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1
Gauss Markov Theorem - Sketch of a proof
2
two tailed Regression t-test
3
Regresion coefficient confidence interval
4
Multicollinearity
5
p-values
6
F-test for linear restrictions in regression model
7
IV notation
8
What's the use of Matrices for regression analysis?
9
Matrix Algebra - Addition
10
Matrix Algebra Multiplication
11
Matrix Algebra Inverse
12
The Regression Model - From Matrix form to Obs form
13
Estimator Consistency and Laws of Large Numbers
14
Asymptotic Normality of OLS parameter Estimators
15
Random Regressors and OLS properties
16
TSdata from the OECD database
17
Regression Assumptions for Time Series Data
18
ECON20110 Spurious Regression
19
ECON20110 Exercise1
20
ARIMA estimation in R
21
Heteroscedasticity Intro
22
Generalised Least Squares (GLS) Theory
23
ECON20110 Detecting Heteroskedasticity
24
ECON20110 Heteroskedasticity Detection in EVIEWS
25
Introduction to Autocorrelation
26
Newey-West Standard Errors
27
ECON20110 Ramsey Reset Test
28
Using dummy variables to model structural change
29
ECON20110 Exercise 2
30
Modelling Summary
31
Measurement Error
32
Two Stage Least Squares to IV Estimator
33
Testing for Autocorrelation
34
Structural Change Example
35
ECON20110 - IV and Proxy
36
Instrumental Variable Estimation - Motivation
37
ECON20110 Exercise 4
38
Maximum Likelihood - A Poisson Example
39
ECON20110 Exam 2011 Q4
40
ECON20110 2011-12 Semester 1 Question 1
41
ECON20110 2012-13 Semester 1 Question 5
42
Introduction to Bayesian Econometrics
43
Bayesian v Frequentist Inference
44
Bayesian Estimation - Exercise
45
Selecting subsamples in EVIEWS
46
Time Series Analysis Question
47
Heteroskedasticity Question
48
Maximum Likelihood Exercise
49
Omitted Variable Bias
50
OLS estimator unbiasedness in multiple regression model
51
Omitted Variable Bias
52
OLS Parameter interpretation
53
OLS estimator variance
54
OLS linking assumptions to properties
55
Econometrics Mid-Term Feedback Nov 2019
Description:
Explore a comprehensive econometrics course covering essential topics in regression analysis, time series data, and statistical inference. Learn about the Gauss-Markov Theorem, multicollinearity, instrumental variables, heteroscedasticity, autocorrelation, and Bayesian econometrics. Dive into matrix algebra applications, asymptotic properties of estimators, and various econometric tests. Practice with real-world examples using OECD data and software like R and EViews. Gain hands-on experience through exercises and exam question reviews, enhancing your understanding of econometric modeling, estimation techniques, and hypothesis testing. Master the skills needed to analyze economic data, interpret results, and make informed decisions in this 14-hour course designed for economics and finance students.

Econometrics

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#Social Sciences #Economics #Econometrics #Data Science #Data Analysis #Time Series Analysis #Mathematics #Statistics & Probability #Statistical Modeling #Regression Analysis #Algebra #Linear Algebra #Matrix Algebra #Autocorrelation #Heteroscedasticity
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Gauss Markov Theorem - Sketch of a proof