A Practical Guide to a PhD in Economics by Professor Abdoulaye Ndiaye

January 9, 2026 Last updated : January 9, 2026 Guest Blog

This article is for undergraduate, master's, and early-career professionals who regularly contact me for career advice about:

  • What do economists do?
  •  Is a PhD worth it?
  • How do you prepare and apply?

Most of these students are first-generation students seeking answers to the above questions, career advice, or mentoring. However, I am unable to respond personally to all of their individual inquiries, so I decided to address many of these common questions in this article. In this piece, I will focus more on applying and preparing for a PhD in Economics.

Part I The PhD in Economics (What It Is, Timeline, and Reality)

What a PhD is in practice

A PhD is training to produce original research. It is not only “more classes.” It is a shift from learning tools to generating knowledge.

Many programs have a similar skeleton:

  • Core microeconomics, macroeconomics, and econometrics.
  • Field courses (your specialization).
  • Research papers leading to a dissertation.
  • A “job market paper” (your flagship paper used to apply for jobs).

Typical program structure (US vs Europe/UK)

United States (often 5-6 years)

  • Year 1: core sequence (micro/macro/metrics), qualifying exams (“prelims”).
  • Year 2: field courses, research exploration, RA/TA work.
  • Years 3-5/6: research papers, dissertation, job market preparation.

Europe/UK (often shorter after a strong master’s)

  • Many paths start after a research-oriented master’s.
  • The PhD can be closer to 3-4 years focused on research, depending on country and structure.

Practical implication:

  • If you already have a research master’s comparable to US core preparation, you may be ready for faster research onset.
  • If your prior training is less mathematical/technical, a strong master’s or pre-doc can be a high-return step (Part III).

The economist job market (stylized calendar)

The market has variations, but the core rhythm is consistent and centralized:

  • Summer (before the market): finalize a strong draft of your job market paper (JMP).
  • September-November: submit applications; letter writers upload letters.
  • December-January: first-round interviews, often around the ASSA/AEA annual meeting period (see: AEA - Understanding the Job Market).
  • January-February: flyouts (full seminars + meetings).
  • February-March: offers.
  • July-September: start date.

Job market tools commonly used:

Tenure and “publish or perish” (universities)

For research faculty, the incentive system is usually a version of:

  • You have a limited window (often 6-8 years) to build a research record.
  • Publication quality and peer evaluation matter.
  • Seminars and conferences are part of how research is validated.

Research vs policy production (policy institutions)

Policy institutions also value rigor, but the production function differs:

  • Publications may be welcome, but policy relevance and internal deliverables matter.
  • Some research is published as working papers, technical notes, or institutional reports.
  • Clearance/approval processes may exist, depending on the employer.

Postdocs (when they matter in economics)

Postdocs are less structurally necessary in economics than in some lab sciences, but they exist:

  • Elite postdocs: often help “buy time” to strengthen a publication pipeline before tenure pressure.
  • Market-clearing postdocs: can be a bridge when a preferred placement did not materialize immediately.

Decision guide (PhD vs master/pre-doc)

A PhD is usually worth it when:

  • You want to be an academic research faculty (tenure-track / research track) or a research economists in policy institutions
  • You enjoy research work for its own sake.
  • You are comfortable with long horizons and delayed gratification.

A PhD may not be necessary when:

  • You want a policy economist track that values applied expertise over publications.
  • You want industry or consulting (many roles are accessible with a strong master’s + skills).

Part II - Getting In: Applications, Signals, and Preparation

The application package (what is commonly required)

Most econ PhD applications weigh:

  • Transcripts (math, statistics, econometrics matter a lot).
  • GRE (quantitative score is a common filter in many places).
  • English proficiency (e.g., TOEFL/IELTS where required).
  • Letters of recommendation (extremely important; detail and credibility matter).
  • Statement of purpose (clear interests, realistic fit, evidence of preparation).
  • Sometimes: writing sample (varies by program).

Useful AEA guidance pages:

A key clarification: econ is not a “lab model” PhD

In many economics PhDs, you are admitted by a committee into a program. You do not usually apply “to work in Professor X’s lab” as the default structure. Faculty fit matters, but admission is typically program-based.

Implication:

  • You should apply broadly to programs where multiple faculty could plausibly advise your interests.
  • Your goal is not one “perfect professor.” It is a training environment with depth in your areas.

What signals matter most in practice

Common strong signals:

  • Math preparation: beyond basic calculus. Linear algebra and probability are often essential.
  • Econometrics and statistics: proof-based or rigorous sequences help.
  • Research exposure: thesis, RA work, pre-doc, research assistantships.
  • Coding: ability to work independently with data (Python/R/Stata; version control is a plus).
  • Letters: from people who have seen you do research-like work.

Common mistakes to avoid

  • Applying “because I like economics” without evidence of technical readiness.
  • Underinvesting in letters (generic letters are damaging).
  • Treating English as an afterthought. You need to read fast and write clearly.
  • Having interests that are too broad and not connected to any preparation.

For francophone / French-university backgrounds: how to bridge the gap

Many strong African francophone candidates face a predictable gap: the transition to English-first, proof-heavy, and empirics-heavy training environments.

Practical ways to close that gap:

  • English: aim for reading research papers weekly and writing short research memos.
  • Math (if you do not have a scientific baccalaureate and or math undergrad): strengthen linear algebra, probability, and (when possible) real analysis.
  • Proof-based micro: if your curriculum was more descriptive, add rigor before PhD cores.
  • Empirical toolkit: become fluent in one workflow (data cleaning -> analysis -> tables/figures -> write-up).
  • RA culture: learn how to work with a PI: clean deliverables, reproducible code, proactive updates.

Part III - Pre-docs, Masters, and Mentorship: Practical Pathways

Pre-docs / RA-ships, what they are and why they exist

A “pre-doc” is usually a 1-2 year full-time research assistant role. It is designed to:

  • Build hands-on research skills.
  • Help you test whether research is a good fit.
  • Generate strong letters from active researchers.
  • Strengthen your technical portfolio (coding, data, empirical design).

Where to find structured information and postings:

Master’s programs as a signal and as training

In many cases, a strong master’s is the cleanest bridge between an undergraduate curriculum and PhD-level expectations.

A research-oriented master’s can:

  • Provide rigorous micro/macro/metrics sequences.
  • Produce a transcript that is legible to PhD committees.
  • Create access to letters and research assistantships.

Examples (non-exhaustive):

Africa-focused capacity-building and pathways:

Mentorship programs: high leverage, especially for underrepresented backgrounds

Mentorship can reduce information frictions that disproportionately hurt students outside the main networks.

Programs worth knowing:

A practical “resource map” of where to search

Part IV - What to Study in Undergrad If You're Keeping the PhD Option Open

The Core Toolkit for PhD Preparation

If you want to preserve the PhD option, aim to graduate with:

  • Math: multivariable calculus, linear algebra. Add real analysis if possible.
  • Probability and statistics: probability theory + mathematical statistics.
  • Econometrics: at least one rigorous sequence, ideally with proofs and applications.
  • Programming: Python or R (plus Stata is common in applied economics).
  • Writing: the ability to write clearly and concisely is a differentiator.

Three Sample Preparation Pathways

Path A: Economics + Mathematics (classic research track)

  • Year 1-2: calculus, linear algebra, intro stats.
  • Year 2-3: probability, mathematical statistics, intermediate micro/macro.
  • Year 3-4: econometrics, real analysis (if available), research thesis.

Path B: Engineering / CS + Economics (empirical/industry-friendly)

  • Strong math and programming backbone.
  • Add econometrics, causal inference, and at least one applied field.

Path C: Business / Public policy + Statistics (policy/industry bridge)

  • Build a serious empirical toolkit.
  • Add micro theory and econometrics rigor to avoid “surface economics.”

Habits That Matter More Than Taking One Extra Class

  • Read one paper per week (even if you understand 60% at first).
  • Write short summaries. Practice turning intuition into clean statements.
  • Keep your code reproducible. Make outputs easy to verify.
  • Seek feedback early. Iteration is the job.

About the Author

Abdoulaye Ndiaye is an Assistant Professor of Economics at New York University's Stern School of Business. He serves as Theme Leader for the Public Sector research group at STEG and is a research fellow at the Centre for Economic Policy Research (CEPR), CESifo, and the Human Capital and Economic Opportunity Global Working Group (HCEO).

His research focuses on macroeconomics, public finance, development economics, and political economy, with a particular focus on how government can address rising economic inequalities, enhance state capacity in low-income African countries, and shape relationships between social movements and finance.

To learn more about his work, visit his website: https://sites.google.com/view/abdoulaye-ndiaye

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Economics Career, Fellowships, Internships, Jobs, Opportunity Alert, Post-docs, Pre-docs, and Research
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