Cambridge 2nd Year Econometrics Course

0 Reviews
5
  • UniversityCambridge University
  • AreaSocial sciences
  • CourseEconometrics
  • ProfessorDebopam Bhattacharya
1 Purchases
A+Verified Grade
  • Authorjackhoyle96gmail-com
  • Created2016
  • Pages44
  • Approved6 August 2017

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About these notes

Nicely formatted notes produced with LaTeX, complete coverage of introductory econometrics with intuitive explanations and derivations of key results. These notes helped me achieve a very high first in this module, with a mark of 78.

 

  • Contents 1 Statistical Concepts 3 1.1 Consistency
  • Types of Datasets
  • 2 Ordinary Least Squares
  • 3 2.1 Goodness-of-Fit
  • 2.2 Expectations of OLS Coefficient Estimators
  • 2.3 Variance of OLS Coefficient Estimators
  • 2.4 The Gauss-Markov Theorem
  • 2.5 Simply Hypothesis Testing
  • 2.6 Hypothesis Testing with Multiple Linear Restrictions
  • 2.7 Asymptotic Properties in Multiple Regression
  • 2.7.1 Consistency
  • 2.7.2 Large Sample Inference – Central Limit Theorem
  • 2.8 Further issues in OLS
  • 2.8.1 Log Models
  • 2.8.2 Quadratic Models
  • 2.8.3 Interaction Terms
  • 2.8.4 Adjusted R-Squared
  • 2.9 Dummy Variables
  • 2.9.1 The Chow Test
  • Linear Probability Model
  • Program Evaluation
  • 2.10 Heteroskedasticity
  • 2.10.1 Parameter Estimates Under Heteroskedasticity
  • 2.10.2 Testing for Heteroskedasticity
  • 2.10.3 The White Test
  • 2.11 Specification and Data Problems
  • 2.11.1 Ramsey’s RESET
  • 2.11.2 Proxy Variables
  • 2.11.3 Lagged Dependent Variables
  • 2.11.4 Measurement Error
  • 2.11.5 Missing Data and Non-Random Samples
  • 1 3 Instrumental Variables and 2SLS 17
  • 3.1 IV Estimation in the Simple Regression Case
  • 8 3.2 IV Estimation in the Multiple Regression Case
  • 19 3.3 Using IV Estimation to Address Errors-in-Variables
  • 19 3.4 The Durbin-Wu-Hausman Test
  • 19 3.5 Testing Overidentifying Restrictions
  • 3.6 Simultaneous Equations
  • 4 Limited Dependent Variables – Probit, Logit 22 4.1 Testing Hypotheses in an LDV Setting
  • 5 Pooled Cross-Section Methods 24 6 Panel Data Methods 25 6.1 First-Difference Estimation
  • 6.2 Fixed Effects Estimation
  • 7 Time-Series Methods 27 7.1 Basic Concepts
  • 7.2 Finite Distributed Lag Models
  • 7.3 Finite Sample Properties of OLS
  • .4 Stationarity and Weak Dependence
  • 7.5 Moving Averages and Autoregression
  • 7.6 Large Sample Properties of OLS
  • 7.7 Dynamically Complete Models
  • 7.8 Testing for Serial Correlation
  • 7.8.1 Testing Strict Exogeneity
  • 7.8.2 The Durbin-Watson Test .
  • 7.8.3 Testing Without Strict Exogeneity
  • 7.9 Dealing With Serial Correlation .
  • 9.1 The Cochrange-Orcutt FGLS Procedure
  • 7.9.2 HAC Standard Errors
  • 7.10 Non-Stationary Processes
  • 7.11 Testing for Unit Roots
  • 7.12 The Dickey-Fuller Test
  • 7.13 Augmented D-F Test
  • 7.14 Spurious Regression
  • 7.15 Integration and Cointegration
  • 7.15.1 The Engle-Granger Procedure
  • 7.16 Further Model Specifications
  • 7.16.1 Autoregressive Distributed Lag Models
  • 7.16.2 Error Correction Models
  • Forecasting
  • 7.17.1 Forecast Intervals
  • 7.17.2 Out-of-sample Forecasting
  • 7.17.3 Multiple-step-ahead Forecasting

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