forecasting. aruoba-diebold-scotti (adsa) business index, fed at philadelphia the...

Forecasting

Aruoba-Diebold-Scotti (ADSA)Business Index, Fed at Philadelphia The Aruoba-Diebold-Scotti business conditions

index is designed to track real business conditions at high frequency. Its underlying economic indicators (weekly initial jobless claims; monthly payroll employment, industrial production, personal income less transfer payments, manufacturing and trade sales; and quarterly real GDP) blend high- and low-frequency information and stock and flow data. Both the ADS index and this web page are updated as data on the index's underlying components are released.

Last Two years

Since 2000

Since 1960

-6

-4

-2

0

2

4

08:1 08:2 08:3 08:4 09:1 09:2 09:3 09:4 10:1 10:2

Q109Q208Q209

Q3O8Q408

Q208

Q308

Q408

Q109

Q209

Forecasts of Rate of Real GDP Growth

Survey of Professional Forecasters

Probability Distribution on Annual growth

Lab 9 ARMA(1,1) model for dlnppifgs

-0.04

-0.02

0.00

0.02

0.04

-0.04

-0.02

0.00

0.02

0.04

75 80 85 90 95 00 05

Residual Actual Fitted

Validation

Correlogram unsatisfactory

0

20

40

60

80

100

120

-0.03 -0.02 -0.01 0.00 0.01 0.02

Series: ResidualsSample 1974:04 2009:04Observations 421

Mean 1.25E-05Median 0.000398Maximum 0.019766Minimum -0.029654Std. Dev. 0.005327Skewness -0.756870Kurtosis 7.634678

Jarque-Bera 416.9944Probability 0.000000

Serial correlation test; unsatisfactory

Validation Serial correlation test and correlogram of

residuals says we need to keep truckinng

Try Arch/Garch

Validation; standardized residuals

Standardized residuals

Standardized residuals squared

Arch LM test

Histogram of Standardized residuals

0

10

20

30

40

50

60

-3 -2 -1 0 1 2 3 4

Series: Standardized ResidualsSample 1974:04 2009:04Observations 421

Mean 0.000408Median 0.053132Maximum 3.812057Minimum -3.539766Std. Dev. 1.003577Skewness -0.054248Kurtosis 4.572801

Jarque-Bera 43.59936Probability 0.000000

Conditional variance

Forecast

Cross-correlation of dlnppifgs & Garch01

Granger test

VAR

Impulse response functions

-0.002

0.000

0.002

0.004

0.006

1 2 3 4 5 6 7 8 9 10

Response of DLNPPIFGS to DLNPPIFGS

-0.002

0.000

0.002

0.004

0.006

1 2 3 4 5 6 7 8 9 10

Response of DLNPPIFGS to GARCH01

-0.000015

-0.000010

-0.000005

0.000000

0.000005

0.000010

0.000015

1 2 3 4 5 6 7 8 9 10

Response of GARCH01 to DLNPPIFGS

-0.000015

-0.000010

-0.000005

0.000000

0.000005

0.000010

0.000015

1 2 3 4 5 6 7 8 9 10

Response of GARCH01 to GARCH01

Response to One S.D. Innovations ± 2 S.E.

Reverse order

-0.002

0.000

0.002

0.004

0.006

1 2 3 4 5 6 7 8 9 10

Response of DLNPPIFGS to DLNPPIFGS

-0.002

0.000

0.002

0.004

0.006

1 2 3 4 5 6 7 8 9 10

Response of DLNPPIFGS to GARCH01

-0.000010

-0.000005

0.000000

0.000005

0.000010

0.000015

0.000020

1 2 3 4 5 6 7 8 9 10

Response of GARCH01 to DLNPPIFGS

-0.000010

-0.000005

0.000000

0.000005

0.000010

0.000015

0.000020

1 2 3 4 5 6 7 8 9 10

Response of GARCH01 to GARCH01

Response to One S.D. Innovations ± 2 S.E.