Summary
I3W aims at generating empirical knowledge and novel theories to explain the joint distribution of work, wealth, and welfare in the population using macroeconomic theory, structural quantitative models, and micro data. Specifically, I3W’s overall goal will be achieved through the following research objectives and their corresponding work packages (WP):
I. Develop a macroeconomic framework of the drivers of welfare inequality. In WP1 I will develop a model based on expected utility—a function of lifetime consumption, lifetime leisure, and life expectancy and their joint distributions—for measuring inequality in economic well-being within a country using rich longitudinal datasets. This framework will allow me to measure and decompose the welfare inequality in a selection of European countries and compare to the US over time, allowing a deeper understanding of the observed heterogeneity in the population along various dimensions: life expectancy, hours worked, wealth, income, consumption, and ultimately also welfare.
II. Analyze underlying factors affecting the drivers: the case of inequality of leisure in relation to access to insurance. In WP2 I will test the hypothesis that better insurance, interpreted in its most general form, leads to a more positive correlation between wages and hours worked. I will base my arguments on observations from micro data, show it theoretically using a theory of labor supply that is consistent with cross-country evidence, evidence over time, and evidence from micro data, and quantify the importance in practice with a carefully calibrated heterogenous-agent model.
The outputs of WP1 and WP2 will be two working papers that will push the current boundaries of the welfare inequality research field while providing policymakers a tool box for the analysis and comparison across European countries of welfare inequality and its drivers.
I. Develop a macroeconomic framework of the drivers of welfare inequality. In WP1 I will develop a model based on expected utility—a function of lifetime consumption, lifetime leisure, and life expectancy and their joint distributions—for measuring inequality in economic well-being within a country using rich longitudinal datasets. This framework will allow me to measure and decompose the welfare inequality in a selection of European countries and compare to the US over time, allowing a deeper understanding of the observed heterogeneity in the population along various dimensions: life expectancy, hours worked, wealth, income, consumption, and ultimately also welfare.
II. Analyze underlying factors affecting the drivers: the case of inequality of leisure in relation to access to insurance. In WP2 I will test the hypothesis that better insurance, interpreted in its most general form, leads to a more positive correlation between wages and hours worked. I will base my arguments on observations from micro data, show it theoretically using a theory of labor supply that is consistent with cross-country evidence, evidence over time, and evidence from micro data, and quantify the importance in practice with a carefully calibrated heterogenous-agent model.
The outputs of WP1 and WP2 will be two working papers that will push the current boundaries of the welfare inequality research field while providing policymakers a tool box for the analysis and comparison across European countries of welfare inequality and its drivers.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101149117 |
| Start date: | 01-04-2024 |
| End date: | 31-03-2026 |
| Total budget - Public funding: | - 210 911,00 Euro |
Cordis data
Original description
I3W aims at generating empirical knowledge and novel theories to explain the joint distribution of work, wealth, and welfare in the population using macroeconomic theory, structural quantitative models, and micro data. Specifically, I3W’s overall goal will be achieved through the following research objectives and their corresponding work packages (WP):I. Develop a macroeconomic framework of the drivers of welfare inequality. In WP1 I will develop a model based on expected utility—a function of lifetime consumption, lifetime leisure, and life expectancy and their joint distributions—for measuring inequality in economic well-being within a country using rich longitudinal datasets. This framework will allow me to measure and decompose the welfare inequality in a selection of European countries and compare to the US over time, allowing a deeper understanding of the observed heterogeneity in the population along various dimensions: life expectancy, hours worked, wealth, income, consumption, and ultimately also welfare.
II. Analyze underlying factors affecting the drivers: the case of inequality of leisure in relation to access to insurance. In WP2 I will test the hypothesis that better insurance, interpreted in its most general form, leads to a more positive correlation between wages and hours worked. I will base my arguments on observations from micro data, show it theoretically using a theory of labor supply that is consistent with cross-country evidence, evidence over time, and evidence from micro data, and quantify the importance in practice with a carefully calibrated heterogenous-agent model.
The outputs of WP1 and WP2 will be two working papers that will push the current boundaries of the welfare inequality research field while providing policymakers a tool box for the analysis and comparison across European countries of welfare inequality and its drivers.
Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
12-03-2024
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