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✨Winter School #IT19 ✨ Sarting the Nineteenth Winter School on #Inequality and #SocialWelfare Theory (#IT19) 3 days, 85 participants, 25 talks, 3 lab sessions, 40 posters/presentations, a lot to learn about! @cesifo.org @liser.lu Uni Verona @cy-univ.bsky.social @lseinequalities.bsky.social

Day 1 #IT19 - @rafaelahlskog.bsky.social on the extent at which genetics explains location choices and persistence of local inequalities across generations.

Day 1 #IT19 - @paulhufe.net on the way of incorporating genetic information into the production function of skills and the causal role of education reforms in attenuating the genes-environment gradient. Identification may require within-family PGIs and exogenous variation in education reforms.

Day 1 #IT19 - @giorgiamenta.bsky.social on epigenetic clocks and the Mulit EpiGenetic Age indicator (which has to do with how the DNA is packed). Clocks are relevant for uncovering effects of environment exposure on DNA early in life, and how these affect major human capital investmets later on.

Day 1 #IT19 - Lidia Ceriani UniVerona on using @forbes.com Billionaires data for addressing wealth concentration at the very top of the (global) distribution. The data are not a redy-made panel and a number of armonizations has to be made. The lab shows how, hands on.

Day 1 - Teresa Munzi @lisdata.bsky.social and Philippe Van Kerm @uni.lu on wealth data hosted and harmonized at LIS. In combination with income, hamonized data highlight distributional aspects across countries, cohorts, families, SES, life-cycle by income and/or wealth. Important for ageing pop.

Day 1 - Emilia Del Bono ISER-Uni Essex on challenges in using socio-emotional skills for addressing human capital formation. Skills are latent, multi-dimensional objects that need to be estimated from multiple items. Measurement strategy is key to mitigate errors. The talk shows how.

Day 2 #IT19 - Jan Stuhler @uc3meconomics.bsky.social on using "names" to link multi-gen data and estimate long-run intergen mobility. Compared to direct/TSTSLS estimators, indirect name-based/grouping estimators under multiplicity emphasize transission of most persistent traits. Sample overlap key.

Day 2 #IT19 - Frank Cowell @lse-sticerd-case.bsky.social on wealth concentration at the top and the role of fertility and integen transmission to explain it. A multi-gen 3-stage model characterizes the wealth equilibrium distribution as Pareto, with inequality inversely related to family size.

Day 2 #IT19 - Lab session by Andrea Del Pizzo @uc3meconomics.bsky.social on using census data for constructing name estimators under multiplicity, using covariates to understand drivers of transmission of advanta across generations. Name serve to group families. Material on the Winter School website

Day 2 #IT19 - Neil Cummins @lseechist.bsky.social @lseinequalities.bsky.social on how combining historic register data, name estimatiors and a dynastic perspective improve our understanding of wealth inequalities. Name estimators give wealth IGE=.8, showing status persistence up to 20 generations!

Day 2 #IT19 - Alain Trannoy @amse-aixmarseille.fr on the value of land: urban production not convex but displays IRS generated by density. Density combined with scarsity of land generate rents related to location, which cumulate in housing values, i.e. 1/3 of wealth (in FR).

Day2 #IT19 - Anthony Lepinteur @uni.lu on the impact of housing wealth on Subjective Well-Being. Easterlin paradox better explained by combination of own (+effect) and comparison (-effect) housing wealth on SWB, owing to the visibility of this form of wealth.

Day 3 #IT19 - Johanna Mollerstrom @georgemasonu.bsky.social on when is tricky to be a meritrocat (eccepts inequalities due to merit, rejects inequalities due to luck - a widely accepted distributional norm). One case is support for redistribution in presence of wealth transfers.

Day 3 #IT19 - Maurizio Bussolo at WB on the urban gender premium in intergenerational mobility in South Asia.

Day 3 #IT19 - Aurelius Noble at Transcribus and Noah Sutter @lseechist.bsky.social on automated transcription of structured handwritten documents. Fascinating to see how deep learning methods can help produce new ready-to-use historic data from non-digitalized archives.

Day 3 #IT19 - Fabrizio Perri at Minneapolis Fed on the implications of inflation for inequality, in income/consumption/wealth. Inflation has redistributive effects on wealth and PP that benefit young middle class (indebted), but negative effects on labour income, mostly for low educ group.

Day 3 #IT19 - Alessandra Fogli at Minneapolis Fed on the within-city nature of inequality in the US. inter-gen mobility is lower in cities where poor/rich parents are more unequal and more segregated. A dynamic model sorts out causal links from endogenous feedbacks of inequality on segregation.