5'1 iii.'.ICENTRAL ALASKA EMPLOYMENT AND POPULATION FORECASTS: AILOCATION BY CENSUS DISTRICT

-fore/:a.~sts of population and empl~yment for the Anchorage area and

th.e ,e-sf of Southcentral Alaska were provided by the MAP regional model

+hrouah \990 and extended to the year 2000. It was necessary to disag-

3ra~o~ ihe results of those forecasts by smaller areas, i.e., census

d'1 V j,; Io !\S' , This discussion describes the methodology through which this

d i~a%ire~ci-/::ion was accomplished. Seven census districts were involved:

~Cho~ e-~-Matanuska--Susitna, Kenai-Cook Inlet, Seward, Valdez-Chitina­

W~H+ \ e.r) Ko<liak, and Cordova-McCarthy.

Funcfarn ,?.ntal to the process was the dichotomy between "basic" and

llnon- ba.s/cn employment . . For the present pttrposes, basic employment was

dQ~1~tc9 S'Omewha t arbitrarily as: (1) agriculture, fores try and fisheries;

c~) MIN i'n[j (3) man u.fa cturing; (lf) construction; and (5) federal govern-

1\\ en-t (QXC?.e.pt military). All historic employment and population estimates

u.+l \ ·l 1,QJ were provided by the Alaska Department of Labor, Research and

Anal ys \ s -:c,e tion.

8c:Y,5 i c.,c0 l ly, the me thodology utilized involved a six-step process:

(I) i:-d.iust Va ldez baseline population. Some hypothetical estimate

~.:: "stable" or "natural" population and employment in Valdez

~as necessary to isolate the short-term effects of pipeline

:c.o, ::; t:cuct:i.on.

(~ A ~_()_c:.'.:t e. ba sic employNent. Increments in basic employment sec­

t.c < : were alloca te d according to historical trends and the

;)~':7 ·w1ed location of major developments.

-2-

(3) Allocate non-basic employment. Non-basic employment was allo­

cated to all census divisions (except Anchorage and Matanuska­

Susitna) baHed on historical basic/non-basic ratios. Remaining

non-basic employment was assigned jointly to Anchorage and

Mat-Su.

(4) Allocate civilian population. Population was assigned on the

basis of historical population/employment ratios.

(5) Separate Anchorage and Mat~Su employment and population. Be­

cause of their special relationship, population and employment

for these two census divisions were combined, but finally

separated using special procedures.

(6) Add military employment and population. Military population

was estimated on the basis of recent experience and held constant.

Step 1: Adjustment of Valdez-Chitina-Whittier Census Division Baseline Data

Forecasts of population and employment levels for the Valdez area are

hampered by the extreme shifts that have resulted from pipeline activity.

To obtain. useful baseline estimates of "real" or "stable" levels of employ­

ment and population, corrections must be made to compensate for temporary

short-term effects of pipeline activity without eliminating more stable

long-term influences. Unfortunately, there is little data available con­

cerning post-pipeline economic activity and population levels in the Valdez

area.

A possible approach would be to use pre-pipeline employment and popu­

lation levels as a baseline. However, it does not seem reasonable that

economic activity or population in the Valdez area would revert to

-3-

pre-pipeline levels in the near future. For one thing, a force of about

500 is employed for Alyeska terminal and pipeline operations, and this

workforce is expected to remain relatively constant in the future. 1 More­

over, it seems fairly safe to assume that structural changes have occurred

which have had a qualitative effect on the local economy.

The procedure utilized here to derive a hypothetical measure of

"stable" or "real 11 employment and population involved the use of regression

analysis and the following process: (1) the relationship between various

employment segments and total employment and between total employment and

population were identified through regression analysis; (2) assumed levels

of basic employment segments were input into the equations to derive esti-

mates of total employment and population.

Two different basic employment groups were analyzed to determine

the best estimator of total employment: total construction employment and

basic employment (construction; manufacturing; agriculture, fishing, and

forestry; and federal government). The historical data is shown in the

table on the following page. Regressions were run using annual average

employment and mid-year population estimates for seven years. The fit of

all equations was very high, but all population or employment variables

had very low values before pipeline construction and very high ones once

construction started and high correlations would be expected. Since the

dominant changes are of large magnitude and in the same direction, normal

1Telephone conversation with Andy Ooms, Manager, Labor Relations and Affirmative Action Program, Alyeska Pipeline Service Company.

-4-

VALDEZ-CHITINA-iffiITTIER CENSUS DIVISION BASIC AND CONSTRUCTION EMPLOYMENT

Basic Employment Construction Year & Total % of % of Quarter Population Employment No. Total No. Total

Annual Average

1970 3,098 831 101 12.2 21 2.5

1971 2,949 1,085 388 35.7 222 20.5

1972 3,487 905 132 14.6 73 8.1

1973 3,568 984 189 19.2 69 7.0

1974 3,833 1,526 459 30.1 399 26.1

1975 9,639 4,633 2,597 56.1 2,518 54.3

1976 13,000 7,818 5,492 70.2 5,414 69.3

Quarterly Average

1974-1 842 87 10.3 38 4.5 -2 1,180 163 13.8 147 12.5 -3 1,787 553 30.9 492 27.5 -4 2,297 992 43.2 919 40.0

1975-1 2,871 1,446 50.4 1,375 47.8 -2 3,910 1,884 48.2 1,816 46.4 -3 4,809 2,537 52.8 2,434 50.6 -4 6,916 4,522 65.4 4,447 64.3

1976-1 6,659 4,388 65.9 4,330 65.0 -2 8,558 6,232 72.8 6,152 71.9 -3 9,240 6,802 73.6 6,704 72. 6 -4 6,814 4,541 66.6 4,472 65.6

1977-1 5,006 3,057 61.1 2,992 59.8 -2 5,455 3,290 60.3 3,231 59.3 -3 N/A N/A N/A -4 N/A N/A N/A

-5-

fluctuations are swamped. It was hypothesized that structural changes

occurred with pipeline construction; regressions run on more recent data

would thus be expected to better reflect the current structure of the

local economy. Quarterly data from 1974 to mid-1977 (fourteen quarters)

was utilized in deriving the estimating equations. Since population esti­

mates were not available on a quarterly basis, population for the second

and third quarters of each year was assumed to equal the mid-year estimate

for that year; population figures for other quarters were interpolations.

The results of the equations are shown in the table on the following

page. Alyeska employment was apparently a poor estimator of other employ-

. ment (r 2=.30); construction employment was a better estimator of non­

construction employment; and basic employment was the best estimator of

derived employment (r 2=.78). Total employment was a very good estimator

of population (r 2=.90); multivariate equations using basic and non-basic

as well as construction and non-construction independent variables ex­

plained a little more of the population variance, but improvement as an

estimator is somewhat problematical because of the collinearity of the

independent variables.

Estimates of "stable" employment were made by inserting appropriate

assumed values of basic employment into the equations. Assumptions were:

(1) Alyeska employment equals 500 non-construction operations

personnel;

(2) construction employment equals 100, the average during the nine

pre-pipeline years (1965-1973); and

Basis

Employment Equations

1. Construction Employment

2. Basic Employment

Population Equations

1. Total Employment

2. Construction Employment

3. Basic Employment

VALDEZ-CHITINA-WHITTIER CENSUS DIVISION: HYPOTHETICAL "STABLE" EMPLOYMENT AND POPULATION

Equation

Derived Employment=

1,347 + .2135 X

Const. Employment

1,175 + .2320 X

Basic Employment

Derived Po£ulation =

3,225 + 1.1856 X

Employment

989 + .7064 x Const. Employment+ 3.047 x Other Employment

1,028 + .7137 x Basic Empl. + 3.1145 x Employment

r2 (adj. r 2)

.67 (.64)

.78 (.75)

.91 (.90)

.94 (.93)

• 94 (.93)

Assumptions

Const. Empl. = (a) 100 (b) 600

Basic Employ. = 75 Const. Empl. = (a) 100

(Basic) (b) 600

Employment= (a) 2,007 (b) 2, 075-

Const. Empl. = 600 Other = 1,475

Basic Empl. = 675 Other = 1,332

Employment Derived Total

(a) 1,368 (a) 1,468 (b) 1,475 (b) 2,075

(a) 1,216 (a) 1,391 (b) 1,332 (b) 2,007

Total Po£ulation

(a) 5,604 (b) 5,685

5,907

5,658

I .(J"\ I

-7-

(3) other basic employment equals 75, the approximate amount in

1976.

A problem arises because of the fact that Alyeska employment is not con­

struction and by our definition is not basic. However, not including

Alyeska employment in the independent variable produces estimates that are

artificially low. In any case, Alyeska employment should be considered

as basic despite the arbitrariness of our defirtition. The basic employ­

ment equation appears to be the best estimator of total employment, and

the employment estimate of about 2,000 (2,007) appears reasonable. Based

on this figure, a population estimate of about 5,600 (5,604-5,685) was

derived.

Stable employment of about 2,000 and population of about 5,600 appears

reasonable when compared to data from 1975, the year in which basic employ­

ment was closest to the assumed stable value of 675, as shown in the table

below. Based on 1975 ratios, total employment would be slightly higher,

but population would be slightly lower. Inserting the higher figure for

total employment into the population equation ("hybrid" estimate) still

only produces a total population of less than 5,900.

VALDEZ-CHITINA-WHITTIER POPULATION ESTIMATES

Hybrid-1975 Basic/other Preferred

1975 1975 Employment Regression Actual Ratios Ratio Equations

Basic employment 459 675 675 675

Total Employment 1,526 2, 21+4 2,244 2,007

Population 3,833 5,512 5,885 5,604

-8-

Step 2: Allocation of Basic Employment to Census Divisions

The MAP regional model provides a forecast for Anchorage and another

for the remainder of the Southcentral region. While the model underesti­

mates the shift of population and supportive economic activity from

Anchorage to the Matanuska-Susitna valleys (see discussion of Step 5),

this is not an important problem for the basic industries, since the

"basic" sectors are exogenous inputs to the model and can be locationally

identified.

Allocations of basic employment to other census divisions in the

Southcentral region were made on the basis of historical patterns and

assumptions concerning the probable location of major industrial projects.

Disclosure rules prohibit the publication of some data, but the distribu­

tion of basic employment in 1970, 1973, and 1976 is shown in the table on

the next page and historical trends are discussed briefly below:

(1) Agriculture, forestry and fisheries. Self-employed workers are

not included in any data but are a particularly important com­

ponent of these industries. Moreover, the 1970 data for these

industries is not reliable because very few employees were

covered by unemployment insurance, the source of the statistics.

Most of the employment in 1973 and 1976 was in Kodiak, although

there were relatively large numbers in the Kenai and Cordova

census divisions.

(2) Mining. Mining employment (petroleum-related) is heavily con­

centrated in the Kenai area. Employment there dropped by one­

half between 1968 and 1971 but has been increasing somewhat in

-9-

DISTRIBUTION OF BASIC EMPLOYMENT 1970-1976 BY CENSUS DIVISION

% of Southcentral Region (excl. Anchorage)

Agriculture, Fisheries, Forestry 1970

Mining

Construction

Manufacturing

Federal Govt.

1973 1976

1970 1973 1976

1970 1973 1976*

1970 1973 1976

1970 1973 1976

Agriculture, Fisheries, Forestry

Mining

Construction'~

Manufacturing

Federal Govt.

Kodiak Cordova Seward Mat-Su Kenai Valdez*

42.6 57.8 67.3

.7

7.9 19.1 15.3

45.1 60.0 50.l

51.1 46.0 43.5

+384

5

+207

+896

-109

9.9 14.3

11.1 9.1 7.0

6.4 3.2 1.5

12.1 10.8

8.8

5.3 5.9 5.8

+87

-27

-13

+89

- 3

47.5 7.6 4.4

1. 7 2.3

.3 3.2

.5

4.5 11. 0 10.4

5.5 6.5 9.2

8.2 2.5 1.8

2.1 1.9

.4

20.7 14.3 12.6

2.1 .5 .9

14.0 18.7 20.2

Change 1970-1976

2

+ 19

+ 6

+267

+ 17

+ 6

-13

+88

- 5

+23

1. 6 20.6 11.5

85.5 86.7 89.8

61.0 50.1 64.1

35.4 26.6 29.3

15.7 14.0 12.8

+ 69

+ 89

+704

+376

- 37

1.6 .7

• 7 .6 .5

3.6 10.1

6.1

.8 2.5

.5

8.3 8.9 8.5

+ 4

- 1

+19

+ 2

- 9

*Valdez 1976 construction employment assumed to equal 100 - see discussion of "Step l" (actual number was 5,415, an increase of 5,394 over 1970).

-10~

recent years. Mining employment is also significant in the

Cordova census division.but is primarily non-petroleum related.

(3) Construction. Employment in this industry is extremely volatile

and was most important in the Kenai, Mat-Su, and Kodiak census

divisions and in Valdez during pipeline construction. Trends

in construction employment closely paralleled those of other

industries in Kenai and Kodiak: fish processing and federal

government in Kodiak and the petroleum industry in Kenai.

(4) Manufacturing. Fish processing is a very big industry in Kodiak

and also in the Kenai census district, where it accounts for

nearly 50 percent of manufacturing employment. It is also im­

portant in the Cordova and Seward areas. There was a sizeable

amount of employment in the Valdez census district in one year

only (1973), which is characteristic of the extreme fluctuations

of the industry. Fish processing employment was at a long-term

peak in 1976 in every census division where the industry was

important: Kodiak, Kenai, Seward, and Cordova.

Lumber products employment was particularly important in

the Kenai census district and also in Seward. There has also

been, in recent years, sizeable lumber products employment in

Kodiak, Up until its peak in 1971, lumber products employment

was also fairly important in the Mat-Su area. Now, most Mat-Su

timber is processed in Seward. Employment peaked in general in

1976, but the industry was on a tenuous footing in 1977 because

of a weakening of the market and because of the difficulty in

-11-

obtaining an adequate supply of timber. The new mill at Tyonek

closed for these reasons.

The petrochemical complex (petroleum refining and chemical

processing) concentrated near the city of Kenai (and accounting

for over one-third of the census district's manufacturing em­

ployment) was the only other manufacturing industry of note.

Employment in that industry increased about 50 percent between

1973 and 1976.

(5) Federal government (civilian). Nearly half of federal employment

in the region was in Kodiak and involved civilian jobs associated

primarily with the Coast Guard (formerly Navy) base on the island.

Much of the federal employment in the rest of the region is asso­

ciated with military or Coast Guard operations. Cutbacks in

these operations have been the cause of federal civilian employ­

ment declines in Kodiak and Kenai. Federal employment in the

Mat-Su division is fairly important and appears unrelated to

military activities but rather a result of Alaska Railroad and

other civilian operations (agriculture, FAA).

Step 3: Allocation of Total Civilian Employment

Once basic employment has been allocated to the census divisions, it

is possible to distribute other employment through the use of basis/non­

basic employment multipliers appropriate to the industries and locations

involved. Unfortunately, not enough is known about specific local factors

and employment interrelationships to accomplish this in a detailed fashion,

and it is necessary to rely on gross relationships between basic and

-12-

non-basic sectors in a given census division. Moreover, this relation­

ship is rather unstable and has fluctuated considerably from one census

division to another and from one time period to another in a given locale

(see table on following page). Some of the problems involve inadequacies

in our definition of basic and non-basic industries, i.e., some specific

industries are actually "basic" but are not categorized as such here, and

vice versa.

The aggregate trend in the Southcentral region has been toward a

higher ratio of total employment to- basic employment. This pattern is·

definite only in the Anchorage and Matanuska-Susitna census divisions.

It is not so apparent in the other census divisions, however, and the

opposite pattern is quite evident in the case of Seward and Valdez •. The

problem with both of these areas is that, initially, there was very little

employment that was classified as basic according to our definition, al­

though much of other employment was functionally 11basic 11 (e.g., hospitals

and nursing homes, Alaska Skill Center, etc.). During the 1970s, some

industries that were defined as basic expanded signific·antly (pipeline

construction in Valdez, lumber and fish processing in Seward).

The very low proportion of basic employment found in the Matanuska­

Susitna census division can be explained by the fact that population and

non-basic employment in the area is more a function of Anchorage employ­

ment and population rather than indigenous basic employment. For this

reason, the Anchorage and Matanuska-Susitna census divisions are treated

-as a single unit; population and employment for the two areas are only

separated at the end, using the special procedures outlined in Step 5.

BASIC EMPLOYMENT: PERCENT OF TOTAL EMPLOYMENT

Total Kenai,

Total Combined Valdez- Kenai- Seward, South- Matanuska- Anchorage/ Chitina- Cook Cordova- Cordova, central Anchora~ Susitna Mat-Su Whittier Inlet Seward McCarthy Kodiak Kodiak

1968 41.7 39.1 23.9 38.7 12.9 61. 7 24.2 50.6 56.8 56.6

1969 38.6 36.7 23.7 36.4 19.2 55.6 22.8 54.2 51.3 51.5

1970 36.7 35.8 24.5 35.5 12.3 47.8 21.4 51.6 48,9 46.1

1971 35.1 34.2 24.9 33.9 26.5 45.5 25.4 46.9 46.0 43.7

1972 33.8 32.8 18.0 32.3 14.6 43.3 30.6 47.4 50.5 44.9 I I'--' w

1973 33.2 31.4 14.9 30.8 19.4 42.0 37.1 47.2 57.8 48.1 I

1974 32.9 31.2 16.6 30.8 30.1 40.9 38.9 41.4 55.1 45.9

1975 32.5 29.1 18.0 28 •. 8 56.1 43.5 39.3 44.2 53.8 46.5

1976 34.1 28.1 16.7 27.8 70.2 45.3 40.0 47.6 57.8 49.3

Average of 1970-76 Ratios 34.0 31.8 19.1 31.4 32.7 44.0 33.2 46.6 52.8 46.4

-14-

The low proportion of basic employment in the Anchorage census divi­

sion indicates that the Anchorage area is capturing a proportion of deri­

vative employment from expansions of basic sectors in other areas of the

Southcentral region (as well as in other parts of the state). Because

of this phenomenon, the following procedure was utilized to ·distribute

total employment:

(1) Incremental basic employment was multiplied by a factor of 2.2

to calculate total employment (i.e., basic employment increases

were assumed to equal 45 percent of total employment increases)

and added to the baseline employment for the following census

divisions:

(a) Valdez-Chitina-ivhittier (baseline employment = "stable"

employment; see Step 1);

(b) Kenai-Cook Inlet;

(c) Seward;

(d) Cordova-McCarthy; and

(e) Matanuska-Susitna (only for incremental employment asso­

ciated with major, "non-base case" projects to be located

in that area).

(2) The same procedure as above was followed for the Kodiak census

division except a multiplier of 1.9 was utilized, assuming that

basic employment increases would equal 54 percent of total em­

ployment increases.

(3) Remaining employment was allocated jointly to the Anchorage and

Matanuska-Susitna census divisions to be disaggregated by the

special procedures outlined in Step 5.

-15-

There was a large arbitrary element involved in the choice of 53 per­

cent for Kodiak and 45 percent base/total employment ratio for the other

census divisions. Some of the considerations that went into these choices

are outlined below:

(1) The basic employment ratio in Seward in the early years was very

low but attained 40 percent in 1976.

(2) The average of the 1970-76 ratios for both the Cordova and Kenai

areas was very close to 45 percent; fluctuations in the ratio

were due to large fluctuations in basic employment in both re­

gions. There appears to be a lag before non-basic employment

is noticeably impacted.

(3) The average of 1970-76 ratios for the combined Kenai, Seward,

Cordova, and Kodiak areas was 46 percent.

(4) The ratio in Kodiak dropped below 50 percent only twice in nine

years; hence, it was felt that a ratio larger than 45 percent

more adequately reflected conditions in Kodiak. ·The average

during the years 1970-76 was 53 percent; during a period of very

stable basic employment (1973-75), the ratio dropped to 54 per­

cent, which suggests that it represents some sort of "equilib­

rium" ratio for the district. The heavy dependence of employment

on seasonal fish processing (35.3 percent of total employment in

Kodiak in 1976 as opposed to 27.8 percent for the Cordova area,

the next most dependent) probably does not create as much of a

local demand·for support services as other employee groups.

-16-

(5) The Valdez ratio was highly inflated during pipeline construc­

tion; it seems reasonable that the ratio for new employment

would approach that of other similar areas (i.e., 45 percent).

Step 4: Allocation of Civilian Population

The basic procedure followed was to apply local historical population

to employment ratio to forecast employment for each census division and

then to adjust the derived figures to equal the total population fore­

cast by the MAP model. This approach compensates in a gross way for local

differences but still insures that the sum of local population allocation

equals the total forecast for the entire Southcentral region. Unfortu­

nately, there is a conceptual difficulty involved with this approach that

arises from the use of local population/employment ratios. An example

illustrates the problem: The procedure implies that a new plant would have

different local population impacts depending on whether it was located in

Cordova or Kenai, which may or may not be reasonable. The main difficulty

involves the fact that the derived populations for each census division

are adjusted to equal the same total regional population in each case.

A change in the location of the plant would thus have an artificially im­

posed impact on the population of each census division, e.g., Kodiak,

which seems most unreasonable.

The best solution to this problem would likely involve the use of

industry-specific population to employment ratios. This information is

not available; moreover, local differences in the ratios could be expected.

The partial solution utilized here sidestepped the issue by using area­

specific population ratios (adjusting local estimates to sum to regional

-17-

totals) for the "base case" or low-growth scenario. Incremental popula­

tion between the low and high growth scenarios was then allocated propor­

tionately to the incremental employment between the two scenarios. Local

considerations thus play a role in the population allocation, which

locational decisions concerning major growth-inducing projects do not have

any arbitrary impacts on other census divisions. Differences in location

will only have a differential population impact on the specific locations

involved and on the Anchorage/Mat-Su areas.

The table on the following page shows historical population/employ­

mer1t ratios for each of the census divisions. The ratio of population to

employment was very low in Anchorage and extremely high in the Mat-Su

area. A special procedure for separating Anchorage and Mat-Su population

is outlined in Step 5; for the purposes of this section, they have been

treated as a single entity.

The two census divisions most dependent on fishing and fish process­

ing (Cordova and Kodiak) had very low population to employment ratios,

which appears to be characteristic of those industries. On the other

hand, ratios for Seward, Kenai, and pre-pipeline Valdez were similar and

generally fairly high.

The population estimates are derived figures, computed after an

analysis of other data such as employment and school enrollments. Since

some of the estimates can be questioned, average ratios for seven years

(1970-76) were utilized in the allocation of future population. Census

divisions with similar population to employment ratios were grouped

POPULATION/EMPLOYMENT RATIOS

Total Kenai,

Total Combined Valdez- Kenai- Seward, South- Matanuska- Anchorage/ Chitina- Cook Cordova- Cordova, central Anchora~ Susitna Mat-Su Whittier Inlet Seward McCarthy Kodiak Kodiak

1968 2.9 2.8 6.5 2.9 3.3 2.5 4.7 3.5 3.0 2.9

1969 2.8 2.6 7.0 2.8 3.0 3.2 4.1 3.1 3.4 3.3

1970 2.9 2.7 5.7 2.8 3.7 3.8 3.2 2.6 3.2 3.5

1971 2.9 2.7 5.2 2.7 2.7 4.0 3.3 2.9 3.2 3.6

1972 2.9 2.7 5.8 2.8 3.9 3.6 2.9 2.5 2.8 3.2 I ~

1973 2.8 2.7 5.3 2.8 3.6 3.4 2.8 2.2 2.3 O:l

2.8 I

1974 2.5 2.4 5.5 2.5 2.5 3.1 2.9 2.1 2.3 2.7

1975 2.5 2.4 6.2 2.5 2.1 2.8 2.7 2.0 2.1 2.5

1976 2.4 2.4 6.2 2.5 1. 7 2.6 3.0 2.2 1.9 2.4

Average of 1970-76 Ratios 2.7 2.6 5.7 2.7 2.9 3.3 3.0 2.4 2.5 3.0

-19-

together and the same ratio used for each member of the group to further

smooth out any unreliable fluctuations. The population allocation method

involved the following:

(1) Low-growth scenario:

(a) multiply Anchorage/Mat-Su new employment by 2.7 (seven­

year average ratio) and add to baseline population;

(b) multiply Cordova and Kodiak new employment by 2.45 (un­

weighted average ratio for the two census divisions) and.

add to baseline population;

(c) multiply Valdez, Kenai, and Seward new employment by 3.16

(average ratio for the divisions, excluding post-pipeline

Valdez, with 1974-76 Kenai and Seward ratios weighted to

replace this exclusion) and add to baseline population; and

(d) proportionately adjust population figures to equal regional

total.

(2) High-growth scenario:

(a) determine distribution of employment increases over low-

growth scenario; and

(b) allocate population increase over low-growth scenario pro­

portionately to employment increase.

Step 5: Disaggretation of Combined Anchorage and Matanuska-Susitna Civilian Emplozment and Population

The MAP regional model provides the capability for separate forecasts

for Anchorage and for the remaining Southcentral region. Unfortunately,

the model does not adequately reflect the shift of population and supporting

-20-

economic activity from Anchorage to the Matanuska-Susitna valleys, which

is essentially a suburbanization phenomenon.

The table on the following page presents historical data concerning

population and employment in the Matanuska~Susitna area and their relation~

ship to corresponding values in Anchorage. Total employment in the Mat-Su

census division has been very consistently equal to a percentage of

Anchorage employment (about 3 percent). In calculating various regres­

sion equations, Anchorage employment was the best estimator of Mat-Su

employment (r 2=.96); the regression line also had a slope of about 3 per­

cent. This regression equation was utilized to disaggregate Anchorage and

Mat-Su employment. The equation was converted into the following form

appropriate to the task of disaggregation:

MAT-SU EMPLOYMENT= .0303 x COMBINED MAT-SU & ANCHORAGE EMPLOYMENT - 59.7

While total Mat-Su employment is a good predictor of Mat-Su popula­

tion (r 2=.97), Anchorage civilian population is an even better estimator

(r 2=.99). This supports the concept that the Matanuska-Susitna population

is essentially a residential spillover from Anchorage and is a function

of the Anchorage population. The high ratio of population to employment

in the area, the relative lack of basic employment, and the relatively

large amount of commuting to Anchorage indicate that much of the economic

activity in the area operates to support the population and is derivative

of the population base. The equation utilized to predict Mat-Su population

(on the basis of Anchorage population) is expressed in the following form

-21-

when used to disaggregate combined population:

MAT-SU POPULATION= .11048 x COMBINED MAT-SU &

ANCHORAGE CIVILIAN POPULATION - 6917

MATANUSKA-SUSITNA CENSUS DIVISION: EMPLOYMENT AND POPULATION: COMPARISON WITH ANCHORAGE

Ratio % of Anchorage Civilian Population/

Census Div_ision Basic

PoEulation EmEloyment Em£loyment PO£Ulation EmEloyment Em12loyment

1970 6,503 l,i45 5.68 5.7 2.7 2.2

1971 7,737 1,414 5.47 6.0 3.1 2.4

1972 8,366 1,445 5.79 6.4 3.0 1. 6

1973 8,586 1,607 5.34 6.3 3.2 1.5

1974 9,787 1,784 5.49 7.0 3.0 1. 6

1975 12,462 2,022 6.16 7.5 2.9 1.9

1976 14,010 2,269 6.17 8.6 3.1 1.8

Average (weighted) = 5. 77 6.9 3.0 1.9

REGRESSION EQUATIONS

Dependent Independent r2 Variable Variable Eguation

Matanuska-Susitna Anchorage Total Employment Total Employment • 963 y = -61.6 + .03125X

Matanuska-Susitna Anchorage Non-Basic Employment Total Employment .835 y = 25 + .0250X

Matanuska-Susitna Anchorage Non-Basic Employment Total Employment .730 y = 310 - .0296X

Matanuska-Susitna Matanuska-Susitna Population Total Employment • 969 y = -1815 + 6.859X

Matanuska-Susitna Anchorage Civilian Population Population .990 y = -7776 + .1242X

Matanuska-Susitna Anchorage Resident Population Population .986 y = -9851 + .1269X

-22-

Step 6: Addition of Military Employment and Population

Military employment is assumed to be equal to military population

(military dependents are included with the civilian population) and is

assumed to remain constant over the forecast period. Hence, total popu­

lation and employment figures for each census division are derived by

adding a single constant term to both civilian employment and population

for all years in each census division. Assumed military populations and

employment are based on the following 1976 estimates:

Census Division

Anchorage

Matanuska-Susitna

Kenai

Seward

Kodiak

Cordova

Valdez

Military Population

12,129

0

53

15

866

53

0

SOURCE: Alaska Department of Labor, Research and Analysis Section.

18

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APPENDIX A

Hunter Origin and Destination Recode Statements

0010IF::(A20 EQ 26) A24=1 0020IF::CA20 EQ 22 OR 23) A24=2 0030IF:;cA20 EQ 18 OR 19 OR 21) A24=3 0040IFt:CA20 EQ 24 OR 25) A24=4 0050IF::(A20 EQ 20) A24=5 0060IF::CA20 EQ 11 OR 12) A24=6 0070IF::CA20 EQ 13 AND A21 EQ 10 AND A22 EQ 2) A24=6 OOBOIF::CA20 EQ 13 AND CA21 GE 24 AND LE 29)) A24=6 0090IF:t(A20 EQ 13 AND (A21 EQ 50 OR 56)) A24=6 0100IF::CA20 EQ 13 AND A21 EQ 54 AND CA22 GE 5 AND LE 11)) 0110! :A24::::6 0120IF;t(A20 ED O:l30IF;; ( ti20 EC~ 0140IFttCA20 EQ 01 ~iO t ! A24=6

13 j .. , . -..:)

1.:3

,;N:o t1ND AND

A21 EG 10 AND A22 EQ 3) A24=6 (A21 GE 36 AND LE 43)) A24=6 A21 EQ 55 AND (A22 EQ 8 OR 9 OR 10))

0160IF:!(A20 EQ 13 AND CA21 EQ 30 OR CGE 1 AND LE 6))) A24=7 0170IFt:CA20 EQ 13 AND A21 EQ 8 AND (A22 EQ 4 OP 5 OR 6)) A24=7 0180IF:t(A20 EQ 13 AND A21 EQ 10 AND CA22 EQ 1 OR 4)) A24=7 0190IF::CA20 EQ 13 AND A21 EQ 54 AND A22 EQ 4) A24=7 0200IF!:(A20 EQ 13 AND A21 EQ 55 AND 0210:tCA22 EQ 11 OR (GE 1 AND LE 7))) A24=7 0220IF::CA20 EQ 13 AND ((A21 GE 31 AND LE 35) OR 0230::(A21 GE 44 AND LE 47))) A24=7 0240IFt:CA20 EQ 13 AND A21 EQ 54 AND (A22 EQ 1 OR 2 OR 3))

0260IF!t(A20 EQ I::"" ... , AND CA21 GE 1 AND LE 5)) A24=9 1 AND 0270IF::CA20 GE LE 4) A24=8 i::- AND ... , 0280IFt:CA20 EQ (A21 EQ 6 OR. 7 OR 8)) A24=16 i::- 1;ND J 0290IF::CA20 EQ (A21 EQ 9 OR 11 OR 12)) A24=11

0300IF!:CA20 EQ 6 AND A21 EQ 3 AND CA22 EQ 7 OR 14)) A24=12 0310IF!:CA20 EQ 6 AND A21 EQ 2 AND CA22 EQ 6 OR 7)) A24=13 0320IF::CA20 EQ 6 AND A21 EQ 3 AND CA22 GE 1 AND LE 6)) A24=13 0330IF::CA20 EQ 6 AND A21 EQ 2 AND C(A22.GE 1 AND LE 5) OR 0340::<A22 GE 8 AND LE 16))) A24=14 0350IF::CA20 EQ 6 AND A21 EQ 91) A24=15 0360IF!:CA20 EQ 6 AND A21 EQ 92) A24=16 0370IF::CA20 EQ 6 AND A21 EQ 93) A24=17 0380IF::CA20 EQ 17) A24=18 0390IF::CA20 EQ 9 AND CA21 EQ 1 OR 2 OR 3 OR.7 OR 9)) A24=18 0400IF::CA20 EQ 9 AND (A21 EQ 14 OR 15 OR 16 OR 21 OR 23 OR 24 0410:!0R 25 OR 32 OR 33 OR 34 OR 40)) A24=19 0420IFt:CA20 EQ 9 AND :CA21 EQ 22 OR 26 OR 27 OR 29 OR 31 OR 35)) 0430tfA24=20

0440ir::cA20 EQ 16 AND A21 EQ 2 AND (A22 EQ 4 OR 0450::11 OR 12 OR 13 OR (GE 16 AND LE 20))) A24=21 0460IF::CA20 EQ 16 AND CA21 EQ 27 OR 28 OR 30 OR 50)) A24=21 0470TF: ~· U:120 Ecr-9,~,r,m ·u:,21 ED 4 ·m~·-s--01:;: .s-oR :so) r ,;24=22 0480IFt:CA20 EQ 16 AND A21 EQ 2 AND (A22 EQ 1 OR 2 DR 3 OR 14 OR 0490::15 OR (GE 5 AND LE 9) OR GE 21)) A24=23 0500IF::CA20 EQ 16 AND CA21 EQ 20 OR 21 OR 25 OR 26)) A24=23 0510IF!!(A20 EQ 16 AND CA21 EQ 1 OR 32 OR 40)) A24=24 0520IF::CA20 EQ 13 AND CA21 EQ 7 OR 9 OR 48 OR 49 OR 52 OR 53 OR 0'.530tt(GE l:l. 0'.540IF: t Ui'.20 0'.'5:::;o t : B cm 9 O'.:i60IFt t (P,20 0570IF t; ({)20 0580IF: t Ui20 O!~j?OIF! ! (rY20 0/JOOIF; :, < t,20 06:1.0IFS t (t120 0620IF t t <r,20 0630IF t I ( r-)20 0640IFt t U,20 0650IF t t U)20 O,S60 IFS t U)20 06?0IF! t (i:)20 06BOIFt ! U)2() 0690IF! t (r-)20 0700IF t t U\:20 0710IFt ! U)20 0720 IF t ! U',20 OT30IF ! ! U120 07-~-0IF t t U',20 0750IF:!(A20 0760IFtt(A20 07?0IFtt(A20 0700IFt!CA20 0790 IF t t ((~20 ODOOIF: t (r:)20 0810IF! t (1;20 OB20IF!!(A20 0830IFtt(A20 0840:CF ! : U)20

(~ND EIJ OR EQ [I]

EQ E1] EQ EO EQ H1 EQ EQ EO EQ EQ EQ EO EL1 EO EC~ EU [I]

EQ [(.1

EQ EQ EQ EQ EQ EQ EQ

L.E 2:-s) ) ) (124=24 13 ,-=-1ND A2J. EQ 8 AN:O (A22 EIJ 1 OR ... > DR

.. , rn;: 7 oi:;: .-:_ w 10) ) J~l 2 .l..} == ~~ .4 1 .. ,

..:) AND A21 EQ 10 AND A "l""'l 1-t.,·:.-:.: En ::; ) 1~24=24 14 i~ND A21 EQ 2) . A24=24 14 (1ND {'i21 EO 1) A2·4==25 14 (~N:O A21 EL1 3) A24=26 :I LS" ···-· AND (~21 EQ 3) A24=27 15 AND (~2:L EQ ?\ . ...._ .. {~2-4.=:~t~ j •=-. .J 10tND {;2:1. EQ 1) ,~24==29 7 t,ND 1;21 EO 91) A:24=30 7 {iND _t)21 EQ 4) A24=3:I. 7 (~ND A21. EQ 3) ,'.'.)24=32 "7 AND A2:I. EQ 2) A24=33 , 7 ,~ND {121 EQ 1) A24=34 6 AND t-121 EC~ 94) 1~2-4=:35 [..-. 1~ND F,21 Et1 95) A24=3{.i; 6 {1ND F121 EQ 96). A24=37 6 r,ND ?',21. EQ 1 AN.O 1;22 EO 1) 1~24=3G 9 t1ND t-,21 EO <J 1. ) A24=39 6 r-,N:O ,~21 EQ 1 ?:,ND• A'=>'=' -~~ Et-1 6) A24=40 G) ,~124°=4:I. "'" tiN:O ,~21 EQ 10) A24=81 .J

6 AND ()21 EQ 10) A24=82 7 M·W ti21 EQ 10) A24=83 j 1::-

. .J t'1ND {-\21. EQ 10) .A24=84 9 Mrn ,~21. EQ 10) A24=91 13 MfO .~21 EC~ 1. 0 AND A22 EQ ()) A24=92 14 ,"1ND ,;21 EQ 1. 0) A24=93 16 ,;ND 1~:~1 EQ 2 f~N:O A'.:"!? EfJ 1. 0) A24===94 1.6 10tND .~21. EQ lO ,~ND A "'iJ"-\

t1..:.:,:.: EQ 0) A24=95 10) A24=9H

DEER DESTINATIONS RECODE STATEMENTS

0010IF; ·> ( t,:?() • 002.JII--.; ·> ( (-)20 • 00301i=·: . ( t,20 ,. 0040IF! ·> I ••• ,,.)_.,

• ~ H.:.•,;

00501Ft • <r-,20 ·>

0060IF! • U',20 • 0070IF! • (A20 • 0080IF! • U~20 ·>

0090IF; • ( t,20 • OlOOIFt • ( P,20 ·>

0110IF! • ((-i20 ·>

0120IFt • (,~20 • 0130IF! • ( ,~20 • 0140IFt • u;20 • O:l.50IF!: (t120 0160IF! • ( f.)20 • 0170:CF! • (,~20 • 0180!!4 OR I::'

,J

0190IFt .. (A20 • 0200IF: • (1~20 • 0210IF! • U-)20 • 0220IF! • (f.)20 • 02301Ft • (A20 •

EC~ EC-l EG Ell EG EIJ EU EQ EQ EQ EQ EC! EQ EQ EQ EiJ EQ OR EQ EQ EQ EQ EQ

:t ) (:, ::.~ .4 :-.;: l 2) ti24=2 3) r'..)24:=<:5

5 AND (A21 GE 1 AND LE 5)) A24=5 5 AND (A21 GE 6 AND LE 9)) A24=6 5 AND A~l EQ 11) A24=7 6 AND A21 EQ 1) A24=8 6 AND A21 EQ 2) A24=9 6 AND A21 EQ 3) A24=10 6 AND (A21 EQ 4 OR 5)) A24=11 6 AND A21 EQ 6) A24=12 6 AND A21 EQ 7) A24=13 6 AND A21 EQ 8) A24=14 6 AND A21 EQ 9) A24=15 6 AND A21 EQ 13 AND A22 EQ 1) A24=15 6 AND A21 EQ 11 AND (A22 EQ 2 OR 3 OR 7)) t',24::::16 6 AND A21 EQ 11 AND(A22 EQ 1 OR 6)) A24=17 6 AND A21 EQ 12) A24=17 6 AND A21 EQ 13 AND(A22 EQ 11 OR 12)) A24=18 6 AND (A21 EQ 14 OR 15)) A24=19 8) 1~24=20

SI-IEE:=· n::::GTIN:~iTION:3 r::ECO:OE ST(1TEr-·1ENT'.]

0010IF:t(A20 EQ 23 OR 24 OR 25 OR 26) A24=1 0020IF:tCA20 EQ 20) A24=2 0030IF::(A20 EQ 17 OR 19 OR 16 OR 9) A24=3 0040IF::CA20 EQ 11 OR 12) A24=4 0050IF::CA20 EQ 13 OR CA20 EQ 14 AND CA21 GE 1 AND LE 5))) A24=5 0060IF:!CA20 EQ 14 AND (A21 EQ 6 OR 7 OR 8 OR 9 OR 11 0070::oR <GE 26 AND LE 33))) A24=6 0080IF::CA20 EQ 14 AND CA21 GE 12 AND LE 25)) A24=7 0090IF::CA20 EQ 15 AND (A21 EQ 14 OR 15 OR 16)) A24=8 0100IF::CA20 EQ 15 AND (A21 EQ 6 OR 7 OR 8 OR 9 OR 11 OR 12 OR 0110::13)) A24=9 0120IF::CA20 EQ 15 0130IF::CA20 EQ 7) 0140IF::(A20 EQ 14 0150IF!!CA20 EQ 14 0160IF::CA20 EQ 15

ANDCA21 .~24=11 ,~1ND A21 c:'.)N:0 1~21 c~ND (~21

GE

EQ EQ EQ

1 AND LE 5) ) A24,::10

lO) (~2-4==:t:::; 34) ?',24=16 :1.0) A24•=:l 7

... ----·-------- ---

Cll? JC IN i:; F:ECODE ::;T ,~ TEMENT'.:;

C) f~ 9S-'6 :I. 4 Of? 99620 or:~ ~? ~;) \s :~ .t DI~ 9 (J<S:~ ~~

or~ <;><;)6::14 ()f~ ') C) ,~) ::) f._, OF~ 99637 OF;: 1:'Jf/6:3~:i or~ 9964::: OF< ?96'.53 0 F< 99660 DF: s>s>6t)1 OF< 9()6<:>6 OF< 9966B or~ 9?670 OF~ 99675 cm 9?6<?() OR </9.:!)</ J. OF: 9?692) A2'.'5 .... ,., .-::..

0160IF::CCA3 GE 99551 AND LE 99555) OR CA3 GE 9957B AND 0170:tLE 99581) OR (A3 GE 99625 AND LE 9?630) OR CA3 GE 0180::99647 AND LE 9?651) OR CA3 GE 99655 AND LE 99658) 0190:tOR CA3 GE 99678 AND LE 99681)) A25 = 2 0200IF::CA3 EQ 99725 OR 99731 OR 99737 DR 99764 OR 99776 OR 0210$%99779 OR 99780 OR CA3 GE 99701 AND LE 99708)) A25 = 3 0240IF::CA3 GE 99801 AND LE 99995) A25 = 4 0250IFt:CA3 EQ 99550 OR 99608 OR 99615 OR 99624 OR 0260::99643 OR 99644 OR 99697) A25 = 6 0270IFttCA3 EQ 99645 OR 99667 OR 99674 OR 99676 DR 0280::99687 OR 99688) A25 = 7 0290IFtt(A3 EQ 99556 OR 99568 OR 99570 OR 99603 OR 0300:t99610 OR 99611 OR 99639 DR 99663 DR 99669 OR 0310::99672 OR 99682) A25 = 8 0320IF:t(A3 EQ 99567 DR 99577 OR 99587 OR 0330::(GE 99501 AND LE 99510)) A25 = 9 0340IF:tCA3 EQ 99572 OR 99605 OR 99631 OR 99664) A25 = 10 0350IFt:CA3 EQ 99566 OR 99573 OR 99586 DR 99588) A25=11 0360IFtt(A3 EQ 99654) A25 = 12 0370IFt:CA3 EQ 99677 OR 99686) A25 - 13 0380IFtt(A3 EQ 99560 OR 99574) A25 = 14 0390IFtt(A3 EQ 99689) A25 - 15 0400IFttCA3 EQ 99997) A25 = 18 0410IF::<A3 EQ 99998) A25 = 16 0420IFtt(A3 EQ 99999) A25 = 17

--o4~50IF~: (ti3-T31:--9:37,:ro- -ANUCF.YB799T ,~!T- ::;: 2()-- ---- ---- --- ·-- --- -- - -- --· ----. --- -- - ---

0440 IF:: ( A3 EQ 98733 OR 98737) A25 = 3 0450IFt:CA3 EQ 98742) A25 - 9 0460IFt:<A3 EQ 98790) A25 = 6

APPENDIX B

Hunter Origin and Destination Maps

Number

l 2

3 4

5

6 7 8 9

10 11

KEY: SHEEP DESTINATIONS

Destination

Brooks Range North Central Alaska Range

and Interior West Alaska Range~·:~·: Wrangell Mountains and North­

east Chugach Mountains Talkeetna Mountains and South-

central Alaska Range

Matanuska-Susitna* West Chugach1: North Kenai Peninsula* West Central Kenai Peninsula* Southwest Kenai Peninsula* East Kenai Peninsula*

Comments

GMU 23, 24, 25, 26 GMU 20

GMU 9, 16, 17, 19 GMU 11, 12

GMU 13, 14B

GMU 14A GMU 14C GMU 15A GMU 15B GMU 15C GMU 7

Number

1 2 3 4 5

6 7 8 9

10

11 12 13 14 15 16

17

KEY: DEER DESTINATIONS

Destination

Southeast 1 Southeast 2 Southeast 3 Southeast 4 Yakutat 1:

Cordova - Mart in Ri ver 1':

Hawkins Island:': Hinchinbrook Island* Montague-Green Islands* Bainbridge Chenega Latouch*

Knight Island:': Naked Island:': Perry Culcross Lone Island* Nelsen Bay-Point Gravina:': Port Fidalgo-Valdez* Passage Canal:':

Kodiak Afognak Island*

Comments

GMU 1 GMU 2 GMU 3 GMU 4 GMU 5 - Yakutat Bay to Harlequin Lake

GMU 6 (part) GMU 6 (part)

GMU 8

Number

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

KEY: MOOSE DESTINATIONS

Destination

North Slope Northwest Southwest Northern Interior Southern Interior

Paxton Lake-Wrangell Mountains Susitna-Tetlin Lakes Southeast Yakutat-Russell Fjord*

Malispina Glacier Forelands1:

Cape Suckling:': Copper-Martin Rivers* Cordova-Eyak;': North Bristol Bay Alaska Peninsula-Northwest

Alaska Peninsula-Southeast* Upper Western Cook Inlet*

Lower Western Cook Inlet;': Upper Skwentna-Yentna River

Susitna Basin Matanuska-Susitna Valley* Anchorage:': Southwest Kenai Peninsula 1':

West Central Kenai Peninsula 1':

Northern Kenai Peninsula* Eastern Kenai Peninsula*

Comments

GMU 26 GMU 22, 23 GMU 18, 19, 21 GMU 24, 25 GMU 20

GMU 11, 12, 13B, 13C GMU 13A and 13D GMU 1, 2, 3, 4 GMU 5 - Yakutat Bay to Harlequin Lake

GMU 5 - Yakutat Bay to Icy Cape

GMU 6A GMU 6B GMU 6C GMU 17, 9B, 9C GMU 9E -Bristol Bay drainages

GMU 9E - Pacific drainages GMU 16B - Beluga Mountain-Redoubt Bay GMU 9A GMU 16B - Northwestern portion

GMU 16A, 13E, 14B GMU 14A GMU 14C GMU 15C GMU 15B GMU 15A GMU 7

Number

1 2 3 4-5

6 7 8 9

10

11 12 13 14-15 16

KEY: HUNTER ORIGINS

Origin

Northcentral Southwest Fairbanks Southeast Kodiak:':

Matanuska-Susitna* West Kenai:': Anchorage:': Seward:': Ahtna

Whittier:': Valdez:': Cordova:': Yakutat:': Rest of United States Foreign

APPENDIX C

Southcentral Alaska Employment and Population Forecasts:

Allocation by Census District

Forecasts of employment and population for the Anchorage area and

the rest of Southcentral Alaska were provided by ISER's Man-in-the-Arctic

Program (MAP) regional econometric and population model through 1990, and

extended to the year 2000. Within Southcentral Alaska, it was necessary

to disaggregate the results of those forecasts by smaller areas, i.e.,

census divisions. This discussion describes the methodology through

which this disaggregation was accomplished. Seven census divisions were

involved: Anchorage, Matanuska-Susitna, Kenai-Cook Inlet, Seward, Valdez­

Chitina-Whittier, Kodiak, and Cordova-McCarthy.

Since the population estimates were heavily dependent upon employ­

ment estimates, fundamental to the disaggregation process was a dichotomy

between "basic" and "nonbasic" employment. For the present purposes,

basic employment was defined somewhat arbitrarily as: 1) agriculture,

forestry, and fisheries; 2) mining; 3) manufacturing; 4) construction;

and (5 federal government civilian employment. All historic employment

and population estimates utilized were provided by the Alaska Depart­

ment of Labor, Research and Analysis Section.

Basically, the methodology utilized involved a six-step process:

(1) Adjust Valdez baseline population. Some hypothetical estimate

of "stable" or "natural" population and employment in Valdez

was necessary to isolate the short-term effects of pipeline

construction.

(2) Allocate basic employment. Increments in basic employment

sectors were allocated according to historical trends and

the assumed location of major developments.

-2-

(3) Allocate rion-basic emplo yment. Non-basic employm ent was allo­

cated to all censu s divisions (except Anchora ge and Matanuska­

Susitna) based on historic a l basic/non-basic ratios. Remaining

non-basic employment was a s signed jointly to Anchorage and

Mat - Su.

(4) Allocate civilian population. Population was assigned on the

basis of historical population/employment ratios.

(5) Separate Anchorage and Mat-Su employment and popul a tion. Be­

cause of their special relationship, population and employment

for these two census divisions were combined, but finally

separated using special procedures.

(6) Add military employment and population. Military population

was estimated on the basis of recent experience and held constant.

Step 1: Adjustment of Valdez-Chitina-Whittier Census Division Baseline Data

Forecasts of population and employment levels for the Valdez area are

hampered by the extreme shifts that have resulted from pipeline activity.

To obtain useful baseline estimates of "real" or "stable" levels of employ­

ment and population, corrections must be made to compensate for temporary

short-term effects of pipeline activity without eliminating more stable

long-term influences. Unfortunately, there is little data available con­

cerning post-pipeline economic activity and population levels in the Valdez

area.

A possible approach would be to use pre-pipeline employment and popu­

lation levels as a baseline. However, it does not seem reasonable that

economic activity or population in the Valdez area would revert to

-3-

pre-pipeline levels in the near future. For one thing, a force of about

500 is employed for Alyeska terminal and pipeline operations, and this

workforce is expected to remain relatively constant in the future. 1 More­

over, it seems fairly safe to assume that structural changes have occurred

which have had a qualitative effect on the local economy.

The procedure utilized here to derive a hypothetical measure of

"stable" or "real" employment and population involved the use of regression

analysis and the following process: (1) the relationship between various

employment segments and total employment and between total employment and

population were identified through regression analysis; (2) assumed levels

of basic employment segments were input into. the equations to derive esti-

mates of total employment and population.

Two different basic employment groups were analyzed to determine

the best estimator of total employment: total construction employment and

basic employment (construction; manufacturing; agriculture, fishing, and

forestry; and federal government). The historical data is shown in the

table on the following page. Regressions were run using annual average

employment and mid-year population estimates for seven years. The fit of

all equations was very high, but all population or employment variables

had very low values before pipeline construction and very high ones once

construction started and high correlations would be expected. Since the

dominant changes are of large magnitude and in the same direction, normal

1Telephone conversation with Andy Ooms, Manager, Labor Relations and Affirmative Action Program, Alyeska Pipeline Service Company.

-4-

VALDEZ-CHITINA-WHITTIER CENSUS DIVISION BASIC AND CONSTRUCTION EHPLOYHENT

Basic Em:eloyment Construction Year & Total % of % of Quarter Po:eulation Em:eloyment No. Total No. Total

Annual Average

1970 3,098 831 101 12.2 21 2.5

1971 2,949 1,085 388 35.7 222 20.5

1972 3,487 905 132 14.6 73 8.1

1973 3,568 984 189 19.2 69 7.0

1974 3,833 1,526 459 30.1 399 26.1

1975 9,639 4,633 2,597 56.1 2,518 54.3

1976 13,000 7,818 5,492 70.2 5,414 69.3

Quarterly Average

1974.:..1 842 87 10.3 38 4.5 -2 1,180 163 13.8 147 12.5 -3 1,787 553 30.9 492 27.5 -4 2,297 992 43.2 919 40.0

1975-1 2,871 1,446 50.4 1,375 47.8 -2 3,910 1,884 48.2 1,816 46.4 -3 4,809 2,537 52.8 2,434 50.6 -4 6,916 4,522 65.4 4,447 64.3

1976-1 6,659 4,388 65.9 4,330 65.0 -2 8,558 6,232 72.8 6,152 71.9 -3 9,240 6,802 73.6 6,704 72. 6 -4 6,814 4,541 66.6 4,472 65.6

1977-1 5,006 3,057 61.1 2,992 59.8 -2 5,455 3,290 60.3 3,231 59.3 -3 N/A N/A N/A -4 N/A N/A N/A

-5-

fluctuations are swamped. It was hypothesized that structural changes

occurred with pipeline construction; regressions run on more recent data

would thus be expected to better reflect the current structure of the

local economy. Quarterly data from 1974 to mid-1977 (fourteen quarters)

was utilized in deriving the estimating equations. Since population esti­

mates were not available on a quarterly basis, population for the second

and third quarters of each year was assumed to equal the mid-year estimate

for that year; population figures for other quarters were interpolations.

The results of the equations are shown in the table on the following

page. Alyeska employment was apparently a poor estimator of other employ­

ment . (r 2=. 30); construction employment was a better estimator of non­

construction employment; and basic employment was the best estimator of

derived employment (r 2=.78). Total employment was a very good estimator

of population (r 2=.90); multivariate equations using basic and non-basic

as well as construction and non-construction independent variables ex­

plained a little more of the population variance, but improvement as an

estimator is somewhat problematical because of the collinearity of the

independent variables.

Estimates of "stable" employment were made by inserting appropriate

assumed values of basic employment into the equations. Assumptions were:

(1) Alyeska employment equals 500 non-construction operations

personnel;

(2) construction employment equals 100, the average during the nine

pre-pipeline years (1965-1973); and

Basis

Employment Equations

1. Construction Employment

2. Basic Employment

Population Equations

1. Total Employment

2. Construction Employment·

3. Basic Employment

VALDEZ-CHITINA-WHITTIER CENSUS DIVISION: HYPOTHETICAL "STABLE" EMPLOYMENT AND POPULATION

Equation

Derived Employment=

1,347 + .·2135 X

Const. Employment

1.,175 + .2320 X

.Basic Employment

Derived Population=

3,225 + 1,1856 X

Employment

989 + .7064 x Const. Employment+ 3.047 x Other Employment

1,028 + .7137 x Basic Empl. + 3 .1145 x Employment

r2 (adj. r 2)

.67 (.64)

.78 (.75)

• 91 (. 90)

.94 (.93)

• 94 (.93)

Assumptions

Const. Empl. = (a) 100 (b) 600

Basic Employ. = 75 Const. Empl. = (a) 100

(Basic) (b) 600

Employment= (a) 2,007 (b) 2, 075-

Const. Empl. = 600 Other = 1,475

Basic Empl. = 675 Other = 1,332

Employment Derived Total

(a) 1,368 (a) 1,468 (b) 1,475 (b) 2,075

(a) 1,216 (a) 1,391 (b) 1,332 (b) 2,007

Total Po£ulation

(a) 5,604 (b) 5,685

5,907

5,658

I

°' I

-7-

(3) other basic employment equals 75, the approximate amount in

1976.

A problem arises because of the fact that Alyeska employment is not con,...

struction and by our definition is not basic. However, not including

Alyeska employment in the independent variable produces estimates that are

artificially low. In any case, Alyeska employment should be considered

as basic despite the arbitrariness of our definition. The basic employ­

ment equation appears to be the best estimator of total employment, and

the employment estimate of about 2,000 (2,007) appears reasonable. Based

on this figure, a population estimate of about 5,600 (5,604-5,685) was

derived.

Stable employment of about 2,000 and population of about 5,600 appears

reasonable when compared to data from 1975, the year in which basic employ­

ment was closest to the assumed stable value of 675, as shown in the table

below. Based on 1975 ratios, total employment would be slightly higher,

but population would be slightly lower. Inserting the higher figure for

total employment into the population equation ("hybrid" estimate) still

only produces a total population of less than 5,900.

VALDEZ-CHITINA-WHITTIER POPULATION ESTIMATES

Hybrid-1975 Basic/other Preferred

1975 1975 Employment Regression Actual Ratios Ratio Equations

Basic employment 459 675 675 675

Total Employment 1,526 2,244 2,244 2,007

Population 3,833 5,512 5,885 5,604

-8-

Step 2: Allocation of Basic Employment to Census Divisions

The HAP regional model provides a forecast for Anchorage and another

for the remainder of the Southcentral region. While the model underesti­

mates the shift of population and supportive economic activity from

Anchorage to the Matanuska-Susit11a valleys (see discussion of Step 5),

this is not an important problem for the basic industries, ·since the

"basic" sectors are exogenous inputs to the model and can be locationally

identified.

Allocations of basic employment to other census divisions in the

Southcentral region were made on the basis of historical patterns and

assumptions concerning the probable location of major industrial projects.

Disclosure rules prohibit the publication of some data, but the distribu­

tion of basic employment in 1970, 1973, and 1976 is shown in the table on

the next page and historical trends are discussed briefly below:

(1) Agriculture, forestry and fisheries. Self-employed workers are

not included in any data but are a particularly important com­

ponent of these industries. Moreover, the 1970 data for these

industries is not reliable because very few employees were

covered by unemployment insurance, the source of the statistics.

Most of the employment in 1973 and 1976 was in Kodiak, although

there were relatively large numbers in the Kenai and Cordova

census divisions.

(2) Mining. Mining employment (petroleum-related) is heavily con­

centrated in the Kenai area. Employment there dropped by one­

half between 1968 and 1971 but has been increasing somewhat in

-9-

DISTRIBUTION OF BASIC EMPLOYMENT 1970-1976 BY CENSUS DIVISION

Z of Southcentral Region (excl. Anchor a&:_}~, Kodiak Cordova Seward Mat-Su Kenai Valdez:~

Agriculture> Fisheries, Forestry 1970 42.6 47.5 8.2 1. 6

1973 57.8 9.9 7.6 2.5 20.6 1.6 1976 67.3 14.3 4.4 1.8 11.5 . 7

Mining 1970 .7 11.1 2.1 85.5 • 7 1973 9.1 1. 7 . 1. 9 86.7 . 6 1976 7.0 2.3 .4 89.8 .5

Construction 1970 7.9 6.4 .3 20.7 61.0 3.6 1973 19.1 3.2 3.2 14.3 50.1 10.1 1976* 15. 3. 1.5 .5 12.6 64.1 6.1

Manufacturing 1970 45.1 12.1 4.5 2.1 35.4 .8 1973 60.0 10.8 11.0 .5 26.6 2.5 1976 50.1 8.8 10.4 .9 29.3 . 5

Federal Govt. 1970 51.1 5.3 5.5 14.0 15.7 8.3 1973 46.0 5.9 6.5 18.7 14.0 8.9 1976 43.5 5.8 9.2 20.2 12.8 8.5

Change 1970-1976

Agriculture, Fisheries, Forestry +384 +87 2 + 6 + 69 + 4

Mining 5 -27 + 19 -13 + 89 - 1

Cons true tion'>'; +207 -13 + 6 +88 +704 +19

Manufacturing +896 +89 +267 - 5 +376 + 2

Federal Govt. -109 - 3 + 17 +23 - 37 - 9

*Valdez 1976 construction employment assumed to equal 100 - see discussion of "Step l" (actual number was 5,415, an increase of 5,394 over 1970).

-10-

recent years. Mining employment is also significant in the

Cordova census division but is primarily non-petroleum related.

(3) Construction. Employment in this industry is extremely volatile

and was. most important in the Kenai, Mat-Su, and Kodiak census

divisions and in Valdez during pipeline construction. Trends

in construction employment closely paralleled those of other

industries in Kenai and Kodiak: fish processing and federal

government in Kodiak and the petroleum industry in Kenai.

(4) Manufacturing. Fish processing is a very big industry in Kodiak

and also in the Kenai census district, where it accounts for

nearly 50 percent of manufacturing employment. It is also im­

portant in the Cordova and Seward areas. There was a sizeable

amount of employment in the Valdez census district in one year

only (1973), which is characteristic of the extreme fluctuations

of the industry. Fish processing employment was at a long-term

peak in 1976 in every census division where the industry was

important: Kodiak, Kenai, Seward, and Cordova.

Lumber products employment was particularly important in

the Kenai census district and also in Seward. There has also

been, in recent years, sizeable lumber products employment in

Kodiak. Up until its peak in 1971, lumber products employment

was also fairly important in the Mat-Su area. Now, most Mat-Su

timber is processed in Seward. Employment peaked in general in

1976, but the industry was on a tenuous footing in 1977 because

of a weakening of the market and because of the difficulty in

-11-

obtaining an adequate supply of timber. The new mill at Tyonek

closed for these reasons.

The petrochemical complex (petroleum refining and chemical

processing) concentrated near the city of Kenai (and accounting

for over one-third of the census district's manufacturing em­

ployment) was the only other manufacturing industry of note.

Employment in that industry increased about 50 percent between

1973 and 1976.

(5) Federal government (civilian). Nearly half of federal employment

in the region was in Kodiak and involved civilian jobs associated

primarily with the Coast Guard (formerly Navy) base on the island.

Huch of the federal employment in the rest of the region is asso­

ciated with military or Coast Guard operations. Cutbacks in

these operations have been the cause of federal civilian employ­

ment declines in Kodiak and Kenai. Federal employment in the

Hat-Su division is fairly important and appears unrelated to

military activities but rather a result of Alaska Railroad and

other civilian operations (agriculture, FAA).

Step 3: Allocation of Total Civilian Employment

Once basic employment has been allocated to the census divisions, it

is possible to distribute other employment through the use of basic/non­

basic employment multipliers appropriate to the industries and locations

involved. Unfortunately, not enough is known about specific local factors

and employment interrelationships to accomplish this in a detailed fashion,

and it is necessary to rely on gross relationships between basic and

-12-

non-basic sectors in a given census division. Moreover, this relation­

ship is rather unstable and has fluctuated considerably from one census

division to another and from one time period to another in a given locale

(see table on following page). Some of the problems involve inadequacies

in our definition of basic and non-basic industries, i.e., some specific

industries are actually "basicll but are not categorized as such here, and

vice versa.

The aggregate trend in the Southcentral region has been toward a

higher ratio of total employment to basic employment. This pattern is

definite only in the Anchorage and Matanuska-Susitna census divisions.

It is not so apparent in the other census divisions, however, and the

opposite pattern is quite evident in the case of Seward and Valdez. The

problem with both of these areas is that, initially, there was very little

employment that was classified as basic according to our definition, al­

though much of other employment was functionally "basic" (e.g., hospitals

and nursing homes, Alaska Skill Center, etc.). During the 1970s, some

industries that were defined as basic expanded significantly (pipeline

construction in Valdez, lumber and fish processing in Seward).

The very low proportion of basic employment found in the Matanuska­

Susitna census division can be explained by the fact that population and

non-basic employment in the area is more a function of Anchorage employ­

ment and population rather than indigenous basic employment. For this

reason, the Anchorage and Matanuska-Susitna census divisions are treated

as a single unit; population and employment for the two areas are only

separated at the end, using the special procedures outlined in Step 5.

BASIC EMPLOYMENT: PERCENT OF TOTAL EMPLOYMENT

Total Kenai,

Total Combined Valdez- Kenai- Seward, South- Matanuska- Anchorage/ Chitina- Cook Cordova- Cordova, central Anchorage Susitna Mat-Su Whittier Inlet Seward McCarthy Kodiak Kodiak

1968 41. 7 39.1 23.9 38.7 12.9 61. 7 24.2 50.6 56.8 56.6

1969 38.6 36.7 23.7 36.4 19.2 55.6 22.8 54.2 51.3 51.5

1970 36.7 35.8 24.5 35.5 12.3 47.8 21.4 51. 6 48.9 46.1

1971 35.1 34.2 24.9 33.9 26.5 45.5 25.4 46.9 46.0 43.7

1972 33.8 32.8 18.0 32.3 14.6 43,3 30.6 47.4 50.5 44.9 I f-' (.;.)

1973 33.2 31.4 14.9 30.8 19.4 42.0 37.1 47.2 57.8 48.1 I

1974 32.9 31.2 16.6 30.8 30.1 40.9 38.9 41.4 55.1 45.9

1975 32.5 29.1 18.0 28.8 56.1 43.5 39.3 44.2 53.8 46.5

1976 34.1 28.1 16.7 27.8 70.2 45.3 . 40.0 47.6 57.8 49.3

Average of 1970-76 Ratios 34.0 31.8 19.1 31.4 32.7 44.0 33.2 46.6 52.8 46.4

-14-

The low proportion of basic employment in the Anchorage census divi­

sion indicates that the Anchorage area is capturing a proportion of deri­

vative employment from expansions .of basic sectors in other areas of the

Southcentral region (as well as in other parts of the state). Because

of this phenomenon, the following procedure was utilized to distribute

total employment:

(1) Incremental basic employment was multiplied by a factor of 2.2

to calculate total employment (i.e., basic employment increases

were assumed to equal 45 percent of total employment increases)

and added to the baseline employment for the following census

divisions:

(a) Valdez-Chitina-ifuittier (baseline employment = "stable"

employment; see Step 1);

(b) Kena:i-Cook Inlet;

(c) Seward;

(d) Cordova-McCarthy; and

(e) Matanuska-Susitna (only for incremental employment asso­

ciated with major, "non-base case" projects to be located

in that area).

(2) The same procedure as above was followed for the Kodiak census

division except a multiplier of 1.9 was utilized, assuming that

basic employment increases would equal 54 percent of total em­

ployment increases.

(3) Remaining employment was allocated jointly to the Anchorage and

Matanuska-Susitna census divisions to be disaggregated by the

special procedures outlined in Step 5.

-15-

There was a large arbitrary element involved in the choice of 53 per­

cent for Kodiak and 45 percent base/total employment ratio for the other

census divisions. Some of the considerations that went into these choices

are outlined below:

(1) The basic employment·ratio in Seward. in the early years was very

low but attained 40 percent in 1976.

(2) The average of the 1970-76 ratios for both the Cordova and Kenai

areas was very close to 45 percent; fluctuations in the ratio

were due to large fluctuations in basic employment in both re­

gions. There appears to be a lag before non-basic employment

is noticeably impacted.

(3) The average of 1970-76 ratios for the combined Kenai, Seward,

Cordova, and Kodiak areas was 46 percent.

(4) The ratio in Kodiak dropped below 50 percent only twice in nine

years; hence, it was felt that a ratio larger than 45 percent

more adequately reflected conditions in Kodiak. The average

during the years 1970-76 was 53 percent; during a period of very

stable basic employment (1973,-75), the ratio dropped to 54 per­

cent, which suggests that it represents some sort of "equilib­

rium" ratio for the district. The heavy'dependence of employment

on seasonal fish processing (35.3 percent of total employment in

Kodiak in 1976 as opposed to 27.8 percent for the Cordova area,

the next most dependent) probably does not create as much of a

local demand for support services as other employee groups.

-16-

(5) The Valdez ratio was highly inflated during pipeline construc­

tion; it seems·reasonable that the ratio for new employment

would approach that of other similar areas (i.e., 45 percent).

Step 4: Allocation of Civilian Population

The basic procedure followed was to apply local historical population

to employment ratio to forecast employment for each census division and

then to adjust the derived figures to equal the total population fore­

cast by the ~IAP model. This approach compensates in a gross way for local

differences but still insures that the sum of local population allocation

equals the total forecast for the entire Southcentral region. Unfortu­

nately, there is a conceptual difficulty involved with this approach that

arises from the use of local population/employment ratios. An example

illustrates the problem: The procedure implies that a new plant would have

different local population impacts depending on whether it was located in

Cordova or Kenai, which may or may not be reasonable. The main difficulty

involves the fact that the derived populations for each census division

are adjµsted to equal the same total regional population in each case.

A change in the location of the plant would thus have an artificially im­

posed impact on the population of each census division, e.g., Kodiak,

which seems most unreasonable.

The best solution to this problem would likely involve the use of

industry-specific population to employment ratios. This information is

not available; moreover, local differences in the ratios could be expected.

The partial solution utilized here sidestepped the issue by using area­

specific population ratios (adjusting local estimates to sum to regional

-17-

totals) for the "base case" or low-growth scenario. Incremental popula­

tion between the low and high growth scenarios was then allocated propor-:­

tionately to the incremental employment between the two scenarios. Local

considerations thus play a role in the population allocation, while

locational decisions concerning major growth-inducing projects do not have

any arbitrary impacts on other census divisions. Differences in location

will only have a differential population impact on the specific locations

involved and on the Anchorage/Mat-Su areas.

The table on the following page shows historical population/employ­

ment ratios for each of the census divisions. The ratio of population to

employment was very low in Anchorage and extremely high in the Mat-Su

area. A special procedure for separating Anchorage and Mat-Su population

is outlined in Step 5; for the purposes of this section, they have been

treated as a single entity.

The two census divisions most dependent on fishing and fish process­

ing (Cordova and Kodiak) had very low population to employment ratios,

which appears to be characteristic of those industries. On the other

hand; ratios for Seward, Kenai, and pre-pipeline Valdez were similar and

generally fairly high.

The population estimates are derived figures, computed after an

analysis of other data such as employment and school enrollments. Since

some of the estimates can be questioned, average ratios for seven years

(1970-76) were utilized in the allocation of future population. Census

divisions with similar population to employment ratios were grouped

POPULATION/EMPLOYMENT RATIOS

Total Kenai,

Total Combined Valdez- Kenai- Seward, South- Matanuska- Anchorage/ Chitina- Cook Cordova- Cordova, central Anchora~ Susitna Mat-Su Whittier Inlet Seward McCarthy Kodiak Kodiak

1968 2.9 2.8 6.5 2.9 3.3 2.5 4.7 3.5 3.0 2.9

1969 2.8 2.6 7.0 2.8 3.0 3.2 4.1 3.1 3.4 3.3

1970 2.9 2.7 5.7 2.8 3.7 3.8 3.2 2.6 3.2 3.5

1971 2.9 2.7 5.2 2.7 2.7 4.0 3.3 2.9 3.2 3.6

1972 2.9 2.7 5.8 2.8 3.9 3.6 2.9 2.5 2.8 3.2 I

r'"" 00

1973 2.8 2.7 5.3 2.8 3.6 3.4 2.8 2.2 2.3 2.8 I

1974 2.5 2.4 5.5 2.5 2.5 3.1 2.9 2.1 2.3 2.7

1975 2.5 2.4 6.2 2.5 2.1 2.8 2.7 2.0 2.1 2.5

1976 2.4 2.4 6.2 2.5 1. 7 2.6 3.0 2.2 L9 2.4

Average of 1970-76 Ratios 2.7 2.6 5.7 2.7 2.9 3.3 3.0 2.4 2.5 3.0

-19-

together and the same ratio used for each member of the group to further

smooth out any unreliable fluctuations. The population allocation method

involved the following:

(1) Low-growth scenario:

(a) multiply Anchorage/Mat-Su new employment by 2.7 (seven­

year average ratio) and add to baseline population;

(b) multiply Cordova and Kodiak new employment by 2.45 (un­

weighted average ratio for the two census divisions) and

add to baseline population;

(c) multiply Valdez, Kenai, and Seward new employment by 3.16

(average ratio for the divisions, excluding post-pipeline

Valdez, with 1974-76 Kenai and Seward ratios weighted to

replace this exclusion) and add to baseline population; and

(d) proportionately adjust population figures to equal regional

total.

(2) High-growth scenario:

(a) determine distribution of employment increases over low­

growth scenario; and

(b) allocate population increase over low-growth scenario pro­

portionately to employment increase.

Step 5: Disaggretation of Combined Anchorage and Matanuska-Susitna Civilian Employment and Population

The MAP regional model provides the capability for separate forecasts

for Anchorage and for the remaining Southcentral region. Unfortunateiy,

the model does not adequately reflect the shift of population and supporting

-20-

economic.activity from Anchorage to the Hatanuska-Susitna valleys, which

is essentially a suburbanization phenomenon.

The· table on the following page presents historical data concerning

population and employment in the Matanuska-Susitna area and their relation-

ship to corresponding values in Anchorage. Total employment in the Mat-Su

census division has beeri very consistently equal to a percentage of

Anchorage employment (about 3 percent). In calculating various regres­

sion equations, Anchorage employment was the best estimator of Mat-Su

employment (r 2=.96); the regression line also had a slope of about 3 per-

cent. This regression equation was utilized to disaggregate Anchorage and

Mat-Su employment. The equation was converted into the following form

appropriate to the task of disaggregation:

MAT-SU EMPLOYMENT= .0303 x COMBINED MAT-SU & ANCHORAGE EMPLOYMENT - 59.7

While total Mat-Su employment is a good predictor of Mat-Su popula­

tion (r 2=.97), Anchorage civilian population is an even better estimator

(r 2=.99). This supports the concept that the Matanuska-Susitna population

is essentially a residential spillover from Anchorage and is a function

of the Anchorage population. The high ratio of population to employment

in the area, the relative lack of basic employment, and the relatively

large amount of commuting to Anchorage indicate that much of the economic

activity in the area operates to support the population and is derivative

of the population base. The equation utilized to predict Mat-Su population

(on the basis of Anchorage population) is expressed in the following form

-21-

when used to disaggregate combined population:

MAT-SU POPULATION= .11048 x COMBINED MAT-SU &

ANCHORAGE CIVILIAN POPULATION - 6917

MATANUSKA-SUSITNA CENSUS DIVISION: EMPLOYMENT AND POPULATION: COMPARISON WITH ANCHORAGE

Ratio % of Anchorage Census Division Civilian Population/ Basic

PoEulation Em:eJ.oyment EmEloyment Po:eulation Em:eloyment Em:eloyrnent

1970 6,503 1,145 5.68 5.7 2.7 2.2

1971 7,737 1,414 5.47 6.0 3.1 2.4

1972 8,366 1,445 5.79 6.4 3.0 1. 6

1973 8,586 1,607 5.34 6.3 3.2 1.5

1974 9,787 1,784 5.49 7.0 3.0 1.6

1975 12,462 2,022 6.16 7.5 2.9 1.9

1976 14,010 2,269 6.17 8.6 3.1 1.8

Average (weighted) = 5. 77 6.9 3.0 1.9

REGRESSION EQUATIONS

Dependent Independent r2 Variable Variable Eguation

Matanuska-Susitna Anchorage Total Employment Total Employment • 963 y = -61. 6 + . 03125X

Natanuska-Susitna Anchorage Non-Basic Employment Total Employment .835 y = 25 + .025ox

Matanuska-Susitna Anchorage Non-Basic Employment Total Employment .730 y = 310 - • 0296X

Matanuska-Susitna Matanuska-Susitna Population Total Employment .969 y = -1815 + 6.859X

Natanuska-Susitna Anchorage Civilian Population Population .990 y = -7776 + .1242X

Matanuska-Susitna Anchorage Resident Population Population .986 y = -9851 + .1269X

-22-

Step 6: Addition of MilitaryEmployment and Population

Military employment is assumed to be equal to military population

(military dependents are included with the civilian population) and is

assumed to remain constant over the forecast period. Hence, total popu­

lation and employment figures for each census division are derived by

adding a single constant term to both civilian employment and population

for all years in each census division. Assumed military populations and

employment are based on the following 1976 estimates:

Census Division

Anchorage

Matanuska-Susitna

Kenai

Seward

Kodiak

Cordova

Valdez

Military Population

12,129

0

53

15

866

53

0

SOURCE: Alaska Department of Labor, Research and Analysis Section.