Category: Economics

  • Personal income in the states

    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.
  • Economic indicators for the states

    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 use the visualization. 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/.
  • State and local government employee and payroll

    State and local government employee and payroll

    Considering all state and local government employees in proportion to population, Kansas has many, compared to other states, and especially so in education.

    When considering all state and local government employees, Kansas spent $254 per person on payroll (March only).1 This was 15th highest among the states, District of Columbia, and the nation as a whole. There were 14.9 citizens for each FTE (full-time equivalent employee), which ranks fourth highest.

    Example from the visualization. Click for larger.
    In other words, Kansas has many government employees compared to other states, and these employees are costly, again compared to other states. This is data from the U.S. Census Bureau for 2015, the most recent year for which data is available.

    When considering all elementary and secondary education employees, Kansas spent $95 per person on payroll (again, March only). This was 12th highest among the states, District of Columbia, and the nation as a whole. There were 34.3 citizens for each FTE (full-time equivalent employee) working in elementary and secondary education, which ranks third highest.

    In other words, Kansas has many elementary and secondary education employees compared to other states, and these employees are costly, again compared to other states.

    Similar results are found for higher education employees. Fortunately, Kansas has zero employees working in state-owned liquor stores.

    In the visualization you may create your own tables. Click here to access the visualization. Source of data is U.S. Census Bureau2 and author’s calculations to derive per-capita figures. Visualization created using Tableau Public.


    Notes

    1. For total payroll (both full-time and part-time employees), the Census Bureau reports a value for a single month, that being March.
    2. U.S. Census Bureau. 2015 Annual Survey of Public Employment and Payroll. www.census.gov/govs/apes/.
  • Spending in the states, by fund

    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

    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

    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.
  • Employment by MSA and industry

    Employment by MSA and industry

    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.


    Notes

    1. Bureau of Economic Analysis. Regional Economic Accounts. https://www.bea.gov/regional/.
    2. 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.
  • Obama’s stimulus, in retrospect

    Obama’s stimulus, in retrospect

    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.


    Notes

    1. Romer, Christine, and Bernstein, Jared. The Job Impact of the American Recovery and Reinvestment plan. https://www.economy.com/mark-zandi/documents/The_Job_Impact_of_the_American_Recovery_and_Reinvestment_Plan.pdf.
    2. 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
    3. For criticims of Keynesian economics from free market perspectives, see
      Mitchell, Daniel J. Keynes Was Wrong on Stimulus, but the Keynesians Are Wrong on Just about Everything. https://www.cato.org/blog/keynes-was-wrong-stimulus-keynesians-are-wrong-just-about-everything.
      Gerald P. O’Driscoll Jr. Keynes vs. Hayek: The Great Debate Continues. https://www.cato.org/publications/commentary/keynes-vs-hayek-great-debate-continues.
      Richard B. McKenzie. John Maynard Keynes, R.I.P. https://fee.org/articles/john-maynard-keynes-rip/.
      Hans-Hermann Hoppe. The Misesian Case against Keynes. https://mises.org/library/misesian-case-against-keynes.
  • Economic development incentives at the margin

    Economic development incentives at the margin

    The evaluation of economic development incentives in Wichita and Kansas requires thinking at the margin, not the entirety.

    When considering the effect of economic development incentives, cities like Wichita use a benefit-cost analysis to determine whether the incentive is in the best interests of the city. The analysis usually also considers the county, state, and school districts (although these jurisdictions have no say over whether the incentive is granted, with a few exceptions). The idea is that by paying money now or forgiving future taxes, the city gains even more in increased tax collections. This is then pitched as a good deal for taxpayers: The city gets more jobs (usually) and a “profit,” too.

    Economic activity usually generates tax revenue that flows to governmental agencies. When people work, they pay income taxes. When they make purchases, they pay sales taxes. When they buy existing property or create new property, they pay property taxes. This happens whether or not the economic activity is a result of government incentives. This is a key point that deserves more exploration.

    Government often claims that without an incentive provided by government, a company would not have located in Wichita. Or, without the incentive, it would not have expanded in Wichita. Now, the city says incentives are necessary to persuade companies to consider remaining in Wichita rather than moving somewhere else.1

    But there are a few problems with the arguments that cities, states, and their economic development agencies promote. One is that the increase in tax revenue happens regardless of whether the company has received incentives. Therefore, the benefit-cost ratio calculations are valid only if incentives were absolutely necessary. Otherwise, government claims credit for something that was going to happen anyway. This is a big question that deserves exploration.

    For example, what about all the companies that locate to Wichita, or expand in Wichita, or simply remain in Wichita without receiving incentives? How do we calculate the benefit-cost ratio when a company receives no incentives? The answer is it can’t be calculated, as there is no government cost, so the divisor in the equation is zero. Instead, there is only benefit.

    Then, we don’t often ask why some companies need incentives, and others do not. Do the companies that receive incentives really need them? Is it really true that a business investment is not feasible without subsidy? Why do some companies receive incentives multiple times while others thrive without incentives?

    We may never know

    We may never know the answer to these questions. Here’s why. Suppose fictional company XYZ Enterprises, Inc. dangles the idea of moving from Wichita to some other city. XYZ cites incentive packages offered by other cities. Wichita and the state then come up with millions in incentives, and XYZ decides to remain in Wichita. Question: Were the incentives necessary? Was the threat to move genuine? If XYZ admits the threat was not real, then it has falsely held Wichita and Kansas hostage for incentives. If the city or state admits the threat was not real, then citizens wonder why government gave away so much.2

    So we’ll never really know. Everyone involved has incentive to maintain the fiction and avoid letting the truth leak out.

    A small lever moves big boulders, they say

    Related is that jurisdictions may grant relatively small incentives and then take credit for the entire deal. I’ve been told that when economic development agencies learn of a company moving to an area or expanding their Wichita operations, they swoop in with small incentives and take credit for the entire deal. The agency is then able to point to a small incentive and take credit for the entire deal. As you can imagine, it’s difficult to get the involved parties to speak on the record about this.

    Further, governments may not credit the contribution of other governments. In the past when the Wichita economic development office presented information about an incentive it proposed to offer to a company, it would sometimes list the incentives the company is receiving from other governments. As an example, when the city offered incentives to NetApp in 2012, the city’s contribution was given as a maximum of $418,000. The agenda material mentioned — obliquely — that the State of Kansas was involved in the incentive package. Inquiry to the Kansas Department of Commerce revealed that the state had promoted incentives worth $35,160,017 to NetApp.3 Wichita’s incentive contribution is just 1.2 percent of what the state offered, which makes us wonder if the Wichita incentive was truly needed. Nonetheless, Wichita city officials spoke as though the city alone was responsible for NetApp’s decision.

    The importance of marginal thinking

    When evaluating economic development incentives, we often fail to properly evaluate the marginal gains. Here’s an example of the importance of looking at marginal gains rather than the whole. In 2012, the City of Wichita developed a program called New HOME (New Home Ownership Made Easy). The crux of the program is to rebate Wichita city property taxes for five years to those who buy newly-built homes in certain neighborhoods under certain conditions.

    Wichita City HallThe important question is how much new activity this program will induce. Often government takes credit for all economic activity that takes place. This ignores the economic activity that was going to take place naturally — in this case, new homes that are going to be built even without this subsidy program. According to data compiled by Wichita Area Builders Association and the WSU Center for Economic Development and Business Research — this is the data that was current at the time the Wichita city council made its decision to authorize the program — in 2011 462 new homes were started in the City of Wichita. The HOME program contemplated subsidizing 1,000 homes in a period of 22 months. That’s a rate of 545 homes per year — not much more than the present rate of 462 per year. But, the city has to give up collecting property tax on all these homes — even the ones that would be built anyway.

    What we’re talking about is possibly inducing a small amount of additional activity over what would happen naturally and organically. But we have to subsidize a very large number of houses in order to achieve that. The lesson is that we need to evaluate the costs of this program based on the marginal activity it may induce, not all activity.

    For more, see Wichita new home tax rebate program: The analysis.


    Notes

    1. “But the Hawker Beechcraft deal is different, focused on saving existing jobs, not creating new jobs, and the result diverts millions in limited taxpayer funds, primarily state income tax revenues, from state coffers to a company’s benefit, simply to have an existing business stay put.” Flentje, Edward. Brinkmanship with jobs. https://wichitaliberty.org/economics/brinkmanship-with-jobs/.
    2. For more on this, see LeRoy, Greg. The Great American Jobs Scam. Especially chapter two, titled Site Location 101: How Companies Decide Where to Expand or Relocate. The entire book may be read online at http://www.greatamericanjobsscam.com/pages/preview-book.html. A relevant excerpt: “These prisoners’ dilemma games also enable companies to create fictions about cause and effect. These fictions can be used to create public versions of how deals happened that no one can credibly contradict, because the company’s real decision-making process will never be revealed. The most important fiction to maintain, of course, is that subsidies matter in deciding where a company expands or relocates. For example, being able to send secret signals to competing cities means companies can tell contradictory stories to different cities and have no fear of being exposed. If a company really has its heart set on City A, it can tell that city that it is in the hunt, but needs to do better. Meanwhile, it can send less urgent signals to Cities B and C, even if they offered bigger packages at first. Eventually, City A offers the biggest package, and the company announces its decision to go there.”
    3. Weeks, Bob. NetApp economic development incentives: all of them. https://wichitaliberty.org/wichita-government/netapp-economic-development-incentives-all-of-them/.