Project 1 2009

Average Weekly Hours, Manufacturing

0

50

100

150

200

37.50 38.75 40.00 41.25 42.50 43.75 45.00

Series: AWHMANSample 1939:01 2009:03Observations 843

Mean 40.65801Median 40.60000Maximum 45.70000Minimum 37.00000Std. Dev. 1.223442Skewness 1.536577Kurtosis 8.945283

Jarque-Bera 1573.272Probability 0.000000

Histogram of AWHMAN

Prewhitening

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4

40 50 60 70 80 90 00

DAWHMAN

36

38

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42

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46

40 50 60 70 80 90 00

AWHMAN

AWHMAN & DAWHMAN

Identification of DAWHMAN Histogram Correlogram Unit root Test

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500

-4 -3 -2 -1 0 1 2

Series: DAWHMANSample 1939:02 2009:03Observations 842

Mean 0.002613Median 0.000000Maximum 2.300000Minimum -3.800000Std. Dev. 0.302534Skewness -1.967531Kurtosis 39.72864

Jarque-Bera 47870.42Probability 0.000000

Histogram DAWHMAN

Model: Conjecture and Estimation

Estimation excluding last 12 months of data

Morgan Hansen ar(1) ar(4) ma(3) ma(4) .289

Jeff Lee ar(3) ma(1) ma(9) .291

Juliann Shan ar(1) ar(3) ar(4) ma(9) .287

Dan Helling ar(1) ar(3) ma(4) ma(9) .288

Matt Mullens ar(3) ma(1) ma(3) ma(9) .288

Chris Stroud ma(1) ma(3) ma(9) .288

Brooks Allen ar(3) ma(1) ma(3) ma(9) .288

Forecast for last 12 months of data

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DAWHMANFORECAST

FORECAST+2*SEFFORECAST-2*SEF

Dawhman, Forecat & Confidence interval, Last 12 Months of Data

Initial Condition, recoloring

Recolored Within Sample Forecast

39.0

39.5

40.0

40.5

41.0

41.5

42.0

00 01 02 03 04 05 06 07 08 09

AWHMANAWHMANG

AWHMANG+2*SEFAWHMANG-2*SEF

Within Sample Forecast Recolored:: Information is what you do not expect

Estimation for Full Period

Model Validation Actual, fitted and residual dawhman Correlogram of residual Histogram of residual Serial correlation test

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40 45 50 55 60 65 70 75 80 85 90 95 00 05

Residual Actual Fitted

Model: dawhman c ar(1) ar(3) ar(4) ma(9)

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-3 -2 -1 0 1 2

Series: ResidualsSample 1939:06 2009:03Observations 838

Mean 4.34E-05Median 0.006584Maximum 1.866925Minimum -3.668665Std. Dev. 0.287639Skewness -2.557315Kurtosis 40.26887

Jarque-Bera 49411.54Probability 0.000000

Histogram of Model Residual

Forecast for Remainder of 2009

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0.0

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0.8

09:04 09:05 09:06 09:07 09:08 09:09 09:10 09:11 09:12

DAWHMANFF ± 2 S.E.

Forecast for last 9 Months of 2009

Forecast of Month to Month Change

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DAWHMANFORECASTF

FORECASTF+2*SEFFFORECASTF-2*SEFF

Initial condition

38

39

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41

42

00 01 02 03 04 05 06 07 08 09

AWHMANAWHMANF

AWHMANF+2*SEFAWHMANF-2*SEF

Forecast of Average Weekly Hours In Manufacturing: 2009.04 - 2009.12

Lessons No single “correct” model, many “correct” Use show command to embellish view of

the forecast Estimate at the prewhitened level. Illustrate

at the cognitive level, i.e. recolor Value of forecasts: Observing what you do

not expect!

As Bernanke Says: “The economy will be slow to

recover”