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Matthew Whitehouse

Matthew Whitehouse

Education

United States Military Academy: B.S., Economics
College of William & Mary: M.B.A
Carnegie Mellon University: M.S., Business Analytics

CV

Matt Whitehouse is a second-year PhD student in Economics at Purdue University and an active-duty Major in the U.S. Army (Functional Area 58, Operations Research/Systems Analysis). His research applies quasi-experimental methods to questions in military manpower economics, using Army administrative data in collaboration with the Office of Economic and Manpower Analysis at West Point. His dissertation includes an evaluation of the Army's Future Soldier Preparatory Course using a regression discontinuity design, and a study of charitable giving behavior among soldiers that examines reciprocity and peer effects. He is advised by Dr. Kevin Mumford and Dr. Jillian Carr. His broader interests span labor economics, public economics, and program evaluation.

  • SS 201 - (2021-2025)

    Students learn to identify opportunity costs and tradeoffs, apply marginal analysis and optimization to decision-making, and analyze how scarcity, incentives, preferences, and risk attitudes shape human behavior. The micro block covers market equilibrium, gains from trade and economic surplus, firm cost structures and competition, market failure and externalities, the winners and losers of price controls, taxes, and trade regulation, and the consequences of asymmetric information, including the distinction between correlation and causation. The macro block covers indicators of aggregate economic well-being, fiscal and monetary policy, and the role of institutions in economic growth. Throughout, students build and critique economic models, examining how modeling assumptions limit predictions and distinguishing positive from normative analysis.

  • MA 367 - (2023)

    An applied mathematics course required for economics majors, covering the tools underlying intermediate microeconomics, macroeconomics, and econometrics: linear algebra, multivariable optimization, differential equations, and stochastic modeling. Students learn to build and modify mathematical models of relationships between variables, actors, and outcomes; solve systems of interrelated equations; analyze economic phenomena under uncertainty; and use models to assess policy decisions. Emphasis throughout is on justifying solutions, communicating results in clear technical writing, and interpreting regression output to support evidence-based recommendations. The course also serves as preparation for graduate study in the social sciences.

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