Due to COVID-19, PhD applicants over the past two years have had quite difficult application periods. It seems common now for students to apply to a range of universities and not be accepted to any of them. In fact, even without this exogenous pandemic factor, admission to economics PhD programs has been becoming increasingly difficult as a result of the excess supply of PhD applicants.

If you go through curricula vitae of recent PhD graduates, you may find it’s not uncommon to see that a PhD owns two master’s degrees. As lots of MA/MSc in Economics programs are one-year programs, some students will pursue an MRes or MPhil in Economics afterwards. Others may opt for a degree in applied mathematics, statistics or another field with an intention to strengthen their quantitative and/or coding skills (summer school programs are another option to do this).

Even more common in those CVs is seeing a predoctoral research assistantship (henceforth, “predoc RA”). For many students, this job was done during their bachelor’s or master’s studies, while for others, it was a full-time predoc RA position in the interim before their PhD programs. Both of these cases are what the phrase “predoc life” refers to in this article.

As a current PhD student who has fairly recently experienced the application process, and who has quite a few friends and peers who have also had this experience, I’m sharing this overview to help others who are considering a PhD. This article is specifically for those students who are not sure whether to apply to a PhD straight away, or to extend their predoc career first.

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The pros and cons of predoc life

There are differing viewpoints about whether prolonging your predoc life is helpful or not. Although receiving broader academic training, replacing the current GPA with a better one, and developing a more fully-fledged research idea are some of the many pros, the cons deserve to be shared. Given increasingly difficult admissions (which has been observed, but as of this writing not proven), a second Master’s without plenty of advanced courses and excellent grades may even hurt your chances of being admitted to a PhD program. Likewise, a full-time predoc RA position does not necessarily help a lot if the professor is not truly satisfied with your work and would not give strong support to your application.

Anyhow, a research Master’s, predoc RA, or even a combination (a few master’s programs actually offer RA positions to all admitted students, such as the Master in Quantitative Economics at LMU Munich) tend to be indispensable for candidates who want to earn a place in prestigious programs, although the minimum requirement of some of those programs on the surface may just be a Bachelor’s degree.

A PhD fellowship is highly demanding, even beyond top-ranked programs. For that reason, many students have to choose between a fully-funded fellowship or a more prestigious program. On the one hand, more prestigious programs are more selective, offering self-funded admission or partial scholarships (tuition waiver or similar) to candidates who are qualified but less competitive in their intake year. On the other hand, “aiming lower” can make applicants eligible for full scholarships in some other programs.

What are common PhD pathways?

Regardless of program choice, sometimes we have no choice but to catch up with our peers, or we may simply self-select and join this marathon. Reasons we do so are complicated. Earlier this year, one of my friends discussed her PhD application with me. Both of us had the same concern that we were not yet well-prepared to be competent in carrying out research after our two-year Master's studies.

Thus, we preferred a structured PhD program involving one to two years of intensive coursework, which corresponds to an MRes or MPhil in Europe but is a default component of PhD programs in the US. I bet we are not the only two people on this planet who were not confident, and puzzled by whether we should extend this “prelude”.

Our concern is somehow endemic to the EU, as, unlike the US, students here generally have two application paths with funding opportunities. One path is position-oriented, often tied to a funded project where the principal investigator (PI) who will be the supervisor can decide the candidacy. Whether applicants’ previous research experience and their proposals fit the project are often the most important factors in the decision. And the application highly hinges on timing – you cannot predict when a PI will obtain a grant and start recruiting a PhD.

This is a traditional pathway in many European countries, including the UK, Germany, Sweden, Spain, etc., for both professors and students to find each other. The positions are typically funded for 3–4 years, with strong heterogeneity across countries, universities and disciplines. Candidates will then be employed as faculty and mainly work for the project they applied to. In most cases, there is no more coursework prior to the dissertation stage.

In contrast, the other pathway is more like the US where the intake is routinely organized with a definite starting date and application deadline. Admission is relatively more merit-based, i.e., utilizing GPA, IELTS and/or GRE scores, and scrutinized by a committee. Top-ranked students will usually receive scholarships with no obligation to teach or assist in research, while others may apply for teaching or research assistantships to get financial aid.

These PhD programs may or may not include a one- to two-year Master’s component. More and more Economics programs do include one, particularly among those that offer funding. Some students accepted in the first pathway will also be enrolled in these programs. There are also similar types of programs that are open for applications throughout the year, but candidates are often required to seek funding opportunities on their own in this case.

Will your studies adequately prepare you for research?

Let’s get back to our puzzle. Should you prolong your predoc life? I do not deny that additional coursework could be helpful and provide more buffer time to allow students to adapt to research. Yet when my friend said she thought she needed it to underpin her research abilities, I started wondering if this is truly the case. Why were we not trained well enough by our Master’s to be capable of doing research right away?

Research is a new domain and requires its own set of skills. Consider that time spent on coursework can indirectly help students develop research abilities. My friend thinks (and I used to agree) that we do not really master what we were taught, but as we have learned topics once, we will understand them better if we learn them again.

Suppose we attend a course in fall 2021 and start a relevant research project in spring 2023. To what extent will we still remember those details? Will we need to learn them a third time? Will a mathematical proof perfectly done in the exam enable us to apply it practically in our projects right away? Will specialized courses taken during a program cover all the knowledge we need for our research?

To be very honest, I’ve found that things I learned from the majority of my courses are irrelevant to my research. This is because as our studies become more advanced, the content of courses becomes narrower and narrower and relies more or less on lecturers’ research interests. Thus, if you have been taught income inequality in a Development Economics course, when you later undertake research on human development you may still need to cover some gaps on your own.

However, this doesn’t mean that those courses are useless. They are meaningful in a way besides directly contributing to my work – they made me aware of what are canonical and/or cutting-edge studies in many subfields and whether I am interested in them or not. Therefore, exposing you to some topics and helping you explore your interests are part of their true value.

The importance of “learning by doing”

I believe we can never be truly “well-prepared” for research. We may often find ourselves falling short in certain knowledge or skills, but we cannot rely on classes and exams forever. My personal experience is that “learning by doing” makes more sense. It’s always somewhat of a mystery until you actually try to do it. This, not uncommonly, goes beyond what you learned in courses such as advanced microeconomics or econometrics and into something much more “niche”.

However, we can hardly figure these things out ex ante. When we kick off our research, we should not only identify gaps in scholarship but also in our own knowledge. In fact, I think learning and researching often co-evolve during my work. When I do a literature review, I always learn about new models, theories or econometric techniques that are not so classical and thus not covered in courses.

Following the literature review, I may choose a few favorite articles as a starting point, think about what they didn’t address and what virtues I can absorb, and accordingly what else I can do based on them. In my case, this could lead me to a better dataset, a new methodology and/or a more refined model. For the latter two, reading and learning from recent articles and books is often important, as all traditional approaches have already been done – after all, how else did they become traditional but by being done often?

In conclusion: recommendations for students

Personally, I would suggest students try a part-time RA in parallel with their studies rather than directly jumping into a second Master’s or other program, ceteris paribus. If this is not an option for you, in my humble opinion, a research Master’s with RA opportunities or a Master’s in statistics or data science is a good option. This is because they can at least improve your employability in industry (if you change your mind, you can apply for an internship before your graduation – enrollment is important in some EU countries for finding interns).

Instead, doing a full-time predoc RA would be more ideal if you are very certain that you want to do a PhD. It will take some commitment, but if you are dedicated to getting your PhD, the payoff could be worth it.

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