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Final ReviewIntroduction ot Econometrics,Fall 2020
Zhaopeng Qu
Nanjing University
12/31/2020
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Information
Exam Time: 𝐽𝑎𝑛.10, 2021, 𝑀𝑜𝑛, 8 ∶ 00 − 10 ∶ 00Books and notes
are not allowed. A calculator is an optional.
You can also bring an paper English-Chinese dictionary
ratherthan electronic one if you want use it.
All questions are in English. And answers in either Chinese
orEnglish or in both can be accepted.
Time Management is very critical. Do not spend too muchtime on a
single question.
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Review: Review Lecture 0
What is econometrics?
Data Structure:
Cross sectionTimes seriesPool-Cross sectionsPanel Data
Micro-Econometrics v.s Macro-Econometrics
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Review Lecture 1
Review of Probability Theory
Main Missions of Empirical Work: Causality v.s. Forecasting
A framework of Causal Inference
Rubin Causal ModelRandomized trial as the benchmarkRCT does not
work in reality?
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Review Lecture 2
Review of Basic Statistics
LLW and CLTStatistical InferencePoint estimation: Estimator and
EstimateThree Characteristics of an EstimatorProperties of the
sample mean and the sample varianceHypothesis Testing and
P-ValueConfidence Interval and significance levelHypothesis Tests
for the Difference Between Two Means
Randomized Controlled Trials
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Review Lecture 3
Simple OLS:
OLS estimator 𝛽R squares
The Least Squares Assumptions:
Assumption 1Assumption 2Assumption 3
Properties of the OLS estimator
The OLS estimator is unbiased, consistent and hasasymptotically
normal sampling distribution.
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Review Lecture 4
Multiple OLS Regression: Estimation
OVB BiasPerfect multicollinearity: Assumption 4Interpretation of
coefficientsPartitioned regression: proof unbiasedAdjusted
R-Squres
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Review Lecture 5
Statistical Inference of 𝛽
standard error of 𝛽Hypothesis concerning 𝛽Confidence
interval
Multiple Regression: Hypotheses tests
Heteroskedasticity & homoskedasticityTesting hypothesis on 2
or more coefficients: F-test
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Review Lecture 6: Nonlinear Regression
Polynomials, Logarithmic transformations and Interactions
How to explain these estimate coefficients?
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Review Lecture 7: Binary Dependent Variable
LPM,Logit and Probit
explain the estimate coefficientMarginal effectThe pseudo-R2
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Review Lecture 8
Internal validity v.s External validity
Threats to internal validity
Omitted variables biasFunction form misspecificationMeasurement
errorSimultaneous causalityMissing Data and Sample
SelectionHeteroskedasticity and/or correlated error terms
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Review Lecture 9: Decompostion
OB decomposition framework
Reference group problem: adjusted-weight
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Review Lecture 10: Instrumental Variables
Two assumptions
Statistical properties of 2SLS estimator
Checking Instrument Validity
first stage: weak instrumentinstitutional backgroud to
arguereduced form: exclusive restricionmore IVs: overidentification
test
Heterogeneous effect and LATE
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Review Lecture 11: Regression DiscontinuityDesign
RDD: Basic Ideas and Types
Basic assumptions
Check Validity of RDD
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Review Lecture 12: Fixed Effects Model and DID
Fixed effect: assumption and estimation
DID: basic idea and assumption
SCM: basic idea and assumption
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Closing Words
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Closing Words
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