economics 105 statistics
Download
Skip this Video
Download Presentation
Economics 105: Statistics

Loading in 2 Seconds...

play fullscreen
1 / 12

Economics 105: Statistics - PowerPoint PPT Presentation


  • 100 Views
  • Uploaded on

Economics 105: Statistics. Go over GH 24 Unit 3 Review is due by 4:30 p.m., Thursday, May 1 st. Multicollinearity. “ Multicollinearity ” typically refers to severe, but imperfect multicollinearity Matter of degree, not existence Consequences

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Economics 105: Statistics' - edison


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
economics 105 statistics

Economics 105: Statistics

Go over GH 24

Unit 3 Review is due by 4:30 p.m., Thursday, May 1st

multicollinearity

Multicollinearity

“Multicollinearity” typically refers to severe, but imperfect multicollinearity

Matter of degree, not existence

Consequences

Estimates of the coefficients are still unbiased

Std errors of these estimates are increased

t-statistics are smaller

Estimates are sensitive to

changes in specification (i.e., which variables are included in the model)

R2 largely unaffected

multicollinearity1

Multicollinearity

Detection

calculate all the pairwise correlation coefficients

> .7 or .8 is some cause for concern

Variance Inflation Factors (VIF) can also be calculated

Hallmark is high R2 but insignificant t-statistics

Remedy

Do nothing

Drop a variable

Transform multicollinear variables

need to have same sign and magnitudes

Get more data (i.e., increase the sample size)

specification bias

Violation of Assumption (1)…

  • true model is (A)
  • but we run (B)
  • Including an irrelevant variable
    • is an unbiased estimator of
    • ; less efficient
    • still an unbiased estimator of
      • thus, t & F tests still valid

Specification Bias

specification bias1

Violation of Assumption (1) …

  • true model is (C)
  • but we run (D)
  • Omitting a relevant variable
    • is a biased estimator of
    • is actually smaller; more efficient
    • now a biased estimator of
      • thus, t & F tests are incorrect

Specification Bias

omitted variable bias

When is an unbiased estimator of ?

  • b21 is the slope coefficient from a regression of the EXCLUDED variable on the INCLUDED variable

Omitted Variable Bias

omitted variable bias1

Omitted Variable Bias

Subcript c indexes 64 countries

Descriptive statistics

omitted variable bias6

Omitted Variable Bias

… approximately equal

ad