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Labor Supply Behavior of Registered Nurses: Factors Affecting Participation and Full-time/Part-time Work Decisions
The demand for registered nurses (RNs) will increase over time for such reasons as changes in technology, the obesity epidemic, aging of the general population, and increased insurance coverage for millions of Americans resulting from the Patient Protection and Affordable Care Act (PPACA). Given that there are around 3 million RNs, and their critical role in the provision of health care, it is important understand the factors affecting RN labor supply, including whether or not the RN chooses to work, whether they work part-time or full-time, and the factors associated with the determinants of hours worked.
The objective of the paper is to estimate the effects of economic and noneconomic factors on different measures of labor supply: labor force participation of RNs and, if they work, whether they work full-time or part-time. In addition to the usual variables such as RN wages and family income, we are interested in estimating the effects of key geographic area variables including general labor market conditions and health market characteristics. We also estimate the labor supply effects associated with the nurse’s job characteristics (e.g. where they work, position held, job satisfaction, etc.).
This will allow us to account for both area economic characteristics as well as numerous health market characteristics (e.g. health personnel, insurance coverage, poverty levels, etc.). Our data sources include the county version of the 2008 National Sample Survey of Registered Nurses (NSSRN 2008), the 2013 and 2014 Current Population Surveys (CPS), various years of the Area Resource File, and various years of the American Hospital Association annual survey.
Our project is ongoing and involves estimating bivariate probit models of participation and whether the RN is a full-time worker. This estimating procedure allows us to test the hypothesis that working is or is not independent of working full-time or part-time. Our results are important to policy makers since many RNs are part-time, making them a potential source for providing additional patient care. The findings will give insights into the factors that impact the full-time/part-time decision. Such factors might include wages, income, young children in the home, and characteristics of the position held by the nurse, characteristics of the general economy, and characteristics of the health market.
Model estimation using the 2008 NSSRN data is complete. Model estimation using the CPS data is in process. Although the NSSRN and CPS are not completely comparable, we should be able to estimate models that are very similar; and should thus provide us with a gauge how of how the sensitive the above results are to different data sets. Moreover, we hope to get an idea as to how the coefficients on the key variables have changed over time.
JEL: I1, J22, J48