Five Questions for Martina Pons
Martina Pons has recently joined our department as an Assistant Professor in Econometrics in the Digital Age.
What are the topics you are currently working on?
My research interests lie in econometrics, with a particular focus on distributional methods and panel data econometrics. I develop new tools to understand how policies affect the entire outcome distribution rather than just the average. Recently, I have been working on a method that makes it possible to analyze inequalities along multiple dimensions simultaneously.
What is the main contribution of this work?
Traditional econometric tools usually capture either differences within groups (for instance, income gaps between rich and poor individuals within a region) or between groups (differences in average or median income across regions or social backgrounds). However, this approach misses important variation within these regions.
These two dimensions are interconnected, and policies can have differential effects on inequalities within and between regions. Modeling only one dimension at a time therefore fails to capture these patterns. To address this, I propose a method that models both dimensions jointly, providing a more detailed and comprehensive picture.
Using this framework, I summarize complex patterns of inequality and heterogeneity in a single, interpretable objectand show how to evaluate policies when reducing one dimension of inequality may inadvertently increase another. The method can be applied to a variety of settings and offers a clearer and more flexible way to describe and assess multidimensional heterogeneity.
Is there another important specific work of yours that you would like to mention?
I have been doing also some applied research. For instance, in another paper, we study the intergenerational transmission of dietary habits using large-scale grocery transaction data. We find strong persistence in dietary choices between parents and their grown-up children which exceeds income persistence. Specifically, we find that socioeconomic status and geography account for only a small share of the transmission. Combined with the absence of a dietary response following a parent’s unexpected lifestyle-related death, these findings underscore the importance of early-life influences and habit formation.
You have recently joined UZH, what motivated you to come to Zurich?
The Department of Economics at UZH has been growing rapidly and offers an inspiring environment with outstanding researchers. It’s a great place to develop and exchange ideas. On a personal note, I grew up in Switzerland, which makes Zurich a special place for me to be.
What is the inspiration behind your work?
I was fascinated by distributional methods from the moment I first encountered them as an undergraduate student. What draws me to quantile methods* is that they uncover patterns standard approaches often miss, offering a richer view of how policies affect different parts of the population. Over time, this curiosity has deepened into an appreciation for researchers who think carefully about what we truly want to measure and how our empirical tools relate to that goal.
*Quantile methods are statistical techniques that allow effects or correlations to be examined at different points of a distribution, rather than focusing solely on the mean value.
Martina Pons' website