Fourteenth International Conference on Interdisciplinary Social Sciences

Abstract

Casual effects of incumbency (holding public office) have enjoyed extensive academic attention since the 1970s. Regression discontinuity (RD) designs that allow for quasi-random assignment of incumbency status have gained popularity in the past decade and replaced older estimation strategies that were provably biased. However, selection bias induced by candidate attrition threatens the internal validity of such designs. I study incumbency effects in elections to the Lok Sabha, the lower house of the Indian parliament, using RD designs and find that candidates who barely win (and become incumbents) are 10.4 percentage points more likely to contest the subsequent election compared to candidates who barely lose (and become non-incumbents), an increase of 32.68%. In fact, this incumbency advantage has increased to 14.4 percentage points post-1991. Furthermore, I find systematic differences between non-incumbents who rerun and those who do not: non-incumbents that are more experienced and represent larger parties, with presumably higher chances of winning, are more likely to contest again. As much fewer non-incumbents contest the next election and candidate attrition is non-random, it follows that the casual effect of incumbency on any outcome of interest (that is unobserved for non-contestants) in the next election is biased. Finally, I find an upper bound on the incumbency effect on the probability of victory in the subsequent election and show the absence of any incumbency advantage in elections to the Lok Sabha.