How elections could get teachers to show up1 min read . Updated: 05 Nov 2018, 09:15 AM IST
Improved teacher attendance in government schools ahead of elections might stem from elected officials' increased concern for public services before the polls.
Teacher absenteeism in government schools is one of the biggest problems plaguing the Indian education system. According to one 2014 estimate, the amount of public money wasted because of absenteeism was around $1.5 billion a year, or 60% of the entire education cess collected in 2010. New research suggests that there is some method to this absenteeism: teacher’s attendance in classrooms could be linked to the election cycle.
In a new study, Emmerich Davies of Harvard Graduate School of Education shows that teacher absenteeism drops in the year immediately preceding an election year and in the same year as the election. To reach this conclusion, he uses data on government schools from the District Information System for Education (DISE) from 2006-2016 and matches it to data on state election timing. Davies finds that, on average, 5.5 teaching days in every school are lost to absenteeism in any given school year. However, the total number of days lost to absenteeism approaches zero in a government school in a constituency election year. Private schools, on the other hand, show no such relation with election cycles.
Improved teacher attendance in government schools ahead of elections might stem from elected officials’ increased concern for public services before the polls. Teachers often pay heed to the concerns of the elected officials, because these officials can affect hiring, firing and transfer of public-sector employees, including teachers. But the improved teacher attendance ahead of elections could also simply be a result of false attendance data. Elected officials may pressurize school administrators to cook the books to make their records look better. Davies warns that DISE’s data is self-reported and is much more optimistic about absenteeism compared to other independent evaluations.