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Presidential priorities, congressional control, and the quality of regulatory analysis: an application to healthcare and homeland security

Abstract

Elected leaders delegate rulemaking to federal agencies, then seek to influence rulemaking through top-down directives and statutory deadlines. This paper documents an unintended consequence of these control strategies: they reduce regulatory agencies’ ability and incentive to conduct high-quality economic analysis to inform their decisions. Using scoring data that measure the quality of regulatory impact analysis, we find that hastily adopted “interim final” regulations reflecting signature policy priorities of the two most recent presidential administrations were accompanied by significantly lower quality economic analysis. Interim final homeland security regulations adopted during the G.W. Bush administration and interim final regulations implementing the Affordable Care Act in the Obama administration were accompanied by less thorough analysis than other “economically significant” regulations (regulations with benefits, costs, or other economic impacts exceeding $100 million annually). The lower quality analysis apparently stems from the confluence of presidential priorities and very tight statutory deadlines associated with interim final regulations, rather than either factor alone.

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Notes

  1. Some of the homeland security regulations were called “interim rules” or “temporary interim rules” rather than “interim final” rules, but the effect is the same. For simplicity, we use the term “interim final” to describe all of them.

  2. The Mercatus Center discontinued evaluating budget regulations in 2010, so the sample consists of all economically significant proposed regulations in 2008 and 2009, and all economically significant prescriptive regulations proposed in 2010. Scores for these regulations are available at www.mercatus.org/reportcards. Scores for the interim final homeland security regulations are from Belcore and Ellig (2009). Scores for the interim final ACA regulations are from http://mercatus.org/reportcards/projects/patient-protection-and-affordable-care-act.

  3. Health care and HHS regulations are not synonymous. Some agencies other than HHS issue health care regulations—most notably Defense and Veterans’ Affairs in administering their health care programs for military personnel and veterans. HHS also issues safety regulations unrelated to health care or health insurance, such as drug regulations issued by the FDA. Similarly, DHS issues some non-security regulations, such as budget-related regulations that implement federal disaster aid programs and environmental regulations issued by the Coast Guard.

  4. The deadline variables measure only whether a legislative deadline exists, not the tightness of the deadline. We know of no data source that lists the length of legislative deadlines for all regulations.

  5. For a complete description of all data sources, an appendix is available online at http://mercatus.org/publication/presidential-priorities-congressional-control-and-quality-regulatory-analysis or from the corresponding author at jellig@mercatus.gmu.edu.

  6. Clinton and Lewis (2008) measured agency policy preferences by asking a panel of experts to identify agencies as more liberal or conservative based on the agency’s mission, history, and culture. Chen and Johnson (2014) construct an alternative measure based on agency employees’ donations to political candidates. When we substitute the Chen–Johnson ideology measure interacted with administrations in specification 5, Interim Final remains significant at the 1 % level. However, neither the Obama administration interaction variable nor the Bush administration interaction variable with the Chen–Johnson ideology measure is anywhere near statistically significant. Thus, the Clinton–Lewis measure, which appears designed to identify agency policy preferences that are more deeply rooted in institutional factors like the agency’s mission and culture, is more correlated with the quality of regulatory analysis than the Chen-Johnson measure, which focuses on the ideology of the individuals currently working in the agency.

  7. Some of these explanatory variables are collinear. To ensure that the insignificant results for these variables are not an artifact of collinearity, we also ran each regression omitting sets of potentially collinear variables. In only one case did an alternative specification change the results; Presidential Priority became positive (the opposite of the expected sign) and significant at the 5 % level when DHS and HHS were omitted.

  8. Regression results are in an appendix available online at the source listed in footnote 5.

  9. We use specification 5 from Table 3, but results are similar for other specifications.

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Acknowledgments

The authors would like to thank Mark Adams and Corey Carpenter for research assistance, and an anonymous referee, Robin Bowen, Jason Fichtner, William Shughart, Georg Vanberg, Richard Williams, and participants at the Public Choice Society and Association for Private Enterprise Education meetings for helpful comments.

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Correspondence to Jerry Ellig.

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Ellig, J., Conover, C.J. Presidential priorities, congressional control, and the quality of regulatory analysis: an application to healthcare and homeland security. Public Choice 161, 305–320 (2014). https://doi.org/10.1007/s11127-014-0201-3

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Keywords

  • Regulation
  • Regulatory impact analysis
  • Cost-benefit
  • Homeland security
  • Healthcare
  • Principal-agent

JEL Classification

  • D61
  • D72
  • D73
  • D78
  • H83
  • K23
  • L51