Bhojpur, Bihar

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Galen Murray

Galen Murray

Ph.D. Candidate Political Science Master’s Candidate Statistics

University of California, Los Angeles

About Me

Currently, I’m a Ph.D. Candidate in Political Science, with a regional focus on India. I study how corruption and criminal elements impede (or facilitate) public service delivery and how politicians’ personal characteristics shape governance strategies. In particular, I research how criminal politicians influence the delivery of India’s largest anti-poverty program. Methodologically, I’m interested in combining qualitative fieldwork with causal inference using observational and spatial data. My research is funded by the American Institute of Indian Studies Jr. Fellowship, UCLA’s Dissertation Fellowship and the UCLA International Institute.

Download my current CV here.

Interests

  • Criminal Politicians
  • Causal Inference
  • Indian Politics

Education

  • PhD Political Science, Expected 2020

    University of California, Los Angeles

  • MS Statistics, Expected 2020

    University of California, Los Angeles

  • BA Political Science, 2009

    University of California, Berkeley

  • BA Film, 2009

    University of California, Berkeley

Dissertation

My dissertation pairs 12 months of fieldwork in India, with novel administrative data collection, and rigorous causal analysis to understand the continued success of criminal politicians in India.

Currently, over 40% of Indian Members of Parliament face a criminal charge. Despite intense political competition, candidates facing criminal charges are routinely elected across India at higher rates than clean candidates. My dissertation asks why voters elect “criminal” politicians. And, once elected, how do criminal politicians perform?

To answer these questions, I construct a novel dataset detailing the criminal histories, wealth, and electoral results of all state legislative candidates in India since 2003 (N = 83,000). I measure political performance with original data on the geo-locations of over 20 million local public works projects from India’s largest anti-poverty scheme (the National Rural Employment Guarantee). Overall, I find criminal politicians underperform in office.

For a more detailed summary of my dissertation work, please see here.

Recent Posts

KRLS Shiny App

Criminal MLAs and NREGS Projects This shiny app provides Kernel Regularized Least Squares (KRLS) Marginal effects for delivery of NREGS projects by Members of the Legislative Assembly (MLAs). Results are for a random subsample of 5,000 polling stations in order to fit the data in the shinyapp free tier.
Jun 12, 2020 1 min read
KRLS Shiny App

Working Papers

Data

  • Members of the Legislative Assembly: Candidates, characteristics (criminality, wealth, education, party, demographics), and constituency results for Indian State Legislators from 2003-2016 (N = 83,000)
  • Polling Station Results and geo-locations: Electoral results and longitude and latitude coordinates for polling stations from 10 state legislative elections in 6 Indian states (N = 120,000)
  • National Rural Employment Gaurantee Scheme: Geo-locations and project details of 20 million local infrastructure projects across India, 2007-2017.

I merged these datasets using fuzzy matching and probabilistic record linkage and included 2001 census data for controls. After I file my dissertation, these datasets can be found on my github.

Teaching

Instructor

  • POL SCI 150: Introduction to Comparative Politics

Teaching Fellow

I have served as a Teaching Fellow for 15 courses, in three different departments at UCLA:

  • Political Science: Data Analysis, Political Economy, Foreign Relations, Politics of Migration, among others
  • International Development Studies: Economic Development
  • Communication: Research Methods

For further evidence of my teaching effectiveness please see here.

Contact