Introducing new PhD Scholar Graham Mazeine

Get to know Graham, one of this year's Stone PhD Scholars.

‍

We're delighted to welcome Graham to the Stone Centre as one of our 2026/2027 Stone PhD Scholars. We caught up with Graham to hear how a switch from History & Politics led to economics, and what the current wave of technological change might mean for young workers.

‍

Could you tell us a little about your academic background and how you came to economics?

‍

In my late teenage years, I developed a keen interest in public affairs — international relations, domestic political debates, really anything that involved politics and policy. So, I started off my undergraduate career studying History & Politics, following that old idea of trying to understand the present and the future by first understanding the past, etc. What I came to learn, from studying my course (and observing with slight jealousy what some of my friends studying economics were learning about), was that my interests lay in how and why individual actors in society (people, firms, governments) make decisions, how those individual decisions combine to produce society-level outcomes, and what role public policy should have in trying to improve the outcomes of those micro-level decision-making processes. I came to realise that, far from being simply about money and finance, economics gives us the best toolkit to study virtually any situation in which human decisions and well-being are centre stage, primarily because it has developed the best methods to give precision and rigour to claims about causality — a concept that is at the root of all the topics in social science that I find most interesting to think about. So, I switched to studying economics (along with politics and philosophy) at the end of my first year, and the rest is history!

‍

What made you want to do a PhD, and was there a particular question or moment that drew you to your topic?

‍

During my undergrad days and for a bit of my master's, I planned on pursuing a career in policymaking — working either in government or at an economic policy think tank seemed like the most appealing paths to me, but I was a bit wary of having to be told what questions to research or policies to analyse, and of working in an environment where output quality might have to be compromised in the name of meeting a deadline. I loved doing research and studying questions that I found personally interesting, so I thought that looking for a job as a research assistant at an economics department would be a good halfway house, giving me more hands-on research experience and helping me decide whether I really was ready to exit academia forever.

‍

My time working as a research assistant to Alan Manning at LSE was crucial in awakening my interest in imperfect labour markets, and in doing a PhD more generally. Alan's body of work shows that in general, labour markets don't adhere to the neoclassical assumptions of perfect competition, wherein there is a single market-clearing wage, and anyone who wants a job at that rate of pay can find one without any cost. Challenging these assumptions opens up a world of new questions that simply can't be studied under the old paradigm of fully competitive, perfect-information labour markets: what should the tax system look like if employers have wage-setting power, or if it's costly for workers to try to find a new job? How do the implications of technological change differ under frictional labour markets, or when early-career workers have to experiment to find out where their comparative advantages lie? By the end of my time as an RA, I had decided that there was still so much work to be done in these areas of research, not just for academic interest but also as inputs to better economic policymaking, that the biggest impact I could have would be through studying some of these questions as part of a PhD.

‍

How would you explain your research to someone outside economics in a few sentences?

‍

The average person knows that it takes time to find a job, and that sometimes you get laid off through no fault of your own; that different employers pay different amounts and have different non-wage attributes that might make them a better or worse place to work, independently of what your salary is today; and that different jobs offer different opportunities for skills formation, or to move up the internal company ladder. And yet, many of the policy prescriptions in areas like taxation, unemployment insurance, and minimum wages come from models where economists assume that none of those things are true! My research, along with a growing body of work from other scholars, tries to take a more realistic approach to thinking about how labour markets work, in order to think through how the government should set taxes, provide social insurance, and respond to technological change in the real world.

‍

What made you interested in how technological change affects the way workers' pay and careers progress, and which workers do you suspect are most at risk of being left behind?

‍

Workers that are early in their careers are often still in the process of developing the skills that will pay off for them in the long run, or even still figuring out what types of jobs they are good at or enjoy doing. Historical episodes of technological change have always generated shifts in the composition of employment across sectors and occupations that affect certain types of workers more than others, but the advent of mass-use generative AI tools like ChatGPT and Claude seems unique in that young workers in entry-level jobs are particularly exposed relative to older workers.

‍

Since entry-level positions are not just about production, but also help to build worker skills and identify their various talents and abilities — both of which help to reduce mismatch in the labour market and get workers into jobs that best suit them — the extent to which these entry-level roles are disrupted is a key object of study if we are to understand the consequences of this new iteration of technical change for inequalities in the labour market and career trajectories.

‍

What role do you think tax policy could play in improving outcomes for workers when labour markets don't work smoothly?

‍

The income tax system affects how intensely workers search for new jobs (since search is costly), and what kinds of jobs they look for (a difficult-to-obtain job may not result in a big enough after-tax raise to justify the effort of competing with lots of other applicants to try to get it). These forces have the potential to worsen the distribution of worker-firm matches and slow wage growth. At the same time, the revenue raised allows us to provide insurance to workers who may have fallen off the job ladder into unemployment, or to top up workers stuck at the bottom of the ladder with in-work benefits like tax credits — both of which would lessen inequality. The insurance provided may even encourage workers to take more risks in the labour market, taking jobs in a competitive industry where the risk of firm failure or layoff is high, but where falling off the ladder is cushioned by the social insurance provided by the state. The empirical balance between these forces, combined with how we value efficiency versus equity in the labour market, ultimately decides what the shape of the tax-and-transfer system should be. In a separate but related project, I plan to measure each of these forces in a unified framework with data from Denmark, and derive the implications for how progressive the tax and benefit system should be.

‍

What are you hoping to get out of being part of the Stone Centre community, and what would you like to have achieved by the end of your PhD?

‍

The Stone Centre will no doubt be a great place to explore some of these ideas — it's full of passionate scholars thinking about similar issues, whose feedback on my own work will be vital in helping me execute my various projects. I'm also very lucky to have a visit to the Yale Department of Economics planned for early next year, with Stone's financial support. By the end of the PhD I'm hoping to have turned these works in progress into papers, and developed a better understanding of exactly what the current wave of technological change is going to mean for young workers' careers, skills mismatch, and inequalities over the life cycle.