Measuring Institutions

The Wheeler Institute recognises Shikhar Singla’s research.

Over the last few decades, economists have shown that different components of culture and economic institutions matter for economic and financial development.

Attitudes and beliefs about groups can have important consequences for their economic performance. Strong economic institutions are a significant cause of long run while creditor rights, bankruptcy protection etc. matter for financial development. Social capital also matters for economic performance. High trust societies have higher economic growth and fewer regulations while poor social institutions (e.g., inter-group ethnic frictions) reduce public good provision.

Whilst the effects of institutions have been well documented, little to no attention has been paid to their measurement. This research measures the different components of institutions systematically across geographies and across time and studies their evolution.

The potential impact  

The research aims to derive a deeper understanding of how machine learning techniques and big data can be used to measure various components of institutions.

“Advances in machine learning and data mining techniques can help us better understand drivers of economic growth.” Shikhar Singla, PhD student, London Business School.

Co-authors 


Shikhar Singla is a PhD student in Finance, graduating class 2022 at London Business School. His research interests are in machine learning, regulation and institutions.
Supervisor: Vikrant Vig, Professor of Finance, London Business School


About the Wheeler Institute for Business and Development PhD Award 

The Wheeler Institute is committed to supporting the development of early career researchers.  The Wheeler Institute PhD Award is a prestigious recognition of cutting-edge research that highlights the merit of the individual PhD student’s academic focus. The award is open to all current PhD students at London Business School whose research is aligned to the Institute’s objectives. Find out more

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