Ph.D. Candidate @ UCLA-Anderson School of Management
I am a development economist with interests in public economics and political economy related issues in India. I aim to use large-scale government data sets (that have only recently begun to be collected) to better understand government capacity and to combine such data sets with field interventions to address questions of first-order causal interest.
Fields: Development, Public Economics
“I not only use all the brains that I have, but all I can borrow.” - Woodrow Wilson
(My most generous lender!)
- Address382 Ventura Avenue, Palo Alto, CA - 94306
- Phone+1 734 780 1120
(with Aprajit Mahajan)
A key stated advantage of the value-added tax (VAT) is that it allows the tax authority to verify transactions by comparing seller and buyer transaction reports. However, there is little evidence on how these paper trails actually affect VAT collections particularly in low compliance environments. We use a unique data set (the universe of VAT returns for the Indian state of Delhi over five years) and the timing of a policy that improved the tax authority's information about buyer-seller interactions to shed light on this issue. Using a difference-in-difference strategy we find that the policy had a large and significant effect on wholesalers relative to retailers. We also document significant heterogeneity with almost the entire increase being driven by changes in the behavior of the largest firms. We also find suggestive evidence that information and enforcement are complementary. Finally, we discuss the details of the policy implementation and argue that this policy which seems simple in principle, faces substantial hurdles in execution, particularly in a system with limited resources.
Who's Bogus? Learning to Identify Fraudulent Firms from Unbalanced and One-side Labelled Tax Returns Data
(with Aprajit Mahajan, Ofir Reich)In Proceedings of the 1st Annual ACM SIGCAS Conference on Computing and Sustainable Societies, COMPASS 2018
We apply a Random Forest classifier on Value Added Tax (VAT) returns from Delhi, India to increase tax compliance by identifying shell firms which can be further targeted for physical inspections. We face a nonstandard applied ML scenario. First, one-sided labels: firms that are not caught as shell are of unknown class: fake or legitimate, and we need to train as well as make predictions on them. Second, multiple time-periods: each firm files several periodic VAT returns but its class is timeless so prediction needs to made at the firm, not firm-period, level. Third, point in time simulation: we estimate the revenue saving potential by simulating the implementation of our system in the past. We do this by rolling back the data to the state of knowledge at a specific time and calculating the revenue impact of catching the fake firms.
Red Tape? The Revenue Impact of the VAT Filing Thresholds
(with Jan Luksic)
Value-added tax systems across the world are afflicted with size-dependent regulations. The benefit of such regulations to the tax authority is unclear. In this paper, we use an administrative dataset from the state of Delhi in India to first show that a policy which mandated different frequencies of filing based on reported turnover resulted in bunching of firms below the thresholds at all levels. Using the change in these reporting policies, we provide further evidence that such sharp bunching indeed occurs due to the VAT reporting frequency thresholds. Second, we calculate the VAT revenue losses due to such bunching and document the longer-term impact of the VAT reporting frequency thresholds. Finally, the subsequent withdrawal of the policy allows us to show that in a regime with size-dependent reporting requirements, more frequent reporting does not lead to greater levels of VAT collection.
Ph.D. in EconomicsUCLA Anderson School of Management
Awards: Dissertation Year Fellowship (2017-18), UCLA Graduate Division
Master of Public PolicyUniversity of Chicago
Awards: Dean’s Scholarship (2011-2013), J.N. Tata Scholar (2011), K.C. Mahindra Scholar (2011)
Bachelor of EngineeringUniversity of Delhi
Specialization: Computer Engineering
Ideas for India, October 18 2017
Value Added Tax 2.0.
- JPAL-GI"Improving the Efficacy of Public Procurement and Public Grievance Monitoring" ($7500)
- EDI"Who is Bogus? Catching fraudulent firms in Delhi" (£22,000)
- IGC "Where’s Value? Using VAT data to Improve Compliance" (£50,830)
- JPAL-GI"Information Provision and Participatory Budgeting:Mohalla Sabhas in Delhi" ($49,050)
- JPAL-GI"Improving Public Service via the Ballot Box: Evidence from Delhi" ($5,000)
- Managerial Economics (MBA)Prof. Romain Wacziarg (2016-17); Prof. Paola Giuliano (2014-15, 2015-16)
- International Studies: India (MBA)Prof. Romain Wacziarg (2015-16, 2017-18)
- Impact Creation and Evaluation (MBA)Prof. Bhagwan Chowdhry (2016-17)
Prof. Romain Wacziarg
UCLA AndersonCo-Chair wacziarg[at]ucla[dot]edu
Prof. Aprajit Mahajan
Dept. of ARE, UC BerkeleyCo-Chair aprajit[at]gmail[dot]com
Prof. Ricardo Perez-Truglia
Get in Touch
Get in Touch
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