◆ Economics

What a labor economist
really does.

20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.

20evidenced tasks
17,790in the US (2025)
$124,720median pay / year
8systems it runs on
See the 20 tasks ↓Open in the atlasThe full career map →
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Forecast economic trends
Produce a six-quarter forecast of employment, wages and vacancy rates …3 sources agree

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The work, task by task

20 tasks
Hands on the work14
Forecast economic trends+
Produce a six-quarter forecast of employment, wages and vacancy rates for the retail sector using historical labour force and payroll series, document model assumptions, run scenario with a mild recession shock, and deliver a one-page note with headline forecasts and confidence bands.
escojdwiki3 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Evaluate policy impacts+
Evaluate the impacts of the proposed minimum wage increase on employment, hours, and household incomes using difference-in-differences on administrative payroll data, test robustness with alternative controls, and produce a technical appendix with codebook and sensitivity tables.
jdonetwiki3 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Analyze market activity and trends+
Produce a market activity report for the past three years that identifies shifts in employment, wages, and vacancy rates, decomposes drivers by industry and region, flags emerging sectors, and summarises implications for hiring policy in a two-page executive brief due next Monday.
jdwiki2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Analyse statistical data+
Clean and analyse the household survey microdata to estimate hourly wage distributions, run quantile regressions controlling for education and experience, produce tables of coefficients with standard errors clustered by PSU, and deliver reproducible scripts plus a results summary by Thursday.
escojd2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Write about economic policy+
Draft a policy brief arguing for a phased minimum wage increase: present theoretical channels, summarise evidence from three comparable countries, simulate employment and income effects under two scenarios, and finish a 1,000-word draft for departmental review by Wednesday.
escowiki2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Advise on product feasibility+
Estimate whether this new consumer appliance can sustain a profitable national rollout: model expected demand by income decile, incorporate wage and unemployment elasticities, cost curves, and a two-year cashflow scenario, then recommend go/no-go with sensitivity runs.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Advise on tax policies+
Assess the labor market effects of the proposed tax change: simulate employment and hours responses across sectors using earnings elasticities, estimate distributional impacts by income percentile, calculate revenue and deadweight loss, and advise on mitigations.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Forecast production and consumption of renewable resources and supply, consumption, and depletion of non-renewable resources.+
Forecast annual production and household and industry consumption of renewable resources and annual supply, consumption, and estimated depletion years for coal, oil, and natural gas for 2026–2035 using historical production series, reserve estimates, and projected demand scenarios; flag model sensitivities.
onet
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Grow the practice3
Watch and assess2
Work with people1

What the work runs on

named inside the evidenced tasks
12 tasksMicrosoft Excelbuilds time-series forecasts, scenario runs and calculates confidence intervals from labour datasetsOpen its task library →
8 tasksIBM SPSS Statisticsruns the econometric DID models and robustness checks and generates tables
7 tasksMicrosoft Wordcompose the syllabus, assignments, and reading list as a formatted document for distributionOpen its task library →
2 tasksMicrosoft SQL Serverstores and queries large administrative payroll datasets for quasi-experimental analysis
2 tasksMicrosoft PowerPointpresent the recommendation and sensitivity charts to stakeholders
1 taskMicrosoft Power BIingest time series data, produce visualisations and regional decompositions for dashboard and exportable figures
1 taskMicrosoft Accessstore and relate multiple source tables, enforce codebooks, and produce a merged longitudinal dataset
1 taskMicrosoft Outlookschedule recurring meetings, send assignments and track deadlines with calendar and email
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The same task, four heights

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ExecuteDo today's task, with fewer mistakesyou are here → ImproveMake it easy for the next person to acceptin the atlas → DecideWork out the right move when it is unclearin the atlas → BecomeLearn the pattern so it stops coming backin the atlas →

Can AI actually do this job?

the honest answer

It can

where it genuinely helps
  • Explain the theory behind the work
  • Draft, tidy and structure your writing
  • Rehearse a hard conversation before you have it
  • Build a study plan that fits your gaps

It cannot

where it stops, completely
  • Be in the room where a labor economist actually works
  • Carry the responsibility when the call is wrong — that weight stays yours
  • Notice what no one wrote down: the hesitation, the thing left unsaid
  • Live with the outcome
M · R6 of R7This job sits on earning — real theory, real diagnosis, but reality still holds the grading pen.

What the work pays

two countries, two different measures

United States

this exact occupation · BLS 2025
  • $124,720 a year — the middle: half earn more, half earn less
  • The lowest tenth earn near $67,360; the top tenth near $238,060
  • 17,790 people employed in this occupation

India

the occupation GROUP, not this job · PLFS via ILOSTAT 2025
  • ₹38,298 a month — the median for Professionals, the group this work sits in
  • India publishes pay by broad occupation group, so this covers many jobs besides this one. It is a shape, not a salary.
read this carefullyThese two numbers are not comparable and must not be converted into each other. One is a yearly figure for this job alone; the other is a monthly figure for a whole family of jobs. What travels between them is the pattern, not the amount: experience lifts pay almost everywhere.

Where the evidence lives

open any of it yourself
O*NETThe US Department of Labor's own record of this job7 of these tasks ESCOThe European skills and occupations register7 of these tasks Job descriptionsReal postings, in the wild10 of these tasks WikipediaHow the world describes this work7 of these tasks US Bureau of Labor StatisticsPay and employment, by occupation2025 figures UK NOS FSPISM10Analyse and report investment implications of national economicsnational standard

Close to this work

12 nearby
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Questions people actually ask

A typical day mixes data work, meetings, and writing. Morning might mean cleaning datasets in Excel or running queries in Microsoft SQL Server to pull employment or wage data. Midday you might run stats in IBM SPSS or draft charts in Power BI for a briefing.

Afternoon often has meetings with policy teams, teaching a class, or writing a report in Word and PowerPoint. You also review others' papers, supervise students or research, and sometimes prepare materials for public presentations or testimony.

Start with Microsoft Excel and PowerPoint: Excel for data cleaning, pivot tables, and basic regression; PowerPoint for presenting results. Many employers expect strong Excel skills.

Next learn Microsoft SQL Server for pulling large datasets, then IBM SPSS Statistics (or similar like Stata/R) for statistical analysis. Learn Power BI for dashboards and Word/Outlook for reports and communication.

Labor economists overlap with data scientists and statisticians but focus on economic questions: wages, employment, policy impacts, and resource allocation. You use the same tools (SQL, SPSS/R, Excel) and methods (regression, forecasting).

The difference is subject matter and interpretation: labor economists translate numbers into policy advice, teach economic theory, and write reports or testimony. If you prefer proving models and coding at scale, data science might be closer; if you like economic theory and policy, this is the role.

AI can speed literature reviews, draft report text, suggest code snippets for SQL or SPSS, and help visualize ideas for Power BI. Use it to generate first drafts or brainstorm model specifications, not to replace your analysis.

Always verify outputs: check statistical code line by line, validate AI-suggested models against theory and data, and cite original sources. Never use AI to fabricate results for reports, expert testimony, or policy recommendations.

You gather pre- and post-policy data (employment rates, wages) using SQL or public datasets, clean them in Excel, and run statistical tests in SPSS or equivalent software. Common methods include difference-in-differences or regression analysis to control for confounders.

Then you write results as reports or presentations in Word and PowerPoint, discuss limitations, and possibly provide testimony. Peer review and replication by others are common steps before claiming strong causal effects.

Per the U.S. Bureau of Labor Statistics (BLS), about 17,790 people work in this occupation. The median annual wage is $124,720; the lowest tenth is $67,360 and the top tenth is $238,060 (BLS).

Pay varies by employer type: think tanks, government, universities, or private consulting. Advanced degrees, published research, and supervisory or litigation-expert roles tend to push pay toward the top decile.

Strong applied regression skills are essential: know how to run, interpret, and check linear and logistic regressions, and methods like difference-in-differences. Employers expect you to justify model choices and check assumptions.

You should be able to implement these in IBM SPSS Statistics (or R/Stata) and extract data using Microsoft SQL Server, then show results clearly in Excel and PowerPoint.

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