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当代计量经济学的研究领域 PowerPoint PPT Presentation


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当代计量经济学的研究领域. 张晓峒 南开大学、吉林大学教授,数量经济学专业博士生导师 中国数量经济学会常务理事 天津市数量经济学会理事长 [email protected][email protected] 当代计量经济学研究的六大领域. 1 .单位根检验 2 .时间序列分析 3 .面板数据分析 4 .向量自回归模型与向量误差修正模型分析 5 .离散选择模型 6 . ARCH 、 GARCH 模型分析 ( 非参数方法、半参数方法、分数积分研究、 Bayes 估计 ).

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当代计量经济学的研究领域

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6617524

[email protected]@yahoo.com.cn


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1

2

3

4

5

6ARCHGARCH

(Bayes)


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  • Dickey (1976) Dickey-Fuller(1979)

  • PhillipsPhillips19861987


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1.


Df adf

DFADF

1 2


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3 4


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DFDickey-FullerADFAugmented-Dickey-Fuller

3


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DF


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DF

5T=50ut IID(0, 1) 10000


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7T =502 1


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8T =1003 1

2006DFt

2, p,126-137


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5ytDFADF


421 szindext

421szindext


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  • H0: c == 0Dickey-FullerF

  • F =3.56 < 4.61H00 ==0=00 =0


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3WSweighted symmetricPantula et al., 1994

4RMArecursively mean-adjusted

Taylor, 2002

5PPPhillips-Perron1988

6KPSSKwiatkowski-Phillips-Schmidt-Shin1992

7ERSElliot-Rothenberg-Stock Point Optimal

1996

8NPNg-Perron2001

1DHFDickey-Hasza-Fuller1984

2HEGYHylleberg-Engle-Granger-Yoo1990


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ADF

1

ADF

Perron (1989, 1990)


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2

Banerjee, Lumsdaine and Stock, (199233

Banerjee, Lumsdaine and Stock (199212


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  • 198041

  • 1981198419851993

  • 199571

  • 1994115.8118.701


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199411

5.8118.701

10 199101188612


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199312DL =

ratet = 5.2029 +2.8168DL+0.0179 t -0.0305 (t-36)DL+

(250.2) (97.7) (18.2) (-22.0)

R2 = 0.9983, DW = 0.3, F = 13635.6, T = 72, (t-36)DL=DT, (1991:1, t = 1)


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REStREStADF

RESt= -0.1957 RESt-1 + 0.3258 RESt-1

(-3.0)* (2.8)

R2 = 0.16, DW = 2.1, T= 70, (1991:03-1996:12)

-4.23-3.0 -4.23


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2

1TAR

2

Box

ARIMAARMAARMAARIMA

SARIMASARSMASARMASARIMA


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Box


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1978 1 1989 12

1978:1~1989:12

1 yt 2 Lnyt


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3 12Lnyt


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SARIMA (1, 1, 1) (1, 1, 0)12

(1+0.5924 L) (1+ 0.4093 L12) 12Lnyt=(1+ 0.4734 L) vt

(4.5) (5.4) (2.9)

R = 0.33, s.e. = 0.146, Q 36 = 15.5, 0.05(36-2-1) = 44

2

2

4 D12DLnyt 5 yt


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3


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Pooled model

Pooled model

yit = + Xit ' +it, i = 1, 2, , N; t = 1, 2, , T

yitXitk1kk1it


Entity fixed effects model

entity fixed effects model

yit= i+ Xit' +it, i = 1, 2, , N; t = 1, 2, , T

iiiXityititXitk1kk1


Time fixed effects model

time fixed effects model

yit= t + Xit'+it, i = 1, 2, , N

tTTXityititXitk1kk1


Entity random effects model

entity random effects model

yit= i+ Xit' +it, i = 1, 2, , N; t = 1, 2, , T

iXityititXitk1kk1


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  • Pooled OLS

  • betweenOLS

  • withinOLS

  • first differenceOLS

  • GLSfeasible GLS


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F

H0i =

H1i

F

F = F( m , T k )

F >F <


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Hausman

H0:

H1:

H > H <


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41/31325%131982198848336numberbeertax


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1982

1 1982 2 1988

1988


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19821988

19821988 = 1.85 + 0.36 beertax 19821988

(42.5) (5.9) SSE=98.75


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OLS

it = 2.375 + - 0.66 beertax it

(24.5) (-3.5) SSE=10.35

it = 2.37 + - 0.646 beertax it

(23.3) (-3.25) SSE=9.92

F-0.66-0.65


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F

H0i=

H1i

F= 50.8 >F 0.05(14, 89) = 1.2


1988 1982

19881982


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1Quah1990

2LLLevin-Lin1992

3LLCLevin-Lin-Chu2002

4Breitung2002

5Hadri

6Abuaf-Jorion1990Jorion-Sweeney1996

7Bai-Ng2001Moon-Perron2002

8IPSIm-Pesaran-Shin1997,2002


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9MWMaddala-Wu1997

10In Choi2001

11VanessaVanessa et al.2004

12Taylor-Sarno1998


4 var vec

4VARVEC


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VAR

1VAR

NkVAR


Var 1980 1 1988 6

VAR19801~19886

(PHO)(QHO)(NHO)T=102


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VAR

1

2

3


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VAR


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VAR

VAR| I - 1L| = 0


Granger

Granger

1999.1.4-2001.10.5SHSZ661


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10Granger

0.05


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VAR


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VAR


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VAR


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VEC


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5

:


Tobit

Tobit


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LogitProbit


Logit probit

LogitProbit

750

Logit


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  • censored regression modelTobit1010

  • truncated regression model

  • count model

  • ordered response model


6 arch garch

6. ARCHGARCH

ARCHGARCH

ARCHGARCH


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D(JPY)


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1ARCH

2GARCH

xt = 0 + 1 xt -1 + 2 xt -2 + + pxt - p + ut

t2 = 0 + 1 ut 1 2 + 1 t -12


3 tgarch

3TGARCH

TARCH

4ABSGARCH /ARCH


5 egarch

5EGARCH

GARCHexponential GARCH

EGARCHNelson 1991


6 garch m absgarch m egarch m

6GARCH-MABSGARCH-MEGARCH-M

d 0.5FIEGARCHEGARCH

7FIGARCH

Ln(t2) = + (L)-1 (1- L) - d [1+(L)] f (ut-1)

f(ut) = ut+[ ut-E ut ]

E[f(ut)] = 0


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1995.1-2000.81427JPY81.12147.14112.9313.31995481.121

JPYD(JPY)D(JPY)

1 JPY 2 DJPY


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AR(3)


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ARCH (7)


Arch 7 garch 1 1

ARCH (7) GARCH(1,1)

GARCH(1,1)


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  • GARCH

    GARCH-M(1,1)

  • TARCH

TARCH

ut 1 2 dt 1GARCH


Earch garch 1 1

EARCH GARCH(1,1)

GARCH(1,1)-5


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