There’s been a huge surge in data usage across all sectors of the economy of late. And in the financial sector, recent research by MIT’s Maryam Farboodi shows that while data resolves some risk for investors, it also creates risk. In this podcast, Farboodi talks about how big data is disproportionally benefiting the larger firms and how the distributional aspects of data may be exacerbating inequality. Maryam Farboodi is an Assistant Professor of Finance at the MIT Sloan School of Management, her research on Data in Finance has been published in the National Bureau of Economic Research. Farboodi was invited to speak at the IMF’s Institute for capacity Development.
Gross domestic product, or GDP, is the one statistic that almost everyone knows is used to measure economic growth. But in this podcast, economist Diane Coyle suggests GDP may be a poor measure of prosperity. With all the technological advances in recent years one would expect that economies have become more productive. But when measured in GDP the numbers show the opposite is true. Coyle refers to this phenomenon as the productivity puzzle, and says the mismeasurement of digital activities within the economy has a lot to do with it. Coyle is Professor of Economics at the University of Manchester, and spoke at the IMF Statistical forum on Measuring the Digital Economy.
Read her blog The Enlightened Economist
Ravi Kanbur says statistics are fundamentally political in nature and in import. Kanbur is Professor of Economics at Cornell University and gave the keynote speech at the Fourth IMF Statistical forum on Statistics for Inclusive Growth, held in November 2016. In this podcast, Kanbur says data doesn’t always reflect reality when it comes to poverty and inequality.
Ravi Kanbur: T. H. Lee Professor of World Affairs and Professor of Economics at Cornell University.