Stockholms universitet ht 2005 Statistiska institutionen



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STOCKHOLMS UNIVERSITET HT 2005

Statistiska institutionen

2005-10-20 MC

Ekonometri 5 poäng

Källa: http://lib.stat.cmu.edu/DASL/Datafiles/agecondat.html

Story Name: Agricultural Economics Studies

Story Topics: Economics , Consumer

Data file Name: Agricultural Economics Studies

Methods: Regression , Multivariate regression , Time series

Reference: F.B. Waugh, Graphic Analysis in Agricultural Economics, Agricultural Handbook No. 128, U.S. Department of Agriculture, 1957.

Authorization: free use

Description: Price and consumption per capita of beef and pork annually from 1925 to 1941 together with other variables relevant to an economic analysis of price and/or consumption of beef and pork over the period.

Abstract: These data provide the student with opportunity to develop models for beef prices, beef consumption, pork prices, and pork consumption that take account of consumption and price of a substitute product, a demand shifter (income), and other factors. Frederick V Waugh was Director of the Division of Agricultural Economics of the Agricultural Marketing Service in the U.S. Department of Agriculture. In the introduction to the handbook from which the data (1925-1941) were taken, he points out (in 1957) that in the 1920's graphic analysis was the principle tool used by agricultural economists, and that with advent of the "new" mathematical models and computers, graphic analysis was receiving less attention. He comments "Nevertheless, it is my own view that graphic analysis is an indispensable tool which should be used right along with the new and fancier gadgets" Now, 30 years later, the personal computer has made this view a practical reality


Number of cases: 17

Variable Names:


  1. PBE = Price of beef (cents/lb)

  2. CBE = Consumption of beef per capita (lbs)

  3. PPO = Price of pork (cents/lb)

  4. CPO = Consumption of pork per capita (lbs)

  5. PFO = Retail food price index (1947-1949 = 100)

  6. DINC = Disposable income per capita index (1947-1949 = 100)

  7. CFO = Food consumption per capita index (1947-1949 = 100)

  8. RDINC = Index of real disposable income per capita (1947-1949 = 100)

  9. RFP = Retail food price index adjusted by the CPI (1947-1949 = 100)

The Data:

YEAR PBE CBE PPO CPO PFO DINC CFO RDINC RFP

1925 59.7 58.6 60.5 65.8 65.8 51.4 90.9 68.5 877

1926 59.7 59.4 63.3 63.3 68.0 52.6 92.1 69.6 899

1927 63.0 53.7 59.9 66.8 65.5 52.1 90.9 70.2 883

1928 71.0 48.1 56.3 69.9 64.8 52.7 90.9 71.9 884

1929 71.0 49.0 55.0 68.7 65.6 55.1 91.1 75.2 895

1930 74.2 48.2 59.6 66.1 62.4 48.8 90.7 68.3 874

1931 72.1 47.9 57.0 67.4 51.4 41.5 90.0 64.0 791

1932 79.0 46.0 49.5 69.7 42.8 31.4 87.8 53.9 733

1933 73.1 50.8 47.3 68.7 41.6 29.4 88.0 53.2 752

1934 70.2 55.2 56.6 62.2 46.4 33.2 89.1 58.0 811

1935 82.2 52.2 73.9 47.7 49.7 37.0 87.3 63.2 847

1936 68.4 57.3 64.4 54.4 50.1 41.8 90.5 70.5 845

1937 73.0 54.4 62.2 55.0 52.1 44.5 90.4 72.5 849

1938 70.2 53.6 59.9 57.4 48.4 40.8 90.6 67.8 803

1939 67.8 53.9 51.0 63.9 47.1 43.5 93.8 73.2 793

1940 63.4 54.2 41.5 72.4 47.8 46.5 95.5 77.6 798

1941 56.0 60.0 43.9 67.4 52.2 56.3 97.5 89.5 830

Correlations: CBE; PBE

Pearson correlation of CBE and PBE = -0,752

P-Value = 0,000




Regression Analysis: CBE versus PBE
The regression equation is

CBE = 85,2 - 0,466 PBE

Predictor Coef SE Coef T P

Constant 85,239 7,301 11,67 0,000

PBE -0,4656 0,1052 -4,42 0,000

S = 2,91166 R-Sq = 56,6% R-Sq(adj) = 53,7%

Analysis of Variance
Source DF SS MS F P

Regression 1 165,95 165,95 19,57 0,000

Residual Error 15 127,17 8,48

Total 16 293,12

Unusual Observations
Obs PBE CBE Fit SE Fit Residual St Resid

11 82,2 52,200 46,970 1,553 5,230 2,12R


R denotes an observation with a large standardized residual.

Durbin-Watson statistic = 0,490446








Residualerna över tid och residualer tidsförskjutna ett steg:





et

et-1


1,15471

*

1,95471

1,15471

-2,20896

1,95471

-4,08451

-2,20896

-3,18451

-4,08451

-2,49473

-3,18451

-3,77240

-2,49473

-2,46006

-3,77240

-0,40684

-2,46006

2,64305

-0,40684

5,22972

2,64305

3,90505

5,22972


3,14660

3,90505

1,04305

3,14660

0,22571

1,04305

-1,52274

0,22571

0,83215

-1,52274

*

0,83215


Correlations: et ; et-1
Pearson correlation of et and et-1 = 0,753

P-Value = 0,001



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