Taxes, Targets, and the Social Cost of Carbon | Tokyo
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Date: Thursday 12 May 2016 Time: 6.30-8pm Venue: Old Theatre, Old Building Speaker: Professor Robert Pindyck Chair: Professor Ian Martin In the Economica-Coase Lecture 2016, Professor Pindyck, one of the world’s leading micro-economists will discuss his recent work, which focuses on economic policies relating to rare disasters, such as low probability catastrophic outcomes from climate change or nuclear terrorism. Robert Pindyck is the Bank of Tokyo-Mitsubishi Professor in Finance and Economics at the Sloan School of Management, MIT. He is also a Research Associate of the NationalBureau of Economic Research and a Fellow of the Econometric Society, and he has been a Visiting Professor at Tel‐Aviv University, Harvard University, and Columbia University. Ian Martin is a Professor of Finance at the LSE. He received his PhD in Economics from Harvard University. Before moving to LSE, he was an Associate Professor of Finance at Stanford GSB. His research interests include cross-country contagion in financial markets; the valuation of long-dated assets; catastrophes; derivative pricing; and forecasting in financial markets. Professor Martin is the Programme Director of the LSE's MSc in Finance and Economics, and is an editor of Economica. The Department of Economics at LSE (@LSEEcon) is one of the largest economics departments in the world. Its size ensures that all areas of economics are strongly represented in both research and teaching.
Comments
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23:40 Or you might be wrong and the models for carbon are understating the calamity that is to come. This guy is a village idiot when comes to climate change.
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Wish I could watch this with seeing the slideshow too. Without, it's hard to share with people who don't know what he's talking about at all.
Just the same, let me add that we do know a great deal about the broad trajectory of climate change, even if we cannot mathematically resolve the impacts down to the square meter or anticipate the decadal timing without sizable margins of error. Nevertheless, we can know that under business as usual conditions over the next several centuries, the likelihood of total GDP collapse (humanity on the brink of extinction) has a significant non-zero probability of occurring. And though that outcome can be considered highly unlikely before the end of this century, it nevertheless has a small but non-zero probability of occurring even in the next 80 years. That 1.0 impact certainly belongs in the range of possible outcomes when we consider frameworks such as this. Also, given that we are dealing with a self-organized critical system (the earth and its ecology) which may easily have hidden power-law feedbacks embedded in its dynamics (especially as humanity struggles to interact with climate outcomes). Then what are we doing forcing fat-tailed and very uncertain statistical outcomes--for all intents and purposes, 100% of our available sample falls on one side of the eventual statistical mean--into a methodology which is all about quieting outliers and forcing thin tailed outcomes?
Again, this is a clever and interesting statistical toy (wish I could have seen the slides), but let us remember that toys are not tools, especially when attempting to lay policy foundations that might impact the lives of billions of people.