What is he best known for?
The fields of study he is best known for:
His primary scientific interests are in Econometrics, Demographic economics, Labour economics, Wage and Panel data.
His work carried out in the field of Econometrics brings together such families of science as Consumer choice and Risk aversion.
His Demographic economics research includes themes of Causation, Full-time, Health economics and Spouse.
His Labour economics research is multidisciplinary, incorporating perspectives in Regression discontinuity design and Health and Retirement Study.
Arthur van Soest interconnects Earnings, Regression analysis and Labour supply in the investigation of issues within Wage.
The concepts of his Panel data study are interwoven with issues in Mental health, Informal sector and Social class.
His most cited work include:
- Structural models of family labor supply: a discrete choice approach. (569 citations)
- Estimating Risk Attitudes using Lotteries: A Large Sample Approach (328 citations)
- Vignettes and Self-Reports of Work Disability in the United States and the Netherlands (286 citations)
What are the main themes of his work throughout his whole career to date?
Econometrics, Demographic economics, Panel data, Labour economics and Labour supply are his primary areas of study.
His Econometrics study integrates concerns from other disciplines, such as Statistics, Parametric statistics, Risk aversion and Sample.
Arthur van Soest focuses mostly in the field of Demographic economics, narrowing it down to matters related to Retirement age and, in some cases, Regression discontinuity design.
His Panel data research integrates issues from Demography, Health and Retirement Study and Survey data collection.
His research in Labour economics intersects with topics in Unemployment and Discrete choice.
He has included themes like Fixed cost, Earnings and Wage in his Labour supply study.
He most often published in these fields:
- Econometrics (26.13%)
- Demographic economics (24.87%)
- Panel data (23.62%)
What were the highlights of his more recent work (between 2014-2021)?
- Demographic economics (24.87%)
- Pension (7.54%)
- Panel data (23.62%)
In recent papers he was focusing on the following fields of study:
Arthur van Soest mainly focuses on Demographic economics, Pension, Panel data, Labour economics and Retirement age.
Arthur van Soest focuses mostly in the field of Demographic economics, narrowing it down to topics relating to Spouse and, in certain cases, Health and Retirement Study, Interdependence and Life events.
Arthur van Soest interconnects Actuarial science, Standard of living, Financial literacy, Incentive and Self in the investigation of issues within Pension.
His Panel data research is multidisciplinary, incorporating perspectives in Endogeneity, Production and Economic model.
His work in Labour economics addresses issues such as Population ageing, which are connected to fields such as Government.
Arthur van Soest undertakes interdisciplinary study in the fields of Stability and Econometrics through his research.
Between 2014 and 2021, his most popular works were:
- What they say and what they do: comparing physical activity across the USA, England and the Netherlands (35 citations)
- The effect of retirement on healthcare utilization: Evidence from China. (18 citations)
- Informal caregiving, employment status and work hours of the 50+ population in Europe (10 citations)
In his most recent research, the most cited papers focused on:
Demographic economics, Panel data, Pension, Labour economics and Retirement age are his primary areas of study.
In general Demographic economics, his work in Hilda survey is often linked to Child care linking many areas of study.
His Panel data research is multidisciplinary, relying on both Test, Grandparent and Affect.
His biological study spans a wide range of topics, including State and Financial literacy.
His study looks at the relationship between Labour economics and fields such as Social policy, as well as how they intersect with chemical problems.
The concepts of his Retirement age study are interwoven with issues in Percentage point, Regression discontinuity design, Survey data collection and Externality.
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