Abstract

Introduction

I will first present my background so the reader can be aware of potential biases in this account. I am a Chilean and studied as an undergraduate in Chile. My major was in Business and Economics, and then I obtained the equivalent of a Master of Arts in Trade Policy and a Master of Science in Statistics.

I finally decided to continue a Ph.D. after working as a practitioner for several years. I followed that path to develop expertise in critical thinking, project management, and writing. To date, I find that I’m awful at writing.

The worst advice I ever got was “your master’s was in Statistics, it is natural to continue a Ph.D. in Statistics.”

During my master’s, I wrote a thesis in International Trade. I am a statistician interested in applying statistical methods to address specific policy-relevant questions, particularly in international trade, migration, investments and theoretically founded empirical work. My work before starting the Ph.D. was focused on three interrelated areas (I hope it keeps that way):

1. Gravity modelling and the role of information on the implications of models
2. Gravity estimation and efficient software implementations
3. Methodology and data compilation practices

After the master’s, I shortly applied to a top Ph.D. in Statistics program at a highly ranked world-class university. Back then, I applied to one program at one university, something that applicants should never do.

Now I’m at another top program, but this time I’ve learned that realizing one’s strengths and weaknesses is essential.

Main challenges

European Ph.D. programs focus on a specific, while the US/Canada feature 1-2 years of general training. Yet, in both cases choosing a field is not a trivial task. I heard before applying that acquired experience before a Ph.D. is critical, such as internships or a master’s degree, and that you need to find a ‘passion.’

In my own experience, after one year in the program, I found all the things I’ve learned at P. U. Católica de Chile to be sound. But that is not limited to course contents. At PUC, we were told, “We must work well, work with dedication, work at all times. Our work will be contributing directly to the development of society.” That is exactly what you do in a Ph.D.

One thing is to be able to write the IELTS test and obtain a good band. Something very different is to be able to process and elaborate your ideas in a language different from yours.

In my case, I translated books, which was easy because I was taking the same order in which somebody else decided to organize their ideas.

There is also the idea of using scholarly metrics from industrialized countries. Those like me, who come from South America, know that research that impacts our region has to focus on problems that are no longer part of academic fashion in the developed world.

A Ph.D. program is, in my opinion, becoming an expert planner. During my first year, I had to face advanced mathematics courses, which involved high-level abstraction and theoretical discussion that I hadn’t previously accessed.

Because of my background, I had to study day and night to level up, yet to find that I didn’t have the required intelligence, nor would I get ties with genius-level classmates. In my program, I was, by definition, in the lower tier because I had classmates who were true geniuses.

I never thought about anything significant, like solving P = NP. I want to develop structural methods to translate observed trade policy changes and changes in trade costs into policy guidelines at the national and sectoral levels.

A Ph.D. also involves developing the ability to think in ‘linear’ terms, unlike most college and master’s courses, where project completion is highly rewarded. Doctoral-level courses care about many little details. If you can look at abstract problems with a magnifying glass, you might be a successful Ph.D, but there are problems and problems.

In my case, I was interested in problems that ended up poorly fitting with the discipline and the program. I was aware that the issues I’m interested in are at the intersection of Computer Science, Economics and Statistics.

One statistical aspect I love is reading articles and writing software to implement the new methods I find, which has led me to two published articles. Writing software is helpful but won’t count towards points to obtain your Ph.D. or give you a tenure-track position. In short, your GitHub profile has a net value of zero in academia. In industry, it’s a very different story.

Distorted self-metrics

As I’ve mentioned above, a Ph.D. means being a professional planner. In my case, I started a journey of poor diet, insufficient sleep, and studying Monday to Sunday. I fell into the opposite of good planning, drinking coffee at 2 AM on a Wednesday, saying I’ll recover sleep during the weekend, eating a lot of pizza thinking about eating healthy later.

Even when I knew I would never be like the geniuses in the program, the Ph.D. program involves a lot of consistency and self-discipline. You can obtain your degree with dedication and aligned goals for sure. I repeatedly told myself that I was there “Because I Want to Fit In.”

That idea of fitting in led me to have all my meals in front of the computer or with open books, usually working on a proof while trying to fill all my background gaps.

What I’m describing is self-deceit, and it’s not productive. It leads to nowhere.

One of the challenges in gravity modelling (my area of interest) is to produce theoretically consistent models that are also computationally efficient. Still, all those abstract courses I took were not pushing me in a direction to do it better. Another self-deceit is when you consciously ignore that the program is not suitable for you, because you desperately want to obtain the degree at any cost.

Leaving a program

I am older than some of my professors, and I’ve heard many stories about why people leave. Leaving a program is a decision that has influences from all sides. You may feel it is a failure because you do not fit in, or you can feel it will end up in a conflict with your parents or wife.

Some people leave because of not having the right feeling about the program focus or courses. Others face different issues, such as antisemitism or sexism, which shouldn’t happen in an educational context or anywhere.

I wanted to devise a proper measurement of trade frictions, which is crucial for reliable analysis of the impact of international trade and trade policy on welfare and all other economic outcomes of interest to academics and policymakers. Switching programs was the best I could do to achieve that goal.

In my case, I live with a disability, which led me deeply into self-deceit because I didn’t want to leave the program and send a weak signal. I’ve often been infantilized or marginalized because of living with a disability, which should enforce the idea of “I don’t have no time for no monkey business” instead of the concept of fitting in.

Unexpected factors

If you apply to a Ph.D. program, many variables affect the result of the application. In my case, I wrote to and interviewed with different professors and discarded all the options that were not as good in my opinion back then, with limited information or because of the lack of funding.

A Ph.D. program consists of four or more years. During those years, you might (hopefully not!) become seriously ill, get married, move to another city or get an unexpected fantastic offer in the industry. This is a summary of some of the things I’ve heard.

The Ph.D. studies are subject to many external variables as well. We are still in the middle of a pandemic, and COVID-19 influences educational decisions and academic performance.