IDENTIFYING GENE-BY-ENVIRONMENT INTERPLAY IN HEALTH BEHAVIOR

  1. Bierut, L., Biroli, P., Galama, T.J., and Thom, K. (2023). Challenges in studying the interplay of genes and environment.  A study of childhood financial distress moderating genetic predisposition for peak smoking. Journal of Economic Psychology. Link to working paper.
  2. Galama, T.J. and van Kippersluis, H. (2022), Economic theories of health across the life course, Elgar Handbook on Health Inequalities Across The Life Course (Forthcoming)
  3. Marees, A.T., Smit, D.J.A., Abdellaoui, A., Nivard, M.G., van den Brink, W., Denys, D., Galama, T.J., Verweij, K.J.H., Derks, E.M. (2021), Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits, Nature Human Behavior, pp.1-9.
  4. Fonseca, R., Michaud, P., Galama, T.J. and Kapteyn, A. (2021). Accounting for the Rise of Health Spending and Longevity. Journal of the European Economic Association,19(1), pp.536-579.
  5. Becker, J. et al (2021), Resource profile and user guide of the Polygenic Index Repository. Nature Human Behaviour, pp.1-15.
  6. Okbay et al. (2022), Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals, Nature Genetics. 54:437-449 (2022)
  7. Dias-Pereira, R., Biroli, P., Galama, T.J., von Hinke, S., van Kippersluis, H., Rietveld, C.A., and Thom, K. (2022), Gene-by-Environment Interplay in the Social Sciences. Oxford Research Encyclopedia of Economics and Finance. Working Paper.
  8. Dias Pereira, R., H. van Kippersluis, and C.A. Rietveld (2022) "The interplay between maternal smoking and genes in offspring birth weight", Journal of Human Resources, Forthcoming.
  9. Barcellos, S., Carvalho, L. and Turley, P. (2019). Distributional Effects of Education on Health (2021), Journal of Human Resources, Forthcoming. NBER Working Paper No. w25898

WORKING PAPERS

  1. Van Alten, S., Domingue, B.W., Faul J., Galama, T.J., and Marees, A.T.  (2022b), Correcting for volunteer bias in GWAS uncovers novel genetic variants and increases heritability estimates. Working Paper.
  2. Van de Kraats, C., Galama, T.J. and Lindeboom, M. (2022), Why Life Gets Better after Age 50 For Some: Mental Well-Being and the Social Norm of Work. Human Capital and Economic Opportunity Global Working Group, Working Paper 2022-040
  3. Galama, T.J. and van Kippersluis, H. (2022), Human-Capital Formation: The Importance of Endogenous Longevity. Human Capital and Economic Opportunity Global Working Group, Working Paper 2022-009 
  4. Van Alten, S., Domingue, B.W., Galama, T.J. and Marees, A.T. (2022a), Reweighting the UK Biobank to reflect its underlying sampling population substantially reduces pervasive selection bias due to volunteering. Working Paper.
  5. Van Kippersluis, H., Biroli, P.. Galama, T.J., Muslimova, D., Meddens, F., von Hinke, S., Pereira, R., Rietveld, N. (2021), "Using Obviously-Related Instrumental Variables to Increase the Predictive Power of Polygenic Scores", R&R at Nature Communications. Link to Working Paper
  6. Barcellos, S., Carvalho, L. and Turley, P. (2021). The Effect of Education on the Relationship between Genetics, Early-Life Disadvantages, and Later-Life SES (under revision at the Journal of Political Economy). NBER Working Paper No. w28750
  7. Muslimova, D., Meddens, F., Rietveld, N., von Hinke, S., and van Kippersluis, H. (2021), “Complementarities in human capital formation: Evidence from birth order and genes.” Working Paper. 
  8. Birol, P. and Zund, C.L. (2021), Genes, Pubs, and Drinks: Gene-environment interplay and alcohol licensing policy in the United Kingdom. Working Paper.
  9. Biroli, P., Galama, T.J., von Hinke, S., van Kippersluis, H., Rietveld, C.A., and Thom, K. (2021), The Economics and Econometrics of Gene-Environment Interplay. R&R Review of Economic Studies. Working Paper.
  10. Muslimova, D., Pereira, R., Rietveld, R., Meddens, F., van Kippersluis, H., von Hinke, S. (2021), "Rank concordance of polygenic indices: implications for personalised intervention and gene-environment interplay”  Working Paper.  
  11. Van Alten, S. and Galama, T. (2021), Genetic and environmental determinants of socioeconomic status: evidence from within-family models in the Dutch Lifelines cohort. In preparation.
  12. Carvalho, L. (2022), Genetics, Economic Choices, and Income. In preparation.
  13. Aranda, R., Galama, T., and Thom, K. (2022), The Long-Run Health Consequences of Title IX. In preparation
  14. Galama, T., Munteanu, A and Thom, K. (2022), Intergenerational Consequences of Compulsory Schooling. In preparation.
  15. Van Kippersluis, H., Meddens, F.. Roestenberg, T., and Van Ourti, T. (2022), Estimating Inequality of Opportunity: Evidence from Stochastic Frontiers and Genes, Mimeo. 
  16. Baker, S., Biroli, P., van Kippersluis, H., von Hinke, S. (2020), "Beyond Barker: The role of gene-environment interactions.”
  17. Van Alten, S., Galama, T.J. and Thom, K. (2021), The distributional consequences of region-specific exposure to Chinese import competition: evidence from a shift-share analysis (1990-2010). In preparation.
  18. Barth, D., Papageorge, N.W., and Thom, K. (2021), Genetic endowments, income dynamics, and wealth accumulation over the lifecycle. In preparation. 
  19. Jeong, Y., Papageorge, N.W., Skira, M.M. and Thom, K. (2021), Genetic endowments, Alzheimer's disease, and economic outcomes. In preparation.
  20. Warly Solsberg, C., van Alten, S., Geier, E.G., Bonham, L., Derks, E.M., Sirota, M., Galama, T.J., Yokoyama, J.S., Marees, A.T. (2021), Conducting a genome wide association study: a roadmap and tutorial. In preparation.
  21. Angrisani, Faul, J., Galama, T. and Kabeto, M. (2021), Money Management Problems as a Precursor of Cognitive Impairment and Dementia. In preparation
  22. Biroli, P., Galama, T.J., Marees, A., et al. (2021), Sources of Inequality at Birth:  the Interplay Between Genes and Parental Socioeconomic Status. In preparation
  23. Van Kippersluis, H., Sopa, G., and Windmeijer, F. (2022), "The polygenic score as a generated regressor: implications for inference.” Mimeo