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Econometrics and Data Science

Econometrics and Data Science

The Econometrics and Data Science Research Group covers a wide number of topics within the areas of modern econometric theory and applications, as well as data science in economics. On the econometrics side, the group’s research interests include: the econometrics of networks, panel data econometrics, identification and semiparametric econometrics, macroeconometrics and financial econometrics. On the data science side, the group is interested in, among other topics, machine learning, artificial intelligence, high-dimensional econometrics and text analysis. Such research is often motivated and applied to problems in other fields, including those in industrial organisation, labour economics, political economy, macroeconomics and finance.

The group organises an Econometric seminar that takes place every two weeks on Mondays at 2pm. The group also participates in the CAGE seminar in applied economics, which runs every two weeks on Tuesdays at 2pm, and engages with other seminars in the Department. Students and faculty of the group present their work in progress in two brown bag seminars which run weekly on Tuesdays and Wednesdays at 1pm. The group also co-organises annual workshops, including the Econometrics Workshop, which is a one-day event coupled with an econometrics masterclass.

Our activities

Econometrics Seminar

Monday afternoons
For faculty and PhD students at Warwick and other top-level academic institutions across the world. For a detailed scheduled of speakers please see our upcoming events.
Organisers: Kenichi Nagasawa and Ao Wang

Work in Progress Seminars

Tuesdays and Wednesdays: 1.00-2.00pm
Students and Faculty of the group present their work in progress in two brown bag seminars. For a detailed scheduled of speakers see our upcoming events.
Organiser: Chris Roth

People

Events

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CWIP (CAGE Work in Progress) - Abhiroop Mukhopadhyay

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Location: S2.79

Title: Transforming Rural Economies through Tertiary Education: Evidence from India

 

Abstract: In this paper, we estimate the impact of a higher share of village population who complete tertiary education on village prosperity in India. To causally identify the effect, we use data from the census of villages in India; we control for a host of geographic, historic and current covariates and use intra state variation. Further, we use historical catholic mission location as an instrumental variable-we show that the mean distance of villages to the nearest Catholic mission location circa 1911, when averaged for a sub-district, predicts the tertiary completion rate of a village and argue, through a myriad of robustness checks, that it doesn't affect village prosperity through any other channel. Further, we find that having tertiary educated people in a rural household raises per acre agricultural revenue from crops, increases crop diversification and makes households more likely to have access to technical advice. Some of the effect also comes from tertiary education impacting occupations-those with university degrees are more likely to be in skilled occupations both in agriculture and in the private job market. Some, though not all, of these jobs are outside the village that are accessed through daily commutes to urban areas. In the stylized version of structural transformation, a rise in education leads to a shift of labour from agriculture to non farm jobs and often involves migration of labour to cities, leading to higher urbanisation. Our analysis shows that a rise in the share of tertiary educated among the rural population can lead to village prosperity through a rise in agricultural productivity as well as non farm jobs within and outside the village.

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