NBER Publications by Denis Nekipelov

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Working Papers and Chapters

May 2014Estimation of Treatment Effects from Combined Data: Identification versus Data Security
with Tatiana Komarova, Evgeny Yakovlev
in Economics of Digitization, Avi Goldfarb, Shane Greenstein, and Catherine Tucker, editors
The security of sensitive individual data is a subject of indisputable importance. One of the major threats to sensitive data arises when one can link sensitive information and publicly available data. In this paper the authors demonstrate that even if the sensitive data are never publicly released, the point estimates from the empirical model estimated from the combined public and sensitive data may lead to a disclosure of individual information. Their theory builds on the work in Komarova, Nekipelov and Yakovlev (2011) where they analyze the individual disclosure that arises from the releases of marginal empirical distributions of individual data. The disclosure threat in that case is posed by the possibility of a linkage between the released marginal distributions. In this chapter, they...
February 2013A Dynamic Model of Subprime Mortgage Default: Estimation and Policy Implications
with Patrick Bajari, Chenghuan Sean Chu, Minjung Park: w18850
The increase in defaults in the subprime mortgage market is widely held to be one of the causes behind the recent financial turmoil. Key issues of policy concern include quantifying the role of various factors, such as home price declines and loosened underwriting standards, in the recent increase in subprime defaults and predicting the effects of various policy instruments designed to mitigate default. To address these questions, we estimate a dynamic structural model of subprime borrowers' default behavior. We prove that borrowers' time preference is identified in our model and propose an easily implementable semiparametric plug-in estimator. Our results show that principal writedowns have a significant effect on borrowers' default behavior and welfare: a uniform 10% reduction in outstan...
February 2006Estimating Static Models of Strategic Interaction
with Patrick Bajari, Han Hong, John Krainer: w12013
We propose a method for estimating static games of incomplete information. A static game is a generalization of a discrete choice model, such as a multinomial logit or probit, which allows the actions of a group of agents to be interdependent. Unlike most earlier work, the method we propose is semiparametric and does not require the covariates to lie in a discrete set. While the estimator we propose is quite flexible, we demonstrate that in most cases it can be easily implemented using standard statistical packages such as STATA. We also propose an algorithm for simulating the model which finds all equilibria to the game. As an application of our estimator, we study recommendations for high technology stocks between 1998-2003. We find that strategic motives, typically ignored in the empiri...

Contact and additional information for this authorAll papers and publicationsWorking Papers onlyWorking Papers with publication info


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