Economist – Definition, Types, Work Area

An economist is a specialist who uses economic theory, data and analytical methods to study how people, organisations and governments make choices under constraints. Economists explain economic behaviour, evaluate policies, forecast trends and communicate evidence that can inform decisions in government, business, finance, research and education.

Introduction

Economists study much more than money, stock markets or national income. They investigate decisions involving employment, education, healthcare, housing, taxation, competition, inequality, energy, technology, the environment and many other areas in which resources are limited and choices have consequences.

Some economists forecast inflation or economic growth. Others estimate whether a public programme improved employment, examine how consumers respond to price changes, study the causes of poverty or assess the costs and benefits of environmental regulation.

This article explains:

• What an economist is.
• What economists study and do.
• The main types of economists.
• How economic research is conducted.
• Which methods and software economists use.
• What qualifications and skills the profession requires.
• How economists differ from related professionals.
• How artificial intelligence is changing economic research.
• Why economic conclusions are often uncertain or conditional.

Key Takeaways

• An economist studies choices, incentives, resource allocation and economic outcomes using theory and evidence.
• Economists work in government, universities, central banks, companies, consultancies, charities and international organisations.
• Their work may involve forecasting, causal analysis, policy evaluation, market research or academic research.
• Most professional economist positions require strong quantitative, research and communication skills; many require postgraduate education.
• Economic findings depend on data quality, assumptions, methods and context, so responsible economists report uncertainty and limitations.
• AI can support research and coding, but economists remain responsible for checking evidence, protecting data and interpreting results.

What Is an Economist?

An economist is a person who applies economic concepts and research methods to investigate how individuals, businesses, institutions and governments allocate scarce resources and respond to incentives.

Economists may:

• Describe how an economy or market is changing.
• Explain why a change may have occurred.
• Predict what might happen under specified conditions.
• Estimate the effect of a policy, programme or event.
• Compare the costs and benefits of different decisions.
• Recommend actions based on evidence and stated objectives.

The term is normally used for someone whose professional work involves economic research, analysis, modelling, teaching or policy advice. However, employers differ in the qualifications and job titles they use.

Economist in simple terms

In simple terms, an economist uses evidence to answer questions about choices and consequences.

For example:

• Why did food prices increase?
• How might higher interest rates affect borrowing?
• Did a job-training programme improve employment?
• How do taxes influence consumer and business behaviour?
• What would be the likely effects of a minimum-wage increase?
• Which environmental policy produces the greatest benefit relative to its cost?

Economist, Economics Graduate and The Economist

These terms should not be confused.

Economist

An economist performs economic research, analysis, forecasting, teaching or policy-related work.

Economics graduate

An economics graduate has completed an academic programme in economics. The graduate may become an economist, but may instead work in banking, management, data analysis, government administration, marketing, law or another field.

A degree describes a person’s education. Economist usually describes a person’s professional role or recognised area of practice.

The Economist

The Economist is an international publication covering economics, politics, business, science and culture. Despite its title, it is not a peer-reviewed academic economics journal.

What Do Economists Study?

Economists study how choices are made when resources, time, information or opportunities are limited. Their research can focus on individual decisions, organisations, markets, governments or entire national and international economies.

Common topics include:

• Prices and inflation.
• Employment, unemployment and wages.
• Consumer behaviour.
• Business investment and productivity.
• Taxation and public spending.
• Poverty and income distribution.
• Education and human capital.
• Healthcare markets and health outcomes.
• International trade and exchange rates.
• Banking, credit and financial stability.
• Economic growth and development.
• Housing and urban development.
• Energy and environmental policy.
• Competition and market power.
• Technology, automation and artificial intelligence.
• Behavioural responses to incentives.
• Economic consequences of laws and regulations.

Microeconomic questions

Microeconomics studies the choices and interactions of individuals, households, workers, firms and specific markets.

A microeconomist might investigate:

• How consumers respond to a price increase.
• Whether a firm has market power.
• How a tax changes labour supply.
• Why some students invest in postgraduate education.
• How hospital competition affects prices and quality.

Macroeconomic questions

Macroeconomics examines economy-wide outcomes and relationships.

A macroeconomist might investigate:

• What causes inflation.
• Why an economy enters a recession.
• How interest-rate changes affect investment.
• Whether government spending stimulates output.
• How productivity influences long-term growth.
• How exchange-rate movements affect trade.

Microeconomics and macroeconomics overlap. Individual and firm-level decisions contribute to economy-wide outcomes, while national policies and economic conditions influence individual behaviour.

What Does an Economist Do?

An economist usually turns a practical problem into a structured research or analytical task. Duties vary substantially by employer and specialisation, but commonly include the following.

1. Formulating research questions

Economists convert broad concerns into questions that can be investigated.

A general concern such as “housing is becoming unaffordable” could be divided into more precise questions:

• How quickly have rents increased relative to household income?
• Is restricted housing supply contributing to higher prices?
• Which groups are most affected?
• Did a particular planning reform change construction activity?
• Would a housing subsidy increase affordability or primarily increase rents?

2. Reviewing theory and previous evidence

Economists examine existing studies and identify relevant theories, mechanisms and unresolved questions.

Theory helps explain why an outcome might occur. For example, a subsidy may increase demand, but its final effect on prices depends on supply responsiveness, market competition and programme design.

3. Collecting and preparing data

Economists may use:

• Government statistics.
• Administrative records.
• Household or business surveys.
• Experimental data.
• Company transactions.
• Financial-market data.
• Satellite and geographic data.
• Historical archives.
• Text from news, laws, reports or social media.
• Data collected through interviews or fieldwork.

Data preparation can involve checking missing values, reconciling definitions, adjusting prices for inflation, matching datasets and documenting how variables were constructed.

4. Building economic or statistical models

A model is a simplified representation of a relationship or decision process.

Models may be:

• Conceptual.
• Mathematical.
• Statistical.
• Econometric.
• Computational.
• Simulation-based.

Models deliberately simplify reality. Their value depends on whether the simplifications are suitable for the question being studied.

5. Estimating relationships and effects

Economists use statistical and econometric methods to estimate quantities such as:

• Price elasticity.
• Wage returns to education.
• Effects of taxes or subsidies.
• Employment effects of policy changes.
• Consumer demand.
• Inflation persistence.
• Economic growth rates.
• Costs and benefits of public programmes.

6. Forecasting

Forecasting economists use historical and current information to estimate future outcomes such as:

• Inflation.
• Employment.
• Gross domestic product.
• Interest rates.
• Tax revenue.
• Product demand.
• Energy consumption.
• Housing prices.

Forecasts should normally be presented with uncertainty ranges, scenarios or explicit assumptions. A forecast is not a guarantee.

7. Evaluating policies and programmes

Policy economists may assess whether an intervention achieved its intended results.

They may ask:

• What happened to participants?
• What would probably have happened without the programme?
• Were the effects large enough to be practically important?
• Did the programme benefit some groups more than others?
• Did its benefits exceed its costs?
• Can the results be applied in another region or population?

8. Communicating findings

Economists communicate through:

• Academic articles.
• Policy briefs.
• Government reports.
• Forecasts.
• Business presentations.
• Dashboards.
• Tables and figures.
• Technical appendices.
• Public commentary.
• Teaching materials.

Good communication separates the evidence from interpretation and explains assumptions, uncertainty and limitations.

How Economists Conduct Research: Step by Step

Although workflows differ, a rigorous economic study often follows nine stages.

Step 1: Define the decision or research problem

The economist specifies what must be understood and who will use the result.

For example:

Did a transport subsidy increase employment among low-income workers?

This is more useful than the vague question “Was the subsidy successful?”

Step 2: Specify the outcome and population

The economist defines:

• The target population.
• The relevant time period.
• The treatment or exposure.
• The outcome variables.
• Important subgroups.
• The unit of analysis.

Employment could mean having any job, hours worked, monthly earnings or sustained employment over one year. These measures may lead to different conclusions.

Step 3: Develop a theory or mechanism

The economist explains how the proposed cause could affect the outcome.

A transport subsidy might improve employment by:

1. Reducing the cost of job searching.
2. Expanding the geographic area in which a person can work.
3. Reducing lateness and absenteeism.
4. Making lower-paid jobs financially worthwhile.

The mechanism guides measurement and interpretation.

Step 4: Identify the counterfactual

The counterfactual is what would have happened to the same people at the same time without the intervention.

Because it cannot usually be observed directly, economists construct a comparison using methods such as:

• Random assignment.
• A similar untreated group.
• A policy threshold.
• A phased introduction.
• A natural experiment.
• A before-and-after comparison with a control group.

A credible counterfactual is central to causal inference.

Step 5: Obtain and assess data

The economist evaluates:

• Coverage.
• Accuracy.
• Missingness.
• Measurement error.
• Consistency over time.
• Sampling design.
• Confidentiality.
• Legal and ethical restrictions.

A large dataset is not automatically a good dataset. Systematic measurement problems can remain even with millions of observations.

Step 6: Select an appropriate method

The method should match the question.

• Descriptive statistics answer what is happening.
• Forecasting models estimate what may happen next.
• Causal designs estimate what changed because of an intervention.
• Structural models examine behaviour under explicit theoretical assumptions.
• Cost-benefit analysis compares valued benefits and costs over time.

Step 7: Estimate and test

The economist estimates the model and examines:

• Statistical uncertainty.
• Model fit.
• Alternative specifications.
• Heterogeneous effects.
• Sensitivity to assumptions.
• Potential confounding.
• Missing data.
• Outliers.
• Measurement choices.

Step 8: Interpret economic significance

A statistically detectable result is not necessarily economically important.

Suppose a programme increases monthly earnings by 0.5%. The estimate may be statistically precise, but policymakers must still ask whether that increase is meaningful relative to the programme’s cost.

Step 9: Document and communicate the analysis

Responsible reporting explains:

• Where the data came from.
• How variables were constructed.
• Which model was used.
• Which assumptions were required.
• How uncertainty was calculated.
• Which analyses were planned or exploratory.
• Whether code and data can be accessed.
• What the study cannot establish.

Common Methods Used by Economists

Economists use different methods for different questions. No single method is appropriate for every study.

Descriptive Analysis

Descriptive analysis summarises what has been observed.

It may report:

• Means and medians.
• Percentages.
• Growth rates.
• Distributions.
• Trends over time.
• Differences among regions or groups.
• Correlations.

Descriptive findings can reveal an important pattern, but they do not automatically establish why the pattern exists.

Regression Analysis

Regression models estimate how an outcome is associated with one or more explanatory variables.

A simple model can be written as:

Yᵢ = β₀ + β₁Xᵢ + εᵢ

Where:

• Yᵢ is the outcome.
• Xᵢ is an explanatory variable.
• β₀ is the intercept.
• β₁ represents the estimated relationship between X and Y.
• εᵢ captures unobserved influences and random variation.

For example, a regression might estimate the relationship between years of education and earnings.

However, regression alone does not guarantee a causal interpretation. Ability, family background, location and work experience may affect both education and earnings.

Elasticity

Elasticity measures how strongly one variable responds to a percentage change in another.

Price elasticity of demand is commonly expressed as:

Price elasticity of demand = Percentage change in quantity demanded ÷ Percentage change in price

If a 10% price increase is associated with a 20% decrease in quantity demanded, the elasticity is approximately −2.

An absolute value greater than one indicates a relatively elastic response. An absolute value below one indicates a relatively inelastic response.

Randomised Controlled Trials

In a randomised controlled trial, eligible units are randomly assigned to treatment and comparison groups.

Randomisation can make the groups comparable on average, allowing differences in outcomes to be attributed more credibly to the intervention.

Economic field experiments have been used to study:

• Education.
• Health.
• Credit.
• Savings.
• Employment.
• Charitable giving.
• Consumer behaviour.
• Development programmes.

Randomised trials are not always ethical, feasible or generalisable. Attrition, non-compliance and spillover effects can also complicate interpretation.

Natural Experiments

A natural experiment occurs when an external event, policy rule or institutional process creates variation that approximates experimental assignment.

Examples may involve:

• Eligibility thresholds.
• Policy changes introduced in only some regions.
• Lottery-based allocation.
• Historical boundaries.
• Unexpected disruptions.
• Differences in timing.

The credibility of a natural experiment depends on whether the variation is plausibly independent of other factors affecting the outcome.

Difference-in-Differences

Difference-in-differences compares changes over time between a treatment group and a comparison group.

The basic estimate is:

(Treatment after − Treatment before) − (Control after − Control before)

Suppose employment rises by 8 percentage points in a region introducing a programme and by 3 points in a comparison region. The difference-in-differences estimate is 5 percentage points.

A major assumption is that, without the programme, the groups would have followed sufficiently similar trends.

Instrumental Variables

Instrumental-variable methods are used when an explanatory variable is correlated with unobserved influences on the outcome.

A valid instrument must:

1. Affect the explanatory variable.
2. Influence the outcome only through that explanatory variable, subject to the model’s assumptions.

Finding a credible instrument is difficult. Weak or invalid instruments can produce misleading conclusions.

Regression Discontinuity

Regression-discontinuity designs exploit a rule in which treatment changes at a threshold.

For example, students scoring below a specific test threshold might receive additional support. Researchers compare individuals just above and below the threshold.

This can produce credible local estimates when people cannot precisely manipulate their position around the cut-off and other conditions change smoothly at the threshold.

Time-Series Analysis

Time-series methods examine observations recorded over time.

Economists use them to study:

• Inflation.
• Interest rates.
• Exchange rates.
• Output.
• unemployment.
• Financial prices.
• Sales.
• Energy demand.

Time-series analysis must account for trends, seasonality, persistence, structural breaks and relationships that change over time.

Cost-Benefit Analysis

Cost-benefit analysis compares the expected benefits and costs of a project or policy, often over several years.

Future values may be converted into present values:

Present value = Future value ÷ (1 + r)ᵗ

Where:

• r is the discount rate.
• t is the number of periods.

Important choices include:

• Which costs and benefits are counted.
• How non-market outcomes are valued.
• Which discount rate is used.
• How uncertainty is handled.
• How gains and losses are distributed.

A policy with positive total net benefits may still create winners and losers.

Structural Economic Models

Structural models represent decision-making using economic theory.

They may model:

• Consumer choice.
• Firm competition.
• Labour supply.
• Investment.
• Household saving.
• Market entry.
• Auctions.
• Tax responses.

Structural models can simulate policies that have not yet been implemented, but their conclusions may depend heavily on theoretical and functional-form assumptions.

Forecasting and Machine Learning

Forecasting focuses on accurately predicting future or unobserved outcomes.

Methods may include:

• Autoregressive models.
• Vector autoregression.
• State-space models.
• Regularised regression.
• Decision trees.
• Random forests.
• Gradient boosting.
• Neural networks.
• Ensemble methods.

Machine learning can improve prediction in high-dimensional settings. Causal questions, however, require more than predictive accuracy. A model that predicts who becomes unemployed may not identify which intervention would prevent unemployment.

Types of Economists

Economists can be classified by subject specialisation, research method or employer. These categories overlap.

Type of economist	Main focus	Example question
Microeconomist	Individual, household and firm decisions	How does a price increase affect demand?
Macroeconomist	Inflation, growth, employment and business cycles	How might an interest-rate change affect inflation?
Labour economist	Employment, wages, skills and labour institutions	Does vocational training improve earnings?
Public economist	Taxation, government spending and public programmes	Who bears the cost of a new tax?
Development economist	Poverty, institutions and growth in lower-income settings	Does access to credit increase household income?
International economist	Trade, exchange rates and cross-border capital	How do tariffs affect domestic prices?
Financial economist	Financial markets, risk and asset valuation	How is risk reflected in asset prices?
Health economist	Healthcare demand, costs, insurance and outcomes	Is a screening programme cost-effective?
Environmental economist	Pollution, climate, resources and environmental regulation	What is the social benefit of reducing emissions?
Behavioural economist	Psychological and social influences on decisions	Do default options increase retirement saving?
Industrial-organisation economist	Competition, pricing and market structure	Does a merger reduce competition?
Urban economist	Housing, transport, land use and cities	How does a new transit line affect rents?
Agricultural economist	Food systems, farming, commodities and rural development	How do input prices affect farm production?
Education economist	Schooling, skills and educational policy	Does class size affect achievement?
Econometrician	Statistical methods for economic evidence	Which estimator best identifies a policy effect?
Business economist	Economic analysis for organisational decisions	How will changing demand affect sales?
Forensic economist	Economic damages and legal disputes	What earnings were lost after an injury?

Where Do Economists Work?

Government

Government economists may work in finance ministries, labour departments, statistical agencies, competition authorities, tax agencies, environmental departments and local government.

Their work may involve:

• Estimating policy effects.
• Preparing budgets and revenue forecasts.
• Analysing employment and prices.
• Evaluating regulations.
• Conducting cost-benefit analysis.
• Producing official statistics.
• Advising ministers and civil servants.

Central Banks

Central-bank economists study:

• Inflation.
• Monetary policy.
• Credit conditions.
• Financial stability.
• Exchange rates.
• Economic growth.
• Household and business expectations.

They may build forecasts, monitor financial risks and prepare analysis for monetary-policy decisions.

Universities

Academic economists usually combine:

• Research.
• Teaching.
• Student supervision.
• Publication.
• Peer review.
• Conference participation.
• Grant applications.
• Administrative responsibilities.

Independent university research positions normally require a PhD. Academic labour markets can be highly competitive.

International Organisations

Organisations such as the World Bank, International Monetary Fund, OECD and regional development banks employ economists to analyse:

• Macroeconomic conditions.
• Development programmes.
• Poverty.
• Debt.
• Trade.
• Public finance.
• Financial stability.
• Institutional reform.

International work often requires advanced quantitative skills, policy experience and the ability to communicate across countries and disciplines.

Businesses and Financial Institutions

Private-sector economists may work in:

• Banks.
• Technology companies.
• Consultancies.
• Retail businesses.
• Energy companies.
• Investment firms.
• Insurers.
• Marketplaces and platforms.
• Property companies.
• Industry associations.

Their questions may concern demand, pricing, competition, market entry, regulation, consumer behaviour or macroeconomic risk.

Research Institutes and Think Tanks

Research organisations employ economists to study public policy and communicate evidence to governments, businesses and the public.

The work may resemble academic research but usually places greater emphasis on policy relevance, shorter publication cycles and accessible communication.

Charities and Non-Governmental Organisations

Economists in nonprofit organisations may evaluate programmes, measure social outcomes, allocate resources or study poverty, health, education and humanitarian interventions.

Real-World Examples of Economist Work

Example 1: Evaluating a minimum-wage increase

A labour economist might:

1. Identify regions or industries affected by the increase.
2. Select comparable unaffected groups.
3. examine employment and wage trends before the policy.
4. Estimate a difference-in-differences model.
5. Test whether pre-policy trends were similar.
6. Examine effects by age, industry and firm size.
7. Report both wage gains and possible employment changes.
8. Explain limitations and uncertainty.

Example 2: Forecasting inflation

A macroeconomist might combine:

• Previous inflation.
• Wage growth.
• Energy prices.
• Exchange rates.
• Inflation expectations.
• Supply-chain indicators.
• Measures of economic activity.

The economist may produce a central forecast and alternative scenarios. A forecast conditioned on stable energy prices will become less useful if an unexpected energy shock occurs.

Example 3: Measuring demand for a product

A business economist might estimate how sales respond to:

• Price.
• Advertising.
• Competitors’ prices.
• Seasonality.
• household income.
• Product availability.

The results could inform pricing or inventory decisions. The economist must consider whether price changes were themselves responses to anticipated demand.

Example 4: Assessing an environmental regulation

An environmental economist might estimate:

• Compliance costs.
• Health benefits.
• Changes in pollution.
• Effects on employment and production.
• Distributional impacts.
• Long-term climate benefits.
• Uncertainty under alternative assumptions.

The final recommendation would depend partly on the policy objective and the values assigned to outcomes occurring at different times.

Positive and Normative Economics

Positive economic analysis

Positive analysis examines what is, what happened or what is likely to happen.

Examples include:

• A tax is estimated to reduce consumption by 4%.
• Unemployment increased during the quarter.
• A subsidy increased programme participation.
• Higher transport costs are associated with lower job search intensity.

Positive claims should be evaluated using evidence, methods and assumptions.

Normative economic analysis

Normative analysis considers what ought to be done.

Examples include:

• The government should increase the tax.
• Income should be redistributed more equally.
• Economic growth should be prioritised over environmental protection.
• The programme is fair.

Normative conclusions involve values, social objectives or ethical judgments. Evidence can clarify likely consequences, but evidence alone may not determine which objective society should choose.

Why the distinction matters

An economist might estimate that a policy increases total income while widening inequality. Whether that policy should be adopted depends on how decision-makers value efficiency, equality and other outcomes.

Responsible analysis makes these value judgments visible rather than presenting them as purely technical facts.

Economist Versus Related Professions

Profession	Main focus	Typical questions	Common methods
Economist	Choices, incentives, markets, policies and economic outcomes	What caused an outcome, and how might a policy change it?	Economic theory, econometrics, forecasting and policy evaluation
Financial analyst	Investments, firms and financial performance	Is an asset or company financially attractive?	Financial statements, valuation models and market analysis
Accountant	Recording, classifying and reporting financial transactions	Are financial records accurate and compliant?	Accounting standards, auditing and financial reporting
Statistician	Developing and applying statistical methods	How should data be collected and analysed reliably?	Sampling, probability, estimation and statistical modelling
Data scientist	Prediction, classification and data-driven systems	Can a model predict behaviour or automate a decision?	Machine learning, programming and data engineering
Policy analyst	Developing and comparing policy options	Which policy is feasible and aligned with stated objectives?	Evidence synthesis, stakeholder analysis and programme evaluation
Market researcher	Customers, products and market demand	What do customers prefer, and how large is the market?	Surveys, interviews, segmentation and consumer analytics

The boundaries are not fixed. An economist may also be a data scientist, statistician or policy analyst, depending on training and role.

Essential Skills for an Economist

Economic reasoning

Economists must understand:

• Scarcity.
• Incentives.
• Trade-offs.
• Opportunity cost.
• Marginal analysis.
• Market equilibrium.
• Strategic behaviour.
• Externalities.
• Public goods.
• Information problems.
• Distributional effects.

Economic reasoning helps organise a problem, but it must be tested against evidence.

Mathematics

The required level depends on the role. Important areas may include:

• Algebra.
• Calculus.
• Linear algebra.
• Probability.
• Optimisation.
• Difference or differential equations.
• Dynamic programming.

Advanced theoretical and econometric work can be mathematically demanding.

Statistics and econometrics

Economists should understand:

• Sampling.
• Estimation.
• Hypothesis testing.
• Confidence intervals.
• Regression.
• Causal inference.
• Panel data.
• Time-series methods.
• Experimental and quasi-experimental design.
• Model diagnostics.

Data management

Research often requires more time for data preparation than for final estimation.

Useful skills include:

• Importing and merging files.
• Reshaping data.
• Creating variables.
• Detecting duplicates.
• Handling missing values.
• Documenting transformations.
• Protecting confidential information.
• Producing reproducible datasets.

Programming and software

Economists commonly use combinations of:

• R.
• Python.
• Stata.
• MATLAB.
• EViews.
• Julia.
• SAS.
• SQL.
• Spreadsheets.
• Data-visualisation software.

The best tool depends on the employer, dataset, method and need for reproducibility.

Critical thinking

Economists must question:

• Whether variables measure the intended concepts.
• Whether a comparison group is credible.
• Whether another explanation fits the evidence.
• Whether assumptions are realistic.
• Whether a result applies outside the study setting.
• Whether uncertainty has been understated.

Communication

An economist must be able to explain technical findings to:

• Other researchers.
• Managers.
• Policymakers.
• Journalists.
• Students.
• Members of the public.

A technically correct study has limited practical value when its findings cannot be understood or used.

Subject knowledge

Specialists also need knowledge of their application area, such as:

• Healthcare.
• Energy.
• Education.
• Banking.
• Competition law.
• Labour institutions.
• Tax systems.
• Agriculture.
• International trade.

Ethical judgment

Economists may work with sensitive information and decisions that affect people’s opportunities and welfare.

Important responsibilities include:

• Protecting personal data.
• Avoiding misleading presentations.
• Disclosing conflicts of interest.
• Reporting inconvenient results.
• Respecting research participants.
• Distinguishing planned from exploratory analysis.
• Documenting methods accurately.

How to Become an Economist

There is no single international pathway. Requirements depend on the country, employer and level of responsibility.

Step 1: Build foundations in economics and mathematics

Useful introductory subjects include:

• Microeconomics.
• Macroeconomics.
• Statistics.
• Calculus.
• Linear algebra.
• Research methods.
• Programming.

Students should not neglect writing and presentation skills.

Step 2: Complete an appropriate bachelor’s degree

Common degree subjects include:

• Economics.
• Econometrics.
• Mathematics.
• Statistics.
• Finance.
• Public policy.
• Data science.
• Business economics.

For some positions, employers require a minimum amount of formal economics coursework even when the degree title is different.

Step 3: Gain practical research experience

Relevant experiences include:

• Research-assistant work.
• Government internships.
• Policy placements.
• Economic consulting.
• Data-analysis projects.
• Undergraduate dissertations.
• Replication exercises.
• Independent portfolio projects.

A strong project should show how the applicant framed a question, prepared data, selected a method and interpreted limitations.

Step 4: Consider postgraduate study

The US Bureau of Labor Statistics identifies a master’s degree as the typical entry-level education for the economist occupation, although some government positions accept candidates with bachelor’s-level economics, statistics or mathematics preparation (BLS, 2025).

A master’s degree may be appropriate for:

• Government economist positions.
• Economic consulting.
• Applied research.
• Policy analysis.
• Forecasting.
• International organisations.
• Specialised quantitative roles.

Step 5: Complete a PhD for research-intensive academic careers

A PhD is normally expected for:

• Independent university research.
• Tenure-track academic positions.
• Advanced economic theory.
• Many senior research positions.
• Some central-bank and international-organisation research roles.

A PhD involves specialised coursework, original research and a dissertation. It should not be treated simply as a higher-paying version of a bachelor’s degree; it is intensive training for producing independent research.

Step 6: Develop a specialisation

Possible specialisations include:

• Labour economics.
• Public economics.
• Development economics.
• Macroeconomics.
• Industrial organisation.
• Environmental economics.
• Health economics.
• Financial economics.
• Econometrics.

Specialisation helps candidates build deeper subject knowledge and a coherent research or professional profile.

Step 7: Build evidence of technical competence

A portfolio might contain:

• A reproducible data analysis.
• A policy brief.
• A forecasting exercise.
• An impact evaluation.
• A literature review.
• A dashboard.
• A replication of a published study.
• Clearly documented code.

Confidential employer or participant data should never be included without permission.

Economist Education in the United States

According to the current Occupational Outlook Handbook:

• A master’s degree is the typical entry-level qualification.
• Some government positions accept a bachelor’s degree with sufficient economics, statistics or mathematics coursework.
• Business, international-organisation and research roles may require a master’s degree, PhD or relevant experience.
• Statistical-software training can strengthen a candidate’s preparation (BLS, 2025).

Requirements for a job titled economic analyst may be lower than those for a research economist position.

Economist Education in the United Kingdom

The UK National Careers Service identifies several possible routes:

• A degree in economics or a related quantitative subject.
• Postgraduate study where preferred by the employer.
• An economist degree apprenticeship.
• Progression from economic research or analyst work.
• The Government Economic Service Fast Stream.

For the Government Economic Service route described by the National Careers Service, applicants generally need an economics degree or a combined degree containing a substantial economics component (National Careers Service, n.d.).

Economist Salary and Job Outlook

Salary figures should always be interpreted by country, year, industry, qualification and experience.

United States

The US Bureau of Labor Statistics reported:

• Median annual pay: $115,440 in May 2024.
• Employment: approximately 17,600 economist jobs in 2024.
• Projected growth: 1% from 2024 to 2034.
• Average projected openings: approximately 900 each year, primarily from replacement needs rather than rapid occupational expansion.

The median is not the same as an average. Half of workers in the occupation earned more and half earned less.

These figures apply to workers classified specifically as economists. Many economics graduates work under other occupational titles and are not counted in that category.

United Kingdom

The National Careers Service lists an illustrative range of approximately:

• £28,000 for starters.
• Up to £60,000 for experienced economists.

Actual earnings may be higher or lower depending on sector, location, seniority and specialisation.

Global interpretation

There is no meaningful single global economist salary. International comparisons are affected by:

• Currency values.
• Purchasing power.
• Public- and private-sector pay structures.
• Local degree requirements.
• Occupational classification.
• Seniority.
• Cost of living.
• Availability of specialist skills.

Economists in Modern Research

Modern economic research increasingly combines traditional economic theory with larger datasets, causal research designs, computational methods and transparent research practices.

The credibility and causal-inference focus

A central concern in applied economics is whether a study has identified a causal effect rather than a simple association.

Researchers increasingly emphasise:

• Explicit identification strategies.
• Research designs based on institutional details.
• Natural experiments.
• Randomised evaluations.
• Sensitivity analysis.
• Pre-analysis plans.
• Transparent reporting.
• Replication.

The aim is not to eliminate uncertainty but to make the basis of a conclusion inspectable.

Administrative and high-frequency data

Economists can now work with:

• Tax records.
• Social-security records.
• Electronic transactions.
• Job-vacancy postings.
• Scanner data.
• Online prices.
• Mobility records.
• Satellite imagery.
• Platform activity.
• Real-time indicators.

These sources can provide detailed or timely evidence, but they also create challenges involving access, representativeness, changing definitions, privacy and computational scale.

Text as economic data

Economists increasingly analyse:

• News reports.
• Central-bank communications.
• Laws.
• Court decisions.
• Earnings calls.
• Job advertisements.
• Political speeches.
• Historical documents.

Text analysis may be used to measure sentiment, policy uncertainty, occupational skills, political emphasis or communication strategies.

Text is not automatically an objective measure. Researchers must justify how documents were selected, processed, classified and validated.

Reproducibility and open research

Reproducible research allows another qualified researcher to understand and, where permitted, rerun the steps used to produce the reported findings.

A strong replication package may include:

• A data-availability statement.
• Variable documentation.
• Data-cleaning code.
• Analysis code.
• Software and package versions.
• A master script.
• Instructions for reproducing tables and figures.
• Explanations for confidential or restricted data.

The American Economic Association’s data and code policy requires extensive documentation and reproducibility materials for relevant empirical, simulation and experimental work submitted to its journals (American Economic Association, 2026).

Digital Tools and Data Sources for Economists

Statistical and programming tools

R

R is widely used for:

• Econometrics.
• Statistics.
• Visualisation.
• Reproducible reports.
• Spatial analysis.
• Machine learning.

Its open-source package system makes it flexible, although package quality and maintenance vary.

Python

Python is useful for:

• Data processing.
• Machine learning.
• Web and application integration.
• Text analysis.
• Automation.
• Large-scale workflows.

It is especially useful when economic analysis overlaps with data engineering or production systems.

Stata

Stata is common in applied microeconomics, health economics, development economics and policy evaluation. It provides integrated commands for data management, econometrics and reporting.

MATLAB, Julia and specialised software

MATLAB and Julia may be used for numerical optimisation, structural models, macroeconomic computation and simulation. EViews is often associated with time-series and forecasting work.

Data-management and collaboration tools

Economists may also use:

• SQL for databases.
• Git for version control.
• Jupyter notebooks.
• Quarto or R Markdown.
• LaTeX.
• Spreadsheets.
• Cloud-computing platforms.
• Secure data environments.
• Reference managers such as Zotero.

Spreadsheets remain useful for checking and communicating small analyses, but complex or repeated workflows are usually safer when transformations are recorded in code.

Authoritative economic data sources

Depending on the question, researchers may use:

• National statistical offices.
• Central banks.
• Labour departments.
• Tax and finance ministries.
• FRED.
• World Bank Open Data.
• IMF databases.
• OECD Data.
• Government administrative records.
• Trusted research repositories.

Researchers should inspect the original producer’s definitions and revision policy rather than relying only on a chart reproduced by another website.

Artificial Intelligence and the Work of Economists

Generative AI and machine learning can assist economists, but they do not remove the need for theory, research design, domain knowledge and verification.

Appropriate AI-assisted tasks

AI tools may help with:

• Brainstorming research questions.
• Explaining unfamiliar code.
• Producing an initial coding template.
• Classifying large text collections.
• Summarising documents for preliminary review.
• Translating code between programming languages.
• Generating test cases.
• Improving the clarity of draft prose.
• Identifying possible robustness checks.
• Creating documentation drafts.

Korinek (2023) groups potential generative-AI applications in economic research into areas including ideation, writing, background research, data analysis, coding and mathematical work.

Tasks that require particular caution

AI outputs should not be trusted automatically for:

• Citations.
• Statistical results.
• Data provenance.
• Legal or regulatory interpretation.
• Mathematical proofs.
• Causal claims.
• Confidential-data processing.
• Literature reviews claimed to be comprehensive.
• Claims about current economic conditions.

AI systems can produce convincing but incorrect text, code and references.

Responsible use of AI

Economists using AI should:

1. Verify every factual and quantitative claim.
2. Run and inspect generated code.
3. Check citations against the original publications.
4. Avoid uploading confidential or personally identifiable data to unauthorised systems.
5. Document material AI use where required.
6. Preserve a reproducible record of the final human-validated analysis.
7. Ensure that a human author remains accountable for the work.
8. Check journal, university and employer policies.

American Economic Association journal guidance states that AI software cannot be listed as an author, material use in manuscript preparation must be disclosed during submission, and authors remain responsible for thoroughly checking AI-assisted outputs.

Will AI Replace Economists?

AI is more likely to change economists’ tasks than eliminate the need for economic judgment.

Some activities can be accelerated:

• Routine coding.
• Data cleaning.
• Document extraction.
• Preliminary summaries.
• Standard forecasting.
• Repetitive reporting.

However, economists still need to decide:

• Which question matters.
• Which data are credible.
• Which comparison identifies a causal effect.
• Whether assumptions are defensible.
• How institutions affect behaviour.
• Whether a result is economically important.
• How competing values should be presented.
• What limitations decision-makers need to understand.

AI may increase the value of economists who combine economic reasoning, research design, data expertise and clear communication.

Advantages of Working as an Economist

Potential advantages include:

• Working on socially and commercially important questions.
• Applying quantitative skills to real decisions.
• Opportunities across government, academia and industry.
• Intellectual variety.
• Transferable data and research skills.
• Potential influence on policy and organisational strategy.
• Opportunities for international and interdisciplinary work.

These benefits vary by role. Academic, government and corporate economists may have very different working conditions.

Challenges of Working as an Economist

Possible challenges include:

• Competitive entry into research-intensive positions.
• Long postgraduate training for academic careers.
• Pressure to produce timely answers from incomplete data.
• Communicating uncertainty to audiences seeking certainty.
• Working with confidential or difficult-to-access data.
• Maintaining technical skills as methods change.
• Distinguishing evidence from political or organisational preferences.
• Public criticism when forecasts are wrong.
• Ethical concerns when analysis affects vulnerable groups.

Limitations of Economic Analysis

Economics is a powerful framework, but economic research does not produce perfectly certain answers.

Models simplify reality

Every model excludes some factors. A model that is useful for one question may be unsuitable for another.

Data can be incomplete or inaccurate

Economic concepts such as productivity, informal employment, expectations and wellbeing can be difficult to measure.

Correlation may be mistaken for causation

Two variables can move together because of:

• Reverse causality.
• A third variable.
• Selection.
• Measurement changes.
• Coincidence.

A causal interpretation requires a credible research design and assumptions.

Results may not generalise

A programme that worked in one country, period or population may perform differently elsewhere.

Researchers should discuss external validity rather than assuming universal effects.

Behaviour changes

People and organisations respond to policies, forecasts and incentives. Relationships estimated in historical data may change after a new policy or technology is introduced.

Forecasts face unexpected events

Wars, pandemics, political changes, financial crises, natural disasters and technological shocks can invalidate assumptions quickly.

Policy choices involve values

Economic analysis can estimate consequences, but questions involving fairness, rights and acceptable risk cannot always be resolved by efficiency calculations alone.

Common Misconceptions About Economists

“Economists only study money”

Economists study decision-making and resource allocation. Money is important, but many economists focus on health, education, crime, families, technology, inequality or the environment.

“Every economics graduate is an economist”

An economics degree provides relevant training, but graduates enter many occupations. The title economist normally reflects a person’s work, role or recognised research practice.

“Economists can predict the future exactly”

Economic forecasts are conditional estimates. They are affected by model uncertainty, data revisions and unexpected events.

“Economists always agree”

Economists may disagree because they use different data, assumptions, models, time horizons or social objectives. Disagreement does not automatically mean that evidence is useless, but the reason for disagreement should be examined.

“A complex model is always better”

Greater complexity can improve realism or prediction, but it can also reduce transparency, increase overfitting and introduce more assumptions.

“A statistically significant result proves a theory”

Statistical significance does not establish that a result is causal, important, unbiased or generalisable.

How to Evaluate a Claim Made by an Economist

Use the following checklist.

1. What is the exact claim?

Is the economist describing, forecasting, explaining or recommending?

2. What evidence supports it?

Look for the original data or research rather than only a media summary.

3. Is the claim causal?

Words such as “caused,” “increased” or “reduced” require stronger evidence than “is associated with.”

4. What comparison was used?

A before-and-after change alone may not show what would have happened without the event or policy.

5. Which assumptions are required?

Forecasts and models are conditional on assumptions that should be disclosed.

6. How large is the effect?

Ask about the size and practical importance, not only whether the estimate is statistically distinguishable from zero.

7. How uncertain is it?

Look for confidence intervals, forecast ranges, alternative scenarios or sensitivity analysis.

8. Who is affected?

An average benefit may hide losses for particular regions, income groups or industries.

9. Does the result apply elsewhere?

Consider whether the population, institutions and period resemble the situation in which the evidence will be used.

10. Are conflicts and limitations disclosed?

Funding sources, professional interests, restricted data and methodological limitations can affect how a study should be interpreted.

Conclusion

An economist is a specialist who combines economic reasoning with data and research methods to study choices, markets, policies and economic outcomes. Economists may describe trends, forecast future conditions, estimate causal effects or advise decision-makers.

The quality of their work depends not simply on mathematical sophistication, but on the relevance of the question, credibility of the data, appropriateness of the research design, transparency of the assumptions and clarity with which uncertainty is communicated.