Ridhi Kashyap - Nuffield College, Univ. of Oxford
Ultrasound technology and ‘missing women’ in India: Analyses and now-casts based on Google searches
Date: 09/14/2017 (Thu)
Time: 3:30pm- 5:00pm
Location: Gross Hall 270
Organizer: Chris Bail
Meeting Schedule: Login or email the organizer to schedule a meeting.
All meetings will be in 230K Gross Hall unless otherwise noted.
8:00am - Jessie West
8:30am - Breakfast- Jessie West
9:00am - Breakfast- Jessie West
9:30am - Maria Cristina Ramos
10:00am - OPEN
10:30am - Seth Sanders
11:00am - Giovanna Merli
11:30am - Emma Zang
12:00pm - LUNCH - Emma Zang, Claire LeBarbenchon
12:30pm - LUNCH - Emma Zang
1:00pm - LUNCH - Emma Zang
2:00pm - Bryce Bartlett, Catherine Moon
2:30pm - Jaemin Lee
3:00pm - Seminar Prep
3:30pm - Seminar Presentation (3:30pm to 5:00pm)
Additional Comments: In contexts of entrenched cultural preference for male offspring, such as in parts of northwest and central India, growing access to prenatal sex determination through ultrasound has enabled the practice of sex-selective abortion. This practice has led to `missing women', with the sex ratio at birth (SRB) becoming distorted with unnaturally more boys born relative to girls. SRB distortions and their variations across different states in India have been widely documented, but data on state-level trends are often erratic and not up-to-date. Moreover, the timeline of diffusion of ultrasound technology is less documented, and so is the role of online information in shaping the decision to practice sex-selective abortion. We use information on Google searches related to ultrasound and sonography, both at the national level and at the level of Indian states, to assess whether these data track the regional and temporal dynamics of SRBs, complementing existing estimates and developing now-casts. For the 2011-2014 period, we find that states with distorted SRBs tend to display a relatively high search activity for ultrasound. Drawing on between-state variation in ultrasound search intensity for the period between 2011 and 2013, we 'now-cast' the 2014 SRB using Google search data. For wealthier states, we find that Google search performs better than lagged variable models in predicting the SRB, highlighting its potential role for indirect demographic estimation. By analysing a population's search footprints, these Google search data exemplify how big data can be used to study behaviours that are not readily measured, and to supplement existing but often slower or incomplete data sources (e.g., Census or civil registration) in the developing world with more `real-time' information.