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 o. k. N 1. N (k+1). (k+1)1. N 1. N 1. OLS estimation (i.e. orthogonality condition). OLS estimator. linear. First two moments of the OLS estimator. unbiased. =  2 (X’X) -1. best. - PowerPoint PPT Presentation

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Page 1: Documento
Page 2: Documento

k

o

N1 N(k+1) (k+1)1 N1

N1

Page 3: Documento

ˆ;0ˆ XYuwhereuX

YXXX

XXYXXYX

0ˆ)ˆ(

OLS estimation (i.e. orthogonality condition)

OLS estimator

uXXXuXXXXXXX

uXXXX

111

1 )(ˆ

uXY

Page 4: Documento

First two moments of the OLS estimator

][)ˆ( 1 uXXXEE

)'(

)'(

]'[

)]'ˆ(ˆ)][ˆ(ˆ[)ˆ(

1

11

11

uuEXX

uuEXXXXXX

XXXuuXXXE

EEEVar

uXXX 1ˆ

= 2 (X’X)-1

best

linear

unbiased

Page 5: Documento

nI2