Abstract
We analyze the effect that state licensing of radiologic technologists (RTs) has had upon RT wages with a unique dataset that allows us to control for place of work and job specialization. Using OLS and several measures of licensing, we find evidence that RTs working in states with licensing statutes earn as much as 3.3% more than RTs working in states without licensing. When we control for endogeneity using instrumental variables (IV) estimation, our estimate of the licensing premium doubles (6.9%). Our results provide further support for existing theories of the effects of occupational licensing on the wages of practitioners.
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Notes
State regulation of the profession increased significantly soon after the passage of the Consumer–Patient Radiation Health and Safety Act. This federal legislation, introduced by former West Virginia Senator Jennings Randolph, was meant to establish uniform standards for state regulation of RTs. Although the legislation was accepted into law in 1981, no state was required to comply with the new federal standards. Since the early 1990’s RTs have lobbied for the passage of new legislation making state compliance with the Consumer–Patient Radiation Health and Safety Act mandatory.
In our sample, there are only a small number (sometimes none) of RTs in states with partial licensing that are practicing in the particular field that requires licensing. We attempted to control for this possibility, but we found that it did not have a substantial effect upon our results.
We also calculated OLS regressions excluding this variable. Our results were very similar.
Each of our proposed measures is meant to measure the same thing—the extent or strictness of licensing. We therefore include each variable separately to avoid potential multicollinearity problems.
States without statutes are coded as zero.
We chose to use proxies since a number of more direct measures were infeasible to use. One commonly used measure of the strictness of regulation is the pass rate on the licensing exam. For many occupations, each individual state will construct its own independent exam for licensure. This is not true for RTs. The overwhelming majority of states that regulate RTs contract out the examination preparation and grading to the ARRT. Education requirements among states are also very similar. Furthermore there is little variation in reciprocity arrangements across states. If a state has reciprocity, it will recognize the license of another state (under certain conditions). All states have reciprocity, with the exception of Delaware.
Of course stiffer continuing education requirements also constitute an additional cost for already licensed RTs. Therefore, it might be argued that the expected sign for this coefficient is indeterminate.
The ASRT also conducted surveys in 1997 and 2004. The 1997 data has several coding problems we were unable to resolve. The ASRT also admitted experiencing distribution problems with the 2004 survey. As a result, we focus solely on the 2001 survey data.
The determinants of wages for salaried employees are likely to differ from the determinants of wages for RTs paid an hourly wage. To avoid any resulting complications, we decided to focus on wage earners in this study.
In the occupational licensing literature, there is evidence of a relationship between migration rates and licensing (Pashigian 1980; Tenn 2001). Since the majority of RTs are married females and most likely not the primary wage earners in the family, we do not think that mobility between licensed and non-licensed states will influence our results.
Since most RTs are female, the negative sign on the marriage dummy coefficient is consistent with the findings of other studies.
Because the coefficients of variables in semilogarithmic regressions are only approximately equal to percentage changes, in our text discussion we have converted regression coefficients to percentage changes using the conversion formula eβ − 1. See Halvorsen and Palmquist (1980) and Thornton and Innes (1989).
We examined simple correlations between board size, RT wages, and our licensing variables. We found that the correlation coefficient between board size and wages is approximately 0.10 while the correlation coefficient between board size and the licensing variables ranges from 0.54–0.70.
Full results from the first stage estimations are available from the authors upon request.
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Acknowledgements
The authors thank seminar participants at Lehigh University, the Eastern Economic Association’s 2006 Conference, and an anonymous referee for their helpful comments.
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Timmons, E.J., Thornton, R.J. The Effects of Licensing on the Wages of Radiologic Technologists. J Labor Res 29, 333–346 (2008). https://doi.org/10.1007/s12122-007-9035-9
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DOI: https://doi.org/10.1007/s12122-007-9035-9