Social Science Applications Forum

The Social Science Applications Forum seminar series, will be held on selected Mondays from 4:30 – 5:30pm in CMSA Building, 20 Garden Street, Room G02.

The list of speakers is below and will be updated as details are confirmed.

Date Name Title/ Abstract                                                               
4/16/2018 Alex Teytelboym

(University of Oxford)

Title: Targeted Carbon Tax Reforms

Abstract: We show that in the presence of intersectoral linkages targeted sectoral carbon taxes might be a more effective way of reducing emissions than economy-wide carbon pricing. A carbon tax imposed on all sectors unambiguously reduces aggregate emissions, but taxes targeted at the set of key sectors can lead to the greatest emissions reduction. Due to intersectoral linkages and a tax rebate effect, taxing non-key sectors dampens the reduction in aggregate emissions. A key sector typically not only produces a lot of emissions, but also has a large influence on emissions in the rest of the economy. We focus on incremental changes in carbon taxes—carbon tax reforms—to characterise the set of key sectors analytically.



Ravi Jagadeesan

(Harvard University)

Title: Optimal income taxation with growth effects

Abstract: I analyze redistributive optimal capital and labor income taxation in endogenous growth models with heterogeneous agents.  The government faces a dynamic equity-efficiency trade-off between redistribution, static distortions, and growth effects. Positive capital income taxation can be optimal, and the redistributive component of the optimal capital income tax is always positive.  With optimal capital income taxation, the optimal marginal labor income tax rates are systematically lower than their static values. My results apply in the AK growth model and in a reduced-form endogenous growth framework that nests models of growth via expanding varieties and Schumpterian growth models.



Scott Kominers

(Harvard University)

Title: Redistribution through Markets

Abstract: Even when global income redistribution is not feasible, market designers can seek to mitigate inequality within individual markets. If sellers are systematically poorer than buyers, for example, they will be willing to sell at relatively low prices. Yet a designer who cares about inequality might prefer to set higher prices precisely when sellers are poor – effectively, using the market as a redistributive tool.

In this paper, we seek to understand how to design goods markets optimally in the presence of persistent inequality. Using a mechanism design approach, we find that redistribution through markets can indeed be optimal. When there is substantial inequality across sides of the market, the designer uses a tax-like mechanism, introducing a wedge between the buyer and seller prices, and redistributing the resulting surplus to the poorer side of the market via lump-sum payments. When there is significant within-side inequality, meanwhile, the designer imposes price controls even though doing so induces rationing.



Bobby Pakzad-Hurson


Title: Crowdsourcing and Optimal Market Design


Jura Liaukonyte  (Cornell) Title:  Background Noise?  TV Advertising Affects Real Time Investor Behavior

Abstract:  Using minute-by-minute television advertising data covering approximately 326,000 ads, 301 firms, and $20 billion in ad spending, we study the real-time effects of TV advertising on investor search for online financial information and subsequent trading activity. Our identification strategy exploits the fact that viewers in different U.S. time zones are exposed to the same programming and national advertising at different times, allowing us to control for contemporaneous confounding events. We find that an average TV ad leads to a 3% increase in SEC EDGAR queries and an 8% increase in Google searches for financial information within 15 minutes of the airing of that ad. Such advertising effects spill over through horizontal and vertical product market links to financial information searches on closest rivals and suppliers. The ad-induced queries on the advertiser and its key rival lead to higher trading volumes of their respective stocks. For large advertisers, around 0.8% of daily trading volume can directly be attributed to advertising. This suggests that advertising, originally intended for consumers, has a sizable effect on financial markets.




Pietro Bonaldi (Carnegie Mellon) Title:  Synthetic Regression Discontinuity – Causal Identification with Machine Learning


Wes Pegden (Carnegie Mellon University)
Title: Developing and applying theorems for the rigorous detection of gerrymandering in the real-world.

Abstract:  We will discuss the role of Markov Chains in the rigorous detection of political gerrymandering.  Specifically, we will discuss theorems which enable Markov Chains to be used in a rigorous way in this context, without heuristic assumptions on the mixing time of the chain.

For a list of past Social Science Applications talks, please click here.

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