Wednesday, April 30, 2014

CGR Report on the Future of County Nursing Homes in NYS

Virtually all nursing homes across New York State, whether operated by a county, for-profit company, or non-profit operator face wide ranging, significant challenges. For county-owned homes, however, the future is especially troubled.
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The Center for Governmental Research (CGR) of Rochester conducted a year-long, statewide study that focused on nursing homes owned by 33 counties, four homes sold by other counties since 2005, and two homes closed by counties in recent years.

CGR’s recommended guidelines for county officials and nursing home administrators include developing county long-term care plans and expanding community-based services; and strengthening working relationships between nursing home administrators, labor representatives and county officials to make county homes more financially viable.

For those counties that opt to sell their homes, the guidelines call for establishing clear county criteria and expectations for potential buyers to meet; and holding potential buyers accountable for meeting those expectations.

To view the entire report and their recommendations visit this link from CGR.

Tuesday, April 29, 2014

2010 Oneida County Retrospective: Our Families and Family Structures

Families and Family Structures in Oneida County in 2010

  • More than three quarters of all families have two parents present in the home
  • Less than half of all families have children under the age of 18 in the home
  • More than 21,000 people have experienced either divorce or marital separation

Populations in Families: According to the 2012 ACS 5 Year Estimates, there are more than 179,000 people living in 57,897 family units in Oneida County. Some additional 40,328 people lived within 33,603 non-family units. Additionally, 14,290 people were in group quarters in 2010.

Family Structures: As a percentage of families, the two-parent family represents the vast majority of all family structures in Oneida County. About 73% of all families are comprised of this more traditional family structure. Female-headed families (with no male present) are the next most common in Oneida County. One in five families (20%) are female-headed. Male-headed families (with no female present) made up about 7% of all familial units.

Children in Families: As a general rule in Oneida County, families with children are less common than those without. Less than half of all families (43%) have children under the age of 18 residing in the family household. This is especially true among more traditional, couple-based families. Less than two out of every five two-parent families (38%) have children living at home with them. Single-parent families (male- or female-headed, with no spouse) are far more likely to have children at home. Three out of every five (60%) female headed families have children 18 or younger living in the home, while 52% of all single dad headed families have young children at home.

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Monday, April 28, 2014

2010 Oneida County Retrospective: Our Aging Population

Aging of Oneida County Population in 2010

  • Median age is above 40 years old for first time
  • About one in six people are age 65 or older
  • Preschool aged youth only make up about 6% of population

The advance of the “baby boom generation” among age cohorts continues to influence the “graying” of the population within Oneida County. With the current median age at 40.6 years old, the baby boom population transition from young adulthood to middle age continues to be felt. More than half (57%) of the county’s population is between the age of 20 and 65. In addition, almost one out of every six residents (16%) is age 65 or older. About one out of every five people (22%) in Oneida County is under the age of 18. The county’s youngest cohort, those under age 5, make up less than 6% of the total population.

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Historical Aging Trends in Oneida County 1950 - 2010

  • Median age grows with "graying" of baby boomers
  • Elderly females driving overall median age of all females to more than 40 years old
  • Elderly males growing in number faster than females

Median Age: The median age of Oneida County residents has changed considerably over the last 60 years. This change has not, however, simply been one of a stagnantly aging population. As a matter of fact, the median age of the population actually declined for a period of twenty years, from 1950 to 1970.  During those 20 years the median age dropped from 32.9 in 1950 to 29.0 in 1970. After 1970, the median age began to climb, rising to the Census 2010 level of 40.6 years of age.

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Baby Boom Influence: Much of this change in median age is a result of the introduction, and the aging, of what has been called the “baby boom” generation. The movement of baby boomers from youth to working age adults to those entering the retirement age can be tracked rather easily over the last half of the 20th century by following their movement through a series of simple population pyramids.

Boomers first begin showing up as a population influence in the 1950s. They basically comprise the youngest members of the county, those who were age 5 and younger. In Chart 3 you can see the very beginning of the largest generational shift in our country's history beginning to make itself known in the local data. By the time of the 1980 Census, the Baby Boom Generation is now generally between 15 and 35, young workers (Chart 4). Over the next thirty years the bugle in the population pyramid representing the baby boomers shifts closer to retirement age. In 2010 the leading edge of the generation reaches 65, as seen in Chart 5 below.

Back to the Future2: The Release of the 2010 County Retrospectives

Often times data lays dormant for years, or in some cases decades, with little or no comprehensive review being undertaken to place current information in any historical context. One of the most sought after but often underutilized resources of such time series data is the decennial census. In December of 2004, the Herkimer Oneida Counties Comprehensive Planning Program released a report on the last 50 years of census related data for both Herkimer and Oneida Counties.

The time has come for the re-release of this series, updated with data from 2010. Given changes to the decennial census, the data source for much of this comparison now comes from the American Communities Survey, or the ACS. The ACS is NOT the equivalent of the decennial census. It is a very different vehicle for data collection. However, to the degree possible, comparative data will be offered.

Such a review of data is, by the very nature of such time constrained data collection, and the introduction of a new source of data (the ACS), of fraught with pitfalls. Changing definitions, as well as the nature of the data collection process itself, often conspire to make many comparisons the equivalent of mixing apples with oranges. As the social constructs of race, poverty, aging, etc., all evolve to better, or perhaps at least different, levels of understanding over the years, the ability to make comparisons with past data becomes tricky, perhaps difficult, and even impossible at times.

These report will attempt to recognize those potential issues and bring them to light. They will involve data collected since the 1950 census through the 2012 ACS Five Year Estimates. In many cases, in terms of the historical sections of each chapter, the data may only extend back to 1960 or 1970 until the 2012 ACS. Much of that is due to the introduction of new concepts (such as poverty) or a change in the basic definitions and collection of data on an issue, such as race. Sometimes, issues are only able to be examined in a broad context, such as white versus non-white populations. But there are many topics in which the data does allow for direct comparison over several decades with little change in how the data was collected or coded.

Still, it is important to strongly urge that each of the data sets be examined in terms of the subtleties of the definitions for each topical issue. Efforts have been made to be sure to compare like items when possible, and to note potential problem areas. All of the included analysis provides at least a loose sketch of the immediate historical past, and, at best, a more thorough review of some of the changes being experienced within Oneida County over the last fifty to sixty years. 

These reports are not intended as an assessment of demographic trends in the last half of the 20th century in either county. Rather they are more of a simple review of what has occurred. While a plethora of other topics could have been included, few have enough historical context (i.e. data available) to make them readily reviewable. As a result, this report focuses on five topics: aging, families, income/poverty, nativity/race, and employment.

Expect to see these chapters released here in the next several weeks (one will be later today!). Oneida County's chapters will be released first and then Herkimer County's will follow. 

Friday, April 25, 2014

Looking at BIG Data: What Social Media Can Tell Us About Ourselves

Big data, like the name says, are, well, BIG. The term is loosely used to refer to any number of data sets that by their very nature are so large as to make them extremely difficult to analyze and to understand. More and more, Big Data includes they types of things we culturally have come to share on places like Facebook and other social media. Recently the New York Times looked at one Big Data set and came up with a sort of interesting map I wanted to share.

There are few things we think of as truly American, but the short list includes motherhood, apple pie, and of course baseball. The dividing lines between various parts of the country as being Yankee fans, or Red Sox fans, for example, have long been debated. Using social media "likes" and the public preferences expressed on Facebook, the NYT came up with the following map showing the country's favorite baseball teams attributed by zip code.

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They also have an interactive map where you can pull down to your local area and click on a zip code to see the top 3 teams favored in that area. Here's what the 13501 area shows us in terms of team loyalty.

While the support of our national pastime is sort of interesting to look at, think about it more in terms of what other things social media's Big Data might say about you, your spending habits, and your other allegiances!

Thursday, April 24, 2014

Cornell PAD Trend Data: Building Upon the Release of IRS Records

The Cornell Program of Applied Demographics (PAD) has recently folded in the IRS records cited in my last post on their Trends page.

The PAD Trends page presents recent demographic and economic county trends. The data presented is collected from a variety of sources. The trends (variables) are organized in chapters and sub-chapters. Each trend has a little sparkline that quickly gives a glance at the recent trend. More detail, including the numbers are also available.

To use their page:
  • Select a county (or the state as a whole) using the drop down menu.
  • The bottom grey bar has some additional menu items:
    • Trends that have to do with dollar amounts can be displayed unadjusted for inflation (Current $) or adjusted for inflation (Constant 2000 $)
    • "Export to Excel" will create a Microsoft Excel file with the data from selected variables.
    • "Analyze" will open a new window with larger graphs. This page allows for some basic computations between variables. Trends for multiple variables are combined when possible (based on the dimension of the variable)
    • "Map" will open a new window with a coloured county map that shows differences beween counties for selected variables. There will be a drop down box with the variables selected.
  • The chapters are listed on the left and assist in scrolling through the available trends.
  • The chapters and sub-chapters can be collapsed and expanded by clicking on the little double arrows or on the chapter title.
  • If you move your mouse over a sparkline, an enlarged chart with axes information will pop-up.
  • Click on the details button to see an enlarged chart and a table. There will also be a reference to the data source.
  • You can select/unselect variables for further analyses by clicking on the little box in front of the variable name.
Further explanation of a variable can be found by clicking on the name of the variable (not available for all variables).

Wednesday, April 23, 2014

Single-County IRS Migration Profiles

State and county migration data for 2010–2011 are now available on Tax Stats. Migration data for the United States are based on year-to-year address changes reported on individual income tax returns filed with the IRS. The data present migration patterns by State or by county for the entire United States and are available for inflows (the number of new residents who moved to a county or State and where they migrated from) and outflows (the number of residents leaving a county or State and where they went).

The Missouri Census Data Center, under the leadership of John Blodgett, one of the true treasures of the national state data center program,  has downloaded and converted these files. Their web application for generating IRS Migration Profile reports has been upgraded to recognize the new year of data. Access this application at the IRS Migration Profile menu page (for single counties, anywhere in the U.S.). 

This application will generate a migration profile with data regarding movement into and out of the chosen county based on tracking movement reflected in IRS tax returns in consecutive tax years.  The report will by default show all counties that had a minimum of 10 tax returns indicating a move into the selected county or out of that county.

Below are just partial samples of what the profiles look like.  Visit the website to explore the entire profiles for Herkimer and Oneida counties!

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