While total employment in Kansas is growing, two industries are the exception.
Kansas employment, seasonally adjusted, selected series. Click for larger.Newly revised data from the Bureau of Labor Statistics lets us examine Kansas employment. This data comes from the Current Employment Statistics, which is a monthly survey of employers.1 I’ve gathered this data and have presented it in an interactive visualization. The accompanying charts are derived from that.
The first chart shows the relative change in jobs for each series, using seasonally adjusted values. Total private sector employment is growing. Employment in mining and logging, which is dominated in Kansas by the oil and gas industry, has cratered since its peak in 2014. Manufacturing employment has remained steady since 2010, but at a lower level than in the past.
Kansas manufacturing employment, not seasonally adjusted, selected series. Click for larger.Looking at manufacturing in more detail, we see that aerospace manufacturing has been on a long downwards trend at the time total manufacturing has remained relatively level. (Aerospace employment is available only as unadjusted data, so it’s shown in a separate chart with unadjusted manufacturing.)
An interactive visualization of Kansas employment by industry.
The Bureau of Labor Statistics is an agency of the United States Department of Labor. It describes its mission as: “The Bureau of Labor Statistics of the U.S. Department of Labor is the principal Federal agency responsible for measuring labor market activity, working conditions, and price changes in the economy. Its mission is to collect, analyze, and disseminate essential economic information to support public and private decision-making. As an independent statistical agency, BLS serves its diverse user communities by providing products and services that are objective, timely, accurate, and relevant.”1
BLS provides monthly employment statistics. It has just updated revised numbers for 2016. I’ve gathered these for Kansas and present them in an interactive visualization.
This data comes from the Current Employment Statistics, which is a monthly survey of employers.2
The tabs along the top of the visualization hold different views of the data. Employment figures are in thousands. You may view seasonally adjusted or unadjusted data. Some views display the number of jobs, while others display the change in jobs by industry since the first year or month that is selected. When using the charts that display annual averages, be aware that using a time selection with a partial year will not provide accurate results.
Two “industries” that are closely followed are “Total Nonfarm” and “Total Private.” These, obviously, are not industries in themselves, but are sums of other industries. There are other examples like this.
Click here to access the visualization. The visualization was created by myself using Tableau Public.
Example from the visualization, showing points of control. Click for larger.
The National Association of State Budget Officers publishes spending data for the states. In this interactive visualization, I present the data in a graphical and flexible format.
Data for each state is subdivided by fund (see below for definitions). Data through 2015 is actual, while data for fiscal year 2016 is estimated. The figures for the “state” United States were computed by summing the spending in all states, then dividing by the U.S. population. These figures are not adjusted for inflation.
In the example from the visualization that is shown below, we see general fund spending for Kansas and selected states. Note that general fund spending on a per-capita basis in Kansas is higher than in Oklahoma, Colorado, and Missouri, and approximately the same as Texas. When using the visualization you may select states, funds, and time periods to create your own comparisons. Because the visualization is interactive, you can do things like clicking on legends to highlight data series.
Of note is the tab comparing spending in states that have an income tax vs. those that have no income tax. Click here to access the visualization.
Example from the visualization, showing general fund spending for Kansas and selected states. Click for larger version.
From NASBO, definitions of the funds.
General Fund: The predominant fund for financing a state’s operations. Revenues are received from broad-based state taxes. However, there are differences in how specific functions are financed from state to state.
Federal Funds: Funds received directly from the federal government.
Other State Funds: Expenditures from revenue sources that are restricted by law for particular governmental functions or activities. For example, a gasoline tax dedicated to a highway trust fund would appear in the “Other State Funds” column. For higher education, other state funds can include tuition and fees. For Medicaid, other state funds include provider taxes, fees, donations, assessments, and local funds.
Bonds: Expenditures from the sale of bonds, generally for capital projects.
State Funds: General funds plus other state fund spending, excluding state spending from bonds.
An interactive visualization of Wichita-area employment by industry.
The Bureau of Labor Statistics, part of the United States Department of Labor, makes monthly employment statistics available. I’ve gathered them for the Wichita metropolitan area and present them in an interactive visualization.
This data comes from the Current Employment Statistics, which is a monthly survey of employers.
An interactive visualization of GDP for each state, by industry.
The Bureau of Economic Analysis is an agency of the United States Department of Commerce. BEA describes its role as “Along with the Census Bureau, BEA is part of the Department’s Economics and Statistics Administration. BEA produces economic accounts statistics that enable government and business decision-makers, researchers, and the American public to follow and understand the performance of the Nation’s economy. To do this, BEA collects source data, conducts research and analysis, develops and implements estimation methodologies, and disseminates statistics to the public.”
One series BEA produces is gross domestic product (GDP) by state for 21 industry sectors on a quarterly basis. BEA defines GDP as “the value of the goods and services produced by the nation’s economy less the value of the goods and services used up in production.” It is the value of the final goods and services produced.
In describing this data, BEA says “These new data provide timely information on how specific industries contribute to accelerations, decelerations, and turning points in economic growth at the state level, including key information about the impact of differences in industry composition across states.” This data series starts in 2005. An announcement of the most recent release of this data is at Gross Domestic Product by State: Third Quarter 2016.
I’ve gathered the data for this series for all states and regions and present it in an interactive visualization using Tableau Public. The data is presented in real dollars, meaning that BEA adjusted the numbers to account for changes in the price level, or inflation.
In the visualization, you may use several different presentations of the data and filter for specific states, industries, and time intervals. Besides a table of values, the series are presented as percentage change over time since the first values, so that growth, rather than magnitude, of GDP is shown.
Proposed changes in the Kansas motor fuel tax and sales tax on groceries affects households in different ways.
As part of a revision to the tax regime in Kansas, a bill proposes to raise the motor fuel tax and reduce the sales tax on most types of groceries. (Restaurant meals would not be affected.) The bill is HB 2237.1 It implements most or all of the elements of a plan called “The Path Forward.”2
Excise taxes (the motor fuel tax) and sales taxes are usually regressive, meaning that their impact is felt most severely by lower-income households.3 Data shows that as income rises, so too does spending on motor fuel and food at home. But the rise in spending is not proportional to income. For example, data from BLS (see below for references) tells us that households in the lowest quintile of income spent an average of $939 per year on motor fuel and oil in 2015. For the highest quintile of households, spending was $3,226.
But when we look at this spending as a percent of household income after taxes, for the lowest quintile spending on motor fuel and oil represents 8.2 percent of income. For the highest quintile, it is 2.3 percent. A similar pattern holds for purchases of food for home consumption.
Because of this relationship, taxes on the sale of gasoline and food affect lower-income households proportionally more. What I have done is to estimate the additional cost, as a percent of after-tax income, of the proposed motor fuel tax. As can be seen in the nearby chart, the additional cost ranges from 0.39 percent of income for the lowest-income households to 0.11 percent for upper-income households. This difference, a factor of 3.5, illustrates the regressive nature of sales taxes, and the gasoline tax is just that — a sales tax.
HB 2237 Additional Tax Cost as Percent of Income After Taxes. Click for larger.The bill proposing the increase in gasoline tax also proposes a reduction in the food sales tax rate from 6.5 percent to five percent. That tax is also regressive. In 2014, as Wichita was considering adding one cent per dollar to the sales tax already paid, my analysis of spending found this: “The lowest income class of families experience an increase nearly four times the magnitude as do the highest income families, as a percentage of after-tax income. This is the regressive nature of sales taxes illustrated in numbers.”4
HB 2237 Sales Tax Savings as Percent of Income After Taxes. Click for larger.A nearby chart shows that the savings from the proposed lower food sales tax ranges from 0.07 percent for high-income households to 0.33 percent for low-income households. This is consistent with the regressive nature of sales taxes: They affect low-income households greatest — when raised, and also when lowered.
HB 2237 Net Cost as Percent of Income After Taxes. Click for larger.Another chart shows the summative effect of the higher fuel tax and lower food sales tax. Of interest, the net effect is highest for the middle 20 percent of households. Note that considering these two taxes, the effect of the proposed bill is to raise taxes for everyone.
Show the math
The Bureau of Labor Statistics, a unit of the U.S. Department of Labor,5 has data for household expenditures on gasoline and oil. This data is available for five intervals, or quintiles, of income.6
Then the U.S. Energy Information Administration, the statistical and analytical agency within the U.S. Department of Energy,7 has gasoline prices. It doesn’t have them for Kansas, but it does for the Midwest.8
From these two values, we can calculate the number of gallons of gasoline purchased for each income level. Here, we lose a bit of validity, as the BLS data is for purchases of gasoline and oil. But it’s the data we have, and purchases of gasoline surely dominate purchases of motor oil.
Once we have the number of gallons of gasoline purchased, we multiply by the proposed eleven cents per gallon additional tax. This produces the extra gasoline sales tax cost per household. This is a static calculation and assumes no change in the number of gallons purchased due to the higher cost from the tax, or from any change in gasoline prices for any reason.
Then, the BLS Consumer Expenditure Survey also holds income after taxes for the five income levels. Simple division gives us the percent of household income that the additional tax represents.
The BLS Consumer Expenditure Survey also holds data for spending on food at home for the five income levels. From that, we can multiply by 1.5 percent to estimate the amount saved if sales tax on food falls to five percent from 6.5 percent. As with purchases of gasoline, this is a static calculation and assumes no change in behavior from reduced sales tax on groceries. Simple division gives us the percent of household income that the tax savings represents.
Then, we can subtract the food sales tax savings from the additional gasoline tax costs to produce a net calculation.
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Notes
Kansas House of Representatives, Committee on Taxation. HB 2237, Concerning taxation; relating to income tax, rates, determination of income, tax credits; motor fuels tax, rates, trip permits, distribution; sales and compensating use tax, food and food ingredients.http://www.kslegislature.org/li/b2017_18/measures/hb2237/. ↩
“A regressive tax is a tax imposed in such a manner that the tax rate decreases as the amount subject to taxation increases.” Wikipedia. Regressive tax.https://en.wikipedia.org/wiki/Regressive_tax. ↩
An interactive visualization of employment in metropolitan areas.
Employment data from the Bureau of Economic Analysis, an agency of the United States Department of Commerce, is available for all metropolitan areas and major industries. I present this data in an interactive visualization using Tableau Public. In this visualization you may access several different presentations of the data. You may filter for specific areas, industries, and time periods. The data is available in a table of employment numbers, or in series presented as the percentage change since the first value. This illustrates relative growth, rather than magnitude, of employment. This is annual data from BEA table CA25N1 through 2015, the last year available at this time.
In the nearby example from the visualization we can see that Wichita has performed poorly compared to some peers of interest.
You may use the visualization yourself by clicking here.
Of note, the definitions of MSAs change from time to time.2
Employment by MSA and Industry example. Click for larger.
Broomfield County, CO, was created from parts of Adams, Boulder, Jefferson, and Weld counties effective November 15, 2001. Estimates for Broomfield county begin with 2002.
Estimates from 2008 forward separate Skagway-Hoonah-Angoon Census Area into Skagway Municipality and Hoonah-Angoon Census Area. Estimates from 2009 forward separate Wrangell-Petersburg Census Area into Petersburg Census Area and Wrangell City and Borough. In addition, a part of the Prince of Wales-Outer Ketchikan Census Area was annexed by Ketchikan Gateway Borough and part (Meyers Chuck Area) was included in the new Wrangell City and Borough. The remainder of the Prince of Wales-Outer Ketchikan Census Area was renamed Prince of Wales-Hyder Census Area. Petersburg Borough was created from part of former Petersburg Census Area and part of Hoonah-Angoon Census Area for 2013 forward. Prince of Wales-Hyder Census Area added part of the former Petersburg Census Area beginning in 2013. For years 2009-2012, Petersburg Borough reflects the geographic boundaries of the former Petersburg Census Area. Wade Hampton Census Area was renamed Kusilvak Census Area on July 1, 2015.
Virginia combination areas consist of one or two independent cities with 1980 populations of less than 100,000 combined with an adjacent county. The county name appears first, followed by the city name(s). Separate estimates for the jurisdictions making up the combination area are not available. Bedford County, VA includes the independent city of Bedford for all years.
Shannon County, SD was renamed to Oglala Lakota County, SD on May 1, 2015.
Nonmetropolitan portion includes micropolitan counties. ↩
A positive effect of the 2009 Obama stimulus appeared only long after its forecasted date.
Many people remember that President Barack Obama warned that the unemployment rate would rise to a high level without a stimulus program. In January 2009 two Obama administration officials, including Christina Romer (who would become chair of the Council of Economic Advisers) wrote a paper estimating what the national unemployment rate would be with, and without, the American Recovery and Reinvestment Plan, commonly known as the stimulus.1 That plan passed.
Stimulus projections from the Obama Administration. Click for larger.That paper included a table projecting what employment levels the country would experience with, and without the stimulus. For the fourth quarter of 2010, the authors estimated payroll employment would be 133,876,000 without the stimulus, and 137,550,000 with the stimulus. That’s a gain of 3,673,000 jobs due to the stimulus, estimated the authors.
What was the actual experience in jobs? First, for a look at the projections regarding the unemployment rate, see Holding politicians to their boasts and promises. The promoters of the stimulus also projected employment levels, that is, the number of jobs.
To examine the effect on jobs, I gathered data from the Bureau of Labor Statistics and compared the results to projections. I used seasonally adjusted data, which is only slightly different from the non-adjusted data.2
Actual employment with lines showing forecasts of employment with and without stimulus. Click for larger.Employment exceeded the forecasted level with the stimulus in January 2014, when seasonally adjusted employment reached 137,574,000. (Employment exceeded the forecasted level for the economy without the stimulus in May 2012, when seasonally adjusted employment reached 133,951,000.)
What was projected (or promised) for the fourth quarter of 2010 wasn’t achieved until January 2014. That’s three years late.
The lesson, I believe, is that the power of government to affect the economy in a positive way is weak and limited, especially when using the Keynesian tools of attempting to manage aggregate demand.3 It’s even more true at a state level, as the tools state governments can use are weaker than the federal government’s.
The BLS data series are:
CES0000000001, series title All employees, thousands, total nonfarm, seasonally adjusted
CEU0000000001, series title All employees, thousands, total nonfarm, not seasonally adjusted ↩
Commissioned by Kansas Policy Institute and written by researchers from Arizona State University, a new report looks at the Kansas economy after the tax reforms passed in 2012.
Much of the discussion over economic growth following the 2012 Kansas tax reforms were enacted is misguided, hobbled by a misunderstanding of what the tax cuts were trying to accomplish and reliance on incomplete data. Additionally, it fails to take into account the fact that most job growth in Kansas has been — and will continue to be — from pass-through businesses (i.e., sole proprietorships, S-corporations, limited liability corporations, and joint partnerships). In fact, the 36,135 jobs created by pass-through entities in Kansas represent 82 percent of all private sector jobs created in 2013 and 2014, the latest data available from the U.S. Census Bureau, and the growth is more than three times as great after tax reform than before.
Using this Census data and other appropriate private sector data our analysis indicates that the impact of the tax reforms has been positive. Kansas comes out on top or at least shows strong growth in almost every relevant state comparison of the most comprehensive private sector job growth metrics. Kansas also matches up with other states well even when the less-comprehensive data often used to make comparisons is adjusted for the size of the state.
It is also important to consider the source of job creation data, the structure of a state’s economic make-up, and a state’s population when comparing job numbers. In short, just as it would not be appropriate to compare student achievement for the Kansas City and Blue Valley school districts for obvious demographic differences, it is not appropriate to compare certain states just because of geographic proximity. The monthly employment numbers from the Bureau of Labor Statistics (BLS) use a different methodology to count employment than does a more comprehensive, but less frequent, analysis from the Bureau of Economic Analysis (BEA). For instance, the BLS data estimates that in 2015, Kansas had an employed private-sector workforce of nearly 1.4 million, while the BEA data puts it at 1.9 million. So while the BLS data warrants monthly media coverage this paper puts more emphasis on the BEA analysis as it better captures those employed by proprietorships and in farm employment.
This study also uses new data from the Kansas Department of Revenue (KDOR) to clearly demonstrate that tax evasion or strategic corporate tax planning has not been widespread. KDOR records also make clear that the total value of the Kansas tax reforms from 2012 was primarily driven by lowering the income tax burden on individual wage earners. This is yet another overlooked aspect of the tax cut, as 71 percent of the overall tax relief went to individual taxpayers and 29 percent went to pass-through businesses through the income tax exemption. A final data point from KDOR also makes clear who is benefitting from the pass-through exemption. Median family income in Kansas is around $52,000 and 88 percent of the filers in 2014 with business income had Kansas adjusted gross income that year of less than $50,000.
While there is still more analysis to be done and more data to be released over the coming years, we believe the preliminary signs indicate that the Kansas tax reforms have had and, more importantly, will continue to have a positive impact on state job growth.
