2015 USDA County Typologies: Herkimer County

An area's economic and social characteristics have significant effects on its development and need for various types of public programs. To provide policy-relevant information about diverse county conditions to policymakers, public officials, and researchers, the USDA Economic Research Service has developed a set of county-level typology codes that captures a range ofeconomic and social characteristics.

The 2015 County Typology Codes classify all U.S. counties according to six mutually exclusive categories of economic dependence and six overlapping categories of policy-relevant themes. The economic dependence types include farming, mining, manufacturing, Federal/State government, recreation, and nonspecialized counties. The policy-relevant types include low education, low employment, persistent poverty, persistent child poverty, population loss, and retirement destination.

What’s interesting about the typography is as much what it DOESN’T show as what it does when it comes to Herkimer County. The six economic dependence categories are defined as follows:

• Farming County: Farming accounted for at 25% or more of the county's earnings or 16% or more of the employment averaged over 2010-2012.
• Mining County: Mining accounted for 13% or more of the county's earnings or 8% of the employment averaged over 2010-12.
• Manufacturing County: Manufacturing accounted for 23% or more of the county's earnings or 16% of the employment averaged over 2010-12.
• Federal/State Government County: Federal and State government accounted for 14% or more of the county's earnings or 9% or more of the employment averaged over 2010-2012.
• Recreation County: Recreation designations were based on three measures.
• Percentage of wage and salary employment in entertainment and recreation, accommodations, eating and drinking places, and real estate as a percentage of all employment reported by the Bureau of Economic Analysis;
• Percentage of total personal income reported for these same categories by the Bureau of Economic Analysis; and
• Percentage of vacant housing units intended for seasonal or occasional use reported in the 2010 Census
• Nonspecialized County: The county was not a farming, mining, manufacturing, government-dependent, or recreation county.

Given those definitions, Herkimer County was tagged by the USDA as a “Recreation County”.

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When it came to the policy-relevant typography of low education, low employment, persistent poverty, persistent child poverty, population loss, and retirement destination, none of these social characteristics met the minimum thresholds for the USDA when examining Herkimer County. That does NOT mean that these issues don’t exist or have serious consequences deserving of being addressed.

Methodologically, low-education (2008-12), low-employment (2008-12), persistent poverty (1980, 1990, 2000, 2007-11), persistent child poverty (1980, 1990, 2000, 2007-11), population loss (1990, 2000, and 2010), and retirement destination (2000 and 2010) classifications were all based on census data from the years in parentheses after their names. They were defined as follows.

• Low Education: At least 20% or more of the residents age 25 to 64 did not have a high school diploma or equivalent between 2008-12.
• Low Employment: Less than 65% of residents age 25-64 were employed in 2008-12
• Persistent Poverty: A county was classified as persistent poverty if 20 percent or more of its residents were poor as measured by the 1980, 1990, and 2000 decennial censuses and the American Community Survey 5-year estimates for 2007-11.
• Persistent Child Poverty: A county was classified as persistent related child poverty if 20 percent or more of related children under 18 years old were poor as measured by the 1980, 1990, and 2000 decennial censuses and the American Community Survey 5-year estimates for 2007-11. See the Census Bureau website
• Population Loss: Number of residents declined between the 1990 and 2000 censuses and also between the 2000 and 2010 censuses.
• Retirement Destination: Number of resident 60 and older grew by 15 percent or more between 2000 and 2010.

In none of these cases did the data meet the thresholds set up by the USDA, hence Herkimer County was not tagged as having a predominance of these characteristics.

FORE ! Puttering Around with Economic Census Data

A recent article in the Herkimer Telegram noted all of the golf courses located in that county.

Below is data from the economic census that shows the number of golf establishments, their sales, employees, and payroll in both Herkimer and Oneida Counties combined from the Economic Census.

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Comparing ACS Data: Economic Changes Over the Last Five Years in Oneida County

An earlier examination of the social changes in Oneida County suggested by the single year estimates of the American Communities Survey (ACS) data between 2008 and 2012, came with a considered warning about placing the data and trends found there within context. It is important to exercise due caution when looking at significant changes in the ACS over time such that the trends that seem to be present make some sense in the larger picture. This is just as true about the economic profiles found in the ACS as it was with the social profiles.

Income Measures: That being said, let's begin with what the data does NOT show us - or more accurately, what it shows us has not changed in the last five years. Specifically, that the income levels of the region have remained relatively stable over that time frame. Income can be measured several ways. Typically we measure income based on the family median income, the household median income or the per capita income of the county. Here's a look back at these measures in the 2011 Five Year ACS for every municipality in the region.

The graph below shows the single year ACS income data from 2008 to 2012. Based on the margins of error for each income measure, the reality is that income levels haven't changed significantly since 2008 for families, households or on a per capita basis.For families it remains around $60,000; for households it is about $47,000; and on a per capita basis it is around $25,000. The fluctuations seen across the last five years are not statistically significant.

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Poverty: At the same time as income has remained relative stable, however, we have seen a significant increase in the percentage of the population that has fallen into poverty.Looking at the population as a whole, the percent of the County's residents who live in poverty has climbed from around 14% in 2008 to about 16.4% in 2012. Similarly, there has been an increase in the percentage of families in poverty over this period - from 10% in 2008 to 12.5% of families in 2012.

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Health Insurance Coverage: The last piece of economic data noted here that has changed significantly since 2008 is the number of people covered by health insurance.  Health insurance is measured in two broad sectors - specifically as being provided by the private sector or as being provided by the public sector.

These two types of coverage are not mutually exclusive, but may be. In other words, you could have someone who receives private insurance, and also has some public/government insurance coverage as well. Keep that in mind as you look at the graphic below, in that the data is not intended to add up to 100% - the coverage by either a private vender or public resource is totally independent of one another.

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Statistically speaking we have seen a decrease in the percentage of the population with private insurance coverage in the last five years. It has fallen from around 72% of the population in 2008 to about 67% of the current population. In terms of public insurance coverage, we have seen an increase in the percentage of the county's population using public insurance options from about 35% in 2008 to roughly 39% as of 2012.

While other comparative data may show statistically significant changes between 2008 and 2012, these few items are the ones that seem to suggest decipherable trends worth noting.