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Development and History

Development and Economic History

Members of the Development and Economic History Research Group combine archival data, lab-in-the-field experiments, randomized controlled trials, text analysis, survey and secondary data along with theoretical tools to study issues in development and economic history. Faculty and students work in the field in South Asia, China and Africa as well as doing archival work in libraries across Europe and Asia.

Almost all faculty are members of CAGE in the economics department and some are also members of Warwick Interdisciplinary Centre for International Development (WICID). There is a regular weekly external seminar, two weekly internal workshops, and high quality research students. We also organise international conferences on campus, or in Venice.

Our activities

Development and Economic History Research Group Workshop/Seminar

Monday: 1.00-2.00pm
For faculty and PhD students at Warwick and other top-level academic institutions across the world. For a detailed scheduled of speakers please follow the link below.
Organisers: Bishnupriya Gupta and Claudia Rei

People

Academics

Academics associated with the Development and Economic History Research Group are:


Bishnupriya Gupta

Co-ordinator

Anant Sudarshan

Deputy Co-ordinator


Events

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CWIP (CAGE Work in Progress) Workshop - Ludovica Gazze

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Location: S2.79

Title: People, places or houses? A decomposition of households' carbon emissions in the UK (with Lucie Gadenne, Peter Levell, Davide Sansone)

Abstract: Understanding the determinants of households' greenhouse gases (GHG) emissions is key to designing successful decarbonization policies. We examine the role of household, house, and place in explaining household GHG emissions from transport and energy in the UK. Using detailed household panel data on housing characteristics enables us to speak to the determinants of both household and place effects and investigate the effects of different policy scenarios (e.g., revenue recycling from carbon taxes). We exploit the panel dimension of our data using a "mover design" approach to disentangle contextual factors, such as place-based drivers of emissions and house characteristics, from household-level determinants.

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