Econometrics - PowerPoint PPT Presentation

1 / 9
About This Presentation
Title:

Econometrics

Description:

Econometrics – PowerPoint PPT presentation

Number of Views:114
Avg rating:3.0/5.0
Slides: 10
Provided by: kuanp
Category:

less

Transcript and Presenter's Notes

Title: Econometrics


1
Econometrics
  • Lecture Notes Hayashi, Chapter 5c
  • Unbalanced Panels

2
Missing Observations
  • Assuming common coefficients, for each equation m
    (1,,M) and for each observation i (1,,n),yim
    zimd ai him
  • Typically, there are missing observations.
  • Assumption No Selection Bias
  • Whether an observation stays in the sample does
    not depend on the error term.

3
Missing Observations
  • Let dim 1 if observation m is in the sample
    dim 0 otherwise. Let Mi be the number of
    observations from i.

4
The Model
  • yi Fib di(big) diai hi(i1,,n)

5
The Transformed Model
  • Let Qi IMi di(didi)-1di IMi didi/Mi
  • Qiyi QiFib Qidi(big) Qidiai Qihi
  • Qiyi QiFib Qihi since Qidi 0
  • yi Fib hi
  • y Fb h
  • With zeroing out missing observation, the
    transformed model remains the same as without
    missing observations. Therefore, the formula for
    the fixed-effects estimator remains the same.

6
Fixed-Effects Estimator
  • The fixed-effects estimator of b is the pooled
    OLS estimator, which is consistent and
    asymptotically normal
  • bFE (FF)1Fy
  • bFE- b (FF)1Fh
  • Est(Avar(bFE)) 1/n (FF)1(FVF)
    (FF)1 where V (y-FbFE)(y-FbFE)

7
Fixed-Effects Estimator
  • If the assumption of spherical distribution is
    assumed E(hihi) s2IMi, so that E(hihi)
    s2Qi
  • Est(Avar(bFE)) n s2 (FF)1
  • s2 is the estimator of s2

8
No Selection Bias Assumption
  • Recall the Orthogonality Assumption for the
    transformed modelE(fim hih) 0 (m,h1,,M)
  • A stronger assumption is need for the case with
    missing observations --No Selection Bias E(fim
    hihdi) 0 (m,h1,,M)

9
Large Sample Properties
  • If the assumption of no selection bias holds in
    addition to other assumptions required for
    establishing the large sample properties of the
    fixed-effects estimator, the same properties
    carry over for unbalanced panels.
Write a Comment
User Comments (0)
About PowerShow.com