My primary research focuses on subjective well-being (e.g. happiness or life satisfaction). I have written extensively about the relationship between migration and happiness.  In general, gaining more money doesn’t make people happier, and so I’m led to wonder whether migration to a wealthier country increases happiness for migrants; I suspect that it makes many of them less happy, that economic migration is sometimes counterproductive insofar as people make great sacrifices to gain more income in the (possibly misguided) belief that the increase will make them happier. 

My current research aims to improve the quantitative modelling used to explore causal effects of various factors on subjective well-being.  There is a great deal of confusion about how to select control variables for this purpose.  I emphasize the need to distinguish between “confounders” (variables that are causally prior not only to the outcome but to the focal independent variable) and “intervening variables” (i.e., they intervene in a path from the causal variable to the outcome).   To estimate a causal impact, we would control for confounders but exclude intervening variables.

For example, using this distinction, we would not need any control variables to estimate the impact of age on life-satisfaction — because no individual-level variables are causally prior to age. Another article on this topic, published recently in Journal of Happiness Studies, demonstrates the need to “look beyond statistical significance” in evaluating whether the relationship is “u-shaped”. (Mostly it isn’t u-shaped.)

I am also extending that perspective to reconsider the role of individual-level control variables in multi-level models intended to evaluate the effect of “level 2” (e.g. country-level) variables on outcomes of various sorts.  This work was supported by a grant from the British Academy’s “Talent Development” program.

One key finding from this research: rising inequality reduces life satisfaction. When we see that we don’t need individual-level control variables, we can use a longitudinal approach for investigating that topic.  Previous research has mainly been cross-sectional and sometimes suggests that inequality is beneficial for life satisfaction — but a longitudinal analysis mitigates bias more effectively and tells us what happens as inequality changes.

Recent publications also draw on a grant from the Economic and Social Research Council for a project titled “The UK Citizenship Process: Understanding Immigrants’ Experiences“, conducted with Leah Bassel (PI), Barbara Misztal and Pierre Monforte.

I am Editor-in-chief of Social Indicators Research.  I was co-editor of the Journal of Happiness Studies for ~8 years, responsible for sociology submissions.  Until July 2023 I was also President of RC31, the International Sociological Association’s research committee on international migration.  In August 2023 I was given a “Research Fellow Award” by the International Society for Quality of Life Studies. I gained my PhD from the University of Wisconsin – Madison, and a BA from Kenyon College.