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• 51. [Article] Canby School District: Enrollment Forecasts 2007-08 to 2011-12

  The Canby School District (CSD) enrolled 5,075 students in Fall 2006, a decrease of 171 students (3.3 percent) from Fall 2005. Much of the K-12 decrease was due to a relatively small kindergarten class ...

  Citation × Citation Citation Abstract Copy Title: Canby School District: Enrollment Forecasts 2007-08 to 2011-12 Author: Portland State University. Population Research Center, Rynerson, Charles, Siu, Vivian Year: 2007 The Canby School District (CSD) enrolled 5,075 students in Fall 2006, a decrease of 171 students (3.3 percent) from Fall 2005. Much of the K-12 decrease was due to a relatively small kindergarten class entering and a record large 12th grade class graduating. Also, unlike most previous years, the District did not have a net gain of students due to migration of families with children. This report presents the results of a demographic study conducted by the Portland State University Population Research Center (PRC). The study includes analysis of population, housing and enrollment trends affecting the District in recent years and forecasts of district-wide and individual school enrollments for the 2007-08 to 2011-12 school years. Title: Canby School District: Enrollment Forecasts 2007-08 to 2011-12 Author: Portland State University. Population Research Center, Rynerson, Charles, Siu, Vivian Year: 2007 The Canby School District (CSD) enrolled 5,075 students in Fall 2006, a decrease of 171 students (3.3 percent) from Fall 2005. Much of the K-12 decrease was due to a relatively small kindergarten class entering and a record large 12th grade class graduating. Also, unlike most previous years, the District did not have a net gain of students due to migration of families with children. This report presents the results of a demographic study conducted by the Portland State University Population Research Center (PRC). The study includes analysis of population, housing and enrollment trends affecting the District in recent years and forecasts of district-wide and individual school enrollments for the 2007-08 to 2011-12 school years. Close

• 52. [Article] Revisiting Rajneeshpuram: Oregon's Largest Utopian Community as Western History

  Between 1981 and 1985, the intentional community of Rajneeshpuram near Antelope, Oregon, hosted up to 15,000 followers of Bhagwan Shree Rajneesh, a spiritual leader from Pune, India. In this essay, Carl ...

  Citation × Citation Citation Abstract Copy Title: Revisiting Rajneeshpuram: Oregon's Largest Utopian Community as Western History Author: Abbott, Carl Year: 2015 Between 1981 and 1985, the intentional community of Rajneeshpuram near Antelope, Oregon, hosted up to 15,000 followers of Bhagwan Shree Rajneesh, a spiritual leader from Pune, India. In this essay, Carl Abbott examines the rise and fall of Rajneeshpuram within the context of western history, which “centers on the processes of migration, settlement, displacement, and rearrangement.” Drawing parallels to earlier religious closed communities, such nineteenth century Mormon settlements, Abbott describes how Rajneeshees fit into the “overarching storylines of frontier utopias and the…narrative of settler colonialism.” Unlike Mormon communities, however, Abbott concludes that Rajneeshpuram ultimately failed because its leaders were not willing to compromise community goals when faced with larger state regulatory systems. Title: Revisiting Rajneeshpuram: Oregon's Largest Utopian Community as Western History Author: Abbott, Carl Year: 2015 Between 1981 and 1985, the intentional community of Rajneeshpuram near Antelope, Oregon, hosted up to 15,000 followers of Bhagwan Shree Rajneesh, a spiritual leader from Pune, India. In this essay, Carl Abbott examines the rise and fall of Rajneeshpuram within the context of western history, which “centers on the processes of migration, settlement, displacement, and rearrangement.” Drawing parallels to earlier religious closed communities, such nineteenth century Mormon settlements, Abbott describes how Rajneeshees fit into the “overarching storylines of frontier utopias and the…narrative of settler colonialism.” Unlike Mormon communities, however, Abbott concludes that Rajneeshpuram ultimately failed because its leaders were not willing to compromise community goals when faced with larger state regulatory systems. Close

• 53. [Article] College-Educated Flock to Central Oregon, Metropolitan Portland

  The number of college-educated Oregonians grew steadily during the past two decades — especially in Central Oregon — but there were significant regional disparities across the state, census data show. ...

  Citation × Citation Citation Abstract Copy Title: College-Educated Flock to Central Oregon, Metropolitan Portland Author: Jurjevich, Jason R., Burnham, Michael Year: 2011 The number of college-educated Oregonians grew steadily during the past two decades — especially in Central Oregon — but there were significant regional disparities across the state, census data show. The proportion of Oregon residents age 25 and older with at least a bachelor’s degree grew from 20.6 percent in 1990 to 25.1 percent in 2000. The figure climbed to 28.3 percent during the 2005-2009 period, according to newly released American Community Survey (ACS) estimates from the U.S. Census Bureau. The margin of error for the five-year period was plus or minus 0.3 percent. Average educational attainment in the Portland metropolitan area, which includes Multnomah, Clackamas and Washington counties, was consistently higher than the state average during the past two decades. What’s more, the proportion of college-educated people in the three counties increased more precipitously than any other part of Oregon. Title: College-Educated Flock to Central Oregon, Metropolitan Portland Author: Jurjevich, Jason R., Burnham, Michael Year: 2011 The number of college-educated Oregonians grew steadily during the past two decades — especially in Central Oregon — but there were significant regional disparities across the state, census data show. The proportion of Oregon residents age 25 and older with at least a bachelor’s degree grew from 20.6 percent in 1990 to 25.1 percent in 2000. The figure climbed to 28.3 percent during the 2005-2009 period, according to newly released American Community Survey (ACS) estimates from the U.S. Census Bureau. The margin of error for the five-year period was plus or minus 0.3 percent. Average educational attainment in the Portland metropolitan area, which includes Multnomah, Clackamas and Washington counties, was consistently higher than the state average during the past two decades. What’s more, the proportion of college-educated people in the three counties increased more precipitously than any other part of Oregon. Close

• 54. [Article] Eugene 4J School District Population and Enrollment Forcasts 2016‐17 to 2025‐26

  The Eugene 4J School District (4J) requested that the Portland State University Population Research Center (PRC) prepare enrollment forecasts for the District and its schools in collaboration with Lane ...

  Citation × Citation Citation Abstract Copy Title: Eugene 4J School District Population and Enrollment Forcasts 2016‐17 to 2025‐26 Author: Portland State University. Population Research Center, Rynerson, Charles, Stewart, Scott Year: 2016 The Eugene 4J School District (4J) requested that the Portland State University Population Research Center (PRC) prepare enrollment forecasts for the District and its schools in collaboration with Lane Council of Governments (LCOG). This report presents a range of three scenarios of district‐wide enrollment forecasts by grade level for 4J for the 10 year period between 2016‐17 and 2025‐26. Each enrollment forecast scenario is related to population forecasts that incorporate different assumptions about growth within the District, with the primary differences being the contribution of net migration to the District’s population and age distribution. Individual school forecasts consistent with the middle range scenario are also presented for the 10 year period. Title: Eugene 4J School District Population and Enrollment Forcasts 2016‐17 to 2025‐26 Author: Portland State University. Population Research Center, Rynerson, Charles, Stewart, Scott Year: 2016 The Eugene 4J School District (4J) requested that the Portland State University Population Research Center (PRC) prepare enrollment forecasts for the District and its schools in collaboration with Lane Council of Governments (LCOG). This report presents a range of three scenarios of district‐wide enrollment forecasts by grade level for 4J for the 10 year period between 2016‐17 and 2025‐26. Each enrollment forecast scenario is related to population forecasts that incorporate different assumptions about growth within the District, with the primary differences being the contribution of net migration to the District’s population and age distribution. Individual school forecasts consistent with the middle range scenario are also presented for the 10 year period. Close

• 55. [Article] Forest Grove School District: Enrollment Forecast 2016-17 to 2025-26

  This report presents a series of three scenarios of district-wide enrollment forecasts by grade level for the Forest Grove School District (FGSD) for the 10 year period between 2016-17 and 2025-26. Each ...

  Citation × Citation Citation Abstract Copy Title: Forest Grove School District: Enrollment Forecast 2016-17 to 2025-26 Author: Portland State University. Population Research Center, Rynerson, Charles, Stewart, Scott, Chun, Nicholas Year: 2016 This report presents a series of three scenarios of district-wide enrollment forecasts by grade level for the Forest Grove School District (FGSD) for the 10 year period between 2016-17 and 2025-26. Each enrollment forecast scenario is related to population forecasts that incorporate different assumptions about growth within the District, with the primary differences being the contribution of net migration to the District’s population and age distribution. Individual school forecasts consistent with the middle series scenario are also presented for the 10 year period. Title: Forest Grove School District: Enrollment Forecast 2016-17 to 2025-26 Author: Portland State University. Population Research Center, Rynerson, Charles, Stewart, Scott, Chun, Nicholas Year: 2016 This report presents a series of three scenarios of district-wide enrollment forecasts by grade level for the Forest Grove School District (FGSD) for the 10 year period between 2016-17 and 2025-26. Each enrollment forecast scenario is related to population forecasts that incorporate different assumptions about growth within the District, with the primary differences being the contribution of net migration to the District’s population and age distribution. Individual school forecasts consistent with the middle series scenario are also presented for the 10 year period. Close

• 56. [Article] Oregon City School District Enrollment Forecasts 2017-18 to 2026-27

  This report presents a range of three scenarios of district‐wide enrollment forecasts by grade level for the Oregon City School District (OCSD) for the 10 year period between 2017‐18 and 2026‐27. Each ...

  Citation × Citation Citation Abstract Copy Title: Oregon City School District Enrollment Forecasts 2017-18 to 2026-27 Author: Portland State University. Population Research Center, Rynerson, Charles, Stewart, Scott, Yang, Xi Year: 2017 This report presents a range of three scenarios of district‐wide enrollment forecasts by grade level for the Oregon City School District (OCSD) for the 10 year period between 2017‐18 and 2026‐27. Each enrollment forecast scenario is related to population forecasts that incorporate different assumptions about growth within the District, with the primary differences being the contribution of net migration to the District’s population and age distribution. Individual school forecasts consistent with the middle range scenario are also presented for the 10 year period. Title: Oregon City School District Enrollment Forecasts 2017-18 to 2026-27 Author: Portland State University. Population Research Center, Rynerson, Charles, Stewart, Scott, Yang, Xi Year: 2017 This report presents a range of three scenarios of district‐wide enrollment forecasts by grade level for the Oregon City School District (OCSD) for the 10 year period between 2017‐18 and 2026‐27. Each enrollment forecast scenario is related to population forecasts that incorporate different assumptions about growth within the District, with the primary differences being the contribution of net migration to the District’s population and age distribution. Individual school forecasts consistent with the middle range scenario are also presented for the 10 year period. Close

• 57. [Article] The State of the Portland MSA Housing Market

  On its surface, the rapid increase of home prices in the Portland Metropolitan Statistical Area (MSA) resembles the overheated moments before the housing bubble burst in 2007. OnPoint Community Credit ...

  Citation × Citation Citation Abstract Copy Title: The State of the Portland MSA Housing Market Author: Portland State University. Northwest Economic Research Center Year: 2016 On its surface, the rapid increase of home prices in the Portland Metropolitan Statistical Area (MSA) resembles the overheated moments before the housing bubble burst in 2007. OnPoint Community Credit Union, concerned that history may already be repeating itself, asked the Northwest Economic Research Center (NERC) to investigate speculation within the Portland housing market, provide a forecast of home prices, and summarize potential market headwinds and tailwinds. To accomplish this, NERC estimates the change in local home prices due to ‘fundamental’ drivers. Using population and income to estimate a fundamental home price index (HPI), this analysis compares the fundamental HPI with the actual level of the Case-Shiller HPI to indicate that home values within the Portland MSA are, within a margin of error, correctly valued. This method indicates that increasing growth in income and migration significantly contributes to rising home prices. This comparison also shows a period of undervaluation following the burst of the last bubble, which helps to explain the price growth of the past few years (the ‘expansion phase’ of the recovery). This analysis uses Error-Correction (EC), General Autoregressive Moving Average (GARMA), and Ordinary Least Squares (OLS) models to forecast the inflation-adjusted Case Shiller HPI to the end of the year. The inherent strengths and weaknesses of these models necessitate a discussion of their assumptions and consequent limitations. Encouragingly, each of the models describes the same basic story: that average home sale prices will increase at a decreasing growth rate from June to at least December 2016. Changes to land use and building height restrictions are among the external shocks to home prices not included in the model. Since predicting policy decisions is fraught with risk, real-world awareness of potential political outcomes should accompany all forecasts based on known factors. Due to data limitations, not all of the indicators NERC feels are important to HPI are explicitly included in the models. Instead, these indicators offer supporting evidence. Generally, they describe a tight housing market with high demand (as indicated by income, employment, and migration) and low supply (as indicated by housing permits and inventory levels). This analysis corroborates the model estimations and supports the forecasts. Title: The State of the Portland MSA Housing Market Author: Portland State University. Northwest Economic Research Center Year: 2016 On its surface, the rapid increase of home prices in the Portland Metropolitan Statistical Area (MSA) resembles the overheated moments before the housing bubble burst in 2007. OnPoint Community Credit Union, concerned that history may already be repeating itself, asked the Northwest Economic Research Center (NERC) to investigate speculation within the Portland housing market, provide a forecast of home prices, and summarize potential market headwinds and tailwinds. To accomplish this, NERC estimates the change in local home prices due to ‘fundamental’ drivers. Using population and income to estimate a fundamental home price index (HPI), this analysis compares the fundamental HPI with the actual level of the Case-Shiller HPI to indicate that home values within the Portland MSA are, within a margin of error, correctly valued. This method indicates that increasing growth in income and migration significantly contributes to rising home prices. This comparison also shows a period of undervaluation following the burst of the last bubble, which helps to explain the price growth of the past few years (the ‘expansion phase’ of the recovery). This analysis uses Error-Correction (EC), General Autoregressive Moving Average (GARMA), and Ordinary Least Squares (OLS) models to forecast the inflation-adjusted Case Shiller HPI to the end of the year. The inherent strengths and weaknesses of these models necessitate a discussion of their assumptions and consequent limitations. Encouragingly, each of the models describes the same basic story: that average home sale prices will increase at a decreasing growth rate from June to at least December 2016. Changes to land use and building height restrictions are among the external shocks to home prices not included in the model. Since predicting policy decisions is fraught with risk, real-world awareness of potential political outcomes should accompany all forecasts based on known factors. Due to data limitations, not all of the indicators NERC feels are important to HPI are explicitly included in the models. Instead, these indicators offer supporting evidence. Generally, they describe a tight housing market with high demand (as indicated by income, employment, and migration) and low supply (as indicated by housing permits and inventory levels). This analysis corroborates the model estimations and supports the forecasts. Close

• 58. [Article] Coordinated Population Forecast for Crook County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065

  Different growth patterns occur in different parts of the County and these local trends within the Prineville UGB and the area outside the UGB collectively influence population growth rates for the county ...

  Citation × Citation Citation Abstract Copy Title: Coordinated Population Forecast for Crook County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065 Author: Portland State University. Population Research Center, Ruan, Xiaomin, Proehl, Risa, Jurjevich, Jason R., Rancik, Kevin, Kessi, Janai, Gorecki, Carson, Tetrick, David Year: 2015 Different growth patterns occur in different parts of the County and these local trends within the Prineville UGB and the area outside the UGB collectively influence population growth rates for the county as a whole. Crook County’s total population has grown slowly since 2000; with average annual growth rates of less than one percent between 2000 and 2010 (Figure 1); however the area outside the Prineville UGB experienced more rapid population growth during the 2000s. Prineville, the only UGB, posted an average annual growth rate of 0.6 percent, while the area outside the UGB grew at an average annual rate of 1.2 percent during the 2000 to 2010 period. Crook County experienced substantial swings in net migration throughout the last decade (2000 to 2010), as a result the countywide population growth rate also fluctuated. At the same time an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years. This along with more women choosing to have fewer children and have them at older ages has led to a decline in the number of births. The growing number of deaths and shrinking number of births led to natural decrease—more deaths than births—beginning in 2011. While net inmigration and natural increase contributed to substantial population growth from 2005 to 2008, both of these numbers shrank during more recent years—leading to population decline between 2009 and 2012. Total population in Crook County as a whole as well as within its sub-areas will likely grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035) relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an expected aging population—a demographic trend which will lead to declining natural increase (births minus deaths). As natural increase declines, population growth will become increasingly reliant on net in-migration. Even so, Crook County’s total population is expected to increase by more than 2,700 over the next 20 years (2015-2035) and by more than 4,500 over the entire 50-year forecast period (2015-2065). The Prineville UGB is forecast to show slightly stronger population growth—relative to the 2000s— in the initial 20-year forecast period, but is expected to slow down substantially during the last 30 years. The area outside the UGB will likely grow at a steadier rate than Prineville throughout the forecast period. Title: Coordinated Population Forecast for Crook County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065 Author: Portland State University. Population Research Center, Ruan, Xiaomin, Proehl, Risa, Jurjevich, Jason R., Rancik, Kevin, Kessi, Janai, Gorecki, Carson, Tetrick, David Year: 2015 Different growth patterns occur in different parts of the County and these local trends within the Prineville UGB and the area outside the UGB collectively influence population growth rates for the county as a whole. Crook County’s total population has grown slowly since 2000; with average annual growth rates of less than one percent between 2000 and 2010 (Figure 1); however the area outside the Prineville UGB experienced more rapid population growth during the 2000s. Prineville, the only UGB, posted an average annual growth rate of 0.6 percent, while the area outside the UGB grew at an average annual rate of 1.2 percent during the 2000 to 2010 period. Crook County experienced substantial swings in net migration throughout the last decade (2000 to 2010), as a result the countywide population growth rate also fluctuated. At the same time an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years. This along with more women choosing to have fewer children and have them at older ages has led to a decline in the number of births. The growing number of deaths and shrinking number of births led to natural decrease—more deaths than births—beginning in 2011. While net inmigration and natural increase contributed to substantial population growth from 2005 to 2008, both of these numbers shrank during more recent years—leading to population decline between 2009 and 2012. Total population in Crook County as a whole as well as within its sub-areas will likely grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035) relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an expected aging population—a demographic trend which will lead to declining natural increase (births minus deaths). As natural increase declines, population growth will become increasingly reliant on net in-migration. Even so, Crook County’s total population is expected to increase by more than 2,700 over the next 20 years (2015-2035) and by more than 4,500 over the entire 50-year forecast period (2015-2065). The Prineville UGB is forecast to show slightly stronger population growth—relative to the 2000s— in the initial 20-year forecast period, but is expected to slow down substantially during the last 30 years. The area outside the UGB will likely grow at a steadier rate than Prineville throughout the forecast period. Close

• 59. [Article] Coordinated Population Forecast for Deschutes County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065

  Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Deschutes ...

  Citation × Citation Citation Abstract Copy Title: Coordinated Population Forecast for Deschutes County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065 Author: Portland State University. Population Research Center, Ruan, Xiaomin, Proehl, Risa, Jurjevich, Jason R., Rancik, Kevin, Kessi, Janai, Gorecki, Carson, Tetrick, David Year: 2015 Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Deschutes County’s total population has grown rapidly since 2000, with an average annual growth rate of more than three percent between 2000 and 2010 (Figure 1); in addition, most of its sub-areas experienced even more rapid population growth during the 2000s. Sisters and La Pine posted the highest average annual growth rates at 7.8 and 6.3 percent, respectively, during the 2000 to 2010 period. Deschutes County’s positive population growth in the 2000s was the direct result of substantial net inmigration and steady natural increase (i.e., more births than deaths). Meanwhile an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years. This along with more women choosing to have fewer children and have them at older ages has led to slower growth in births. The more rapid growth in deaths relative to that of births caused natural increase—the difference between births and deaths—to shrink between 2007 and 2014. While net in-migration and steady natural increase contributed to population growth during the early and middle years of the last decade, it is clear that in more recent years (i.e., 2010 to 2014) net inmigration played the most prominent role in population growth. Total population in Deschutes County as a whole as well as within its sub-areas is forecast to grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035), relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to lead to natural decrease (more deaths than births). As natural decrease occurs, population growth will become increasingly reliant on net in-migration. Even so, Deschutes County’s total population is forecast to increase by more than 78,000 over the next 20 years (2015-2035) and by more than 186,000 over the entire 50 year forecast period (2015-2065). Sub-areas that showed strong population growth in the 2000s are expected to experience similar rates of population growth during the forecast period. Title: Coordinated Population Forecast for Deschutes County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065 Author: Portland State University. Population Research Center, Ruan, Xiaomin, Proehl, Risa, Jurjevich, Jason R., Rancik, Kevin, Kessi, Janai, Gorecki, Carson, Tetrick, David Year: 2015 Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Deschutes County’s total population has grown rapidly since 2000, with an average annual growth rate of more than three percent between 2000 and 2010 (Figure 1); in addition, most of its sub-areas experienced even more rapid population growth during the 2000s. Sisters and La Pine posted the highest average annual growth rates at 7.8 and 6.3 percent, respectively, during the 2000 to 2010 period. Deschutes County’s positive population growth in the 2000s was the direct result of substantial net inmigration and steady natural increase (i.e., more births than deaths). Meanwhile an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years. This along with more women choosing to have fewer children and have them at older ages has led to slower growth in births. The more rapid growth in deaths relative to that of births caused natural increase—the difference between births and deaths—to shrink between 2007 and 2014. While net in-migration and steady natural increase contributed to population growth during the early and middle years of the last decade, it is clear that in more recent years (i.e., 2010 to 2014) net inmigration played the most prominent role in population growth. Total population in Deschutes County as a whole as well as within its sub-areas is forecast to grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035), relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to lead to natural decrease (more deaths than births). As natural decrease occurs, population growth will become increasingly reliant on net in-migration. Even so, Deschutes County’s total population is forecast to increase by more than 78,000 over the next 20 years (2015-2035) and by more than 186,000 over the entire 50 year forecast period (2015-2065). Sub-areas that showed strong population growth in the 2000s are expected to experience similar rates of population growth during the forecast period. Close

• 60. [Article] Coordinated Population Forecast for Jefferson County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065

  Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Jefferson ...

  Citation × Citation Citation Abstract Copy Title: Coordinated Population Forecast for Jefferson County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065 Author: Portland State University. Population Research Center, Ruan, Xiaomin, Proehl, Risa, Jurjevich, Jason R., Rancik, Kevin, Kessi, Janai, Gorecki, Carson, Tetrick, David Year: 2015 Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Jefferson County’s total population has grown steadily since 2000, with average annual growth rates of a little more than one percent between 2000 and 2010 (Figure 1); however some of its sub-areas experienced more rapid population growth during the 2000s. Culver posted the highest average annual growth rate 5.4 percent during the 2000 to 2010 period. Jefferson County’s positive population growth in the 2000s was the result of steady natural increase— the difference between births and deaths—and substantial net in-migration from 2006 to 2008. Meanwhile an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years and a consequent decline in births. The growing number of deaths and shrinking number of births led to declining natural increase. While net inmigration and steady natural increase contributed to population growth during the early and middle years of the last decade, both of these numbers shrank during more recent years—slowing population growth from 2010 to 2013. Total population in Jefferson County as a whole as well as within its sub-areas will likely grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035) relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to lead to declining natural increase (births minus deaths). As natural increase declines population growth will become increasingly reliant on net in-migration. Even so, Jefferson County’s total population is forecast to increase by more than 5,100 over the next 20 years (2015-2035) and by nearly 11,000 over the entire 50-year forecast period (2015-2065). The Madras UGB will likely show slightly stronger population growth—relative to the 2000s—in the initial 20 year forecast period, but population growth is expected to slow during the last 30 years. Population within the Culver UGB is expected to grow at a much slower rate—relative to the 2000s—in the initial 20-year forecast period. Population growth in Culver is also expected to taper throughout the last 30 years of the forecast period. The area outside UGBs is forecast to grow at a steadier, although lower rate than the UGBs throughout the forecast period. Title: Coordinated Population Forecast for Jefferson County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065 Author: Portland State University. Population Research Center, Ruan, Xiaomin, Proehl, Risa, Jurjevich, Jason R., Rancik, Kevin, Kessi, Janai, Gorecki, Carson, Tetrick, David Year: 2015 Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Jefferson County’s total population has grown steadily since 2000, with average annual growth rates of a little more than one percent between 2000 and 2010 (Figure 1); however some of its sub-areas experienced more rapid population growth during the 2000s. Culver posted the highest average annual growth rate 5.4 percent during the 2000 to 2010 period. Jefferson County’s positive population growth in the 2000s was the result of steady natural increase— the difference between births and deaths—and substantial net in-migration from 2006 to 2008. Meanwhile an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years and a consequent decline in births. The growing number of deaths and shrinking number of births led to declining natural increase. While net inmigration and steady natural increase contributed to population growth during the early and middle years of the last decade, both of these numbers shrank during more recent years—slowing population growth from 2010 to 2013. Total population in Jefferson County as a whole as well as within its sub-areas will likely grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035) relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to lead to declining natural increase (births minus deaths). As natural increase declines population growth will become increasingly reliant on net in-migration. Even so, Jefferson County’s total population is forecast to increase by more than 5,100 over the next 20 years (2015-2035) and by nearly 11,000 over the entire 50-year forecast period (2015-2065). The Madras UGB will likely show slightly stronger population growth—relative to the 2000s—in the initial 20 year forecast period, but population growth is expected to slow during the last 30 years. Population within the Culver UGB is expected to grow at a much slower rate—relative to the 2000s—in the initial 20-year forecast period. Population growth in Culver is also expected to taper throughout the last 30 years of the forecast period. The area outside UGBs is forecast to grow at a steadier, although lower rate than the UGBs throughout the forecast period. Close