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14.381

Estimation and Inference for Linear Causal and Structural Models

3-0-3 units · Graduate

Explains basic econometric ideas and methods, illustrating with empirical applications. Causal inference is emphasized and examples of economic structural models are given. Topics include randomized trials, regression, including discontinuity designs and diffs-in-diffs, and instrumental variables, including local average treatment effects. Basic asymptotic theory for regression is covered and robust standard errors and statistical inference methods are given. Restricted to PhD students from Courses 14 and 15. Instructor approval required for all others.

Fall 2018 · Statistical Method in Economics

This course is divided into two sections, Part I and Part II. Part I, found here, provides an introduction to statistical theory. Topics include normal distribution, limit theorems, Bayesian concepts, and testing, among others.

Readings

  • [SI] Casella, George and Roger Berger. Statistical Inference . 2nd Edition. Cengage Learning, 2001. ISBN: 9780534243128.
    Listed reading
  • [SI] Chapters 5.1–5.4
    Listed reading
  • [SI] Chapter 5
    Listed reading
  • [SI] Chapters 6.1–6.4
    Listed reading
  • [SI] Chapter 7.3
    Listed reading
  • [SI] Chapter 7.2.1
    Listed reading
  • [SI] Chapter 7.2.2
    Listed reading
  • [SI] Chapters 8.1–8.3
    Listed reading
  • [SI] Chapters 9.1–9.3
    Listed reading
  • Casella, George and Roger Berger. Statistical Inference . 2nd Edition. Cengage Learning, 2001. ISBN: 9780534243128.
    Listed reading

Prerequisites & course information

Prereq: 14.380 and 18.06 G (Fall; second half of term) 3-0-3 units

Sources