Understanding How the Share of Business Activity by Size Varies Widely by Industry

Written by: Andrew W. Hait

We’ve all heard about the importance of small businesses to the U.S. economy, but have you ever wondered what “small” means? Is it a business with a few employees, or is it based on sales? Is it based on an entire company, or each of its separate locations?

The Small Business Administration (SBA) defines a small business as a “business concern with less than 500 employees or less than $7.5 million in annual receipts.” While this SBA standard is essential for specific purposes, it is not necessarily the only way to define “small.”

Fortunately, the Census Bureau publishes detailed statistics that allow us to classify business size in a variety of ways and for a variety of purposes. For example,  the Economic Census, County Business Patterns, and the statistics of US Businesses  produce data on establishment and firm size with respect to employment and sales for detailed industries and at the National, State, and local  area levels.  These data sources provide detailed breakouts that allow users to build their own totals using their own size definitions.

Looking at the data from the Retail Trade Establishment and Firm Size report from the 2012 Economic Census, we see that gas stations with convenience stores (NAICS 447110) with seven to 14 employees make up only 36.2 percent of the businesses (35,222 out of 97,394 businesses) but nearly half (47.8 percent or $204.2 billion out of $427.1 billion) of the sales of this industry. Conversely, businesses with less than five employees make up 28.9 percent (or 27,182 businesses) of the total businesses but only 13.5 percent of the sales (or $57.5 billion.)

Hait Fig 1

Comparing this breakout with the data for the manufacturing sector (NAICS 31-33), we see a dramatically different picture. While 44.0 percent of all manufacturing businesses have less than five employees (130,715 out of 297,191 businesses), these businesses account for only 1.1 percent ($61.4 billion out of $5.7 trillion) of total shipments. On the other hand, 56.3 percent of all manufacturing shipments ($3.2 trillion out of $5.7 trillion) are from locations with 100 to 999 employees, though these locations make up only 7.8 percent (23,291 out of 297,191) of the total number of manufacturing businesses.

Hait Fig 2

While most Census Bureau data on businesses focus on companies with one or more paid employees (or “employers”), we also publish data on businesses with no paid employees, or “nonemployers.” These “small” independent contractors (and similar businesses) are the bulk (23 out of 30 million)_of all U.S. firms. Looking at the data from the 2013 Nonemployer Statistics report, we see that businesses with less than $25,000 in annual revenue make up 65.8 percent (or $15.1 million) of all nonemployers.

Hait Fig 3

These data can help users understand how the share of business activity by size varies widely by industry. Knowing this can help regional planners and economic development staff focus their limited resources on these key businesses and help small businesses grow. These data can also help business owners themselves better understand their own industry and compare their business to other businesses like them. Knowing this can help them with their business investment strategy by knowing what the “ideal” size of a business in their industry is and what to aspire to.

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Thousands of U.S. Veterans Call the Island Areas Home

Written by: Braedyn Kromer, Social, Economic and Housing Statistics Division

Forty years ago, the Covenant to Establish a Commonwealth of the Northern Mariana Islands was signed, establishing a political union between the Northern Mariana Islands and the United States. In preparation for the 2020 Island Area Census, and as a way of recognizing the contributions of the Commonwealth of the Northern Mariana Islands and all of our U.S. Island Area neighbors, the U.S. Census Bureau has put together some information about a population that many people might not be aware we collect data about — Island Area veterans who have served in the U.S. armed forces.

According to the 2010 Census, there were 14,047 veterans living in the four Island Areas (American Samoa, Guam, Northern Mariana Islands and the U.S. Virgin Islands) in 2010. They represented 5.6 percent of the civilian Island Area population age 18 and over. Guam reported the largest number of veterans at 8,041 (see Figure 1). At 7.9 percent, Guam also had the highest proportion of veterans in its civilian population 18 and over, compared with the other Island Areas. There are currently about 90,000 veterans living in Puerto Rico, but Puerto Rico is not part of the Island Areas census. Data on the population of Puerto Rico are collected annually in the Puerto Rico Community Survey, which is part of the American Community Survey program.

Figure 1.
Total Veterans 18 Years and Over, by Island Area: 2010

Total Veterans 18 Years and Over, by Island Area 2010
Source: U.S. Census Bureau, 2010 Island Area Census

While the majority of U.S. veterans are men, the Department of Veterans Affairs has stated that women are the fastest-growing subpopulation within the veteran community. At 11.3 percent, the proportion of women veterans in the total Island Areas was higher than the proportion stateside, which was 7.2 percent in 2010, according to the 2010 American Community Survey. The U.S. Virgin Islands reported the highest proportion of women veterans at 12.7 percent (see Figure 2).

Figure 2.
Proportion of Women Veterans, by Island Area: 2010
(in percent)

Proportion of Women Veterans, by Island Area: 2010

Source: U.S. Census Bureau, 2010 Island Area Census

The veteran population tends to be older because of the large Vietnam Era, Korean War and World War II cohorts. The majority (66.4 percent) of veterans in the states were over the age of 55 in 2010. Island Area veterans were younger, with more than half under age 55. Roughly 6 percent of Island Area veterans served in the Korean War and World War II, while almost 40 percent served during the Gulf War Era (see Figure 3).

Figure 3. Distribution of Period of Service for the Total Island Areas: 2010
(in percent)

Distribution of Period of Service for the Total Island Areas: 2010 (in percent)

Source: U.S. Census Bureau, 2010 Island Area Census
Note: Veterans are categorized in their most recent period of service. For example, a veteran who served in both Gulf War I and Gulf War II would be categorized as Gulf War II.

Service members are a mobile population, many moving several times during their time in the military. Once they leave service, veterans may not always move back to their place of birth. About half of all Island Area veterans were born in their island area of residence. However, this varies by island area. For example, 73.5 percent of veterans living in American Samoa in 2010 were born in American Samoa, whereas only 43.7 percent of U.S. Virgin Island veterans were originally from the U.S. Virgin Islands. In 2010, 4,206 veterans living in the four Island Areas were born in the states, while 17,200 stateside veterans were originally from the four Island Areas.

The Department of Veterans Affairs (VA) also serves veterans living in the Island Areas. The Island Areas are currently home to eight VA facilities, including cemeteries, veteran centers and medical facilities. Veterans who incurred a disability while serving are of particular concern to the VA. In 2010, roughly 19 percent of veterans living in the four Island Areas had a service-connected disability rating. This proportion was higher than stateside veterans, where approximately 16 percent had a service-connected disability rating.

For additional data on the four Island Areas, please visit the 2010 Census Island Area home page.

For additional data on Island Area and stateside veterans, please visit American FactFinder and view the following datasets: 2010 U.S. Virgin Islands SF, 2010 Guam SF, 2010 Commonwealth of the Northern Mariana Islands SF and 2010 American Samoa SF.

For more information on veterans, please visit our veteran topic page and the American Community Survey page.

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Shift Toward Greater Educational Attainment for Women Began 20 Years Ago

Written by: Kurt Bauman, Chief, Education and Social Stratification Branch

Statistics from the American Community Survey show women now lead men in college completion (see Women Now at the Head of the Class, Lead Men in College Attainment). Colleges have been graduating more women than men for more than 20 years, but what is new is that the advantage is no longer limited to new graduates and young women. Counting the entire population 25 and older, even women and men who are retired, women are ahead of men in college graduation. That is to say, the average adult woman in the U.S. is more likely to be a college graduate than the average adult man.

In order to better understand this change, the report “Educational Attainment in the United States: 2015” assembles statistics on historical trends in men’s and women’s college graduation. The Current Population Survey has collected data on Americans’ educational attainment since 1967 and provides an unparalleled data set for looking at the education level of the population over a broad period of time.

To look more closely at what is happening to education levels of women and men, it helps to look at trends among younger people. Women age 25 to 29 have had higher college attainment rates than men of the same age since 1996. This higher rate is not limited to women in the United States. Nearly all the countries with advanced economies that form the Organisation for Economic Co-operation and Development report that young women are ahead of young men in college completion.

Figure 1 shows the percentage of men and women in the U.S. population age 25 to 29 who had completed a bachelor’s or higher degree. Before 1986, men had higher college completion; from 1996 forward, women were in the lead. Across the period, women had a fairly steady increase in college attainment, while men’s attainment has been more subject to ups and downs.


Looking at the broader 25- to 34-year-old group (because sample sizes by race, gender and age group become too small for precise estimates), the increase in college completion of women relative to men is seen in all major race and Hispanic-origin groups (Figure 2).


The figure shows the college attainment of women relative to men of this age range for each race and Hispanic-origin group — a rise in the curve showing an increase in women’s attainment compared with men. In the early part of the period shown here, from 1976 to 1989, a smaller portion of young non-Hispanic white women than young non-Hispanic white men had bachelor’s degrees. By contrast, in this period young black women were not statistically different from young black men. Other sources show that by some measures they were actually ahead. Young Hispanic women were somewhere in between, sometimes ahead of their male counterparts, sometimes not. Data on Asian women and men are not available for this period.

In 1990, young Asian women were less likely to have completed a bachelor’s than young Asian men, and the gap was larger than for blacks, non-Hispanic whites and Hispanics. After that point, a transition took place. By 2010, young women of all these race and Hispanic-origin groups were more likely to have completed college than their young male counterparts (all comparisons 2010 to 2015 are statistically significant except for Asians in 2012 and 2014).

Research on this topic has not given us a clear answer as to why women have overtaken men in college attainment. Traditionally, researchers have looked at levels of education as being driven by the resources available, especially from families, and by the rewards of education, particularly earnings and occupational standing. Most research has concluded that the rewards of education for men and women have not shifted over time in a way that explains women’s higher attainment. An exception is work by Bachman and DiPrete holding that women benefit from education as “insurance against poverty” in a time of increasing family instability. Even if rewards haven’t shifted, women’s gains might have resulted from changes in resources for education (family encouragement and educational practices) that once may have favored men. Increasing age at marriage may have also played a role. Reviews on this subject are available from Aliprantis et al (2011) and Buchman and DiPrete (2008).

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Labor Force Participation Rates for An Aging World – 2015

Written by: Daniel Goodkind

Today the U.S. Census Bureau released An Aging World-2015, a report that examines the older population’s demographic, health and economic characteristics in the United States and around the world. The Census Bureau regularly tracks trends in international aging and examines their significance. In the coming decades, almost all countries will see an increase in their older population because of expected improvements in health and falling fertility.

Among the key findings highlighted in the report are the proportions of the older population in the labor force (e.g., those who are either employed or seeking employment). The labor force participation rate varies widely across age groups, countries and sex. For instance, at least 90 percent of men in their late 40s are in the labor force in most countries of the world. However, rates generally decline for each successively older age group.

By age 60 to 64, labor force participation rates among men and women were less than half the level for those age 45 to 49 in countries such as South Africa, Tunisia, Italy, Russia and Ukraine (Table 1). Another sizable decline is typically observed for age 65 and over. This is not unexpected, given that individuals may stop working because of increasing frailty, health issues or retirement options. Among women, labor force participation tends to be lower than men across the age groups. The lower proportions of women in the labor force reflect, in part, the fact that women perform unpaid work within a household, which clearly has value and would be expensive to replace but is not included in the formal definition.

There are also notable differences in labor force participation across countries. In general, countries with higher incomes per capita and more developed social security systems tend to have lower labor force participation among the older population. In contrast, in lower income countries, the notion of retirement may not make sense — the older population may need to continue to work, perhaps at a reduced level, until physically or mentally unable to do so.

In Table 1, we see that labor force participation remains above 50 percent for men age 65 and over in Zambia and Guatemala. The World Bank published labor force participation rates for the older population in 25 African countries for 2011 with rates exceeding 50 percent in 12 of the countries.

aging world table 1


At the other extreme are Germany and Italy with participation rates below 10 percent for those age 65 and over. The low labor force participation among Europe’s older population likely stems from its substantial economic resources, policies that encourage early retirement and patterns of public spending that provide security for the older population.

Labor force participation rates in the United States, on the other hand, lie well between the extremes of Africa and Europe. Labor force participation rates for U.S. males in 2012 were

88 percent at age 45 to 49, 60 percent at age 60 to 64, and 24 percent at age 65 and above, while U.S. female rates at these age groups were about 10 percentage points lower (76 percent, 50 percent and 14 percent, respectively).

Just as important are changes in labor force participation over time. Between 2001 and 2011, developed countries experienced an increase in labor force participation among the older population. In the United States, for instance, rates at ages 55 to 64 rose from 62 percent to

64 percent, while rates at ages 65 to 69 rose from 26 percent to 32 percent. Other countries with large increases in participation rates over the 2001 to 2011 period include Finland, Germany and the Netherlands.

In the less developed world, the picture was more mixed. There was no clear trend in labor force participation among males, among whom such participation was quite high — typically averaging almost 50 percent at ages 65 and over.

In contrast, labor force participation of older females in developing countries, among which labor force participation is typically under 10 percent, did evince a notable increase from those very low levels.

One of the key megatrends over the past dozen years has been an increase in labor force participation among older women around the world, but the gap between the labor force participation of older men and older women remains. Among the countries shown in Table 2, the gender gap in 2012 ranged from a low of 1.5 percentage points in France to a high of 51.4 percentage points in Guatemala.


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Growth or Decline: Understanding How Populations Change

Written By: Luke T Rogers and C Peter Borsella

With the release of the 2015 county and metro/micro area population estimates and components of change, we can explore the question – how did the United States population change in the last year? Demographers, researchers who study population change, begin to answer this question by looking at the components of change.  There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change.  Populations grow or shrink depending on if they gain people faster than they lose them.  Looking at an area’s unique combination of natural change and migration helps us understand why its population is changing, and how quickly the change is occurring.

Natural Increase

Natural change is the difference between births and deaths in a population. Often times, natural change is positive, which means that more babies are being born than people are dying. This positive natural change is referred to as natural increase. Examples of natural increase exist across the United States, one being the Salt Lake City metro area in Utah. Between 2014 and 2015, Salt Lake City had around 19,100 births and 6,400 deaths. Since there were about 12,700 more births than deaths, Salt Lake City had a natural increase of about 12,700 people, making natural increase a key reason why its population grew over the year.

The opposite of natural increase is called natural decrease, where more people are dying than babies being born, which can cause a population to shrink. Areas with aging populations often have natural decrease. Two states had natural decrease between 2014 and 2015, Maine and West Virginia. Between 2014 and 2015, Maine had 450 more deaths than births and West Virginia had 940 more deaths than births. In both cases, natural decrease was one of the reasons why their populations shrank between 2014 and 2015 in our latest estimates.


Migration is the movement of people from one area to another. It is often expressed as net migration, which is the difference between how many people move into and out of an area. When net migration is positive, a population has more people moving in than out. We split migration into domestic migration and international migration.

Domestic migration refers to people moving between areas within the United States, and is often one of the largest contributors to population change. Regionally, the South gains the most net domestic migrants, with roughly 440,000 more people moving into southern states than leaving them between 2014 and 2015. Sometimes net domestic migration is negative, in which case more people are moving away than are moving in. The Chicago metro area in Illinois, Indiana, and Wisconsin lost about 80,000 people through migration between 2014 and 2015, which is consistent with a long-standing pattern of negative net domestic migration for the metro area.

International migration refers to people moving into and out of the United States, and consists of a diverse group of people such as foreign-born immigrants from many countries around the world, members of the U.S. Armed Forces, and U.S. citizens working abroad. Some areas, like the Miami metro area in Florida, grow (in part) due to net international migration. Miami gained about 70,000 net international migrants between 2014 and 2015, making net international migration a major factor in Miami’s population growth.

The Big Picture

Analyzing the components of change is an enlightening way to understand how the U.S. population is shifting over time. Looking at counties across the country, we can identify clusters of counties that grow mainly due to migration and others that grow due to natural increase. Clusters seen in areas like Florida and Texas, which grew primarily due to net migration gain between 2014 and 2015, are visible in Map 1. Other clusters shown in Map 1, such as those in California, Utah, and along the east coast from Virginia up to New York, grew over the same span of time in large part due to natural increase.

Map 1

Counties with shrinking populations are also clustered geographically. For many of these shrinking counties, net migration is the primary cause of population loss. How these counties can cluster together is shown in Map 2, where several areas along the Mississippi River (Arkansas, Louisiana, and Mississippi) had net migration loss between 2014 and 2015. States like Illinois, Kansas, New Mexico, and New York also had several counties that lost population due to net migration loss. Areas that declined mainly due to natural decrease are similarly clustered, as seen along the Virginia/North Carolina border and in northern Michigan.

Pop est 2

Natural change and net migration both contribute to population change, sometimes with unexpected results. Frequently, natural change and net migration push a population in opposite directions, making it more difficult to determine whether a population is growing or shrinking. Los Angeles County, California—the largest county in the United States—experienced both natural increase and net migration loss between 2014 and 2015. As noted earlier, natural increase contributes to population growth, while net migration loss can cause a population to shrink. This can beg the question, how might a population change when subjected to seemingly contradictory components? The answer is that it depends. In the case of Los Angeles, the growth due to natural increase was much larger than the loss due to net migration, and the county saw a sizeable population increase. All across the United States, stories like the one playing out in Los Angeles exist, with each area having a unique combination of natural change and net migration that determines whether they grow or shrink from year to year. By looking at these basic components of population change, demographers gain insight into the complexities of how populations change over time.

“Summing” It All Up

Overall, population grows or shrinks through two very basic components – natural change (births minus deaths) and migration (domestic plus international). As illustrated in this blog, the balance between these components is unique in each area, while following general patterns across states or regions. This balance gives areas their own unique story as they change over time. Through the production of annual population estimates, and the types of analysis provided here, demography continues to be an important, ongoing focus of study at the Census Bureau that contributes to our understanding of where we’ve been and where we’re headed in the future.


The Office of Management and Budget’s statistical area delineations for metro areas are those issued by that agency in February 2013. Metro areas contain at least one urbanized area of 50,000 or more population, and consist of one or more whole counties or county equivalents. Some metro area titles are abbreviated in the text of the blog.

The Census Bureau develops annual population estimates by measuring population change since the most recent census. The Census Bureau uses births, deaths, administrative records and survey data to develop estimates of the U.S. population. For more details regarding the methodology, see https://www.census.gov/popest/methodology/

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