Friday, October 17, 2014

Weekly Hours Worked and Weeks Worked Per Year By "For Profit", "Non-Profit", "Government" and "Self Employed" Workers

Now that summer vacation has come and gone and we head into winter, I thought it would be interesting to look at the weeks worked each year and the hours worked per week by various parts of the workforce. Specifically I used the 2012 ACS Five Year Estimates PUMS data "Class of Worker" typography to compare those that work in "for profit" businesses, those in "not for profits", those in "government employment" and those that are "self employed".

Below are several graphs which show the distribution of each of these classifications in terms of the hours and weeks worked in the past year. To start with, as you can see below, most of the workforce is working between 31 to 40 hours weekly - the majority of those working at for profit businesses (56%), those in non-profits (55%), and those working in the public sector/government (62%) all work in the 31 to 40 hour range.

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The lone exception are workers who are self employed. While more of them work 31 to 40 hours per week (26%) than any other ten hour span, it is not a number approaching the 50% mark as with the other three workforce groups. If we look a bit deep at these numbers the reason why is obvious.

Below are four pie charts showing the percent of workforce for each group that work more than 40 hours per week. In the case of for profits, non-profits, and government workers, somewhere between 38% and 45% worked in excess of 40 hours each week in the past year. However, note the percent of self employed workers who put in more than 40 hours of work each week - nearly 3 in 4 (74%) worked in excess of 40 hours per week. And from the PUMS data, it shows that as many as 15% worked in excess of 50 hours each week!


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Not surprisingly, most of the workforce works 50 or more weeks per year - regardless of the sector, between 70% and 75% worked 50 to 52 weeks in the last year.

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Here is the distribution of each group's workforce in regard to the number of weeks less than 50 that they worked in the prior year.

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How The Census Bureau Measures Poverty

The US Census Bureau offers two measures of poverty. The official measure of poverty is the more traditional piece based on a 1963 definition of poverty living based largely on cash resource availability. The second measure is the Supplemental Poverty Measure (SPM) which accounts for non-cash benefits from government programs aimed at low income families as well as cash resources of the household.

Below is an infographic comparing the two measures which helps explain their differences more fully. A publication by the Census Bureau, located here, provides some comparisons between the official and SPM data by state. To see local information for your community on poverty, visit this previous post of poverty and income by municipality.


how census measures poverty infographic image [Source: U.S. Census Bureau]

Tuesday, October 14, 2014

A Look at Seniors in Herkimer County From the 2012 ACS Five Year Estimates

Below are two tables showing characteristics of the current population age 65 and over in Herkimer County. New data for Herkimer County will be available at the end of this month in the form of the 2013 ACS Three Year Estimates!

Herkimer County Elderly Profile (Part 1)

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Herkimer County Elderly Profile (Part 2)

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Monday, October 13, 2014

New Zip Code Data from the IRS

The IRS recently released ZIP Code data showing selected income and tax items classified by State, ZIP Code, and size of adjusted gross income. These data are based on individual income tax returns filed with the IRS and are available for Tax Years 1998, 2001, 2004 through 2012.
 
The map on the IRS page allows you to select a set of state ZIP Codes and peruse their data. 
 
 
The data include items such as:
  • Number of returns, which approximates the number of households
  • Number of personal exemptions, which approximates the population
  • Adjusted gross income 
  • Wages and salaries
  • Dividends before exclusion
  • Interest received  

So pick a year below and take a look at your local ZIP code !
ZIP Code Data
ZIP Code Data 1998–2010
1998  2001  2004  2005  2006  2007  2008  2009  2010

Tuesday, October 7, 2014

An Example of Using ACS Estimates Over Time: Poverty and Family Types 2005 to 2013

As the single year (and the three year) American Community Survey (ACS) data continues to be released, it is important to remember that data now exists going back to 2005 for our area. One of the hopes of the Census Bureau was that such data availability would allow policymakers, as well as the public, the opportunity to look at their region longitudinally, albeit with a certain amount of caution.

As an example, below are the historical estimates of poverty by family type, in this case single mom families versus two parent families in Oneida County. Not surprisingly, poverty rates for single parents are quite a bit higher than they are for dual parent families - the average over the nine years is about 30% for single moms and around 5.5% for dual parent families.

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What's important to note is the trends depicted by the shaded areas in the chart, which represent the margins of error for each year. As can been seen, they are rather large for single moms and fairly small for dual parents. This is mainly because of the small number of single mom's sampled (due to their fairly small number within the community). Just be sure to take a look at those margins of error as you explore the ACS data as there are times that they are exceedingly large, and should then be viewed with a some caution.

Thursday, October 2, 2014

Does Buying Local REALLY Matter?

A post at Demo Memo, a great site analyzing demographics data, looked at the issue of local businesses and the impact "buying local" has. As they asked the question, "Does buying local matter to economic well being?"

What they found was that this question is addressed in a Federal Reserve Bank of Atlanta analysis  of county level economic data for the 2000 to 2009 time period. Economist Anil Rupasingha examines the local share of employment by county and compares those numbers to real per capita income growth, employment growth, and poverty.

In most counties, employment in locally-owned businesses surpasses employment in "nonresident-owned" businesses. But the local share varies greatly by county, which you can see at a glance in the county-level maps included in the analysis. The share of employment in locally-owned businesses varies by county from 11 to 87 percent. The share of employment in nonresident-owned businesses varies by county from zero to 85 percent.

Percent of Residents Working in Locally Owned Businesses (2007)


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"Historically, the most popular local economic development approach was to attract businesses outside a particular municipality, state, or region," says Rupasingha. But theories about local economic development are changing, he says, and "economic development based on local entrepreneurship is increasingly gaining traction." Which approach is better?

Local is better. According to the study's results, the greater the local entrepreneurship, the greater the per capita income and employment growth and the lower the poverty. Also and interestingly, smaller local businesses have a greater effect on local economic performance than larger local businesses. "My results suggest that fostering smaller local businesses may be good local economic development policy," Rupasingha concludes.

Locally, businesses with less than 50 employees make up about 98% of companies in Herkimer county and 95% of those in Oneida County. There are more than 10,000 people who consider themselves "self employed" in the region ! So obviously small businesses play a big part of our local economy.

Monday, September 29, 2014

Determining Fiscal Stress of Municipal Entities in 2013

The New York State Comptrollers Office recently released a report on their Fiscal Stress Monitoring System for various municipal entities across New York State. They also have a website where you can search for these municipal entities by name, etc. at http://wwe1.osc.state.ny.us/localgov/fiscalmonitoring/fsms.cfm.

The object of the monitoring system is to help New York State local officials deal with fiscal challenges and to identify clearly those local governments and school districts that are moving towards, or are already in, fiscal stress. Such monitoring of the fiscal health of local governments and school districts should allow for early actions to prevent these entities from ending up in severe fiscal stress. The preventive actions – ideally developed with active participation from citizens who will be affected − should result in less cost and less disruption to vital services.


The Fiscal Stress Monitoring System evaluates local governments (counties, cities, towns and villages)and school districts based on both financial and environmental indicators. The financial indicators will be calculated using financial data that is filed in annual update documents (AUDs) by each local government and in annual financial reports (ST-3s) for school districts. A score will be calculated for each financial indicator to arrive at an overall score for each local government and school district, which will then be used to classify whether the unit is in “significant fiscal stress,” “moderate fiscal stress,”is “susceptible to fiscal stress,” or “no designation.” 

Below are the stress scores for entities from Herkimer and Oneida Counties. For a full explanation of the scores visit the Comptroller's link above.

Herkimer County

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Oneida County

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The website will also give you a full fiscal self assessment of each municipal entity if you click on their scores.