This project develops new statistical tools for economists and other social scientists interested in studying individual behavior and outcomes over time.

The research is centered on two general scenarios. The first scenario involves situations in which a researcher is interested in the duration of some event. The tools developed in this part of the project will be useful in many areas of economics: in labor economics, to study the duration of unemployment; in public economics, to study participation in welfare programs; in marketing, to study the long-run effects of advertising; and in health economics, to study the evolution in health status. The innovation in these methods is that they will explicitly incorporate the possibility that one person's actions have an important impact upon the actions of others. For example, a teenager's decision to start smoking may be influenced by the smoking behavior of her friends and vice versa, or one family member's decision about how much to work may be effected by the decisions of the other family members. Such interactions imply that the effect of a policy that changes one person's behavior will be enlarged by the fact that that person's behavior will influence others. It is therefore important to have tools for measuring the importance of these interactions.

The other general scenario addressed in this research involves situations in which two outcomes interact with each other over time. For example, it is well-established that health and socioeconomic status are related. In interpreting such correlations, it is important to determine whether the correlation exists because a change in one of the two causes the other to change in the future (and, if so, which causes which), or because they are both determined by the same factor. The project develops general methods that can be used to answer such questions, and uses them to investigate the relationship between health and socioeconomic status in the US, as well as in a number of European countries.

Broader impacts: The most direct broader impact comes from the fact that software for the new statistical tools will be made available online, and from the training of the students involved in the project. The project will also improve the way economists and other social scientists think about their empirical findings.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Application #
0718063
Program Officer
Nancy A. Lutz
Project Start
Project End
Budget Start
2007-08-15
Budget End
2011-07-31
Support Year
Fiscal Year
2007
Total Cost
$228,089
Indirect Cost
Name
Princeton University
Department
Type
DUNS #
City
Princeton
State
NJ
Country
United States
Zip Code
08540