Tag Archives: Economics

Wichita, Kansas, and U.S. economic dashboards

Dashboards of economic indicators for Wichita and Kansas, compared to the United States.

Example of the Wichita economic dashboard. Click to view.
The Federal Reserve Bank of St. Louis gathers economic data from sources like the U.S. Bureau of Labor Statistics and the U.S. Bureau of Economic Analysis. This data is then available in an interactive graphing and charting system.

Example of the Kansas economic dashboard. Click to view.
Using this system, I’ve created dashboards (collections of charts) holding economic data for Wichita and Kansas. The charts, as they appear on the dashboard, are static, although they should show the most current data. At the bottom of each chart is the link “View on FRED.” By clicking on that link you gain access to the interactive version of the chart. You may then make many different types of customizations.

Click here for the Wichita dashboard, and click here for the Kansas dashboard.

Real Gross Domestic Product by State and Industry

An interactive visualization of state Gross Domestic Product 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 and annual 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 here.

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. This visualization uses annual data.

Tabs along the top of the visualization hold different views of the data. You may select a time period, one or more industries, and one or more states.

Click here to access the visualization. The visualization was created by myself using Tableau Public.

Example from the visualization. Click for larger.

Explaining the Kansas budget, in a way

A video explaining the Kansas budget is accurate in many aspects, but portrays a false and harmful myth regarding school spending.

A popular video explaining the Kansas budget deserves scrutiny for some of the data presented. The video is available at the Facebook page of Loud Light.

The presentation makes a few good points. For example, the video is correct in that the sales tax is a regressive tax, affecting low-income households in greater proportion. During the capaign for a Wichita city sales tax in 2014 I analyzed Census Bureau data and found that 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.1 2

The video also rightly notes that Kansas is now, and it has in the past under other legislatures and governors, inadequately funding KPERS, the state employee pension plan.

Interestingly, the video praises Kansas for its early adoption of “progressive economics.” I think the narrator meant “progressive taxation,” as the video shows Kansas adopting an income tax in 1933. How has that worked for Kansas? There are a variety of ways to look at the progress of Kansas compared to the nation, but here’s a startling fact: For the 73rd Congress (1933 to 1935) Kansas had seven members in the U.S. House of Representatives. (It had eight in the previous session.) Today Kansas has four members, and may be on the verge of losing one after the next census. This is an indication of the growth of Kansas in comparison to the nation.

Kansas Department of Transportation Funding, partial. Click for larger.
The narrator states, “Kansas Department of Transportation is mostly funded by restricted revenue like fuel tax.” This was true at one time. But starting in 2011 KDOT has received more funding from sales tax than motor fuel tax.3 The gap is getting wider, as can be seen in the nearby chart. (By the way, there are proposals to increase the motor fuel tax. This tax is just like the sales tax, affecting low-income households greatest.)

School spending

The greatest problem in this video is its explanation of state spending on K through 12 schools. This is important, as the video correctly notes that this spending is half of the general fund budget. In introducing this section, the narrator notes “budget report gamesmanship that’s created a rhetorical paradox,” conceding it is “technically” true that education spending is at record levels.

The video then shows a chart titled “State Aid Per Pupil.” The chart starts with a value a little over $6,000 in 1993, declining to about $4,000 in 2013, then staying at that level. The citation is “Governor’s Budget Report” from the Kansas Division of Budget, and at the end of the video there is the explanation, “All financial data in this video is inflation adjusted to January 2017.”

A more accurate title for the chart is “Base State Aid Per Pupil.” That’s the actual name for the component of school spending that the video displays. This is important because base state aid is only the starting point for determining spending. Actual state aid to schools is much higher.

Kansas school spending, showing base state aid and total state aid. See article for notes about 2015. Click for larger.
Base state aid per pupil — the statistic the video presents — is an important number.4 It’s the starting point for the Kansas school finance formula used before the 2015-2016 (fiscal 2016) school year, and something like it may be used in a new formula. 5

Base state aid, however, is not the only important number. To calculate the funding a school district receives, weightings are added. If students fall into certain categories, weightings for that category are added to determine a weighted enrollment. That is multiplied by base state aid to determine total state aid to the district. 6

While this may seem like a technical discussion that doesn’t make a difference, it’s very important. Some of the weightings are large and have increased by large amounts. The at-risk weighting, intended to cover the additional costs of teaching students from low-income families, started at five percent in 1993. In other words, for every student in this category, a school district received an extra five percent of base state aid. The value of this weighting has risen by a factor of nine, reaching 45.6 percent starting with the 2008-2009 school year.7

So in the nearby chart that I prepared using data adjusted for inflation in 2016, we see base state aid per pupil on a downward trend, just as the video shows. But I also plotted total state aid per pupil, which includes weightings. This number is on a mostly upward trend.

Kansas school spending, showing ratio of total state aid to base state aid. See article for notes about 2015. Click for larger.
Kansas school spending. See article for notes about 2015. Click for larger.
The weightings have a large effect on school funding. For example: During the 2004-2005 school year, base state aid was $3,863 and the at-risk weighting was ten percent. An at-risk student, therefore, generated $4,249 in state funding. (Other weightings might also apply.)

Ten years later base state aid was $3,852 — almost exactly the same — and the at-risk weighting was up to 45.6 percent. This generates funding of $5,609. For a district that qualified for the maximum high-density at-risk weighting, an additional $404 in funding was generated. (These numbers are not adjusted for inflation.)

So even though base state aid remained (almost) unchanged, funding targeted at certain students rose, and by a large amount.

Over time, values for the various weightings grew until by 2014 they added 85 percent to base state aid. A nearby chart shows the growth of total state aid as compared to base state aid. (Starting in fiscal 2015 the state changed the way local tax dollars are counted. That accounts for the large rise for the last year of data in the chart. For school years 2016 and 2017, block grants have replaced the funding formula, so base aid and weightings do not apply in the same way.)

All this determines state aid to schools only. There is also local aid and federal aid.

The questions Kansans should ask are these: Why doesn’t this video explain that “base state aid per pupil” is not the same as “state aid per pupil?” And why not explain that total state aid per pupil is much higher than base state aid, and has been rising over the long term?


Notes

  1. Weeks, Bob. Wichita sales tax hike would hit low income families hardest. Analysis of household expenditure data shows that a proposed sales tax in Wichita affects low income families in greatest proportion, confirming the regressive nature of sales taxes. Available at https://wichitaliberty.org/wichita-government/wichita-sales-tax-hike-hit-low-income-families-hardest/.
  2. Weeks, Bob. Kansas sales tax has disproportionate harmful effects. Kansas legislative and executive leaders must realize that a shift to consumption taxes must be accompanied by relief from its disproportionate harm to low-income households. https://wichitaliberty.org/taxation/kansas-sales-tax-has-disproportionate-harmful-effects/.
  3. Kansas Department of Transportation. Comprehensive Annual Financial Report for 2016.
  4. Weeks, Bob. Kansas school weightings and effects on state aid. In making the case for more Kansas school spending, the focus on base state aid per pupil leaves out important considerations. https://wichitaliberty.org/wichita-kansas-schools/kansas-school-weightings-and-effects-on-state-aid/.
  5. For the fiscal 2016 and 2017 school years, the formula was replaced by block grants.
  6. Amendments to the 1992 School District Finance And Quality Performance Act and the 1992 School District Capital Improvements State Aid Program (Finance Formula Components), Kansas Legislative Research Department, May 20, 2014
    http://ksde.org/Portals/0/School%20Finance/amends_to_sdfandqpa_2015.pdf
  7. There’s also the high-density at-risk weighting. Starting with the 2006-2007 school year districts with a high concentration of at-risk students could receive an extra weighting of four percent or eight percent. Two years later the weightings were raised to six percent and ten percent. (This formula was revised again in 2012 in a way that may have slightly increased the weightings.)

Census data for downtown Wichita workers

Is the presentation of the number of workers in downtown Wichita an innocent mistake, mere incompetence, or a willful lie?

There’s a question regarding how many people work in downtown Wichita, the Wichita Eagle reports.1 Other sources have noticed a discrepancy.2

Promotional material on the former Henry’s building. Click for larger.
At issue is the meaning of “working” in a certain location. Data that the Center for Economic Development and Business Research at Wichita State University supplied to the Wichita Downtown Development Corporation indicates about 26,000 people work in downtown Wichita, for these purposes defined as zip code 67202. This number is used in a wide variety of ways, including in Wichita city budgets and federal grants made by the city.

It’s appropriate, then, to understand what the 26,000 number means. The Eagle article mentions “a likely mistake in how the number of jobs downtown is calculated.”3 The same article quotes Jeremy Hill, director of CEDBR, as saying, “It looks very obvious and plausible that it is an error.”

There is no “mistake” or “error” in this Census data, which is known as LEHD Origin-Destination Employment Statistics, or LODES. But we need to be curious or cautious enough to investigate what this data means. Documentation from the Census Bureau for LODES data gives the definition of the place of work and a cautionary note: “A place of work is defined by the physical or mailing address reported by employers in the QCEW (formerly ES-202) or Multiple Worksite Reports. An address from administrative data may or may not be the actual location that a worker reports to most often.”

The Census Bureau continues with another warning regarding this data: “Nonreporting of multiple worksites is especially common with state and local governments and school districts. In such a case, LEHD infrastructure files assign all workers for that employer (within the state) to the main address provided.”4

In the case of downtown Wichita, the mistake was made in the application of this data, which is the claim that there are 26,000 workers in downtown Wichita. There may be that many people who draw a paycheck from an administrative office located in downtown. But large numbers of these don’t come to downtown to perform their jobs.

Census block 201730043001036, showing 7,740 workers.
The LODES data reports a one square block in downtown that holds 7,740 workers. This is the block that holds the administrative office building for the Wichita public school district. Regarding this, the Eagle article reports: “One of the most likely reasons for the difference, according to multiple local academics, including Hill, is that the Census is reporting that every employee for USD 259 works downtown. Most USD 259 employees work in buildings across the city, but the central office is located downtown.” This is something the Census Bureau warns users to consider.

There’s another area of erroneous application, too, and it isn’t mentioned in the Eagle article. This concerns the second largest concentration of workers in downtown Wichita (according to the LODES data) in a Census block which has 3,437 employees. This is the block that holds Wichita city hall. In 2014 the city had 3,270 employees. But they don’t all work at Main and Central. They’re dispersed throughout the city in police stations, fire stations, and other sites.

How was this missed?

The Census Bureau OnTheMap application for downtown Wichita, zip code 67202. Click for larger.
Nearby is an example of using the Census OnTheMap application.5 This is the source of LODES data that the WDDC cites in its footnotes to its annual report. When using the application for zip code 67202, there are two — and only two — large dark blue dots. These represent the census blocks with the greatest number of workers, 7,740 and 3,437. I’d like to think that if someone at CEDBR, WDDC, or city hall looked at this map and saw those two big blue dots, they might ask a few questions. Wasn’t someone curious as to how a single block of downtown Wichita manages to hold so many employees? Which companies do they work for? What can we learn from the success of these companies that employ so many people? Can we duplicate this success in other parts of downtown?

But I don’t think anyone asked these questions. No one — not at CEDBR, WDDC, or city hall — was inquisitive enough to really look at this data and see what it means. It’s either that or there was a willful misrepresentation.

The Eagle article also reports this: “This won’t make much of a difference to most businesses downtown, according to Hill. They already know how big the market is because they have experience with it. … The best companies will look at census data when coming up with their business plans, Hill said, but every business relies on several numbers, so even if there are thousands of fewer jobs downtown than previously thought, it’s unlikely that it would have much of an impact.”

On these remarks, I would say that first, we’re trying to recruit new businesses to downtown Wichita. It’s those business firms that this data speaks to. While the “best” companies may use other sources of data, I don’t think we want to discriminate. All companies are welcome to Wichita, I hope.

Second, Hill says companies “will look at census data.” Well, this is census data.

Third, Hill says this mistake won’t have “much of an impact.” In the future, I think we’ll need to ask CEDBR, WDDC, and city hall if the data they supply is intended to have an impact, or is it for something else.

Trends of business activity in downtown Wichita. Click for larger.
Fourth, there is other census data. The United States Census Bureau tracks business data by zip code.6 The data that is available includes the number of business establishments, the number of employees, and the annual payroll, expressed in thousands of dollars not adjusted for inflation. It includes private-sector workers only, so it does not count all workers.

Nearby are results for zip code 67202. For 2015 the number of jobs is 13,581, not much more than half of what city leaders have told us. Again, these are private-sector workers only.7

Not only are these numbers much smaller, the results since 2007 show fewer business establishments, fewer people working downtown, and lower earnings generated in downtown Wichita. In all cases, the trend is lower. The LODES data is on a downwards trend, too.


Notes

  1. Morrison, Oliver. How many people work downtown? Fewer than Census says. Wichita Eagle, May 10, 2017. Available at http://www.kansas.com/news/local/article149848144.html.
  2. Weeks, Bob. Downtown Wichita jobs, sort of. Available at https://wichitaliberty.org/wichita-government/downtown-wichita-jobs/.
  3. “But the reason for this is not because 7,000 workers actually will leave but because of a likely mistake in how the number of jobs downtown is calculated.
  4. “For LODES, a place of work is defined by the physical or mailing address reported by employers in the QCEW (formerly ES-202) or Multiple Worksite Reports. An address from administrative data may or may not be the actual location that a worker reports to most often. The distinction of worksite and administrative address may be especially significant in some industries such as construction, where work is often carried out at temporary locations. In some cases, employers do not provide a multiple worksite report when it would be appropriate to do so. Nonreporting of multiple worksites is especially common with state and local governments and school districts. In such a case, LEHD infrastructure files assign all workers for that employer (within the state) to the main address provided. Bureau of Labor Statistics (BLS) data show a national noncompliance rate of 5.61 percent of multiunit employers responsible for about 4.45 percent of multiunit employment.” U.S. Census Bureau. Matthew R. Graham, Mark J. Kutzbach, and Brian McKenzie. Design comparison of LODES and ACS commuting data products. Available at ftp://ftp2.census.gov/ces/wp/2014/CES-WP-14-38.pdf.
  5. U.S. Census Bureau. OnTheMap application. Available at https://onthemap.ces.census.gov/.
  6. U.S. Census Bureau. County Business Patterns (CBP). https://www.census.gov/programs-surveys/cbp/data.html.
  7. Weeks, Bob. Downtown Wichita business trends. Available at https://wichitaliberty.org/wichita-government/downtown-wichita-business-trends/.

Wichita post-recession job growth

Since 1990 the country has experienced three recessions. For the first two of these, Wichita was able to catch up with the employment growth experienced by the entire nation.

For the most recent recession, however, this hasn’t been the case. In fact, as time progressed since 2010, the gap between Wichita and the nation has grown.

Following are three charts of private sector employment for the Wichita metro area and the nation. Each is indexed starting with the end of a recession so that job growth may be compared. Click charts for larger version. You may access and alter the chart here.

Downtown Wichita jobs, sort of

The claim of 26,000 workers in downtown Wichita is based on misuse of data so blatant it can be described only as malpractice.

Have you heard that 26,000 people work in downtown Wichita, defined as zip code 67202? It’s likely you have, as this number appears in many places.

It appears in the Wichita city budget.1

Downtown Wichita brochure.
It is cited by our chief economic development agency.2

State of Downtown Report, 2016. Click for larger.
The city’s downtown development agency uses this number in brochures and annual reports.3 4

It appears in a federal grant application made by the city.5

It appears in our state’s largest newspaper, as reported by a journalist billed as a data specialist.6

Promotional material on the former Henry’s building. Click for larger.
It appears in a Wichita specialty business newspaper quoting a Wichita business leader.7

It’s advertised on a vacant downtown building, the former Henry’s store at Broadway and William.

The Wichita Downtown Development Corporation states the data for workers in downtown Wichita, which is defined for these purposes as zip code 67202, comes from the United States Census Bureau, specifically an application called “OnTheMap Application and LEHD Origin-Destination Employment Statistics.”8 The data is commonly known as LODES. Using this application and focusing analysis on zip code 67202 produces the figure 25,850 primary jobs. Round that to 26,000, and that’s the source of the job claims for downtown Wichita.

But: Census documentation for this data gives the definition of the place of work and a cautionary note: “A place of work is defined by the physical or mailing address reported by employers in the QCEW (formerly ES-202) or Multiple Worksite Reports. An address from administrative data may or may not be the actual location that a worker reports to most often.”

The Census Bureau continues with another warning regarding this data: “Nonreporting of multiple worksites is especially common with state and local governments and school districts. In such a case, LEHD infrastructure files assign all workers for that employer (within the state) to the main address provided.”9

Census block 201730043001036
Census block 201730043001036, satellite view.
This is highly relevant and important in the case of downtown Wichita. When using the OnTheMap application for zip code 67202, there are two large bright blue dots that stand out from all others. These represent the two highest concentrations of workers in downtown Wichita. One is Census block 201730043001036, which has 7,740 employees. This is a one square block area from First to Second Streets, and Wichita to Water Streets. The block consists mostly of surface parking lots, although there are three buildings. One building is the Wichita school district administration building, and there’s the problem with the way the city uses this data. The school district has thousands of employees. Only a small fraction, however, work in the downtown administrative building at First and Water Streets. The rest are dispersed throughout the city in school buildings and other sites such as the large facility at 37th Street North and Hydraulic.

But this Census data counts all these employees in one census block. This is an example of the warning the Census Bureau supplies with the data: Nonreporting of multiple worksites is especially common with state and local governments and school districts.

There’s another example. The second largest concentration of workers in downtown Wichita appears in Census block 201730043001023, which has 3,437 employees. This is the block that holds Wichita city hall. In 2014 the city had 3,270 employees. But they don’t all work at Main and Central. They’re dispersed throughout the city in police stations, fire stations, and other sites.

(By the way, the 26,000 number is often qualified as daytime workers. But we know that many police officers and firefighters work at night. The same is true for people working at the many hotels, restaurants, and bars in downtown. They aren’t all daytime workers.)

Here’s something to consider: The Wichita school district is moving its administrative offices to the former Southeast High School building at Lincoln and Edgemoor. That’s in zip code 67218. What will happen to the reporting of jobs in downtown Wichita when some seven thousand workers start receiving their paychecks from an office in that zip code, and the Census Bureau adjusts it data accordingly?

So how many people do actually work in downtown Wichita, zip code 67202? A different set of Census data gives the number 13,593 for 2014.10 This data is much more representative of the number of people actually working in a location, although it includes private-sector workers only. Se we might add a few to that number. But it’s clear that the claim of 26,000 workers is far from true.

We’re told that the city makes decisions based on data and analysis. In the city manager’s policy message in the current city budget, the manager wrote: “In 2016, the City was selected by Bloomberg Philanthropies as a What Works City for making a public commitment to use data for informed decision making.” The same document also states: “Departmental goals and data drive decision making within each department.”

The use of data for decision making is especially important for downtown planning, we’ve been told. In selling the plan for downtown Wichita in 2010, the city’s consultants told us that the plan is “grounded in data and hard analysis.”11 But I showed that data the consultants relied on — a “walk score” — was based on nonsensical data.

We’re left with a few observations:

  • The claim of 26,000 workers in downtown Wichita is true. But as we’ve seen, it is not true in the way it is used, which is as an indication of the number of human beings actually working in downtown.
  • Did the person who gathered this data about downtown workers know what it means? If not, why not?
  • Did the person who decided to use this data in marketing downtown Wichita know what it means? If not, why not?
  • If someone knew the meaning of this data and decided to use it anyway: What does that tell us?
  • Did no one at Wichita city hall look at this data? As I’ve shown, it’s easy to see that the mapping application says 3,437 people work in the block holding city hall. Did no one look at the big blue dot and that number and realize that it is not real?
  • What if you opened a lunch counter in downtown Wichita based on the claim of 26,000 daytime workers, and then you learn there are really only half that many, with some of those working at night?

We want to trust our city leaders. We want downtown Wichita and the entire metropolitan area to succeed so that people may prosper and be happy. But episodes like this destroy trust and breed well-deserved cynicism. We can — we must — do better than this.


Notes

  1. City of Wichita. Proposed Budget 2017 – 2018. Page 2. “Over 26,000 workers also populate downtown every day, working in industries such as education, finance, manufacturing, health care, government, and retail.
  2. Greater Wichita partnership. Living & Working. “With a highly trained pool of talent and a deeply rooted entrepreneurial spirit, Downtown Wichita is work central, boasting 26,000 daytime workers in the financial, healthcare, education, oil & gas and creative services industries.” Available at http://greaterwichitapartnership.org/living_working/downtown_wichita.
  3. Wichita Downtown Development Corporation. Wichita — Center of Progress. Available at http://www.downtownwichita.org/brochure/files/inc/792168633.pdf.
  4. Wichita Downtown Development Corporation. State of Downtown Report 2016. This document states over 25,000 workers. Available at http://downtownwichita.org/user/file/2016_State_of_Downtown_Report_2.pdf.
  5. City of Wichita. Multi-Modal Transportation Connections for Wichita State Innovation Campus. 2016 TIGER Grant Application. Available at http://www.wichita.gov/Government/Departments/Planning/TIGER%20Grant%20Documents/2016%20TIGER%20Grant%20Application.pdf.
  6. Ryan, Kelsey. 9 things happening with Wichita downtown development. Wichita Eagle. June 01, 2015. Available at http://www.kansas.com/news/business/real-estate-news/article22844223.html.
  7. Stearns, John. Downtown’s office exodus — Nearly 1,000 are leaving, so why aren’t downtown developers having a heart attack? Wichita Business Journal. October 4, 2013. Available at http://www.bizjournals.com/wichita/print-edition/2013/10/04/downtowns-office-exodus.html.
  8. U.S. Census Bureau. OnTheMap application. Available at https://onthemap.ces.census.gov/.
  9. “For LODES, a place of work is defined by the physical or mailing address reported by employers in the QCEW (formerly ES-202) or Multiple Worksite Reports. An address from administrative data may or may not be the actual location that a worker reports to most often. The distinction of worksite and administrative address may be especially significant in some industries such as construction, where work is often carried out at temporary locations. In some cases, employers do not provide a multiple worksite report when it would be appropriate to do so. Nonreporting of multiple worksites is especially common with state and local governments and school districts. In such a case, LEHD infrastructure files assign all workers for that employer (within the state) to the main address provided. Bureau of Labor Statistics (BLS) data show a national noncompliance rate of 5.61 percent of multiunit employers responsible for about 4.45 percent of multiunit employment.” Matthew R. Graham, Mark J. Kutzbach, and Brian McKenzie. Design comparison of LODES and ACS commuting data products. Available at ftp://ftp2.census.gov/ces/wp/2014/CES-WP-14-38.pdf.
  10. Weeks, Bob. Downtown Wichita business trends. Available at https://wichitaliberty.org/wichita-government/downtown-wichita-business-trends/.
  11. Weeks, Bob. Some Goody Clancy Wichita findings not credible. Available at https://wichitaliberty.org/wichita-government/some-goody-clancy-wichita-findings-not-credible/.

Rich States, Poor States, 2107 edition

In Rich States, Poor States, Kansas improves its middle-of-the-pack performance, but continues with a mediocre forward-looking forecast.

In the 2017 edition of Rich States, Poor States, Utah continues its streak at the top of Economic Outlook Ranking, meaning that the state is poised for growth and prosperity. Kansas continues with middle-of-the-pack performance rankings, and after falling sharply in the forward-looking forecast, continues at the same level.

Rich States, Poor States is produced by American Legislative Exchange Council. The authors are economist Dr. Arthur B. Laffer, Stephen Moore, who is Distinguished Visiting Fellow, Project for Economic Growth at The Heritage Foundation, and Jonathan Williams, who is vice president for the Center for State Fiscal Reform at ALEC.

In addition to the printed and pdf versions of Rich States, Poor States there is now an interactive web site at www.richstatespoorstates.org.

Rich States, Poor States computes two measures for each state. The first is the Economic Performance Ranking, described as “a backward-looking measure based on a state’s performance on three important variables: State Gross Domestic Product, Absolute Domestic Migration, and Non-Farm Payroll Employment — all of which are highly influenced by state policy.” The process looks at the past ten years.

Looking forward, there is the Economic Outlook Ranking, “a forecast based on a state’s current standing in 15 state policy variables. Each of these factors is influenced directly by state lawmakers through the legislative process. Generally speaking, states that spend less — especially on income transfer programs, and states that tax less — particularly on productive activities such as working or investing — experience higher growth rates than states that tax and spend more.”

Economic outlook ranking for Kansas and nearby states. Click for larger.
For economic performance (the backward-looking measure), Kansas ranks twentieth. That’s up from twenty-seventh last year.

In this year’s compilation for economic outlook, Kansas ranks twenty-sixth, up one position from the previous year, but down from eighteenth and fifteenth the years before. In 2008, the first year for this measure, Kansas was twenty-ninth.

Kansas compared to other states

A nearby chart shows the Economic Outlook Ranking for Kansas and some nearby states, shown as a trend over time since 2008. The peak of Kansas in 2013 is evident, as is the decline since then.

Why Kansas fell

Kansas fell in the Economic Outlook Ranking from 2013 to 2016 and moved by just one position in 2017. To investigate why, I gathered data for Kansas from 2008 to 2017. The nearby table shows the results for 2017 and the rank among the states, with the trend since 2008 shown. A rank of one is the best ranking. For the trend lines, an upward slope means a decline in ranking, meaning the state is performing worse.

There are several areas that account for the difference.

The most notable change is in the measure “Recently Legislated Tax Changes (per $1,000 of personal income)” Kansas fell four positions in rank. By this measure, Kansas added $2.66 in taxes per $1,000 of personal income, which ranked forty-sixth among the states. This is a large change in a negative direction, as Kansas had ranked seventh two years before.

For the state liability system, Kansas ranks nineteenth, when it was fifth two years ago.

Kansas remains one of the states with the most public employees, with 669.8 full-time equivalent employees per 10,000 population. This ranks forty-eighth among the states.

Kansas has no tax and spending limits, which is a disadvantage compared to other states. These limitations could be in the form of an expenditure limit, laws requiring voter approval of tax increases, or supermajority requirements in the legislature to pass tax increases.

How valuable is the ranking?

Correlation of ALEC-Laffer state policy ranks and state economic performance
Correlation of ALEC-Laffer state policy ranks and state economic performance
After the 2012 rankings were computed, ALEC looked retrospectively at rankings compared to actual performance. The nearby chart shows the correlation of ALEC-Laffer state policy ranks and state economic performance. In its discussion, ALEC concluded:

There is a distinctly positive relationship between the Rich States, Poor States’ economic outlook rankings and current and subsequent state economic health.

The formal correlation is not perfect (i.e., it is not equal to 100 percent) because there are other factors that affect a state’s economic prospects. All economists would concede this obvious point. However, the ALEC-Laffer rankings alone have a 25 to 40 percent correlation with state performance rankings. This is a very high percentage for a single variable considering the multiplicity of idiosyncratic factors that affect growth in each state — resource endowments, access to transportation, ports and other marketplaces, etc.

Rich States, Poor States compilation for Kansas. Click for larger version.

Wichita metro employment by industry

An interactive visualization of Wichita-area employment and jobs 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 asking about jobs.1

The four tabs along the top of the visualization hold different views of the data; one table and three charts. Employment figures are in thousands. All series except one are not seasonally adjusted.

Click here to access the visualization. The visualization was created by myself using Tableau Public.

Example from the visualization. Click for larger.


Notes

  1. Bureau of Labor Statistics. Current Employment Statistics data and their contributions as key economic indicators. www.bls.gov/opub/mlr/2016/article/current-employment-statistics-data-and-their-contributions-as-key-economic-indicators.htm.

Tax collections by the states

An interactive visualization of tax collections by state governments.

Each year the United States Census Bureau collects data from the states regarding tax collections in various categories. I present this data in an interactive visualization.

The values are for tax collections by the state only, not local governmental entities like cities, counties, townships, improvement districts, cemetery districts, library districts, drainage districts, watershed districts, and school districts.

Of particular interest is the “State Total” tab. Here you can select a number of states and compare their tax burdens. (Probably three or four states at a time is the practical limit.) This data is presented on a per-person basis.

The example shown below compares Kansas and Colorado. Many might be surprised to know that tax collections in Kansas are higher than in Colorado, on a per-person basis.

Data is as collected from the United States Census Bureau, Annual Survey of State Government Tax Collections, and not adjusted for inflation. Visualization created using Tableau Public. Click here to access the visualization.

An example from the visualization, comparing Colorado and Kansas state tax collections per capita. Click for larger.

Tax rates and taxes paid

Is there a relationship between marginal tax rates and tax dollars collected?

The top marginal tax rate — that’s the rate that applies to high income earners on most of their income — was above 90 percent during most of the 1950s. From 2003 to 2012 it was 35 percent, and is now 39.6 percent. Some see that as a lost opportunity. If we could return to the tax rates of the 1950s, they say, we could generate much more revenue for government.

The top marginal tax rate is the rate that applies to income. It’s not the same as what is actually paid. This fact is unknown or ignored by those who clamor for higher taxes on the rich.

Top marginal tax rates and tax paid. Click for larger.
A nearby charts illustrates the lack of relationship between the top marginal income tax rate and the income taxes actually paid. (Click chart for larger version.)

The top marginal tax rate has varied widely. But since World War II, the taxes actually collected, expressed as a percentage of gross domestic product, has been fairly constant. In 1952 the top tax rate was 92.0 percent, and income taxes paid as a percent of GDP was 18.5 percent. In 2007, for example, the top rate was 35.0 percent, and income taxes paid as a percent of GDP was 17.9 percent.

Try as we might, raising tax rates won’t generate higher revenues (as a percentage of gross domestic product), due to Hauser’s law.

W. Kurt Hauser explains in The Wall Street Journal: “Even amoebas learn by trial and error, but some economists and politicians do not. The Obama administration’s budget projections claim that raising taxes on the top 2% of taxpayers, those individuals earning more than $200,000 and couples earning $250,000 or more, will increase revenues to the U.S. Treasury. The empirical evidence suggests otherwise. None of the personal income tax or capital gains tax increases enacted in the post-World War II period has raised the projected tax revenues. Over the past six decades, tax revenues as a percentage of GDP have averaged just under 19% regardless of the top marginal personal income tax rate. The top marginal rate has been as high as 92% (1952-53) and as low as 28% (1988-90). This observation was first reported in an op-ed I wrote for this newspaper in March 1993. A wit later dubbed this ‘Hauser’s Law.'”

For many people, there is a direct relationship between tax rates and the amount of tax paid. For workers who earn a paycheck, there’s not much they can do to change the timing of their income, find tax shelters, or shift income to capital gains. When income tax rates rise, they have to pay more.

But people with high incomes can use these and other strategies to reduce the taxes they pay. In fact, there is an entire industry of accountants and lawyers to help people reduce their tax. Often — particularly in the past when top marginal rates were very high — investments and transactions were made solely for the purpose of avoiding taxes, not for productive economic benefit.

People react to changes in tax law. As tax rates rise, people seek to reduce their taxable income, and make investments in unproductive tax shelters. There is less incentive to work and invest. These are some of the reasons why tax hikes usually don’t generate the promised revenue.

But: High tax rates make the middle class feel better about paying their own taxes. With top tax rates of 90 percent, they may believe that the rich are paying a lot of tax. The middle class may take comfort in the fact that someone else is worse off. But that is based on the misconception that high tax rates mean rich people actually pay correspondingly higher tax.

Data is from The Tax Policy Center (TPC), a joint venture of the Urban Institute and Brookings Institution.

Personal income in the states

An interactive visualization of income growth and change in the states, by major sector.

The Bureau of Economic Analysis, an agency of the United States Department of Commerce, collects and analyses data regarding the U.S. and world economies. One series is personal income, defined by BEA as “Personal income is the income received by, or on behalf of, all persons from all sources: from participation as laborers in production, from owning a home or business, from the ownership of financial assets, and from government and business in the form of transfers. It includes income from domestic sources as well as the rest of world. It does not include realized or unrealized capital gains or losses.”1

An example from the visualization. Click for larger.
Data is available for farm and non-farm income. I’ve gathered this data from BEA and present it in an
interactive visualization. This is a series named SA4. Data is subdivided farm or non-farm, and also by state and regions. There are three views of data. Some work best with just two or three states, while others can show many states. You may choose a range of dates (this data is annual through 2016). Also, select one or more states or regions. Click on the legend to highlight one or more series. Trends over time are shown as percentage change from the first year so that comparisons may be made.

Of note is the steep decline in farm income in Kansas and other Plains states.

Click here to use the visualization.


Notes

  1. Bureau of Economic Analysis. State Personal Income, 2016. https://www.bea.gov/newsreleases/regional/spi/sqpi_newsrelease.htm.

WichitaLiberty.TV: The regulatory and administrative state

In this episode of WichitaLiberty.TV. Fred L. Smith, Jr. is the founder of the Competitive Enterprise Institute. He explains the problems with excessive regulation and a large administrative state. Episode 145, broadcast April 2, 2017. View below, or click here to view at YouTube.

Shownotes

Economic indicators for the states

An index of past economic activity for each state, and another index looking forward. Presented in an interactive visualization.

The Federal Reserve Bank of Philadelphia calculates two indexes that track and forecast economic activity in the states and the country as a whole.

The coincident index is a measure of current and past economic activity for each state.1 This index includes four indicators: nonfarm payroll employment, the unemployment rate, average hours worked in manufacturing, and wages and salaries (adjusted for inflation). July 1992 is given the value 100.

The leading index anticipates the six-month growth rate of the state’s coincident index.2 In addition to the coincident index, “the models include other variables that lead the economy: state-level housing permits (1 to 4 units), state initial unemployment insurance claims, delivery times from the Institute for Supply Management (ISM) manufacturing survey, and the interest rate spread between the 10-year Treasury bond and the 3-month Treasury bill.”

Positive values mean the coincident index is expected to rise in the future six months, while negative values mean it is expected to fall.

I’ve created an interactive visualization of these two indexes. An example appears nearby. Click here to open the visualization in a new window. You may select a range of dates and one or more states to include on the chart. Click on a state’s legend color to spotlight it against other states.

Example from the visualization. Click for larger.


Notes

  1. Federal Reserve Bank of Philadelphia. State Coincident Indexes. https://www.philadelphiafed.org/research-and-data/regional-economy/indexes/coincident/.
  2. Federal Reserve Bank of Philadelphia. State Leading Indexes. https://www.philadelphiafed.org/research-and-data/regional-economy/indexes/leading/.

Kansas revenue estimates

Kansas revenue estimates are frequently in the news and have become a political issue. Here’s a look at them over the past decades.

A favorite criticism of liberals and progressives across the nation is that in Kansas, actual revenues to the state’s general fund have fallen short of projections, month after month. Reading most newspaper reports and editorials, one might think that these negative variances are a new phenomenon, and one relished by the Left. As many as a dozen articles on this topic have appeared in the New York Times in the past two years.

The revenue estimates in Kansas are produced by a body known as the Consensus Revenue Estimating Group. It consists of one member each from the Division of the Budget, Department of Revenue, Legislative Research Department, and one consulting economist each from the University of Kansas, Kansas State University, and Wichita State University.

As described: “This group meets each spring and fall. Before December 4th, the group makes its initial estimate for the budget year and revises the estimate for the current year. By April 20th, the fall estimate is reviewed, along with any additional data. A revised estimate is published, which the Legislature may use in adjusting expenditures, if necessary.”1

The estimates are important because the legislature and governor are required to use them when formulating budgets and spending plans. If the estimates are high, meaning that revenue is less than expected, it’s possible that the legislature or (more likely) the governor will need to make spending cuts. (The other alternative is that leftover funds from prior years may be used, if available.)

If, on the other hand, the estimates are too low, meaning that revenue is higher than expected, the state has collected too much tax revenue. In this case, the state should refund the excess to taxpayers. Some states do that, notably Colorado, although residents may vote to let the state keep the excess.

Some states have true rainy day funds, and the excess revenue might be used to build that fund’s balance. In a true rainy day fund, the fund’s balances can be spent only during specific sets of circumstances.

But in Kansas, the excess revenue is simply called the “ending balance” and is available to spend at the legislature’s whim. That’s what happened in fiscal years 2014 and 2015, when the state spent $340 million and $308 million, respectively, of the ending balance rather than cut spending.

What has been the history of the revenue estimates compared to actual revenue? First, know that making these estimates is not easy. Some of the inputs to the process include the inflation rate in future years, interest rates in future years, and the prices of oil and natural gas in the future. If someone knew these values with any certainty, they could earn huge profits by trading in futures markets.

The state makes the revenue estimates available.2 I’ve presented the results since 1975 in a chart at the end of this article. For each year, two numbers are presented. One it the difference from the Original Estimate and actual revenue. The other is the difference from the Adjusted Final Estimate and actual revenue.

We can see that in fiscal years 2014 and 2016, the variance of the estimates is negative, meaning that revenue was lower than the estimates. The magnitude of these variances, however, is not out of line with the magnitude of the variances of other years, either positive or negative.

In fact, the negative variances — revenue shortfalls, in other words — in the periods 2002 to 2003 and 2009 to 2010 were generally much larger in magnitude than those of recent years. This is of interest as Duane Goossen, who was the budget director during these periods, is a prominent critic of the recent revenue shortfalls. Evidently, he has forgotten the difficulty of creating these estimates.

While Goossen along with newspaper reporters and editorialists use the negative revenue estimate variances as a political weapon against the governor and conservatives, it is in the interest of the people of Kansas that revenue estimates be as accurate as possible. In an effort to produce more accurate revenue estimates, Governor Brownback created a commission to study the issue. That group released its report in October.3

Kansas revenue estimate errors. Click for larger.


Notes

  1. Consensus Revenue Estimating Group. Available at budget.ks.gov/cre.htm.
  2. Kansas Division of the Budget. State General Fund Receipt Revisions for FY 2016 and FY 2017. May 2, 2016. Available at: budget.ks.gov/files/FY2017/CRE_Long_Memo_April2016.pdf. Also Kansas Legislative Research for 2016 figures.
  3. Governor’s Consensus Revenue Estimating Working Group. Final Recommendations. Available at budget.ks.gov/files/FY2017/cre_workgroup_report.pdf.

Kansas manufacturing and oil not recovering

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.)

You can access the visualization and create your own examples through the article Kansas employment by industry.


Notes

  1. Bureau of Labor Statistics. Current Employment Statistics data and their contributions as key economic indicators. www.bls.gov/opub/mlr/2016/article/current-employment-statistics-data-and-their-contributions-as-key-economic-indicators.htm.

Kansas employment by industry

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.


Notes

  1. Bureau of Labor statistics. About BLS. https://www.bls.gov/bls/infohome.htm.
  2. Bureau of Labor Statistics. Current Employment Statistics data and their contributions as key economic indicators. www.bls.gov/opub/mlr/2016/article/current-employment-statistics-data-and-their-contributions-as-key-economic-indicators.htm.

Spending in the states, by fund

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.

Wichita metro employment by industry

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.

Click here to access the visualization.

Example from the visualization. Click for larger.


Notes

GDP by state and industry

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.

Click here to open the visualization.

Example from the visualization. Click for larger.