County Growth Management Population Projections by · PDF file2012 . P. rojections. County...

Forecasting Division

august 2012

state oF Washington

oFFice oF Financial ManageMent

County Growth Management Population Projections by Age and Sex: 2010-2040

2012 Projections

To accommodate persons with disabilities, this document is available in alternative formats by calling the Office of Financial Management at 360-902--0599. TTY/TDD users should contact OFM via the Washington Relay Service at 711 or 1-800-833-6388. This publication and other current and historical demographic data are available electronically.

Visit our website at www.ofm.wa.gov

Acknowledgements

The Forecasting Division of the Office of Financial Management (OFM) prepared this report. Primary staff responsible for the Growth Management Act (GMA) projections was Yi Zhao. Staff assisting the project and publication include Erica Gardner and Webb Sprague.

The GMA projections benefited from the participation of many individuals and agencies during both the preparation and review process. Special thanks are due to the Department of Commerce Growth Management Office, who provided OFM with outreach opportunities. We would also like to express our sincere appreciation to the state and regional transportation planning staffs and the economic development council representatives who provided data and expertise in both the preparation and review stages of the GMA process.

Any questions regarding this publication should be directed to the Forecasting Division at 360-902-0599; email: [email protected].

mailto:[email protected]

2012 Projections

County Growth Management Population Projections by Age and Sex: 2010-2040

Forecasting Division

august 2012

Washington state

oFFice oF Financial ManageMent

TABLE OF CONTENTS Overview ............................................................................................................................................................... iii

Growth Management Act Population Projections: 2010-2040 ........................................................................ 1

Section I. Washington State Population Forecast: 2010-2040 ................................................................ 1 General Discussion ....................................................................................................................................... 1 Figure 1. State Population Forecast Comparison: Total Population ............................................................ 1 Figure 2. State Population Forecast Comparison: Net Migration ................................................................. 2 Table 1. Forecasted Net Migration: 2007 GMA versus 2012 GMA ............................................................ 2 Figure 3. State Population Forecast: Natural Increase ................................................................................ 3 Discussion of Assumptions ............................................................................................................................ 3 Table 2. State Population Forecast Comparison: Data Inputs .................................................................... 4 Table 3. Population and Components of Population Change: 2000 to 2040 .............................................. 5

Section II. County Population Projections: 2010 to 2040 .......................................................................... 6 General Discussion ....................................................................................................................................... 6 Table 4. Projected Versus Actual 2010 Population and Projections for 2030 ............................................ 6 Figure 4. Population Pyramids: Franklin County .......................................................................................... 7 Figure 5. Actual and Projected Births and Deaths: Franklin County ............................................................ 7 Figure 6. Population Pyramids: Jefferson County ........................................................................................ 8 Figure 7. Actual and Projected Births and Deaths: Jefferson County .......................................................... 8 Discussion of County Projection Assumptions .............................................................................................. 8 Figure 8. 2010 Total Fertility Rates by County ............................................................................................. 10 Discussion of High and Low Projection Alternatives ..................................................................................... 11

Section III. State and County Growth Profiles ............................................................................................. 13 Section IV. Final Projections of the Total Resident Population for the Growth Management Act:

2010-2040 ..................................................................................................................................... 94 High Series .................................................................................................................................................... 94 Medium Series ............................................................................................................................................... 95 Low Series ..................................................................................................................................................... 96

Section V. Projections of the Total Resident Population for the Growth Management Act: 2010 to 2040 by Single Year After 2015 .................................................................................................. 97

High Series .................................................................................................................................................... 98 Medium Series ............................................................................................................................................... 100 Low Series ..................................................................................................................................................... 102

Appendix A: Data Concepts ............................................................................................................................... 104 Appendix B: Historical Data ............................................................................................................................... 105

Historical and Projected Population for Growth Management and Other Purposes ..................................... 105 Historical and Projected Net Migration for Growth Management and Other Purposes ................................ 107

Appendix C: Population Age 65 and Over ........................................................................................................ 109 Population Age 65 and Over .................................................................................................................... 109 Population Age 65 and Over as a Percent of Total County Population ................................................... 110

Appendix D: RCW 43.62.035 Determining Population -- Projections ............................................................. 111

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Overview Development of population projections for the Growth Management Act (GMA) is a shared responsibility. Pursuant to RCW 43.62.035, this document contains county population projections prepared by the Office of Financial Management (OFM) for growth management planning. State and county populations are provided at five-year intervals between 2010 and 2040. The additional single year interval projections between 2015 and 2040 were developed to accommodate the various GMA planning targets specified by counties. The GMA projections present high, medium, and low growth expectations for each county. As indicated in RCW 36.70A.110 and RCW 36.70A.115, local officials are responsible for selecting a 20-year GMA planning target that is within the high and low growth projections prepared by OFM. If the county shows population dynamics that would invalidate the GMA projections before the next set of GMA projections is performed, the county may petition OFM to make changes to their forecast. The GMA county population projections are developed with a “top down” procedure. The 2012 GMA county projections are developed within the framework of November 2011 Washington state forecast of population, births, deaths, and migration. The top down approach is used because at the state level more data is available, the population dynamics are more stable, and projections have been demonstrated to be more accurate. Such an approach makes the county-level forecasts better. Total populations and components of change for each county over the projection period are reconciled with the total state population projection for each five-year time interval. Note that independently developed county projections, even using the same methods and assumptions, would not match the 2012 GMA projections because they would not be controlled to the state projection. Why are low, medium and high series needed? Projections are statements about the future based on a particular set of assumptions. The medium series is considered the most likely because it is the best foreseeable future based on assumptions that have been validated with past and current information. However, assumptions may not hold true if factors influencing population growth should change. Thus, uncertainty should be considered while using those projections for planning purposes. Caution is recommended when users see variation between current population estimates and long term projections. Users should consider allowing long term projections time to “play out” before changing them. Often, migration or fertility may seem to change dramatically for a year or two, but such changes usually return to a longer term trend within a few years. However, if significant structural changes occur with high demographic impact – such as the recent recession – adjustment to forecasts should be considered within the high and low framework.

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Growth Management Act Population Projections: 2010-2040 Section I: Washington State Population Forecast: 2010-2040 General Discussion:

The November 2011 state population forecast is developed with a cohort-component model, which projects the state future births, deaths and net migration separately based on a set of validated assumptions. Compared to the state forecast used in the 2007 Growth Management Act (GMA) county population projections, the November 2011 forecast projects lower population growth between 2010 and 2040, delaying the 2007 expectations by approximately five years. This decline is the result of the severe recession that occurred after the 2007 GMA release and subsequent adjustments made to the fertility, mortality and migration assumptions in response to recessionary impacts on population growth patterns. Figure 1. State Population Forecast Comparison: Total Population

Washington’s net migration is expected to be less than what OFM anticipated in 2007. Migration is the most variable – and the most difficult – demographic component to measure and predict. During the first decade of the 21st century, Washington experienced two recessions with pronounced effects on state migration and projections. The collapse of the dot-com bubble brought the state net migration level down to about 33,000 in 2003, but migration quickly rebounded and peaked in 2006 with nearly 84,000 migrants. The 2007 GMA forecast was produced in the middle of a housing boom, and short-term migration assumptions were predicted to be only moderately lower than the peak numbers that gradually blended into the long-term average of 48,100 in 2015.

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Figure 2. State Population Forecast Comparison: Net Migration

The crash of the financial and housing markets in the last quarter of 2007 led to the “great recession,” marked by the highest unemployment rates since 1983 and a severe housing market correction. Lack of employment opportunities nationwide resulted in a decline of migration in most states that continues to today. Furthermore, because of falling home prices, many homeowners have gone “underwater” and are unwilling to sell their homes at a loss even if a good job is available elsewhere. Between 2005 and 2010, Washington witnessed 125,000 fewer (36 %) net migrants than expected in the 2007 state forecast. Net migration continued to drop and hit bottom with 4,800 net migrants in 2011 due to continuing high unemployment nationwide. The new forecast expects the state to gradually gain economic strength and to start to attract more migrants, but the slow pace of the economic recovery affects the short-term migration projection. For the 2010 to 2015 period, the anticipated net migration to Washington state has been adjusted down by 154,000 persons from the 2007 forecast, from 259,000 to 104,900. Also, this drop in short-term migration will influence long-term population growth through changes to the age structure and subsequent effects on total fertility and mortality. Table 1. Forecasted Net Migration: 2007 GMA versus 2012 GMA

GMA 2007 GMA 2012 Numerical Difference

Percent Difference

2005-2010 347,057 222,154 -124,903 -36.0% 2010-2015 259,000 104,909 -154,091 -59.5% 2015-2020 240,500 210,000 -30,500 -12.7% 2020-2025 240,500 217,000 -23,500 -9.8% 2025-2030 240,500 225,000 -15,500 -6.4% Washington’s natural increase is likely to decline more than forecasted in 2007. The recent recession also affects people’s decisions regarding marriage and childbearing. Beginning in 2006, the children of the boomers started reaching childbearing age and the number of births in Washington began to increase. This high level of births, referred to by demographers as the “third wave” of the baby boom, was expected to remain high for some time. Fertility patterns started to change in 2009 as women began having fewer children. Even though the current decline in total fertility rates (TFR) from 2.02 in 2008 to 1.93 in 2011 may not form a long-term trend, this recession-related baby bust will lead to another cycle of low number of births 15 or 20 years from now when those babies grow up and are ready to have families.

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OFFICE OF FINANCIAL MANAGEMENT

With the first of the baby boomers turning 65 in 2011, Washington state’s population will become increasingly older (in aggregate) each year, affecting the dynamics of “natural increase”. This aging process will change the age structure of the state, and the increase of elderly population will accelerate until the last of the boomers turn 65 in 2029. The aging population will likely cause a decline in the overall number of births due to a smaller proportion of women at childbearing age. At the same time, an elderly population with a higher risk of dying will contribute to a rising number of deaths (note that people’s life expectancy is expected to increase slowly in the future, but older ages will still die much faster than younger ages). Consequently, the population change due to natural increase – the excess of births over deaths – will decline. Figure 3. State Population Forecast: Natural Increase

Discussion of Assumptions:

Detailed descriptions about the assumptions used in the November 2011 state forecast can be found online at http://www.ofm.wa.gov/pop/stfc/default.asp. The following table is a brief comparison of the changes made between the 2007 and 2011 releases with respect to the demographic components of population change (mortality, fertility and migration). The life expectancy has been adjusted slightly upward based on the Social Security Administration intermediate mortality projections. The long-term TFR has not been adjusted because we do not know if there has been a structural change in Washington women’s fertility behavior, or whether the recent drop in the TFR is a short-term response to the recessionary environment. Migration is much more variable than natural increase. Washington, as seen in the migration graph (Figure 2), has tended to exhibit growth spurts interrupted by periods of slower growth, stagnation, and sometimes even decline – largely due to migration. One example is the well-known “Boeing Bust” of the early 1970s that affected the central Puget Sound area. Another example is the “rural rebound” and influx of Hispanic residents experienced in the early 1990s – rural and nonmetropolitan growth in Washington during the early 1990s was far greater than anticipated, but slowed in the mid-1990s. At present there is a high degree of uncertainty as to future population growth due to the lack of any clear

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WASHINGTON STATE COUNTY POPULATION PROJECTIONS

http://www.ofm.wa.gov/pop/stfc/default.asp

indication of when the economy will fully recover; and due to possible long-term changes in U.S. immigration policy and their effect on international migration. Therefore, aside from the near-term migration produced by the state econometric model, no attempt is made to predict the timing and magnitude of any significant migration rebound. While migration is expected to gradually increase as the state economic situation improves, short term-growth patterns are blended into general trends. Long-term migration expectations have been adjusted downwards from the annual expectation of 48,100 persons specified in the 2007 forecast to 45,000 per year after 2015. Table 2. State Population Forecast Comparison: Data Inputs Specific Input

November 2011 Forecast

July 2007 Forecast

1. Base census 2010 2000 2. Estimates of annual population growth and migration based on actual symptomatic data through:

April 1, 2011 April 1, 2007

3. Net migration based on an econometric model input relating Washington’s migration to traded sector employment change in Washington, California, and the rest of the nation. Source and date of employment forecasts:

· Economic & Revenue Forecast Council (Washington) · Global Insight. Inc. (California & rest of the nation)

October, 2011 Long range migration anticipation: 45,000

June 2007 Long range migration anticipation: 48,100

4. Actual vital events: · Births · Deaths

2010 to 2011 2010 to 2011

2000 to 2005 2000 to 2005

5. Forecast average lifetime births per woman: 2015 to 2040 Constant at about 2.0

2006 to 2030 Constant at about 2.0

6. Forecast life expectancy in years: · Male · Female

In 2011 Forecast 2010 2040

76.7 yrs 79.5 yrs 82.1 yrs 84.5 yrs

In 2007 Forecast 2006 2030

75.5 yrs 78.0 yrs 81.4 yrs 83.7 yrs

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Table 3. Population and Components of Population Change: 2000 to 2040 Population ------------------Components of Change from Previous Period------------------ at End of Population Change Births Deaths Natural Net Migration Period Number Percent Number Rate Number Rate Increase Number Rate 2000-2001 5,970,330 76,187 1.28 80,732 13.61 43,923 7.40 36,809 39,378 6.64 2001-2002 6,059,316 88,986 1.48 79,291 13.18 44,900 7.46 34,391 54,595 9.08 2002-2003 6,126,885 67,569 1.11 79,069 12.98 44,732 7.34 34,337 33,232 5.45 2003-2004 6,208,515 81,630 1.32 80,957 13.13 46,025 7.46 34,932 46,698 7.57 2004-2005 6,298,816 90,301 1.44 81,845 13.09 45,623 7.30 36,222 54,079 8.65 2000-2005 404,673 401,894 225,203 176,691 227,982 2005-2006 6,420,258 121,442 1.91 83,170 13.08 45,277 7.12 37,893 83,549 13.14 2006-2007 6,525,086 104,828 1.62 87,752 13.56 46,161 7.13 41,591 63,237 9.77 2007-2008 6,608,245 83,159 1.27 89,568 13.64 47,947 7.30 41,621 41,538 6.33 2008-2009 6,672,159 63,914 0.96 89,838 13.53 48,116 7.25 41,722 22,192 3.34 2009-2010 6,724,540 52,381 0.78 88,408 13.20 47,665 7.12 40,743 11,638 1.74 2005-2010 425,724 438,736 235,166 203,570 222,154 2010-2011 6,767,900 43,360 0.64 86,547 12.83 47,996 7.11 38,551 4,809 0.71 2011-2012 6,816,600 48,700 0.72 87,500 12.88 48,900 7.20 38,600 10,100 1.49 2012-2013 6,875,900 59,300 0.87 88,700 12.96 49,900 7.29 38,800 20,500 2.99 2013-2014 6,944,700 68,800 1.00 90,000 13.02 51,500 7.45 38,500 30,300 4.38 2014-2015 7,022,200 77,500 1.11 91,300 13.07 53,000 7.59 38,300 39,200 5.61 2010-2015 297,660 444,047 251,296 192,751 104,909 2015-2016 7,100,451 78,251 1.11 91,856 13.01 55,605 7.87 36,251 42,000 5.95 2016-2017 7,178,675 78,224 1.10 92,684 12.98 56,460 7.91 36,224 42,000 5.88 2017-2018 7,256,835 78,160 1.08 93,496 12.95 57,336 7.94 36,160 42,000 5.82 2018-2019 7,334,646 77,811 1.07 94,095 12.90 58,284 7.99 35,811 42,000 5.76 2019-2020 7,411,977 77,331 1.05 94,621 12.83 59,290 8.04 35,331 42,000 5.70 2015-2020 389,777 466,752 286,975 179,777 210,000 2020-2021 7,489,586 77,609 1.04 95,066 12.76 60,457 8.11 34,609 43,000 5.77 2021-2022 7,566,384 76,798 1.02 95,544 12.69 61,746 8.20 33,798 43,000 5.71 2022-2023 7,642,316 75,932 1.00 96,042 12.63 63,110 8.30 32,932 43,000 5.65 2023-2024 7,717,276 74,960 0.98 96,547 12.57 64,587 8.41 31,960 43,000 5.60 2024-2025 7,793,173 75,897 0.98 97,019 12.51 66,122 8.53 30,897 45,000 5.80 2020-2025 381,196 480,218 316,022 164,196 217,000 2025-2026 7,867,861 74,688 0.95 97,414 12.44 67,726 8.65 29,688 45,000 5.75 2026-2027 7,941,330 73,469 0.93 97,858 12.38 69,389 8.78 28,469 45,000 5.69 2027-2028 8,013,600 72,270 0.91 98,394 12.33 71,124 8.92 27,270 45,000 5.64 2028-2029 8,084,539 70,939 0.88 98,971 12.30 73,032 9.07 25,939 45,000 5.59 2029-2030 8,154,193 69,654 0.86 99,555 12.26 74,901 9.22 24,654 45,000 5.54 2025-2030 361,020 492,192 356,172 136,020 225,000 2030-2031 8,222,550 68,357 0.83 100,169 12.23 76,812 9.38 23,357 45,000 5.50 2031-2032 8,289,815 67,265 0.81 100,810 12.21 78,545 9.51 22,265 45,000 5.45 2032-2033 8,355,592 65,777 0.79 101,517 12.20 80,740 9.70 20,777 45,000 5.41 2033-2034 8,420,097 64,505 0.77 102,288 12.19 82,783 9.87 19,505 45,000 5.36 2034-2035 8,483,628 63,531 0.75 103,099 12.20 84,568 10.01 18,531 45,000 5.32 2030-2035 329,435 507,883 403,448 104,435 225,000 2035-2036 8,546,278 62,650 0.74 103,934 12.21 86,284 10.13 17,650 45,000 5.28 2036-2037 8,608,251 61,973 0.72 104,819 12.22 87,846 10.24 16,973 45,000 5.25 2037-2038 8,669,660 61,409 0.71 105,744 12.24 89,335 10.34 16,409 45,000 5.21 2038-2039 8,730,526 60,866 0.70 106,672 12.26 90,806 10.44 15,866 45,000 5.17 2039-2040 8,790,981 60,455 0.69 107,602 12.28 92,147 10.52 15,455 45,000 5.14 2035-2040 307,353 528,771 446,418 82,353 225,000 2010-2040 2,066,441 2,919,863 2,060,331 859,532 1,206,909 Notes: Rates computed per 1,000 population at midpoint of time period. Unrounded data should not be considered accurate to the last digit.

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Section II. County Population Projections: 2010 to 2040 General Discussion:

Three sets of county population projections are provided: a high series, an intermediate series, and a low series. The high and low series generally reflect assumptions as to the uncertainty regarding growth over the next 30 years. These assumptions are based on the historical high and low decade migration patterns for each county and on current factors affecting the economic base and attractiveness of specific areas in the state. The alternative series are a means of taking the fundamental unpredictability of long-range projections into account. This section mainly focuses on the assumptions and population growth projected in the middle series.

Census 2010 counts were used as the benchmark for the 2012 projections. Rebasing the GMA projections to the most recent decennial census changes the “jump off” point of both the population totals and the population age structure. When a projection begins with fewer people, the subsequent population will be lower, all other things equal. Additionally, when a different age structure interacts with similar fertility, mortality, and migration rates, population outcomes can be very different. Table 4 shows the difference in the projected and actual 2010 populations for select counties and the state as a whole as well as the difference in the projected 2030 population. Table 4. Projected Versus Actual 2010 Population and Projections for 2030

GMA 2007 Projection

for 2010 Census

2010 Numerical Difference

Percent Difference

GMA 2007 Projection

for 2030

GMA 2012 Projection

for 2030 Numerical Difference

Percent Difference

Benton 168,839 175,177 6,338 3.8% 198,528 223,689 25,161 11.2% Franklin 70,038 78,163 8,125 11.6% 109,861 130,284 20,423 15.7% Pierce 836,688 795,225 -41,463 -5.0% 1,050,953 967,601 -83,352 -8.6% Snohomish 725,963 713,335 -12,628 -1.7% 950,066 908,807 -41,259 -4.5% State 6,792,318 6,724,540 -67,778 -1.0% 8,509,161 8,154,193 -354,968 -4.4% Some counties are “older” than others, and therefore are impacted more by the aging process. Natural increase varies significantly between counties with balanced age cohorts and those with larger elderly population. Franklin County, for example, has a very young age structure and will continue its population momentum throughout the projection horizon because much of its population growth is due to natural increase (see Figures 4 and 5). On the other hand, over 56 percent of the population in Jefferson County is 50 years old and over. Since older individuals tend to have very low fertility rates and high mortality rates, Jefferson County is expected to lose population due to “natural decrease” -- the excess of deaths over births (see Figures 6 and 7).

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Figure 4. Population Pyramids: Franklin County

Figure 5. Actual and Projected Births and Deaths: Franklin County

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Figure 6. Population Pyramids: Jefferson County

Figure 7. Actual and Projected Births and Deaths: Jefferson County

Migration to Washington is not evenly distributed among all counties, with some counties showing negative net migration. A county will typically see net in-migration if it: (1) has large amounts of employment, (2) serves as a retirement destination, or (3) serves as a bedroom community for an employment center. It has been more evident in the 2010 census that rural and remote counties without a solid economic base or infrastructure for retirement communities are unlikely to attract movers or sustain current population levels. Counties such as Columbia, Garfield, and Wahkiakum are likely to see population loss due to zero or negative net migration. Discussion of County Projection Assumptions:

County projections are developed using a version of the standard cohort-component approach to projecting population as discussed in the state methodology section. Cohort-component simply

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means that populations are disaggregated into age-sex groups and moved forward through time using specific rates of fertility, mortality and migration for each projection interval. In the present case for the county projections, the age ranges and projection intervals are both five years. Annual rates for single-year age ranges are too variable to use for populations of less than 500,000. Middle series county projections are developed within the framework of the previously discussed state projection. County populations and components of population change were compared and reconciled to the statewide age-sex, birth, death, and net migration projections for each five-year interval from 2010 to 2040. Annual county projections are derived by interpolation between the interval endpoints and then forcing county data to sum to the state projection that is developed on a single-year basis. Fertility: Considerable variation exists in the 2010 TFRs across counties (see Figure 8). At the same time relatively consistent trends over time are found in the majority of the counties. Numerous studies on fertility show that certain demographic characteristics influence women’s fertility behavior. Immigrants tend to have higher TFRs than native born women. Hispanic women, in particular, tend to have the highest TFRs, compared to those who have come from Asian or European countries. Second generation Hispanic women tend to have lower TFRs than the first generation but still higher than other racial/ethnic groups. Women attending college, in the labor force, or with higher educational attainment tend to have lower TFRs than their counterparts. TFRs tend to be low in counties with a high proportion of females in their pre-retirement and retirement years relative to females in their childbearing years. These findings are used to understand the changes in each county’s TFR over time and are utilized with historical trends to determine future county TFRs. In general:

· Counties with large Hispanic populations where at least 40 percent or more of the Hispanic population is foreign born have TFRs higher than 2.7. Such trends are expected to continue with moderate decline likely over the forecast horizon assuming the proportion of foreign born Hispanic declines as evidenced already in the 2006-2010 American Community Survey.

· Counties with a high proportion of the population attending college have the lowest TFRs and are expected to stay low in the future.

· Counties that historically have low TFRs due to a proportionally large number of young women either attending college or professional women in labor force are likely to stay constant over the forecast period for these counties.

· Rural counties with relatively larger retirement population or counties with multiple diverse characteristics make generalizations difficult. With minor adjustments, the TFRs for these counties are held constant at their 2010 levels.

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Figure 8. 2010 Total Fertility Rates by County

Mortality: The projected life expectancy at birth, i.e., the average number of years a person is expected to live from age 0, is used to estimate the number of deaths each county will experience. The 2012 GMA projection of Washington counties’ mortality is based on 2010 national life expectancy released by the Center for Disease Control in its 2010 Health Report. In general, life expectancy has been increasing since the early 20th century. Based on historical trends, we made several adjustments so that the national life expectancy is more likely to reflect Washington and its counties’ mortality experiences. Using the U.S. life expectancy as a base, we add 0.1 to the base year because Washington historically has shown 1 to 1.5 years higher life expectancies than the U.S. per decade. Historically, life expectancy is lower for black populations and higher for Hispanic populations. At the county level, if 25 percent of the population is Hispanic, life expectancy is adjusted up by 1.2 years at the base year. Research at

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WhitmanSan Juan

KittitasWhatcom

KingAsotin

ThurstonJefferson

SkamaniaSpokane

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StateSnohomish

ClallamKitsapPierceClark

IslandPacificCowlitzMason

Grays HarborColumbia

KlickitatBenton

WahkiakumSkagit

StevensLincoln

LewisGarfieldDouglas

Pend OreilleChelan

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GrantFranklinAdams

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the national level has consistently shown that those people with higher education tend to live longer than their counterparts. We increased the life expectancy by 0.75 at the base year for counties where over 31 percent of the population has a bachelor’s degree or more. The life expectancies for counties with less than 18 percent of the population with a bachelor’s degree or more were declined by 0.75 at the base year. Migration: The middle series of the county projections are based on a set of broad propositions that relate to migration as the main driver of population change for the state and counties. Decade migration patterns for each county from 1980 through 2010 are also used to project future migration. General tendencies are based on: (1) 1980-2010 trends in relative population growth and (2) a set of assumptions that is both grounded in past experience and that seems reasonable, given what is known about the economic, demographic, and social character of each of the 39 counties. These assumptions are:

· In general, the 2012 GMA county migration distribution assumptions still agree with those in the 2007 GMA forecast. The metro and urban centers and areas with good accessibility to transportation routes will continue to be magnets for population growth.

· Areas that have sustained growth due to retirement and telecommuting migration will continue this pattern.

· Furthermore, with the increase of oldest old population, retirement migration to rural counties, for economic and quality of life reasons, may decline as the oldest old return to metro areas for better social and health services.

· Over the last two decades, about 70 percent of Washington’s net migration came from abroad. The majority of these immigrants came to Washington through the family reunification program and settled in counties where their families were located. This trend is expected to continue. Counties with the larger numbers of immigrants and sustainable domestic migration are expected to increase their migration share.

· The current recessionary environment has an inevitable impact on all counties’ net migration. In general, it is expected that the 2007 migration expectations for counties will be pushed off for five years for the majority of the counties. For the others, some recover a little faster, but if counties had negative or little migration historically, they may never have migration at levels forecasted in the 2007 GMA projections.

The “population centers” noted above are Seattle, Spokane, Yakima, Tri-Cities, and Portland. Growth assumptions for individual counties are largely manifested in the migration numbers presented in the tables. In practice, the assumptions are not rigidly applied, but serve as guidelines for modifying various migration and population share trends out towards the projection horizon. Discussion of High and Low Projection Alternatives:

GMA specifications require that county projections be expressed as a “reasonable” range. County high and low projection alternatives actually reflect uncertainty bands. As noted, they are not, in a formal sense, alternative scenarios. In general, the uncertainty bands will be larger for smaller counties than large ones. They will be larger for faster growing than slower growing areas. They will be larger for counties with erratic growth in the past and smaller for counties that have had steadier growth. They will be larger for counties that may be impacted by changes

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in variable military, college, correctional, or other special populations. These uncertain factors are reflected in the “high” and “low” growth ranges. For example, Kittitas and Whitman counties have wide ranges because of the uncertainty of how and where increasing university enrollments in Washington will be accommodated. Both series sum to statewide low and high projections similar to the medium series. Annual projections for the years 2010 through 2040 are provided on OFM’s website (http://www.ofm.wa.gov/pop/gma/projections12/projections12.asp) to accommodate the various target years used for GMA planning.

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http://www.ofm.wa.gov/pop/gma/projections12/projections12.asp

Section III. State and County Growth Profiles A two-page population profile is provided for the state and each county. These profiles are developed from the intermediate population series and contain age/gender detail. Graphs are included showing high, medium, and low growth expectations.

13


Washington State Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 6,724,540 3,349,707 3,374,833 7,022,200 3,499,254 3,522,946 7,411,977 3,692,485 3,719,492 0-4 439,657 225,088 214,569 446,684 228,543 218,141 473,872 242,481 231,391 5-9 429,877 219,702 210,175 450,041 230,522 219,519 466,355 238,585 227,770 10-14 438,233 224,717 213,516 440,743 225,296 215,447 465,487 238,488 226,999 15-19 462,128 237,577 224,551 448,030 229,558 218,472 453,203 231,545 221,658 20-24 461,512 238,131 223,381 480,140 247,111 233,029 470,158 240,365 229,793 25-29 480,398 245,014 235,384 476,277 244,426 231,851 509,009 260,905 248,104 30-34 453,383 229,863 223,520 493,786 251,491 242,295 498,963 255,568 243,395 35-39 448,607 226,850 221,757 452,280 228,603 223,677 507,696 258,248 249,448 40-44 459,698 232,587 227,111 464,336 234,536 229,800 458,761 231,393 227,368 45-49 492,909 246,507 246,402 460,049 231,763 228,286 467,044 235,365 231,679 50-54 495,296 245,997 249,299 500,091 249,028 251,063 459,405 230,640 228,765 55-59 453,078 221,321 231,757 488,420 240,520 247,900 494,369 244,639 249,730 60-64 382,087 186,378 195,709 432,199 209,288 222,911 476,760 232,371 244,389 65-69 270,474 131,064 139,410 349,136 168,245 180,891 414,735 197,988 216,747 70-74 186,746 88,760 97,986 238,292 113,571 124,721 324,305 153,231 171,074 75-79 142,068 64,325 77,743 159,040 73,046 85,994 208,699 96,389 112,310 80-84 111,118 45,743 65,375 113,038 48,592 64,446 126,514 55,355 71,159 85+ 117,271 40,083 77,188 129,618 45,115 84,503 136,642 48,929 87,713


2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 8,790,981 4,368,634 4,422,347 2010-15 297,660 444,047 251,296 104,909 0-4 533,920 273,234 260,686 2015-20 389,777 466,752 286,975 210,000 5-9 535,624 274,082 261,542 2020-25 381,196 480,218 316,022 217,000 10-14 538,240 275,480 262,760 2025-30 361,020 492,192 356,172 225,000 15-19 540,759 276,636 264,123 2030-35 329,435 507,883 403,448 225,000 20-24 550,016 280,813 269,203 2035-40 307,353 528,771 446,418 225,000 25-29 549,207 279,297 269,910 30-34 555,835 282,454 273,381 35-39 542,004 274,430 267,574 40-44 544,172 275,786 268,386 45-49 559,556 284,877 274,679 50-54 523,460 266,010 257,450 55-59 513,106 257,798 255,308 60-64 447,555 221,357 226,198 65-69 435,771 213,032 222,739 70-74 401,055 192,573 208,482 75-79 385,891 178,504 207,387 80-84 309,118 136,191 172,927 85+ 325,692 126,080 199,612

14


2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

9,000,000

10,000,000

11,000,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Washington State

Census / OFM Estimate

2012 GMA High

2012 GMA Medium

2012 GMA Low

15


Adams Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 18,728 9,544 9,184 20,257 10,337 9,920 21,640 11,067 10,573 0-4 2,015 1,071 944 2,270 1,156 1,114 2,393 1,224 1,169 5-9 1,811 924 887 2,067 1,105 962 2,326 1,196 1,130 10-14 1,647 831 816 1,856 947 909 2,077 1,105 972 15-19 1,649 907 742 1,628 847 781 1,774 929 845 20-24 1,261 664 597 1,387 743 644 1,318 663 655 25-29 1,242 612 630 1,395 719 676 1,522 804 718 30-34 1,256 627 629 1,304 651 653 1,417 737 680 35-39 1,144 587 557 1,237 617 620 1,287 644 643 40-44 1,055 553 502 1,182 607 575 1,234 617 617 45-49 1,037 520 517 1,048 550 498 1,154 592 562 50-54 1,003 488 515 1,026 518 508 1,014 530 484 55-59 957 489 468 956 468 488 991 502 489 60-64 736 345 391 857 437 420 869 424 445 65-69 599 328 271 631 298 333 771 401 370 70-74 449 220 229 494 266 228 531 240 291 75-79 336 157 179 368 173 195 397 216 181 80-84 267 132 135 261 119 142 275 128 147 85+ 264 89 175 290 116 174 290 115 175

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 22,964 11,758 11,206 24,289 12,439 11,850 25,690 13,176 12,514 0-4 2,442 1,256 1,186 2,529 1,300 1,229 2,684 1,381 1,303 5-9 2,426 1,246 1,180 2,471 1,266 1,205 2,564 1,318 1,246 10-14 2,311 1,186 1,125 2,422 1,243 1,179 2,465 1,269 1,196 15-19 1,970 1,074 896 2,193 1,149 1,044 2,298 1,206 1,092 20-24 1,438 734 704 1,626 863 763 1,801 916 885 25-29 1,463 712 751 1,596 800 796 1,800 938 862 30-34 1,575 836 739 1,501 746 755 1,642 833 809 35-39 1,412 742 670 1,557 829 728 1,476 736 740 40-44 1,274 639 635 1,373 725 648 1,521 812 709 45-49 1,192 595 597 1,246 622 624 1,341 711 630 50-54 1,111 569 542 1,156 575 581 1,194 596 598 55-59 950 497 453 1,050 538 512 1,109 558 551 60-64 895 455 440 869 460 409 957 496 461 65-69 760 374 386 797 410 387 786 421 365 70-74 677 355 322 651 321 330 681 347 334 75-79 440 195 245 564 292 272 545 252 293 80-84 307 159 148 332 140 192 428 221 207 85+ 321 134 187 356 160 196 398 165 233

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 27,205 13,966 13,239 2010-15 1,529 2,272 589 -154 0-4 2,878 1,482 1,396 2015-20 1,383 2,399 637 -379 5-9 2,723 1,402 1,321 2020-25 1,324 2,458 659 -475 10-14 2,559 1,319 1,240 2025-30 1,325 2,578 694 -559 15-19 2,332 1,230 1,102 2030-35 1,401 2,767 728 -638 20-24 1,888 963 925 2035-40 1,515 2,989 772 -702 25-29 2,006 1,016 990 30-34 1,815 954 861 35-39 1,618 818 800 40-44 1,454 722 732 45-49 1,481 794 687 50-54 1,291 675 616 55-59 1,118 560 558 60-64 1,008 511 497 65-69 867 456 411 70-74 688 365 323 75-79 574 296 278 80-84 425 194 231 85+ 480 209 271

16


7,500

10,000

12,500

15,000

17,500

20,000

22,500

25,000

27,500

30,000

32,500

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Adams County


2012 GMA High

2012 GMA Medium

2012 GMA Low

17


Asotin Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 21,623 10,453 11,170 21,818 10,607 11,211 22,033 10,749 11,284 0-4 1,261 627 634 1,082 559 523 1,090 558 532 5-9 1,335 660 675 1,302 648 654 1,105 567 538 10-14 1,273 666 607 1,370 678 692 1,309 654 655 15-19 1,395 713 682 1,289 677 612 1,365 680 685 20-24 1,188 580 608 1,052 519 533 989 503 486 25-29 1,245 571 674 1,174 586 588 1,240 619 621 30-34 1,168 585 583 1,291 600 691 1,215 603 612 35-39 1,096 536 560 1,178 588 590 1,303 605 698 40-44 1,214 576 638 1,148 562 586 1,173 589 584 45-49 1,536 744 792 1,229 582 647 1,115 541 574 50-54 1,650 775 875 1,568 758 810 1,197 563 634 55-59 1,613 794 819 1,642 765 877 1,545 737 808 60-64 1,477 708 769 1,614 795 819 1,674 781 893 65-69 1,267 614 653 1,436 692 744 1,636 818 818 70-74 1,043 524 519 1,191 586 605 1,427 703 724 75-79 776 360 416 957 478 479 1,086 530 556 80-84 570 238 332 651 297 354 795 392 403 85+ 516 182 334 644 237 407 769 306 463

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 22,196 10,864 11,332 22,313 10,945 11,368 22,358 10,981 11,377 0-4 1,104 566 538 1,104 562 542 1,084 555 529 5-9 1,135 577 558 1,142 592 550 1,168 595 573 10-14 1,136 579 557 1,149 591 558 1,181 602 579 15-19 1,330 667 663 1,162 600 562 1,184 608 576 20-24 1,049 504 545 1,034 506 528 911 459 452 25-29 1,151 585 566 1,235 593 642 1,192 586 606 30-34 1,308 659 649 1,228 630 598 1,294 625 669 35-39 1,215 612 603 1,314 658 656 1,242 642 600 40-44 1,292 600 692 1,216 608 608 1,323 662 661 45-49 1,146 577 569 1,303 605 698 1,207 604 603 50-54 1,123 551 572 1,144 571 573 1,293 594 699 55-59 1,194 554 640 1,096 527 569 1,150 570 580 60-64 1,572 757 815 1,201 558 643 1,144 555 589 65-69 1,684 787 897 1,598 773 825 1,240 586 654 70-74 1,635 833 802 1,674 793 881 1,601 782 819 75-79 1,309 641 668 1,514 770 744 1,551 731 820 80-84 882 420 462 1,074 520 554 1,247 630 617 85+ 931 395 536 1,125 488 637 1,346 595 751

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 22,356 10,993 11,363 2010-15 195 1,082 1,133 246 0-4 1,043 535 508 2015-20 215 1,077 1,345 483 5-9 1,130 579 551 2020-25 163 1,080 1,519 602 10-14 1,213 616 597 2025-30 117 1,086 1,680 711 15-19 1,228 636 592 2030-35 45 1,057 1,822 810 20-24 943 468 475 2035-40 -2 1,014 1,921 905 25-29 1,038 521 517 30-34 1,288 631 657 35-39 1,341 653 688 40-44 1,270 656 614 45-49 1,334 673 661 50-54 1,228 614 614 55-59 1,301 602 699 60-64 1,184 589 595 65-69 1,164 569 595 70-74 1,236 588 648 75-79 1,494 740 754 80-84 1,282 579 703 85+ 1,639 744 895

18


10,000

12,500

15,000

17,500

20,000

22,500

25,000

27,500

30,000

32,500

35,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Asotin County


2012 GMA High

2012 GMA Medium

2012 GMA Low

19


Benton Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 175,177 87,486 87,691 184,882 92,388 92,494 197,806 98,800 99,006 0-4 13,071 6,706 6,365 12,862 6,584 6,278 13,959 7,148 6,811 5-9 13,081 6,743 6,338 13,691 7,033 6,658 13,816 7,072 6,744 10-14 13,350 6,880 6,470 13,722 7,085 6,637 14,590 7,499 7,091 15-19 12,914 6,642 6,272 13,348 6,958 6,390 13,837 7,226 6,611 20-24 10,955 5,533 5,422 10,740 5,335 5,405 11,175 5,632 5,543 25-29 11,972 6,097 5,875 12,721 6,405 6,316 12,499 6,184 6,315 30-34 11,066 5,570 5,496 13,048 6,728 6,320 14,276 7,265 7,011 35-39 10,672 5,362 5,310 11,382 5,731 5,651 13,919 7,183 6,736 40-44 11,062 5,455 5,607 11,264 5,669 5,595 11,832 5,953 5,879 45-49 12,443 6,119 6,324 11,207 5,514 5,693 11,534 5,801 5,733 50-54 12,624 6,323 6,301 12,710 6,237 6,473 11,330 5,556 5,774 55-59 11,759 5,913 5,846 12,336 6,141 6,195 12,500 6,105 6,395 60-64 9,622 4,858 4,764 11,054 5,515 5,539 11,897 5,868 6,029 65-69 6,787 3,332 3,455 8,748 4,374 4,374 10,572 5,215 5,357 70-74 4,728 2,281 2,447 5,955 2,861 3,094 8,096 3,966 4,130 75-79 3,546 1,576 1,970 4,041 1,886 2,155 5,227 2,437 2,790 80-84 2,747 1,156 1,591 2,864 1,203 1,661 3,263 1,459 1,804 85+ 2,778 940 1,838 3,189 1,129 2,060 3,484 1,231 2,253

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 210,803 105,173 105,630 223,689 111,482 112,207 236,007 117,526 118,481 0-4 14,741 7,547 7,194 15,418 7,893 7,525 16,010 8,203 7,807 5-9 14,954 7,654 7,300 15,780 8,078 7,702 16,447 8,422 8,025 10-14 14,690 7,528 7,162 15,883 8,131 7,752 16,705 8,553 8,152 15-19 14,680 7,632 7,048 14,793 7,667 7,126 15,932 8,248 7,684 20-24 11,669 5,890 5,779 12,477 6,278 6,199 12,553 6,307 6,246 25-29 12,968 6,491 6,477 13,477 6,766 6,711 14,342 7,181 7,161 30-34 14,090 7,062 7,028 14,596 7,407 7,189 15,088 7,669 7,419 35-39 15,188 7,748 7,440 15,002 7,539 7,463 15,502 7,874 7,628 40-44 14,459 7,458 7,001 15,710 8,009 7,701 15,533 7,805 7,728 45-49 12,101 6,087 6,014 14,773 7,609 7,164 15,996 8,140 7,856 50-54 11,643 5,840 5,803 12,211 6,126 6,085 14,890 7,663 7,227 55-59 11,150 5,451 5,699 11,498 5,750 5,748 12,078 6,065 6,013 60-64 12,076 5,842 6,234 10,757 5,196 5,561 11,081 5,474 5,607 65-69 11,347 5,518 5,829 11,560 5,524 6,036 10,317 4,916 5,401 70-74 9,783 4,719 5,064 10,507 4,997 5,510 10,739 5,022 5,717 75-79 7,111 3,376 3,735 8,621 4,033 4,588 9,269 4,268 5,001 80-84 4,208 1,867 2,341 5,760 2,625 3,135 7,032 3,138 3,894 85+ 3,945 1,463 2,482 4,866 1,854 3,012 6,493 2,578 3,915

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 247,856 123,380 124,476 2010-15 9,705 12,703 6,251 3,253 0-4 16,626 8,516 8,110 2015-20 12,924 13,638 7,283 6,569 5-9 17,074 8,743 8,331 2020-25 12,997 14,413 8,219 6,803 10-14 17,413 8,918 8,495 2025-30 12,886 15,108 9,276 7,054 15-19 16,752 8,671 8,081 2030-35 12,318 15,774 10,493 7,037 20-24 13,553 6,802 6,751 2035-40 11,849 16,455 11,617 7,011 25-29 14,389 7,190 7,199 30-34 15,972 8,090 7,882 35-39 15,989 8,147 7,842 40-44 16,043 8,151 7,892 45-49 15,844 7,947 7,897 50-54 16,115 8,190 7,925 55-59 14,785 7,626 7,159 60-64 11,650 5,766 5,884 65-69 10,656 5,206 5,450 70-74 9,612 4,492 5,120 75-79 9,527 4,317 5,210 80-84 7,566 3,323 4,243 85+ 8,290 3,285 5,005

20


50,000

75,000

100,000

125,000

150,000

175,000

200,000

225,000

250,000

275,000

300,000

325,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Benton County


2012 GMA High

2012 GMA Medium

2012 GMA Low

21


Chelan Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 72,453 36,130 36,323 75,180 37,531 37,649 78,586 39,256 39,330 0-4 4,915 2,577 2,338 5,219 2,674 2,545 5,525 2,832 2,693 5-9 4,864 2,517 2,347 5,049 2,653 2,396 5,403 2,768 2,635 10-14 5,072 2,554 2,518 4,977 2,579 2,398 5,155 2,710 2,445 15-19 5,202 2,668 2,534 5,098 2,611 2,487 4,971 2,615 2,356 20-24 4,260 2,239 2,021 4,093 2,015 2,078 3,974 1,948 2,026 25-29 4,309 2,229 2,080 4,780 2,489 2,291 4,802 2,361 2,441 30-34 4,098 2,058 2,040 4,502 2,359 2,143 4,998 2,634 2,364 35-39 4,082 2,004 2,078 4,083 2,046 2,037 4,552 2,385 2,167 40-44 4,291 2,151 2,140 4,203 2,063 2,140 4,094 2,058 2,036 45-49 5,034 2,487 2,547 4,326 2,158 2,168 4,231 2,069 2,162 50-54 5,523 2,699 2,824 5,209 2,564 2,645 4,366 2,168 2,198 55-59 5,214 2,627 2,587 5,629 2,724 2,905 5,278 2,575 2,703 60-64 4,414 2,205 2,209 5,209 2,608 2,601 5,728 2,738 2,990 65-69 3,237 1,588 1,649 4,246 2,134 2,112 5,248 2,643 2,605 70-74 2,582 1,272 1,310 2,908 1,415 1,493 4,040 2,023 2,017 75-79 1,961 927 1,034 2,207 1,060 1,147 2,540 1,201 1,339 80-84 1,562 658 904 1,548 693 855 1,765 812 953 85+ 1,833 670 1,163 1,894 686 1,208 1,916 716 1,200

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 81,885 40,884 41,001 84,778 42,299 42,479 87,168 43,468 43,700 0-4 5,673 2,911 2,762 5,673 2,908 2,765 5,680 2,910 2,770 5-9 5,712 2,924 2,788 5,873 3,005 2,868 5,872 3,005 2,867 10-14 5,519 2,825 2,694 5,822 2,984 2,838 5,988 3,068 2,920 15-19 5,129 2,728 2,401 5,478 2,846 2,632 5,783 3,007 2,776 20-24 3,860 1,952 1,908 4,028 2,069 1,959 4,337 2,170 2,167 25-29 4,623 2,270 2,353 4,521 2,281 2,240 4,672 2,390 2,282 30-34 5,024 2,508 2,516 4,852 2,404 2,448 4,739 2,421 2,318 35-39 5,053 2,662 2,391 5,076 2,538 2,538 4,925 2,452 2,473 40-44 4,567 2,393 2,174 5,043 2,657 2,386 5,094 2,544 2,550 45-49 4,099 2,053 2,046 4,574 2,391 2,183 5,053 2,658 2,395 50-54 4,288 2,093 2,195 4,148 2,071 2,077 4,619 2,407 2,212 55-59 4,435 2,185 2,250 4,336 2,079 2,257 4,183 2,049 2,134 60-64 5,410 2,620 2,790 4,585 2,259 2,326 4,518 2,186 2,332 65-69 5,771 2,769 3,002 5,437 2,651 2,786 4,637 2,300 2,337 70-74 5,017 2,512 2,505 5,512 2,633 2,879 5,197 2,517 2,680 75-79 3,576 1,747 1,829 4,470 2,189 2,281 4,923 2,292 2,631 80-84 2,007 908 1,099 2,908 1,371 1,537 3,664 1,731 1,933 85+ 2,122 824 1,298 2,442 963 1,479 3,284 1,361 1,923

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 89,246 44,485 44,761 2010-15 2,727 5,186 3,357 898 0-4 5,861 3,005 2,856 2015-20 3,406 5,462 3,600 1,544 5-9 5,881 3,013 2,868 2020-25 3,299 5,614 3,802 1,487 10-14 6,008 3,077 2,931 2025-30 2,893 5,613 4,190 1,470 15-19 5,971 3,108 2,863 2030-35 2,390 5,636 4,677 1,431 20-24 4,595 2,302 2,293 2035-40 2,078 5,814 5,168 1,432 25-29 5,005 2,506 2,499 30-34 4,896 2,535 2,361 35-39 4,804 2,454 2,350 40-44 4,927 2,445 2,482 45-49 5,119 2,552 2,567 50-54 5,113 2,683 2,430 55-59 4,663 2,382 2,281 60-64 4,374 2,152 2,222 65-69 4,587 2,237 2,350 70-74 4,449 2,196 2,253 75-79 4,656 2,220 2,436 80-84 4,058 1,813 2,245 85+ 4,279 1,805 2,474

22


30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

110,000

120,000

130,000

140,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Chelan County


2012 GMA High

2012 GMA Medium

2012 GMA Low

23


Clallam Population Projection: Intermediate Series



2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 77,224 38,239 38,985 2010-15 464 3,273 4,696 1,887 0-4 3,523 1,797 1,726 2015-20 1,748 3,316 5,116 3,548 5-9 3,683 1,877 1,806 2020-25 1,406 3,341 5,471 3,536 10-14 3,851 1,963 1,888 2025-30 1,090 3,322 5,837 3,605 15-19 4,418 2,402 2,016 2030-35 674 3,331 6,208 3,551 20-24 3,644 2,056 1,588 2035-40 438 3,382 6,488 3,544 25-29 3,723 1,960 1,763 30-34 3,865 2,079 1,786 35-39 3,758 1,883 1,875 40-44 4,194 2,083 2,111 45-49 3,897 1,926 1,971 50-54 4,565 2,290 2,275 55-59 4,624 2,345 2,279 60-64 4,883 2,498 2,385 65-69 4,983 2,518 2,465 70-74 4,626 2,249 2,377 75-79 5,060 2,257 2,803 80-84 4,794 2,113 2,681 85+ 5,133 1,943 3,190

24


20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Clallam County


2012 GMA High

2012 GMA Medium

2012 GMA Low

25


Clark Population Projection: Intermediate Series




26


0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Clark County


2012 GMA High

2012 GMA Medium

2012 GMA Low

27


Columbia Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 4,078 2,022 2,056 4,047 1,999 2,048 4,013 1,972 2,041 0-4 216 115 101 204 103 101 220 108 112 5-9 197 100 97 223 120 103 206 100 106 10-14 247 116 131 201 102 99 225 122 103 15-19 230 118 112 236 116 120 179 100 79 20-24 158 76 82 225 102 123 217 96 121 25-29 182 94 88 152 75 77 226 111 115 30-34 166 92 74 171 91 80 146 71 75 35-39 193 89 104 156 91 65 178 90 88 40-44 229 124 105 196 91 105 147 85 62 45-49 324 158 166 242 130 112 198 94 104 50-54 306 154 152 329 159 170 229 119 110 55-59 342 171 171 287 140 147 321 153 168 60-64 351 178 173 330 163 167 296 145 151 65-69 305 144 161 339 168 171 322 159 163 70-74 222 119 103 290 136 154 328 162 166 75-79 149 68 81 212 112 100 266 122 144 80-84 116 52 64 113 50 63 157 79 78 85+ 145 54 91 141 50 91 152 56 96


2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 3,700 1,785 1,915 2010-15 -31 193 255 31 0-4 207 107 100 2015-20 -34 210 284 40 5-9 229 120 109 2020-25 -45 218 310 47 10-14 233 122 111 2025-30 -73 216 346 57 15-19 224 122 102 2030-35 -95 209 364 60 20-24 185 90 95 2035-40 -00 204 365 61 25-29 171 89 82 30-34 191 101 90 35-39 166 83 83 40-44 222 95 127 45-49 214 104 110 50-54 144 71 73 55-59 154 75 79 60-64 146 73 73 65-69 177 76 101 70-74 203 102 101 75-79 299 134 165 80-84 210 91 119 85+ 325 130 195

28


3,000

3,250

3,500

3,750

4,000

4,250

4,500

4,750

5,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Columbia County


2012 GMA High

2012 GMA Medium

2012 GMA Low

29


Cowlitz Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 102,410 50,542 51,868 105,130 51,808 53,322 108,588 53,390 55,198 0-4 6,564 3,274 3,290 6,478 3,315 3,163 6,928 3,544 3,384 5-9 6,760 3,370 3,390 6,738 3,364 3,374 6,728 3,440 3,288 10-14 6,994 3,593 3,401 6,921 3,456 3,465 6,864 3,427 3,437 15-19 7,157 3,656 3,501 6,460 3,322 3,138 6,353 3,174 3,179 20-24 5,683 2,820 2,863 6,095 3,035 3,060 5,449 2,726 2,723 25-29 5,702 2,837 2,865 6,636 3,294 3,342 7,141 3,553 3,588 30-34 5,956 2,975 2,981 5,921 2,974 2,947 6,905 3,458 3,447 35-39 6,140 3,061 3,079 5,919 2,957 2,962 5,997 3,021 2,976 40-44 6,420 3,189 3,231 6,320 3,154 3,166 5,899 2,942 2,957 45-49 7,237 3,632 3,605 6,467 3,189 3,278 6,339 3,139 3,200 50-54 7,837 3,947 3,890 7,439 3,705 3,734 6,494 3,185 3,309 55-59 7,342 3,644 3,698 7,899 3,917 3,982 7,479 3,677 3,802 60-64 6,813 3,341 3,472 7,246 3,539 3,707 7,958 3,878 4,080 65-69 5,173 2,557 2,616 6,439 3,142 3,297 7,155 3,473 3,682 70-74 3,618 1,760 1,858 4,609 2,241 2,368 6,019 2,891 3,128 75-79 2,728 1,258 1,470 3,045 1,435 1,610 3,998 1,883 2,115 80-84 2,117 885 1,232 2,134 935 1,199 2,391 1,075 1,316 85+ 2,169 743 1,426 2,364 834 1,530 2,491 904 1,587



30


50,000

75,000

100,000

125,000

150,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Cowlitz County


2012 GMA High

2012 GMA Medium

2012 GMA Low

31


Douglas Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 38,431 19,198 19,233 40,603 20,302 20,301 43,619 21,819 21,800 0-4 2,803 1,434 1,369 2,824 1,442 1,382 3,099 1,586 1,513 5-9 2,832 1,418 1,414 2,917 1,497 1,420 3,011 1,542 1,469 10-14 2,956 1,540 1,416 2,963 1,482 1,481 3,086 1,583 1,503 15-19 2,895 1,504 1,391 2,799 1,464 1,335 2,834 1,428 1,406 20-24 2,192 1,141 1,051 2,531 1,287 1,244 2,450 1,250 1,200 25-29 2,360 1,209 1,151 2,548 1,322 1,226 2,950 1,487 1,463 30-34 2,344 1,151 1,193 2,544 1,316 1,228 2,834 1,487 1,347 35-39 2,342 1,159 1,183 2,395 1,173 1,222 2,699 1,401 1,298 40-44 2,318 1,150 1,168 2,455 1,222 1,233 2,479 1,214 1,265 45-49 2,591 1,301 1,290 2,334 1,150 1,184 2,516 1,246 1,270 50-54 2,685 1,345 1,340 2,651 1,323 1,328 2,371 1,168 1,203 55-59 2,514 1,239 1,275 2,659 1,315 1,344 2,639 1,309 1,330 60-64 2,156 1,066 1,090 2,464 1,214 1,250 2,689 1,326 1,363 65-69 1,747 869 878 2,066 1,017 1,049 2,505 1,221 1,284 70-74 1,291 640 651 1,662 826 836 2,059 1,013 1,046 75-79 1,008 487 521 1,150 559 591 1,503 742 761 80-84 701 298 403 831 396 435 935 435 500 85+ 696 247 449 810 297 513 960 381 579

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 46,662 23,360 23,302 49,583 24,828 24,755 52,256 26,178 26,078 0-4 3,335 1,706 1,629 3,483 1,785 1,698 3,553 1,814 1,739 5-9 3,303 1,694 1,609 3,533 1,814 1,719 3,686 1,883 1,803 10-14 3,174 1,619 1,555 3,470 1,778 1,692 3,702 1,897 1,805 15-19 2,945 1,513 1,432 3,016 1,553 1,463 3,287 1,682 1,605 20-24 2,475 1,207 1,268 2,583 1,297 1,286 2,627 1,322 1,305 25-29 2,851 1,450 1,401 2,860 1,394 1,466 2,990 1,492 1,498 30-34 3,265 1,673 1,592 3,137 1,604 1,533 3,127 1,551 1,576 35-39 2,970 1,567 1,403 3,418 1,750 1,668 3,271 1,688 1,583 40-44 2,775 1,447 1,328 3,043 1,597 1,446 3,501 1,805 1,696 45-49 2,514 1,233 1,281 2,816 1,463 1,353 3,086 1,626 1,460 50-54 2,538 1,255 1,283 2,527 1,232 1,295 2,834 1,459 1,375 55-59 2,368 1,160 1,208 2,522 1,227 1,295 2,488 1,194 1,294 60-64 2,669 1,316 1,353 2,406 1,179 1,227 2,575 1,271 1,304 65-69 2,723 1,337 1,386 2,714 1,340 1,374 2,445 1,190 1,255 70-74 2,510 1,229 1,281 2,727 1,347 1,380 2,747 1,357 1,390 75-79 1,878 904 974 2,316 1,121 1,195 2,521 1,235 1,286 80-84 1,240 589 651 1,564 734 830 1,938 913 1,025 85+ 1,129 461 668 1,448 613 835 1,878 799 1,079


32


10,000

20,000

30,000

40,000

50,000

60,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Douglas County


2012 GMA High

2012 GMA Medium

2012 GMA Low

33


Ferry Population Projection: Intermediate Series



2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 7,692 3,925 3,767 2010-15 68 316 381 133 0-4 349 179 170 2015-20 87 333 445 199 5-9 379 196 183 2020-25 45 338 519 226 10-14 402 201 201 2025-30 3 339 574 238 15-19 556 316 240 2030-35 -14 339 623 270 20-24 380 207 173 2035-40 -48 337 650 265 25-29 342 170 172 30-34 439 221 218 35-39 417 237 180 40-44 469 217 252 45-49 438 234 204 50-54 481 259 222 55-59 424 222 202 60-64 386 215 171 65-69 407 217 190 70-74 404 185 219 75-79 476 233 243 80-84 408 184 224 85+ 535 232 303

34


2,000

4,000

6,000

8,000

10,000

12,000

14,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Ferry County


2012 GMA High

2012 GMA Medium

2012 GMA Low

35


Franklin Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 78,163 40,447 37,716 87,755 45,321 42,434 100,926 52,494 48,432 0-4 8,297 4,251 4,046 8,758 4,486 4,272 9,880 5,060 4,820 5-9 7,699 3,935 3,764 8,782 4,506 4,276 9,529 4,883 4,646 10-14 6,912 3,572 3,340 8,176 4,185 3,991 9,502 4,875 4,627 15-19 6,214 3,218 2,996 6,764 3,548 3,216 8,246 4,346 3,900 20-24 5,645 2,986 2,659 5,695 2,973 2,722 6,671 3,724 2,947 25-29 6,482 3,416 3,066 6,409 3,325 3,084 6,835 3,669 3,166 30-34 6,187 3,264 2,923 7,125 3,748 3,377 7,376 3,869 3,507 35-39 5,464 2,824 2,640 6,401 3,355 3,046 7,697 4,027 3,670 40-44 4,683 2,542 2,141 5,841 3,025 2,816 6,758 3,545 3,213 45-49 4,278 2,206 2,072 4,784 2,589 2,195 6,043 3,119 2,924 50-54 4,078 2,111 1,967 4,404 2,269 2,135 4,891 2,644 2,247 55-59 3,734 1,980 1,754 4,001 2,056 1,945 4,370 2,244 2,126 60-64 2,794 1,435 1,359 3,538 1,861 1,677 3,884 1,980 1,904 65-69 1,948 974 974 2,558 1,302 1,256 3,423 1,783 1,640 70-74 1,342 675 667 1,722 850 872 2,392 1,197 1,195 75-79 993 463 530 1,160 567 593 1,526 724 802 80-84 780 330 450 803 355 448 946 440 506 85+ 633 265 368 834 321 513 957 365 592

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 115,142 60,028 55,114 130,284 67,662 62,622 146,103 75,614 70,489 0-4 11,042 5,664 5,378 12,148 6,241 5,907 13,316 6,843 6,473 5-9 10,764 5,521 5,243 12,080 6,203 5,877 13,194 6,781 6,413 10-14 10,330 5,298 5,032 11,711 6,018 5,693 13,045 6,706 6,339 15-19 9,714 5,177 4,537 10,592 5,628 4,964 11,899 6,321 5,578 20-24 8,227 4,632 3,595 9,532 5,307 4,225 10,285 5,693 4,592 25-29 7,583 4,164 3,419 8,981 4,826 4,155 10,430 5,569 4,861 30-34 7,631 3,983 3,648 8,335 4,375 3,960 9,864 5,106 4,758 35-39 7,879 4,057 3,822 8,098 4,095 4,003 8,813 4,497 4,316 40-44 8,133 4,258 3,875 8,347 4,302 4,045 8,528 4,318 4,210 45-49 7,018 3,676 3,342 8,474 4,437 4,037 8,635 4,445 4,190 50-54 6,191 3,201 2,990 7,206 3,774 3,432 8,648 4,526 4,122 55-59 4,866 2,629 2,237 6,190 3,199 2,991 7,176 3,754 3,422 60-64 4,272 2,176 2,096 4,796 2,579 2,217 6,084 3,111 2,973 65-69 3,776 1,898 1,878 4,154 2,092 2,062 4,691 2,500 2,191 70-74 3,223 1,655 1,568 3,546 1,748 1,798 3,928 1,948 1,980 75-79 2,128 1,033 1,095 2,906 1,456 1,450 3,180 1,521 1,659 80-84 1,245 561 684 1,744 810 934 2,413 1,163 1,250 85+ 1,120 445 675 1,444 572 872 1,974 812 1,162


36


0

25,000

50,000

75,000

100,000

125,000

150,000

175,000

200,000

225,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Franklin County


2012 GMA High

2012 GMA Medium

2012 GMA Low

37


Garfield Population Projection: Intermediate Series




38


0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Garfield County


2012 GMA High

2012 GMA Medium

2012 GMA Low

39


Grant Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 89,120 45,420 43,700 95,822 48,660 47,162 104,078 52,761 51,317 0-4 8,075 4,126 3,949 8,274 4,232 4,042 8,725 4,465 4,260 5-9 7,421 3,733 3,688 8,417 4,307 4,110 8,740 4,472 4,268 10-14 7,350 3,760 3,590 7,733 3,888 3,845 8,801 4,510 4,291 15-19 7,193 3,799 3,394 6,965 3,575 3,390 7,298 3,684 3,614 20-24 6,101 3,338 2,763 6,263 3,230 3,033 6,016 3,003 3,013 25-29 6,008 3,178 2,830 6,312 3,393 2,919 7,290 3,753 3,537 30-34 5,681 2,855 2,826 6,497 3,476 3,021 6,885 3,741 3,144 35-39 5,492 2,781 2,711 5,790 2,914 2,876 6,769 3,628 3,141 40-44 5,180 2,692 2,488 5,773 2,925 2,848 5,920 2,980 2,940 45-49 5,429 2,778 2,651 5,297 2,731 2,566 5,896 2,977 2,919 50-54 5,396 2,748 2,648 5,644 2,873 2,771 5,402 2,772 2,630 55-59 4,935 2,504 2,431 5,510 2,763 2,747 5,768 2,897 2,871 60-64 4,328 2,135 2,193 4,941 2,477 2,464 5,607 2,767 2,840 65-69 3,469 1,765 1,704 4,144 2,036 2,108 4,935 2,462 2,473 70-74 2,383 1,169 1,214 3,136 1,579 1,557 3,908 1,884 2,024 75-79 1,982 953 1,029 2,015 953 1,062 2,759 1,358 1,401 80-84 1,409 630 779 1,579 721 858 1,590 713 877 85+ 1,288 476 812 1,532 587 945 1,769 695 1,074

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 112,525 56,957 55,568 121,204 61,227 59,977 129,779 65,433 64,346 0-4 9,200 4,717 4,483 9,809 5,028 4,781 10,277 5,274 5,003 5-9 9,194 4,717 4,477 9,700 4,972 4,728 10,318 5,290 5,028 10-14 9,132 4,681 4,451 9,594 4,919 4,675 10,090 5,174 4,916 15-19 8,323 4,277 4,046 8,644 4,448 4,196 9,064 4,663 4,401 20-24 6,331 3,117 3,214 7,253 3,639 3,614 7,508 3,774 3,734 25-29 6,969 3,467 3,502 7,322 3,592 3,730 8,349 4,174 4,175 30-34 7,975 4,154 3,821 7,631 3,844 3,787 7,947 3,947 4,000 35-39 7,141 3,887 3,254 8,319 4,355 3,964 7,913 3,996 3,917 40-44 6,915 3,707 3,208 7,289 3,968 3,321 8,492 4,443 4,049 45-49 6,042 3,024 3,018 7,046 3,765 3,281 7,415 4,024 3,391 50-54 6,016 3,020 2,996 6,169 3,073 3,096 7,188 3,817 3,371 55-59 5,520 2,799 2,721 6,154 3,054 3,100 6,306 3,102 3,204 60-64 5,895 2,918 2,977 5,660 2,830 2,830 6,328 3,096 3,232 65-69 5,631 2,772 2,859 5,925 2,921 3,004 5,716 2,855 2,861 70-74 4,693 2,308 2,385 5,371 2,608 2,763 5,664 2,762 2,902 75-79 3,414 1,597 1,817 4,160 2,000 2,160 4,766 2,249 2,517 80-84 2,219 1,049 1,170 2,722 1,217 1,505 3,362 1,556 1,806 85+ 1,915 746 1,169 2,436 994 1,442 3,076 1,237 1,839


40


25,000

50,000

75,000

100,000

125,000

150,000

175,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Grant County


2012 GMA High

2012 GMA Medium

2012 GMA Low

41


Grays Harbor Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 72,797 37,357 35,440 73,575 37,952 35,623 74,408 38,396 36,012 0-4 4,260 2,136 2,124 4,125 2,108 2,017 4,147 2,120 2,027 5-9 4,141 2,073 2,068 4,355 2,185 2,170 4,225 2,159 2,066 10-14 4,493 2,304 2,189 4,231 2,115 2,116 4,413 2,212 2,201 15-19 4,770 2,499 2,271 4,717 2,406 2,311 4,410 2,207 2,203 20-24 4,312 2,364 1,948 4,007 2,288 1,719 3,888 2,154 1,734 25-29 4,294 2,347 1,947 4,535 2,604 1,931 4,527 2,502 2,025 30-34 4,266 2,361 1,905 4,284 2,288 1,996 4,496 2,534 1,962 35-39 4,216 2,296 1,920 4,114 2,232 1,882 4,179 2,188 1,991 40-44 4,390 2,354 2,036 4,272 2,308 1,964 4,031 2,164 1,867 45-49 5,176 2,682 2,494 4,348 2,316 2,032 4,213 2,263 1,950 50-54 5,707 2,879 2,828 5,267 2,725 2,542 4,313 2,301 2,012 55-59 5,634 2,842 2,792 5,990 3,038 2,952 5,499 2,866 2,633 60-64 5,289 2,607 2,682 5,650 2,874 2,776 6,118 3,129 2,989 65-69 3,933 2,020 1,913 4,782 2,340 2,442 5,342 2,702 2,640 70-74 2,936 1,443 1,493 3,351 1,694 1,657 4,293 2,059 2,234 75-79 2,022 975 1,047 2,420 1,144 1,276 2,803 1,378 1,425 80-84 1,509 628 881 1,530 706 824 1,845 824 1,021 85+ 1,449 547 902 1,597 581 1,016 1,666 634 1,032

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 75,529 39,090 36,439 76,428 39,555 36,873 76,905 39,786 37,119 0-4 4,230 2,163 2,067 4,313 2,207 2,106 4,344 2,221 2,123 5-9 4,272 2,185 2,087 4,405 2,258 2,147 4,482 2,296 2,186 10-14 4,317 2,211 2,106 4,385 2,245 2,140 4,516 2,312 2,204 15-19 4,659 2,358 2,301 4,641 2,392 2,249 4,741 2,448 2,293 20-24 3,736 2,073 1,663 3,960 2,187 1,773 3,943 2,225 1,718 25-29 4,441 2,413 2,028 4,145 2,215 1,930 4,395 2,338 2,057 30-34 4,555 2,469 2,086 4,490 2,360 2,130 4,185 2,157 2,028 35-39 4,427 2,450 1,977 4,499 2,372 2,127 4,439 2,271 2,168 40-44 4,122 2,129 1,993 4,374 2,401 1,973 4,440 2,317 2,123 45-49 3,990 2,139 1,851 4,103 2,123 1,980 4,351 2,386 1,965 50-54 4,202 2,263 1,939 4,016 2,158 1,858 4,110 2,123 1,987 55-59 4,535 2,441 2,094 4,464 2,425 2,039 4,290 2,340 1,950 60-64 5,629 2,964 2,665 4,663 2,530 2,133 4,563 2,484 2,079 65-69 5,806 2,955 2,851 5,369 2,824 2,545 4,467 2,420 2,047 70-74 4,808 2,400 2,408 5,268 2,648 2,620 4,861 2,519 2,342 75-79 3,647 1,696 1,951 4,093 1,995 2,098 4,504 2,206 2,298 80-84 2,154 1,010 1,144 2,839 1,250 1,589 3,197 1,502 1,695 85+ 1,999 771 1,228 2,401 965 1,436 3,077 1,221 1,856

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 77,070 39,861 37,209 2010-15 778 4,119 3,713 372 0-4 4,346 2,231 2,115 2015-20 833 4,105 4,073 801 5-9 4,515 2,313 2,202 2020-25 1,121 4,171 4,274 1,224 10-14 4,601 2,359 2,242 2025-30 899 4,239 4,693 1,353 15-19 4,877 2,518 2,359 2030-35 477 4,283 5,116 1,310 20-24 4,037 2,288 1,749 2035-40 165 4,290 5,421 1,296 25-29 4,356 2,374 1,982 30-34 4,417 2,273 2,144 35-39 4,136 2,066 2,070 40-44 4,406 2,222 2,184 45-49 4,420 2,299 2,121 50-54 4,369 2,394 1,975 55-59 4,427 2,342 2,085 60-64 4,381 2,381 2,000 65-69 4,387 2,384 2,003 70-74 4,045 2,165 1,880 75-79 4,147 2,095 2,052 80-84 3,544 1,662 1,882 85+ 3,659 1,495 2,164

42


50,000

60,000

70,000

80,000

90,000

100,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Grays Harbor County


2012 GMA High

2012 GMA Medium

2012 GMA Low

43


Island Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 78,506 38,857 39,649 80,337 39,714 40,623 82,735 40,798 41,937 0-4 4,542 2,268 2,274 4,650 2,380 2,270 4,881 2,490 2,391 5-9 4,338 2,274 2,064 4,473 2,218 2,255 4,672 2,375 2,297 10-14 4,518 2,333 2,185 4,213 2,211 2,002 4,415 2,184 2,231 15-19 4,615 2,384 2,231 4,240 2,243 1,997 4,004 2,155 1,849 20-24 5,157 2,901 2,256 5,341 2,927 2,414 4,935 2,739 2,196 25-29 5,023 2,717 2,306 5,567 3,148 2,419 5,732 3,151 2,581 30-34 4,121 2,077 2,044 4,696 2,392 2,304 5,348 2,890 2,458 35-39 4,053 2,026 2,027 3,807 1,889 1,918 4,507 2,264 2,243 40-44 4,412 2,154 2,258 3,692 1,767 1,925 3,387 1,606 1,781 45-49 5,251 2,543 2,708 4,368 2,124 2,244 3,679 1,753 1,926 50-54 5,730 2,646 3,084 5,410 2,604 2,806 4,435 2,143 2,292 55-59 6,206 2,842 3,364 6,354 2,929 3,425 6,015 2,897 3,118 60-64 6,101 2,935 3,166 6,575 3,020 3,555 6,878 3,172 3,706 65-69 4,994 2,360 2,634 5,636 2,693 2,943 6,390 2,902 3,488 70-74 3,500 1,736 1,764 4,340 2,028 2,312 5,142 2,428 2,714 75-79 2,475 1,205 1,270 2,972 1,427 1,545 3,730 1,678 2,052 80-84 1,718 788 930 2,005 935 1,070 2,344 1,079 1,265 85+ 1,752 668 1,084 1,998 779 1,219 2,241 892 1,349



44


0

20,000

40,000

60,000

80,000

100,000

120,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Island County


2012 GMA High

2012 GMA Medium

2012 GMA Low

45


Jefferson Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 29,872 14,798 15,074 30,469 15,033 15,436 32,017 15,718 16,299 0-4 1,068 554 514 1,017 518 499 1,142 585 557 5-9 1,127 556 571 1,118 582 536 1,146 592 554 10-14 1,367 694 673 1,178 587 591 1,248 645 603 15-19 1,354 696 658 1,328 688 640 1,220 620 600 20-24 1,105 619 486 1,210 620 590 1,244 642 602 25-29 1,121 611 510 1,323 742 581 1,422 719 703 30-34 1,197 605 592 1,227 674 553 1,567 890 677 35-39 1,253 649 604 1,202 596 606 1,335 721 614 40-44 1,478 763 715 1,308 667 641 1,274 623 651 45-49 1,942 913 1,029 1,502 767 735 1,369 694 675 50-54 2,561 1,204 1,357 2,050 948 1,102 1,586 792 794 55-59 3,063 1,438 1,625 3,074 1,446 1,628 2,503 1,155 1,348 60-64 3,394 1,616 1,778 3,504 1,664 1,840 3,677 1,746 1,931 65-69 2,852 1,422 1,430 3,267 1,559 1,708 3,612 1,708 1,904 70-74 1,878 959 919 2,554 1,258 1,296 3,117 1,458 1,659 75-79 1,338 700 638 1,575 777 798 2,222 1,066 1,156 80-84 948 477 471 1,046 526 520 1,228 580 648 85+ 826 322 504 986 414 572 1,105 482 623

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 33,678 16,468 17,210 35,657 17,403 18,254 37,914 18,536 19,378 0-4 1,272 647 625 1,345 687 658 1,455 735 720 5-9 1,300 661 639 1,467 748 719 1,616 828 788 10-14 1,291 663 628 1,484 761 723 1,710 867 843 15-19 1,300 695 605 1,371 723 648 1,583 829 754 20-24 1,161 589 572 1,256 664 592 1,321 692 629 25-29 1,458 756 702 1,448 730 718 1,607 853 754 30-34 1,742 892 850 1,842 953 889 1,862 949 913 35-39 1,747 977 770 2,017 1,026 991 2,196 1,128 1,068 40-44 1,439 772 667 1,941 1,078 863 2,283 1,147 1,136 45-49 1,369 667 702 1,558 832 726 2,124 1,167 957 50-54 1,473 732 741 1,468 695 773 1,712 888 824 55-59 1,962 988 974 1,848 910 938 1,873 879 994 60-64 3,013 1,398 1,615 2,433 1,228 1,205 2,308 1,158 1,150 65-69 3,849 1,820 2,029 3,218 1,483 1,735 2,620 1,333 1,287 70-74 3,494 1,626 1,868 3,820 1,778 2,042 3,178 1,438 1,740 75-79 2,734 1,235 1,499 3,151 1,424 1,727 3,478 1,576 1,902 80-84 1,761 798 963 2,185 937 1,248 2,589 1,122 1,467 85+ 1,313 552 761 1,805 746 1,059 2,399 947 1,452

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 40,093 19,708 20,385 2010-15 597 1,008 1,911 1,500 0-4 1,575 800 775 2015-20 1,548 1,083 2,248 2,713 5-9 1,718 878 840 2020-25 1,661 1,178 2,527 3,010 10-14 1,878 957 921 2025-30 1,979 1,239 2,857 3,597 15-19 1,818 949 869 2030-35 2,257 1,301 3,214 4,170 20-24 1,536 796 740 2035-40 2,179 1,411 3,476 4,244 25-29 1,663 870 793 30-34 2,057 1,099 958 35-39 2,195 1,106 1,089 40-44 2,466 1,247 1,219 45-49 2,487 1,240 1,247 50-54 2,345 1,279 1,066 55-59 2,169 1,128 1,041 60-64 2,358 1,129 1,229 65-69 2,494 1,248 1,246 70-74 2,602 1,314 1,288 75-79 2,858 1,249 1,609 80-84 2,863 1,243 1,620 85+ 3,011 1,176 1,835

46


0

10,000

20,000

30,000

40,000

50,000

60,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Jefferson County


2012 GMA High

2012 GMA Medium

2012 GMA Low

47


King Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 1,931,249 962,090 969,159 2,012,782 1,004,091 1,008,691 2,108,814 1,052,126 1,056,688 0-4 120,294 61,616 58,678 122,979 62,919 60,060 127,203 65,071 62,132 5-9 113,295 57,899 55,396 119,274 61,115 58,159 124,058 63,461 60,597 10-14 110,789 56,832 53,957 110,852 56,658 54,194 116,768 59,844 56,924 15-19 117,514 60,118 57,396 115,198 58,040 57,158 115,597 57,922 57,675 20-24 129,822 65,628 64,194 142,056 72,163 69,893 141,466 70,503 70,963 25-29 160,656 81,708 78,948 142,698 72,925 69,773 163,695 84,271 79,424 30-34 152,061 77,549 74,512 165,269 84,582 80,687 148,403 76,238 72,165 35-39 149,158 75,962 73,196 147,119 75,053 72,066 163,499 83,859 79,640 40-44 147,632 75,601 72,031 150,767 76,850 73,917 144,617 73,760 70,857 45-49 147,837 74,745 73,092 144,509 73,765 70,744 147,273 74,950 72,323 50-54 143,295 71,813 71,482 146,783 73,957 72,826 140,420 71,480 68,940 55-59 126,272 61,981 64,291 137,283 68,262 69,021 140,456 70,340 70,116 60-64 101,945 49,447 52,498 115,895 56,267 59,628 128,320 62,984 65,336 65-69 67,317 32,165 35,152 90,143 42,958 47,185 106,940 50,855 56,085 70-74 45,430 20,930 24,500 58,203 27,239 30,964 81,704 37,966 43,738 75-79 35,200 15,485 19,715 38,926 17,310 21,616 50,799 22,975 27,824 80-84 28,948 11,429 17,519 28,602 11,969 16,633 31,059 13,104 17,955 85+ 33,784 11,182 22,602 36,226 12,059 24,167 36,537 12,543 23,994


2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 2,418,850 1,203,837 1,215,013 2010-15 81,533 123,412 60,931 19,052 0-4 142,288 72,822 69,466 2015-20 96,032 126,697 71,671 41,006 5-9 137,498 70,374 67,124 2020-25 87,388 129,821 80,600 38,167 10-14 129,932 66,519 63,413 2025-30 80,958 133,159 89,225 37,024 15-19 131,863 66,178 65,685 2030-35 73,416 137,582 100,150 35,984 20-24 159,867 79,636 80,231 2035-40 68,274 143,014 110,437 35,697 25-29 176,350 88,959 87,391 30-34 176,094 89,424 86,670 35-39 165,833 84,141 81,692 40-44 162,182 82,687 79,495 45-49 159,706 83,134 76,572 50-54 133,498 68,494 65,004 55-59 143,518 72,511 71,007 60-64 122,467 61,292 61,175 65-69 118,596 58,275 60,321 70-74 106,037 51,132 54,905 75-79 96,416 44,439 51,977 80-84 76,323 33,366 42,957 85+ 80,382 30,454 49,928

48


750,000

1,000,000

1,250,000

1,500,000

1,750,000

2,000,000

2,250,000

2,500,000

2,750,000

3,000,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

King County


2012 GMA High

2012 GMA Medium

2012 GMA Low

49


Kitsap Population Projection: Intermediate Series




50


50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Kitsap County


2012 GMA High

2012 GMA Medium

2012 GMA Low

51


Kittitas Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 40,915 20,793 20,122 42,592 21,493 21,099 45,255 22,660 22,595 0-4 2,034 1,029 1,005 2,111 1,079 1,032 2,385 1,218 1,167 5-9 2,040 1,033 1,007 2,100 1,060 1,040 2,329 1,197 1,132 10-14 2,147 1,105 1,042 2,111 1,069 1,042 2,304 1,177 1,127 15-19 3,879 1,929 1,950 3,745 1,887 1,858 3,763 1,893 1,870 20-24 6,822 3,653 3,169 7,713 3,962 3,751 7,467 3,723 3,744 25-29 2,764 1,535 1,229 2,899 1,518 1,381 3,374 1,597 1,777 30-34 2,013 1,009 1,004 1,913 1,032 881 2,140 1,134 1,006 35-39 2,010 1,016 994 2,062 1,033 1,029 2,102 1,129 973 40-44 2,100 1,068 1,032 2,102 1,060 1,042 2,196 1,102 1,094 45-49 2,399 1,191 1,208 2,108 1,066 1,042 2,198 1,113 1,085 50-54 2,673 1,349 1,324 2,456 1,218 1,238 2,190 1,107 1,083 55-59 2,534 1,275 1,259 2,745 1,388 1,357 2,591 1,293 1,298 60-64 2,288 1,140 1,148 2,493 1,256 1,237 2,856 1,456 1,400 65-69 1,808 906 902 2,073 1,028 1,045 2,437 1,226 1,211 70-74 1,256 651 605 1,558 771 787 1,934 939 995 75-79 824 389 435 1,051 528 523 1,363 645 718 80-84 603 259 344 642 288 354 859 423 436 85+ 721 256 465 710 250 460 767 288 479

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 47,949 23,902 24,047 50,567 25,161 25,406 53,032 26,396 26,636 0-4 2,613 1,342 1,271 2,753 1,416 1,337 2,841 1,456 1,385 5-9 2,623 1,346 1,277 2,859 1,467 1,392 2,975 1,534 1,441 10-14 2,524 1,300 1,224 2,838 1,460 1,378 3,076 1,580 1,496 15-19 3,962 1,994 1,968 4,214 2,140 2,074 4,582 2,332 2,250 20-24 7,410 3,583 3,827 7,441 3,556 3,885 7,717 3,694 4,023 25-29 3,333 1,613 1,720 3,369 1,616 1,753 3,528 1,700 1,828 30-34 2,441 1,183 1,258 2,472 1,246 1,226 2,512 1,256 1,256 35-39 2,341 1,248 1,093 2,682 1,309 1,373 2,669 1,356 1,313 40-44 2,243 1,203 1,040 2,489 1,322 1,167 2,806 1,369 1,437 45-49 2,299 1,156 1,143 2,325 1,246 1,079 2,570 1,365 1,205 50-54 2,283 1,162 1,121 2,370 1,191 1,179 2,393 1,282 1,111 55-59 2,337 1,183 1,154 2,434 1,231 1,203 2,503 1,257 1,246 60-64 2,711 1,351 1,360 2,436 1,243 1,193 2,526 1,289 1,237 65-69 2,814 1,421 1,393 2,665 1,321 1,344 2,390 1,222 1,168 70-74 2,307 1,142 1,165 2,641 1,313 1,328 2,470 1,204 1,266 75-79 1,681 797 884 2,022 982 1,040 2,324 1,129 1,195 80-84 1,084 495 589 1,353 612 741 1,632 759 873 85+ 943 383 560 1,204 490 714 1,518 612 906

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 55,436 27,613 27,823 2010-15 1,677 2,114 1,509 1,072 0-4 2,965 1,531 1,434 2015-20 2,663 2,331 1,686 2,018 5-9 3,063 1,576 1,487 2020-25 2,694 2,539 1,868 2,023 10-14 3,175 1,638 1,537 2025-30 2,618 2,669 2,109 2,058 15-19 4,820 2,447 2,373 2030-35 2,465 2,790 2,358 2,033 20-24 8,242 3,960 4,282 2035-40 2,404 2,941 2,569 2,032 25-29 3,740 1,819 1,921 30-34 2,690 1,349 1,341 35-39 2,703 1,356 1,347 40-44 2,790 1,416 1,374 45-49 2,882 1,399 1,483 50-54 2,625 1,392 1,233 55-59 2,503 1,348 1,155 60-64 2,600 1,323 1,277 65-69 2,481 1,258 1,223 70-74 2,214 1,112 1,102 75-79 2,161 1,024 1,137 80-84 1,882 881 1,001 85+ 1,900 784 1,116

52


10,000

20,000

30,000

40,000

50,000

60,000

70,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Kittitas County


2012 GMA High

2012 GMA Medium

2012 GMA Low

53


Klickitat Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 20,318 10,268 10,050 20,606 10,363 10,243 20,943 10,444 10,499 0-4 1,114 561 553 1,053 543 510 1,117 578 539 5-9 1,207 630 577 1,134 572 562 1,082 554 528 10-14 1,336 708 628 1,209 629 580 1,133 572 561 15-19 1,231 608 623 1,374 743 631 1,249 663 586 20-24 832 434 398 940 445 495 1,051 543 508 25-29 927 494 433 919 478 441 1,053 492 561 30-34 1,031 498 533 920 498 422 939 494 445 35-39 1,195 616 579 996 482 514 928 497 431 40-44 1,208 634 574 1,208 619 589 979 469 510 45-49 1,423 720 703 1,212 627 585 1,218 622 596 50-54 1,655 803 852 1,480 744 736 1,213 624 589 55-59 1,853 897 956 1,699 807 892 1,490 735 755 60-64 1,681 859 822 1,878 893 985 1,752 814 938 65-69 1,332 720 612 1,639 840 799 1,924 913 1,011 70-74 908 460 448 1,224 656 568 1,560 786 774 75-79 619 299 320 790 387 403 1,070 560 510 80-84 414 199 215 498 228 270 639 305 334 85+ 352 128 224 433 172 261 546 223 323

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 21,225 10,504 10,721 21,430 10,530 10,900 21,492 10,501 10,991 0-4 1,176 606 570 1,213 618 595 1,209 615 594 5-9 1,149 589 560 1,235 633 602 1,239 635 604 10-14 1,100 566 534 1,181 608 573 1,244 639 605 15-19 1,185 620 565 1,166 612 554 1,259 662 597 20-24 957 494 463 911 453 458 920 467 453 25-29 1,171 605 566 1,059 534 525 1,001 491 510 30-34 1,081 508 573 1,227 639 588 1,130 582 548 35-39 937 482 455 1,085 514 571 1,255 654 601 40-44 915 487 428 923 483 440 1,095 512 583 45-49 988 466 522 915 492 423 944 482 462 50-54 1,229 628 601 1,002 476 526 934 492 442 55-59 1,257 638 619 1,271 636 635 1,042 480 562 60-64 1,556 752 804 1,304 649 655 1,332 650 682 65-69 1,791 826 965 1,592 765 827 1,345 674 671 70-74 1,838 857 981 1,708 774 934 1,528 733 795 75-79 1,363 667 696 1,626 735 891 1,505 663 842 80-84 860 436 424 1,101 510 591 1,316 567 749 85+ 672 277 395 911 399 512 1,194 503 691

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 21,439 10,452 10,987 2010-15 288 1,059 969 198 0-4 1,201 616 585 2015-20 337 1,111 1,177 403 5-9 1,259 647 612 2020-25 282 1,161 1,363 484 10-14 1,285 656 629 2025-30 205 1,183 1,554 576 15-19 1,330 692 638 2030-35 62 1,173 1,723 612 20-24 986 501 485 2035-40 -53 1,166 1,828 609 25-29 1,002 498 504 30-34 1,057 527 530 35-39 1,145 588 557 40-44 1,263 655 608 45-49 1,116 514 602 50-54 974 497 477 55-59 976 509 467 60-64 1,098 498 600 65-69 1,364 666 698 70-74 1,304 641 663 75-79 1,366 642 724 80-84 1,194 503 691 85+ 1,519 602 917

54


10,000

15,000

20,000

25,000

30,000

35,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Klickitat County


2012 GMA High

2012 GMA Medium

2012 GMA Low

55


Lewis Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 75,455 37,750 37,705 77,621 38,845 38,776 80,385 40,261 40,124 0-4 4,585 2,383 2,202 4,909 2,505 2,404 5,198 2,657 2,541 5-9 4,539 2,327 2,212 4,736 2,464 2,272 5,149 2,632 2,517 10-14 5,094 2,560 2,534 4,675 2,396 2,279 4,902 2,549 2,353 15-19 5,311 2,915 2,396 5,202 2,677 2,525 4,813 2,528 2,285 20-24 4,242 2,206 2,036 4,238 2,281 1,957 4,141 2,070 2,071 25-29 4,269 2,167 2,102 4,876 2,487 2,389 4,860 2,558 2,302 30-34 4,201 2,111 2,090 4,503 2,311 2,192 5,210 2,687 2,523 35-39 4,120 2,039 2,081 4,218 2,118 2,100 4,636 2,379 2,257 40-44 4,449 2,268 2,181 4,286 2,125 2,161 4,287 2,152 2,135 45-49 5,316 2,600 2,716 4,458 2,262 2,196 4,288 2,122 2,166 50-54 5,655 2,832 2,823 5,457 2,667 2,790 4,482 2,271 2,211 55-59 5,482 2,677 2,805 5,977 3,012 2,965 5,754 2,824 2,930 60-64 5,116 2,591 2,525 5,528 2,711 2,817 6,138 3,107 3,031 65-69 4,169 2,036 2,133 4,663 2,347 2,316 5,276 2,565 2,711 70-74 3,116 1,564 1,552 3,585 1,722 1,863 4,208 2,084 2,124 75-79 2,296 1,063 1,233 2,596 1,265 1,331 3,034 1,401 1,633 80-84 1,753 780 973 1,788 776 1,012 1,999 929 1,070 85+ 1,742 631 1,111 1,926 719 1,207 2,010 746 1,264



56


30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

110,000

120,000

130,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Lewis County


2012 GMA High

2012 GMA Medium

2012 GMA Low

57


Lincoln Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 10,570 5,277 5,293 10,616 5,306 5,310 10,707 5,352 5,355 0-4 551 294 257 513 263 250 590 307 283 5-9 645 306 339 570 312 258 532 269 263 10-14 744 376 368 666 317 349 586 320 266 15-19 676 355 321 680 344 336 624 293 331 20-24 391 215 176 598 306 292 594 293 301 25-29 405 193 212 457 243 214 678 344 334 30-34 463 234 229 432 212 220 482 264 218 35-39 480 235 245 458 228 230 435 209 226 40-44 566 289 277 489 236 253 469 238 231 45-49 719 351 368 577 297 280 497 244 253 50-54 948 476 472 742 361 381 568 289 279 55-59 916 450 466 1,002 508 494 792 391 401 60-64 869 446 423 937 472 465 1,038 533 505 65-69 690 347 343 799 407 392 880 440 440 70-74 549 279 270 606 304 302 714 361 353 75-79 393 190 203 460 228 232 505 246 259 80-84 282 133 149 304 138 166 358 169 189 85+ 283 108 175 326 130 196 365 142 223


2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 10,817 5,397 5,420 2010-15 46 510 570 106 0-4 643 325 318 2015-20 91 583 677 185 5-9 699 360 339 2020-25 93 655 744 182 10-14 731 372 359 2025-30 65 678 788 175 15-19 673 342 331 2030-35 -3 652 822 167 20-24 503 248 255 2035-40 -5 627 842 170 25-29 489 243 246 30-34 571 308 263 35-39 671 316 355 40-44 748 373 375 45-49 742 386 356 50-54 493 273 220 55-59 456 223 233 60-64 509 266 243 65-69 517 257 260 70-74 534 276 258 75-79 569 267 302 80-84 636 306 330 85+ 633 256 377

58


7,000

8,000

9,000

10,000

11,000

12,000

13,000

14,000

15,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Lincoln County


2012 GMA High

2012 GMA Medium

2012 GMA Low

59


Mason Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 60,699 31,400 29,299 63,203 32,541 30,662 67,545 34,598 32,947 0-4 3,278 1,717 1,561 3,274 1,677 1,597 3,513 1,798 1,715 5-9 3,357 1,749 1,608 3,401 1,781 1,620 3,582 1,831 1,751 10-14 3,513 1,808 1,705 3,492 1,817 1,675 3,702 1,939 1,763 15-19 3,688 1,967 1,721 3,886 2,087 1,799 4,001 2,167 1,834 20-24 3,124 1,778 1,346 3,501 2,029 1,472 3,731 2,147 1,584 25-29 3,532 1,944 1,588 3,301 1,839 1,462 3,660 2,079 1,581 30-34 3,371 1,905 1,466 3,597 1,918 1,679 3,574 1,904 1,670 35-39 3,403 1,826 1,577 3,209 1,716 1,493 3,700 1,862 1,838 40-44 3,548 1,890 1,658 3,458 1,803 1,655 3,291 1,713 1,578 45-49 4,388 2,220 2,168 3,568 1,893 1,675 3,590 1,871 1,719 50-54 4,783 2,481 2,302 4,607 2,309 2,298 3,754 1,981 1,773 55-59 4,998 2,452 2,546 5,461 2,798 2,663 5,325 2,650 2,675 60-64 4,604 2,268 2,336 5,435 2,657 2,778 6,158 3,142 3,016 65-69 3,722 1,804 1,918 4,327 2,115 2,212 5,469 2,644 2,825 70-74 2,842 1,437 1,405 3,243 1,557 1,686 4,027 1,948 2,079 75-79 2,006 1,037 969 2,401 1,169 1,232 2,817 1,297 1,520 80-84 1,424 673 751 1,581 779 802 1,925 896 1,029 85+ 1,118 444 674 1,461 597 864 1,726 729 997

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 71,929 36,669 35,260 76,401 38,819 37,582 80,784 40,952 39,832 0-4 3,793 1,935 1,858 4,074 2,078 1,996 4,345 2,220 2,125 5-9 3,875 1,980 1,895 4,189 2,137 2,052 4,501 2,299 2,202 10-14 3,898 1,994 1,904 4,230 2,162 2,068 4,585 2,343 2,242 15-19 4,237 2,304 1,933 4,467 2,384 2,083 4,842 2,577 2,265 20-24 3,846 2,220 1,626 4,108 2,368 1,740 4,342 2,450 1,892 25-29 3,948 2,219 1,729 4,091 2,310 1,781 4,351 2,452 1,899 30-34 4,037 2,198 1,839 4,417 2,394 2,023 4,572 2,501 2,071 35-39 3,667 1,846 1,821 4,177 2,140 2,037 4,622 2,384 2,238 40-44 3,815 1,866 1,949 3,798 1,858 1,940 4,335 2,157 2,178 45-49 3,443 1,787 1,656 3,997 1,949 2,048 3,984 1,943 2,041 50-54 3,809 1,977 1,832 3,655 1,890 1,765 4,248 2,063 2,185 55-59 4,380 2,295 2,085 4,449 2,288 2,161 4,272 2,201 2,071 60-64 6,015 2,970 3,045 4,952 2,573 2,379 5,038 2,571 2,467 65-69 6,196 3,146 3,050 6,089 2,979 3,110 5,007 2,588 2,419 70-74 5,132 2,452 2,680 5,835 2,938 2,897 5,721 2,763 2,958 75-79 3,525 1,651 1,874 4,551 2,124 2,427 5,163 2,533 2,630 80-84 2,226 968 1,258 2,799 1,254 1,545 3,691 1,653 2,038 85+ 2,087 861 1,226 2,523 993 1,530 3,165 1,254 1,911


60


10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

110,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Mason County


2012 GMA High

2012 GMA Medium

2012 GMA Low

61


Okanogan Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 41,120 20,750 20,370 42,230 21,291 20,939 43,163 21,704 21,459 0-4 2,805 1,443 1,362 2,917 1,495 1,422 3,032 1,555 1,477 5-9 2,531 1,295 1,236 2,819 1,459 1,360 2,932 1,500 1,432 10-14 2,616 1,384 1,232 2,523 1,297 1,226 2,782 1,433 1,349 15-19 2,673 1,373 1,300 2,354 1,244 1,110 2,244 1,152 1,092 20-24 2,022 1,060 962 2,226 1,116 1,110 1,915 991 924 25-29 2,156 1,101 1,055 2,367 1,238 1,129 2,604 1,305 1,299 30-34 2,146 1,105 1,041 2,150 1,106 1,044 2,329 1,232 1,097 35-39 2,260 1,129 1,131 2,067 1,057 1,010 2,076 1,071 1,005 40-44 2,295 1,162 1,133 2,276 1,140 1,136 2,009 1,030 979 45-49 2,752 1,342 1,410 2,278 1,149 1,129 2,231 1,108 1,123 50-54 3,247 1,573 1,674 2,812 1,368 1,444 2,254 1,130 1,124 55-59 3,353 1,669 1,684 3,307 1,584 1,723 2,855 1,375 1,480 60-64 3,194 1,636 1,558 3,373 1,670 1,703 3,364 1,594 1,770 65-69 2,410 1,271 1,139 3,096 1,606 1,490 3,371 1,684 1,687 70-74 1,774 932 842 2,189 1,149 1,040 2,928 1,513 1,415 75-79 1,261 622 639 1,530 785 745 1,910 986 924 80-84 842 366 476 1,017 484 533 1,225 607 618 85+ 783 287 496 929 344 585 1,102 438 664

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 43,978 22,056 21,922 44,619 22,300 22,319 45,127 22,491 22,636 0-4 3,064 1,572 1,492 3,089 1,586 1,503 3,183 1,636 1,547 5-9 3,060 1,574 1,486 3,105 1,587 1,518 3,160 1,621 1,539 10-14 2,926 1,499 1,427 3,069 1,574 1,495 3,141 1,609 1,532 15-19 2,481 1,281 1,200 2,638 1,354 1,284 2,789 1,427 1,362 20-24 1,841 912 929 2,072 1,044 1,028 2,226 1,114 1,112 25-29 2,247 1,162 1,085 2,159 1,079 1,080 2,415 1,219 1,196 30-34 2,623 1,331 1,292 2,286 1,191 1,095 2,207 1,108 1,099 35-39 2,278 1,201 1,077 2,602 1,325 1,277 2,275 1,185 1,090 40-44 2,031 1,048 983 2,242 1,190 1,052 2,564 1,302 1,262 45-49 1,989 1,018 971 2,022 1,033 989 2,228 1,179 1,049 50-54 2,236 1,106 1,130 1,999 1,017 982 2,040 1,041 999 55-59 2,311 1,151 1,160 2,296 1,130 1,166 2,045 1,042 1,003 60-64 2,906 1,389 1,517 2,373 1,173 1,200 2,363 1,145 1,218 65-69 3,394 1,625 1,769 2,938 1,423 1,515 2,413 1,211 1,202 70-74 3,194 1,589 1,605 3,233 1,538 1,695 2,803 1,351 1,452 75-79 2,561 1,292 1,269 2,807 1,350 1,457 2,838 1,307 1,531 80-84 1,509 746 763 2,038 992 1,046 2,233 1,033 1,200 85+ 1,327 560 767 1,651 714 937 2,204 961 1,243

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 45,707 22,766 22,941 2010-15 1,110 2,936 1,944 118 0-4 3,324 1,699 1,625 2015-20 933 3,026 2,307 214 5-9 3,254 1,670 1,584 2020-25 815 3,041 2,621 395 10-14 3,199 1,638 1,561 2025-30 641 3,068 2,918 491 15-19 2,868 1,472 1,396 2030-35 508 3,155 3,208 561 20-24 2,380 1,194 1,186 2035-40 580 3,306 3,374 648 25-29 2,563 1,284 1,279 30-34 2,479 1,256 1,223 35-39 2,210 1,114 1,096 40-44 2,271 1,186 1,085 45-49 2,569 1,305 1,264 50-54 2,259 1,189 1,070 55-59 2,101 1,068 1,033 60-64 2,133 1,075 1,058 65-69 2,423 1,195 1,228 70-74 2,301 1,148 1,153 75-79 2,460 1,149 1,311 80-84 2,271 1,006 1,265 85+ 2,642 1,118 1,524

62


20,000

25,000

30,000

35,000

40,000

45,000

50,000

55,000

60,000

65,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Okanogan County


2012 GMA High

2012 GMA Medium

2012 GMA Low

63


Pacific Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 20,920 10,488 10,432 20,860 10,398 10,462 20,990 10,432 10,558 0-4 995 535 460 940 483 457 984 506 478 5-9 978 499 479 1,003 537 466 975 502 473 10-14 1,016 506 510 988 496 492 1,031 555 476 15-19 1,172 668 504 929 460 469 896 460 436 20-24 889 470 419 972 546 426 775 375 400 25-29 904 467 437 1,048 554 494 1,145 636 509 30-34 914 492 422 907 477 430 1,089 580 509 35-39 897 440 457 891 480 411 912 471 441 40-44 1,091 555 536 911 446 465 896 479 417 45-49 1,330 666 664 1,079 551 528 888 435 453 50-54 1,620 792 828 1,364 681 683 1,084 540 544 55-59 1,988 962 1,026 1,844 892 952 1,579 782 797 60-64 1,943 945 998 2,158 1,042 1,116 2,057 994 1,063 65-69 1,725 853 872 1,798 863 935 2,108 1,008 1,100 70-74 1,289 649 640 1,501 739 762 1,632 776 856 75-79 921 449 472 1,096 531 565 1,277 605 672 80-84 653 320 333 722 325 397 857 406 451 85+ 595 220 375 709 295 414 805 322 483

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 21,261 10,541 10,720 21,495 10,636 10,859 21,736 10,759 10,977 0-4 997 513 484 1,027 523 504 1,041 530 511 5-9 1,034 531 503 1,076 548 528 1,108 566 542 10-14 1,018 519 499 1,088 557 531 1,158 593 565 15-19 992 534 458 989 508 481 1,081 556 525 20-24 785 391 394 861 452 409 883 442 441 25-29 907 442 465 905 450 455 992 523 469 30-34 1,265 707 558 1,024 499 525 1,030 518 512 35-39 1,138 607 531 1,352 761 591 1,095 530 565 40-44 933 481 452 1,181 633 548 1,409 797 612 45-49 902 478 424 973 508 465 1,215 641 574 50-54 934 455 479 946 508 438 993 514 479 55-59 1,269 631 638 1,089 527 562 1,106 593 513 60-64 1,746 866 880 1,432 715 717 1,236 595 641 65-69 2,022 968 1,054 1,738 853 885 1,444 712 732 70-74 1,952 931 1,021 1,872 880 992 1,628 786 842 75-79 1,411 652 759 1,708 791 917 1,620 739 881 80-84 1,014 457 557 1,107 479 628 1,376 614 762 85+ 942 378 564 1,127 444 683 1,321 510 811

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 22,042 10,944 11,098 2010-15 -60 935 1,342 347 0-4 1,082 551 531 2015-20 130 961 1,522 691 5-9 1,134 582 552 2020-25 271 963 1,667 975 10-14 1,195 609 586 2025-30 234 973 1,796 1,057 15-19 1,130 584 546 2030-35 241 996 1,892 1,137 20-24 973 485 488 2035-40 306 1,037 1,952 1,221 25-29 1,011 502 509 30-34 1,142 606 536 35-39 1,119 560 559 40-44 1,147 556 591 45-49 1,467 826 641 50-54 1,274 670 604 55-59 1,196 620 576 60-64 1,258 665 593 65-69 1,253 603 650 70-74 1,336 658 678 75-79 1,413 662 751 80-84 1,298 566 732 85+ 1,614 639 975

64


10,000

12,000

14,000

16,000

18,000

20,000

22,000

24,000

26,000

28,000

30,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Pacific County


2012 GMA High

2012 GMA Medium

2012 GMA Low

65


Pend Oreille Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 13,001 6,593 6,408 13,289 6,648 6,641 13,692 6,742 6,950 0-4 698 341 357 671 348 323 746 385 361 5-9 696 386 310 718 349 369 705 362 343 10-14 868 460 408 723 405 318 727 354 373 15-19 791 409 382 809 427 382 664 363 301 20-24 488 243 245 662 333 329 687 352 335 25-29 511 251 260 588 293 295 803 406 397 30-34 533 263 270 522 264 258 613 311 302 35-39 644 327 317 535 261 274 528 263 265 40-44 730 369 361 655 330 325 533 262 271 45-49 994 490 504 739 369 370 675 340 335 50-54 1,143 561 582 1,037 498 539 754 370 384 55-59 1,244 655 589 1,190 566 624 1,072 506 566 60-64 1,176 612 564 1,271 645 626 1,241 563 678 65-69 933 463 470 1,148 586 562 1,287 642 645 70-74 608 333 275 858 413 445 1,094 545 549 75-79 424 212 212 520 280 240 769 353 416 80-84 263 128 135 342 158 184 428 216 212 85+ 257 90 167 301 123 178 366 149 217

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 13,977 6,772 7,205 14,129 6,764 7,365 14,149 6,710 7,439 0-4 794 412 382 800 409 391 798 407 391 5-9 771 391 380 827 422 405 832 424 408 10-14 724 367 357 806 411 395 863 441 422 15-19 689 335 354 665 338 327 742 381 361 20-24 558 302 256 592 284 308 582 289 293 25-29 789 410 379 654 352 302 670 319 351 30-34 831 424 407 842 433 409 693 371 322 35-39 614 308 306 847 432 415 860 449 411 40-44 535 261 274 605 308 297 869 444 425 45-49 534 257 277 556 275 281 629 315 314 50-54 700 347 353 560 268 292 563 270 293 55-59 776 367 409 714 337 377 573 260 313 60-64 1,129 512 617 815 369 446 755 344 411 65-69 1,264 559 705 1,144 501 643 833 364 469 70-74 1,246 601 645 1,206 509 697 1,101 471 630 75-79 966 464 502 1,098 509 589 1,073 436 637 80-84 608 261 347 762 353 409 879 389 490 85+ 449 194 255 636 254 382 834 336 498

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 14,116 6,655 7,461 2010-15 288 674 666 280 0-4 804 414 390 2015-20 403 740 804 467 5-9 826 425 401 2020-25 285 779 935 441 10-14 858 435 423 2025-30 152 780 1,065 437 15-19 795 402 393 2030-35 20 779 1,187 428 20-24 660 328 332 2035-40 -33 791 1,242 418 25-29 678 334 344 30-34 722 345 377 35-39 716 388 328 40-44 872 456 416 45-49 871 443 428 50-54 647 314 333 55-59 586 273 313 60-64 608 266 342 65-69 783 354 429 70-74 815 351 464 75-79 983 397 586 80-84 854 320 534 85+ 1,038 410 628

66


5,000

7,500

10,000

12,500

15,000

17,500

20,000

22,500

25,000

27,500

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Pend Oreille County


2012 GMA High

2012 GMA Medium

2012 GMA Low

67


Pierce Population Projection: Intermediate Series


2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 923,912 456,518 467,394 967,601 477,861 489,740 1,006,614 496,845 509,769 0-4 60,447 30,920 29,527 60,920 31,163 29,757 62,269 31,847 30,422 5-9 61,963 31,690 30,273 62,427 31,926 30,501 62,852 32,137 30,715 10-14 61,570 31,481 30,089 65,037 33,261 31,776 65,434 33,462 31,972 15-19 57,488 29,733 27,755 60,311 31,231 29,080 63,731 32,997 30,734 20-24 53,918 27,645 26,273 57,346 29,428 27,918 60,020 30,825 29,195 25-29 55,950 28,618 27,332 56,992 29,105 27,887 60,555 30,938 29,617 30-34 62,447 31,464 30,983 58,603 29,657 28,946 59,720 30,193 29,527 35-39 64,460 32,430 32,030 64,672 32,647 32,025 60,635 30,752 29,883 40-44 63,158 30,749 32,409 66,029 32,972 33,057 66,246 33,170 33,076 45-49 55,764 27,340 28,424 64,402 31,301 33,101 67,199 33,516 33,683 50-54 56,128 27,702 28,426 56,215 27,485 28,730 64,931 31,480 33,451 55-59 55,328 27,108 28,220 55,462 27,273 28,189 55,726 27,208 28,518 60-64 57,604 28,298 29,306 53,772 26,020 27,752 53,822 26,089 27,733 65-69 53,519 25,608 27,911 55,485 26,892 28,593 51,928 24,783 27,145 70-74 41,744 19,230 22,514 50,078 23,541 26,537 51,905 24,715 27,190 75-79 30,169 13,750 16,419 36,586 16,350 20,236 44,202 20,241 23,961 80-84 17,313 7,444 9,869 24,202 10,564 13,638 29,459 12,575 16,884 85+ 14,942 5,308 9,634 19,062 7,045 12,017 25,980 9,917 16,063

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 1,042,341 514,330 528,011 2010-15 36,719 56,607 29,938 10,050 0-4 64,500 32,975 31,525 2015-20 44,621 59,068 32,741 18,294 5-9 64,200 32,816 31,384 2020-25 47,347 59,243 34,247 22,351 10-14 65,824 33,654 32,170 2025-30 43,689 59,731 39,064 23,022 15-19 64,107 33,199 30,908 2030-35 39,013 61,215 44,841 22,639 20-24 63,504 32,614 30,890 2035-40 35,727 63,554 50,327 22,500 25-29 63,306 32,369 30,937 30-34 63,468 32,120 31,348 35-39 61,791 31,295 30,496 40-44 62,117 31,236 30,881 45-49 67,503 33,751 33,752 50-54 67,649 33,655 33,994 55-59 64,468 31,239 33,229 60-64 54,097 26,012 28,085 65-69 52,026 24,886 27,140 70-74 48,719 22,814 25,905 75-79 45,742 21,199 24,543 80-84 35,937 15,816 20,121 85+ 33,383 12,680 20,703

68


250,000

375,000

500,000

625,000

750,000

875,000

1,000,000

1,125,000

1,250,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Pierce County


2012 GMA High

2012 GMA Medium

2012 GMA Low

69


San Juan Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 15,769 7,665 8,104 15,907 7,699 8,208 16,256 7,812 8,444 0-4 539 258 281 486 252 234 543 281 262 5-9 647 322 325 572 271 301 534 275 259 10-14 776 379 397 674 334 340 627 302 325 15-19 746 376 370 741 361 380 669 333 336 20-24 511 265 246 653 323 330 663 322 341 25-29 589 270 319 614 315 299 768 370 398 30-34 668 338 330 642 302 340 697 361 336 35-39 730 379 351 672 338 334 689 321 368 40-44 841 397 444 777 406 371 716 358 358 45-49 1,124 543 581 859 407 452 816 423 393 50-54 1,398 642 756 1,184 573 611 892 421 471 55-59 1,707 815 892 1,533 693 840 1,303 621 682 60-64 1,836 873 963 1,807 862 945 1,655 745 910 65-69 1,382 712 670 1,742 820 922 1,785 847 938 70-74 892 453 439 1,245 637 608 1,642 755 887 75-79 558 288 270 781 386 395 1,096 548 548 80-84 373 184 189 451 225 226 634 302 332 85+ 452 171 281 474 194 280 527 227 300

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 16,606 7,917 8,689 16,939 8,035 8,904 17,216 8,153 9,063 0-4 600 311 289 632 322 310 642 328 314 5-9 619 320 299 676 346 330 710 363 347 10-14 601 308 293 686 359 327 758 387 371 15-19 623 294 329 602 310 292 693 353 340 20-24 614 294 320 587 276 311 577 288 289 25-29 767 360 407 717 340 377 664 308 356 30-34 926 461 465 944 447 497 880 432 448 35-39 761 400 361 1,048 523 525 1,078 515 563 40-44 746 349 397 846 439 407 1,150 573 577 45-49 763 383 380 794 368 426 896 468 428 50-54 856 444 412 820 411 409 857 392 465 55-59 999 463 536 958 490 468 929 459 470 60-64 1,412 667 745 1,109 517 592 1,071 553 518 65-69 1,665 742 923 1,428 666 762 1,121 515 606 70-74 1,686 780 906 1,561 677 884 1,370 635 735 75-79 1,438 645 793 1,478 663 815 1,403 591 812 80-84 875 419 456 1,149 492 657 1,198 513 685 85+ 655 277 378 904 389 515 1,219 480 739

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 17,443 8,279 9,164 2010-15 138 484 788 442 0-4 641 324 317 2015-20 349 526 1,013 836 5-9 714 363 351 2020-25 350 565 1,255 1,040 10-14 786 402 384 2025-30 333 591 1,410 1,152 15-19 778 398 380 2030-35 277 596 1,555 1,236 20-24 663 332 331 2035-40 227 588 1,619 1,258 25-29 670 335 335 30-34 810 380 430 35-39 995 490 505 40-44 1,176 557 619 45-49 1,238 615 623 50-54 964 497 467 55-59 951 427 524 60-64 1,044 524 520 65-69 1,099 567 532 70-74 1,093 495 598 75-79 1,221 555 666 80-84 1,136 453 683 85+ 1,464 565 899

70


0

5,000

10,000

15,000

20,000

25,000

30,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

San Juan County


2012 GMA High

2012 GMA Medium

2012 GMA Low

71


Skagit Population Projection: Intermediate Series




72


25,000

50,000

75,000

100,000

125,000

150,000

175,000

200,000

225,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Skagit County


2012 GMA High

2012 GMA Medium

2012 GMA Low

73


Skamania Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 11,066 5,565 5,501 11,282 5,668 5,614 11,548 5,797 5,751 0-4 604 301 303 521 271 250 549 282 267 5-9 648 326 322 631 317 314 539 275 264 10-14 730 367 363 663 335 328 663 332 331 15-19 717 378 339 675 340 335 637 323 314 20-24 451 235 216 619 317 302 592 285 307 25-29 501 242 259 535 283 252 721 372 349 30-34 639 330 309 529 257 272 564 299 265 35-39 674 316 358 649 332 317 536 259 277 40-44 710 351 359 704 328 376 653 337 316 45-49 943 487 456 702 341 361 705 330 375 50-54 1,013 486 527 976 502 474 702 345 357 55-59 1,028 533 495 1,059 511 548 1,000 526 474 60-64 812 427 385 1,029 541 488 1,075 526 549 65-69 617 312 305 741 391 350 985 520 465 70-74 364 185 179 536 271 265 668 342 326 75-79 276 138 138 295 146 149 475 235 240 80-84 188 89 99 219 106 113 247 114 133 85+ 151 62 89 199 79 120 237 95 142

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 12,014 6,020 5,994 12,447 6,219 6,228 12,816 6,386 6,430 0-4 612 313 299 621 318 303 655 335 320 5-9 609 314 295 649 334 315 679 346 333 10-14 567 292 275 639 326 313 698 357 341 15-19 636 313 323 576 293 283 640 331 309 20-24 547 264 283 576 282 294 501 247 254 25-29 680 332 348 642 314 328 656 319 337 30-34 827 435 392 791 391 400 727 361 366 35-39 600 318 282 880 462 418 851 422 429 40-44 556 268 288 628 330 298 931 486 445 45-49 678 346 332 584 283 301 649 341 308 50-54 720 340 380 680 355 325 604 291 313 55-59 746 373 373 772 368 404 731 388 343 60-64 1,053 559 494 793 396 397 809 381 428 65-69 1,035 500 535 1,023 532 491 752 375 377 70-74 915 470 445 957 452 505 943 491 452 75-79 580 293 287 805 406 399 839 383 456 80-84 383 174 209 458 220 238 655 321 334 85+ 270 116 154 373 157 216 496 211 285

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 13,082 6,506 6,576 2010-15 216 513 453 156 0-4 646 331 315 2015-20 266 552 551 265 5-9 697 356 341 2020-25 466 588 634 512 10-14 744 381 363 2025-30 433 615 733 551 15-19 705 364 341 2030-35 369 616 835 588 20-24 560 281 279 2035-40 266 610 923 579 25-29 580 284 296 30-34 742 366 376 35-39 796 397 399 40-44 876 430 446 45-49 971 511 460 50-54 684 360 324 55-59 653 322 331 60-64 764 403 361 65-69 777 369 408 70-74 707 343 364 75-79 830 426 404 80-84 660 284 376 85+ 690 298 392

74


5,000

7,000

9,000

11,000

13,000

15,000

17,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Skamania County


2012 GMA High

2012 GMA Medium

2012 GMA Low

75


Snohomish Population Projection: Intermediate Series




76


0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Snohomish County


2012 GMA High

2012 GMA Medium

2012 GMA Low

77


Spokane Population Projection: Intermediate Series




78


200,000

300,000

400,000

500,000

600,000

700,000

800,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Spokane County


2012 GMA High

2012 GMA Medium

2012 GMA Low

79


Stevens Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 43,531 21,782 21,749 44,262 22,197 22,065 45,212 22,679 22,533 0-4 2,310 1,182 1,128 2,132 1,090 1,042 2,232 1,138 1,094 5-9 2,756 1,449 1,307 2,571 1,317 1,254 2,299 1,177 1,122 10-14 3,244 1,629 1,615 2,920 1,490 1,430 2,758 1,410 1,348 15-19 3,205 1,699 1,506 2,322 1,278 1,044 2,354 1,257 1,097 20-24 1,675 883 792 1,890 1,018 872 2,045 1,100 945 25-29 1,723 850 873 1,948 1,012 936 2,210 1,185 1,025 30-34 1,984 921 1,063 2,107 1,053 1,054 2,188 1,156 1,032 35-39 2,270 1,152 1,118 2,230 1,034 1,196 2,252 1,127 1,125 40-44 2,583 1,229 1,354 2,562 1,306 1,256 2,329 1,077 1,252 45-49 3,153 1,526 1,627 2,778 1,312 1,466 2,633 1,334 1,299 50-54 3,822 1,845 1,977 3,415 1,652 1,763 2,832 1,340 1,492 55-59 3,817 1,888 1,929 4,089 1,999 2,090 3,535 1,734 1,801 60-64 3,473 1,784 1,689 3,910 1,957 1,953 4,159 2,056 2,103 65-69 2,797 1,480 1,317 3,295 1,685 1,610 3,769 1,878 1,891 70-74 1,917 1,010 907 2,519 1,311 1,208 3,024 1,516 1,508 75-79 1,235 601 634 1,673 861 812 2,187 1,104 1,083 80-84 817 379 438 1,004 470 534 1,333 659 674 85+ 750 275 475 897 352 545 1,073 431 642

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 46,447 23,245 23,202 47,834 23,899 23,935 49,340 24,646 24,694 0-4 2,417 1,234 1,183 2,648 1,350 1,298 2,840 1,453 1,387 5-9 2,420 1,239 1,181 2,622 1,343 1,279 2,875 1,472 1,403 10-14 2,459 1,262 1,197 2,604 1,335 1,269 2,838 1,447 1,391 15-19 2,682 1,377 1,305 2,419 1,239 1,180 2,565 1,316 1,249 20-24 2,071 1,078 993 2,430 1,217 1,213 2,191 1,102 1,089 25-29 2,375 1,268 1,107 2,407 1,247 1,160 2,774 1,378 1,396 30-34 2,518 1,365 1,153 2,738 1,476 1,262 2,786 1,458 1,328 35-39 2,329 1,227 1,102 2,727 1,478 1,249 3,001 1,623 1,378 40-44 2,361 1,180 1,181 2,458 1,302 1,156 2,869 1,553 1,316 45-49 2,384 1,099 1,285 2,440 1,220 1,220 2,547 1,340 1,207 50-54 2,711 1,375 1,336 2,449 1,126 1,323 2,533 1,267 1,266 55-59 2,943 1,408 1,535 2,820 1,456 1,364 2,586 1,213 1,373 60-64 3,576 1,777 1,799 3,005 1,457 1,548 2,884 1,500 1,384 65-69 4,013 1,969 2,044 3,463 1,705 1,758 2,914 1,400 1,514 70-74 3,478 1,700 1,778 3,704 1,789 1,915 3,194 1,543 1,651 75-79 2,615 1,268 1,347 3,026 1,438 1,588 3,240 1,525 1,715 80-84 1,715 835 880 2,058 948 1,110 2,415 1,099 1,316 85+ 1,380 584 796 1,816 773 1,043 2,288 957 1,331

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 50,929 25,490 25,439 2010-15 731 2,038 2,006 699 0-4 2,956 1,514 1,442 2015-20 950 2,165 2,450 1,235 5-9 3,104 1,582 1,522 2020-25 1,235 2,320 2,823 1,738 10-14 3,131 1,602 1,529 2025-30 1,387 2,538 3,179 2,028 15-19 2,800 1,434 1,366 2030-35 1,506 2,728 3,483 2,261 20-24 2,333 1,173 1,160 2035-40 1,589 2,839 3,676 2,426 25-29 2,489 1,237 1,252 30-34 3,222 1,629 1,593 35-39 3,058 1,608 1,450 40-44 3,175 1,718 1,457 45-49 3,002 1,622 1,380 50-54 2,626 1,385 1,241 55-59 2,655 1,355 1,300 60-64 2,630 1,242 1,388 65-69 2,836 1,475 1,361 70-74 2,719 1,289 1,430 75-79 2,791 1,310 1,481 80-84 2,592 1,168 1,424 85+ 2,810 1,147 1,663

80


10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Stevens County


2012 GMA High

2012 GMA Medium

2012 GMA Low

81


Thurston Population Projection: Intermediate Series




82


0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Thurston County


2012 GMA High

2012 GMA Medium

2012 GMA Low

83


Wahkiakum Population Projection: Intermediate Series




84


1,500

2,500

3,500

4,500

5,500

6,500

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Wahkiakum County


2012 GMA High

2012 GMA Medium

2012 GMA Low

85


Walla Walla Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 58,781 29,835 28,946 60,015 30,498 29,517 61,685 31,478 30,207 0-4 3,513 1,807 1,706 3,508 1,791 1,717 3,777 1,930 1,847 5-9 3,613 1,812 1,801 3,630 1,867 1,763 3,655 1,868 1,787 10-14 3,764 1,875 1,889 3,728 1,872 1,856 3,730 1,914 1,816 15-19 4,887 2,464 2,423 4,789 2,330 2,459 4,791 2,338 2,453 20-24 5,223 2,852 2,371 5,618 3,059 2,559 5,621 2,983 2,638 25-29 3,831 2,200 1,631 4,240 2,490 1,750 4,553 2,716 1,837 30-34 3,483 1,907 1,576 3,701 2,019 1,682 4,084 2,310 1,774 35-39 3,294 1,761 1,533 3,366 1,774 1,592 3,623 1,912 1,711 40-44 3,460 1,815 1,645 3,475 1,882 1,593 3,458 1,860 1,598 45-49 3,809 1,983 1,826 3,312 1,654 1,658 3,314 1,728 1,586 50-54 4,052 2,012 2,040 3,709 1,855 1,854 3,136 1,491 1,645 55-59 3,795 1,903 1,892 3,923 1,934 1,989 3,573 1,782 1,791 60-64 3,279 1,644 1,635 3,531 1,756 1,775 3,713 1,810 1,903 65-69 2,412 1,197 1,215 2,953 1,460 1,493 3,306 1,623 1,683 70-74 1,736 791 945 2,099 1,027 1,072 2,685 1,299 1,386 75-79 1,586 695 891 1,456 633 823 1,832 871 961 80-84 1,429 547 882 1,247 514 733 1,138 464 674 85+ 1,615 570 1,045 1,730 581 1,149 1,696 579 1,117

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 63,368 32,329 31,039 64,978 33,116 31,862 66,378 33,801 32,577 0-4 3,930 2,007 1,923 3,992 2,046 1,946 4,005 2,054 1,951 5-9 3,954 2,016 1,938 4,112 2,101 2,011 4,176 2,134 2,042 10-14 3,794 1,935 1,859 4,098 2,088 2,010 4,247 2,171 2,076 15-19 4,823 2,404 2,419 4,905 2,431 2,474 5,256 2,611 2,645 20-24 5,526 2,942 2,584 5,546 2,999 2,547 5,644 3,041 2,603 25-29 4,346 2,505 1,841 4,282 2,474 1,808 4,293 2,518 1,775 30-34 4,364 2,466 1,898 4,179 2,265 1,914 4,097 2,229 1,868 35-39 4,038 2,210 1,828 4,293 2,343 1,950 4,084 2,135 1,949 40-44 3,729 1,997 1,732 4,120 2,281 1,839 4,405 2,433 1,972 45-49 3,298 1,693 1,605 3,564 1,828 1,736 3,945 2,098 1,847 50-54 3,161 1,573 1,588 3,140 1,541 1,599 3,384 1,670 1,714 55-59 3,027 1,432 1,595 3,072 1,526 1,546 3,058 1,508 1,550 60-64 3,405 1,683 1,722 2,892 1,348 1,544 2,916 1,428 1,488 65-69 3,498 1,686 1,812 3,219 1,573 1,646 2,736 1,260 1,476 70-74 3,039 1,460 1,579 3,208 1,508 1,700 2,943 1,405 1,538 75-79 2,344 1,098 1,246 2,652 1,232 1,420 2,807 1,278 1,529 80-84 1,456 664 792 1,879 846 1,033 2,134 959 1,175 85+ 1,636 558 1,078 1,825 686 1,139 2,248 869 1,379

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 67,655 34,436 33,219 2010-15 1,234 3,496 2,727 465 0-4 4,038 2,065 1,973 2015-20 1,670 3,757 2,916 829 5-9 4,173 2,127 2,046 2020-25 1,683 3,888 3,007 802 10-14 4,306 2,205 2,101 2025-30 1,610 3,957 3,159 812 15-19 5,429 2,692 2,737 2030-35 1,400 3,989 3,379 790 20-24 6,058 3,262 2,796 2035-40 1,277 4,045 3,560 792 25-29 4,341 2,545 1,796 30-34 4,112 2,290 1,822 35-39 4,030 2,118 1,912 40-44 4,198 2,222 1,976 45-49 4,196 2,230 1,966 50-54 3,768 1,942 1,826 55-59 3,306 1,630 1,676 60-64 2,909 1,403 1,506 65-69 2,762 1,345 1,417 70-74 2,506 1,123 1,383 75-79 2,567 1,192 1,375 80-84 2,279 994 1,285 85+ 2,677 1,051 1,626

86


30,000

40,000

50,000

60,000

70,000

80,000

90,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Walla Walla County


2012 GMA High

2012 GMA Medium

2012 GMA Low

87


Whatcom Population Projection: Intermediate Series




88


50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Whatcom County


2012 GMA High

2012 GMA Medium

2012 GMA Low

89


Whitman Population Projection: Intermediate Series

2010 2015 2020 Age Total Male Female Total Male Female Total Male Female Total 44,776 22,806 21,970 46,139 23,408 22,731 47,826 24,159 23,667 0-4 1,978 1,069 909 2,190 1,118 1,072 2,414 1,234 1,180 5-9 1,810 908 902 1,997 1,076 921 2,338 1,200 1,138 10-14 1,789 950 839 1,837 920 917 2,120 1,147 973 15-19 6,072 2,911 3,161 5,591 2,716 2,875 5,725 2,704 3,021 20-24 11,394 6,162 5,232 12,190 6,617 5,573 11,207 6,175 5,032 25-29 3,621 1,899 1,722 3,433 1,772 1,661 3,568 1,817 1,751 30-34 2,324 1,220 1,104 2,510 1,199 1,311 2,481 1,168 1,313 35-39 1,806 912 894 2,143 1,103 1,040 2,490 1,168 1,322 40-44 1,864 927 937 1,843 933 910 2,230 1,152 1,078 45-49 2,003 980 1,023 1,825 896 929 1,869 945 924 50-54 2,212 1,099 1,113 1,976 954 1,022 1,843 913 930 55-59 1,967 1,018 949 2,111 1,041 1,070 1,956 950 1,006 60-64 1,679 804 875 1,802 930 872 2,064 1,007 1,057 65-69 1,343 664 679 1,481 699 782 1,764 901 863 70-74 885 420 465 1,166 570 596 1,396 643 753 75-79 716 338 378 740 338 402 1,040 499 541 80-84 584 255 329 570 254 316 590 258 332 85+ 729 270 459 734 272 462 731 278 453

2025 2030 2035 Age Total Male Female Total Male Female Total Male Female Total 49,346 24,796 24,550 50,577 25,374 25,203 51,563 25,847 25,716 0-4 2,395 1,224 1,171 2,213 1,129 1,084 2,094 1,081 1,013 5-9 2,561 1,309 1,252 2,534 1,305 1,229 2,324 1,192 1,132 10-14 2,470 1,273 1,197 2,677 1,375 1,302 2,622 1,349 1,273 15-19 6,074 2,921 3,153 6,505 3,080 3,425 6,898 3,261 3,637 20-24 11,003 5,981 5,022 11,180 6,156 5,024 11,611 6,325 5,286 25-29 3,093 1,737 1,356 3,152 1,718 1,434 3,365 1,899 1,466 30-34 2,398 1,077 1,321 1,956 1,046 910 2,033 1,027 1,006 35-39 2,419 1,108 1,311 2,320 992 1,328 1,855 968 887 40-44 2,562 1,201 1,361 2,476 1,128 1,348 2,346 1,004 1,342 45-49 2,272 1,177 1,095 2,592 1,216 1,376 2,494 1,138 1,356 50-54 1,906 968 938 2,275 1,174 1,101 2,578 1,200 1,378 55-59 1,837 903 934 1,845 926 919 2,214 1,135 1,079 60-64 1,905 915 990 1,778 877 901 1,798 905 893 65-69 1,987 958 1,029 1,841 872 969 1,699 828 871 70-74 1,650 831 819 1,858 879 979 1,689 785 904 75-79 1,225 550 675 1,457 716 741 1,614 741 873 80-84 838 381 457 969 409 560 1,168 562 606 85+ 751 282 469 949 376 573 1,161 447 714

2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 52,504 26,299 26,205 2010-15 1,363 2,230 1,212 345 0-4 2,162 1,107 1,055 2015-20 1,687 2,410 1,383 660 5-9 2,194 1,123 1,071 2020-25 1,520 2,371 1,514 663 10-14 2,395 1,233 1,162 2025-30 1,231 2,192 1,637 676 15-19 6,888 3,251 3,637 2030-35 986 2,098 1,784 672 20-24 12,194 6,639 5,555 2035-40 941 2,184 1,914 671 25-29 3,662 1,993 1,669 30-34 2,289 1,241 1,048 35-39 1,940 958 982 40-44 1,889 980 909 45-49 2,355 1,005 1,350 50-54 2,461 1,122 1,339 55-59 2,484 1,141 1,343 60-64 2,147 1,095 1,052 65-69 1,713 852 861 70-74 1,586 763 823 75-79 1,469 667 802 80-84 1,298 564 734 85+ 1,378 565 813

90


30,000

35,000

40,000

45,000

50,000

55,000

60,000

65,000

70,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Whitman County


2012 GMA High

2012 GMA Medium

2012 GMA Low

91


Yakima Population Projection: Intermediate Series



2040 Summary Data Age Total Male Female Period Change Births Deaths Migration Total 318,494 159,601 158,893 2010-15 13,110 22,009 8,506 -393 0-4 25,782 13,224 12,558 2015-20 13,006 22,993 9,273 -714 5-9 25,671 13,165 12,506 2020-25 12,710 23,413 9,718 -985 10-14 25,058 12,856 12,202 2025-30 12,388 24,229 10,690 -1,151 15-19 22,267 11,439 10,828 2030-35 12,191 25,284 11,806 -1,287 20-24 18,538 9,291 9,247 2035-40 11,858 26,142 12,850 -1,434 25-29 20,580 10,313 10,267 30-34 20,777 10,513 10,264 35-39 19,673 9,898 9,775 40-44 18,897 9,600 9,297 45-49 19,116 9,844 9,272 50-54 16,419 8,529 7,890 55-59 16,187 8,044 8,143 60-64 14,226 7,086 7,140 65-69 13,552 6,689 6,863 70-74 11,874 5,835 6,039 75-79 11,323 5,367 5,956 80-84 8,787 4,068 4,719 85+ 9,767 3,840 5,927

92


100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Yakima County


2012 GMA High

2012 GMA Medium

2012 GMA Low

93


Section IV. Final Projections of the Total Resident Population for the Growth Management Act: 2010- 2040 Final Projections of the Total Resident Population for the Growth Management Act High Series: 2010 to 2040

Census Projections

2010 2015 2020 2025 2030 2035 2040

Washington 6,724,540 7,696,799 8,323,520 8,943,546 9,545,810 10,120,536 10,676,170 Adams 18,728 21,085 23,158 25,172 27,187 29,278 31,483 Asotin 21,623 24,527 26,155 27,728 29,252 30,699 32,097 Benton 175,177 204,292 221,552 238,812 256,072 273,332 290,592 Chelan 72,453 80,634 88,524 96,414 104,304 112,194 120,084 Clallam 71,404 77,825 81,323 84,458 87,259 89,618 91,727 Clark 425,363 497,767 545,695 593,144 638,814 681,134 720,688 Columbia 4,078 4,250 4,280 4,310 4,340 4,370 4,400 Cowlitz 102,410 110,570 115,985 121,400 126,815 132,230 137,645 Douglas 38,431 45,031 49,469 53,935 58,270 62,336 66,223 Ferry 7,551 8,619 9,102 9,541 9,934 10,309 10,647 Franklin 78,163 104,430 128,310 153,318 179,327 206,066 233,862 Garfield 2,266 2,417 2,492 2,567 2,642 2,717 2,792 Grant 89,120 101,720 114,891 128,253 141,847 155,337 168,810 Grays Harbor 72,797 77,990 79,990 81,990 83,990 85,990 87,990 Island 78,506 91,944 99,714 107,419 115,351 123,358 131,741 Jefferson 29,872 34,492 37,748 41,127 44,850 48,872 52,810 King 1,931,249 2,133,549 2,280,673 2,418,634 2,549,780 2,672,931 2,790,631 Kitsap 251,133 297,455 326,510 355,786 383,613 408,976 432,873 Kittitas 40,915 47,759 52,395 57,065 61,652 66,075 70,431 Klickitat 20,318 22,914 23,938 24,903 25,784 26,511 27,114 Lewis 75,455 86,431 92,016 97,358 102,378 107,059 111,684 Lincoln 10,570 11,253 11,403 11,553 11,703 11,853 12,003 Mason 60,699 69,904 76,239 82,618 89,093 95,472 101,583 Okanogan 41,120 47,000 49,600 52,200 54,800 57,400 60,000 Pacific 20,920 22,000 22,600 23,200 23,800 24,400 25,000 Pend Oreille 13,001 14,697 15,691 16,646 17,509 18,322 19,068 Pierce 795,225 907,455 964,600 1,024,690 1,080,829 1,131,918 1,179,458 San Juan 15,769 18,270 19,736 21,204 22,654 24,043 25,378 Skagit 116,901 137,199 150,199 164,858 179,929 195,148 210,827 Skamania 11,066 12,415 12,932 13,665 14,363 14,991 15,509 Snohomish 713,335 836,247 921,136 1,004,154 1,084,952 1,161,003 1,232,605 Spokane 471,221 548,980 595,683 641,412 684,623 724,554 762,387 Stevens 43,531 50,733 54,689 58,953 63,381 67,937 72,583 Thurston 252,264 295,512 324,412 353,312 382,212 411,112 440,012 Wahkiakum 3,978 4,245 4,295 4,345 4,395 4,445 4,495 Walla Walla 58,781 62,483 65,853 69,223 72,593 75,963 79,333 Whatcom 201,140 231,274 255,019 278,764 302,509 326,254 350,000 Whitman 44,776 51,090 54,172 57,074 59,663 61,988 64,264 Yakima 243,231 300,341 321,341 342,341 363,341 384,341 405,341

Note: Unrounded data should not be considered accurate to the last digit. OFM/Forecasting | August 2012

94


Final Projections of the Total Resident Population for the Growth Management Act Medium Series: 2010 to 2040

Census Projections

2010 2015 2020 2025 2030 2035 2040

Washington 6,724,540 7,022,200 7,411,977 7,793,173 8,154,193 8,483,628 8,790,981 Adams 18,728 20,257 21,640 22,964 24,289 25,690 27,205 Asotin 21,623 21,818 22,033 22,196 22,313 22,358 22,356 Benton 175,177 184,882 197,806 210,803 223,689 236,007 247,856 Chelan 72,453 75,180 78,586 81,885 84,778 87,168 89,246 Clallam 71,404 71,868 73,616 75,022 76,112 76,786 77,224 Clark 425,363 447,201 477,884 508,124 536,717 562,207 585,137 Columbia 4,078 4,047 4,013 3,968 3,895 3,800 3,700 Cowlitz 102,410 105,130 108,588 111,706 114,158 115,798 116,897 Douglas 38,431 40,603 43,619 46,662 49,583 52,256 54,762 Ferry 7,551 7,619 7,706 7,751 7,754 7,740 7,692 Franklin 78,163 87,755 100,926 115,142 130,284 146,103 162,900 Garfield 2,266 2,238 2,220 2,210 2,202 2,175 2,143 Grant 89,120 95,822 104,078 112,525 121,204 129,779 138,337 Grays Harbor 72,797 73,575 74,408 75,529 76,428 76,905 77,070 Island 78,506 80,337 82,735 85,073 87,621 90,239 93,205 Jefferson 29,872 30,469 32,017 33,678 35,657 37,914 40,093 King 1,931,249 2,012,782 2,108,814 2,196,202 2,277,160 2,350,576 2,418,850 Kitsap 251,133 262,032 275,546 289,265 301,642 311,737 320,475 Kittitas 40,915 42,592 45,255 47,949 50,567 53,032 55,436 Klickitat 20,318 20,606 20,943 21,225 21,430 21,492 21,439 Lewis 75,455 77,621 80,385 82,924 85,165 87,092 88,967 Lincoln 10,570 10,616 10,707 10,800 10,865 10,862 10,817 Mason 60,699 63,203 67,545 71,929 76,401 80,784 84,919 Okanogan 41,120 42,230 43,163 43,978 44,619 45,127 45,707 Pacific 20,920 20,860 20,990 21,261 21,495 21,736 22,042 Pend Oreille 13,001 13,289 13,692 13,977 14,129 14,149 14,116 Pierce 795,225 831,944 876,565 923,912 967,601 1,006,614 1,042,341 San Juan 15,769 15,907 16,256 16,606 16,939 17,216 17,443 Skagit 116,901 121,624 128,249 136,410 144,953 153,632 162,738 Skamania 11,066 11,282 11,548 12,014 12,447 12,816 13,082 Snohomish 713,335 750,358 805,015 857,939 908,807 955,281 997,634 Spokane 471,221 489,491 513,910 537,428 558,614 576,763 592,969 Stevens 43,531 44,262 45,212 46,447 47,834 49,340 50,929 Thurston 252,264 266,224 288,265 307,930 326,426 343,019 358,031 Wahkiakum 3,978 3,931 3,877 3,830 3,772 3,716 3,669 Walla Walla 58,781 60,015 61,685 63,368 64,978 66,378 67,655 Whatcom 201,140 210,050 225,307 241,138 256,643 271,142 284,901 Whitman 44,776 46,139 47,826 49,346 50,577 51,563 52,504 Yakima 243,231 256,341 269,347 282,057 294,445 306,636 318,494


95


Final Projections of the Total Resident Population for the Growth Management Act Low Series: 2010 to 2040

Census Projections

2010 2015 2020 2025 2030 2035 2040

Washington 6,724,540 6,449,120 6,650,235 6,841,751 7,014,758 7,162,261 7,291,717 Adams 18,728 19,147 19,605 20,004 20,404 20,880 21,470 Asotin 21,623 19,838 19,800 19,715 19,588 19,394 19,158 Benton 175,177 165,472 166,377 167,282 168,187 169,092 169,997 Chelan 72,453 68,266 70,499 72,634 74,396 75,695 76,706 Clallam 71,404 68,000 66,400 64,800 63,200 61,600 60,000 Clark 425,363 420,369 431,998 443,210 452,874 459,621 463,962 Columbia 4,078 3,900 3,800 3,700 3,600 3,500 3,400 Cowlitz 102,410 99,690 99,750 99,810 99,870 99,930 99,990 Douglas 38,431 35,630 36,679 37,754 38,716 39,451 40,031 Ferry 7,551 6,914 6,900 6,846 6,754 6,646 6,507 Franklin 78,163 75,685 82,752 90,781 99,661 109,165 119,568 Garfield 2,266 2,059 1,999 1,939 1,879 1,819 1,759 Grant 89,120 90,398 94,134 98,061 102,220 106,275 110,313 Grays Harbor 72,797 69,161 69,161 69,161 69,161 69,161 69,161 Island 78,506 71,110 70,516 69,867 69,411 69,020 68,949 Jefferson 29,872 27,426 27,426 27,426 27,426 27,426 27,426 King 1,931,249 1,892,015 1,954,815 2,009,490 2,058,120 2,099,661 2,136,369 Kitsap 251,133 232,674 236,712 240,939 243,931 244,823 244,467 Kittitas 40,915 40,036 40,631 41,226 41,821 42,416 43,011 Klickitat 20,318 18,433 18,218 17,952 17,616 17,148 16,574 Lewis 75,455 72,964 72,964 72,964 72,964 72,964 72,964 Lincoln 10,570 9,979 9,974 9,969 9,964 9,959 9,954 Mason 60,699 56,447 58,741 61,075 63,489 65,821 67,925 Okanogan 41,120 38,000 38,000 38,000 38,000 38,000 38,000 Pacific 20,920 20,000 20,000 20,000 20,000 20,000 20,000 Pend Oreille 13,001 11,976 12,097 12,109 11,999 11,767 11,487 Pierce 795,225 749,813 775,290 803,274 827,893 848,210 865,504 San Juan 15,769 14,104 13,896 13,688 13,464 13,189 12,868 Skagit 116,901 109,034 112,269 116,917 121,917 127,041 132,559 Skamania 11,066 10,605 10,785 10,965 11,145 11,325 11,505 Snohomish 713,335 675,034 710,024 743,419 774,922 802,384 826,053 Spokane 471,221 450,827 464,485 477,297 487,917 495,682 501,621 Stevens 43,531 39,271 38,695 38,381 38,207 38,143 38,155 Thurston 252,264 238,686 252,724 264,576 275,352 284,377 291,949 Wahkiakum 3,978 3,617 3,512 3,407 3,302 3,197 3,092 Walla Walla 58,781 56,825 57,090 57,355 57,620 57,885 58,150 Whatcom 201,140 192,540 202,407 210,985 217,628 224,268 230,908 Whitman 44,776 43,371 43,371 43,371 43,371 43,371 43,371 Yakima 243,231 229,804 235,739 241,402 246,769 251,955 256,834


96


Section V. Projections of the Total Resident Population for the Growth Management Act: 2010 to 2040 by Single Year After 2015

97


Proj

ectio

ns o

f the

Tot

al R

esid

ent P

opul

atio

n fo

r the

Gro

wth

Man

agem

ent A

ct

Hig

h Se

ries:

201

0 to

204

0 by

Sin

gle

Year

Afte

r 201

5

Ce

nsus

20

10

2015

20

16

2017

20

18

2019

20

20

2021

20

22

2023

20

24

2025

20

26

2027

W

ashin

gton

6,724

,540

7,696

,794

7,789

,204

7,927

,837

8,063

,285

8,195

,266

8,323

,502

8,441

,134

8,565

,855

8,691

,181

8,817

,087

8,943

,536

9,057

,765

9,179

,402

Adam

s 18

,728

21,08

6 21

,454

21,88

1 22

,307

22,73

3 23

,157

23,53

3 23

,939

24,34

8 24

,758

25,17

1 25

,553

25,95

6 As

otin

21,62

3 24

,527

24,74

5 25

,118

25,47

8 25

,823

26,15

4 26

,454

26,77

3 27

,091

27,41

0 27

,729

28,02

1 28

,329

Bento

n 17

5,177

20

4,290

20

6,660

21

0,565

21

4,355

21

8,021

22

1,552

22

4,836

22

8,296

23

1,779

23

5,285

23

8,813

24

2,109

24

5,567

Ch

elan

72,45

3 80

,635

82,09

4 83

,687

85,29

0 86

,902

88,52

3 90

,014

91,59

6 93

,191

94,79

7 96

,415

97,91

2 99

,493

Clall

am

71,40

4 77

,826

78,30

1 79

,111

79,88

5 80

,623

81,32

2 81

,915

82,55

9 83

,197

83,83

0 84

,456

84,99

1 85

,568

Clar

k 42

5,363

49

7,767

50

4,900

51

5,446

52

5,777

53

5,867

54

5,696

55

4,670

56

4,220

57

3,817

58

3,460

59

3,144

60

1,775

61

1,031

Co

lumbia

4,0

78

4,251

4,2

47

4,258

4,2

68

4,275

4,2

81

4,286

4,2

92

4,297

4,3

03

4,308

4,3

15

4,322

Co

wlitz

10

2,410

11

0,571

11

1,423

11

2,604

11

3,758

11

4,885

11

5,982

11

7,034

11

8,119

11

9,208

12

0,302

12

1,399

12

2,453

12

3,537

Do

uglas

38

,431

45,03

0 45

,696

46,66

8 47

,623

48,55

7 49

,470

50,31

7 51

,212

52,11

4 53

,021

53,93

4 54

,754

55,63

2 Fe

rry

7,551

8,6

20

8,670

8,7

89

8,900

9,0

04

9,101

9,1

85

9,275

9,3

65

9,453

9,5

42

9,615

9,6

95

Fran

klin

78,16

3 10

4,429

10

8,285

11

3,195

11

8,177

12

3,220

12

8,312

13

2,781

13

7,760

14

2,843

14

8,029

15

3,317

15

8,038

16

3,221

Ga

rfield

2,266

2,4

18

2,427

2,4

44

2,460

2,4

76

2,490

2,5

05

2,520

2,5

35

2,551

2,5

66

2,581

2,5

96

Gran

t 89

,120

101,7

20

104,1

82

106,8

03

109,4

61

112,1

57

114,8

90

117,3

78

120,0

50

122,7

52

125,4

86

128,2

50

130,8

10

133,5

30

Gray

s Har

bor

72,79

7 77

,989

78,16

0 78

,671

79,14

8 79

,587

79,99

0 80

,385

80,78

6 81

,187

81,59

0 81

,993

82,38

5 82

,784

Islan

d 78

,506

91,94

2 92

,984

94,75

6 96

,471

98,12

6 99

,714

101,1

72

102,7

16

104,2

72

105,8

41

107,4

20

108,9

48

110,5

29

Jeffe

rson

29,87

2 34

,493

34,99

9 35

,701

36,39

4 37

,077

37,74

7 38

,388

39,05

7 39

,737

40,42

7 41

,127

41,84

8 42

,579

King

1,9

31,24

9 2,1

33,54

9 2,1

57,80

7 2,1

89,40

7 2,2

20,44

5 2,2

50,88

0 2,2

80,67

5 2,3

06,70

1 2,3

34,74

1 2,3

62,75

0 2,3

90,71

7 2,4

18,63

6 2,4

43,65

2 2,4

70,24

8 Ki

tsap

251,1

33

297,4

53

301,5

72

308,0

54

314,3

82

320,5

40

326,5

10

332,0

82

337,9

59

343,8

69

349,8

11

355,7

83

361,0

20

366,6

77

Kittit

as

40,91

5 47

,758

48,46

0 49

,473

50,46

8 51

,443

52,39

6 53

,282

54,21

7 55

,159

56,10

8 57

,063

57,93

2 58

,857

Klick

itat

20,31

8 22

,912

22,99

9 23

,263

23,50

8 23

,734

23,94

1 24

,126

24,32

2 24

,517

24,71

1 24

,904

25,07

3 25

,254

Lewi

s 75

,455

86,42

8 87

,104

88,42

5 89

,686

90,88

4 92

,015

93,03

3 94

,115

95,19

7 96

,278

97,35

6 98

,311

99,33

2 Lin

coln

10,57

0 11

,252

11,24

5 11

,293

11,33

5 11

,371

11,40

1 11

,431

11,46

2 11

,492

11,52

2 11

,553

11,58

3 11

,613

Maso

n 60

,699

69,90

4 70

,880

72,25

7 73

,611

74,93

9 76

,239

77,45

0 78

,725

80,01

2 81

,309

82,61

7 83

,858

85,15

3 Ok

anog

an

41,12

0 47

,000

47,26

2 47

,902

48,50

6 49

,073

49,60

0 50

,103

50,62

3 51

,146

51,67

2 52

,199

52,70

3 53

,223

Pacif

ic 20

,920

22,00

0 22

,085

22,22

2 22

,353

22,48

0 22

,601

22,71

9 22

,839

22,95

9 23

,080

23,20

0 23

,317

23,43

7 Pe

nd O

reille

13

,001

14,70

0 14

,838

15,06

3 15

,280

15,49

0 15

,691

15,87

3 16

,067

16,26

0 16

,453

16,64

5 16

,806

16,98

3 Pi

erce

79

5,225

90

7,454

91

4,327

92

7,750

94

0,624

95

2,918

96

4,601

97

6,448

98

8,423

1,0

00,45

6 1,0

12,54

5 1,0

24,69

0 1,0

35,35

4 1,0

46,79

5 Sa

n Jua

n 15

,769

18,26

8 18

,468

18,80

1 19

,124

19,43

5 19

,735

20,01

5 20

,310

20,60

6 20

,904

21,20

4 21

,482

21,77

4 Sk

agit

116,9

01

137,1

98

139,0

58

141,9

20

144,7

34

147,4

94

150,1

96

153,0

67

155,9

42

158,8

65

161,8

36

164,8

58

167,7

28

170,7

34

Skam

ania

11,06

6 12

,419

12,45

6 12

,585

12,70

7 12

,822

12,93

0 13

,089

13,22

8 13

,371

13,51

7 13

,665

13,79

9 13

,941

Snoh

omish

71

3,335

83

6,250

84

9,237

86

7,735

88

5,910

90

3,722

92

1,133

93

6,708

95

3,448

97

0,273

98

7,177

1,0

04,15

5 1,0

19,43

3 1,0

35,76

2 Sp

okan

e 47

1,221

54

8,976

55

5,476

56

6,018

57

6,251

58

6,149

59

5,685

60

4,370

61

3,598

62

2,849

63

2,121

64

1,411

64

9,572

65

8,357

St

even

s 43

,531

50,73

4 51

,237

52,14

7 53

,027

53,87

5 54

,689

55,51

9 56

,360

57,21

3 58

,077

58,95

1 59

,804

60,68

5 Th

ursto

n 25

2,264

29

5,512

29

9,832

30

6,173

31

2,392

31

8,475

32

4,410

32

9,870

33

5,665

34

1,505

34

7,388

35

3,314

35

8,798

36

4,591

W

ahkia

kum

3,978

4,2

46

4,240

4,2

56

4,269

4,2

81

4,290

4,3

02

4,312

4,3

23

4,333

4,3

44

4,354

4,3

64

Wall

a Wall

a 58

,781

62,48

1 63

,109

63,79

6 64

,482

65,16

8 65

,852

66,50

4 67

,179

67,85

6 68

,537

69,22

1 69

,874

70,54

9 W

hatco

m 20

1,140

23

1,275

23

5,226

24

0,231

24

5,202

25

0,132

25

5,016

25

9,491

26

4,253

26

9,054

27

3,892

27

8,767

28

3,263

28

8,023

W

hitma

n 44

,776

51,09

1 51

,448

52,18

5 52

,887

53,54

9 54

,171

54,72

5 55

,317

55,90

5 56

,491

57,07

3 57

,560

58,09

3 Ya

kima

243,2

31

300,3

40

301,6

11

307,1

84

312,3

50

317,0

79

321,3

44

325,3

73

329,5

80

333,8

11

338,0

65

342,3

43

346,3

81

350,5

88

Notes

: Data

may

be sl

ightly

diffe

rent

from

those

pres

ented

in th

e 5 ye

ar in

terva

ls du

e to r

ound

ing. U

nrou

nded

data

shou

ld no

t be c

onsid

ered

accu

rate

to the

last

digit.

OFM/

Fore

casti

ng | A

ugus

t 201

2

98


Proj

ectio

ns o

f the

Tot

al R

esid

ent P

opul

atio

n fo

r the

Gro

wth

Man

agem

ent A

ct

Hig

h Se

ries:

201

0 to

204

0 by

Sin

gle

Year

Afte

r 201

5 (c

ont.)

20

28

2029

20

30

2031

20

32

2033

20

34

2035

20

36

2037

20

38

2039

20

40

Was

hingto

n 9,3

01,30

8 9,4

23,45

2 9,5

45,79

5 9,6

54,45

2 9,7

70,79

7 9,8

87,27

9 10

,003,8

69

10,12

0,536

10

,229,0

94

10,33

8,920

10

,450,0

30

10,56

2,439

10

,676,1

66

Adam

s 26

,363

26,77

3 27

,187

27,58

8 28

,003

28,42

3 28

,848

29,27

8 29

,706

30,14

0 30

,580

31,02

7 31

,480

Asoti

n 28

,637

28,94

6 29

,253

29,52

9 29

,823

30,11

6 30

,409

30,70

1 30

,976

31,25

3 31

,533

31,81

5 32

,100

Bento

n 24

9,048

25

2,549

25

6,071

25

9,378

26

2,836

26

6,315

26

9,813

27

3,331

27

6,699

28

0,109

28

3,561

28

7,055

29

0,592

Ch

elan

101,0

85

102,6

88

104,3

02

105,8

06

107,3

88

108,9

79

110,5

81

112,1

93

113,7

28

115,2

85

116,8

63

118,4

62

120,0

83

Clall

am

86,13

9 86

,702

87,25

8 87

,697

88,18

8 88

,672

89,15

0 89

,620

90,03

7 90

,456

90,87

7 91

,300

91,72

5 Cl

ark

620,2

92

629,5

55

638,8

16

646,7

41

655,3

72

663,9

84

672,5

72

681,1

35

688,8

68

696,6

89

704,5

98

712,5

98

720,6

88

Colum

bia

4,328

4,3

34

4,341

4,3

47

4,353

4,3

59

4,365

4,3

71

4,377

4,3

82

4,388

4,3

93

4,399

Co

wlitz

12

4,625

12

5,719

12

6,816

12

7,870

12

8,954

13

0,042

13

1,134

13

2,230

13

3,296

13

4,370

13

5,453

13

6,545

13

7,646

Do

uglas

56

,510

57,39

0 58

,272

59,03

2 59

,858

60,68

4 61

,509

62,33

4 63

,093

63,86

2 64

,640

65,42

7 66

,224

Ferry

9,7

75

9,854

9,9

33

10,00

7 10

,083

10,15

9 10

,235

10,31

1 10

,377

10,44

4 10

,511

10,57

8 10

,646

Fran

klin

168,4

98

173,8

68

179,3

27

184,2

17

189,5

50

194,9

71

200,4

77

206,0

67

211,3

49

216,7

66

222,3

22

228,0

20

233,8

65

Garfie

ld 2,6

12

2,627

2,6

43

2,658

2,6

72

2,687

2,7

02

2,717

2,7

32

2,748

2,7

63

2,778

2,7

94

Gran

t 13

6,276

13

9,048

14

1,846

14

4,376

14

7,085

14

9,815

15

2,566

15

5,335

15

7,941

16

0,592

16

3,286

16

6,026

16

8,812

Gr

ays H

arbo

r 83

,185

83,58

6 83

,988

84,38

2 84

,781

85,18

2 85

,583

85,98

5 86

,382

86,78

0 87

,181

87,58

3 87

,987

Islan

d 11

2,123

11

3,730

11

5,351

11

6,882

11

8,479

12

0,091

12

1,718

12

3,359

12

4,992

12

6,646

12

8,323

13

0,021

13

1,742

Je

fferso

n 43

,322

44,07

8 44

,847

45,63

3 46

,430

47,23

6 48

,051

48,87

5 49

,638

50,41

3 51

,201

52,00

0 52

,812

King

2,4

96,80

7 2,5

23,31

9 2,5

49,77

8 2,5

73,21

0 2,5

98,21

3 2,6

23,17

1 2,6

48,07

8 2,6

72,92

9 2,6

96,06

6 2,7

19,40

3 2,7

42,94

2 2,7

66,68

5 2,7

90,63

3 Ki

tsap

372,3

31

377,9

77

383,6

13

388,3

25

393,5

12

398,6

84

403,8

39

408,9

75

413,6

47

418,3

72

423,1

52

427,9

86

432,8

75

Kittit

as

59,78

5 60

,717

61,65

2 62

,487

63,38

1 64

,277

65,17

6 66

,078

66,92

7 67

,786

68,65

6 69

,538

70,43

1 Kl

ickita

t 25

,431

25,60

8 25

,782

25,91

7 26

,070

26,22

1 26

,367

26,51

2 26

,632

26,75

2 26

,872

26,99

3 27

,115

Lewi

s 10

0,349

10

1,363

10

2,375

10

3,263

10

4,214

10

5,164

10

6,113

10

7,061

10

7,969

10

8,886

10

9,810

11

0,741

11

1,681

Lin

coln

11,64

4 11

,674

11,70

5 11

,735

11,76

4 11

,794

11,82

4 11

,854

11,88

3 11

,913

11,94

2 11

,971

12,00

1 Ma

son

86,45

8 87

,771

89,09

2 90

,309

91,59

4 92

,882

94,17

5 95

,471

96,66

2 97

,869

99,09

0 10

0,327

10

1,579

Ok

anog

an

53,74

7 54

,272

54,79

9 55

,304

55,82

4 56

,347

56,87

2 57

,399

57,91

0 58

,426

58,94

6 59

,471

60,00

0 Pa

cific

23,55

7 23

,677

23,79

8 23

,915

24,03

5 24

,155

24,27

6 24

,396

24,51

5 24

,635

24,75

5 24

,876

24,99

7 Pe

nd O

reille

17

,159

17,33

5 17

,509

17,66

5 17

,831

17,99

5 18

,159

18,32

3 18

,469

18,61

7 18

,765

18,91

5 19

,066

Pier

ce

1,058

,191

1,069

,538

1,080

,831

1,090

,460

1,100

,907

1,111

,301

1,121

,639

1,131

,916

1,141

,269

1,150

,699

1,160

,207

1,169

,794

1,179

,460

San J

uan

22,06

7 22

,361

22,65

5 22

,918

23,19

9 23

,480

23,76

1 24

,042

24,30

3 24

,567

24,83

4 25

,104

25,37

7 Sk

agit

173,7

70

176,8

35

179,9

30

182,8

16

185,8

56

188,9

25

192,0

23

195,1

49

198,1

89

201,2

76

204,4

11

207,5

95

210,8

28

Skam

ania

14,08

2 14

,223

14,36

3 14

,483

14,61

3 14

,742

14,86

8 14

,993

15,09

5 15

,197

15,30

0 15

,404

15,50

8 Sn

ohom

ish

1,052

,128

1,068

,527

1,084

,952

1,099

,239

1,114

,700

1,130

,152

1,145

,590

1,161

,006

1,174

,985

1,189

,132

1,203

,449

1,217

,939

1,232

,603

Spok

ane

667,1

29

675,8

86

684,6

22

692,1

23

700,2

63

708,3

83

716,4

81

724,5

54

731,9

67

739,4

56

747,0

22

754,6

65

762,3

86

Stev

ens

61,57

4 62

,472

63,37

9 64

,258

65,16

7 66

,083

67,00

7 67

,940

68,84

4 69

,760

70,68

9 71

,630

72,58

3 Th

ursto

n 37

0,425

37

6,298

38

2,211

38

7,719

39

3,510

39

9,340

40

5,207

41

1,110

41

6,735

42

2,436

42

8,216

43

4,075

44

0,014

W

ahkia

kum

4,374

4,3

85

4,395

4,4

04

4,414

4,4

24

4,433

4,4

43

4,453

4,4

63

4,474

4,4

84

4,494

W

alla W

alla

71,22

6 71

,907

72,59

0 73

,245

73,92

1 74

,599

75,28

0 75

,963

76,62

5 77

,293

77,96

7 78

,646

79,33

2 W

hatco

m 29

2,818

29

7,648

30

2,510

30

7,026

31

1,784

31

6,575

32

1,398

32

6,252

33

0,869

33

5,551

34

0,300

34

5,116

35

0,000

W

hitma

n 58

,622

59,14

5 59

,664

60,10

0 60

,575

61,04

8 61

,519

61,98

8 62

,437

62,88

9 63

,344

63,80

3 64

,265

Yakim

a 35

4,816

35

9,067

36

3,339

36

7,388

37

1,595

37

5,822

38

0,071

38

4,340

38

8,452

39

2,607

39

6,807

40

1,053

40

5,343

Notes

: Data

may

be sl

ightly

diffe

rent

from

those

pres

ented

in th

e 5 ye

ar in

terva

ls du

e to r

ound

ing. U

nrou

nded

data

shou

ld no

t be c

onsid

ered

accu

rate

to the

last

digit.

OFM/

Fore

casti

ng | A

ugus

t 201

2

99


Proj

ectio

ns o

f the

Tot

al R

esid

ent P

opul

atio

n fo

r the

Gro

wth

Man

agem

ent A

ct

Med

ium

Ser

ies:

201

0 to

204

0 by

Sin

gle

Year

Afte

r 201

5

C

ensu

s

20

10

2015

20

16

2017

20

18

2019

20

20

2021

20

22

2023

20

24

2025

20

26

2027

W

ashin

gton

6,724

,540

7,022

,200

7,100

,451

7,178

,675

7,256

,835

7,334

,646

7,411

,977

7,489

,586

7,566

,384

7,642

,316

7,717

,276

7,793

,173

7,867

,861

7,941

,330

Adam

s 18

,728

20,25

7 20

,502

20,79

4 21

,082

21,36

4 21

,640

21,90

4 22

,170

22,43

5 22

,698

22,96

4 23

,235

23,50

0 As

otin

21,62

3 21

,818

21,85

2 21

,905

21,95

4 21

,996

22,03

3 22

,076

22,10

9 22

,141

22,16

7 22

,196

22,23

3 22

,260

Bento

n 17

5,177

18

4,882

18

7,492

19

0,054

19

2,631

19

5,217

19

7,806

20

0,422

20

3,022

20

5,612

20

8,189

21

0,803

21

3,438

21

6,033

Ch

elan

72,45

3 75

,180

75,85

4 76

,550

77,23

8 77

,918

78,58

6 79

,274

79,94

2 80

,598

81,23

8 81

,885

82,49

2 83

,092

Clall

am

71,40

4 71

,868

72,27

3 72

,617

72,95

6 73

,290

73,61

6 73

,919

74,21

5 74

,495

74,75

8 75

,022

75,27

9 75

,514

Clar

k 42

5,363

44

7,201

45

3,499

45

9,548

46

5,638

47

1,753

47

7,884

48

3,971

49

0,058

49

6,096

50

2,077

50

8,124

51

3,953

51

9,781

Co

lumbia

4,0

78

4,047

4,0

38

4,034

4,0

28

4,021

4,0

13

4,006

3,9

97

3,989

3,9

78

3,968

3,9

55

3,942

Co

wlitz

10

2,410

10

5,130

10

5,814

10

6,534

10

7,239

10

7,924

10

8,588

10

9,254

10

9,896

11

0,514

11

1,109

11

1,706

11

2,241

11

2,765

Do

uglas

38

,431

40,60

3 41

,218

41,81

2 42

,411

43,01

4 43

,619

44,23

0 44

,841

45,44

8 46

,051

46,66

2 47

,254

47,84

7 Fe

rry

7,551

7,6

19

7,634

7,6

55

7,674

7,6

91

7,706

7,7

16

7,727

7,7

36

7,743

7,7

51

7,752

7,7

56

Fran

klin

78,16

3 87

,755

90,36

3 92

,902

95,51

1 98

,185

100,9

26

103,6

44

106,4

50

109,2

98

112,1

86

115,1

42

118,0

67

121,0

67

Garfie

ld 2,2

66

2,238

2,2

34

2,231

2,2

28

2,225

2,2

20

2,220

2,2

18

2,215

2,2

12

2,210

2,2

11

2,209

Gr

ant

89,12

0 95

,822

97,44

7 99

,090

100,7

44

102,4

08

104,0

78

105,7

52

107,4

35

109,1

21

110,8

09

112,5

25

114,2

79

116,0

13

Gray

s Har

bor

72,79

7 73

,575

73,70

1 73

,898

74,08

3 74

,253

74,40

8 74

,698

74,91

4 75

,121

75,31

9 75

,529

75,75

5 75

,949

Islan

d 78

,506

80,33

7 80

,808

81,30

7 81

,796

82,27

3 82

,735

83,23

4 83

,700

84,15

9 84

,610

85,07

3 85

,647

86,15

0 Je

fferso

n 29

,872

30,46

9 30

,818

31,10

8 31

,405

31,70

9 32

,017

32,35

9 32

,683

33,01

1 33

,339

33,67

8 34

,100

34,48

3 Ki

ng

1,931

,249

2,012

,782

2,031

,620

2,051

,383

2,070

,888

2,090

,044

2,108

,814

2,126

,575

2,144

,420

2,161

,897

2,178

,979

2,196

,202

2,213

,306

2,229

,846

Kitsa

p 25

1,133

26

2,032

26

4,698

26

7,433

27

0,161

27

2,865

27

5,546

27

8,406

28

1,159

28

3,876

28

6,555

28

9,265

29

1,834

29

4,390

Ki

ttitas

40

,915

42,59

2 43

,152

43,67

1 44

,195

44,72

3 45

,255

45,80

3 46

,343

46,87

9 47

,410

47,94

9 48

,487

49,01

6 Kl

ickita

t 20

,318

20,60

6 20

,667

20,74

3 20

,815

20,88

1 20

,943

21,00

9 21

,068

21,12

2 21

,173

21,22

5 21

,279

21,32

4 Le

wis

75,45

5 77

,621

78,16

9 78

,741

79,30

2 79

,852

80,38

5 80

,920

81,43

8 81

,942

82,43

0 82

,924

83,41

0 83

,873

Linco

ln 10

,570

10,61

6 10

,632

10,65

4 10

,674

10,69

2 10

,707

10,73

3 10

,751

10,76

8 10

,784

10,80

0 10

,820

10,83

5 Ma

son

60,69

9 63

,203

64,13

4 64

,968

65,81

6 66

,675

67,54

5 68

,426

69,30

3 70

,175

71,04

5 71

,929

72,84

9 73

,744

Okan

ogan

41

,120

42,23

0 42

,383

42,59

7 42

,799

42,98

9 43

,163

43,34

5 43

,513

43,67

3 43

,825

43,97

8 44

,128

44,26

4 Pa

cific

20,92

0 20

,860

20,88

4 20

,913

20,94

0 20

,966

20,99

0 21

,067

21,11

6 21

,164

21,21

1 21

,261

21,32

0 21

,368

Pend

Ore

ille

13,00

1 13

,289

13,37

2 13

,457

13,53

8 13

,616

13,69

2 13

,751

13,81

3 13

,871

13,92

5 13

,977

14,01

0 14

,047

Pier

ce

795,2

25

831,9

44

840,6

54

849,6

78

858,6

91

867,6

59

876,5

65

886,4

94

895,9

11

905,2

53

914,5

12

923,9

12

932,8

94

941,8

36

San J

uan

15,76

9 15

,907

15,98

2 16

,052

16,12

2 16

,189

16,25

6 16

,333

16,40

4 16

,473

16,53

7 16

,606

16,68

3 16

,752

Skag

it 11

6,901

12

1,624

12

2,945

12

4,246

12

5,567

12

6,902

12

8,249

12

9,992

13

1,567

13

3,158

13

4,760

13

6,410

13

8,175

13

9,873

Sk

aman

ia 11

,066

11,28

2 11

,328

11,38

3 11

,438

11,49

3 11

,548

11,66

1 11

,747

11,83

4 11

,922

12,01

4 12

,107

12,19

5 Sn

ohom

ish

713,3

35

750,3

58

761,7

34

772,4

28

783,2

24

794,0

90

805,0

15

815,5

47

826,2

28

836,8

26

847,3

26

857,9

39

868,2

97

878,6

22

Spok

ane

471,2

21

489,4

91

494,4

31

499,3

48

504,2

43

509,1

00

513,9

10

518,7

59

523,5

20

528,2

00

532,7

92

537,4

28

541,8

46

546,2

10

Stev

ens

43,53

1 44

,262

44,43

6 44

,636

44,83

4 45

,026

45,21

2 45

,497

45,73

2 45

,967

46,20

2 46

,447

46,75

9 47

,033

Thur

ston

252,2

64

266,2

24

270,9

18

275,1

94

279,5

16

283,8

75

288,2

65

292,0

47

296,0

84

300,0

67

303,9

91

307,9

30

311,6

67

315,4

39

Wah

kiaku

m 3,9

78

3,931

3,9

17

3,909

3,8

99

3,889

3,8

77

3,870

3,8

61

3,851

3,8

41

3,830

3,8

21

3,810

W

alla W

alla

58,78

1 60

,015

60,34

3 60

,690

61,03

1 61

,363

61,68

5 62

,055

62,39

1 62

,719

63,03

9 63

,368

63,73

0 64

,057

Wha

tcom

201,1

40

210,0

50

213,3

03

216,2

28

219,2

09

222,2

35

225,3

07

228,5

14

231,6

67

234,8

14

237,9

51

241,1

38

244,2

86

247,4

18

Whit

man

44,77

6 46

,139

46,47

2 46

,822

47,16

5 47

,501

47,82

6 48

,147

48,45

9 48

,761

49,05

3 49

,346

49,61

0 49

,869

Yakim

a 24

3,231

25

6,341

25

8,730

26

1,462

26

4,150

26

6,780

26

9,347

27

1,956

27

4,512

27

7,037

27

9,530

28

2,057

28

4,652

28

7,148

Notes

: Data

may

be sl

ightly

diffe

rent

from

those

pres

ented

in th

e 5 ye

ar in

terva

ls du

e to r

ound

ing. U

nrou

nded

data

shou

ld no

t be c

onsid

ered

accu

rate

to the

last

digit.

OFM/

Fore

casti

ng | A

ugus

t 201

2

100


Proj

ectio

ns o

f the

Tot

al R

esid

ent P

opul

atio

n fo

r the

Gro

wth

Man

agem

ent A

ct

Med

ium

Ser

ies:

201

0 to

204

0 by

Sin

gle

Year

Afte

r 201

5 (c

ont.)

20

28

2029

20

30

2031

20

32

2033

20

34

2035

20

36

2037

20

38

2039

20

40

Was

hingto

n 8,0

13,60

0 8,0

84,53

9 8,1

54,19

3 8,2

22,55

0 8,2

89,81

5 8,3

55,59

2 8,4

20,09

7 8,4

83,62

8 8,5

46,27

8 8,6

08,25

1 8,6

69,66

0 8,7

30,52

6 8,7

90,98

1 Ad

ams

23,76

3 24

,027

24,28

9 24

,580

24,85

7 25

,134

25,41

1 25

,690

25,99

3 26

,296

26,59

9 26

,901

27,20

5 As

otin

22,28

2 22

,300

22,31

3 22

,335

22,34

6 22

,354

22,35

7 22

,358

22,36

4 22

,365

22,36

5 22

,361

22,35

6 Be

nton

218,6

08

221,1

60

223,6

89

226,2

06

228,6

98

231,1

58

233,5

92

236,0

07

238,3

93

240,7

67

243,1

36

245,4

97

247,8

56

Chela

n 83

,674

84,23

6 84

,778

85,28

3 85

,782

86,26

1 86

,721

87,16

8 87

,603

88,02

6 88

,441

88,84

7 89

,246

Clall

am

75,73

1 75

,931

76,11

2 76

,279

76,43

0 76

,564

76,68

1 76

,786

76,89

3 76

,990

77,07

7 77

,154

77,22

4 Cl

ark

525,5

23

531,1

67

536,7

17

541,9

00

547,1

41

552,2

61

557,2

78

562,2

07

566,8

65

571,4

83

576,0

65

580,6

14

585,1

37

Colum

bia

3,926

3,9

11

3,895

3,8

78

3,859

3,8

40

3,820

3,8

00

3,781

3,7

61

3,741

3,7

21

3,700

Co

wlitz

11

3,261

11

3,724

11

4,158

11

4,524

11

4,886

11

5,216

11

5,519

11

5,798

11

6,047

11

6,280

11

6,498

11

6,703

11

6,897

Do

uglas

48

,432

49,01

2 49

,583

50,12

3 50

,668

51,20

6 51

,734

52,25

6 52

,762

53,26

4 53

,765

54,26

4 54

,762

Ferry

7,7

57

7,757

7,7

54

7,757

7,7

54

7,751

7,7

46

7,740

7,7

32

7,723

7,7

14

7,703

7,6

92

Fran

klin

124,1

05

127,1

77

130,2

84

133,3

42

136,4

83

139,6

53

142,8

59

146,1

03

149,3

57

152,6

60

156,0

18

159,4

30

162,9

00

Garfie

ld 2,2

07

2,205

2,2

02

2,198

2,1

93

2,186

2,1

81

2,175

2,1

70

2,163

2,1

57

2,150

2,1

43

Gran

t 11

7,746

11

9,477

12

1,204

12

2,928

12

4,650

12

6,364

12

8,072

12

9,779

13

1,481

13

3,187

13

4,897

13

6,613

13

8,337

Gr

ays H

arbo

r 76

,126

76,28

5 76

,428

76,55

8 76

,672

76,76

5 76

,842

76,90

5 76

,958

77,00

0 77

,032

77,05

5 77

,070

Islan

d 86

,647

87,13

7 87

,621

88,19

8 88

,716

89,22

6 89

,732

90,23

9 90

,848

91,44

8 92

,041

92,62

6 93

,205

Jeffe

rson

34,87

0 35

,262

35,65

7 36

,139

36,58

3 37

,025

37,46

8 37

,914

38,34

9 38

,786

39,22

1 39

,656

40,09

3 Ki

ng

2,246

,017

2,261

,781

2,277

,160

2,292

,847

2,307

,841

2,322

,417

2,336

,632

2,350

,576

2,364

,682

2,378

,541

2,392

,180

2,405

,604

2,418

,850

Kitsa

p 29

6,879

29

9,295

30

1,642

30

3,714

30

5,828

30

7,864

30

9,830

31

1,737

31

3,547

31

5,322

31

7,067

31

8,783

32

0,475

Ki

ttitas

49

,540

50,05

6 50

,567

51,07

4 51

,573

52,06

6 52

,551

53,03

2 53

,518

54,00

1 54

,482

54,96

0 55

,436

Klick

itat

21,36

5 21

,401

21,43

0 21

,449

21,46

9 21

,483

21,49

0 21

,492

21,48

7 21

,479

21,46

8 21

,455

21,43

9 Le

wis

84,32

0 84

,751

85,16

5 85

,588

85,98

5 86

,366

86,73

3 87

,092

87,48

7 87

,870

88,24

4 88

,610

88,96

7 Lin

coln

10,84

8 10

,858

10,86

5 10

,871

10,87

1 10

,869

10,86

7 10

,862

10,85

6 10

,848

10,83

9 10

,829

10,81

7 Ma

son

74,63

4 75

,521

76,40

1 77

,303

78,18

7 79

,059

79,92

4 80

,784

81,61

6 82

,444

83,27

0 84

,095

84,91

9 Ok

anog

an

44,39

1 44

,509

44,61

9 44

,743

44,84

8 44

,945

45,03

9 45

,127

45,25

4 45

,375

45,49

1 45

,601

45,70

7 Pa

cific

21,41

3 21

,456

21,49

5 21

,558

21,60

5 21

,650

21,69

3 21

,736

21,80

3 21

,866

21,92

7 21

,985

22,04

2 Pe

nd O

reille

14

,080

14,10

7 14

,129

14,13

3 14

,143

14,14

9 14

,152

14,14

9 14

,146

14,14

1 14

,134

14,12

6 14

,116

Pier

ce

950,6

09

959,1

96

967,6

01

975,6

77

983,6

80

991,4

87

999,1

19

1,006

,614

1,013

,921

1,021

,137

1,028

,276

1,035

,339

1,042

,341

San J

uan

16,81

7 16

,879

16,93

9 17

,004

17,06

1 17

,115

17,16

6 17

,216

17,26

4 17

,312

17,35

7 17

,401

17,44

3 Sk

agit

141,5

70

143,2

62

144,9

53

146,7

35

148,4

63

150,1

85

151,9

07

153,6

32

155,4

51

157,2

70

159,0

90

160,9

12

162,7

38

Skam

ania

12,28

1 12

,366

12,44

7 12

,526

12,60

3 12

,677

12,74

8 12

,816

12,87

2 12

,927

12,98

0 13

,031

13,08

2 Sn

ohom

ish

888,8

23

898,8

83

908,8

07

918,2

63

927,7

67

937,0

89

946,2

49

955,2

81

963,8

54

972,3

67

980,8

31

989,2

49

997,6

34

Spok

ane

550,4

64

554,5

95

558,6

14

562,4

19

566,1

74

569,8

05

573,3

29

576,7

63

580,1

17

583,4

09

586,6

47

589,8

30

592,9

69

Stev

ens

47,30

2 47

,568

47,83

4 48

,172

48,46

8 48

,761

49,05

0 49

,340

49,66

6 49

,989

50,30

5 50

,619

50,92

9 Th

ursto

n 31

9,161

32

2,822

32

6,426

32

9,782

33

3,189

33

6,525

33

9,797

34

3,019

34

6,059

34

9,078

35

2,077

35

5,061

35

8,031

W

ahkia

kum

3,797

3,7

85

3,772

3,7

64

3,753

3,7

40

3,728

3,7

16

3,708

3,6

98

3,689

3,6

79

3,669

W

alla W

alla

64,37

5 64

,682

64,97

8 65

,292

65,57

9 65

,855

66,12

1 66

,378

66,64

8 66

,911

67,16

5 67

,414

67,65

5 W

hatco

m 25

0,524

25

3,599

25

6,643

25

9,578

26

2,525

26

5,430

26

8,300

27

1,142

27

3,911

27

6,668

27

9,418

28

2,161

28

4,901

W

hitma

n 50

,117

50,35

3 50

,577

50,79

4 51

,000

51,19

5 51

,383

51,56

3 51

,763

51,95

6 52

,145

52,32

6 52

,504

Yakim

a 28

9,615

29

2,046

29

4,445

29

7,036

29

9,485

30

1,896

30

4,276

30

6,636

30

9,052

31

1,443

31

3,811

31

6,161

31

8,494

Notes

: Data

may

be sl

ightly

diffe

rent

from

those

pres

ented

in th

e 5 ye

ar in

terva

ls du

e to r

ound

ing. U

nrou

nded

data

shou

ld no

t be c

onsid

ered

accu

rate

to the

last

digit.

OFM/

Fore

casti

ng | A

ugus

t 201

2

101


Proj

ectio

ns o

f the

Tot

al R

esid

ent P

opul

atio

n fo

r the

Gro

wth

Man

agem

ent A

ct

Low

Ser

ies:

201

0 to

204

0 by

Sin

gle

Year

Afte

r 201

5

C

ensu

s

20

10

2015

20

16

2017

20

18

2019

20

20

2021

20

22

2023

20

24

2025

20

26

2027

W

ashin

gton

6,724

,540

6,449

,135

6,521

,181

6,545

,400

6,574

,953

6,609

,884

6,650

,247

6,687

,486

6,726

,247

6,764

,872

6,803

,392

6,841

,760

6,874

,869

6,910

,434

Adam

s 18

,728

19,15

1 19

,244

19,33

5 19

,425

19,51

6 19

,606

19,68

1 19

,762

19,84

4 19

,925

20,00

5 20

,082

20,16

1 As

otin

21,62

3 19

,837

19,93

4 19

,875

19,83

4 19

,809

19,80

0 19

,781

19,76

6 19

,750

19,73

3 19

,715

19,68

9 19

,667

Bento

n 17

5,177

16

5,473

16

6,343

16

6,180

16

6,132

16

6,198

16

6,377

16

6,557

16

6,738

16

6,918

16

7,099

16

7,280

16

7,461

16

7,642

Ch

elan

72,45

3 68

,266

69,13

9 69

,372

69,67

6 70

,052

70,49

9 70

,919

71,35

5 71

,786

72,21

3 72

,636

72,96

5 73

,335

Clall

am

71,40

4 68

,000

67,79

1 67

,413

67,05

6 66

,719

66,40

1 66

,076

65,75

6 65

,436

65,11

8 64

,800

64,47

5 64

,156

Clar

k 42

5,363

42

0,372

42

3,803

42

5,570

42

7,523

42

9,665

43

1,998

43

4,209

43

6,484

43

8,744

44

0,985

44

3,210

44

5,072

44

7,094

Co

lumbia

4,0

78

3,902

3,8

87

3,864

3,8

43

3,822

3,8

02

3,782

3,7

62

3,742

3,7

22

3,702

3,6

82

3,662

Co

wlitz

10

2,410

99

,691

99,88

4 99

,806

99,75

7 99

,739

99,75

1 99

,763

99,77

5 99

,787

99,79

9 99

,811

99,82

4 99

,836

Doug

las

38,43

1 35

,627

36,08

9 36

,172

36,29

8 36

,467

36,67

8 36

,894

37,11

0 37

,325

37,54

0 37

,755

37,94

1 38

,140

Ferry

7,5

51

6,913

6,9

43

6,925

6,9

12

6,903

6,9

00

6,887

6,8

79

6,869

6,8

59

6,847

6,8

27

6,811

Fr

ankli

n 78

,163

75,68

6 77

,676

78,75

2 79

,954

81,28

6 82

,753

84,31

8 85

,884

87,48

4 89

,117

90,78

4 92

,503

94,24

5 Ga

rfield

2,266

2,0

59

2,057

2,0

41

2,026

2,0

13

2,001

1,9

89

1,977

1,9

65

1,953

1,9

41

1,929

1,9

16

Gran

t 89

,120

90,39

8 91

,293

91,95

5 92

,649

93,37

6 94

,137

94,91

0 95

,687

96,47

1 97

,263

98,06

2 98

,890

99,71

6 Gr

ays H

arbo

r 72

,797

69,16

3 70

,113

69,63

9 69

,321

69,16

1 69

,159

69,16

0 69

,160

69,16

0 69

,160

69,16

0 69

,160

69,15

9 Isl

and

78,50

6 71

,114

71,43

2 71

,095

70,83

1 70

,638

70,51

6 70

,378

70,24

7 70

,118

69,99

2 69

,866

69,78

6 69

,688

Jeffe

rson

29,87

2 27

,427

27,21

6 27

,320

27,39

0 27

,425

27,42

5 27

,426

27,42

7 27

,427

27,42

7 27

,428

27,42

8 27

,427

King

1,9

31,24

9 1,8

92,01

5 1,9

11,55

8 1,9

20,71

7 1,9

30,97

2 1,9

42,33

5 1,9

54,81

8 1,9

65,12

2 1,9

76,41

5 1,9

87,57

5 1,9

98,60

1 2,0

09,48

9 2,0

18,80

1 2,0

28,82

3 Ki

tsap

251,1

33

232,6

74

234,9

38

235,0

16

235,3

37

235,9

03

236,7

13

237,5

88

238,4

41

239,2

83

240,1

14

240,9

35

241,4

89

242,1

59

Kittit

as

40,91

5 40

,038

40,25

4 40

,324

40,41

1 40

,513

40,63

2 40

,750

40,86

8 40

,987

41,10

6 41

,225

41,34

4 41

,463

Klick

itat

20,31

8 18

,435

18,49

7 18

,402

18,32

5 18

,263

18,21

9 18

,164

18,11

4 18

,062

18,00

9 17

,955

17,88

4 17

,819

Lewi

s 75

,455

72,96

5 73

,292

73,12

8 73

,018

72,96

3 72

,962

72,96

2 72

,962

72,96

3 72

,963

72,96

3 72

,964

72,96

5 Lin

coln

10,57

0 9,9

80

10,02

2 9,9

98

9,982

9,9

74

9,972

9,9

71

9,970

9,9

69

9,968

9,9

67

9,966

9,9

65

Maso

n 60

,699

56,45

0 57

,335

57,57

6 57

,891

58,27

8 58

,741

59,19

8 59

,663

60,13

2 60

,603

61,07

7 61

,554

62,03

5 Ok

anog

an

41,12

0 38

,002

38,00

2 38

,002

38,00

2 38

,002

38,00

2 38

,000

38,00

0 37

,998

37,99

8 37

,997

37,99

8 37

,998

Pacif

ic 20

,920

19,99

9 20

,040

20,02

0 20

,007

20,00

0 20

,000

20,00

1 20

,001

20,00

1 20

,002

20,00

2 20

,002

20,00

2 Pe

nd O

reille

13

,001

11,97

5 12

,084

12,06

9 12

,066

12,07

6 12

,097

12,21

4 12

,097

12,03

2 12

,045

12,11

0 12

,083

12,06

6 Pi

erce

79

5,225

74

9,814

75

9,471

76

2,208

76

5,753

77

0,111

77

5,290

78

1,011

78

6,562

79

2,123

79

7,694

80

3,274

80

7,958

81

3,051

Sa

n Jua

n 15

,769

14,10

0 14

,153

14,06

6 13

,995

13,94

0 13

,899

13,85

6 13

,815

13,77

3 13

,731

13,68

9 13

,644

13,60

1 Sk

agit

116,9

01

109,0

35

110,3

48

110,6

31

111,0

44

111,5

89

112,2

68

113,2

65

114,1

44

115,0

45

115,9

69

116,9

18

117,9

13

118,9

01

Skam

ania

11,06

6 10

,606

10,68

5 10

,700

10,72

1 10

,750

10,78

6 10

,822

10,85

7 10

,893

10,92

9 10

,965

11,00

1 11

,036

Snoh

omish

71

3,335

67

5,033

68

6,890

69

1,427

69

6,786

70

2,980

71

0,024

71

6,432

72

3,197

72

9,950

73

6,691

74

3,417

74

9,502

75

5,921

Sp

okan

e 47

1,221

45

0,827

45

5,838

45

7,434

45

9,406

46

1,754

46

4,483

46

6,990

46

9,609

47

2,200

47

4,763

47

7,297

47

9,301

48

1,536

St

even

s 43

,531

39,26

9 39

,396

39,15

4 38

,958

38,80

6 38

,697

38,64

8 38

,574

38,50

5 38

,441

38,38

1 38

,354

38,31

3 Th

ursto

n 25

2,264

23

8,686

24

3,373

24

5,256

24

7,438

24

9,924

25

2,722

25

4,890

25

7,353

25

9,789

26

2,198

26

4,576

26

6,636

26

8,851

W

ahkia

kum

3,978

3,6

15

3,611

3,5

82

3,556

3,5

33

3,512

3,4

91

3,470

3,4

49

3,429

3,4

08

3,385

3,3

64

Wall

a Wall

a 58

,781

56,82

4 57

,024

57,00

4 57

,008

57,03

7 57

,090

57,14

2 57

,194

57,24

7 57

,300

57,35

2 57

,406

57,45

9 W

hatco

m 20

1,140

19

2,542

19

5,767

19

7,121

19

8,677

20

0,437

20

2,405

20

4,025

20

5,812

20

7,568

20

9,293

21

0,987

21

2,153

21

3,549

W

hitma

n 44

,776

43,37

0 43

,483

43,42

8 43

,391

43,37

3 43

,373

43,37

1 43

,371

43,37

0 43

,370

43,36

9 43

,371

43,37

1 Ya

kima

243,2

31

229,8

02

232,2

76

232,8

23

233,5

82

234,5

54

235,7

39

236,8

43

237,9

89

239,1

32

240,2

70

241,4

05

242,4

46

243,5

31

Notes

: Data

may

be sl

ightly

diffe

rent

from

those

pres

ented

in th

e 5 ye

ar in

terva

ls du

e to r

ound

ing. U

nrou

nded

data

shou

ld no

t be c

onsid

ered

accu

rate

to the

last

digit.

OFM/

Fore

casti

ng | A

ugus

t 201

2

102


Proj

ectio

ns o

f the

Tot

al R

esid

ent P

opul

atio

n fo

r the

Gro

wth

Man

agem

ent A

ct

Low

Ser

ies:

201

0 to

204

0 by

Sin

gle

Year

Afte

r 201

5 (c

ont.)

20

28

2029

20

30

2031

20

32

2033

20

34

2035

20

36

2037

20

38

2039

20

40

Was

hingto

n 6,9

45,60

9 6,9

80,38

8 7,0

14,75

7 7,0

42,28

0 7,0

72,90

7 7,1

03,12

0 7,1

32,90

3 7,1

62,26

5 7,1

87,85

4 7,2

13,58

9 7,2

39,48

3 7,2

65,52

2 7,2

91,72

3 Ad

ams

20,24

1 20

,322

20,40

3 20

,499

20,59

0 20

,684

20,77

9 20

,877

20,99

4 21

,112

21,23

0 21

,349

21,46

9 As

otin

19,64

3 19

,618

19,59

1 19

,548

19,51

1 19

,473

19,43

4 19

,394

19,34

6 19

,298

19,25

0 19

,203

19,15

5 Be

nton

167,8

23

168,0

04

168,1

86

168,3

67

168,5

47

168,7

28

168,9

10

169,0

91

169,2

71

169,4

52

169,6

33

169,8

14

169,9

95

Chela

n 73

,696

74,04

9 74

,392

74,62

5 74

,905

75,17

8 75

,441

75,69

7 75

,898

76,09

9 76

,300

76,50

2 76

,705

Clall

am

63,83

7 63

,519

63,20

1 62

,876

62,55

6 62

,237

61,91

8 61

,600

61,27

6 60

,955

60,63

4 60

,316

59,99

9 Cl

ark

449,0

69

450,9

96

452,8

74

454,0

57

455,5

37

456,9

57

458,3

17

459,6

17

460,4

83

461,3

51

462,2

21

463,0

92

463,9

65

Colum

bia

3,642

3,6

22

3,602

3,5

80

3,560

3,5

40

3,519

3,4

99

3,479

3,4

60

3,440

3,4

21

3,402

Co

wlitz

99

,848

99,86

1 99

,873

99,88

2 99

,893

99,90

3 99

,913

99,92

4 99

,938

99,95

1 99

,965

99,97

8 99

,992

Doug

las

38,33

5 38

,527

38,71

6 38

,849

39,00

6 39

,158

39,30

7 39

,451

39,56

7 39

,682

39,79

9 39

,915

40,03

2 Fe

rry

6,794

6,7

76

6,758

6,7

34

6,713

6,6

91

6,668

6,6

46

6,618

6,5

90

6,563

6,5

35

6,508

Fr

ankli

n 96

,018

97,82

4 99

,661

101,4

79

103,3

52

105,2

58

107,1

95

109,1

66

111,1

71

113,2

13

115,2

92

117,4

10

119,5

66

Garfie

ld 1,9

04

1,892

1,8

80

1,868

1,8

56

1,844

1,8

32

1,820

1,8

07

1,794

1,7

81

1,769

1,7

56

Gran

t 10

0,547

10

1,382

10

2,222

10

3,007

10

3,823

10

4,641

10

5,460

10

6,280

10

7,075

10

7,876

10

8,683

10

9,496

11

0,315

Gr

ays H

arbo

r 69

,159

69,15

9 69

,159

69,16

0 69

,160

69,16

1 69

,161

69,16

2 69

,162

69,16

1 69

,161

69,16

0 69

,160

Islan

d 69

,592

69,49

9 69

,410

69,32

8 69

,243

69,16

3 69

,088

69,01

8 69

,004

68,99

0 68

,977

68,96

3 68

,949

Jeffe

rson

27,42

7 27

,427

27,42

6 27

,426

27,42

6 27

,426

27,42

6 27

,426

27,42

6 27

,427

27,42

7 27

,428

27,42

8 Ki

ng

2,038

,718

2,048

,485

2,058

,121

2,065

,938

2,074

,550

2,083

,042

2,091

,413

2,099

,662

2,106

,953

2,114

,269

2,121

,610

2,128

,977

2,136

,369

Kitsa

p 24

2,789

24

3,379

24

3,930

24

3,974

24

4,253

24

4,487

24

4,677

24

4,823

24

4,752

24

4,681

24

4,610

24

4,539

24

4,468

Ki

ttitas

41

,583

41,70

2 41

,822

41,94

1 42

,060

42,17

9 42

,299

42,41

9 42

,537

42,65

4 42

,773

42,89

1 43

,010

Klick

itat

17,75

3 17

,685

17,61

4 17

,514

17,42

5 17

,335

17,24

2 17

,147

17,03

1 16

,915

16,80

1 16

,687

16,57

4 Le

wis

72,96

6 72

,966

72,96

7 72

,965

72,96

4 72

,963

72,96

2 72

,961

72,96

2 72

,963

72,96

3 72

,964

72,96

5 Lin

coln

9,964

9,9

63

9,962

9,9

62

9,961

9,9

61

9,960

9,9

60

9,959

9,9

57

9,956

9,9

54

9,953

Ma

son

62,51

7 63

,001

63,48

7 63

,943

64,41

6 64

,886

65,35

5 65

,822

66,23

7 66

,655

67,07

6 67

,499

67,92

5 Ok

anog

an

37,99

8 37

,999

37,99

9 37

,999

37,99

9 37

,999

37,99

9 37

,999

37,99

9 37

,999

37,99

9 37

,999

37,99

9 Pa

cific

20,00

1 20

,001

20,00

1 20

,001

20,00

1 20

,001

20,00

1 20

,001

20,00

1 20

,000

20,00

0 19

,999

19,99

9 Pe

nd O

reille

12

,046

12,02

4 12

,000

11,94

6 11

,904

11,86

0 11

,814

11,76

7 11

,710

11,65

4 11

,598

11,54

2 11

,487

Pier

ce

818,0

73

823,0

19

827,8

90

831,6

56

835,9

06

840,0

83

844,1

84

848,2

09

851,6

40

855,0

85

858,5

44

862,0

17

865,5

04

San J

uan

13,55

6 13

,511

13,46

5 13

,406

13,35

3 13

,298

13,24

3 13

,187

13,12

3 13

,059

12,99

6 12

,933

12,87

0 Sk

agit

119,8

97

120,9

03

121,9

18

122,9

15

123,9

32

124,9

58

125,9

93

127,0

38

128,1

23

129,2

18

130,3

22

131,4

35

132,5

58

Skam

ania

11,07

2 11

,108

11,14

4 11

,181

11,21

7 11

,254

11,29

1 11

,328

11,36

3 11

,398

11,43

4 11

,469

11,50

5 Sn

ohom

ish

762,2

99

768,6

32

774,9

20

780,0

87

785,7

69

791,3

82

796,9

22

802,3

86

807,0

65

811,7

71

816,5

04

821,2

65

826,0

54

Spok

ane

483,7

18

485,8

47

487,9

20

489,2

98

490,9

72

492,5

94

494,1

65

495,6

84

496,8

66

498,0

50

499,2

37

500,4

27

501,6

20

Stev

ens

38,27

5 38

,239

38,20

7 38

,201

38,18

3 38

,167

38,15

4 38

,143

38,14

6 38

,148

38,15

1 38

,153

38,15

6 Th

ursto

n 27

1,042

27

3,209

27

5,350

27

7,026

27

8,911

28

0,766

28

2,589

28

4,378

28

5,876

28

7,383

28

8,897

29

0,419

29

1,949

W

ahkia

kum

3,343

3,3

22

3,301

3,2

82

3,262

3,2

41

3,222

3,2

02

3,179

3,1

57

3,135

3,1

13

3,091

W

alla W

alla

57,51

3 57

,566

57,62

0 57

,673

57,72

6 57

,779

57,83

2 57

,885

57,93

9 57

,992

58,04

6 58

,099

58,15

3 W

hatco

m 21

4,926

21

6,286

21

7,625

21

8,928

22

0,258

22

1,591

22

2,927

22

4,267

22

5,580

22

6,900

22

8,228

22

9,563

23

0,907

W

hitma

n 43

,371

43,37

1 43

,372

43,37

2 43

,372

43,37

2 43

,371

43,37

1 43

,371

43,37

1 43

,372

43,37

2 43

,372

Yakim

a 24

4,614

24

5,693

24

6,768

24

7,787

24

8,835

24

9,880

25

0,920

25

1,958

25

2,927

25

3,899

25

4,875

25

5,855

25

6,839

Notes

: Data

may

be sl

ightly

diffe

rent

from

those

pres

ented

in th

e 5 ye

ar in

terva

ls du

e to r

ound

ing. U

nrou

nded

data

shou

ld no

t be c

onsid

ered

accu

rate

to the

last

digit.

OFM/

Fore

casti

ng | A

ugus

t 201

2

103


Appendix A: Data Concepts Projections in this publication assume generally accepted demographic definitions and concepts used by the U.S. Census Bureau. This section presents the most important ones. Reference date. Federal censuses since 1930 have a reference date of April 1. All estimate, vital statistics, and projection data in this publication are based on that date. An April 1 reference date is used because it is considered the time of the year when most people are living at their “usual residence.” Usual residence is an important population count concept and discussed in more detail under resident population. Age ranges. These are based on a person’s age as of April 1. For example, the 5-9 age group includes everyone who has passed their fifth birthday, but not their 10th. Resident population. Most census data and the data here deal with the population that usually resides in an area. People are counted where they usually live, not where they happen to be on April 1. For example, a trucker, businessman, or holiday traveler in a motel on April 1 would be reported as living wherever they usually live, not at the location of their motel. On the other hand, some people have no usual place of residence, so the census reports them as living where they were found by enumerators. Generally, “residence” refers to where one spends the largest part of the year. Resident population for an area includes military personnel, military dependents, persons in correctional facilities, persons living in nursing homes, and other long-term care facilities. College students are considered residents of the place where they live while attending school. This is why student populations show up so dramatically in the age structure of the population in Kittitas and Whitman Counties. Residency is an important issue for planners when the matter of seasonal population and seasonal housing arises. Seasonal populations, such as vacationers or migrant farm workers, are counted as residents of the place they consider their usual home. Yet, these populations absorb a considerable amount of the housing in counties where they live part of the year. Some seasonal housing is for migrant workers. Other seasonal housing is recreational. Examples include vacation homes, timeshare condominiums, and beach, hunting, or ski cabins. In 2000, seasonal housing represented eight percent or more of the total housing in seventeen Washington counties. In Mason, Pacific, Pend Oreille, and San Juan Counties, seasonal housing was 20 to 30 percent of total housing. Seasonal housing implies seasonal population changes. Planners need to deal with the environmental impacts of seasonal housing and the service impacts of seasonal populations such as need for police and fire protection, and infrastructure development and maintenance. Furthermore, many seasonal units are potential year-round housing. Some people sell their city houses upon retirement and move to their rustic hideaway.

104


Appendix B: Historical Data Tables showing historical census results, population estimates, components of change, growth rates, and so forth are included as reference material for users interested in doing analyses of the projections. These data were used both by OFM staff and county officials and planners to help evaluate preliminary versions of the projections. Historical and Projected Population for Growth Management and Other Purposes Medium Series: History 1960 to 2010 for Projections from 2015 to 2040

1960 1965 1970 1975 1980 1985 1990 1995 2000

Washington 2,853,214 3,065,000 3,413,250 3,567,890 4,132,353 4,415,785 4,866,659 5,396,569 5,894,143 Adams 9,929 10,400 12,014 13,100 13,267 13,418 13,603 15,030 16,428 Asotin 12,909 12,900 13,799 14,800 16,823 17,154 17,605 18,937 20,551 Benton 62,070 62,500 67,540 74,500 109,444 108,452 112,560 128,359 142,475 Chelan 40,744 39,800 41,103 40,200 45,061 49,250 52,250 60,079 66,616 Clallam 30,022 31,900 34,770 41,100 51,648 52,465 56,210 60,548 64,179 Clark 93,809 108,500 128,454 156,800 192,227 206,744 238,053 286,804 345,238 Columbia 4,569 4,300 4,439 4,200 4,057 4,046 4,024 4,051 4,064 Cowlitz 57,801 62,500 68,616 72,100 79,548 79,259 82,119 87,232 92,948 Douglas 14,890 15,300 16,787 18,300 22,144 23,206 26,195 29,312 32,603 Ferry 3,889 3,800 3,655 4,600 5,811 6,016 6,295 6,812 7,260 Franklin 23,342 24,200 25,816 27,100 35,025 36,584 37,473 42,516 49,347 Garfield 2,976 2,800 2,911 2,800 2,468 2,418 2,248 2,322 2,397 Grant 46,477 44,500 41,881 43,200 48,522 50,805 54,798 64,099 74,698 Grays Harbor 54,465 56,400 59,553 60,400 66,314 63,870 64,175 65,820 67,194 Island 19,638 22,400 27,011 34,700 44,048 49,661 60,195 66,378 71,558 Jefferson 9,639 9,800 10,661 11,800 15,965 17,873 20,406 23,950 26,299 King 935,014 1,024,000 1,159,375 1,155,300 1,269,898 1,356,552 1,507,305 1,625,241 1,737,046 Kitsap 84,176 89,800 101,732 116,090 147,152 168,709 189,731 218,308 231,969 Kittitas 20,467 22,400 25,039 24,700 24,877 25,407 26,725 29,791 33,362 Klickitat 13,455 12,900 12,138 13,400 15,822 16,504 16,616 17,603 19,161 Lewis 41,858 42,900 45,467 48,700 56,025 56,592 59,358 63,835 68,600 Lincoln 10,919 10,100 9,572 9,500 9,604 9,233 8,864 9,330 10,184 Mason 16,251 17,800 20,918 23,500 31,184 35,125 38,341 44,128 49,405 Okanogan 25,520 25,100 25,867 26,800 30,663 32,687 33,350 36,702 39,564 Pacific 14,674 14,700 15,796 15,800 17,237 17,764 18,882 19,990 20,984 Pend Oreille 6,914 6,100 6,025 7,600 8,580 8,744 8,915 10,267 11,732 Pierce 321,590 358,600 412,344 421,600 485,667 529,753 586,203 649,284 700,818 San Juan 2,872 3,100 3,856 5,400 7,838 8,904 10,035 12,747 14,077 Skagit 51,350 50,900 52,381 54,100 64,138 69,472 79,545 92,627 102,979 Skamania 5,207 5,500 5,845 6,300 7,919 7,946 8,289 9,057 9,872 Snohomish 172,199 212,700 265,236 270,100 337,720 381,094 465,628 531,704 606,024 Spokane 278,333 277,200 287,487 304,300 341,835 351,417 361,333 391,318 417,939 Stevens 17,884 17,500 17,405 21,200 28,979 30,667 30,948 35,523 40,066 Thurston 55,049 64,400 76,894 90,500 124,264 139,738 161,238 186,419 207,355 Wahkiakum 3,426 3,400 3,592 3,700 3,832 3,505 3,327 3,546 3,824 Walla Walla 42,195 41,400 42,176 43,500 47,435 48,287 48,439 51,461 55,180 Whatcom 70,317 75,100 81,983 91,700 106,701 115,483 127,780 149,942 166,826 Whitman 31,263 34,000 37,900 38,900 40,103 39,512 38,775 39,451 40,740 Yakima 145,112 143,400 145,212 155,500 172,508 181,469 188,823 206,046 222,581


105


Historical and Projected Population for Growth Management and Other Purposes Medium Series: History 1960 to 2010 for Projections from 2015 to 2040 (cont.)

2005 2010 2015 2020 2025 2030 2035 2040

Washington 6,298,816 6,724,540 7,022,200 7,411,977 7,793,173 8,154,193 8,483,628 8,790,981 Adams 17,643 18,728 20,257 21,640 22,964 24,289 25,690 27,205 Asotin 20,939 21,623 21,818 22,033 22,196 22,313 22,358 22,356 Benton 159,286 175,177 184,882 197,806 210,803 223,689 236,007 247,856 Chelan 68,963 72,453 75,180 78,586 81,885 84,778 87,168 89,246 Clallam 67,672 71,404 71,868 73,616 75,022 76,112 76,786 77,224 Clark 394,600 425,363 447,201 477,884 508,124 536,717 562,207 585,137 Columbia 4,135 4,078 4,047 4,013 3,968 3,895 3,800 3,700 Cowlitz 97,673 102,410 105,130 108,588 111,706 114,158 115,798 116,897 Douglas 34,466 38,431 40,603 43,619 46,662 49,583 52,256 54,762 Ferry 7,405 7,551 7,619 7,706 7,751 7,754 7,740 7,692 Franklin 62,572 78,163 87,755 100,926 115,142 130,284 146,103 162,900 Garfield 2,315 2,266 2,238 2,220 2,210 2,202 2,175 2,143 Grant 80,121 89,120 95,822 104,078 112,525 121,204 129,779 138,337 Grays Harbor 70,812 72,797 73,575 74,408 75,529 76,428 76,905 77,070 Island 75,951 78,506 80,337 82,735 85,073 87,621 90,239 93,205 Jefferson 28,356 29,872 30,469 32,017 33,678 35,657 37,914 40,093 King 1,814,999 1,931,249 2,012,782 2,108,814 2,196,202 2,277,160 2,350,576 2,418,850 Kitsap 239,819 251,133 262,032 275,546 289,265 301,642 311,737 320,475 Kittitas 37,660 40,915 42,592 45,255 47,949 50,567 53,032 55,436 Klickitat 19,753 20,318 20,606 20,943 21,225 21,430 21,492 21,439 Lewis 71,771 75,455 77,621 80,385 82,924 85,165 87,092 88,967 Lincoln 10,367 10,570 10,616 10,707 10,800 10,865 10,862 10,817 Mason 54,739 60,699 63,203 67,545 71,929 76,401 80,784 84,919 Okanogan 40,267 41,120 42,230 43,163 43,978 44,619 45,127 45,707 Pacific 20,675 20,920 20,860 20,990 21,261 21,495 21,736 22,042 Pend Oreille 12,356 13,001 13,289 13,692 13,977 14,129 14,149 14,116 Pierce 756,919 795,225 831,944 876,565 923,912 967,601 1,006,614 1,042,341 San Juan 15,180 15,769 15,907 16,256 16,606 16,939 17,216 17,443 Skagit 109,977 116,901 121,624 128,249 136,410 144,953 153,632 162,738 Skamania 10,515 11,066 11,282 11,548 12,014 12,447 12,816 13,082 Snohomish 661,346 713,335 750,358 805,015 857,939 908,807 955,281 997,634 Spokane 438,249 471,221 489,491 513,910 537,428 558,614 576,763 592,969 Stevens 41,792 43,531 44,262 45,212 46,447 47,834 49,340 50,929 Thurston 229,286 252,264 266,224 288,265 307,930 326,426 343,019 358,031 Wahkiakum 3,867 3,978 3,931 3,877 3,830 3,772 3,716 3,669 Walla Walla 57,005 58,781 60,015 61,685 63,368 64,978 66,378 67,655 Whatcom 184,965 201,140 210,050 225,307 241,138 256,643 271,142 284,901 Whitman 42,498 44,776 46,139 47,826 49,346 50,577 51,563 52,504 Yakima 231,902 243,231 256,341 269,347 282,057 294,445 306,636 318,494


106


Historical and Projected Net Migration for Growth Management and Other Purposes Medium Series: History 1960 to 2010, Projections 2015 to 2040

1960-65 1965-70 1970-75 1975-80 1980-85 1985-90 1990-95 1995-00

Washington 36,630 217,905 46,357 427,242 101,529 267,625 328,454 316,328 Adams -404 967 264 -911 -914 -602 417 389 Asotin -522 633 755 1,707 -171 71 1,085 1,418 Benton -4,894 1,734 4,040 29,687 -8,597 -1,801 9,926 8,148 Chelan -2,599 362 -1,341 3,921 2,655 1,068 5,674 4,399 Clallam 183 2,014 5,318 9,038 -700 2,919 4,243 4,253 Clark 9,188 14,989 22,551 27,442 5,334 21,814 37,180 44,397 Columbia -370 110 -202 -196 -38 -17 41 61 Cowlitz 943 2,814 449 4,275 -3,214 308 2,699 3,996 Douglas -389 986 954 2,871 7 2,115 1,883 2,209 Ferry -295 -277 744 965 -126 95 372 388 Franklin -967 265 -189 5,261 -1,688 -1,693 1,487 3,080 Garfield -291 61 -158 -392 -103 -139 139 125 Grant -7,584 -4,909 -870 2,487 -646 1,302 5,943 6,534 Grays Harbor -204 1,576 -506 3,912 -4,591 -918 736 824 Island 406 2,719 5,700 7,050 3,076 7,926 3,162 2,964 Jefferson -231 669 1,072 3,883 1,567 2,434 3,470 2,644 King 31,231 88,469 -31,056 86,710 42,639 98,064 60,039 60,362 Kitsap 1,315 8,496 10,807 25,620 13,425 12,557 18,499 5,935 Kittitas 1,015 1,992 -930 -357 -120 878 2,591 3,091 Klickitat -1,377 -1,171 879 1,785 11 -302 598 1,163 Lewis -163 1,674 2,188 5,442 -1,428 1,462 3,379 3,892 Lincoln -1,215 -603 -99 -37 -486 -364 482 882 Mason 833 2,595 2,111 6,863 2,809 2,553 5,250 5,030 Okanogan -1,584 173 165 2,783 476 -358 2,144 1,924 Pacific -203 1,020 -8 1,241 369 1,212 1,261 1,372 Pend Oreille -1,139 -246 1,361 636 -95 -30 1,121 1,351 Pierce 12,561 34,009 -7,951 41,799 16,144 28,018 34,618 27,639 San Juan 286 808 1,596 2,366 939 956 2,656 1,321 Skagit -2,522 247 666 8,491 3,066 8,124 10,560 8,074 Skamania -36 160 228 1,284 -377 59 595 655 Snohomish 27,666 40,499 -6,598 55,347 24,586 62,379 41,072 51,295 Spokane -16,370 1,938 7,375 26,137 -3,784 -1,744 18,086 16,454 Stevens -966 -468 3,261 6,603 206 -692 3,877 3,848 Thurston 5,414 9,675 10,481 29,359 9,387 15,863 19,261 16,009 Wahkiakum -125 142 39 16 -348 -172 248 329 Walla Walla -2,398 2 1,054 3,170 -357 -554 1,997 2,738 Whatcom 2,263 5,157 7,443 11,697 4,569 8,595 17,838 12,858 Whitman 772 2,502 -199 -22 -1,946 -1,668 -327 303 Yakima -10,598 -3,878 4,963 9,309 -7 -2,093 4,152 3,974


107


Historical and Projected Net Migration for Growth Management and Other Purposes Medium Series: History 1960 to 2010, Projections 2015 to 2040 (cont.)

2000-05 2005-10 2010-15 2015-20 2020-25 2025-30 2030-35 2035-40

Washington 227,982 222,154 104,909 210,000 217,000 225,000 225,000 225,000 Adams 28 -449 -154 -379 -475 -559 -638 -702 Asotin 148 572 246 483 602 711 810 905 Benton 11,055 9,627 3,253 6,569 6,803 7,054 7,037 7,011 Chelan 572 1,465 898 1,544 1,487 1,470 1,431 1,432 Clallam 4,476 4,977 1,887 3,548 3,536 3,605 3,551 3,544 Clark 34,817 15,571 9,187 17,871 17,658 18,002 17,859 17,923 Columbia 130 -18 31 40 47 57 60 61 Cowlitz 3,327 3,196 1,105 1,924 1,849 1,851 1,801 1,802 Douglas 920 2,553 940 1,761 1,749 1,771 1,742 1,742 Ferry 75 186 133 199 226 238 270 265 Franklin 8,497 9,215 2,828 5,766 6,003 6,255 6,222 6,126 Garfield -34 -4 19 26 25 33 34 39 Grant 1,206 4,050 1,589 3,222 3,338 3,451 3,424 3,394 Grays Harbor 3,565 1,472 372 801 1,224 1,353 1,310 1,296 Island 2,541 865 924 2,048 2,535 3,243 3,667 4,103 Jefferson 2,438 2,044 1,500 2,713 3,010 3,597 4,170 4,244 King 23,963 51,588 19,052 41,006 38,167 37,024 35,984 35,697 Kitsap 1,907 5,820 5,410 8,356 9,788 10,302 10,140 10,091 Kittitas 3,731 2,616 1,072 2,018 2,023 2,058 2,033 2,032 Klickitat 281 322 198 403 484 576 612 609 Lewis 2,719 2,702 1,078 1,952 1,909 1,932 1,881 1,896 Lincoln 264 298 106 185 182 175 167 170 Mason 5,145 5,628 2,265 4,493 4,811 5,159 5,332 5,310 Okanogan 77 -97 118 214 395 491 561 648 Pacific 230 691 347 691 975 1,057 1,137 1,221 Pend Oreille 680 637 280 467 441 437 428 418 Pierce 32,325 10,114 10,050 18,294 22,351 23,022 22,639 22,500 San Juan 1,201 700 442 836 1,040 1,152 1,236 1,258 Skagit 4,962 4,539 2,458 4,810 6,889 7,928 8,776 9,629 Skamania 478 381 156 265 512 551 588 579 Snohomish 32,619 26,881 14,755 32,528 32,486 34,526 34,578 34,097 Spokane 11,275 22,284 7,416 14,381 14,343 14,647 14,441 14,464 Stevens 1,335 1,466 699 1,235 1,738 2,028 2,261 2,426 Thurston 17,268 17,378 8,456 17,028 15,333 15,555 15,058 14,502 Wahkiakum 155 198 63 113 163 184 203 211 Walla Walla 947 1,123 465 829 802 812 790 792 Whatcom 14,475 11,975 5,313 11,814 12,873 13,727 14,020 14,028 Whitman 870 1,260 345 660 663 676 672 671 Yakima -2,686 -1,672 -393 -714 -985 -1,151 -1,287 -1,434


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Appendix C: Population Age 65 and Over Population Age 65 and Over Medium Series: History 2010, Projections 2015 to 2040

Census Projections

2010 2015 2020 2025 2030 2035 2040

Washington 827,677 989,124 1,210,895 1,449,119 1,654,289 1,774,401 1,857,527 Adams 1,915 2,044 2,264 2,505 2,700 2,838 3,034 Asotin 4,172 4,879 5,713 6,441 6,985 6,985 6,815 Benton 20,586 24,797 30,642 36,394 41,314 43,850 45,651 Chelan 11,175 12,803 15,509 18,493 20,769 21,705 22,029 Clallam 17,189 18,600 21,311 24,213 25,677 25,340 24,596 Clark 48,710 60,822 76,033 91,612 106,363 116,716 125,863 Columbia 937 1,095 1,225 1,315 1,396 1,317 1,214 Cowlitz 15,805 18,591 22,054 25,804 28,469 29,464 29,835 Douglas 5,443 6,519 7,962 9,480 10,769 11,529 12,157 Ferry 1,428 1,746 2,183 2,423 2,509 2,386 2,230 Franklin 5,696 7,077 9,244 11,492 13,794 16,186 19,282 Garfield 506 533 614 670 701 649 618 Grant 10,531 12,406 14,961 17,872 20,614 22,584 24,723 Grays Harbor 11,849 13,680 15,949 18,414 19,970 20,106 19,782 Island 14,439 16,951 19,847 22,579 24,567 25,058 24,340 Jefferson 7,842 9,428 11,284 13,151 14,179 14,264 13,828 King 210,679 252,100 307,039 365,051 416,445 451,560 477,754 Kitsap 33,296 42,450 53,818 64,814 73,610 77,058 77,458 Kittitas 5,212 6,034 7,360 8,829 9,885 10,334 10,638 Klickitat 3,625 4,584 5,739 6,524 6,938 6,888 6,747 Lewis 13,076 14,558 16,527 18,814 20,458 20,711 20,446 Lincoln 2,197 2,495 2,822 3,207 3,277 3,141 2,889 Mason 11,112 13,013 15,964 19,166 21,797 22,747 23,172 Okanogan 7,070 8,761 10,536 11,985 12,667 12,491 12,097 Pacific 5,183 5,826 6,679 7,341 7,552 7,389 6,914 Pend Oreille 2,485 3,169 3,944 4,533 4,846 4,720 4,473 Pierce 87,785 103,731 127,147 157,687 185,413 203,474 215,807 San Juan 3,657 4,693 5,684 6,319 6,520 6,311 6,013 Skagit 18,876 22,548 27,682 33,107 37,575 40,025 41,606 Skamania 1,596 1,990 2,612 3,183 3,616 3,685 3,664 Snohomish 73,544 90,203 116,172 147,831 178,728 199,920 215,336 Spokane 60,969 71,611 87,302 103,887 118,007 124,248 127,847 Stevens 7,516 9,388 11,386 13,201 14,067 14,051 13,748 Thurston 32,764 39,940 49,971 59,426 67,252 72,179 76,368 Wahkiakum 1,015 1,302 1,507 1,562 1,595 1,509 1,386 Walla Walla 8,778 9,485 10,657 11,973 12,783 12,868 12,791 Whatcom 26,640 32,426 40,387 47,915 54,553 58,614 61,629 Whitman 4,257 4,691 5,521 6,451 7,074 7,331 7,444 Yakima 28,122 32,155 37,644 43,455 48,855 52,170 55,303

Note: Unrounded data should not be considered accurate to the last digit.

OFM/Forecasting | August 2012

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Population Age 65 and Over as a Percent of Total County Population Medium Series: History 2010 and Projections from 2015 to 2040

Census Projections

2010 2015 2020 2025 2030 2035 2040

Washington 12.31 14.09 16.34 18.59 20.29 20.92 21.13 Adams 10.23 10.09 10.46 10.91 11.12 11.05 11.15 Asotin 19.29 22.36 25.93 29.02 31.30 31.24 30.48 Benton 11.75 13.41 15.49 17.26 18.47 18.58 18.42 Chelan 15.42 17.03 19.74 22.58 24.50 24.90 24.68 Clallam 24.07 25.88 28.95 32.27 33.74 33.00 31.85 Clark 11.45 13.60 15.91 18.03 19.82 20.76 21.51 Columbia 22.98 27.06 30.53 33.14 35.84 34.66 32.81 Cowlitz 15.43 17.68 20.31 23.10 24.94 25.44 25.52 Douglas 14.16 16.06 18.25 20.32 21.72 22.06 22.20 Ferry 18.91 22.92 28.33 31.26 32.36 30.83 28.99 Franklin 7.29 8.06 9.16 9.98 10.59 11.08 11.84 Garfield 22.33 23.82 27.66 30.32 31.83 29.84 28.84 Grant 11.82 12.95 14.37 15.88 17.01 17.40 17.87 Grays Harbor 16.28 18.59 21.43 24.38 26.13 26.14 25.67 Island 18.39 21.10 23.99 26.54 28.04 27.77 26.11 Jefferson 26.25 30.94 35.24 39.05 39.76 37.62 34.49 King 10.91 12.52 14.56 16.62 18.29 19.21 19.75 Kitsap 13.26 16.20 19.53 22.41 24.40 24.72 24.17 Kittitas 12.74 14.17 16.26 18.41 19.55 19.49 19.19 Klickitat 17.84 22.25 27.40 30.74 32.38 32.05 31.47 Lewis 17.33 18.76 20.56 22.69 24.02 23.78 22.98 Lincoln 20.79 23.50 26.36 29.69 30.16 28.92 26.71 Mason 18.31 20.59 23.63 26.65 28.53 28.16 27.29 Okanogan 17.19 20.75 24.41 27.25 28.39 27.68 26.47 Pacific 24.78 27.93 31.82 34.53 35.13 33.99 31.37 Pend Oreille 19.11 23.85 28.81 32.43 34.30 33.36 31.69 Pierce 11.04 12.47 14.51 17.07 19.16 20.21 20.70 San Juan 23.19 29.50 34.97 38.05 38.49 36.66 34.47 Skagit 16.15 18.54 21.58 24.27 25.92 26.05 25.57 Skamania 14.42 17.64 22.62 26.49 29.05 28.75 28.01 Snohomish 10.31 12.02 14.43 17.23 19.67 20.93 21.58 Spokane 12.94 14.63 16.99 19.33 21.12 21.54 21.56 Stevens 17.27 21.21 25.18 28.42 29.41 28.48 26.99 Thurston 12.99 15.00 17.34 19.30 20.60 21.04 21.33 Wahkiakum 25.52 33.12 38.87 40.78 42.29 40.61 37.78 Walla Walla 14.93 15.80 17.28 18.89 19.67 19.39 18.91 Whatcom 13.24 15.44 17.93 19.87 21.26 21.62 21.63 Whitman 9.51 10.17 11.54 13.07 13.99 14.22 14.18 Yakima 11.56 12.54 13.98 15.41 16.59 17.01 17.36

OFM/Forecasting | August 2012

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Appendix D: RCW 43.62.035 Determining Population – Projections The Office of Financial Management (OFM) shall determine the population of each county of the state annually as of April 1 of each year and on or before July 1 of each year shall file a certificate with the Office of the Secretary of State (SOS) showing its determination of the population for each county. OFM also shall determine the percentage increase in population for each county over the preceding ten-year period, as of April 1, and shall file a certificate with the SOS by July 1 showing its determination. At least once every five years or upon the availability of decennial census data, whichever is later, the OFM shall prepare twenty-year growth management planning population projections required by RCW 36.70A.110 for each county that adopts a comprehensive plan under RCW 36.70A.040 and shall review these projections with such counties and the cities in those counties before final adoption. The county and its cities may provide to the office such information as they deem relevant to the office's projection, and the office shall consider and comment on such information before adoption. Each projection shall be expressed as a reasonable range developed within the standard state high and low projection. The middle range shall represent the office's estimate of the most likely population projection for the county. If any city or county believes that a projection will not accurately reflect actual population growth in a county, it may petition the office to revise the projection accordingly. The office shall complete the first set of ranges for every county by December 31, 1995. A comprehensive plan adopted or amended before December 31, 1995, shall not be considered to be in noncompliance with the twenty-year growth management planning population projection if the projection used in the comprehensive plan is in compliance with the range later adopted under this section. [1997 c 429 § 26; 1995 c 162 § 1; 1991 sp.s. c 32 § 30; 1990 1st ex.s. c 17 § 32.] NOTES: Severability -- 1997 c 429: See note following RCW 36.70A.3201. Effective date -- 1995 c 162: "This act is necessary for the immediate preservation of the public peace, health, or safety, or support of the state government and its existing public institutions, and shall take effect immediately [April 27, 1995]." [1995 c 162 § 2.] Section headings not law -- 1991 sp.s. c 32: See RCW 36.70A.902. Severability -- Part, section headings not law -- 1990 1st ex.s. c 17: See RCW 36.70A.900 and 36.70A.901.

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http://apps.leg.wa.gov/RCW/default.aspx?cite=36.70A.110






Washington state office of financial ManageMent

insurance Building • Po Box 43113olyMPia, Wa 98504-3113 • (360) 902-0555 • fax (360) 664-2832

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