AGRICULTURAL RESOURCES AND S0CIO-ECONIC
AFFLUENCE OF OREGON COUNTIES
by
BARRY RALPH BENSON
A RESEARCH PAPER
submitted to
THE DEPARTMENT OF GEOGRAPHY
in partial fulfillment of
the requirements for the
degree of
MASTER OF SCIENCE
1975
TABLE OF CONTENTS
Introduction .
. . .
1
.................. .. ............
2
Organization of Research Data . a .. .. . ....
Agricultural Resource Indicators . . a .. a
5
IIScope
III
IV
,
.
.
,
. .
. . . .
.
. . . . . . . . .
.
.
a a
Farmland. .
Cro1aa
a
aa
a
aa aa
.
a a
,
a
a
.
.
....
8
Harvested Cropland i..sis..aalaaasa
9
aa
a
.
a a
Irrigated Land
Crop Returti
a a
a
a
aa
a
aa
a
Fa
Sales.... .......
Farni Acre 1/alijes
.
.
.
a..
aa aa
a
a a
a
e
a a
a
a
..a
aaa
Utilization of Grazing Land
.
a
a a
11
aa
a..
12
a
aa .
.
a
.
. all ..
a
13
.a.aa.. ..,......
14
. .
.
.
.
.
.
. .
.
.
.
.
. .
.
.
. .
.. .. ., .a..a. a..a...a ....
Value of Equipment ...................
Class I Far'nis
V
Socio-Economic Affluence Indicators
Unemployment
a
a
Poverty Level,
aa aa
aa aa
a
a
.
.
a
aa
a
.
.
aa aa
a
.
a
. .
.
a a
.
16
17
...
18
a
18
a
a a
15
.
.
.
19
Welfare... .a........ ,.a. a... a. ....a..a
20
Migration
21
a a
a a
a a a
.
a a a
.
a a
aa
a
a a
aa aa
a a
Education..... .a ...aa..aaa. a..aa.a ..
Income... .
a a...., aa aa a
23
Bank Deposits.
a a . .
VI
7
a a
a a
a
aa
a
.
aa
Analysis of County Ranking.. .
Rank Group Correlation.... a.
.
a
,
a
a
a
a
.
. .
24
aa
a a a
a
a
24
.
a
.
26
.... ..
30
Agricultural Resources.............
32
Socio-Economic Affluence...........
37
Correlations of Rank Groups.. . ... . . ... 39
VIIConclusion..... .. ........ ....... .1.S.I 42
VIIIAppendix I . .
1Appendic II . .
. . . .
.
.
.
.
.
.
. . . . . .
.
.
. .
. .
.
.
a .
.
.
. . . .
.
.
. . . .
. .
.
.
.
. .
.
. .
. .
.
. .
.
.
.
47
.
48
Appendic 111....... ......... ....... . .... 49
I)C
Bibliography.
.
1
.
. .
. . . . .. . .. . .
.
.
.
50
LIST OF ILLUSTRATIONS
Figure 1
Distribution of Agricultural Resources by Group
Ranked Oregon Counties..................... 33
Figure 2
Distribution of Socio-Economic Affluence by
Group Ranked Oregon Counties.. .. .. . .... .... 38
Figure 3
Distribution of Oregon County Rank Group
Correlation................................ 40
LIST OF TABLES
Table
1
Farmland as a Percent of Total County Area.......... 8
Table
2
Cropland as a Percent of Farmland
Table
3
Harvested Cropland as a Percent of Total Cropland ..l0
Table
4
Irrigated Land as a Percent of Cropland ... . .. .. ... 11
Table
5
Crop Return.. .
Table
6
UtilizationofGrazingLand........................l3
Table
7
Farm Sales ............. ....... .. .. ........... ..... 14
Table
8
Farm Acre Values.. ....... ........ .... .... ......... 15
Table
9
Class I Farms as a Percent of all Commercial Units. 16
.
.
.
. .
. . . .
.
.
.
.
.
.
.
.
.
. .
.
.
.
.
. ..... ... .......
. .
.
.
. . . . .
.
.
. . . . .
9
12
. .
17
. . .
19
Table 10
Value of Equipment .
Table 11
Unemployment Rate. . .
Table 12
Percent of Families with less than $3000 Income.... 20
Table 13
Pt.iblic Assistance. .
.
.
. . . . . . . .
Table 14
Migration Rate. .
.
.
.
Table 15
Percent of Persons Twenty-Five Years and Older
.
.
.
.
.
.
.
.
. .
.
. .
.
.
.
.
. .
.
. .
.
.
.
.
.
.
.
.
. .
. .
. .
.
.
.
. .
.
.
. .
.
.
.
.
.
.
. .
.
.
.
.
.
.
.
.
.
. .
.
.
.
.
.
.
.
.
. .
.
.
.
.
. .
.
.
.
.
.
. . . .
.
. .
.
.
.
.
.
21
. . .
.
22
. . . . .
.
.
.
.
.
.
with Twelve or More Years of Education.. . .... 23
24
Table 16
Per Capita Income .
Tablel7
PerCapitaBankDeposits...........................25
.
.
.
. .
.
.
. .
.
.
. . . .
. . . .
. .
. .
.
.
. .
.
.
.
.
.
.
Tablel8 SynthesisofCountyRanks..........................27
Table 19
Ranlc Differences
Table 20
Majority Rank Groups of Oregon Counties... ... ...... 31
.
.
. . . . . . .
.
.
.
.
.
.
.
.
.
.
. .
. .
.
.
. .
.
.
.
.
.
.
. .
28
AGRICULTURAL RESOURCES AND SOCIO-ECONOMIC
AFFLUENCE OF OREGON COUNTIES
ABSTRACT:
Limited measures of socio-economic affluence
among some Oregon counties reflect deficiency in the
availability and development of agricultural resources.
Seventeen indicators qualify county census data into
comparable relative values.
Rank correlation analysis
of the relationship between agricultural resources and
socio-economic affluence demonstrates a significant
correlation coefficient at the 95 percent confidence
level.
Counties within rank groups correlate positively
in 61.1 percent of the cases with distribution primarily
in western Oregon counties.
KEY WORDS: Correlation,
Agricultural resources, Socio-economic affluence,
Oregon.
INTRODUCTION
Agricultural resources and their impact on Oregon are not
uniformly distributed throughout the state, and this may be
reflected by varying levels of socio-economic affluence among
the thirty-six counties.
This investigation will delineate
the measure and distribution of correlation between the level
of socio-economic affluence of Oregon counties, and the
2
availability and development of agricultural resources.
SCOPE
A problem of this nature is difficult to approach because
of the initial incomparability of the variables, the size of
the area to be examined, and the physical and economic diversity
of the counties.
1
Before the investigation can commence,
explanations of the variables within the context of the problem
are necessary.
Agricultural resources are influenced by the distribution
of physical factors including latitude, elevation, topography,
climate, soils, and water availability.
2
Agricultural resources,
however, are a product of human occupance and endeavors by man
to modify and improve the land base through the application of
technology. In a given circumstance, an agricultural resource
is tied directly to man's ability to develop it and ultimately
to it's availability.
Where no capability for development
exists, there is no agricultural resource.
Socio-economic affluence can be defined in most cases as
material wealth and abundance.
For this problem, it will be
concerned with the general well-being of the inhabitants of
a county unit.
For socio-economic affluence to be usable as
a variable for an area as large as a county, the variable must
be a measure of the county's average well-being.
If there are
many factors that indicate that a county is deficient in
various areas and markedly affluent in others, and the measures
are in similar proportions, then the measures equalize each
3
other and the county can be considered to be average in socioeconomic affluence
A simple way to determine the level of availability and
development of agricultural resources would be to examine the
gross sales of county agricultural products.
The gross sales
of the counties would be a measure of the magnitude of production
of county agricultural products.
From this, could be seen
which counties are high in production and therefore high in
availability and development of agricultural resources.
Large
agricultural counties such as Umatilla, Marion, and Maiheur
would be in the upper levels if they were compared to the
remainder of the counties.
The smaller counties such as Gilliam,
Sherman, and Wheeler, with more limited agricultural resources,
would occupy the lower levels.
Where a county is large in
area, with many agricultural units, it may have an immense
volume of sales; but where a county is small in area, with
fewer but larger farms and ranches, the gross sales of production
may be so small as to make the county appear to be deficient
in agricultural resources.
A similar analysis could be followed in regard to levels
of soda-economic affluence.
Total per capita county product
could be an indicator of affluence but it would not take into
consideration county population distribution, major industrial
character, or the nature of the labor force.
Per capita county
product would not indicate factors which make a county socially
and economically affluent nor would it show the manner in which
a county is lacking in socio-economic affluence.
Most
4
importantly, gross sales of production and per capita county
product are not directly comparable because of the diversity
of the Oregon economy.6 There are a multitude of possible
indicators of availability and development of agricultural
resources and levels of socio-economic affluence but the
measures, in the raw state, are gross and largely unusable.
Each indicator of agricultural resources and socio-economic
affluence used in correlation analysis must have the magnitude
bias removed so that the indicators are a relative measure
of the variable.
For the variables to be comparable, it is
required that the counties be measured not by the quantity
of the agricultural resource or level of socio-economic
affluence, but by the quality of the measure.
This examination
will compare and analyze the counties and their relative
value of indicators, not to make a comparison of the county's
consequence because of population or area, but to compare
and correlate the problem variables by utilizing the counties
as a means of measurement.7
Of the many possible indicators of agricultural resources,
ten indicators should serve to denote county availability and
development.
They are arranged in no particular order of
importance and for simplicity of operation, all have equal
weight.
8
1)
Farmland
2)
Cropland
3)
Harvested cropland
4)
Irrigated land
5)
Crop return
6)
Utilization of pasture and range
7)
Farm sales
8)
Farm acre values
9)
Class I agricultural units
10) Value of equipment
The volume of socio-economic affluence indicators is vast
but only a relative few can be used.
Some representative
indicators of the county socio-economic affluence measure
includes:9
1)
Unemployment rate
2)
Families with less than $ 3000 income
3)
Welfare payments
4)
Migration
5)
Education
6)
Income
7)
Bank deposits
ORGANIZATION OF RESEARCH DATA
Raw data for agricultural resources and levels of socio-
economic affluence indicators represent a vast amount of
unmanageable and incomparable information because each
indicator has a different form.
To make all the counties
comparable within each variable, the data must be derived into
relative measures.
For agricultural resources the relative
value measures will include; rates, value per unit, volume
per unit, percentages and measures of average county farms.
An average county farm is the total amount of the county
indicator divided by the number of agricultural units.
County
size and the number of agricultural units vary widely among
the counties, so the counties are comparable in some indicators
if the average county farm is used as a measure.
10
In regard to levels of socio-economic affluence, indicators
utilizing rates, percentages, and per capita relative values,
will place the counties on a more even basis and the magnitude
bias will be extirpated.
When the variables are reduced to
indicators that represent relative values of measures they
are still not directly comparable.
There are seventeen indicators
and thirty-six counties, so there are a total of 612 individual
sample points to be used in correlation analysis.
This amount
of information would be difficult to handle even as relative
values, so a system of ranking must be employed to make county
data directly comparable and meaningful.
The counties are ranked according to their relative value
for each indicator with 1 being the highest, and 36 the lowest.
Ranking will result in comparable measures that can be used
to determine the degree and distribution of correlation
between the availability and development of agricultural
resources and the level of socio-economic affluence of the
counties.
After the ranking process, the counties are divided into
rank groups according to their position among the counties.
Counties with ranks 1-12 are in the upper third rank group;
ranks 13-24 are in the middle third group; and ranks 25-36 are
7
Rank groups are used to determine
in the lower third group.
the distribution of correlation and serve as a basis for
cartographic representation.
11
AGRICULTURAL RESOURCE INDICATORS
Agricultural resource data are derived into relative
measures, but since this examination is qualatative, some
factors that distort county data must be dealt with.
Relative
values of agricultural resources are used for class I-V, or
the commercial units only.
Of all state agricultural units
only 58.5 percent are classified as commercial farms based
on the value of farm sales.
While this percentage is just
more than one-half of the total number of units, their value
of production is more than 97.6 percent of the total value
of sales for all farms and ranches in Oregon.
Part-time,
retired farmers, and abnormal farms do not make a sufficient
impact on Oregon agriculture to warrent their inclusion in
this investigation.
12
Farmland
Farmland as a percentage of the total county area gives a
good indication of the availability of land for agriculture in
the county ( Table 1 ).
More than 51.8 percent of the land in
Oregon is in Federal ownership, with additional land being
owned by state and local governments. Much of the Federal land
is leased as range to stockmen but is not included in the
indicator of availability of agricultural resources.
13
TABLE 1.-- FARMLAND AS A PERCENT OF TOTAL COUNTY AREA
County
Farmland
Acres
Baker
Benton
782592
101159
141082
14612
53712
166166
964590
80363
134637
397798
748205
1022095
1357207
24847
270008
486314
28991
659197
Clackarnas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Klamath
County
Percent of
County Area
Percent of
County Area
875796
200831
31945
325480
1324344
Malheur
254237
Marion
992792
Morrow
30966
Multnomah
183218
Polk
460728
Sherman
42457
Tillamook
1274140
Umatilla
458009
Union
649037
Wallowa
881004
Wasco
Washington 137546
707652
Wheeler
170851
Yarnhill
Lake
Lane
Lincoln
Linn
39.9
237
11.7
3.0
13.1
16.2
50.8
7.7
6.9
12.3
96.8
35.3
20.8
7.4
15.0
42.4
2.8
17.3
Farmland
Acres
/
16.6
7.0
5.0
22.3
21.0
36.0
75.3
11.4
38.9
86.7
6.0
61.7
23.6
31.9
57.8
30.0
64.8
37.6
Rank Groups
upper group
1 Gilliam
2 Sherman
3 Morrow
4 Wheeler
5 Umatilla
6 Wasco
7 Crook
8 Jefferson
9 Baker
10 Polk
11 Yarnhill
12 Marion
middle group
13 Grant
14 Wallowa
15 Washington
16 Bentori
17
18
19
20
21
22
23
24
Union
Linn
Malheur
Harney
Klamath
Lake
Coos
Jackson
lower group
25 Columbia
26 Douglas
27 Clackamas
28 Multnomah
29 Curry
30 Hood River
31 Lane
32 Deschutes
33 Tillamook
34 Lincoln
35 Clatsop
36 Josephine
Source: 1969 Census of Agriculture
Cropl and
Cropland as a percentage of farmland is an indicator of the
development of available county farmland and in part, a measure
of land capability ( Table 2 ). Harvested cropland and cropland
used for pasture are included.
TABLE 2. - - CROPLAND AS A PERCENT OF FARMLAND
County
Cropland
Acres
Baker
Benton
Clackamas
Clatsop
Columbia
145133
62603
87525
6585
22340
38054
104560
13536
61118
85283
266020
73286
196887
17549
60338
98446
14798
237784
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kiamath
Percent of
Farmland
185
61.9
62.0
45.0
41.6
22.9
10.8
16.8
45.4
21.4
35.6
7.2
14.5
70.6
22.4
20.2
50.6
36.0
Cropland
Acres
County
166790
107931
9290
241216
257765
199802
436483
Morrow
22432
Multnomah
127361
Polk
284797
Sherman
21574
Tillamook
614959
Umatilla
169604
Union
122127
Wallowa
228299
Wasco
Washington 106331
35507
Wheeler
115605
Yarnhill
Lake
Lane
Lincoln
Linn
Maiheur
Marion
Percent of
Farmland
19.0
53.7
29.0
74.1
19.5
78.6
44.0
72.4
69.5
61.8
50.8
48.3
37.0
18.8
25.9
77.3
5.0
67.7
Rank Groups
upper group
1 Marion
2 Washington
3 Linn
4 Multnomah
5 Hood River
6 Polk
7 Yamhill
8 Clackamas
9 Benton
10 Sherman
11 Lane
12 Tillamook
middle group
lower group
13
14
15
16
17
18
19
20
25
26
27
28
29
30
31
32
33
34
35
36
Josephine
Umatilla
Deschutes
Clatsop
Morrow
Columbia
Union
Klamath
21 Gilliani
22 Lincoln
23 Wasco
24 Coos
Jackson
Douglas
Jefferson
Maiheur
Lake
Wallowa
Baker
Curry
Harney
Crook
Grant
Wheeler
Source: 1969 Census of Agriculture
Harvested Cropland
Harvested cropland as a percentage of total cropland indicates
a measure of utilization and resource development ( Table 3 ).
Returns from harvested cropland are greater than from cropland
used for pasture, so the counties with the largest percentage of
10
cropland harvested will have the higher ranks, and the counties
where cropland is used mçst1y for pasture, will have a lower rank.
TABLE 3. - - HARVESTED
County
ROPLAND AS A PERCENT OF TOTAL CROPLAND
Cropi and
Pecent of
Crpland
79233
47075
54516
2622
12090
12389
51219
2363
26213
28135
115497
50346
122179
15712
35009
64337
6379
133334
4.6
5.2
2.4
9.8
4.1
2.6
9.0
7.5
2.9
3.0
3.4
8.7
2.4
9.5
8.0
2.4
3.1
6.1
Harvested
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Klainath
Harvested
Cropland
County
Lake
Lane
Lincoln
Linn
Malheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
95473
70704
3414
195123
181554
148122
181974
15313
95185
128527
5769
351349
99490
61407
101700
83639
15950
87248
Groups
upper group
1
2
3
4
5
6
7
8
9
10
11
12
12
12
Hood River
Linn
Washington
Yamhill
Benton
Polk
Marion
Maiheur
Grant
Multnomah
Lane
Clackamas
Harney
Jefferson
miIdle group
15 Union
16 Jackson
17 Lake
18 Umatilla
19 Kiamath
20 Baker
21 Columbia
22 Wheeler
23 Crook
24 Sherman
Source: 1969 Censusof Agriculture
lower group
25
26
27
28
29
30
31
32
33
34
35
36
Wallowa
Wasco
Gilliam
Josephine
Deschutes
Morrow
Clatsop
Lincoln
Douglas
Coos
Tillamook
Curry
Percent of
Cropland
57.2
65.5
36.8
81.0
70.4
74.1
41.7
68.3
74.8
45.0
26.7
57.1
58.7
44.6
44.7
78.7
50.2
75.5
11
Irrigated Land
The amount of land tIat is irrigated by all methods is an
nd development of agricultural resources
indicator of management
( Table 4 ). In the summer months, all Oregon counties require
irrigation for some crop
depending on the type of agriculture.
TABLE 4.-- IRRIGATED LAND AS A PERCENT OF CROPLAND
County
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliarn
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kiamath
Irrigated
Acres
$rcent
106811
13475
11862
447
5884
7397
67512
2604
34046
9988
5232
40640
121443
16073
40781
53219
9928
192694
73.6
21.5
13.6
6.8
26.3
19.4
64.6
19.2
55.7
11.7
2.0
55.5
61.7
91.6
67.7
54.1
67.1
81.0
Rnk
upper group
1 Hood River
2 Lake
3 Malheur
4 Kiamath
5 Baker
6 Jackson
7 Josephine
8 Crook
9 Harney
10 Deschutes
11 Grant
12 Jefferson
of
Irrigated
Acres
County
Ciopland
Lake
Lane
Lincoln
Linn
Malheur
Marion
Marrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
139348
26316
881
26579
211052
62658
20177
5555
13975
1486
3548
68515
39409
38215
21239
12884
14997
19573
Groups
middle group
13 Wheeler
14 Marion
15' Wallowa
16, Columbia
17 Multnomah
18 Lane
19 Union
20, Benton
21
22
23
24
Percent of
Cropland
Coos
Curry
Yamhill
Tillamook
Source: 1969 Census of Agriculture
lower group
25 Clackamas
26 Washington
27 Douglas
28 Umatilla
29 Polk
30 Linn
31 Lincoln
32 Wasco
33 Clatsop
34 Morrow
35 Gilliam
36 Sherman
83.6
24.4
9.5
11.0
81.9
31.4
4.6
24.8
11.0
0.5
16.5
11.1
23.2
31.3
9.3
12.1
42.2
16.9
12
Crop Return
Crop return as an indicator denotes dry tons per acre of
alfalfa, a crop ubiquitous to all the counties ( Table 5 ). Tons
per acre is a measure of resource management and development.
Crop return also serves as a measure of overall land capability.
TABLE 5.-- CROP RETURN
Tons/Acre
2.98
4.02
3.60
1.83
3.39
County
Acres
Tons
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
32556
1531
3721
1819
1146
371
25097
97164
6145
13365
3332
3891
561
75705
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kiamath
12
36
18453 48585
3160
8898
2946 10688
10018 24891
16093 40645
1814
512
6057 18951
5964 21835
705
2706
34687 124842
1.51
2.93
3.00
2.63
2.82
3.62
2.48
2.53
3.54
3.12
3.66
3.83
3.59
Acres Tons
County
20447 54920
Lake
2614 10555
Lane
150
262
Lincoln
5097
1537
Linn
46739 177350
Malheur
4620 16982
Marion
38824
9687
Morrow
4872
Multnomah 1496
2866
8919
Polk
1857
741
Sherman
6804
Tillamook 2734
Umatilla 21681 93216
22661 48982
Union
19417 50542
Wallowa
10917 33297
Wasco
Washington 5817 21947
Wheeler
4753 11995
3999 15965
Yamhill
Rank Groups
upper group
1 Umatilla
2
3
4
5
6
7
8
9
10
11
12
Lane
Benton
Morrow
Yamhill
Josephine
Malheur
Washington
Marion
Jefferson
Gilliam
Clackamas
middle group
13
Klamath
25 Lake
Columbia
Linn
Multnomah
Jackson
Polk
Wasco
Curry
Baker
Crook
Douglas
26
27
28
29
30
31
31
33
34
35
36
14 Hood River
15
16
17
18
19
20
21
22
23
24
lower group
Source: 1969 Census of Agriculture
Deschutes
Wallowa
Harney
Wheeler
Sherman
Grant
Tillamook
Union
Clatsop
Lincoln
Coos
Tons/Acre
2.69
4.04
1.75
3.31
3.79
3.67
4.00
3.25
3.11
2.51
2.48
4.29
2.16
2.60
3.05
3.77
2.52
3.99
13
F
Utilization of Grazing Land
Utilization of pasture and rangeland by cattle is a measure
of resource development ( Table 6 ). Other livestock are not
considered because of lesser impact as compared to cattle.
Cattle require relatively high quality pasture and range, so
the utilization indicator is a measure of land quality.
TABLE 6.-- UTILIZATION OF PASTURE AND RANGELAND BY CATTLE
County
Acres
Baker
Benton
Clackamas
676913
36327
53004
7925
Clatsop
Columbia
30856
108331
Coos
Crook
888617
Curry
64639
Deschutes 99719
Douglas
324710
490228
Gilliam
Grant
937828
1190090
Harney
Hood River 2318
213026
Jackson
Jefferson 386948
Josephine 12036
Kianiath 470311
Head
Acres
County
87275
8757
24925
4125
17765
24767
61135
6652
18806
30675
19110
57246
91048
1644
37586
34465
7742
80577
7.76
3.74
2.13
1.92
1.74
4.37
14.54
9.72
5.30
10.59
25.65
16.38
13.07
1.41
5.67
11.23
1.55
5.84
Lake
Lane
Acres
Head
726161
91956
Lincoln
17440
93536
Linn
Maiheur 1079323
48050
Marion
Morrow
592218
7215
Multnomah
Polk
54173
177929
Sherman
Tillamook 28024
Umatilla 662188
290621
Union
541039
Wallowa
651211
Wasco
Washington 25424
Wheeler
661573
Yarnhill
48934
74921
24411
4351
25016
160527
26102
26788
5276
13751
9398
23397
89287
32510
51974
27273
19334
21330
15992
Rank Groups
upper group
1 Tillamook
2 Washington
3
4
5
6
7
8
9
Multnomah
Hood River
Josephine
13 Polk
25
26
27
28
29
30
Lincoln
Linn
Deschutes
18 Jackson
19 Klaniath
20 Malheur
17
Columbia
Marion
Clatsop
Clackamas
21
22
23
24
Lane
Source:
lower group
16 Coos
10 Yamhill
11 Benton
12
middle group
14
15
1969
Umatilla
Baker
Union
Lake
Census of Agriculture
Curry
Douglas
Wallowa
Jefferson
Harney
Crook
31 Grant
32
33
34
35
36
Acres
Head
Head
Sherman
Wasco
Morrow
Gilliam
Wheeler
9.69
3.77
4.01
4.14
6.72
1.84
22.11
1.37
3.99
18.93
1.20
7.42
8.94
10.41
23.88
1.31
31.02
3.06
14
Farm Sales
Farm sales by
an average county farm is an indicator of the
average measure of development and production of county farm
units and this reflects their resources ( Table 7
).
Farm
sales in this case compares an average farm in a given county
to an average farm in another county.
The factors of magnitude
of production and county area are eliminated.
TABLE 7.-- FARM SALES
County
Market Value
of Production $
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Des chutes
Douglas
Gilliam
Grant
Harney
Hood River
Jacks on
Jeffers on
Josephine
Klaniath
Market Value
of Production $
County
Lake
Lane
Lincoln
Linn
Malheur
Marion
25941
29771
26331
20206
17648
17197
39562
21095
22987
12790
39862
29909
34559
33418
34867
63587
22166
43416
Morrow
Multnornah
Polk
Sherman
Till amook
Umatilla
Union
Wallowa
Was Co
Washington
Wheeler
Yanthill
37899
26982
13841
32275
37204
28430
34008
37465
23325
24252
25205
61915
24473
23539
26065
23666
25841
22967
Rank Groups
upper group
1
2
3
4
5
6
7
8
9
10
11
12
Jefferson
Umatilla
Klamath
Gilliam
Crook
Lake
Multnomah
Maiheur
Harney
Jackson
Morrow
Hood River
middle group
13 Linn
14 Grant
15 Benton
16 Marion
17 Lane
18 Clackamas
19 Wasco
20 Baker
21 Wheeler
22 Tillamook
23 Union
24 Sherman
Source: 1969 Census of Agriculture
lower group
25
26
27
28
Washington
Wallowa
Polk
Deschutes
29 Yanthill
30
31
32
33
34
35
36
Josephine
Curry
Clatsop
Columbia
Coos
Lincoln
Douglas
15
Farm Acre Values
Farm acre values are a measure of resource development and
represent the market value per acre of an average county farm
Urban counties have high acre values because of
( Table 8 ).
pressure from urban sprawl, but, these areas also tend to be
highly developed.
Large rural counties with vast farms have
low values per acre.
TABLE 8.-- FARM ACRE VALUES
County
Value per Acre
(Dollars)
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliani
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kianiath
70.42
403.23
808.01
377.64
507.24
203.53
54.01
172.37
268.76
174.08
62.57
42.72
38.97
1315.75
315.99
101.93
469.57
170.56
County
Lake.
Lane
Lincoln
Linn
Maiheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
Value per Acre
(Dollars)
56.39
529.87
320.92
377.59
96.91
600.98
65.92
1635.65
369.80
96.47
564.22
139.03
135.31
77.74
76.66
806.86
30.50
471.16
Rank Groups
upper group
1 Multnomah
2 Hood River
3 Clackamas
4 Washington
5 Marion
6 Tillamook
7 Lane
8 Columbia
9 Yamhill
10 Josephine
11 Benton
12 Clatsop
middle group
13 Linn
14 Polk
15 Lincoln
16 Jackson
17 Deschutes
18 Coos
19 Douglas
20 Curry
21 Klamath
22 Umatilla
23 Union
24 Jefferson
Source: 1969 Census of Agriculture
lower group
25 Sherman
26 Malheur
27 Wallowa
28 Wasco
29 Baker
30 Morrow
31 Gilliam
32 Crook
33 Lake
34 Grant
35 Harney
36 Wheeler
16
Class I Farms
The percent of class I farms of all commercial units serves
as an indication of the degree to which farmers and ranchers
have developed their own resources ( Table 9 ).
TABLE 9.-- CLASS I FARMS AS A PERCENT OF ALL C1MERCIAL UNITS
County
Class
I
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
77
50
167
15
21
36
51
13
Crook
Curry
Deschutes
29
36
Douglas
42
Gilliam
42
Grant
58
Harney
Hood River 103
86
Jackson
97
Jefferson
Josephine
21
Klamath
150
Class
I-V
%
98
236
424
229
118
277
598
218
218
235
380
497
303
178
623
Class
I
17.0
18.9
14.0
15.3
8.9
8.5
22.3
11.0
10.5
6.0
26.3
19.3
24.7
27.1
17.3
32.0
11.8
24.0
483
265
1196
County
Lake
Lane
Lincoln
Linn
Malheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
50
146
9
214
256
320
71
77
97
25
68
182
61
52
80
131
10
115
Class
I-V
218
770
115
950
1150
1629
277
344
597
194
344
870
469
344
418
953
90
783
Rank Groups
upper group
middle group
lower group
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Jefferson
Gilliam
Hood River
Morrow
Harney
Klamath
Linn
Lake
Multnomah
Crook
Maiheur
Umatjlla
Tillamook
Marion
Grant
Wasco
Lane
Benton
Jackson
Baker
Polk
Clatsop
Wallowa
Yamhill
Source: 1969 Census of Agriculture
Clackamas
Washington
Union
Sherman
Wheeler
Curry
Deschutes
Columbia
Coos
Josephine
Lincoln
Douglas
22.9
19.0
7.8
22.5
22.3
19.6
25.6
22.4
16.2
12.9
19.8
20.9
13.0
15.1
19.1
13.7
11.1
14.7
17
Value of Equipment
To better develop their agricultural resources, farmers
must have appropriate equipment that are in good condition
and in proportion to the agricultural type of the county. The
value of equipment of an average county farm is an indicator of
ability to develop available agricultural resources ( Table 10 ).
TABLE 10. - - VALUE OF EQUIPMENT
County
Value of Equipment
(Dollars)
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliani
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kiamath
12798.90
20297.54
9783.67
7912.70
9714.50
9536.40
16748.87
8696.83
10802.51
8782.37
36939.78
13830.31
17407.30
14645.25
12257.50
28881.25
10544.95
21641.89
Value of Equipment
(Dollars)
County
Lake
Lane
Lincoln
Linn
Maiheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yanthill
15924.52
14254.14
8839.28
16998.69
21107.61
15031.32
31178.42
12288.10
15862.53
33803.40
9130.70
23606.52
17329.20
15281.78
17303.49
12188.47
17178.54
14476.61
Rank Groups
upper group
1 Gilliani
2
3
4
5
6
7
8
9
10
11
12
Sherman
Morrow
Jefferson
Umatilla
Kiamath
Maiheur
Benton
Harney
Union
Wasco
Wheeler
middle group
13 Linn
14 Crook
15 Lake
16 Polk
17 Wallowa
18 Marion
19 Hood River
20 Yanihill
21
22
23
24
Lane
Grant
Baker
Multnomah
Source: 1969 Census of Agriculture
lower group
25 Jackson
26 Washington
27 Deschutes
28 Josephine
29 Clackamas
30 Coos
31 Columbia
32 Tillamook
33 Lincoln
34 Douglas
35 Curry
36 Clatsop
SOCIO-ECONc4IC AFFLUENCE INDICATORS
The socio-economic affluence of Oregon counties is a
measure of the overall well-being of the people.
Urbanized
counties, where employment opportunities are an attractive
force and income levels are high, may have a considerable
measure of affluence.
This assumption however, does not take
into consideration the probability that a small county, with
a small population may by socially and economically affluent,
and often to such a degree as to rank with the developed
urban counties.
The veritable well-being of a county is
not a function of magnitude of county population or income,
but a function of the limiting factors that indicate that
the inhabitants of the county are or are not socially and
economically affluent.
Unemployment
The measure of unemployment in a county is the unemployment
rate which is the unemployed labor force divided by the total
labor force ( Table 11 ).
Military personel and persons
under sixteen years old are omitted in this measurement as
they contribute little to the economy of a county.
An un-
employment rate that is relatively low indicates positive
affluence and has a high rank among the counties. A high rate
of unemployment signifies a low level of affluence and therefore a low ranking.
TABLE 11.-- UNEMPLOYMENT RATE
Labor
Force
5690
Baker
29598
Benton
Clackamas 67025
11337
Clatsop
10616
Columbia
21492
Coos
4069
Crook
4939
Curry
Deschutes 12391
Douglas
26429
782
Gilliam
2751
Grant
3009
Harney
Hood River 5417
Jackson
35664
Jefferson
3553
Josephine 12018
18745
Klamath
County
Unemployed Rate
546
1389
4031
823
803
1513
305
498
836
2345
29
337
233
505
3097
201
1169
1285
9.6
6.7
6.0
7.3
7.6
7.1
7.5
10.1
6.8
8.9
3.7
12.3
7.7
9.3
8.7
5.7
9.7
6.9
County
Labor
Force
Lake
Lane
Lincoln
Linn
2507
84010
9850
26485
8741
56669
1749
240891
13299
Maiheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
Unemployed
831
6636
17596
7199
2424
7820
67365
762
15710
211
6771
820
2172
398
3866
123
15383
820
24
406
1253
698
263
523
3376
50
1076
Rate
8.4
8.1
8.3
8.2
4.6
6.7
7.0
6.4
6.2
2.9
6.1
7.1
9.7
10.9
6.8
5.0
6.6
6.9
Rank Groups
upper group
1
2
3
4
5
6
Sherman
Gilliam
Maiheur
Washington
Jefferson
Clackamas
7 Tillarnook
8
9
10
11
11
Polk
Multnomah
Wheeler
Benton
Marion
middle group
13
13
15
15
17
Wasco
Deschutes
Klamath
Yamhill
Morrow
18
19
20
21
22
23
24
Coos
Umatilla
Clatsop
Crook
Columbia
Harney
Lane
lower group
25
26
27
28
29
30
31
32
33
34
35
36
Linn
Lincoln
Lake
Douglas
Jackson
Hood River
Baker
Josephine
Union
Curry
Wallowa
Grant
Source: 1970 Census of Population
Poverty Level
The percel)tage of families with less than $3000 annual
income is an indicator used to locate counties with concentrations
of low income ( Table 12 ).
A low percentage among the counties
indicates relative positive affluence and a high percent reflects
negative affluence..
20
TABLE 12.-- PERCENT OF FAMILIES WITH LESS THAN $3000 INC4E
County
Baker
Benton
Clackamas
Clatsop
Columbia
Percent of Families
16.4
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kiamath
8.6
6.9
10.1
10.2
8.8
11.5
13.0
12.1
11.7
9.2
8.8
7.5
11.7
11.1
11.8
15.4
9.7
Percent of Families
County
12.9
Lake
8.8
Lane
10.4
Lincoln
14.3
Liim
10.5
Maiheur
12.7
Marion
10.5
Morrow
8.1
Multnomah
11.4
Polk
11.2
Sherman
12.2
Tillamook
10.6
Umatilla
9.8
Union
14.2
Wallowa
8.7
Wasco
5.1
Washington
12.6
Wheeler
11.3
Yamhill
Rank Groups
upper group
middle group
lower group
1
2
3
4
5
6
7
7
7
10
11
12
13
14
15
16
16
18
19
20
21
22
23
24
25 Douglas
26 Jefferson
27 Deschutes
Washington
Clackamas
Harney
Multnomah
Benton
Wasco
Coos
Grant
Lane
Gilliam
Klamath
Union
Clatsop
Columbia
Lincoln
Malheur
Morrow
Umatilla
Jackson
Sherman
Yamhill
Polk
Crook
Hood River
28 Tillaniook
29
30
30
32
33
34
35
36
Wheeler
Lake
Marion
Curry
Wallowa
Linn
Josephine
Baker
Welfare
Welfare or public assistance is a measure of old age pensions
and aid to dependent children paid by the county ( Table 13 ).
Pensions paid to the aged who are not in the work force and
who have no other income except social security payments, and
a high degree of payments for support of dependent children
21
indicates negative affluence. This measure indicates the percentage
of public assistance recipients of the total county population.
TABLE 13.-- PUBLIC ASSISTANCE
County
Number of
Recipients
Baker
Benton
716
991
4841
1025
1007
3108
499
537
1182
3273
39
235
162
453
4451
429
2803
2193
Cl ackamas
Clatsop
Columbia
Coos
Crook
Curry
Des chutes
Doug 1 as
Gill jam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Klaniath
Percent of
Population
4.8
1.8
2.9
3.6
3.5
5.5
5.0
4.1
3.9
4.6
Number of
Recipients
County
201
10975
1178
3969
1780
8613
128
35642
2066
Lake
Lane
Lincoln
Linn
Malheur
Marion
Morrow
Multnomah
Polk
Sherman
1.7
3.3
2.2
3.4
4.7
5.0
7.8
4.3
Till am 00k
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
29
801
1927
518
210
551
4182
73
2407
Percent of
Population
3.2
5.1
4.6
5.5
7.6
5.6
2.8
6.4
5.8
1.3
4.5
4.2
2.6
3.4
2.7
2.6
4.0
6.0
Rank Groups
middle group
lower group
Sherman
Gilliam
Benton
Harney
Union
14
15
16
17
18
25 Baker
26 Crook
26 Jefferson
Wasco
Morrow
Clackamas
Lake
Grant
Hood River
Wallowa
20 Klaniath
upper group
1
2
3
4
5
6 Washington
7
8
9
10
11
12
12
Columbia
Clatsop
Deschutes
Wheeler
Curry
19 Umatilla
21
22
22
24
Tillamook
Douglas
Lincoln
Jackson
28 Lane
29 Coos
29 Linn
31
32
33
34
35
36
Marion
Polk
Yainhill
Muitnomab
Maiheur
Josephine
Source: County and City Data Book, 1972
Migration
High mobility is characteristic of our society. Mobility
22
results in population structure changes which reflect the
character of the county.
The net change in population from
1960 to 1970 indicates real growth or decline.
The Oregon
average rate of growth for that decade was nine percent. Any
county rate dissimilar to this can be considered to be the
result of in or out migration ( Table 14 ).
14
A county
with a high positive rate is affluent as it is experiencing
growth, and a county with a negative rate is declining and so
is deficient in affluence for this indicator.
TABLE 14.-- MIGRATION RATE
County
Net Rate
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
-19.1
22.9
366
2.4
19.9
-8.4
-2.8
-19.1
23.2
-7.3
-30.8
-18.8
County
Net Rate
Harney
Hood River
Jackson
Jefferson
Josephine
Klamath
Lake
Lane
Lincoln
Linn
Malheur
Marion
-6.8
-6.9
19.7
-1.5
13.7
-7.1
-19.5
15.4
0.5
10.5
-9.2
16.4
County
Net Rate
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yarnhill
Rank Groups
upper group
I Washington
2 Clackarnas
3 Polk
4 Deschutes
5 Benton
6 Columbia
7
Jackson
8 Yainhill
9 Marion
10 Lane
11 Josephine
12 Linn
middle group
13 Clatsop
14 Union
15 Lincoln
16 Multnomah
17 Jefferson
18 Crook
19 Umatilla
20 Harney
21 Hood River
22 Kiamath
23 Douglas
24 Wasco
Source: 1970 Census of Population
lower group
25 Coos
26 Maiheur
27 Tillamook
28 Morrow
29 Grant
30 Baker
30 Curry
32 Lake
33 Sherman
34 Wallowa
35 Gilliam
36 Wheeler
-15.1
0.1
24.2
-20.4
-12.3
-6.1
0.7
-17.5
-8.7
56.7
-39.1
17.8
23
Education
Earning ability in many instances is related to educational
level and skills.
The percentage of persons twenty-five years
and older with twelve or more years of education is an indicator
of earning capability ( Table 15 ).
The mean education level
for the thirty-six Oregon counties is 12.3 years with some
counties slightly more and others slightly less.
High levels
of education in a county can be considered a measure of
affluence
TABLE 15.-- PERCENT OF PERSONS TWENTY-FIVE YEARS AND OLDER WITH
TWELVE OR MORE YEARS OF EDUCATION
County
Percent
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
53.6
74.9
63.7
54.9
52.1
49.9
53.7
52.0
61.5
50.7
70.1
53.9
County
Percent
Harney
Hood River
Jackson
Jefferson
Josephine
Klaniath
Lake
Lane
Lincoln
Linn
Malheur
Marion
County
54.8
53.8
57.1
56.2
50.4
58.7
56.0
61.9
53.9
53.8
54.6
Morrow
Multnomah
Polk
Sherman
611
Yanthill
Percent
Tillarnook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
59.7
61.0
58.3
60.1
50.6
57.1
59.7
60.2
57.5
71.7
52.1
55.4
Rank Groups
upper group
1 Benton
2 Washington
3 Gilliam
4 Clackamas
5 Deschutes
6 Lane
7 Marion
8 Wallowa
9 Sherman
10 Multnomah
11 Morrow
12 Union
middle group
lower group
13 Klaniath
25
26
27
28
29
30
30
32
33
34
35
36
14
15
16
17
18
19
20
21
22
23
24
Polk
Wasco
Umatilla
Jackson
Jefferson
Lake
Yamhill
Clatsop
Harney
Malheur
Lincoln
Source: County and City Data Book, 1972
Grant
Linn
Hood River
Crook
Baker
Columbia
Wheeler
Curry
Douglas
Josephine
Tillamook
Coos
24
Income
Per capita personal income is an indicator of individual
earned income of county inhabitants based on the population
( Table 16 ).
TABLE 16.-- PER CAPITA INCOME
County
Baker
Bent on
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Des chutes
Douglas
Gilliam
Grant
Per Capita County
Income $
2585
Harney
Hood River
3089
Jackson
3405
Jefferson
3150
Josephine
2870
Kiamath
2974
Lake
2749
Lane
2939
Lincoln
2985
Linn
2761
2625
Malheur
2600
Marion
Per Capita
Income $
2856
2887
2876
2618
2612
2912
2628
3038
2897
2720
2377
2847
County
Morrow
Multnomah
Polk
Sherman
Till amook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
Per Capita
Income $
3071
3510
2860
2638
2793
2795
2743
2604
2877
3719
2578
2744
Rank Groups
upper group
middle group
lower group
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
25
26
27
28
29
30
31
32
33
34
35
36
Washington
Multnomah
Clackamas
Clatsop
Benton
Morrow
Lane
Coos
Curry
Kiamath
Lincoln
Deschutes
Hood River
Wasco
Jackson
Columbia
Polk
Harney
Marion
Umatilla
Tillamook
Douglas
Crook
24 Yajnhill
Union
Linn
Sherman
Lake
Gilliam
Jefferson
Josephine
Wallowa
Grant
Wheeler
Baker
Malheur
Source: compiled from County and City Data Book, 1972
Bank Deposits
A per capita bank deposit is a measure of dollars deposited
in county banks regardless of where it was earned ( Table 17 ).
Generally, where per capita bank deposits are high, the county
25
positive affluence, but this is not true in all cases and
has
Clackamas and Washington Counties are an example.
Both are
ranked low in bank deposits and it is likely that a substantial
portion of the inhabitants of these counties are employed and
deposit their incomes in Multnomah County banks.
TABLE 17.-- PER CAPITA BANK DEPOSITS
County
Percapita
County
Depos it
Baker
Benton
Clackamas
Clatsop
Columbia
$ 1749
1419
996
2055
1271
1732
1802
1846
1928
1635
2785
1682
Coos
Crook
Curry
Des chutes
Douglas
Gill i am
Grant
Harney
Hood River
Jacks on
Jefferson
Josephine
Klamath
Lake
Lane
Lincoln
Linn
Malheur
Marion
Per Capita
Deposit
$ 1996
2108
1551
1626
1689
1377
2585
1739
1722
1473
1942
1739
County
Per Capita
Deposit
Morrow
Multnomah
Polk
Sherman
Till amook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
Rank Groups
upper group
1 Multnomah
2 GUliam
3
4
5
6
7
8
9
10
11
12
Lake
Morrow
Hood River
Wasco
Clatsop
Wallowa
Harney
Maiheur
Deschutes
Tillamook
middle group
13 Curry
14 Crook
15 Baker
16 Marion
17 Lane
18 Coos
19 Lincoln
20 Union
21 Josephine
22 Grant
23 Wheeler
23 Yanthill
lower group
25
26
27
28
29
30
31
32
33
34
35
36
Douglas
Sherman
Jefferson
Jackson
Umatilla
Linn
Benton
Kiamath
Columbia
Washington
Clackamas
Polk
Source: County and City Data Book, 1972
$ 2396
2839
767
1630
1850
1511
1708
2017
2106
1048
1649
1649
26
ANALYSIS OF COUNTY RANKING
County rank data for the indicators are of little utility
unless they are examined statistically to determine the degree
of correlation between the availability and development of
agricultural resources and the level of socio-economic affluence.
There are many statistical procedures that can be used to
determine correlation between variables, but for ranked data
within two variables, the Spearman's Rank Correlation
Coefficient r
is most useful.
It is applied when factors
within variables are placed in rank order and because of
complexity, cannot retain numerical values.
15
This is the
case when determining the degree of correlation between the
problem variables.
Ranking the counties within the variables
is probably the most expedient way to make the variables
directly comparable and because of the number of indicators,
the only practical method.
The initial task involved in the utilization of Spearman's
Rank Correlation Coefficient is to derive for each county, an
overall rank for agricultural resources and socio-economic
affluence that is resultant directly from the counties ranks
for each of the indicators ( Table 18 ).
This is accomplished
by aggregating all ranks for all the indicators.
This
synthesis of county ranks are in turn used to rank each
county's position among the counties within each variable.
27
TABLE 18.-- SYNTHESIS OF COUNTY RANKS
County
Baker
Benton
Clackanias
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kiamath
Lake
Lane
Lincoln
Linn
Malheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
of Agricultural
Resource Ranks
Rank
Eof Socio-Economic
Affluence Ranks
Rank
36
201
116
168
260
205
269
186
282
232
287
167
215
189
22
3
15
32
201
61
61
23
33
19
34
30
135
141
153
l68
86
7
36
179
83
163
33
91
177
127
197
132
1
181
126
286
129
136
103
170
120
161
213
209
128
209
231
214
137
238
142
14
28
20
17
6
:
21
9
18
5
35
8
10
2
16
4
13
26
24
93
99
131
139
149
200
121
149
99
133
182
149
121
90
76
132
117
149
24
29
140
123
162
27
85
11
31
12
49
178
146
7
Sourcex compiled by the author
2
2
9
19
22
28
31
5
30
10
16
20
24
35
13
24
10
18
34
24
13
8
4
17
12
24
20
15
29
6
1
32
23
4;]
Spearman's Rank Correlation Coefficient r5= i,..
6
d
n-,-n
where d2 is the square of the difference in rank of the variables,
and n is the number o
co1inies, compares the overall difference
in rank of county ordered pairs.
16
The counties, with their
ranks for agricultural resources and socio-economic affluence
are arranged so their difference of ranks between the variables
can be determined and used in correlational analysis ( Table 19 ).
TABLE 19.-- RANK DIFFERENCES
County
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Agricultural
Resources
d2
196
36
14
3
2
2
9
1
1
13
23
4
11
169
529
15
32
23
33
19
34
30
36
14
28
20
1
17
6
21
9
Lake
Lane
Lincoln
Linn
18
Maiheur
Marion
Morrow
Multnomah
Polk
Sherman
10
Tillaniook
24
Yanthill
d
22
Klainath
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Socio-Economic
Affluence
5
35
8
2
16
4
13
26
7
24
29
27
11
31
12
19
22
28
31
9
3
7
23
33
3
9
2
5
30
10
16
20
24
35
13
24
10
18
34
24
13
10
15
16
121
81
9
529
9
81
4
100
225
3
9
18
14
4
324
196
6
5
17
26
14
11
16
36
25
289
676
196
121
64
4
8
0
17
12
4
14
24
20
15
29
0
0
13
169
9
0
81
1
21
10
441
100
32
23
1
1
11
121
8
6
0
16
196
0
5147
29
Working through Spearman's Rank Correlation Coefficient
,
we find that r5= 1-
,
and r5= .338
Spearman's Rank Correlation Coefficient is a measure of
correlation between one ranked variable and another.
+ 1.0
would indicate perfect positive correlation, where every county
rank for one variable is identical to every county rank for
the other variable.
-1 would indicate perfect negative
correlation and 0 would signify no relationship at all. A
positive coefficient generally indicates that if a county has
a high rank in one variable, it will have a correspondingly
high rank in the other variable.
The same can be stated for
the lower ranked counties if a positive coefficient exists.
17
The question must come up as to the significance of r5= .338.
There must be some cases where correlation of agricultural
The
resources and socio-economic affluence is coincidental.
Spearman's Rank Correlation Coefficient has a critical value
for n=30 at the .05 level of significance of .306
18
For
paired ordered variables numbering greater than thirty, this
critical value decreases slightly.
The test correlation
coefficient, r5= .338 is greater than the critical value for
thirty-six ordered pairs.
With this, it can be safely stated
with 95 percent confidence, that there is a moderately significant
positive correlation between the availability and development
of agricultural resources and the level of socio-economic
affluence of the thirty-six oregon counties.
19
This analysis has shown the level of overall rank correlation
of the counties but not the distribution of correlation.
30
Rank Group Correlation
The distribution of correlation between agricultural
resources and socio-economic affluence of Oregon counties is
determined by analysis of the rank groups which serve as an
index to the county's collective position within the indicators.
Rank groups are generalized to a greater degree than are the
overall county rankings.
It is very difficult to indicate
cartographically the distribution of any factor or phenomena
if there is no solid basis for representation.
For analysis
and mapping to be effected, it is necessary to generalize the
county ranks for the indicators.
This operation requires the
choice of a rank for the agricultural resource variable and
for the socio-economic affluence variable for each county,
so they will be directly comparable.
Each county in Oregon has special and unique physical,
economic, and social qualities which determine the character
of the county.
Some qualities, which are of equal importance
and weight initially, become more salient especially when these
qualities are at the saiie level of development. If a county has
a marked majority of a single rank group among the various
indicators, then that rank group and the measures indicated by
it are the most important in determining the county's level of
agricultural resources and socio-economic affluence ( Table 20 ).
For this part of the investigation it is not the overall ranks
of the counties that are examined but the factors that are the most
influential in determining the comparable socio-economic affluence
characteristics and aggregate quality of the agricultural resources.
31
TABLE 20.-- MAJORITY RANK GROUPS OF OREGON COUNTIES
Socio-Economic Affluence
Agricultural Resources
'c
0)0)
4J4J
0
.r1
4J
Cj
cccl)cçN
0)0
a)
CH0)
0
0
UD
County
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
HoodRiver
Jackson
Jefferson
Josephine
Klamath
Lake
Lane
Lincoln
Linn
Maiheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yarnhill
0J.r1r-C
C0)4JCQr-4'
Z
1321222322
2112112121
3113112133
3233313123
3222213133
2232323233
1321231312
3332233233
3231323233
3223131313
1233131311
2131133232
2311331311
3111211113
2321221223
1311131211
3231113133
2221221211
2321321312
3112112122
3233323233
2113222212
2311121311
1112112122
1233131311
3112211112
1113223222
1123333233
3132312123
1223121211
2222322231
2332333322
1233232321
2113113133
1322332331
1112113122
2
1
1
3
2
3
1
3
3
3
1
3
1
1
2
1
3
2
2
1
3
2
1
1
1
1
2
3
3
1
2
3
2
1
3
1
1 = upper rank group
2 = middle rank group
3 = lower rank group
4
ct
EQ
00
0H0).r.r.1
1
Cl)
Ii
4J1-i0).,-1
CCCCECI
EO-4O00
CflW.r)
3333332
1111113
1111113
2222211
2221323
2133313
2232322
3323312
2321111
3322323
1113131
3113332
2112221
3212321
3221223
1332233
3331332
2122213
3313231
2131113
3222212
3331333
1233231
1331122
2213111
1132111
1231223
1213133
1323321
2222221
3112132
3313131
2112221
1111113
1323332
2231222
0
0
3
1
1
2
2
3
2
3
1
3
1
3
2
2
2
3
3
2
3
1
2
3
3
1
1
1
2
3
3
2
1
3
2
1
3
2
32
Agricultural Resources
Agricultural resources are available and developed in some
Oregon counties but are absent or at a low level in others
because of differences in the physical and economic characteristics
among the counties.
Economic and physical factors interact
complexly and determine the level to which agricultural resources
of a county unit can be developed.
Resources within each county
are not uniformly distributed throughout the unit and often
an intense concentration of agricultural development constitutes
the entire agricultural resource base for the county.
The counties
represented by rank groups are averaged so the factors of area,
magnitude of production, and concentrations of development are
removed, so measurement is dependent upon the factors that
determine the agricultural character of the county.
Oregon has specific agricultural regions including; the
Coast, the Willamette Valley, the Blue Mountains, the Columbia
River Basin, South Central and Southern Oregon.
Each of these
regions are classified by geomorphic type, topography, climate,
soils and other factors and each has a different type of
agricultural resource base° Many of the counties classified in
rank groups are adjacent and this suggests regionality of
resources based on levels of availability and development
( Fig. 1
)
The counties of the Willainette Valley rank in the upper
group
in availability and development of resources with the
exception of Polk and Linn Counties.
These two counties rank
high in magnitude of gross sales of production, but each has
p
a
''l's'
I.
-
p
I-
,
- 5
-
S
-
S
S
I
-
-
S
.-
S
I
-
S
S
34
many small commercial farms, so the production, sales, and
development per average county farm is rather low giving a
low rank to a majority of indicators and thus is placed in a
low rank group.21 For parts of these counties, development
may be intensive but for the most part it is not, so Polk and
Linn Counties are relegated to the middle rank group.
The remainder of the Willamette Valley counties including;
Multnomah, Washington, Yamhill, Clackamas, Marion, Benton and
Lane have a marked majority of the upper rank group among the
indicators, because they rank high in cropland, harvested
cropland, crop return, utilization of grazing land and farm
acre values. Other indicators are noted but are not as important
in determining the counties relative worth.
Valley counties
rank low in irrigation, percent of class I farms and sales
and equipment value per average county farm.
Irrigation is
dependent upon climate and in many cases, it is not required
for valley counties except for crops that require supplemental
irrigation.
The valley counties have many commercial farms
but a relative low percent of superfarms as compared to other
areas of the state and this is indicated by average county
farm sales. Willamette Valley farms tend to be small and this
is reflected by low levels of equipment value except for
Benton County which is the highest of the Valley counties.
The counties of the Oregon Coast including; Clatsop,
Tillamook, Lincoln, Coos, and Curry are deficient in availability
and development of agricultural resources and this is indicated
by a low rank group for every county.
Each of these counties
35
has a low rank for almost every indicator and this can be
expected because agriculture is not the principal industry
of this region.
Agricultural resources are not available in
the coastal counties and this strongly affects any degree of
development.
The Columbia River Basin in Oregon includes Wasco, Sherman,
Hood River, Umatilla, Gilliarn, and Morrow Counties.
Umatilla,
Gilliam, and Morrow Counties have consistently high rankings
in many indicators including farmland, crop return, class I
farms, and farm sales and equipment value per average county
farm, and are placed in the upper rank group.
These counties
are ranked low in irrigated land and acre values but this is
a function of the agricultural type (dry cropping) which is
extensive.
Hood River County is totally dissimilar from the
other Columbia Basin counties.
Farmland available is less than
eight percent of the area of the county.
Land that is available
for agriculture is highly developed with high percentages of
the farmland being cropped and harvested.
Hood River County
has high rankings in a majority of indicators and is placed in
the upper rank group on the basis of utilization, class I farms,
sales and acre values, as well as cropland and harvested cropland.
Wasco County is developed to a more restricted level than the
other counties and has a majority of ranks in the middle group.
Wasco County has high ranks in resource availability, but low
ranks in development.
Sherman County is deficient in all
indicators except farmland and cropland which indicates that
the resources that are available and utilized, are at a low
36
level of development.
The counties of the Blue Mountains agricultural region are
in the middle and lower rank groups.
Wheeler, Wallowa, and
Grant Counties are placed in the lower rank group because of
low rankings in harvested cropland, which indicates that much
of the cropland is used for grazing purposes with a lower return
per acre than can be derived from a crop, utilization of
grazing land, farm sales and acre values per average county
farm, and percent of class I farms.
Baker and Union Counties
are slightly higher in these respects with nearly all of their
indicators in the middle rank group.
The central Oregon counties of Jefferson and Crook are
placed in the upper rank group because of high rankings in
all indicators except cropland and acre values. Deschutes
County is an island of low ranking surrounded by higher
ranked counties.
Deschutes County's physical resources are
limited and this is reflected by low ranking in all indicators
except irrigated land.
The counties of southern Oregon are represented by all
rank groups.
Jackson, Klamath and Lake Counties have high
rankings in irrigated land but are placed in the middle rank
group because of deficiency in availability and development
of the county resources as a whole.
These counties have
highly developed concentrations of agricultural enterprise
which support the remainder of the county.
Douglas County
is placed in the lower rank group because of low rankings in
available farmland, irrigated land, acre values and equipment
37
values.
Josephine County, in the lower rank group, has much
of the same agricultural character as the coastal counties.
Malheur and Harney Counties are in the upper rank group
based on high rankings in harvested cropland, irrigated land,
class I farms, and sales and equipment value per average
county farm.
For these two counties, ranking is high in all
areas except the percent of county in farmland and acre values
per average county farm, which shows that where resources are
available, they are well developed.
The counties arranged in rank groups often conform to
the established agricultural regions.
The distribution of
group ranked agricultural resources indicates diversity
among the counties where differences are a consequence of
availability and development and not county size or magnitude
of production.
Socio-Economic Affluence
The distribution of socio-economic affluence rank groups
suggests only a limited measure of regionality as compared to
agricultural resources C Fig. 2 ).
Urbanized or metropolitan
counties including Multnomah, Washington, Clackamas, Marion,
Benton, Lane and Deschutes Counties are assigned to the upper
rank group based on a majority of high ranks for the indicators:
unemployment, migration, education, and income.
Gilliam,
Morrow, and Union Counties have consistently high rankings in
poverty level, welfare, education and bank deposits and are
included in the upper group.
N
SOC 10-ECONOMIC
AFFLUENCE
.
................]
........u.u...uu I
I................ I
I.
middle rank
group
.
Scale 1:4000000
.1
lower rank
0
50
group
Fig. 2 Distribution of Socio-Economic Affluence by
Group Ranked Oregon Counties
100 mi.
39
The remaining twenty-six Oregon counties have no specific
distribution pattern and are placed in the middle and lower
rank groups. These counties have various factors that combine
in sufficient strength to place them in ranks that are not at
the most optimum level of socio-economic affluence.
Each of
these counties has upper group ranks in only a limited number
of indicators, and show marked majorities in the middle and
lower rank groups.
For the counties in the lower and middle
groups, deficiency in education level, migration, and a
significant degree of welfare recipients contribute to low
rankings, with unemployment also being a contributing factor.
Socio-economic affluence cannot be controlled by income
or county production only.
The desired result to be derived
for the socio-economic variable is the character of the county,
socially and economically, as a product of many factors and
not only one or a few.
Correlations of Rank Groups
In correlational analysis of the rank groups it is most
evident that there are strong positive correlations in
western Oregon counties. Central and eastern counties cor-
relate positively in only seven instances ( Fig. 3 ).
Among the upper rank group counties, there are eight
perfect positive correlations and these include: Benton,
Clackamas, Lane, Marion, Muitnomab, Washington, Morrow, and
Gilliam.
These counties are located in the Willamette Valley
except Morrow and Gilliam which are in the wheat growing
40
Scale 1:4000000
positive
0
50
100 mi.
correlations
Fig. 3
Distribution of Oregon County Rank Group Correlation
41
region of the Columbia River Basin.
Five counties correlate positively in the middle rank
group and these include: Columbia, Wasco, Jackson, Kiarnath, and
Polk.
For the lower rank group many perfect positive correlations
can be seen between the variables.
Correlations of these
counties includes: Coos, Curry, Douglas, Grant, Josephine,
Sherman, Tillamook, Wallowa, and Wheeler.
These counties are
located in northeast Oregon and in the vacinity of the coast.
It can be noted that for all the counties in Oregon that
do not correlate perfectly, there are many partial or near
correlations between the rank groups.
This indicates a county
may be ranked in the upper group for agricultural resources
and in the middle group for socio-econornic affluence; or a
county may be in the middle group for agricultural resources
and in the lower group for socio-economic affluence, and so on.
Only Jefferson, Malheur, and Deschutes Counties correlate
negatively. This can be attributed to major discrepencies
between the level of availability and development of agricultural
resources and levels of socio-economic affluence for those
counties. Jefferson and Maiheur Counties have relatively
high degrees of poverty, a substantial rate of out-migration,
low educational lecel compared to other counties, and low
per capita incomes.
At the same time, Jefferson and Maiheur
are highly developed where agricultural land is available and
rank among the top ten in sales of county agricultural products.
Deschutes county has a low level of agricultural availability
and development, but a viable degree of development socially
42
and economically including a high rate of in-migration, a
large percentage of persons over twenty-five years old with
twelve or more years of education, and a considerable measure
of per capita personal income and bank deposits.
Of Oregon's
thirty-six counties, twenty-two or 61.1 percent correlate
positively within the majority rank groups; eleven or 30.5
percent correlate partially; and only three counties or 8.33
percent have negative correlations.
CONCLUS ION
It is beyond the scope of this problem to formulate
exacting explanations why correlations exist and why they
do not.
There is an inordinate number of factors that were
not measures and cannot be assessed and successfully weighed.
The forms of correlational analysis employed have been adapted
from procedures designed to survey a reduced number of factors
than have been incorporated within the scope of this problem.
This investigation has revealed some interesting and
unexpected results.
It cannot be asserted that high levels
of agricultural resource availability and development will
guarantee a viable degree of socio-economic affluence, although
this is manifested for the urban counties.
There are too
many other factors involved that contribute to the measure
of socio-econornic affluence.
If the counties with deficient availability and development
43
of agricultural resources are well endowed with other resources
and industries, the counties should have a substantial degree
of socio-economic affluence if those resources and industries
are well developed, but for the most part, this is not the case.
One-fourth of all Oregon counties are deficient in viable
levels of socio-economic affluence and simultaneously have
only limited agricultural resources.
In light of this, it
can be significantly implied that diminutive measures of
socio-economic affluence of Oregon counties directly reflect
deficiency in the availability and development of agricultural
resources.
44
FOOTNOTES
1
R. 0. Coopedge, Agriculture 1980- A Projection for Oregon,
Special Report 313, Agricultural Experiment Station,
Oregon State University, Corvallis, Oregon
,
December 1970,
p. 1.
2
Agriculture in Oregon Counties- Sales and General Characteristics, Special Report 330, Cooperative Extension Service,
Oregon State University, Corvallis, Oregon, June 1971, p. 1.
3
J. R. Tarrant, Agricultural Geography, ( Plymouth, England:
David and Charles Ltd., 1974), pp. 12-13.
4
Socio-Economic Indicators, Speak Out, ( Fort Collins, Colorado:
Colorado State University Division of Continuing Education,
November 1967 ), pp. 4-5.
5
See Appendix III. This information is derived from the 1969
Census of Agriculture, for class I-V farms.
6
N. Ginsberg, "Natural Resources and Economic Development,"
Annals, Association of American Geographers, Vol. 47 (1957),
p. 198.
7
County area as a factor is to be removed so the counties
will be directly comparable.
A. H. Robinson,
" The Necessity
of Weighting Values in Correlation Analysis of Areal Data,"
Annals, Association of American Geographers, Vol. 46 (1956),
p. 233, demonstrated that weighting by county area must be
implemented in correlational analysis. Robinson employed only
a very limited number of variables in their areal study, so
weighting was necessary.
For analysis of many varying
indicators, weighting is not feasable or desired.
45
8
All factors must have equal weight as there is no useable
proceedure for weighting all indicators successfully.
R. M. Highsmith, Atlas of Oregon Agriculture, (Corvallis,
Oregon: Oregon State College, 1958), PP. 16-22 served as
a basis for selection of part of the agricultural resource
indicators.
9
These indicators are obtainable direct-ly from: Bureau
of the Census, 1970 Census of Population, and County and
City Data Book,(1972).
10
Average county farm information is available directly
from the 1969 Census of Agriculture for all Oregon counties.
11
Socio-Economic Indicators, op. cit., footnote 4, p. 5.
The authors list socio-economic indicators only and make
no attempt at analysis of any type.
12
The percentage of class I farms of all farms and their
value of production is derived from 1969 Census
13
Agriculture.
Oregon Conservation Needs Inventory Committee, Oregon Soil
and Water Conservation Needs Inventory, USDA Soil Conservation
Service, Agricultural Stabilization and Conservation Service,
Extension Service, Oregon State University,(l972), p. 8.
14
See Appendix II for county population changes, 1960 to 1970.
15
J. Madge, The Tools of Social Science, ( London: Longmans
Green and Co., 1957), pp. 74-75.
16
5. Szulec, Statistical Methods,
1965), pp.49O-49l.
( Oxford: Pergamon Press,
46
17
P. J. McCarthy, Introduction to Statistical Reasoning,
(New York: McGraw-Hill, 1957), pp. 380-381.
18
E. G. Olds, "The 5% Significance Levels of Sums of Squares
of Rank Differences and Correlation," Annals of Mathematical
Statistics, Vol. 29 (1949), p. 117.
19
R. Hammond and P. McCullagh, Quantative Techniques in
Geography, (Oxford: Clarendon Press, 1974), pp.198-199.
20
School of Agriculture, Oregon State College, An Analysis
of Oregon Agriculture, (Corvallis, Oregon:
1947), Vol. 1,
p. 7.
21
See Appendix III for rankings of counties for sales of
production
0
(0
C
o
rr1
:iz
rt
.4:..
APPENDIX II
County
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Kiamath
Lake
Lane
Lincoln
Linn
Maiheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yarnhill
Area Sq. Mi.
3068
668
1884
805
639
1604
2975
1627
3031
5063
1208
4530
10166
523
2812
1793
1625
5970
8231
4552
986
2283
9859
1166
2060
423
736
830
1115
3227
2032
3178
2381
716
1707
711
1970 Population
14919
53776
166088
28473
28790
56515
9985
13006
30442
71743
2342
6996
7215
13187
94533
8548
35746
50021
6343
213358
25755
71914
23169
151309
4465
556667
35349
2139
17930
44923
19377
6247
20133
157920
1849
40213
Source: 1970 Census of Population.
1960 Population
17295
39165
113038
27380
22379
54955
9430
13983
23100
68458
3069
7726
6744
13395
73962
7130
29917
47475
7158
162890
24635
58867
22764
120888
4871
522813
26523
2446
18955
44352
18180
7102
20205
92237
2722
32478
49
APPENDIX III
County
Agricultural Product
Millions of Dollars
Baker
Bent on
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
Hood River
Jackson
Jefferson
Josephine
Klainath
1
2
3
4
5
6
7
8
9
10
11
12
Umatilla
Marion
Malheur
Clackamas
Linn
Klamath
Washington
Lane
Jefferson
Yanthill
Jackson
Polk
11.75
7.89
31.47
1.98
4.17
7.29
9.06
2.50
6.37
7.65
6.38
6.52
8.12
12.70
17.33
19.27
3.95
27.05
County
Agricultural Product
Millions of Dollars
8.26
20.78
1.59
30.66
42.79
46.31
9.42
12.89
13.93
4.70
8.67
53.87
11.48
8.10
10.89
22.54
2.33
17.98
Lake
Lane
Lincoln
Linn
Malheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yarnhill
Ranking of Counties
13 Multnomah
14 Hood River
15 Baker
16 Union
17
Wasco
18 Morrow
19 Crook
20 Tillamook
21
Lake
22 Harney
23 Wallowa
24 Benton
Source: 1969 Census of Agriculture
25
26
27
28
29
30
31
32
33
34
35
36
Douglas
Coos
Grant
Gilliam
Deschutes
Sherman
Columbia
Josephine
Curry
Wheeler
Lincoln
Clatsop
50
BIBLIOGRAPHY
Agriculture in Oregon Counties-Farm Sales and General Characteristics, Special Report 330, (Corvallis, Oregon: Cooperative
Extension Service, Oregon State University, June 1971).
Bell, George, editor, Oregon Blue Book,(Salem, Oregon: Clay Meyers,
Secretary of State, 1970).
Bureau of the Census, 1969 Census of Agriculture, Vol. 1, Part 47,
Oregon, (Washington,D. C.: United States Department of
Coriuiierce, Social and Economic Statistics Administration).
1970 Census of Population, Characteristics of the Population,
United States
Vol. 1, Part 39, Oregon, (Washington, D. C.
Department of Commerce, Social and Economic Statistics
Administration).
:
United States
County and City Data Book, (Washington, D. C.
Department of Commerce, Social and Economic Statistics
Administration, 1972).
:
Connor, L. S., Statistics in Theory and Practice, (London: Sir
Isaac Pitman and Sons Ltd., 1938TT383 pp.
Coopedge, Robert 0., Agriculture 1980-A Pro.jection for Oregon,
Special Report 313, (Corvallis, Oregon: Agricultural
Experiment Station, Oregon State University, December 1970).
DuBois, Phillip H., Multivariate Correlational Analysis, (New York:
Harper and Brothers, 1957), 202 pp.
Ginsberg, Norton, "Natural Resources and Economic Development,"
Annals, Association of American Geographers, Vol. 47 (1957)
pp. 197-208.
Gregor, Howard F., Geography of Agriculture-Themes in Research,
Prentice Hall, Inc., 1970), 181 pp.
(Englewood Cliffs, N. J.
:
Hammond, R. and P. S. McCullagh, Quantative Techniques in
Geography, (Oxford: Clarendon Press, 1974), 318 pp.
Highsmith, Richard M., Atlas of Oregon Agriculture, (Corvallis,
Oregon: Agricultural Experiment Station, Oregon State
College, 1958), 43 pp.
Atlas of the Pacific Northwest, (Corvallis, Oregon: OSU Press,
1973), 128 pp.
Keyserling, Leon H., Agriculture and the Public Interest,
(Washington, D. C.: Conference on Economic Progress,
February 1965), 123 pp.
51
Madge, John, The Tools of Social Science, (London: Longmans, Green
and Co.,1957), 308 pp.
McCarthy, Phillip J., Introduction to Statistical Reasoning,
(NewYork: McGraw-Hill, 1957), 401 pp.
Olds, E. G., "The 5% Significance Levels of Sums of Squares of
Rank Differences and Correlation," Annals of Mathematical
Statistics, Vol. 20 (1949), pp. 115-121.
Oregon Conservation Needs Inventory Committee, Oregon Soil and
Water Conservation Needs, ( USDA, SCS, ASCS and Extension
Service, Oregon State University, 1972).
Robinson, A. H., "A Method for Describing Quantatively the
Correspondence of Geographical Distributions," Annals,
Association of American Geographers, Vol. 47 (1957), 379-392.
"The Necessity of Weighting Values in Correlation Analysis
of Areal Data," Annals, Association of American Geographers,
Vol. 46 (1956), 233-236.
School of Agriculture, An Analysis of Oregon Agriculture, Vol. 1
(1947),(Corvallis, Oregon: Oregon State College Press, 1947).
Socio-Economic Indicators, Speak cAit, (Fort Collins, Colorado:
Division of Continuing Education, November 1967), 2Opp.
Swidder, H. D. and E. B. Hurd, Graphic Summary of Agriculture
and Land Use in Oregon, Station Circular 114,(Corvallis,
Oregon: Agricultural Experiment Station, Oregon Agricultural
College, December 1935).
Szulec, Stefan, Statistical Methods, (Oxford: Perganion Press,
1965), 666pp.
Tarrent, John R., Agricultural Geography, (Plymouth, England:
David and Charles Ltd., 1974), 279 pp.