LINDY: Life-cycle INequality DYnamics

Summary

Concerns about inequality and questions of social justice and cohesion have re-entered the public arena and animate debate, provoked by the recent rapid increases in cross-sectional inequality. While much has been learnt from the literature on inequality, Deaton (2015) has outlined in his Nobel lecture several imperatives that are key to understanding inequalities and formulating welfare-enhancing policies, namely that: (i) differences in resources across individuals should be measured not only at specific points in time but also across the life course; (ii) direct economic measures of well-being should be developed to assess better socio-economic outcomes; and (iii) data should be reconciled with lifecycle models to explain the causal mechanisms behind outcomes.

Our proposal is built on these imperatives, and brings together several coherently linked work packages (WPs) that focus, from a life-course perspective, on the causes of inequalities in and fluctuations of economic resources, most prominently income and wealth, and their implications for welfare and policy. Empirically, coherence is achieved by working with a common unique data source (SOEP-RV), housed at team member DIW, that combines information collected in the German Socio-Economic Panel (SOEP) with record-linked administrative microdata from the statutory German pension system. It is unique in its recording of labour market events over entire life-courses including the retirement phase as provided in the administrative microdata, while adding the rich individual and household level data of the SOEP. Our team will be among the first to use SOEP-RV. Since today’s labour market performance affects pension entitlements (“augmented wealth”), our data permits extending the traditional life-cycle perspective beyond the retirement data (“extended life-cycle”).

Our central research questions are:

1. How can the life-course dynamics of incomes be characterised?
2. How can we systematically evaluate the effects of negative events (e.g. health shocks), or positive ones (job changes) on trajectories of economic resources?
3. How can we construct coherent and comprehensive measures of lifetime resources, which also accounts for uncertainty? How unequal and mobile are lifetime resources?
4. Taking a comprehensive life course view, how can policy intervene effectively to combat inequality? What is the equity-efficiency trade-off?

LINDY is organised as a set of four integrated WPs that address these questions, moving from descriptive and statistical work in WP1 to explanations using dynamic models in WP2 that seek to distinguish between events (e.g. health shock) and individual decisions given constraints. Having characterised the life-course dynamics, WP3 develops integrated measures of economic capacity that allow to measure inequality in a comprehensive way, going beyond current-period incomes. WP4 synthesizes the results and puts forward policy measures to efficiently combat inequality.

The work packages (WPs)

1. WP1: Life-cycle inequality – descriptive statistics and reduced-form models
   1. Risk factors over the life-cycle
   2. The shape of earnings changes
   3. Reduced form models of earnings process
2. WP2: Structural empirical life-cycle models of income dynamics: The role of health
   1. Health shocks, Employment and Retirement (HER) over the life cycle: model building
   2. HER-model estimation
   3. HER-model estimation semi-structurally
3. WP3: Measuring inequality and mobility of economic resources
   1. Measuring the inequality of lifetime economic resources and well-being
   2. Mobility of economic well-being