The forthcoming article “Does Affirmative Action Worsen Bureaucratic Performance? Evidence from the Indian Administrative Service” (https://doi.org/10.1111/ajps.12497) by Rikhil R. Bhavnani and Alexander Lee is summarized by the author(s) below.
Although many countries recruit bureaucrats using affirmative action,
the effect of affirmative action recruits on bureaucratic performance
has rarely been examined. Some worry that affirmative action worsens
bureaucratic performance by diminishing the quality of recruits, while
others posit that it improves performance by making recruits more
representative of and responsive to the population.
This paper examines the effects of affirmative action in India, which
has a powerful upper bureaucracy that recruits using affirmative
action. India’s elite bureaucracy, the Indian Administrative Service
(IAS), is one of the world’s most powerful, monopolizing the most
important bureaucratic posts and supervising the implementation of
anti-poverty programs vital to hundreds of millions. While IAS
officers are selected through a fiercely competitive national exam, at
least 50% of positions are reserved for members of three categories of
traditionally marginalized groups whose low exam scores would
otherwise disqualify them from office.
Our dataset, obtained using online sources and India’s Right to
Information Act, includes detailed data on the origins, educational
backgrounds and complete service histories of every IAS officer, as
well as their caste category and exam scores. The latter two criteria
determine whether and how–with or without affirmative
action–candidates joined the IAS. We therefore know which candidates
were recruited using affirmative action, and by how much they
benefited.
We focus on the implementation of the world’s largest anti-poverty
program, the Mahatma Gandhi National Rural Employment Guarantee Act
(MGNREGA), which aims to reduce poverty by providing rural households
with employment on public works as needed.
To estimate the effects of affirmative action on bureaucratic output,
we examine whether the assignment of affirmative action hires to
districts changes MGNREGA outcomes in those districts. We find that
districts served by affirmative action recruits have similar levels of
MGNREGA employment to other districts. We find similar results when we
estimate the effects of affirmative action hires on road construction,
and time to approval of projects sponsored by legislators using their
constituency development funds.
To explore the mechanisms behind the null estimated effect of
affirmative action, we disaggregate the affirmative action treatment
bundle into two components–disadvantaged group status and exam
performance. We find a slight, statistically insignificant, negative
association between MGNREGA implementation and officer exam rank,
which is more than counterbalanced by a positive and statistically
significant association between disadvantaged group identity and
MGNREGA implementation. In other words, among officers with similar
exam ranks, disadvantaged group officers perform better than others.
The fact that disadvantaged group IAS recruits perform poorly on the
interview portion of the recruitment exam, where it is relatively easy
to guess caste identity, rather than the more objective written
portions of the exam, points to the specific stage at which candidate
quality is understated.
Our results suggest that, at least within selective bureaucracies like
the IAS, improvements in diversity can be obtained without efficiency
losses for some kinds of bureaucratic output. This finding allows us
to reject the worst fears of affirmative action skeptics, namely that
these programs inevitably worsen bureaucratic performance.
About the Author(s): Rikhil Bhavnani is Associate Professor at the University of Wisconsin Madison and Alexander Lee is Assistant Professor at the University of Rochester. Their research “Does Affirmative Action Worsen Bureaucratic Performance? Evidence from the Indian Administrative Service” (https://doi.org/10.1111/ajps.12497) is now available in Early View and will appear in a forthcoming issue of the American Journal of Political Science.
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