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Summary:

  • By and large, the project area is under performing in both the creation of jobs and the employment rate of its citizens.

  • Though minority racial and ethnic groups make up a small portion of the project area’s population, their proportion of poverty is exponentially higher.




  • Example of Bootstrap 3 Accordion

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    Photo: Ship loading up with wood chips.
    Credit: International Port of Coos Bay

    A report of the current economic climate as it relates to the socioeconomic background of an area is necessary for understanding any community. The Coos County region has an economic history much like the rest of the
    Western United States in that it was largely founded on natural resource extraction (see Background below). Like many economies based on natural resource extraction, the project area has seen its share of boom/bust
    cycles, which in turn has affected the local job market.

    While “Chapter 4: Community Demographics” describes how the population of Coos County peaked in the 1980s, with the 1980 decennial census showing a population of over 64,000, this chapter describes the transformation of
    Coos County’s regional economy from 1980 to current day.

    In this chapter, we use Decennial Census and American Community Surveys data at the state level, aggregated county level, and where appropriate city level to summarize the socioeconomic history of the region. Our
    analysis focuses on the period between 1980 and present day, presenting snapshots of the economic climate in 1980, 2000, and 2015 (economic date for North Bend is not available from the 1980 Decennial Census).

    This chapter analyzes the historical and current economic climate of the project area in two sections: Jobs and Wages.

    Jobs outlines the overall historical profile of employment in the project area. It provides comparisons of employment data over time and across industries.

    Wages expounds upon the jobs section by describing the change of wage structures over time, looking at trends in comparison to state,
    regional and national averages. In addition, it compares wages across demographic divisions, including racial and gender makeup.

    These sections are followed by a general Background section that provides more historical context and describes ways the community is attempting to address the current economic performance.

    A measure and description of the jobs available
    in a community are key pieces of understanding the economic health of a region. The quantity, availability, variety, and quality of jobs in a community are a measurement of economic stability, sustainability, and resilience. This section provides an overview of the economic environment of Coos County, Coos Bay, and North Bend in comparison to the State of Oregon.

    This section describes the overall historical profile of employment in the project area, with a short history of the region’s basis in logging, agriculture, and sea and the transformation over time. This is followed by comparisons of census data on employment over time, from the region’s peak in the 1980s to current day: what the largest industries are, employment trends (industry mix, size of employers, and common occupations), and an analysis of the region’s competitiveness in comparison to the state (a shift/share analysis).

    History

    At its integration as a county in 1853, the economy of the Coos County region was largely based in resource extraction industries like trapping, fishing, agriculture, mining, and lumber. Much like many rural areas in the
    western United States, this industrial profile stayed largely the same until the post-World War II era and the recession and subsequent lumber crash in the 1980s. The Lumber industry had long been a large part of Oregon’s economy, providing 12% of the State’s GDP in 1963 (eventually falling to less than 1% by 2009).

    After World War II many rural communities experienced an influx in population of returning veterans and other citizens who had been trained in trades specific to the war efforts. This influx (in combination with the
    lumber crash of the 1980s, and the expansion of environmental protections instituted by the National Environmental Protection Act, the Endangered Species Act, and others of the like), led to the diversification or failure
    of rural economies. Rural areas either moved away from the focus on extractive natural resource industries or saw their populations move away to areas that had. Coos County, if judged solely through statistical measurements, survived the economic transformation better than many other counties.

    Employment Status

    To begin the description of the transformation of the project area’s economy over time, we begin with a description of the overall pool of available jobs and the unemployment rate described in the decennial census and American Community Survey.

    Figure 1 shows the total number of employed citizens in the project area. The data shows that, even though the population of Coos County peaked in the 1980s, the total number of employed citizens age 16 and up peaked in the 2000s. This small difference between data points is likely due to fluctuations in the health of the national economy, with the 1980s data and 2015 data reflecting periods of economic downturn.

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    Figure 1: Total employed working-age citizens in the project area by location. Data Source: US Census Decennial 1980, 2000; US 2015 American
    Community Survey.

    The general health of the national economy in specific time periods is reflected in Figure 2, which shows the total number of unemployed citizens in the project area. As seen in the data, the 1980s and post-recession periods had the highest number of unemployed citizens.

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    Figure 2: Total unemployed working-age citizens in the project area by location. Data Source: US Census Decennial 1980, 2000; US 2015 American Community Survey.

    When looking at this data as unemployment rate and comparing it to the state average(Figure 3), the data demonstrates that the project area’s consistently under-performs in comparison to the state as a whole.

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    Figure 3: Unemployment rates in the project area during 1980, 2000, and 2015. State of Oregon rates are shown for comparison. Data Source: US Census
    Decennial 1980, 2000; US 2015 American Community Survey.

    Employment Trends

    Employment trends in the project area can be described through an analysis of the leading industries (by percentage of the total employment pool), the largest employers in the area and the most common sizes of businesses, and the leading occupations. Data in this section is displayed at the county and city levels, with exception for “Percentage of Industry Total,” as data from the city level (Coos Bay and North Bend) does not differ significantly
    from that displayed.

    The total percentage of each industrial category of employment in the Coos County region from the 1980 decennial census to the 2015 American Community Survey can be seen in Table 1. This table clearly displays (in bold) the transformation of the Coos County economy from a natural resource extraction economy. “Manufacturing,” a category that includes most aspects of lumber production, is the single largest category of change shown with a loss of about 15%. The decrease in lumber manufacturing corresponds with an
    increased proportion of service and skilled jobs, such as “Education Services,” and “Arts, Entertainment and Recreation.”

    The size and number of businesses in Coos County, Coos Bay, and North Bend by number of employees in the year 2015 is shown in Table 2. The data shows that nearly all of the businesses in the project area are small businesses
    with fewer than 50 employees. Less than 3% of the businesses in Coos County
    have more than 50 employees.

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    Table 1: Percentage of Industry Total for Coos County. Values in bold are discussed in the text. Data Source: US Census Decennial 1980, 2000; US 2015 American Community Survey.

    We can understand what types of occupations are the most common in Coos County, Coos Bay, and North Bend by looking at Table 3. “Professional and Related”, “Office and Administrative Support Occupations” and “Management, Business, and Financial Operations” represent the largest percentages of the overall pool of employees in all three geographic areas. These categories include jobs such as: Management positions, Architects, Computer Programmers, Business Operations, Legal Occupations, etc. “Protective Service,” and “Farming, Fishing, and Forestry” show the smallest percentages of the overall pool. These categories include jobs such as:
    Firefighters, Police Officers, Animal Breeders, and Logging Workers.

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    Table 2: Size and number of businesses in Coos County, Coos Bay and North Bend in 2015. Data Source: US 2015 American Community Survey.

    Figure 4 breaks this down further by providing an overview of wages for the job types shown in Table 3. The data shows that two of the largest categories of jobs in the project area, “Professional and Related” and “Management, Business, and Financial Operations” include some of the highest paying jobs, such as “Architecture and Engineering,” and “Management.” However, though these categories make up about 27% of the overall pool of jobs in the project area, the other 73% of the pool include most of the lowest paying jobs available, such as “Food Preparation” and
    “Janitorial Services.” We provide more detail on wage breakdown in the next section of this chapter (see “Wages” below).

    The next step of a shift share analysis is a calculation of the state growth rate component. The state growth rate component is a measurement of the growth that a region would expect in a sector if it were based on total state employment growth. In the period between 1980 and 2015 the total number of jobs in Oregon increased by 57%. With an equivalent job growth rate, Coos County could have expected to add over 14,000 jobs in the 35-year period (this does not account for the lack of population growth in Coos County during the same period).

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    Table 3: Percentage of people employed within each occupation category for Coos County, Coos Bay and North Bend in 2015. Data Source: US 2015 American Community Survey.

    The next step in the analysis is the industrial mix component, which is a calculation of the amount of employment change that can be attributed to state trends in each sector. The industrial mix component represents the share of the project area’s industry growth that can be explained by the growth of each specific industry at the state level. This is calculated by subtracting the overall state growth rate from the state growth rate of each specific industry and applying that growth percentage to jobs in the project area. The majority of changes in employment in the project area can be attributed to statewide trends.

    The overall industrial mix share of -1,095 means that the project area has 1,095 less jobs than it would have if its structure were identical to the state’s. The negative industrial mix means that the project area’s economy is growing slower than the state average.

    The final step in a shift-share analysis is to determine the competitive share component (Table 5). The regional competitiveness effect explains how much change in a given industry can be explained by some unique competitive
    advantage that the region possesses. The negative competitive share shown in Table 5 means that, in general, Coos County’s economic position is not attributable to any form of economic advantage in comparison to that of the state. Likewise, Coos County does not outperform the state in any job category.

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    Table 4: Percentage change for employment by occupation sector in Oregon and Coos County from 1980 to 2015. Industrial classification data from the US Census Bureau differs between years 1980 and 2015. 1980 classifications are based on the SIC (Standard Industrial Classification) system, and in 2000 the census bureau switched to NAICS (North American Industry Classification System). Industrial classifications differ between these two systems, but for the purposes of this analysis the differences can be considered null. Data Source: US Census Decennial 1980, 2000; US 2015 American Community Survey.

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    Table 5: Shift-share analysis for Coos County, Oregon. Industrial classification data from the US Census Bureau differs between years 1980 and 2015. 1980 classifications are based on the SIC (Standard Industrial Classification) system, and in 2000 the census bureau switched to NAICS (North American Industry Classification System). Industrial classifications differ between these two systems, but for the purposes of this analysis the differences can be considered null. Data Source: US Census Decennial 1980, 2000; US 2015 American Community Survey.

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    Figure 4: Median Annual Income by Occupation in the project area. Dollars are in 2015 values.
    Data Source: Bureau of Labor Statistics, 2016

    In the “Jobs” section above, we established the leading industries and regional competitiveness of the project area. On a whole, the project area is under-performing in the creation of jobs and the employment rate of its
    citizens. The purpose of this section on wages is to understand the quality of the available jobs in the project area both currently, and over time. We can look at measurements such as per capita and median income, wage distribution, cost of living, and income distribution to help us gain a more in depth understanding of the economic health of theproject area.

    This section outlines current measurements and trends from 1980 to 2015 of wages in the project area and includes overviews of:

    • Income and Wages by analyzing median household income, per capita income, the Gini coefficient, and mean household income; and

    • Demographics of Wages by analyzing poverty status and poverty rate and income by gender and race or ethnicity.

    Income and Wages

    The data shown in the “Jobs” section of this document demonstrates that the project area experienced a transformation over time that roughly mirrored the state economy. A review of median household income and per capita income over time also demonstrates the same pattern. Median household income is a representation of the halfway point of a region’s wage income. In other words, half of the study area’s population makes more than the median and half makes less. Like the previous section, we used a sample period of 1980, 2000, and 2015 as a snapshot of the project’s area’s recent change.

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    Figure 5: Median household income for Coos Bay, North Bend, and Coos County compared to the State of Oregon for 1980, 2000 and 2015. Dollars represent 2015 inflation values. Data Source: US Census Decennial 1980, 2000; US 2015 American Community Survey.

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    Figure 6: Per capita income for Coos Bay, North Bend, and Coos County compared to the State of Oregon for 1980, 2000 and 2015. Dollars represent 2015 inflation values. Data Source: US Census Decennial 1980, 2000; US 2015 American Community Survey.

    Figure 5 shows the change of median household income from 1980 to 2015 (data for North Bend is not available for the 1980 period). The graph shows that the project area’s median household income peaked in the 1980s. The continual lessening of the median income through the three time periods demonstrates that the quality of jobs available has lessened over time (if measured solely in wages). The available data for the North Bend area demonstrates a large difference in economic health to that of its neighbor Coos Bay, with a higher median income in both 2000 and 2015. However, when compared to state median incomes all geographical locations within the project area have lower earning wages.

    Per capita income is a representation of the wealth of a population in comparison to other populations but does not reflect income distribution. Per capita income is the average income of the entire population. In other
    words, it is the combined income of a study area divided by its population (age 15 and up). Figure 6 shows the per capita income for the project area from 1980 to 2015 (again, data for North Bend is not available for the 1980 period). In contrast to the downward trend in median income for the same time period, Figure 6 shows an upward trend of per capita income into the 2000s. It should be noted that this could be the effect of an increase in a small wealthy class rather than the majority of the population increasing
    its income. Overall, the data shows that the populations of Coos Bay and North Bend are equally “wealthy,” and mirror the overall wealth of the project area.

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    Figure 7: Distribution of mean household income in Coos County, Coos Bay, and North Bend as compared to the State of Oregon. Data Source: American Community Survey, 2015.

    Figures 5 and 6 demonstrate that the project area’s economy consistently under-performs as compared to that of the State of Oregon. In the “Jobs” section of this report we demonstrated through a shift-share analysis that the project area under-performs in job creation. This is mirrored in the region’s lower median household income and per capita income in each of the time periods shown. To further understand the disparity in economic health between the project area and the State of Oregon, we can look at the distribution of mean household income between these geographical areas (Figure 7). Forty-nine percent of Oregon’s households make less than $50,000 per year, with the largest single group of earners (13%) in the “$75,000 – $99,999” range. By contrast, in Coos County 63% of households make less than $50,000 per year, with the largest single group of earners (11%) in the “Less than $10,000” range.

    Coos Bay and North Bend similarly reflect the county distribution of income
    with 62% and 58% of households earning less than $50,000 per year, respectively. The highest single group of Coos Bay household incomes is in the less than $10,000 per year group (12% of households), while North Bend
    matches the state with its highest percentage of households in a single group earning between $75,000 and $99,000 per year (11% of households).

    The description of income in the project area that is portrayed in Figure 7 can also be described through a Gini coefficient. A Gini coefficient is a measurement that represents the wealth distribution of an area. This
    measurement is scaled from 0 – 1, with a score of 0 representing complete equality between earners, and a score of 1 representing complete income disparity. According to the American Community Survey (2015), the project area is in the middle with a Gini coefficient of 0.47. This is only slightly higher than that of the State of Oregon (0.46).

    Wage Demographics

    In conjunction with the project area’s wages and quality of jobs, it is important to understand the equality level of wages. In most cases,
    underrepresented groups and groups that are traditionally marginalized receive less for their work. Data from the American Community
    Survey and Bureau of Labor Statistics are used in this section to provide a description of the demographics of wages. This describes the economic health of the project area as it relates to underrepresented groups, beginning with a review of the poverty status of the project area in comparison to the State of Oregon.
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    Poverty status is determined from various statistics gathered through the census and is measured on a family to family basis. The computation is based on a “poverty threshold” for an individual or family (based on family size), where earnings in a calendar year are compared to the threshold (see sidebar). If an individual or family’s earnings are greater than the determined threshold, they are not considered to be in poverty. Figure 8
    shows the poverty rate of Oregon in comparison to the project area. The data shows Coos County with a higher rate of poverty (18% or over 11,000 people) than the State of Oregon, (16% or over 600,000 people). Coos Bay has a much higher rate of poverty at 23% (over 3,600 people) than North Bend (13% or over 1,200 people). This disparity reflects the difference in median and per capita income discussed in the previous section.

    “Chapter 4: Community Demographics” discusses the overall gender and racial make-up of the project area. The chapter shows that, in 2010, the ratio of male to female populations was nearly even, 85.5% of the population was white, with the remaining 14.5% being made up of various racial and ethnic
    groups (6% Hispanic or Latino, 5.9% Native American, 2.9% two or more races, 2.5% other, 2.1% Asian, 1% Black, and .6% Pacific Islander).

    Though minority racial and ethnic groups make up a smaller portion of the project area’s population, their proportion of poverty is exponentially higher. Figure 9 shows that in every category of racial or ethnic background, with the exceptions of “Two or More Races,” the rate of poverty exceeds that of the “White” population in the project area. In the case of the “Black or African American” population, the vast majority live below the poverty line.

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    Figure 8:Poverty status for Coos County, Coos Bay, and North Bend as compared to the State of Oregon in 2015. Data Source: US 2015 American Community Survey.

    This high rate of poverty for underrepresented groups is underscored in Figure 10, which portrays the per capita income by race. This figure shows that, in every case, underrepresented groups have a lower per capita income
    than both the state average, and those under the category of “White.” The per capita income for “Black or African American” respondents is less than 25% of the state average, and the per capita income for “Native Hawaiian”
    respondents is less than 50% of the state average.

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    Figure 9: Poverty status broken down by race/ethnicity for Coos County, Data Source: US 2015 American Community Survey.

    The underperforming rate of both Per Capita Income and Poverty by Race could be explained by the small populations of races other than “White” in the project area. Though this may be the case, it is important to acknowledge the fact that underrepresented groups experience hardship in the project area at a much higher rate, and to a much higher magnitude than the state average. When looking at how gender affects poverty levels, we can see that “Females” in both the State of Oregon and in the project area
    experience poverty at a higher rate than that of “Males” (Figure 11). In Coos County, 2.5% more females experience poverty than males, which equates to over 1,000 more females living in poverty than males. In Coos Bay 5% (or
    600) more females experience poverty than males while North Bend is fairly balanced between the genders.

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    Figure 10: Per capita income broken down by race for Coos County and the State of Oregon, Dollars are expressed in 2015 values.
    Data Source: US 2015 American Community Survey.

    Similar findings are seen when looking at median income by gender (Figure 12). “Male” vs. “Female” incomes in both Oregon and the project area are very uneven. In Coos County females make less than 64% of the median wage of males. In Coos Bay, the median wage for females is about 51% of the median male wage, and in North Bend the female median wage is about 65% of the male wage.

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    Figure 11: Poverty status broken down by gender for Coos County, Data Source: US 2015 American Community Survey.

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    Figure 12: Median income broken down by gender for Coos County, Dollars are expressed in 2015 values. Data Source: US 2015 American Community Survey.

    Before establishment as a county in 1853 and Oregon’s integration into the United States in 1859, the Coos County region’s economy was based in the traditional trade of natural resources: trapped animals, fish, timber and
    rough handmade goods. Over time, with the integration into the United States and the establishment of railroad systems for freight from the inner areas of the state, the region’s economy transitioned to intensive natural resource extraction (through mining, timber, and grazing), and an agriculture base.

    By 1947, Oregon had over 1,500 operating lumber mills, in addition to paper mills, planing mills, and furniture factories (OPB n.d.). The industry peaked in the 1960’s when more than 20% of the nation’s timber products was supplied from Oregon forests (ODF 2005). By the early 1980s, however, Oregon’s timber-based economy began to suffer from high national inflation and interest rates and the subsequent halt to home construction (WWPA 2001). When the 1980s crash happened, small town rural resource-based economies felt it the hardest, as high amounts of jobs were lost and the economy shifted to urban centers.

    The State of Oregon as a whole, has been deliberately diversifying its economy since that time, to include the high technology and services industries (Mapes 2012). As we saw above however, Coos County continues to lag behind the state. Economic forecasts predict that growth will continue to lag behind the urban areas of the state, suggesting the local need to invest in projects and activities that lead to economic diversification, job growth and improved community services (CCD Business Development Corporation 2013).

    Case in point, the 2013 CCD Business Development Corporation report describes how the local seafood and agricultural industries are experiencing a period of stress that are strikingly parallel to that experienced by the wood products industry thirty years ago. They add that the historically diverse independent network of seafood processing facilities throughout the northwest has been consolidated to just a few entities, which in turn has had a negative impact on traditionally low wage
    employment in the seafood processing industry.

    Local entities, such as the City of Coos Bay, are including strategies to address the limitations of the current local economy. The City of Coos Bay’s 2010 updated strategic plan lists areas where they see opportunities
    for economic growth, such as an increase in bulk container shipping traffic, an increase in tourism, and growth of the healthcare sector. Specifically, their targets are water-dependent industries (including wood product and commercial fishing), outdoor recreation businesses, solar and metal fabrication, and technology industries dependent on being near fiber optic lines.

    A variety of economic development efforts in the area has been created to provide incentives for expansion and retention of existing industry and recruitment of new industry. Probably the most notable of these is the Bay
    Area Enterprise Zone, which is located within and adjacent to the cities of Coos Bay and North Bend. According the to CCD Business Development Corporation, qualifying businesses benefit from “100 percent abatement
    from local property taxes for at least three, and in some cases up to five years on plant and equipment newly invested in the zone. Property tax exemptions of 7 to 15 years may be available to businesses making sizable
    investments and bringing well-paying jobs”.