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B.A. Economics and Applied Mathematics

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B.S. Business Administration

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B.A. Economics, M.A. Economics

B.A. Economics

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A.B. Applied Mathematics

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B.S. Mathematics; M.S. Statistics

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S.B. Electrical Engineering; S.B. Mathematical Economics

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B.S. Finance; M.S. Economics

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B.A. Economics; M.A. Economics

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B.S.E. Electrical & Computer Eng., M.Sc. Econometrics and Mathematical Econ.

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B.A. Finance; M.Sc. Economics

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B.S. Economics and Applied Mathematics

B.A. Accounting, M.A. Economics

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The Statistics and Data Science Center is an MIT-wide focal point for advancing research and education programs related to statistics and data science. The Center was created in 2015 with the goal of formalizing and consolidating efforts in statistics at MIT. The Center’s academic mission is to host and develop new academic programs, from a minor to a PhD in statistics and data science. The Center is also a window on the cutting-edge research in statistics and data science that is performed at MIT, characterized by a unique integration of computation and domain knowledge to statistical questions.

The ubiquity and rapid proliferation of data have created unprecedented challenges and opportunities in research for which statistics is a uniquely powerful tool — from economics and anthropology to computer science and environmental engineering. The Statistics and Data Science Center was formed as part of MIT’s  Institute for Data, Systems, and Society (IDSS)  and plays a vital role in addressing these new challenges at MIT. IDSS and the Statistics and Data Science Center provide a shared space for these disciplines, shaping the practice of statistics at MIT and fostering multidisciplinary collaborations that examine some of the most complex societal challenges we face today.

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Master’s in Data, Economics, and Design of Policy (DEDP)

The fight against poverty and inequality is more data-driven than ever before. Producing and understanding rigorous evidence has become increasingly critical for those seeking to affect change globally, but opportunities to acquire these skills remain limited. As the first master’s degree to be offered by MIT’s Department of Economics, the Data, Economics, and Design of Policy (DEDP) program is designed to meet this rising demand. Jointly run by the Economics Department and the  Abdul Latif Jameel Poverty Action Lab (J-PAL ), the program equips development professionals from across the globe with the practical skills and theoretical knowledge needed to tackle some of the world's most pressing challenges. 

Our program draws students with a wide range of backgrounds. Whether they focus on policy, practice, or further academic study, our graduates go on to impactful careers in the development sector and government.

The DEDP program offers two tracks. The International Development Track allows learners to apply the tools acquired through the core courses to explore development issues that are most prevalent in low- and middle-income countries experiencing massive and persistent poverty.

The Public Policy Track will also require learners to rely on the tools acquired through the core courses, but to address a range of public policies, including both local issues and those that transcend geographic boundaries.

Innovative admissions model

The DEDP program employs a unique approach to admissions. Before applying, all students must first successfully complete the online  MITx MicroMasters  credential. No other standardized tests such as the GRE or GMAT are required to apply.

Learners admitted to the DEDP program complete one semester of coursework at MIT and an approved capstone project. Graduates of the program earn a Master of Applied Science in Data, Economics, and Design of Policy from MIT.

This innovative approach to admissions has drawn students from nontraditional backgrounds who not only excel at MIT but also inspire the community with their drive and passion for improving the lives of millions around the world.

A student body that reflects the demographics of the world at large will be better poised to implement change for good worldwide. Esther Duflo, Faculty Director of the DEDP program

Diversity of the study body

DEDP master's students come to MIT from across the globe, bringing with them different perspectives that are shaped by their life experiences. The DEDP class of 2024, comprising 19 students from 16 countries, joins a vibrant community of DEDP students and alumni who are deeply committed to using evidenced-based approaches to alleviate poverty around the world. Learn more about our students and alumni .

Master's in Data, Economics, and Design of Policy: Class of 2024

"These have been some of the best months of my life. I've learned a great deal and met very interesting people who are really on the edge of human knowledge when it comes to economics and doing world-class research." Tomas Dulka, DEDP Class of 2022

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MicroMasters Program in Data, Economics, and Design of Policy

Grapple with some of the world’s most pressing problems from a rigorous, data-driven perspective.

The DEDP Program, previously known as the MicroMasters Program in Data, Economics, and Development Policy, underwent a name change in June 2023 to “ Data, Economics, and Design of Policy'' to coincide with the launch of the new Public Policy Track and to reflect the expansion of the program’s curriculum. For further details on the changes and what they entail for you, refer to our blog and FAQ articles .

About the MicroMasters Program in Data, Economics, and Design of Policy

MIT’s Department of Economics and the Abdul Latif Jameel Poverty Action Lab (J-PAL) designed the MicroMasters® program in Data, Economics, and Design of Policy (DEDP) to equip learners with both practical skills and theoretical knowledge to address pressing global challenges. Taught by esteemed Economics faculty at MIT, including the program’s faculty directors Esther Duflo , Abhijit Banerjee , Sara Fisher Ellison , and Benjamin Olken , the program offers graduate-level courses that combine the modern tools of economics and policy design with a strong foundation in economic and mathematical principles.

The core curriculum covers essential topics such as economics, probability and statistics, data analysis, and designing and running randomized evaluations to assess the effectiveness of social programs. Esther Duflo and Abhijit Banerjee, winners of the 2019 Nobel Prize in Economic Sciences and pioneers in development economics, contribute their expertise on methodologies for poverty alleviation.

The program’s elective courses explore a range of key issues facing society today. These courses are organized into two distinct tracks: International Development and Public Policy .

The International Development Track allows learners to apply the tools acquired through the core courses to explore development issues that are most prevalent in low- and middle-income countries experiencing massive and persistent poverty.

The Public Policy Track will also require learners to rely on the tools acquired through the core courses, but to address a range of public policies, including both local issues and those that transcend geographic boundaries.

You can learn more about the requirements for each track in our relevant FAQ articles .

Earn a MicroMasters Program Credential

Learners can enroll in courses for free on the Audit track or upgrade to the Verified (Paid) track to earn a certificate for each course. More information about course pricing is detailed below, and you can learn more about the two tracks in our FAQ articles .

Students who successfully pass five classes as well as a proctored exam for each class will receive a MicroMasters Credential from MITx. Whether you’re interested in a career in development, public policy, or interested in graduate admissions, this certificate will signal your competence with advanced material. Learners who receive a MicroMasters program credential will be eligible to apply to a DEDP Master’s program at MIT or pursue an accelerated degree at one of our pathway universities around the world.

Who should enroll?

• Students interested in pursuing admissions to graduate programs in development economics, public policy, political science, or related fields
• Mid-career professionals from governments, NGOs, international aid agencies, foundations, and other entities in the development sector
• Academics and evaluators looking to re-tool and apply data-driven perspectives to social and development programs
• Instructors and professors looking to incorporate new material in their courses
• Anyone interested in these topics as life-long learners!

Benefits of the MicroMasters Program in DEDP:

• Reach: Our courses are open to anyone with computer and internet access - there are no formal prerequisites. Anyone can participate!
• Rigor: Courses offer the same challenge as residential MIT classes - and combine theoretical tools with practical skill-building.
• Flexibility: Courses run between one to three times per year - you can spread out the coursework and exams based on your schedule.
• Access: You are charged between $250 and $1000 per course - depending on your ability to pay. You can learn your personal course price directly through your MicroMasters program dashboard.
• Credit: Learners admitted to the blended Master’s program will earn MIT credit for their MicroMasters program courses.

Pricing for the verified track

If you choose to pay for DEDP courses, the course price is determined by your ability to pay. You will need to request financial assistance when you enroll in a course on MITx Online to receive a personalized course price. Learn more about course pricing , or enroll in a course to request financial assistance and calculate your own course price.

Annual Household Income:

• $0 - $25,000: $250 USD per course
• Over $25,000 - $50,000: $350 USD per course
• Over $50,000 - $75,000: $500 USD per course
• Over $75,000: $1,000 USD per course

We offer a limited number of $100 course price coupons to learners with an annual income of less than $10,000 USD. This group of learners is randomly selected in each term through a lottery system. Learners who are not randomly selected in the lottery will retain a course price of $250 according to the pricing tiers above. Learn more about the lottery in our relevant FAQ articles .

We also offer scholarship opportunities for learners in different regions of the world! Please check back in August 2024 for more information about scholarships options for the the fall term.

Questions? Contact our support team at [email protected] .

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Interdisciplinary Doctor of Philosophy in Statistics

Interdisciplinary Doctoral Program in Statistics

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Common core.

All students in the Interdisciplinary Doctoral Program in Statistics are required to complete the common core for a total of 27 units.

Program-specific Requirements

Each student must complete the requirements specified by their home department in the lists below by taking one subject from the Computation and Statistics category and one subject from the Data Analysis category.

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The Heterogeneous Impact of Market Size on Innovation: Evidence from French Firm-Level Exports

A previous version of this paper was circulated under the title: “The Impact of Export on Innovation: Theory and Evidence” We thank, without implicating Daron Acemoglu, Ufuk Akcigit, Pol Antras, Kirill Borusyak, Elhanan Helpman, Giammario Impullitti, Thierry Mayer, Isabelle Mejean, Torsten Persson, Stephen Redding, Thomas Sampson, Dan Trefler, John Van Reenen, Daniel Xu, and participants at the 2017 AEA meeting, the NBER Summer Institute 2017, CIFAR, and numerous seminars for useful discussions and advice. We are grateful to Connie Lee for excellent research assistance. This work is supported by a public grant overseen by the French National Research Agency as part of the Investissements d’Avenir program (ANR-10-EQPX-17, Centre d’accès securisé aux données—CASD) and has received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (grant agreement 786587). P.A. and M.L. thank the support of EUR grant ANR-17-EURE-0001.

A supplemental appendix is available online at https://doi.org/10.1162/rest_a_01199 .

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Philippe Aghion , Antonin Bergeaud , Matthieu Lequien , Marc J. Melitz; The Heterogeneous Impact of Market Size on Innovation: Evidence from French Firm-Level Exports. The Review of Economics and Statistics 2024; 106 (3): 608–626. doi: https://doi.org/10.1162/rest_a_01199

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We analyze how demand conditions faced by a firm in its export markets affect its innovation decisions. We exploit exogenous firm-level export demand shocks and find that firms respond by patenting more; furthermore, this response is driven by the subset of initially more productive firms. The patent response arises two to five years after the shock, highlighting the time required to innovate. In contrast, the demand shock raises contemporaneous sales and employment for all firms regardless of their productivity. This skewed innovation response to common demand shocks arises naturally from a model of endogenous innovation and competition with firm heterogeneity.

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Welcome to Resource Economics

In the Department of Resource Economics, we apply economics to tackle a wide range of questions including those related to the environment, health care, how industries are organized, and human behavior. 

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In the news, upcoming events, spring 2024 seminars.

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• LEO Graduate outcomes provider level data

This is the latest data

Introduction

Leo graduate outcomes provider level data: employment and earnings outcomes of higher education first degree graduates by subject studied and graduate characteristics, with breakdowns by he provider . .

This release updates previously published figures with the latest available data (2021/22 tax year). These are official statistics. For more information on what this means, please see the ‘Official statistics’ section at the end of this publication. 

The 2021/22 tax year overlapped with the coronavirus (COVID-19) pandemic. During this period some support programmes such as the Coronavirus Job Retention Scheme (CJRS) were coming to an end while other programmes aimed at supporting economic recovery such as the Kickstart Scheme had been introduced. The statistics in this release should be understood in this context.

This publication provides information about outcomes for UK domiciled first degree graduates, focusing on outcomes among those adults who graduated from Higher Education Institutes (HEIs) five years after graduation in 2016. Additional information about UK domiciled adults who graduated from all types of Higher Education Provider (that is, HEIs, Further Education Colleges (FECs) and Alternative Providers (APs)) one, three, and five years after graduation is available in the Excel tables that are provided in the ‘Additional supporting files’ section below.

The analysis presented in this publication does not control for differences in the characteristics of graduates who studied a particular subject across different HE Providers. This is a very important consideration when comparing graduate outcomes across providers. A report by the Institute for Fiscal Studies investigated how returns (in terms of earnings) to undergraduate degrees vary by graduates' socio-economic background and ethnicity The returns to undergraduate degrees by socio-economic group and ethnicity | Institute for Fiscal Studies (ifs.org.uk) .

We present the provider median and distribution of graduate earnings by subject and/or region in figures 1, 2, 4 and 8. Provider median is the median earnings across graduates who studied at a particular provider. We also present key points and intervals in the distribution of graduate earnings (upper and lower quartiles, and minimum and maximum values). Care should be taken not to confuse provider median graduate earnings with median earnings of all graduates (regardless of provider). The latter type of median earnings are presented in our publication https://explore-education-statistics.service.gov.uk/find-statistics/leo-graduate-and-postgraduate-outcomes/2021-22 . More information about the definition of provider median is provided in the section below entitled, 'About this release'. 

One of the most detailed breakdowns in this publication is a provider level table which compares employment and earnings outcomes for graduates who studied specific subject areas. You can find this in the ‘Graduate outcomes by provider and subject’ Excel file, within the ‘Additional supporting files’ section below.  

Data on full cycle (home, study and current regions) movement shows graduate movement through the full cycle of study – before entering higher education (home region), during study (study region), and after completing their course (current region). Data for each provider is available in the ‘Full cycle movement data 2021/22’ file under the ‘Additional supporting files’ section below.

This publication does not compare graduate employment outcomes to non-graduate outcomes. The Graduate Labour Market Statistics publication  Graduate labour market statistics, Calendar year 2022 – Explore education statistics – GOV.UK (explore-education-statistics.service.gov.uk) compares the earnings of graduates of working age with individuals who are working age but did not participate in higher education. This publication is not comparable with the LEO data, as it is based on survey data from the Labour Force Survey while LEO uses administrative data sources. For lifetime labour market returns to HE, see  The impact of undergraduate degrees on lifetime earnings: research report . The Higher Education Statistics Agency (JISC) also publishes employment and earnings outcomes based on data collected in the  Graduate Outcomes survey .

Headline facts and figures - 2021-22

The amount of variation in graduate employment outcomes between providers is similar across most subjects.  In the 2021/22 tax year, five years after graduating (in 2016), the greatest variation between providers in the percentage of UK domiciled graduates in sustained employment, further study or both was for graduates who had studied Languages and area studies (47.1% to 96.1%). The smallest variation in this outcome was among graduates who had studied Medicine and dentistry and Veterinary sciences (86.3% to  100.0% and 84.1% to 100.0%, respectively). We have excluded Celtic Studies from this comparison because it is offered by few providers.

The amount of variation in graduate earnings between providers is greater for some subjects than for others. Five years after graduation, the biggest differences in median earnings between providers were for graduates in Computing (£23,400 to £99,600), followed by Economics, Law, and Mathematical Sciences. Again, excluding Celtic studies , the smallest differences were for Sports and exercise sciences and English Studies (£21,500 to £35,000 and £19,700 to £33,900, respectively).

Earnings of graduates from providers in Scotland and the North East are most negatively affected by their graduates tending to work in regions with (on average) lower salaries.  Earnings will be impacted by the region of residence five years after graduation, which may be different to the region of the HE provider. Adjusted earnings figures are therefore provided, based on the overall regional distribution of graduates five years after graduation. This has the effect of raising earnings for graduates from HE providers in Scotland and the North East and lowering earnings for graduates from HE providers in Wales, the North West, and London.

For most providers and subjects, graduates’ earnings have increased at or above the rate of inflation since 2015/16. Between the 2015/16 and 2021/22 tax years, the rate of inflation Consumer Price Index that includes owner occupiers' housing costs (CPIH) was 13.1% based on data published by the Office for National Statistics (ONS). In the 2021-22 tax year, graduates from almost three quarters (72%) of HE providers by subject combinations had median earnings five years after graduation that were at least 13.1% higher than they had been for the 2015-16 cohort five years after graduation.

Graduates’ earnings in some subjects are more strongly associated with their prior attainment than other subjects. The largest difference between median earnings in the top and bottom prior attainment bands was for Economics, at £23,500. Computing had the second largest difference, of £21,900. The smallest difference was for Nursing and midwifery with a difference in median earnings of just £200. The pattern was reversed for Architecture, building and planning; providers with median prior attainment in the lowest band had median graduate earnings five years after graduation that were £6,200 higher than those of providers in the highest median prior attainment band, a finding that could reflect the length and structure of courses leading to qualifications in this subject.

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Additional supporting files

All supporting files from this release are listed for individual download below:

Employment outcomes and earnings by subject and provider (xlsb, 19 Mb) (xlsb, 19 Mb)

Outcomes one, three and five years after graduation by CAH3 subject for HEIs in England, Scotland and Wales and all tax years

Full cycle movement (xlsx, 3 Mb) (xlsx, 3 Mb)

Numbers of graduates domiciled in the UK who have lived in each combination of home region, HE provider region, and region during the tax year that earnings data are reported.

How to read box plots (.doc, 85 Kb) (docx, 85 Kb)

Explains the meaning of box plots

Provider main tables (xlsb, 11 Mb) (xlsb, 11 Mb)

Tables with all the underlying provider data

Provider underlying data 2021-22 (csv, 65 Mb) (csv, 87 Mb)

Underlying provider level data for all tax years and characteristics

Weighted earnings (xlsb, 705 Kb) (xlsb, 705 Kb)

Provider level earnings adjusted for region

About this release

Background  .

The LEO dataset links information about students, including: 

• Personal characteristics such as sex, ethnic group and age;
• Education, including schools, colleges and higher education provider attended, courses taken, and qualifications achieved;
• Employment and income;
• Benefits claimed.

By combining these sources, we can track progress of higher education leavers into the labour market. Further information on the data included in the LEO dataset is provided in the accompanying methodology note, which also contains further information on data quality and match rates. 

Years after graduation (YAG)  

The time periods used in this publication are one, three and five years after graduation, which refer to the first, third and fifth full tax years after graduation. So, for the 2021/22 tax year, we present outcomes for those who graduated in the academic years 2019/20, 2017/18 and 2015/16. Because academic and tax years run between different months, it isn't possible to use exact numbers of years after graduation. We have used outcomes five years after graduation in the sections below but the full range of cohorts is available in the downloadable data. 

We do not include outcomes ten years after graduation because prior attainment data is unavailable for the cohort with outcomes data ten years after graduation. 

This publication includes those who graduated with a first degree qualification from HE providers and FE providers in Great Britain and are UK domiciled. Only data for HE providers is shown in the main text of this publication as they typically have larger cohorts than FE providers. All data is available in the accompanying Excel tables under the ‘Additional supporting files’ section above.   

Employment outcomes for UK domiciled graduates  

The employment outcomes in this publication are grouped into five categories. These are: 

• Activity not captured - graduates who have been   successfully matched to DWP’s Customer Information System but do not have any employment, out-of-work benefits or further study records in the tax year of interest.
• No sustained destination - graduates who have an employment or out-of-work benefits record in the tax year of interest but were not classified as being in ‘sustained employment’ and do not have a further study record. 
• Sustained employment, further study or both - graduates with a record of sustained employment and/ or  further study.  

Of which there are subset groups: 

• Sustained employment only - graduates who have a record of sustained employment but no record of further study.
• Sustained employment with or without further study -    graduates with a record of sustained employment, regardless of whether they also have a record of further study or not.
• Further study with or without sustained employment - graduates with a further study record regardless of whether they have a record of sustained employment or not. This is equivalent to the difference between the ‘sustained employment, further study or both’ and ‘sustained employment only’ categories. 

Provider median

This is defined as the median earnings across the graduates who studied at the provider. This median is obtained by ranking the annualised earnings of all graduates from the provider and taking the value at which half the graduates earning s are higher and half are lower. The median, rather than the mean, is used as the measure of average earnings because it is less affected by the skewed distribution of earnings with relatively small numbers of very high earners. 

Contextual information for providers

The data presented here does not control for differences in the characteristics of graduates, such as ethnicity or socio-economic background. We do, however, provide contextual information about prior attainment and the Participation of Local Areas (POLAR) classification for each provider. This should be taken into account when comparing graduate salaries across providers. 

The type of work/industry of employment and hours worked also influence graduate employment outcomes, and in particular earnings. These factors are not included in this publication.

Participation in higher education is associated with a range of personal and societal benefits that extend beyond earnings. These wider outcomes should also be borne in mind when making comparisons between subjects.

Employment outcomes across providers and subjects

Figure 1 shows the proportion of graduates with a sustained destination (in sustained employment, further study or both) five years after graduation by subject studied. For each subject, proportions are calculated for each provider, and so the range of values for a subject is the range of proportions across all providers. Languages and area studies and Combined and general studies had the lowest median proportions of graduates in sustained employment, further study or both (81.1% and 82.4%, respectively) while Nursing and midwifery and Medical sciences had the highest median proportions (92.9% and 93.5%, respectively). The amount of variation between providers also differed by subject studied. The greatest difference between providers was for Language and area studies (49.0%, ranging from 47.1% for one provider to 96.1% for another) and the smallest difference was for Medicine and dentistry (13.7%, ranging from 85.3% to 100%).

Earnings outcomes across providers and subjects

Figure 2 presents the distribution of provider median earnings  ? (show glossary term definition) for each subject five years after graduation. Each subject is offered by a particular number of providers, so the number of providers included for each subject differs.  

Figure 2 shows that the range of graduate median earnings across providers was greater for some subjects than others. For example, the range of earnings across providers among graduates in Sports and exercise sciences was relatively small (£13,500, from £21,500 to £35,000). By contrast, the median earnings for providers offering Computing varied much more, with a range of £76,300 (£23,400 to £99,600). 

The level of variation in provider median earnings associated with subject studied is likely to be affected by labour market opportunities. For example, some sectors - like the National Health Service - have standardised salaries, which reduces the variation in earnings across providers. 

Provider median earnings were highest among graduates who had studied Medicine and dentistry. This is consistent with the graduate and postgraduate outcomes publication, which presents median earnings of all graduates, regardless of which provider they graduated from (see https://explore-education-statistics.service.gov.uk/find-statistics/leo-graduate-and-postgraduate-outcomes/2021-22 ). Although the ranking of subjects based on median earnings are not identical in the two publications, graduates from the same 12 subjects have highest median earnings in this publication and the graduate and postgraduate outcomes publication. Note that for some subjects, for example Computing, maximum earnings are very high.

Median earnings and prior attainment by provider

The median prior attainment of each provider is based on the UCAS points of each graduate’s top three A level grades. We ranked providers by median prior attainment and then assigned each provider to one prior attainment band, with the top 25% of providers placed in band 1, the middle 50% placed in band 2, and the bottom 25% placed in band 3. Note that this approach to creating the prior attainment bands is different to that used in the  Widening Participation publication (see the methodology document for full details).

Some providers have not been placed in a band and are not included in Figures 3 and 4, below. These providers include Scottish and Welsh providers (as prior attainment data is from an English data source) as well as any provider for which prior attainment information is based on a small number of students. 

Figure 3 presents distributions of median prior attainment across providers for each subject studied. Subjects are ordered by the proportion of providers with graduates who studied this subject in the highest of the three prior attainment bands.  The number of providers in each band is not included in Figure 3 but is shown in the accompanying table. 

The subject with the highest proportion (96.2%) of providers in prior attainment band 1 was Medicine and dentistry. This probably reflects the high entry requirements set by most providers to study Medicine and dentistry.

Figure 4 shows some different patterns between prior attainment and Provider median earnings five years after graduation for selected subjects. Data for other subjects are available in the ‘Provider main tables 2021/22’ file under the ‘Additional supporting files’ section above. 

For Nursing and midwifery, the median graduate earnings across providers are similar for prior attainment bands 1, 2, and 3, possibly because the career paths of graduates in Nursing and midwifery are similar regardless of the provider. For Education and teaching and Creative arts and design, there is an incremental step-like relationship, whereby graduates from providers in the top prior attainment band earned on average more than those who graduated from providers in the middle band, who in turn earned more than graduates from providers in the bottom band. For Computing, and to a lesser extent Engineering, graduates from providers in the highest prior attainment band earned on average substantially more than those from the majority of providers in the lower attainment bands.  

Earnings by subject and sex

Figure 5 shows the difference between male and female Provider median earnings (five years after graduation) by subject, ordered by the proportion of providers whose female graduate median earnings in that subject are more than 15% lower than the median earnings for male graduates. Some providers are excluded because low numbers of females and/or males in the provider studied the subjectand the number of providers included for each subject area is presented in the accompanying table. For example, figure 5 (and table 5) show that of the 33 providers included for Medicine and dentistry, 69.7% had female graduate median earnings that were over 15% lower than their male graduate median earnings.   

Excluding Materials and technology (because we have earnings data by sex for only one provider), in almost two-thirds of subjects (21 out of 33), male median earnings exceeded female median earnings by more than5% for at least half of the providers that offered the subject. The subjects with the largest proportions of providers for which male median earnings were more than 5% higher than female median earnings were Health and social care (90%, 18 of 20 providers) and Nursing and midwifery (83.7%, 41 of 49).

For three subjects, there were no providers for which median female earnings were at least 5% greater than median male earnings. These are Medicine and dentistry (33 providers included), Nursing and midwifery (49 providers included), and Health and social care (20 providers included).

Media, journalism and communications and Chemistry had the highest proportions of providers from which female and male median earnings were within 5% of one other (47.5% and 47.1% respectively).

The subjects for which the highest proportions of providers had female median earnings that exceeded male median earnings by more than 5% were Performing arts (46.3%), followed by English studies , and Media, journalism and communications.

Comparison of outcomes by subject and tax years

In this section, we provide information about how graduate earnings have changed over time for different subjects. We compare Provider median earnings five years after graduation between two cohorts of graduates; those who graduated in 2010 and those who graduated in 2016, with earnings during tax years 2015/16 and 2021/22, respectively. This .  

Earnings outcomes for a certain subject at a particular provider may vary from year to year due to a wide range of factors including changes in the way in which the course is provided, changes in intake, and changes in the graduate labour market. 

Earnings also change with inflation. The rate of inflation according to the Consumer Price Index (CPIH) was 13.1% between the 2015/16 and 2021/22 tax years, and between these years, median earnings increased by at least 13.1% for 72% of provider by subject combinations.

We consider changes in median earnings of “more than 5% decrease”, “within 5%” and “5% to 10% increase” to be decreases in real terms, and consider groupings above this as increases in real terms. For more information on CPIH see  Inflation and price indices - Office for National Statistics (ons.gov.uk) . 

Figure 6 shows how the median earnings of graduates at different providers changed between the 2015/16 and 2021/22 tax years for each subject, ordered by the proportion of providers whose median earnings were more than 20% higher in 2021/22 than they were in 2015/16. Excluding Celtic studies, Computing has the highest proportion of providers whose median graduate earnings increased by over 20% (76.5%). 

The list of subjects (below) for which there was an increase in median earnings for a high proportion of providers between 2015/16 and 2021/22 is similar to the list produced in the previous  publication, which showed changes between the 2014/15 and 2019/20 tax years (see LEO Graduate outcomes provider level data, Tax year 2020-21 – Explore education statistics – GOV.UK (explore-education-statistics.service.gov.uk) . The subjects (excluding Celtic studies) for which median graduate earnings increased by over 10% between the 2015/16 and 2021/22 tax years among at least 90% of providers are listed below: 

• Medical sciences (97.2% of 36 providers),
• Materials and technology (94.1% of 17 providers),
• Sociology, social policy and anthropology (93.3% of 89 providers),
• Computing (91.8% of 98 providers),
• Law (91.4% of 93 providers),
• Allied health (90.9% of 66 providers),
• Psychology (90.7% of 107 providers),

There are no subjects for which median earnings decreased substantially in real terms for the majority of providers. However, for some subjects, median earnings decreased in real terms (less than a 10% observed increase) for at least 30% providers:

• Architecture, building and planning (38.9% of 54 providers),
• Engineering (35.8% of 81 providers),
• Pharmacology, toxicology and pharmacy (34.6% of 26 providers),
• Media, journalism and communications (33.8% of 83 providers),
• Medicine and dentistry (31.2% of 32 providers),
• Education and teaching (30.0% of 70 providers).

Interaction of region and earnings at provider level

On 18th July 2019 we published  regional graduate outcomes , which shows that the regions where graduates live after graduation are associated with the region in which they studied, and that there are regional differences in average earnings. For example, graduates from London providers may be more likely than graduates from providers in the North East to live in London five years after graduation, where average earnings are high relative to other regions in England. 

In order to better understand relationships between studying in a specific provider region and earnings in the region where the graduate lives five years later, we weight the numbers of graduates from each provider region so that the weighted numbers match the regional distribution of all graduates (five years after graduation). For example, if University A has 3% of its graduates living in the North East five years after graduation compared to 12% nationally, then graduates living in the North East from University A would be given a weighting of 4.0 (3% x 4.0 = 12%). More details about this calculation, and the providers included, are in the methodology document for this release. 

Figure 7 shows how the Provider median earnings for providers in each region change when adjusted to account for the regional distribution of their graduates. Regions are ordered by their proportion of providers whose regionally adjusted median was more than 10% higher than their raw median.  

The impact of regional adjustment on median earnings varies a lot between provider regions. More than half the providers in each of Scotland, the North East, the North West, and Yorkshire and The Humber had regionally adjusted earnings that were 5% or more higher than raw earnings, indicating that graduates from these providers typically work in regions with, on average, relatively low salaries. In contrast, half the providers in London had lower earnings after regional adjustment, which indicates that graduates from these providers typically work in regions with average salaries that are relatively high (for example, in London). 

Figure 8 shows adjusted Provider median earnings five years after graduation among graduates from providers in each region. It allows us to compare graduate earnings by provider region net of the impacts of regional differences in earnings. 

After adjustment, providers in Scotland and the North East have the highest median earnings of £34,300 and £33,200, respectively. In contrast, providers in Wales, the North West, and London providers had the lowest adjusted median earnings (£27,200, £27,900, and £28,300, respectively)(. This suggests that prospective students in Scotland and the North East have relatively good access to local providers with good earnings outcomes (after regional adjustment), while those in Wales and the North West have local providers with poorer adjusted earnings outcomes. This similarly applies to prospective students in London, unless, of course, they get into one of the small number of top providers in London for which even adjusted median earnings are very high.

Full cycle movement (home, study and current regions)

Data on graduate movement throughout the full cycle of study – before attending higher education (home region), during study (study region), and after graduating (current region) are provided in the accompanying Excel tables under the ‘Additional supporting files’ section above. Table 6 of the ‘Provider main tables’file provides information about the home region of graduates and the region they live in after graduation. This is broken down by HE provider and sex. We do not include an additional breakdown by subject because numbers of graduates for many combinations are very low. 

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To find information on topics of interest, expand the relevant section. In each section there are tables and charts with a summary of the key points. Some sections include links to pre-prepared summary tables or additional useful documents, like the methodology or Excel tables documents.  

At the top of the release, there is a link ‘Additional supporting files’ which includes: 

• Excel tables documents with outcomes by provider,
• underlying data files used in this release,
• ‘How to read boxplots’ document. 

You can also create your own tables through the  table tool  or modify the pre-prepared tables which use the same files.  

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These are official statistics and have been produced in line with the Code of Practice for Statistics.  

This can be broadly interpreted to mean that the statistics;  

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• are well explained and readily accessible;  
• are produced according to sound methods, and  
• are managed impartially and objectively in the public interest;.

The department has a set of  statistical policies  in line with the Code of Practice for Official statistics. 

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Methodology.

Find out how and why we collect, process and publish these statistics.

These are Official Statistics and have been produced in line with the Code of Practice for Official Statistics .

This can be broadly interpreted to mean that these statistics are:

• managed impartially and objectively in the public interest
• meet identified user needs
• produced according to sound methods
• well explained and readily accessible

Find out more about the standards we follow to produce these statistics through our Standards for official statistics published by DfE guidance .

Our statistical practice is regulated by the Office for Statistics Regulation (OSR).

OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to.

You are welcome to contact us directly with any comments about how we meet these standards. Alternatively, you can contact OSR by emailing [email protected] or via the OSR website .

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