Chapter VI: Part II: Mathematical Study of Supply and Demand in the Hog Market

Mathematical formulation of price-making factors is necessary in order to know when extraordinary or strategic considerations are influencing the market. The mathematical methods are highly technical, and in order to explain most clearly we shall follow a specific problem thru from beginning to end.

The problem is to determine the price of hogs from hog receipts (supply) and from business conditions (demand). To represent business conditions, we are using bank clearings outside of New York City. The actual figures for heavy hog prices at Chicago are given in the Appendix. Hog receipts at Chicago and bank clearings outside of New York City are given on pages 81 and 82. The problem is to evolve from these figures the law of hog prices.

The first step is to determine the secular or long-time trend of these figures. Find, for example, the secular trend of such a series as:

1901 2
1902 3
1903 2
1904 5
1905 2
1906 6
1907 4
1908 6
1909 6

From looking at these figures, we know that the secular trend slopes upward, starting with about 2 in 1901, reaching 3 or 4 by 1905, and 5 or 6 by 1909. To express the matter with mathematical accuracy, the method as applied to this series is as follows: First add all the figures together. Answer in this case, 36. Then divide by the number of figures—in this case 9. Thirty-six divided by 9 gives 4, which is the value of the secular trend for 1905, which is the central year.

The year 1904 is the −1 year, 1903 the −2 year, 1902 the −3 year, 1901 the −4 year, and in like manner 1906 is the +1 year, 1907 the +2 year, 1908 the +3 year and 1909 the +4 year. Multiply the minus years by their respective values: −1 by 5, −2 by 2, −3 by 3 and −4 by 2, and also the plus years, +1 by 6, +2 by 4, +3 by 6 and +4 by 6. The totals are −26 and +56, or a net of +30. Now the sum of the squares of −1, −2, −3, −4, +1, +2, +3 and +4 is 60. Sixty divided into 30 gives .5, which is the rate of movement of the secular trend each year, or if, as we found, 4 is the secular trend value for 1905, then 3.5 is the value for 1904, 3.0 for 1903, 2.5 for 1902, and 2.0 for 1901, and in like manner 4.5 for 1906, 5.0 for 1907, 5.5 for 1908 and 6 for 1909. The secular trend is a straight line, and the actual goes above and below the secular trend in more or less wave-like fashion. In Chart I, the straight line is the secular trend of heavy hog prices at Chicago for 1903–1916, and the irregular line fluctuating above and below is the actual price of heavy hogs.

BANK CLEARINGS OF THE UNITED STATES OUTSIDE NEW YORK CITY.

(7 ciphers omitted)

══════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════
│1903.│1904.│1905.│1906.│1907.│1908.│1909.│1910.│1911.│1912.
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
│ $ │ $ │ $ │ $ │ $ │ $ │ $ │ $ │ $ │ $
Jan. │ 390│ 376│ 411│ 510│ 542│ 463│ 516│ 591│ 597│ 623
Feb. │ 323│ 330│ 353│ 415│ 449│ 388│ 437│ 498│ 497│ 566
Mar. │ 358│ 359│ 419│ 463│ 510│ 430│ 513│ 600│ 585│ 604
Apr. │ 364│ 353│ 405│ 436│ 499│ 430│ 507│ 570│ 543│ 614
May │ 354│ 339│ 418│ 444│ 507│ 421│ 491│ 537│ 557│ 604
June │ 368│ 350│ 408│ 443│ 479│ 419│ 504│ 548│ 562│ 567
July │ 379│ 348│ 403│ 440│ 506│ 448│ 515│ 543│ 555│ 602
Aug. │ 326│ 336│ 392│ 432│ 467│ 404│ 482│ 508│ 528│ 572
Sep. │ 338│ 350│ 403│ 420│ 454│ 434│ 506│ 516│ 542│ 564
Oct. │ 394│ 405│ 460│ 521│ 561│ 491│ 582│ 592│ 606│ 701
Nov. │ 356│ 418│ 461│ 505│ 418│ 480│ 572│ 582│ 603│ 655
Dec. │ 380│ 430│ 476│ 504│ 406│ 512│ 594│ 591│ 609│ 655
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
Totals│ 4330│ 4394│ 5009│ 5533│ 5798│ 5320│ 6219│ 6676│ 6784│ 7327
──────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────

══════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════
│1913.│1914.│1915.│1916.│1917.│1918.│1919.│1920.│1921.│1922.
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
│ $ │ $ │ $ │ $ │ $ │ $ │ $ │ $ │ $ │ $
Jan. │ 693│ 683│ 620│ 781│ 1051│ 1182│ 1456│ │ │
Feb. │ 584│ 563│ 543│ 719│ 884│ 1000│ 1160│ │ │
Mar. │ 628│ 640│ 628│ 820│ 1056│ 1224│ 1359│ │ │
Apr. │ 626│ 635│ 620│ 775│ 1036│ 1239│ 1326│ │ │
May │ 618│ 593│ 599│ 816│ 1073│ 1271│ 1428│ │ │
June │ 598│ 610│ 610│ 810│ 1064│ 1246│ 1449│ │ │
July │ 621│ 631│ 623│ 799│ 1048│ 1324│ 1562│ │ │
Aug. │ 563│ 535│ 573│ 805│ 1041│ 1320│ 1516│ │ │
Sep. │ 599│ 540│ 614│ 850│ 1015│ 1271│ 1598│ │ │
Oct. │ 703│ 613│ 741│ 1002│ 1254│ 1516│ 1809│ │ │
Nov. │ 631│ 568│ 756│ 1016│ 1239│ 1375│ 1672│ │ │
Dec. │ 668│ 611│ 797│ 1036│ 1192│ 1415│ 1576│ │ │
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
Totals│ 7532│ 7222│ 7724│10229│12953│15383│17909│ │ │
──────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────

RECEIPTS OF HOGS AT CHICAGO IN MILLIONS OF POUNDS.

(000,000 omitted)

══════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════
│1903.│1904.│1905.│1906.│1907.│1908.│1909.│1910.│1911.│1912.
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
Jan. │ 170│ 179│ 198│ 195│ 180│ 239│ 166│ 119│ 115│ 187
Feb. │ 144│ 174│ 152│ 158│ 151│ 184│ 141│ 122│ 150│ 172
Mar. │ 112│ 126│ 143│ 135│ 132│ 153│ 152│ 86│ 168│ 143
Apr. │ 117│ 116│ 121│ 111│ 136│ 108│ 102│ 74│ 125│ 129
May │ 130│ 124│ 143│ 127│ 152│ 132│ 123│ 110│ 154│ 146
June │ 156│ 128│ 139│ 141│ 139│ 136│ 113│ 120│ 132│ 128
July │ 128│ 79│ 115│ 135│ 147│ 118│ 101│ 96│ 118│ 125
Aug. │ 133│ 120│ 115│ 138│ 128│ 105│ 92│ 112│ 116│ 103
Sep. │ 120│ 87│ 115│ 113│ 121│ 83│ 82│ 92│ 99│ 95
Oct. │ 109│ 110│ 135│ 121│ 104│ 131│ 91│ 107│ 124│ 118
Nov. │ 145│ 164│ 162│ 127│ 99│ 174│ 127│ 127│ 144│ 127
Dec. │ 194│ 184│ 178│ 148│ 172│ 184│ 138│ 136│ 145│ 147
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
Totals│1,658│1,591│1,716│1,649│1,661│1,747│1,428│1,301│1,590│1,620
──────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────

══════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════╤═════
│1913.│1914.│1915.│1916.│1917.│1918.│1919.│1920.│1921.│1922.
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
Jan. │ 182│ 157│ 200│ 239│ 224│ 157│ 256│ │ │
Feb. │ 149│ 145│ 166│ 193│ 162│ 212│ 212│ │ │
Mar. │ 141│ 127│ 149│ 157│ 131│ 232│ 155│ │ │
Apr. │ 129│ 103│ 109│ 119│ 116│ 190│ 147│ │ │
May │ 133│ 110│ 132│ 135│ 127│ 157│ 163│ │ │
June │ 149│ 139│ 130│ 128│ 114│ 121│ 182│ │ │
July │ 126│ 112│ 122│ 122│ 110│ 153│ 146│ │ │
Aug. │ 132│ 102│ 109│ 136│ 79│ 105│ 96│ │ │
Sep. │ 131│ 90│ 97│ 106│ 58│ 98│ 110│ │ │
Oct. │ 134│ 119│ 85│ 164│ 92│ 159│ 135│ │ │
Nov. │ 133│ 95│ 152│ 207│ 146│ 202│ 182│ │ │
Dec. │ 189│ 226│ 223│ 218│ 168│ 223│ 234│ │ │
──────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────┼─────
Totals│1,728│1,525│1,674│1,924│1,527│2,009│2,018│ │ │
──────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────┴─────

The next problem is to eliminate the normal seasonal variation. For example, hog prices have a normal tendency to go down in the fall of the year, whereas bank clearings have an equally normal tendency to go up. Obviously, seasonal trends must be eliminated if such series as hog prices and bank clearings are to be compared.

As an average of the fourteen years from 1903 to 1916, inclusive, heavy hog prices at Chicago averaged in January, $6.54; February, $6.83; March, $7.22; April, $7.30; May, $7.10; June, $7.10; July, $7.18; August, $7.14; September, $7.29; October, $7.08; November, $6.65; December, $6.55; average for the entire year, $7. On this basis, January is 93 per cent of the yearly average; February, 98 per cent; March, 103 per cent; April, 104 per cent; May, 101 per cent; June, 101 per cent; July, 103 per cent; August, 102 per cent; September, 104 per cent; October, 101 per cent; November, 95 per cent, and December, 94 per cent. The December average for 1902–1915 is $6.30, or 90 per cent. Obviously, the seasonal variation as just stated in percentages is affected to some extent by the secular trend, for the Decembers of 1902–1915 average 90 per cent, and those of 1903–1916 average 94 per cent. Taking the secular trend out of our seasonal, or adding 2 points to the early months of the year and subtracting 2 points from the last months of the year, we get approximately: January, 95; February, 99; March, 104; April, 105; May, 102; June, 101; July, 103; August, 102; September, 103; October, 100; November, 94, and December, 92.[6]

Hog receipts at Chicago, in the same manner, have a modified seasonal factor of January, 132 per cent; February, 117 per cent; March, 102 per cent; April, 85 per cent; May, 99 per cent; June, 99 per cent; July, 87 per cent; August, 87 per cent; September, 74 per cent; October, 86 per cent; November, 103 per cent; December, 129 per cent.

For bank clearings outside of New York City, the modified seasonal factors are: January, 109; February, 93; March, 104; April, 100; May, 99; June, 97; July, 98; August, 90; September, 93; October, 108; November, 103, and December, 106.

After securing normal seasonal variation, the next step is to modify secular trend for seasonal variation. Secular trend of hog prices, as modified seasonally, is portrayed in Chart II. The secular trend price of hogs in January, 1903, is $5.19, which sum, multiplied by the seasonal factor 96, gives $4.98 as the secular price of hogs modified seasonally for January, 1903. The actual price was $6.60, or $1.62 above the secular modified seasonally, or 31 per cent greater than the secular price of $5.19. In this way the percentage of departure for each month from 1903 thru 1916 may be figured. This has been done for hog prices, hog receipts and bank clearings outside of New York City.[7]

Now, as it happens, hog receipts are a much more violently fluctuating series than bank clearings outside of New York City. To put the series on an even footing, resort is made to what is known as the standard deviation. To secure the standard deviation of hog price percentage departures, add up the squares of these departures. The total for the 168 months from 1903 thru 1916 is 31,894, or, dividing by 168, we get 190. The square root of 190 is 13.8, which is the standard deviation of hog prices. Standard deviation means that the probabilities are that on the average not more than one out of three of the series of figures under consideration will exceed the standard deviation. Standard deviation for hog receipts is 15, and for bank clearings 8.7. This indicates that hog receipts depart from the secular trend as modified seasonally with nearly twice as great violence as do bank clearings.

To put all three series on the same footing, we divide the percentage departures by the standard deviation, 13.8 in the case of hog prices, 15 in the case of hog receipts, and 8.7 in the case of bank clearings. In January of 1903, for example, hog prices were greater than the secular modified seasonally by 2.3 times the standard deviation; hog receipts were less by .3 of the standard deviation, and bank clearings were over by .9 of the standard deviation. The cycles of the hog prices, hog receipts and bank clearings, as secured in this way by reducing for standard deviation, are comparable. The results are charted in Charts III, IV, V.

Chart I—Irregular line represents actual Chicago hog prices. Straight
line represents secular trend.
]

Chart II is identical with Chart I except that the dotted line has
been added, which represents the secular trend as corrected
seasonally.
]

It may be seen from examining these charts that hog prices seem to be related directly to bank clearings and inversely to hog receipts. The problem is: Blend hog receipts and bank clearings together in such a way as to secure hog prices. The mathematical method of approach is by correlation coefficients and lines of regression.

First, a simple illustration of the method of securing correlation coefficients:

Take the two series, A and B, which deviate from their respective means by the amounts stated in Columns 2 and 3. In Column 1 is the year, which has nothing to do with the mathematics of the case. Column 4 is A squared, Column 5 is B squared, and Column 6 is A multiplied by B.

═════════╤═════════╤═════════╤═════════╤═════════╤═════════
1 │ 2 │ 3 │ 4 │ 5 │ 6
─────────┼─────────┼─────────┼─────────┼─────────┼─────────
│ A │ B │A squared│B squared│A times B
─────────┼─────────┼─────────┼─────────┼─────────┼─────────
1901 │ −3│ −5│ 9│ 25│ +15
1902 │ −1│ +1│ 1│ 1│ −1
1903 │ +2│ +3│ 4│ 9│ +6
1904 │ +2│ +1│ 4│ 1│ +2
Sum │ │ │ 18│ 36│ +22
─────────┴─────────┴─────────┴─────────┴─────────┴─────────

The standard deviation of A is the square root of the sum of the A squares, or 18, divided by 4. The square root of 18 divided by 4 is 2.1. Standard deviation of B, in like manner, is 3. The sum of AB divided by 4, or +22 divided by 4, equals +5.5. The correlation coefficient is +5.5 divided by the standard deviation of A multiplied by the standard deviation of B, or 5.5 divided by 6.3, which gives +.87. A correlation coefficient of .87 is very high, perfect correlation being 1. Correlation over .5 is considered fairly good, especially if there is a long list (fifty or more) of figures in each series.

The formula for determining A in terms of B is:

A equals r((σ_{a})/(σ_{b}))B

In this formula, r is the correlation coefficient and σa is the standard deviation of A, and σb is the standard deviation of B. Substituting for the specific problem, we get:

A equals .87((2.1)/(3.0))B or

A equals .609 B

When B is −5 we would expect A to be 3.05; when B is +1 we would expect A to be +.609; when B is +3, we would expect A to be 1.827.

Suppose now, in addition, that there are three series: A, B and C, and that the object is to determine A in terms of B and C. The three series stand:

════╤════════════╤════════════╤════════════
│ A │ B │ C
────┼────────────┼────────────┼────────────
1901│ −3│ −5│ +2
1902│ −1│ +1│ +3
1903│ +2│ +3│ −3
1904│ +2│ +1│ −2
────┴────────────┴────────────┴────────────

We already know that the standard deviation of A is 2.1, and of B is 3.0, and that the correlation coefficient between A and B is +.87. Using the customary method, we find that the standard deviation of C is 2.55 and that the correlation coefficient of A and C is −.89, and of B and C −.59. To find A in terms of B and C, we use the following formula:

A equals ((r_{ab} − r_{ac}r_{bc})/(1 − r^2_{bc}))((σ_{a})/(σ_{b}))B
+ ((r_{ac} − r_{ab}r_{bc})/(1 − r^2_{bc}))((σ_{a})/(σ_{c}))C

In this formula r_{ab} means correlation coefficient between A and B, etc.; σ_{a} means standard deviation of A.

Substituting, we get:

A equals ((+.87 − .53)/(.65))((2.1)/(3.0))B − ((−.89 +
.51)/(.65))((2.1)/(2.55))C
or, A equals .37B − .49C

Chart III. Cycles of hog prices secured by dividing the percentage
deviation of actual prices from the secular corrected seasonally, by
the standard deviation.
]

Chart IV—Cycles of hog receipts, secured by dividing the percentage
deviation from secular trend corrected seasonally, by the standard
deviation.
]

Chart V—Cycles of bank clearings outside of New York City, secured by
dividing the percentage deviation from the secular trend corrected
seasonally, by the standard deviation.
]

Applying this formula, we find that when C is +2 and B is −5, as in the year 1901, we would expect A to be −2.83, and when C is +3 and B is +1, as in 1902, we would expect A to be −1.1. In like manner, in 1903, we would expect A to be +2.60 and in 1904 +1.35.

The results expressed in a table are:

════╤════════╤══════════════════════════════════════
│Actual A│A as predicted by formula from B and C
────┼────────┼──────────────────────────────────────
1901│ −3│ −2.83
1902│ −1│ −1.10
1903│ +2│ +2.60
1904│ +2│ +1.35
────┴────────┴──────────────────────────────────────

The practical problem is to express hog prices in terms of hog receipts and bank clearings. Practically the same method is used with the 168 months from 1903 thru 1916, as with the four years which have just been used for illustration.

The standard deviations are 10.1 for hog receipts, 10.5 for hog prices and 9.8 for bank clearings. The correlation coefficients are +.39 between hog prices and bank clearings, +.26 between hog receipts and bank clearings, and −.4 between hog receipts and hog prices.

Using the formula:

A equals r((σ_{a})/(σ_{b}))B

and allowing A to represent hog prices and B to represent bank clearings, we get:

Hog prices equal .39((10.5)/(0.8)) bank clearings, or

Hog prices equal .417 bank clearings

This formula is converted back into percentage departures from secular trend modified seasonally, and finally into hog prices as affected by bank clearings. The demand, or bank clearing, price, of hogs as compared with the actual is shown in Chart VI.

In like manner we get:

Hog prices equal −.4((10.5)/(10.1)) hog receipts, or

Hog prices equal −.426 hog receipts

This formula is converted back into percentage departures from the secular trend modified seasonally, and finally into hog prices as affected by hog receipts. The supply price of hogs as compared with the actual is shown in Chart VII.

Chart VI—Dotted line is the demand price of hogs, based on bank
clearings. Irregular solid line is actual price, and straight line
is secular trend.
]

Chart VII—Dotted line is supply price of hogs, based on receipts at
Chicago. Irregular solid line is actual price, and straight line is
secular trend.
]

Chart VIII—Dotted line is supply-and-demand price of hogs, based on
bank clearings and hog receipts. Irregular solid line is actual
price.
]

Using the longer formula on page 89, we get: Hog prices equal .56 bank clearings minus .56 hog receipts. Or converted into percentage departures from the secular trend corrected seasonally: .90 of bank clearings in percentage departures minus .51 of hog receipts in percentage departures equals the percentage which hog prices depart from their secular corrected seasonally. For instance, in January, 1903, bank clearings were 8 per cent above the secular corrected seasonally, and hog receipts were 5 per cent below. Eight times .90 plus 5 times .51 gives 9.7 as the percentage which we would expect hog prices to be over their secular corrected seasonally. The secular for January, 1903, was $5.19; 9.7 per cent of $5.19 gives 50 cents. The secular corrected seasonally for January, 1903, is $4.98. Add 50 cents to $4.98 and we get $5.48 as the price which we would have expected heavy hogs to sell at Chicago in January, 1903, on the basis of good business and small hog receipts. Actually, hogs sold for $6.60, or $1.12 over the price predicted by formula.

This is done for all the months from 1903 to 1916, and the supply-and-demand price of hogs, as derived from hog receipts at Chicago and bank clearings outside of New York is charted in Chart VIII, in comparison with the actual prices.

PREDICTING THE FUTURE OF HOG PRICES

We assume that at the present time, and probably for some time to come, we are on a basis of 90 per cent above 1913 for hog prices, and 100 per cent over 1913 in bank clearings. This conclusion is based to some extent on the reasoning presented in the June monthly supplement of the Harvard Review of Economic Statistics for the year 1919.

On this basis, the secular trend of heavy hog prices at Chicago, modified seasonally, should be roughly as follows for the several years beginning with 1919: January, $14.35; February, $15.07; March, $15.82; April, $15.67; May, $15.22; June, $15.22; July, $15.52; August, $15.22; September, $15.52; October, $15.07; November, $14.16, and December, $13.86.[8] This is on the assumption that hog prices and prices generally will have for their normal mean a level 90 per cent above the 1913 level. It is expected that in a rough way hog prices will depart from this level according to the size of hog receipts and the condition of general business as expressed by bank clearings. (During 1920, and possibly 1921, heavy exports will doubtless have influence.)

The secular trend of bank clearings outside New York, modified seasonally, for the year beginning with 1919, is taken as: January, $13,952,000,000; February, $11,648,000,000; March, $13,056,000,000; April, $12,800,000,000; May, $12,416,000,000; June, $12,416,000,000; July, $12,544,000,000; August, $11,648,000,000; September, $12,032,000; October, $13,824,000,000; November, $13,440,000,000, and December, $13,824,000,000.

The secular trend of hog receipts at Chicago in millions of pounds, modified seasonally, for the period beginning with 1919, is taken as: January, 184; February, 163; March, 143; April, 118; May, 139; June, 139; July, 121; August, 121; September, 103; October, 120; November, 144, and December, 180.

Based on the formula as secured in the preceding chapter (hog price equals .56 bank clearings minus .56 hog receipts), we would expect the following scale of hog prices in January, when receipts follow the secular trend (184,000,000 pounds at Chicago), but bank clearings are variable:

Bank Clearings in January. Heavy Hog Prices.
$11,000,000,000 $11.35
11,500,000,000 11.85
16,500,000,000 16.85

In like manner, tables may be made up for each month of the year, the idea being that for each $500,000,000 the bank clearings outside of New York are above or below the secular trend seasonally modified, fifty cents is added to or subtracted from the secular trend hog price seasonally modified. Thus for April the tables would be:

Bank Clearings in April. Heavy Hog Prices.
$ 9,800,000,000 $12.67
12,800,000,000 15.67
15,800,000,000 18.67

Taking the tables as worked out for bank clearings and hog prices, we next modify for hog receipts. An excess of 33,000,000 pounds of hog receipts at Chicago in a month means on the average $1.80 lower prices, and vice versa. Thus, in January, with bank clearings at $13,952,000,000, we would expect the following prices with various sizes of hog receipts:

Hog Receipts (in Pounds). Heavy Hog Prices.
162,000,000 $15.55
184,000,000 14.35
195,000,000 13.75
206,000,000 13.15
228,000,000 11.95

The tables herewith give this problem worked out in detail for the various months. It is realized that at this writing, in early 1920, financial matters are still so deranged by the great war that our secular trend for bank clearings may be wide of the mark. This is the best prediction we can offer at this writing, and we are offering it fully aware of its weakness, but fully believing that predictions of this sort will stimulate more thoro research. It is believed that better measures of demand may eventually be found than bank clearings outside of New York City, and that better measures of supply may be found than receipts at Chicago. Also there is a possibility that the varying size of exports of hog products should be taken into account.

PRICE OF HEAVY HOGS PER HUNDREDWEIGHT, AS PREDICTED FROM HOG RECEIPTS
AND BANK CLEARINGS OUTSIDE OF NEW YORK CITY.

JANUARY.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 162 │ 173 │ 184 │ 195 │ 206 │ 217 │ 228 │ 239
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$13,000,000,000│$14.55│$13.95│$13.35│$12.75│$12.15│$11.55│$10.95│$10.35
13,500,000,000│ 15.05│ 14.45│ 13.85│ 13.25│ 12.65│ 12.05│ 11.45│ 10.85
14,000,000,000│ 15.55│ 14.95│ 14.35│ 13.75│ 13.15│ 12.55│ 11.95│ 11.35
14,500,000,000│ 16.05│ 15.45│ 14.85│ 14.25│ 13.65│ 13.05│ 12.45│ 11.85
15,000,000,000│ 16.55│ 15.95│ 15.35│ 14.75│ 14.15│ 13.55│ 12.95│ 12.35
15,500,000,000│ 17.05│ 16.45│ 15.85│ 15.25│ 14.65│ 14.05│ 13.45│ 12.85
16,000,000,000│ 17.55│ 16.95│ 16.35│ 15.75│ 15.15│ 14.55│ 13.95│ 13.35
16,500,000,000│ 18.05│ 17.45│ 16.85│ 16.25│ 15.65│ 15.05│ 14.45│ 13.85
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

FEBRUARY.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 141 │ 152 │ 163 │ 174 │ 185 │ 196 │ 207 │ 218
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$10,600,000,000│$15.27│$13.67│$14.07│$13.47│$11.87│$12.27│$11.67│$11.07
11,100,000,000│ 15.77│ 14.17│ 14.57│ 13.97│ 12.37│ 12.77│ 12.17│ 11.57
11,600,000,000│ 16.27│ 14.67│ 15.07│ 14.47│ 12.87│ 13.27│ 12.67│ 12.07
12,100,000,000│ 16.77│ 15.17│ 15.57│ 14.97│ 13.37│ 13.77│ 13.17│ 12.57
12,600,000,000│ 17.27│ 15.67│ 16.07│ 15.47│ 13.87│ 14.27│ 13.67│ 13.07
13,100,000,000│ 17.77│ 16.17│ 15.57│ 15.97│ 14.37│ 14.77│ 14.17│ 13.57
13,600,000,000│ 18.27│ 16.67│ 17.07│ 16.47│ 14.87│ 15.27│ 14.67│ 14.07
14,100,000,000│ 18.77│ 17.17│ 17.57│ 16.97│ 15.37│ 15.77│ 15.17│ 14.57
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

MARCH.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 121 │ 132 │ 143 │ 154 │ 165 │ 176 │ 187 │ 198
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$12,100,000,000│$16.02│$15.42│$14.82│$14.22│$13.62│$13.02│$12.42│$11.82
12,600,000,000│ 16.52│ 15.92│ 14.32│ 14.72│ 14.12│ 13.52│ 12.92│ 12.32
13,100,000,000│ 17.02│ 16.42│ 15.82│ 15.22│ 14.62│ 14.02│ 13.42│ 12.82
13,600,000,000│ 17.52│ 16.92│ 16.32│ 15.72│ 15.12│ 14.52│ 13.92│ 13.32
14,100,000,000│ 18.02│ 17.42│ 16.82│ 16.22│ 15.62│ 15.02│ 14.42│ 13.82
14,600,000,000│ 18.52│ 17.92│ 17.32│ 16.72│ 16.12│ 15.52│ 14.92│ 14.32
15,100,000,000│ 19.02│ 18.42│ 17.72│ 17.22│ 16.62│ 16.02│ 15.42│ 14.82
15,600,000,000│ 19.52│ 18.92│ 18.32│ 17.72│ 17.12│ 16.52│ 15.92│ 15.32
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

APRIL.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 96 │ 107 │ 118 │ 129 │ 140 │ 151 │ 162 │ 173
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$11,800,000,000│$15.87│$15.27│$14.67│$14.07│$13.47│$12.87│$12.27│$11.67
12,300,000,000│ 16.37│ 15.77│ 15.17│ 14.57│ 13.97│ 13.37│ 12.77│ 12.17
12,800,000,000│ 16.87│ 16.27│ 15.67│ 15.07│ 14.47│ 13.87│ 13.27│ 12.67
13,300,000,000│ 17.37│ 16.77│ 16.17│ 15.57│ 14.97│ 14.37│ 13.77│ 13.17
13,800,000,000│ 17.87│ 17.27│ 16.67│ 16.07│ 15.47│ 14.87│ 14.27│ 13.67
14,300,000,000│ 18.37│ 17.77│ 17.17│ 16.57│ 15.97│ 15.37│ 14.77│ 14.17
14,800,000,000│ 18.87│ 18.27│ 17.67│ 17.07│ 16.47│ 15.87│ 15.27│ 14.67
15,300,000,000│ 19.37│ 18.77│ 18.17│ 17.57│ 16.97│ 16.37│ 15.77│ 15.17
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

MAY.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 117 │ 128 │ 139 │ 150 │ 161 │ 172 │ 183 │ 194
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$11,400,000,000│$15.42│$14.82│$14.22│$13.62│$13.02│$12.42│$11.82│$11.22
11,900,000,000│ 15.92│ 15.32│ 14.72│ 14.12│ 13.52│ 12.92│ 12.32│ 11.72
12,400,000,000│ 16.42│ 15.82│ 15.22│ 14.62│ 14.02│ 13.42│ 12.82│ 12.22
12,900,000,000│ 16.92│ 16.32│ 15.72│ 15.12│ 14.52│ 13.92│ 13.32│ 12.72
13,400,000,000│ 17.42│ 16.82│ 16.22│ 15.62│ 15.02│ 14.42│ 13.82│ 13.22
13,900,000,000│ 17.92│ 17.32│ 16.72│ 16.12│ 15.52│ 14.92│ 14.32│ 13.72
14,400,000,000│ 18.42│ 17.82│ 17.22│ 16.62│ 16.02│ 15.42│ 14.82│ 14.22
14,900,000,000│ 18.92│ 18.32│ 17.72│ 17.12│ 16.52│ 15.92│ 15.32│ 14.72
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

JUNE.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 117 │ 128 │ 139 │ 150 │ 161 │ 172 │ 183 │ 194
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$11,400,000,000│$15.42│$14.82│$14.22│$13.62│$13.02│$12.42│$11.82│$11.22
11,900,000,000│ 15.92│ 15.32│ 14.72│ 14.12│ 13.52│ 12.92│ 12.32│ 11.72
12,400,000,000│ 16.42│ 15.82│ 15.22│ 14.62│ 14.02│ 13.42│ 12.82│ 12.22
12,900,000,000│ 16.92│ 16.32│ 15.72│ 15.12│ 14.52│ 13.92│ 13.32│ 12.72
13,400,000,000│ 17.42│ 16.82│ 16.22│ 15.62│ 15.02│ 14.42│ 13.82│ 13.22
13,900,000,000│ 17.92│ 17.32│ 16.72│ 16.12│ 15.52│ 14.92│ 14.32│ 13.72
14,400,000,000│ 18.42│ 17.82│ 17.22│ 16.62│ 16.02│ 15.42│ 14.82│ 14.22
14,900,000,000│ 18.92│ 18.32│ 17.72│ 17.12│ 16.52│ 15.92│ 15.32│ 14.72
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

JULY.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 99 │ 110 │ 121 │ 132 │ 143 │ 154 │ 165 │ 176
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$11,500,000,000│$15.72│$15.12│$14.52│$13.92│$13.32│$12.72│$12.12│$11.52
12,000,000,000│ 16.22│ 15.62│ 15.02│ 14.42│ 13.82│ 13.22│ 12.62│ 12.02
12,500,000,000│ 16.72│ 16.12│ 15.52│ 14.92│ 14.32│ 13.72│ 13.12│ 12.52
13,000,000,000│ 17.22│ 16.62│ 16.02│ 15.42│ 14.82│ 14.22│ 13.62│ 13.02
13,500,000,000│ 17.72│ 17.12│ 16.52│ 15.92│ 15.32│ 14.72│ 14.12│ 13.52
14,000,000,000│ 18.22│ 17.62│ 17.02│ 16.42│ 15.82│ 15.22│ 14.62│ 14.02
14,500,000,000│ 18.72│ 18.12│ 17.52│ 16.92│ 16.32│ 15.72│ 15.12│ 14.52
15,000,000,000│ 19.22│ 18.62│ 18.02│ 17.42│ 16.82│ 16.22│ 15.62│ 15.02
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

AUGUST.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 99 │ 110 │ 121 │ 132 │ 143 │ 154 │ 165 │ 176
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$10,600,000,000│$15.42│$14.82│$14.22│$13.62│$13.02│$12.42│$11.82│$11.22
11,100,000,000│ 15.92│ 15.32│ 14.72│ 14.12│ 13.52│ 12.92│ 12.32│ 11.72
11,600,000,000│ 16.42│ 15.82│ 15.22│ 14.62│ 14.02│ 13.42│ 12.82│ 12.22
12,100,000,000│ 16.92│ 16.32│ 15.72│ 15.12│ 14.52│ 13.92│ 13.32│ 12.72
12,600,000,000│ 17.42│ 16.82│ 16.22│ 15.62│ 15.02│ 14.42│ 13.82│ 13.22
13,100,000,000│ 17.92│ 17.32│ 16.72│ 16.12│ 15.52│ 14.92│ 14.32│ 13.72
13,600,000,000│ 18.42│ 17.82│ 17.22│ 16.62│ 16.02│ 15.42│ 14.82│ 14.22
14,100,000,000│ 18.92│ 18.32│ 17.72│ 17.12│ 16.52│ 15.92│ 15.32│ 14.72
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

SEPTEMBER.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 81 │ 92 │ 103 │ 114 │ 125 │ 136 │ 147 │ 158
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$11,000,000,000│$15.72│$15.12│$14.52│$13.92│$13.32│$12.72│$12.12│$11.52
11,500,000,000│ 16.22│ 15.62│ 15.02│ 14.42│ 13.82│ 13.22│ 12.62│ 12.02
12,000,000,000│ 16.72│ 16.12│ 15.52│ 14.92│ 14.32│ 13.72│ 13.12│ 12.52
12,500,000,000│ 17.22│ 16.62│ 16.02│ 15.42│ 14.82│ 14.22│ 13.62│ 13.02
13,000,000,000│ 17.72│ 17.12│ 16.52│ 15.92│ 15.32│ 14.72│ 14.12│ 13.52
13,500,000,000│ 18.22│ 17.62│ 17.02│ 16.42│ 15.82│ 15.22│ 14.62│ 14.02
14,000,000,000│ 18.72│ 18.12│ 17.52│ 16.92│ 16.32│ 15.72│ 15.12│ 14.52
14,500,000,000│ 19.22│ 18.62│ 18.02│ 17.42│ 16.82│ 16.22│ 15.62│ 15.02
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

OCTOBER.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 98 │ 109 │ 120 │ 131 │ 142 │ 153 │ 164 │ 175
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$12,800,000,000│$15.27│$14.67│$14.07│$13.47│$12.87│$12.27│$11.67│$11.07
13,300,000,000│ 15.77│ 15.17│ 14.57│ 13.97│ 13.37│ 12.77│ 12.17│ 11.57
13,800,000,000│ 16.27│ 15.67│ 15.07│ 14.47│ 13.87│ 13.27│ 12.67│ 12.07
14,300,000,000│ 16.77│ 16.17│ 15.57│ 14.97│ 14.37│ 13.77│ 13.17│ 12.57
14,800,000,000│ 17.27│ 16.67│ 16.07│ 15.47│ 14.87│ 14.27│ 13.67│ 13.07
15,300,000,000│ 17.77│ 17.17│ 16.57│ 15.97│ 15.37│ 14.77│ 14.17│ 13.57
15,800,000,000│ 18.27│ 17.67│ 17.07│ 16.47│ 15.87│ 15.27│ 14.67│ 14.07
16,300,000,000│ 18.77│ 18.17│ 17.57│ 16.97│ 16.37│ 15.77│ 15.17│ 14.57
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

NOVEMBER.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 122 │ 133 │ 144 │ 155 │ 166 │ 177 │ 188 │ 199
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$12,400,000,000│$14.36│$13.76│$13.16│$12.56│$11.96│$11.36│$10.76│$10.16
12,900,000,000│ 14.86│ 14.26│ 13.66│ 13.06│ 12.46│ 11.86│ 11.26│ 10.66
13,400,000,000│ 15.36│ 14.76│ 14.16│ 13.56│ 12.96│ 12.36│ 11.76│ 11.16
13,900,000,000│ 15.86│ 15.26│ 14.66│ 14.06│ 13.46│ 12.86│ 12.26│ 11.66
14,400,000,000│ 16.36│ 15.76│ 15.16│ 14.56│ 13.96│ 13.36│ 12.76│ 12.16
14,900,000,000│ 16.86│ 16.26│ 15.66│ 15.06│ 14.46│ 13.86│ 13.26│ 12.66
15,400,000,000│ 17.36│ 16.76│ 16.16│ 15.56│ 14.96│ 14.36│ 13.76│ 13.16
15,900,000,000│ 17.86│ 17.26│ 16.66│ 16.06│ 15.46│ 14.86│ 14.26│ 13.66
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

DECEMBER.

═══════════════╤═══════════════════════════════════════════════════════
Bank Clearings │ Hog Receipts at Chicago, in Millions of Pounds.
Outside New │
York. │
───────────────┼──────┬──────┬──────┬──────┬──────┬──────┬──────┬──────
„ │ 158 │ 169 │ 180 │ 191 │ 202 │ 213 │ 224 │ 235
───────────────┼──────┼──────┼──────┼──────┼──────┼──────┼──────┼──────
$12,800,000,000│$14.06│$13.46│$12.86│$12.26│$11.66│$11.06│$10.46│$ 9.86
13,300,000,000│ 14.56│ 13.96│ 13.36│ 12.76│ 12.16│ 11.56│ 10.96│ 10.36
13,800,000,000│ 15.06│ 14.46│ 13.86│ 13.26│ 12.66│ 12.06│ 11.46│ 10.86
14,300,000,000│ 15.56│ 14.96│ 14.36│ 13.76│ 13.16│ 12.56│ 11.96│ 11.36
14,800,000,000│ 16.06│ 15.46│ 14.86│ 14.26│ 13.66│ 13.06│ 12.46│ 11.86
15,300,000,000│ 16.56│ 15.96│ 15.36│ 14.76│ 14.16│ 13.56│ 12.96│ 12.36
15,800,000,000│ 17.06│ 16.46│ 15.86│ 15.26│ 14.66│ 14.06│ 13.46│ 12.86
16,300,000,000│ 17.56│ 16.96│ 16.36│ 15.76│ 15.16│ 14.56│ 13.96│ 13.36
───────────────┴──────┴──────┴──────┴──────┴──────┴──────┴──────┴──────

LIMITATIONS OF THE MATHEMATICAL METHOD

Such a mathematical formula as: Hog prices equal .56 bank clearings—.56 hog receipts must always be applied with common sense. In November of 1914, for instance, hog receipts at Chicago were abnormally small on account of foot-and-mouth disease, and in December of the same year they were abnormally large for the same reason. Judging from receipts, we might have expected heavy hogs to sell for $8.83 in November and $6.44 in December. As a matter of fact, the actual price was $7.50 in November and $7.10 in December. It was commonly recognized by the trade that hog receipts at Chicago in November and December of 1914 were abnormal, and not representative of the potential supply in the country at large.

Occasionally, as in November of 1907, falling prices act to curtail receipts. The small receipts in November, 1907, would have indicated a price of $6.75, whereas the actual price was $4.90. As a matter of fact, there was a large number of hogs that year, and the actual price reflected the potential supply rather than the temporary supply.

It is possible to refine the method considerably. For instance, it may be worth while to proceed on the assumption that the relation between hog prices and hog receipts is best expressed by an equation representative of a hyperbola or skew curve instead of a straight line. The straight line equation, based on the years 1903 to 1915, inclusive, is:

Hog prices equal −.8 −.56 hog receipts.

The hyperbola equation for these years is:

Hog prices equal −1.24 −.55 hog receipts
+.0046 hog receipts
squared.

The skew or cubic curve equation is:

Hog prices equal −1.18 −.24 hog receipts
+.0027 hog receipts squared
−.00079 hog receipts cubed.

Using these more complex mathematical methods, it is often possible to express the relationships more exactly. But no method, however far refined, will take the place of common sense market judgment. Nevertheless, it may be decidedly helpful to a better understanding of the normal working of supply and demand to use both hyperbolas and cubic curves on occasion.

Chart illustrating the straight line as compared with the skew curve,
for purposes of expressing the relation between hog receipts at
Chicago and hog prices at Chicago. On the basis of the curve when
the receipts are 45 per cent less than the secular trend corrected
seasonally, the price should be 38 per cent over, and when the
receipts are 42 per cent over the secular trend corrected
seasonally, the price should be 33 per cent under.
]

Other refinements of the mathematical study of hog prices may consist in working out the correlation coefficients between hog prices and receipts at six markets or eleven markets instead of using Chicago receipts alone. Work may be done looking into the relation between hog prices and potential supply as contrasted with the temporary or month-by-month supply. So far as the relation between hog prices and business conditions is concerned, it should be worth while to work out correlation coefficients between hog prices and the amount of new building, or hog prices and Dun’s index number. In fact, there are a great many measures of business activities which may possibly measure the demand for hogs better than bank clearings outside of New York City.[9]

Some people may think it advisable to work out a correlation and line of regression illustrating the relation between hog prices and corn prices. This has been attempted, but it has been found that after the secular and seasonal trends are taken out of both corn prices and hog prices there is practically no relation between them. It is a curious commentary on our present marketing systems that corn prices and hog prices, while very closely related decade by decade, have very little influence on each other month by month. In other words, changing costs of production can have practically nothing to do with the month-by-month changes in the market price under our present economic system. Unusually high corn prices today are more likely to influence the hog prices of next year than the hog prices of today.

After everything has been done which can be done by mathematical method, there will still be room for common sense judgment. But such judgment is best applied by men wise in market lore, men familiar with the technique of production, and who also are familiar with such mathematical methods as are here described.

CONCLUSIONS BASED ON RATIOS AND MATHEMATICS OF SUPPLY AND DEMAND

By means of corn-hog ratios, it is possible to determine with great accuracy month by month the production cost of one hundred pounds of hog flesh. The actual price, however, has been quite different from the cost-of-production price, except as an average of long periods of time. This is indicated by the profit and loss chart on page 32, the black areas above and below the zero line indicating the departure of the actual price from the ratio or cost of production price.

The actual price heretofore has been determined chiefly by the action of supply and demand and not by cost of production. The close agreement between actual price and the supply-and-demand price as based on a formula derived from bank clearings and hog receipts is shown on page 96. In the chart on page 107 are presented the cost-of-production price based on ratios and the supply-and-demand price as based on bank clearings and hog receipts.

The ratio or cost-of-production price is much steadier than the supply-and-demand price. If the farmers could arrange with the packers for a price more nearly representing the cost-of-production or ratio price, it is obvious that the supply of hogs might be considerably steadied. Once farmers realize that neither excessive profits nor excessive losses are to be expected in the hog business, they will steady down to producing about the same number of hogs each year, and they will send them to market in a uniform stream, instead of in irregular spurts.

Of course, there are always uncertainties in the way of weather, disease, etc. Hot, dry weather in July and August may curtail the corn crop and shoot up the price of corn and the cost of producing hogs. Such hot, dry weather immediately increases the cost of producing hogs. The packers, heretofore, have been either unable or unwilling to pay a price for hogs sufficient to cover the increased cost of production caused by the hot, dry weather, and as a result they have been compelled to pay more than cost of production a year or so later. Why shouldn’t the packers and farmers constantly educate the public to pay the cost-of-production price? Tell the public that the drouth and high corn prices have increased the cost of producing hogs, and the price must be increased to prevent a shortage next year. Why shouldn’t the farmers try to find a way to regulate the supply with an iron hand, in an endeavor to maintain approximately the cost-of-production price at all times? This means willingness to lower the price of hogs in years when the corn crop is large, as well as ability to raise the price in years of a short corn crop.

Dotted line represents the supply-and-demand price of hogs as derived
from bank clearings and hog receipts. Solid line represents cost of
producing hogs, based on corn-hog ratios.
]

Unquestionably there are vagaries in the consuming demand for pork which might make the payment of a cost-of-production price difficult for a time. It is believed, however, that powerful corn belt farmers’ organizations working in co-operation with the packers should be able to educate consumers to the cost-of-production idea, and so far as seasonal vagaries in the demand are concerned, the farmers and packers should be able to come to an agreement providing for paying rather more than the demand price for hogs in times of poor demand and rather less than the demand price for hogs in times of good demand, in an effort to make price meet cost of production rather than temporary demand idiosyncrasies.

It is realized that the difficulties in the way of paying cost of production at all times are even greater than here indicated. The idea, in fact, runs counter to the _laissez faire_, competitive price system under which business is conducted today. It is believed, however, that in the future more and more attention must be paid to production and less and less to price manipulation. To this end, products must be sold at all times as nearly as possible at the cost-of-production price. There must be no prospect of unusual profit or unusual loss in the production of staple products. We are now referring to industries as a whole. It is inevitable, of course, that certain individuals will make great profits and others will incur losses, even in years when the cost-of-production or ratio price is paid. Full consideration must always be given to the physical facts and to special emergencies as they arise. Standard ratios representing cost of production for an industry may suddenly be rendered out-of-date by a new invention. New situations must be recognized frankly, but at all times the guiding motive should be to pay the cost-of-production price, in order that supply and demand may operate more smoothly.

To give the cost of production price broader sway in our price system does not necessarily involve governmental control. The first step is education in price judging. Even in the grade schools and country schools, ratio methods of price judgment should be taught. In high schools the matter may be carried farther, and it is suggested that not only should the ratio method of price judging be taught in high school, but also the practical use of correlation coefficients and lines of regression in determining prices from business conditions and the supply. In college (and the colleges have been most neglectful in this matter) specific problems should be worked out in great detail. Students in such classes should have access to adding machines, calculating machines, rechentaffels, and other modern devices for making calculations easy and accurate. But the most important thing of all just now is adequate research by colleges, by experiment stations, and by governmental departments. The government and market agencies must continue to improve their statistical records, and research students must study these records with all the refinements of statistical method.

An excellent start along this line has been made by the Harvard University Committee on Economic Research. This committee seems to be concerned altogether with the industrial world. It is essential that the agricultural world be given similar service.

The object of it all is to discover the best possible kind of machinery thru which the law of supply and demand may work to the end that violent fluctuations in supply and demand may be reduced to the lowest possible point consistent with changing weather and unforeseeable accidents. The present price system is not perfect; it can be improved. But before improvements can be made, the present system must be studied with the greatest thoroness. The great weakness of the present price system is that the men who operate it are concerned chiefly with making the greatest possible profit, and not at all with making the law of supply and demand operate smoothly on a price level roughly equivalent to cost of production.

The highest purpose of our price system should be to tell producers truthfully what to do in the future, instead of capitalizing a temporary supply and demand situation to the advantage of certain bright speculators. The $4.50 price for hogs in January of 1908 was a lie so far as it guided the future action of hog producers. So also was the $11 price in March of 1910. Both prices told the approximate truth about a temporary supply-and-demand situation. But both were fundamentally lies. Our whole _laissez faire_ system is full of lies of this sort. Surely we have enough in the way of legitimate physical handicaps such as weather and pests so that we should be willing to run our price system more truthfully.

So far as farmers are concerned, the object of studies of this kind is, first, to play the price game as well as capital and labor; and, second, to co-operate with capital and labor to enforce prices roughly equivalent to cost of production, to the end that supply and demand may operate more smoothly.

It is anticipated that greater emphasis on “cost-of-production price” and less emphasis on “supply-and-demand price” will result in gradually replacing most business men with production engineers and statistical economists. Business men have had profit as their sole motive. What we need is production engineers whose chief concern is production methods, and statistical economists who are able to understand the delicate inter-relations of different industries. It is believed that there is in most men a desire to do their work well, and that this desire will find more complete expression, to the benefit of the bulk of the people, under the guidance of men whose supreme motive is not profit but technical understanding and love of the work to be done. All this concerns the farmer, to the extent that when the industrial world shifts to this kind of basis, he may be more certain of a stable price for his products.

Substituting production engineers and statistical economists for business men means doing away with the chance of excessive gains and excessive losses. And this is proper so far as production of and trade in staple products is concerned.

The only place where the commercial imagination of the old-fashioned risk-taking business men has legitimate place is in working with things which are not staple, such as theaters, luxuries, newspapers, etc.