Clayton Nall is an Assistant Professor of Political Science. His research explains how policies that manipulate geographic space change American elections, issue politics, and public policy. Clayton's book manuscript, The Road to Division: How the American Highway System Segregates Communities and Polarizes Politics, examines how the largest public works project in U.S. history created Republican suburbs, increased the urban-suburban political divide, broke apart political networks in urban neighborhoods, and polarized issue politics. The dissertation version of this manuscript won the Harvard Department of Government’s Toppan Prize for best dissertation in political science and the American Political Science Association's William Anderson Award for the best dissertation in the general field of federalism or intergovernmental relations, state and local politics. Clayton's other research projects encompass public policy, causal inference, political geography, and American political development.

Academic Appointments

Administrative Appointments

  • Faculty Mentor, Summer Research College, Stanford University (2012 - 2013)
  • Head Teaching Fellow, Department of Government, Harvard University (2009 - 2009)
  • Teaching Fellow, Harvard University (2008 - 2008)
  • Course Assistant, John F. Kennedy School of Government, Harvard University (2008 - 2008)
  • Teaching Fellow, Department of Government, Harvard University (2007 - 2007)
  • Faculty Fellow, Institute for Research in the Social Sciences, Stanford University (2012 - 2013)
  • Urban Dissertation Fellowship, Taubman Center for State and Local Government, Harvard Kennedy School (2010 - 2010)
  • Dissertation Completion Fellowship, Center for American Political Studies (2010 - 2011)
  • Dissertation Research Fellowship, Center for American Political Studies (2009 - 2010)
  • Leonard M. Rieser Undergraduate Research Fellowship, Bulletin of the Atomic Scientists (2000 - 2000)
  • Affiliated Faculty, American Studies Program, Stanford University (2012 - Present)
  • Affiliated Faculty, Emmett Interdisciplinary Program in Environment and Resources, Stanford University (2012 - Present)
  • Affiliated Faculty, Urban Studies Program, Stanford University (2011 - Present)

Honors & Awards

  • William Anderson Award, American Political Science Association (2013)
  • Robert Noxon Toppan Prize for best dissertation upon a subject of political science, Department of Government, Harvard University (2011)
  • William Yandell Elliott Prize, Harvard University Department of Government (2005)
  • Harry S. Truman Scholarship, Harry S. Truman Scholarship Foundation (2000)
  • Phi Beta Kappa, Phi Beta Kappa Society (2000)

Boards, Advisory Committees, Professional Organizations

  • Reviewer, American Political Science Review
  • Reviewer, American Journal of Political Science
  • Reviewer, Journal of Politics
  • Reviewer, American Politics Research
  • Reviewer, Salud Pública de México
  • Participant, Local Elections in America Project, National Science Foundation (2010 - 2010)
  • Research Intern, AT&T Shannon Laboratory, Statistics Research (2008 - 2008)
  • Research Analyst, Service Employees International Union (2003 - 2005)

Professional Education

  • Ph.D., Harvard University, Political Science (2011)
  • B.S., University of Wisconsin-Madison, Political Science (2001)

2019-20 Courses

All Publications

  • The Complications of Controlling Bureaucratic Timing: FDA Review Deadlines and Postmarket Drug Safety American Journal of Political Science Carpenter, D., Chattopadhyay, J., Moffitt, S., Nall, C. 2011; 56 (1): 98-114
  • Public policy for the poor? A randomised assessment of the Mexican universal health insurance programme LANCET King, G., Gakidou, E., Imai, K., Lakin, J., Moore, R. T., Nall, C., Ravishankar, N., Vargas, M., Maria Tellez-Rojo, M., Hernandez Avila, J. E., Hernandez Avila, M., Hernandez Llamas, H. 2009; 373 (9673): 1447-1454


    We assessed aspects of Seguro Popular, a programme aimed to deliver health insurance, regular and preventive medical care, medicines, and health facilities to 50 million uninsured Mexicans.We randomly assigned treatment within 74 matched pairs of health clusters-ie, health facility catchment areas-representing 118 569 households in seven Mexican states, and measured outcomes in a 2005 baseline survey (August, 2005, to September, 2005) and follow-up survey 10 months later (July, 2006, to August, 2006) in 50 pairs (n=32 515). The treatment consisted of encouragement to enrol in a health-insurance programme and upgraded medical facilities. Participant states also received funds to improve health facilities and to provide medications for services in treated clusters. We estimated intention to treat and complier average causal effects non-parametrically.Intention-to-treat estimates indicated a 23% reduction from baseline in catastrophic expenditures (1.9% points; 95% CI 0.14-3.66). The effect in poor households was 3.0% points (0.46-5.54) and in experimental compliers was 6.5% points (1.65-11.28), 30% and 59% reductions, respectively. The intention-to-treat effect on health spending in poor households was 426 pesos (39-812), and the complier average causal effect was 915 pesos (147-1684). Contrary to expectations and previous observational research, we found no effects on medication spending, health outcomes, or utilisation.Programme resources reached the poor. However, the programme did not show some other effects, possibly due to the short duration of treatment (10 months). Although Seguro Popular seems to be successful at this early stage, further experiments and follow-up studies, with longer assessment periods, are needed to ascertain the long-term effects of the programme.

    View details for DOI 10.1016/S0140-6736(09)60239-7

    View details for Web of Science ID 000265501900033

    View details for PubMedID 19359034

  • The Essential Role of Pair Matching in Cluster-Randomized Experiments, with Application to the Mexican Universal Health Insurance Evaluation STATISTICAL SCIENCE Imai, K., King, G., Nall, C. 2009; 24 (1): 29-72

    View details for DOI 10.1214/08-STS274

    View details for Web of Science ID 000271478500002