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Modeling

Modeling. Joseph Guse Econ 398, Fall 2011. A Typical Article Outline. Introduction Literature Review Conceptual Framework Empirical Approach Description of Data Empirical Model Results Conclusion References.

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Modeling

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  1. Modeling Joseph Guse Econ 398, Fall 2011

  2. A Typical Article Outline • Introduction • Literature Review • Conceptual Framework • Empirical Approach • Description of Data • Empirical Model • Results • Conclusion • References

  3. Outline Example: Courtemanche, “Silver Lining” http://onlinelibrary.wiley.com/doi/10.1111/j.1465-7295.2009.00266.x/pdf • “Introduction” • Motivation: obesity is an expensive and growing problem • Briefly explain theoretical connection between gas prices and obesity. • Summarizes empirical results. • “Background and Theory.” • Conceptual framework • Literature review. • “Data.” • Describes data sources. • Describes how variables are constructed. • Presents summary statistics. • “Reduced-Form Estimation • Lays out regression models. • Describes and interprets results. • “Explaining the Gas Price Effect” • Extended Analysis to answer further questions about pathways. • “Conclusion”

  4. Outline Example: Garces Et Al, “LT Effect of Head Start” http://www.jstor.org/stable/3083291 • “Introduction” • Motivation: scope, size and intent of HS • States main Research Question: Long Term Effects • Describes More specific hypotheses and summarize findings • “Background” • Brief history of HS • Literature review. • Conceptual Framework: sibling fixed effects • “Data.” • Describes how PSID captures HS and other relevant data. • Describes relevant problems with survey data: recall error • Presents summary statistics. • “Empirical Methods” • Lays out regression models. • “Results” • Extensive Interpretation especially of difference between variations on regression model. • “Conclusion”

  5. What an Introduction Should Do? • Motivate the Research Question • State the Research Question • Briefly explain the conceptual framework for your analysis • Specific Hypotheses to be tested. • Summarize empirical approach and findings

  6. Literature Review • Not necessarily a separate section. • Can be subsumed into introduction or theory / background sections • Does not summarize entire articles. • Relates articles to your question. • If directly attacked your question • What did they find? • How is your approach different? • If asked a different question • Why are finding relevant? (Econometric method, causal pathway, analogous question, etc?)

  7. Theory / Conceptual Framework • Most papers: “Effect of X on Y”? This is where you tell a story about why we would expect an effect. • Does X affect human capital accumulation? • Head Start (Garces et al, 2000; Kinsey 2012) • Year Round Schooling (Wu and Stone, 2010) • Does X alter incentives? • Gas Prices (Courtemanche, 2011) • Tort Reform (Yang et al, 2008; Hopkins 2012) • Insurance Elligibility (Currie and Gruber, 1996; Upton, 2012) • Marginal Tax Rates (Goolsbee, 2000; MacKie-Mason, 1990) • Ag Subsidies (Grote, 2012) • Prison Spending (Grigsby, 2012) • Wealth Effects (McFarland, 2012) • Does X Alter Institutional Environment? • Government Form (Cornell and Kalt 2000; Johnson, 2012) • Trade Blocks (Binder, 2012) • How? Enumerate Pathways to Y. • Link Back to Incentives / Behavioral model. • Formal Model: Optimization model in which X alters “budget set”; comparative statics exercise generates hypotheses to be tested. • Narrative: Just tell a story in which the behavioral model is respected but not formalized

  8. Empirical Approach / Identification • Lay out Regression Equation to be Estimated • Enumerate the “ideal” set of variables needed. • Relate back to conceptual framework. What will a positive means in terms of your theory? • Explain exactly how you build the set of variables from the data available. • Explain how you are accounting for problems. • Selection bias, omitted variable bias, measurement error, etc. • Identification. • Sufficient Variation? • Sufficient Number of Observations? • Validity of IVs and Proxies? • Several Models? To What end? What is being tested? • Robustness / Falsification Tests.

  9. Empirical Model Example: Card and Dahl (2009)http://www.nber.org/papers/w15497 • Estimate Poission Regression with Mean Modeled as • log(μjt) = θj + Xjtγ + g(Sjt, yjt; λ) . Where… • g(Sjt, yjt , λ) = λ1·1(Sjt < −3) + λ2·1(Sjt < −3) 1(yjt = 0) • + λ3·1(−3≤ Sjt ≤ 3) + λ4·1(−3≤ Sjt ≤ 3) 1(yjt = 0) • λ5·1( Sjt > 3) + λ6·1( Sjt > 3) 1(yjt = 1) • Link back to their behavioral model? • Justified regression types? • Identification Issues?

  10. Empirical Model of Courtemanche • Time Dummies: • BMIist = α0 + α1PGASst + α2Xist+τt + λs + εist • Quadratic Trend: • BMIist = β0 + β1PGASst (3) + β2Xist+β3t + β4t2 + σs + ist • Identification Issues? • Link back to Conceptual Framework?

  11. Garces et al * Family Fixed Effects - All about identification / controlling for omitted variables * Relates back to conceptual framework?

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