We use a research design created by forced migrations to examine the costs and benefits of leaving agriculture in mid-20th century Finland. After World War II, 11% of the Finnish population was resettled from areas ceded to the Soviet Union. Entire rural communities were moved to locations that resembled the origin areas, and displaced farmers were given land and assistance to establish new farms. Despite this policy of reconstructing the pre-war situation, forced migration increased the likelihood of switching to non-agricultural jobs and moving to urban areas. Consequently, forced migration also increased the long-term income of the displaced rural population. By contrast, forced migration decreased the income of the resettled urban population. We examine the extent to which these effects can be explained by the quality of the new farms, human capital investments, networks, and discrimination, but do not find evidence supporting these mechanisms. Instead, we argue that habit formation toward residential locations provides the most compelling rationalization for our results.

Social rörlighet – eller rörlighet mellan generationer – är av stort intresse iden allmänna debatten och inom forskningen. Sociologer har länge studeratklassrörlighet mellan föräldrar ochbarn. Under de senaste decennierna harnationalekonomer bidragit till sådanforskning och särskilt med analyser avinkomströrlighet mellan generationer. Både sociologer och nationalekonomer har också studerat rörlighet i olikadimensioner av utbildning. Det finns därför en omfattande forskning om social eller intergenerationell rörlighet, som bör spridas till en bred publik. Två färska svenska exempel på rapporter somgår igenom forskning på området och vänder sig till en bredare publik är en bilaga till 2019 års Långtidsutredning, med titeln ”Utvecklingen av intergenerationell rörlighet i Sverige” (Brandénoch Nybom 2019) och en SNS-rapportmed titeln ”Social rörlighet” (Adermonm fl 2021a). Denna kommentar är motiverad av dessa rapporter.

I nummer 5 av årets Ekonomisk Debatt (Björklund m fl 2022) utgick vi fråntvå färska rapporter som för en bredare svensk publik presenterade ny forskning om social eller intergenerationell rörlighet. Vi tog tillfället i akt att diskutera hur vi ser på denna forskning och hur vi tycker forskningen bör utvecklas.Vårt inlägg vände sig både till aktiva forskare på området (inom olika discipliner) och till en bredare publik som intresserar sig för jämlikhetsfrågor.

Grouped data in the form of income shares have conventionally been used to estimate income inequality due to the lack of individual records. We present a systematic evaluation of the performance of parametric distributions and non-parametric techniques to estimate economic inequality using more than 3300 data sets. We also provide guidance on the choice between these two approaches and their estimation, for which we develop the GB2group R package. Our results indicate that even the simplest parametric models provide reliable estimates of inequality measures. The non-parametric approach, however, fails to represent income distributions accurately.

Artikeln granskar fyra ansatser att studera familjebakgrundens betydelse för de ekonomiska utfallen inkomst och utbildningsår. Föräldrars och barns inkomster och utbildning samvarierar positivt, men sambanden förklarar bara en liten del av variationen i ekonomiska utfall och är i liten utsträckning kausala. Den starka kopplingen mellan syskons utfall ger däremot skäl att tro att familjebakgrunden, i vidare mening, förklarar en stor del av variationen i ekonomiska utfall och att många viktiga bakgrundsfaktorer saknar koppling till föräldrars inkomster och utbildning. Ansatsen att studera jämlikhet i möjligheter kan fånga upp sådana faktorer, men har hittills inte uppnått förklaringsgrader som närmar sig syskonkorrelationerna.

This paper presents and discusses four different approaches to the study of how individuals’ income and education during adulthood are related to their family background. The most well-known approach, intergenerational mobility, describes how parents’ and offspring’s income or education are related to each other. The intergenerational-effect literature addresses the question how an intervention that changes parental income or education causally affects their children’s outcome. The sibling-correlation approach estimates the share of total inequality that is attributed to factors shared by siblings. This share is generally substantially higher than what is revealed by intergenerational mobility estimates. Finally, the equality-of-opportunity approach is looking for a set of factors, in the family background and otherwise, that are important for children’s outcomes and that children cannot be held accountable for.

We argue that all four approaches are most informative and that recent research has provided insightful results. However, by comparing results from the different approaches, it is possible to paint a more nuanced picture of the role of family background. Thus, we recommend that scholars working in the four subfields pay more attention to each other’s research.

We examine the complex relationship between money and happiness. We find that both permanent income and wealth are better predictors of life satisfaction than current income and wealth. They matter not only in absolute terms but also in comparative terms. However, their relative impacts differ. The first exerts a comparison effect-the higher the permanent income of the reference group, the lower life satisfaction-the second exerts an information effect-the higher the permanent wealth of the reference group, the higher life satisfaction. We also show that negative transitory shocks to income reduce life satisfaction while transitory shocks to wealth have no effect. Lastly, we analyse the effects of their components and find that not all of them predict life satisfaction: permanent taxes do not matter, while only the value of permanent real estate, financial and business assets do. Finally, we use quantile regression and analyse to what extent our results vary along the well-being distribution, finding the impacts to be larger at lower levels of life satisfaction.

This paper reexamines the determinants of redistribution in light of improved data and methods relative to earlier literature. In particular, we use the latest version of the UNU-WIDER's Income Inequality Database to have the best available estimates of both pre- and post-redistribution inequality for the largest set of countries and periods. We tackle head-on problems related to model specification that risk generating large biases in estimates because of mechanical associations between the dependent and explanatory variables. The results suggest that the bias in the earlier work can be substantial. The descriptive analysis highlights, in addition, how scarce the data are when it comes to information about the extent of redistribution in developing countries.

This paper presents and discusses four different approaches to the study of how individuals’ income and education during adulthood are related to their family background. The most well-known approach, intergenerational mobility, describes how parents’ and offspring’s income or education are related to each other. The intergenerational-effect literature addresses the question how an intervention that changes parental income or education causally affects their children’s outcome. The sibling-correlation approach estimates the share of total inequality that is attributed to factors shared by siblings. This share is generally substantially higher than what is revealed by intergenerational mobility estimates. Finally, the equality-of-opportunity approach is looking for a set of factors, in the family background and otherwise, that are important for children’s outcomes and that children cannot be held accountable for. We argue that all four approaches are most informative and that recent research has provided insightful results. However, by comparing results from the different approaches, it is possible to paint a more nuanced picture of the role of family background. Thus, we recommend that scholars working in the four subfields pay more attention to each other’s research.