Skip to Content
  Contact Us

Notes from Regional Strategic, Ltd.

Tag: Market Analysis

Data Disappearance and You

Posted on March 6, 2025 - 4:48 pm by

On February 6, 2025, I posted a note on the closure of the United States Agency for International Development (USAID). Regional Strategic, Ltd. turned down a contract to analyze the economic impact of that closure on an area of the Upper Midwest, because, in concert with the closure, the administration foreclosed access to data documenting USAID’s purchases and expenditures. The government actively denied the public the ability to evaluate government actions.

That denied my company the ability to conduct meaningful analysis for an industry group that needed to make immediate plans. That, in turn, foreclosed the generation of business incomes (and the residual personal incomes) on both sides of the potential transaction.

The note indicated that this was not the only case of data access restrictions occurring under the new administration in Washington, D.C. At that point, two weeks into the administration, data on healthcare, weather, and climate change that undercut the administration’s political positions had already been removed from public access. The note detailed some of the commercial problems these data restrictions would cause.

Yesterday, the administration moved again to restrict and/or alter major data streams available from the federal government. This time it was the Department of Commerce (USDOC). The USDOC is one of the major sources of data in the federal government. Data agencies within the USDOC include

  • The Census Bureau (Census) – which collects data on population, demographics, housing, employment, income, commercial activity, and international trade. These data streams are used to allocate congressional and state legislative seats, benchmark the National Income and Product Accounts (NIPA), manage and evaluate congressionally mandated programs, and determine the need for and effects of tariffs and trade restrictions.
  • The Bureau of Economic Analysis (BEA) – which is the national accountant. The BEA consolidates and analyzes data from the Census, the Bureau of Labor Statistics, the Department of Agriculture, and the Treasury to provide the consistent production, employment, income, and consumption data to generate the NIPA, which, in turn, is the source of national income and gross domestic product statistics.
  • The International Trade Administration (ITA) – which collects data on our international trade and the trade positions of our trading partners.

Sounds like pretty dry stuff, but this data underpins nearly every

  • Piece of market research
  • Investment decision
  • Community economic development plan
  • Interest rate
  • Bond issue
  • Congressional revenue and expenditure enactment

made in the United States.

On a personal level, this data underpins a complex integrated financial system that supports your auto loans, mortgages, and credit card transactions – all of which will get significantly more expensive as the quality and consistency of these data streams deteriorates.

The accuracy and consistency of these data streams is critical to business decisions, government action, and personal income.

On Sunday, March 2, 2025, Howard Lutnick, Secretary of Commerce, announced his intention to strip government activities from gross domestic product data. On Tuesday, March 4, 2025, he announced the disbanding of two important advisory boards:

  • The Federal Economic Statistics Advisory Committee
  • The Bureau of Economic Analysis Advisory Committee

These committees are made up primarily of professional and academic statisticians that advise the USDOC on proper data handling and increasing the quality and precision of the data and estimates the government produces and disseminates. To be effective, however, committee members need to be made aware of changes being made and how those changes are being accomplished.

Over the past five days, the federal government has, in quick succession,

  • Announced its intentions to make one of the most radical changes to federal data systems in modern memory
  • Dismissed the very experts it would need in order to accurately and successfully accomplish these changes.  

While much of the general public is not aware of these data streams on a daily basis, interrupting them is a major affair that will directly and significantly affect their livelihoods if not done correctly. It will be infinitely more disastrous if these disruptions are done politically.

This is a big deal that should command more attention than it is getting.

Post script

The list below is of posts I have made over the past 15 months that would not have been possible or accurate without the consistency of the data streams put at risk over the past five days. These are just short musings I have put up as examples of what can be done.

They do not include the extensive market reports I have generated for Midwest businesses and industry groups, economic impact studies I have done for the likes of John Deere, Des Moines University, the Iowa Off-Highway Vehicle Association, the National Balloon Classic, and others, or the policy analyses I have done for agricultural commodity groups. None of these efforts would have been possible without consistent quality data streams on the economy.

Beyond this, most people don’t spend their lives with there noses in the data. Most who do perform internal statistical analysis and do not work with the economic and social environments that underpin economic and policy analyses. Removing or corrupting the data streams discussed above will eliminate the jobs of hundreds of thousands of folks like me that connect the data to markets, the economy, development initiatives, and social and recreational initiatives.

Here are the posts:

Demographic Analysis of Votes Cast

Posted on January 30, 2025 - 9:36 pm by

We have recently been engaged in some demographic analysis of voter data here at Regional Strategic, Ltd. While a lot of news is made with exit polls on election day, those polls are seldom representative of the population as a whole. News organizations position pollsters at select stations, but they don’t have the resources to cover the gamut of socio-economic areas represented by precincts nationwide. They rely on sampling frames (see our November 24, 2024 blog at www. regionalstrategic.com/wp/the-moveable-middle-statistics-information-progress/ for some thoughts on sampling frames) which rely on expert insights that may have as much to do with news value as with statistical coverage.

After the fact, substantial voter analysis can be done with official statistics. Regional Strategic, Ltd. is supporting some analysis in Iowa utilizing data from the Iowa Secretary of State’s office:

  • The January 6, 2025 release of the Iowa Voter Registration Database. This includes all Iowa voter registrations on January 6 and information on their voting history. January 6 is the first release that includes 2024 general election information for all current registrants.
  • The Official Canvass by County, which includes vote totals, undervotes, and overvotes for every state and federal office contested in the election on a county level.
  • Precinct Results by County, which brings vote counts down to a precinct level.

The Iowa Voter Registration Database is the largest of these. It comes in at more than 2.2 million records with 132 fields. It offers information on voter age, sex, location (address, county, precinct) and voting history. It comes in multiple files for each of four congressional districts.

The first step is to combine files by district. The entire state is too big to conveniently handle in Excel. The 3rd Congressional District was consolidated and cleaned up. There are always some broken and/or incomplete files. This isn’t due to malfeasance or incompetence. In a world where taxpayers insist on paring government functions to the bone, there simply is not enough help to adequately process the masses of data and sources of data that must be reconciled. This scarcity of resources is also evident in the period of two months that is necessary to release files after an election.

The 2025 registration file is an improvement over recent periods. Only 10 damaged records were encountered in the 569,000 records for the 3rd Congressional District. These were all successfully reconciled into 4 complete records. As a result, the 3rd Congressional District file for analysis contained 568,994 registration records. The fields were checked to make certain all general 2024 election results were in the proper field (this year they were – another improvement). At this point, we had a data file for analysis.

Original fields allow data to be separated by county and precinct. These generate fields for national and statewide offices, and local election districts. Age, sex, and political affiliation (if any) are also recorded. In areas where political parties organize on the basis of neighborhood groups, a field can be inserted to identify these if they are defined in terms of groups of precincts.

The graph below shows the number of registered voters and the number of votes cast by sex and party as percentages of total registrations and votes for Iowa’s 3rd Congressional District.

Similar representations can be made by age group, sex by age group, or age group by sex. Any of these can be done statewide or by

  • Congressional district
  • Any state legislative district
  • County
  • Precinct
  • Any other jurisdiction that can be created with these groups

The graph below represents the same data splits as the graph above. This time, however, the area is Polk County. Polk is by far the most populous of the 21 counties that make up Iowa’s 3rd Congressional District. It accounts for approximately 61 percent of registered voters in the district and approximately 61 percent of district votes cast in the 2024 general election.

In both Polk County and the 3rd Congressional District, Democrats are dependent upon female voters and Republicans are dependent upon male voters. Both of these groups are significantly more likely to vote than any other groups depicted in the graphs.

Also apparent is the size of the independent group. In the 3rd Congressional District, Independents are the largest registered voter block. In Polk County, they are the second largest block. Independents do not turn out at the same rates as Republicans and Democrats, but the potential size of the block means it has significant impacts on elections.

We can take the voter results derived from the Iowa Voter Registration Database and blend them with candidate results from the Official Canvass by County and Precinct Results by County to get a pretty good estimate of the number of Independents who voted for candidates of either party. Without accounting for undervotes (registrants that voted in the election but did not vote in this contest) or overvotes (registrants that voted for too many candidates in this contest and, thus, had their votes voided), we can roughly estimate that 47.5% of voting Independents voted for the Democratic candidate for congress and 44.4% voted for the Republican candidate in the race for Iowa’s 3rd Congressional District seat. In Polk County, 51.2% voted for the Democratic candidate and 41.8% voted for the Republican candidate in the race. In neither area do the totals sum to 100%. Accounting for overvotes and undervotes (which could be done with available data) would push up all of these percentages. It is also nearly certain that some Independents (as well as some Republicans and Democrats) placed write-in votes for unlisted candidates.

This work is ongoing as inquiries for election analysis come in. Regional Strategic, Ltd. has the data in-house to work on 2024 general election results for Iowa. Data for other states can be obtained. Analysis is possible by age, sex, political affiliation and region to the extent that any individual state’s database will support.

Stick to the Voodoo You Do

Posted on January 3, 2025 - 3:56 pm by

We all get our best results if we stick to things we are good at and interested in, but every enterprise involves a lot of tasks that don’t fit into any team member’s, “Voodoo set.”

Many economic development staff, business entrepreneurs, and community advocates are vision people. They must be to keep teams of volunteers, employees, and stakeholders together, focused on the goal, and moving forward.

It takes a lot of marketing, a good bit of dreaming, and a whole bunch of optimism.

That doesn’t leave a lot of time for analysis – whether that is the quantitative analysis of hard data or the qualitative analysis of personal feedback, surveys, and community discussions.

A lot of this very important stuff gets done at the frustration level. That is a recipe for lost opportunities.

Regional Strategic, Ltd. specializes in the analysis of data and community input. We can help you build a solid foundation under your vision. We are data experts. We are stakeholder input experts.

THAT IS THE VOODOO WE DO.

Texas Household Income Distribution

Posted on December 16, 2024 - 9:04 pm by

We are doing some market analysis in Texas and surrounding states. One of the issues is to identify populations that might be potential purchasers of a particular offering. That is at least partially a function of income.

The graph below shows estimates of real per capita income trends within Texas household income quintiles.

To get this, we started with state income distributions from the U.S. Bureau of Economic Analysis (BEA) at https://www.bea.gov/data/special-topics/distribution-of-personal-income. This provided nominal incomes by household income quintiles for

  • Total personal income
  • Net earnings by place of residence
  • Proprietors’ income
  • Net compensation
  • Dividends and interest income
  • Rental income
  • Personal current transfer payments

For this graph, we didn’t work with any of the detailed categories. We stuck with total personal income.

Data came in a zip file with data for every state from 2012 to 2022. There were separate workbooks for every state. For every state there were separate worksheets for every year. Job one was to extract the data and combine all the years for Texas.

The downloaded data was not adjusted for inflation. We could easily see that some quintiles had seen income growth. With others, however, we could not immediately see if that was growth or if that was inflation. Step two was to download Consumer Price Index (CPI) data and adjust all of the years and quintile values to 2022-equivalent dollars. CPI data is available for download at https://www.bls.gov/cpi/data.htm. We used data for all urban consumers in the Southern region of the U.S. We used annual measurements that were not seasonally adjusted.

With inflation-adjusted data for quintiles of Texas households, we still could not see if individuals were gaining or losing ground. This is because every year the quintiles each give data for one-fifth of the households, but we have no idea of household or population growth.

We made a simple assumption that households averaged the same size across all five quintiles. That allowed us to take annual Texas population estimates divided by five as the number of people in each quintile. Dividing inflation-adjusted quintile incomes by population gave us the per capita income estimates shown in the graph. We utilized Texas population estimates from the BEA at https://www.bea.gov/data/by-place-states-territories, because data from the BEA is remarkably easy to locate, download, and use.

There are a few things about the data and the data manipulation that deserve note.

First, for every year the total income received by the top quintile was greater than the income received by the bottom four quintiles combined. This was not changed by any of the manipulations described above.

Second, the assumption that household sizes are the same across all quintiles was convenient and gave us the ability to normalize the data for population size but is probably not completely accurate. For any quintile where household sizes are larger than the overall average, the quintile’s per capita estimate would shift down. Conversely, for any quintile where households are smaller than the overall average, the quintile’s per capita estimate would shift up.

Our best guess is that the lower quintiles have larger households and that the higher quintiles have smaller households. This is consistent with the demographic arguments in the recent post, “The Coming Depopulation.” If so, the lines for the bottom quintiles would drop and the lines for the top quintiles would rise.

Third, the data estimates current realized income. That is pretty close to total income for the bottom quintiles. Households in the upper quintiles, however, are likely to have significant levels of unrealized unearned incomes in the form of appreciation or capital gains on investments. These streams are reported and show up in the data as they are realized. If they are realized in a constant steady stream over time, the data is probably an accurate reflection of reality. To the extent that unrealized income streams are growing over time, the data will underestimate them during any period.

This was an interesting exercise undertaken as part of a larger analysis of market potential in the Southern U.S. It is possible to replicate this for any state and to engage the data at a more specific level. While multistate regions can also be analyzed, they require additional manipulation because income ranges on household quintiles will be unique to every state. In all cases, a careful disclosure of assumptions made and the potential implications of those assumptions is required.

Interested in Learning More About Regional Strategic, Ltd.? Send Us a Message

Contact Us