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  • October–December 2022
  • Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed...  View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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  • 2023
  • Working Paper

Estimating Models of Supply and Demand: Instruments and Covariance Restrictions
By: Alexander MacKay and Nathan H. Miller
We consider the identification of empirical models of supply and demand with imperfect competition. We show that a covariance restriction on unobserved demand and cost shocks resolves endogeneity and identifies the price parameter. We demonstrate how to employ this...  View Details
Keywords: Demand Estimation; Identification; Endogeneity Bias; Covariance Restrictions; Ordinary Least Squares; Instrumental Variables
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  • 2014
  • Working Paper

Bridging Science and Technology Through Academic-Industry Partnerships
By: Sen Chai and Willy C. Shih
Scientific research and its translation into commercialized technology is a driver of wealth creation and economic growth. Partnerships to foster the translational processes from public research organizations, such as universities and hospitals, to private firms are a...  View Details
Keywords: Innovation; Firm Performance; Public-private Partnership Funding; Translational Research; Small And Medium Enterprises; Partners and Partnerships; Public Sector; Private Sector; Performance; Science-Based Business; Innovation and Invention
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  • June 2011
  • Article

Truth in Giving: Experimental Evidence on the Welfare Effects of Informed Giving to the Poor
By: Christina Fong and Felix Oberholzer-Gee
It is often difficult for donors to predict the value of charitable giving because they know little about the persons who receive their help. This concern is particularly acute when making contributions to organizations that serve heterogeneous populations. While we...  View Details
Keywords: Philanthropy and Charitable Giving; Policy; Information; Knowledge Acquisition; Game Theory; Prejudice and Bias; Poverty; Welfare
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  • 2009
  • Working Paper

Watch What I Do, Not What I Say: The Unintended Consequences of the Homeland Investment Act
By: Dhammika Dharmapala, C. Fritz Foley and Kristin J. Forbes
This paper analyzes the impact on firm behavior of the Homeland Investment Act of 2004, which provided a one-time tax holiday for the repatriation of foreign earnings by U.S. multinationals. The analysis controls for endogeneity and omitted variable bias by using...  View Details
Keywords: Investment; Multinational Firms and Management; Government Legislation; Taxation; Business and Shareholder Relations; Behavior; United States
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