The Curse of Multidisciplinary Research

My life goal is about understanding income inequality. When I was a teenager, my dad was unemployed for many years. He was a single father raising a teenager at the age of 63 who immigrated to the United States from Poland when he was in hid mid 30s. Even though he has a PhD in Chemistry, we struggled financially. Some summers, I would visit my family in Europe with my mother (my parents are divorced). I recognize that this sounds lavish – whisking off to “summer” in Europe. Only the wealthy can use seasons as verbs. But, I lived a dichotomous life between parents. My father has very little, and I worked full time in high school so that I could afford the costs of extracurricular activities and pay for lunch. My mother didn’t pay child support, and she lived alone in a large house echoing Ms. Havasham’s manor. When I visited my mother over the summer, we’d visit family in Europe, and if you stay with family and friends the entire trip, it’s less of a vacation and more closely related to being dropped off at your cousins house.

She had a boyfriend who lived in Vienna (and also Polish). He was unemployed at the same time as my father.  Comparing her boyfriend’s living situation to my father’s life led me to realize that policy matters. A lot. Ever since then, I sought on a quest to research income inequality. As it turns out, there are MANY things that cause income inequality – education, race, gender, occupation, industry, innovation, and the list goes on. In general, capitalism does a lot of agglomerating capital, and we’re constantly trying to figure out how to combat this.

Along the way, because inequality is so multifaceted, I ended up working on a wide range of topics. When you’re a young PhD student, you’re eyes glitter with fascination and the limits of possibilities seem unbounded. And, if my quest was to understand inequality this meant that it would touch a lot of topics. At first, I was interested in development related work and wanted to understand inequality through a macroeconomic point of view. I was surrounded my macroeconomists at The New School for Social Research and they modeled the role of inequality and the distribution of wealth through a macroeconomic view point.  When I took econometrics, this shifted my interest – I loved to estimate! The thrill of empirical work motivated me to search for a PhD program that had a good program in applied economics, but was open to a variety of approaches to economics.

This led me to a PhD at UNU-MERIT, where there were excellent econometricians, and open minded professors. There was true plurality – where you had staunch neo-classical modelers alongside professors who didn’t believe in a stable singular equilibrium. There were lively debates in class and in seminars – it was a place where we could debate over lunch on conditional cash transfers, the myth of homoeconomicus, and gazelles and unicorns. Above all, my interest in inequality started to narrow. I joined UNU-MERIT at the prospect of understanding the role that innovation played on inequality. I started with macroeconomics by looking at the role that economic complexity played on inequality and growth differences, and later found a love with microeconomics – particularly working with big data which presents it’s own challenges.

I was particularly drawn to network analysis. It’s something that I stumbled upon during my Masters studies, and at the time, this was mostly written about by sociologists (Strogratz and Watz, 1998). I thought that if we can understand the world in relative terms, we could have a better understanding about inequality, after all, inequality is relative. During my PhD, there were two papers that I came across that massively influenced me – The Building Blocks of Economic Complexity by Hausmann and Hidalgo, and Skill relatedness and firm diversification by Frank Neffke.  This was revolutionary forme.  I saw that network analysis could capture many complex processes – if we could only merge economic theories with network analysis. And so, that’s what I did in my PhD.

I’m now on the job market, and I feel quite torn.  It is highly competitive, and I’m quickly finding that no one quite understands nor cares about applied network analysis to economic problems (in the USA).  I want to publish in good journals, and I want to show departments that I can publish in these journals. But, economists aren’t quite interested in my topic, especially the approach to my topic. Rather, other disciplinary fields are interested. I can’t publish in the top 5 Economics journals, but I am confident that I can publish in the top 5 Management, Sociology or Social Computer Science Journals. Will economics departments be willing to take a chance on me? Will business schools look past the fact that I am an economist?

At this moment, I am doubting whether I can break into an academic career. I took the wrong path – I wanted to do something somewhat different. It’s creative, but it’s not valued. I don’t know if it’s because of what I am doing that is not valued, or because I am just not good enough to be an academic.  I’m an economist who has broad reaching interests. Is this hurting my chances at a job?

For some encouragement in this moment of uncertainty, I’m going to do something I am always told to never do. I’m going to share my strengths. I will quiet the voice in the back of my head that is constantly yelling at me to, “Be humble. Don’t say that out loud – others can tell you that, but you can’t say that. Well, there are a lot of people who are good at those things. There are also a lot of people who are better at you in those things.” For one moment, here is a list of stuff I know I can do well.

I can teach students who have very little mathematical background about complex quantitative concepts.  I encourage students so that they persevere and become successful in the course – and more importantly, continue studying economics when they doubted themselves. I collaborate well, I listen to others and bring forward disagreements, and my co-authors and I always find a better result this way. I have courage to research topics that aren’t “hot” or popular. I am good at applying other types of quantitative techniques to traditional economic problems. I have creative solutions to real world problems. I am collegial and support others around me. I am good at creating communities and developing new projects. I know how to organize effectively. I network and know a lot of people because I’m interested in a variety of topics – and I connect people to each other. I take part in creating a supportive academic community.

In this last moment of this post expressing utter vulnerability, something we rarely show to one another in academia, I’ll talk a bit about how I see my work developing in the next 5 – 10 years. As I write, I am constantly trying to cobble together some line of research – one identifiable bucket where all of my work fits comfortably. Where I can publish in one place. The problem is that I have varied interests, and as a consequence no “one” bucket exists, and this is treacherous in academic. It’s something I keep a secret – my “real” research agenda. Nonetheless, I’m going to tell you about the projects that I am most passionate about – where I believe interesting work can be achieved and built on. These are big ideas and initiatives that will require an initiative of many, not one. But, what other place can undertake these topics but in academia?

  • Organizational Setting and Mentorship in Tech Firms

Expanding on my research on age and teamwork on the invention process, I would like to investigate the role that organization plays on innovation outcomes. Does the organization determine team selection, and for a subsection of firms, do more innovative firms have different mentorship practices? Using information about ages that we collected, I want to understand team composition within organizational settings, and if there are certain combinations of individuals that spur higher innovative outcomes (either age or inventor experience).

  • Gig Work, Contracts and Income Instability

Using firm level data in Europe that also has information about contracts, I want to investigate the usage of temp. contracts and part-time hours in high tech companies to understand their impact on wages and income stability for workers. I have found that the use of temp contracts is increasing in a few European countries, and I’d like to understand where the rise of the usage of these contracts is coming from, and analyze its impact on wage distribution and income stability.

  • AI Ethics & Survivors of Sexual Assault/Harassment

This interdisciplinary work has developed a NLP algorithm to identify types of harassment based on text and suggest relevant resources regarding the specific attack an individual experiences. The relevant question that we’d like to address is if AI tools are effective means of helping individuals who have experienced sexual assault or harassment. To address this question, we design an experiment where the participant believes that individuals that they chatted with about their experience, and were provided information to help electronically was submitted by a human as compared to a computer. Using sentiment analysis, we will analyze the responses the participant provides to detail if participants interact in a different way towards an AI bot versus a person.

  • Opportunity Index: Creating Policy to Promote Mobility of Opportunity

Individuals are often locked into a location despite other opportunities existing elsewhere. This is especially difficult for low-income or skill-specific individuals. We want to estimate the effectiveness of mobility grants, and also, estimate the financial constraints of moving to certain locations, and secondly, the opportunity cost to move to another location given a certain set of skills.

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