Yesterday, Regional Strategic, Ltd. was asked to evaluate the effect shutting down the United States Agency for International Development (USAID) would have on demand for agricultural commodities in a specific area of the Midwest. We had to decline the project. After looking at available data, we found that, in shutting down the USAID website, the administration had denied citizens and the business community the ability to evaluate what had been lost and plan for the alternatives that remained.
The question is not trivial. It appears that USAID acquired approximately $1.8 billion in U.S. food products to support its activities in 2022. Every $100 million spent on food production and processing in the upper Midwest generates approximately
$100 to $120 million in value-added economic activity within the Midwest
$55 to $70 million in labor income
$30 to $65 million in corporate profits and tax revenue
1,000 jobs
Any of these estimates could be increased 18 times to accommodate the $1.8 billion demand loss from eliminating USAID. All of these totals would go up if the impact was evaluated across the entire United States.
Clearly, local regions that are heavily invested in commodity production and processing would like to evaluate what portion of existing demand is being taken off the table:
Every $100 million reduction in 2022 Iowa corn purchases in Iowa would have been equivalent to idling over 75,500 acres of 200-bushel corn
A similar reduction for wheat in Kansas would have been equivalent to idling over 310,000 acres of 37-bushel wheat
The sudden lack of data with which to evaluate these impacts on local areas is a business issue. It is a family welfare issue. It is an employment issue. It is a public policy issue.
This is not limited to the situation involving USAID. In the first two weeks of the present administration, data access has been restricted in the areas of health care, climate, and weather forecasting where those data run counter to the administration’s political inclinations. This is bad for business, and it is dangerous.
Health data is being restricted at a time when the United States is experiencing a growing bird flu epidemic, Africa is experiencing renewed Ebola outbreaks, and drug-resistant tuberculosis is becoming more prevalent worldwide. Any one of these situations could rapidly become an international health problem. Any one of these is a personal safety issue. Each of these could rapidly become a workforce issue.
Weather and climate data are critical for construction, shipping, food production, tourism, energy distribution, and many other industries. Data on income, trade, consumption expenditures, and demographics are critical to any business doing market, workforce, or facility siting analysis. In any of these cases, businesses that rely on private vendor subscriptions are not immune, as their private vendors all depend upon public data sources as foundations for their models.
Given the rapidity of data “Disappearances” in the first two weeks of the administration, we don’t expect it to stop. There is plenty of information that contradicts the administrations political proclivities in the Bureau of Economic Analysis, the Bureau of Labor Statistics, the Census, the Energy Information Administration, the International Trade Administration, the Department of Agriculture and other agencies. We anticipate that many of these sources will disappear or become restricted in the coming months. Restriction of any one of these would have major implications for significant portions of the economy.
The situation is made more critical by online data access and delivery. Thirty years ago, data histories for all these sources were published and available in libraries across the country. That is no longer the case. Unless restrictions are anticipated and data is downloaded, catalogued, and stored, even data histories will be unavailable. The reduction in publication and distribution costs has resulted in more and better data over the intervening period, but it has also put citizens and business at risk under the current administration.
There has always been public data that made elected officials uncomfortable. The current difference is that the administration is not willing to address and live with its discomforts – opting instead to eliminate the evidence of its contradictions.
THIS IS A BUSINESS ISSUE. It is time for businesses to step up to help resolve it.
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.
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.
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.
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.
This all started with some import-export data from the United States Bureau of Economic Analysis (BEA) and a couple of import-export graphs from the Economic Research Service (ERS) of the United States Department of Agriculture (USDA). It is not really about imports and exports in general, however, or even agricultural imports and exports in particular. It is about how our international transactions are influenced by the United States’ system of taxation. In particular, it is a discussion of how the United States’ tax system disadvantages labor relative to other factors of production and how that disadvantage affects our transactions with the world.
The graph below is “Export value share of production, 2013-22” for U.S. agricultural and food production. While we are just looking at industry production shares and not total volumes, it is clear that U.S. agricultural and food exports are heavily weighted towards relatively nonperishable commodities, low value food products. The majority of U.S. agricultural products are non-manufactured and non value added. Since 2008, the export share of U.S. agricultural production has remained relatively constant at about 20 percent.
The second graph is “Import share of U.S. food consumption, 2011-21.” The accompanying explanatory notes indicate that imports accounted for 15 percent of U.S. food consumption for the period, and that they steadily grew as a consumption share over the period. The unstated takeaway is that imports must be significantly above 15 percent of U.S. food consumption now.
As in the export graph, we are looking at industry shares rather than total volumes or values. It is still clear, however, that U.S. agricultural and food imports are skewed towards perishable and value-added food products – high value stuff. The explanatory notes also suggest that this is due to, “…numerous factors – including relative competitiveness in production…,” but no explanation for the, “…relative competitiveness of production…,” is given. It is assumed that relative competitiveness is a given – a state of nature.
It is not.
One of the reasons the U.S. exports nonperishable, non-manufactured, low value-added agricultural products and imports perishable, manufactured, and high value-added products is the competitive position of labor within the U.S. We often hear about the competitive position of labor between the U.S. and other countries, but that is not what we are discussing here.
The uncompetitive position of labor within the U.S. is largely a creature of the U.S. tax system. The tax system penalizes labor utilization within the U.S. in a number of ways. In general, taxes on labor are high. Income taxes, which are levied on wages and salaries, earned income, are substantially higher than taxes on capital gains, which are levied on incomes derived from physical and financial capital. This artificially raises the cost of labor in production. It also artificially lowers the cost of capital in production.
Income taxes are also generally levied on gross earned income and are collected immediately upon payment. Labor has very few means of minimizing or deferring their share of taxes. Labor pays gross rates. In addition, the U.S. government funds very large components of its social expenditure package (Social Security and Medicare) with direct taxes on labor. All of these increase the production cost of utilizing labor. It also increases the participation threshold of labor in production, making it less likely that labor will participate in the production process.
Conversely, recipients of receipts from physical and financial capital benefit from multiple incentives that can reduce rates that are already favored over labor (and further distort investment decisions). Among these is a very favorable schedule of depreciation, allowing owners of physical capital to claim a significant portion of receipts during the depreciation cycle as expense deductions. Recipients of returns from capital also have substantial leeway in determining when and how to realize those returns. This allows them to time and combine their receipts in tax-advantaged ways. When they do realize those returns, the recipients pay taxes at filing time rather than upon receipt. They pay net rates rather than gross rates. Furthermore, a large proportion of receipts from returns on capital is self-reported, generating substantial opportunities for tax avoidance.
Taken together, U.S. tax policy raises the relative cost of utilizing labor and lowers the relative cost of utilizing capital in the production process. At this point, one might ask, “What the heck does that have to do with the industry distribution of agricultural imports and exports?”
The answer is relatively simple. High-value food products, perishable, manufactured, and specialty foods, are generally more labor intensive than low-value foods. Through its tax policies, the U.S. disadvantages local production of high-value foods and encourages the production of low-value foods. This is mirrored in the types of food the U.S. exports and imports. There are other factors, but U.S. tax policy is a significant factor in this imbalance.
Tax policy doesn’t just affect employment and production in agriculture. Its effects are economy-wide. Luxury cars and watches are not generally products of the United States. Premium handmade shoes are generally imported, as are handmade suits. We export relatively capital-intensive goods and services. We import relatively labor-intensive goods. Both trends are supported by a domestic tax system that penalizes labor (earned incomes) and rewards physical and financial capital (unearned income).
If you recall your international trade course in undergraduate economics, trade is determined by relative input cost differentials within countries. Movement between countries equalizes internal cost differentials for both partners regardless of single-factor cost differentials between them. That means we can alter our import and export mix with the rest of the world by reducing the tax policy distortions between earned and unearned income. We are often told that unfair competition is stealing American jobs, but before anyone can be accused of cheating, we need to stop driving American jobs away with a distortionary tax regime.
In addition to the artificial cost differentials between labor and capital, the practice of funding social benefits through taxes on labor builds the cost of pensions and health care into the cost of goods on the market. This directly penalizes domestic consumers, and it increases the prices of U.S. exports, making labor-intensive exports even less competitive on the world markets. In most industrial nations, pensions are paid through general taxation and do not directly translate into export prices. In many, such benefits are paid for through value-added taxes that are only levied on goods sold domestically. This makes exports from these countries more competitive than exports from the U.S.
The tax distortions also cause fundamental economic problems and political distortions. While producers face artificially high costs of labor due to taxes, labor gets artificially low returns due to those same taxes. As a result, productive labor is often not an attractive trade-off with respect to the informal economy or household production. High labor costs due to taxes are coupled with low returns to labor due to taxes. We end up with:
A labor to capital cost differential that distorts our production and international trade
Stagnating labor incomes
A shortage of labor
All tied to a tax regime that penalizes earned income and rewards unearned income.
Recipients of unearned income recognize there are distortions in the labor market, but they have no interest in giving up their tax advantages. As an alternative, they insist that U.S. labor is paid too much. They fight to reduce the rights of labor to organize. They fight to reduce labor regulations that address fair payroll practices, overtime payments, working hours, and child labor. In order to get labor costs back in line, they fight to further reduce returns to labor while also defending and expanding the tax differentials that are the root of the problem.
I am a recovering economist. I spent most of my adult life with production functions, growth models, economic impact studies, and such. Traditional economic practice and the concepts of progress it embodies assume things grow. Sure, there are recessions. There are depressions. There are areas of the world that stagnate and decline. Those, however, are aberrations. They are failures of individuals or small groups of people. They grow out of market failures that can be identified and cured. At least, that’s the theory…
While we studied the concept of scarcity when we learned price theory in introductory microeconomics the production functions in upper-level micro seldom have explicit limits. It is assumed that individual players are too small to affect total supply or demand, so individual players appear to have an unlimited supply of resources at their disposal. It is only a small conceptual jump for most of us – even those of us who are economists – to internalize the assumption that the resources of production are unlimited.
Input-output systems utilized in economic impact modelling explicitly assume unlimited linear production relationships. It is possible in the context of these models to define an economic event that will employ an additional 10,000 workers in areas having populations of less than 10,000. The model will dutifully crank out an impact to scale (for a quick look at some of the implications of this, see my blog post at Regional Strategic, Ltd.)
Beyond economic impact modeling, whenever we perform cost-benefit analysis looking forward, we discount future costs and benefits on the basis of some factor (generally an assumed future interest rate). The effect of this is that current benefits nearly always swamp future costs. Future costs approach zero the farther out we look because the discount rate reduces them at a geometric rate. In a world of limited resources, one might think that future costs should approach infinity as we run out of valuable stuff to consume, but that is not how we model the future. Our modeled perceptions are probably some distance from our grandchildren’s coming realities.
The Coming Depopulation
These ubiquitous assumptions of continuous growth are running headlong into the reality of worldwide population decline. This is not the Malthusian catastrophe or Paul Ehrlich’s population bomb. It is not due to famine or war ignited by overpopulation, poverty, and despair. The simple fact seems to be that as people around the world are getting better off they are having fewer children.
This reinforces theories of economic demography which suggest that in poor societies children are demanded as a form of insurance against illness, injury, and incapacity. Where infant and child mortality are high, this generates a substantial demand for more children as a hedge against both poverty and mortality. On the other side of the coin, in rich societies with low infant and child mortality and significant insurance infrastructures, the increased demand for children is channeled into quality rather than quantity. In this sense, children in rich societies are acquired much like luxury durable goods – why have a Chevrolet when you can have a Mercedes? Fewer children have greater opportunities to participate in elite sports or arts groups, get more prestigious educations, and, later in life, receive larger inheritances. This increases the status of their parents as an exclusive cadre of exceptional children is paraded about town.
This, to varying degrees, increasingly appears to be the situation around the world, at present. For individual families and children, it is a favorable development. Society wide, perhaps, not so much.
Worldwide population decline has not been experienced since the 14th century when the great famine and the bubonic plague savaged the known world in quick succession. That episode, however, generated substantially different demographic effects than we can expect from the current depopulation of choice.
The famine and the plague inevitably victimized weaker segments of the population – likely the elderly and the infirm – at greater rates than they affected the stronger. As population declined, the working-age population increased relative to other population segments. This increased the productive potential of the population that remained. As total population declined, it also bid up the wages of the working population that remained. Finally, because they inordinately victimized the elderly, the twin catastrophes accelerated intergenerational transfers of wealth.
As a result, the famine and the plague increased the productivity of the remaining population and redistributed wealth towards the working portion of the population. It is quite likely that the rapid population and wealth redistributions of the 14th century were substantial factors in the coming of the renaissance in the 15th and 16th centuries. In other words, increasing the proportion of the productive labor supply in the population and increasing the proportion of society’s resources available to that productive labor supply helped usher in two centuries of phenomenal economic innovation and growth.
The coming depopulation of choice will have very different ramifications. The coming depopulation will be the product of millions of decisions to have fewer children. That will mean fewer people entering the labor force. At the same time, increasing life expectancies will result in an increasing number of older people who have left the labor force. Unlike the 14th century situation in which the relative size of the working-age population increased and the relative size of the elderly population decreased, in the coming depopulation there will be an increasing proportion of elderly matched against a decreasing labor force.
Increasing the relative size of the elderly population can also be expected to decrease the resources available to the working-age population for two reasons. First, it will be necessary to commit an increasing share of output to a population that is no longer productive. Second, as people live longer, the intergenerational transfer of wealth slows. When people die at 50, inheritances accrue to people who are 30 and improve the lives of the dependent children of those beneficiaries. On the other hand, when people die at 80, the inheritances accrue to people who are 60 and will be held by those beneficiaries to support their coming unproductive years.
In the coming depopulation, we can expect the remaining population to become less productive because of the resulting age distribution and the reduction in resources that can and will be dedicated to support the productive portion of that population.
The Current Situation
In affluent countries, where life expectancies are high and premature death rates low, the replacement birth rate is approximately 2.1 children per adult female. This replaces two parents and accounts for pre-adult mortality. In less affluent countries, where pre-adult mortality rates are higher, the replacement rate must also be higher. In 2022, fertility rates in every region of the world except Africa, the Middle East, and Central and South Asia were below affluent-society replacement rates (2.1 children) and falling. Even the fertility rates in regions above the replacement level are falling. With the exception of Sub-Saharan Africa, fertility rates are below 3.0 for all of the above-replacement regions.
The population in China is already falling. East Asia as a whole has a fertility rate of only one-half the replacement level. The fertility rate in India is already below the replacement rate, as is true of all four of the world’s most populous countries (India, China, the United States, and Indonesia). While these trends are increasingly becoming the subjects of attention, they have been recognizable in every region of the world since at least the 1960s.
The United States is not experiencing depopulation. Fertility in the United States, at 1.6 births per female, is far below replacement levels, but strong immigration supports continued growth in the United States population. On the basis of current trends, the United States will continue to have an increasing population until about 2080, but current trends are largely dependent upon immigration.
As outlined in the previous section, the coming depopulation will be accompanied by significant aging in the population. Over the past 30 years, the proportion of the population over the age of 65 has increased by about 15 percentage points in East Asia, 10 percentage points in the European Union, and 5 percentage points in the United States. At varying rates, this trend is occurring in every region of the planet.
As the elderly live longer, working-age people move into the ranks of the elderly, and low birth rates fail to replenish the labor force, fewer and fewer productive people will be supporting larger and larger unproductive populations. In addition, as the elderly live longer, intergenerational transfers of wealth will slow and will become almost entirely transfer cycles within a multigenerational elderly population – continually concentrating resources within the ranks of the unproductive population.
The two demographic solutions to this are higher fertility and accelerating elder mortality. Neither of these appear to be on the horizon anywhere in the world.
Potential for Immigration and Replacement
In spite of sub-replacement fertility, the United States still experiences population growth due to strong levels of immigration. This immigration is driven by the need for labor force replacement in the United States coupled with a positive wage differential between the United States and the immigrants’ home countries.
These two factors are in place throughout the Western industrialized world. While Europe is increasingly concerned about immigration, Europe needs immigration to support its labor force. Hostility towards European Union immigration rules was a major instigator driving the Brexit movement, but Great Britain still needs to fill the labor gaps generated by an aging population with a declining labor force.
The wage differential between the United States and the undeveloped areas of the world (particularly Latin America) all but guarantees immigration, legal or illegal, into the United States. The same is true for Western Europe, particularly with respect to the Middle East and Africa. No nation has ever been able to stop economically driven immigration. In fact, dedicating significant resources in the attempt to stop such immigration will almost certainly exacerbate the internal labor force issues that are the major drivers of immigration in the first place. At best, nations can hope to shape the quality and quantity of their immigrant packages through carefully integrating national entrance and foreign policies.
A major issue with the labor force needs of the developed world is the skillset of immigrants from areas of the world with surplus populations. In an increasingly technical world, labor force needs will require immigrants with substantial skills. In contrast, it is estimated that 90 percent of young people in Sub-Saharan Africa and India, the two largest pools of remaining non declining population in the world, lack basic skills. To a lesser extent, this is also true of Latin America, the Middle East, and the rest of South Asia. These people are drawn to the labor shortages and wage differentials of the developed world, but they are not equipped to contribute at the levels required. The immigrant labor the developed world desperately needs is woefully educationally deficient.
What the Situation Requires
At its base, a solution to the problems that will accompany global depopulation and aging must revolve around increasing economic productivity. This is such an urgent need that the September 2024 issue of the International Monetary Fund’s Finance & Development publication is titled, “PRODUCTIVITY and how to revive it.” As smaller and smaller populations of productive people are left to support the needs of larger and larger unproductive aging populations, we will need to either generate increased levels of output from the productive population or succumb to decreasing standards of living for the population as a whole.
There are basically three means of increasing productivity:
Increase the availability of resources.
Increase the technical ability to transform those resources into goods and services that generate income and wealth.
Increase the skills of the population engaged in resource transformation.
The first of these offers, at best, limited potential. Having treated resource availability as infinite for over three centuries since the industrial revolution, the world’s available resources are becoming harder and harder to locate, develop, and acquire. In fact, the world is dedicating increasingly large shares of the second and third factors of increased productivity to the acquisition of the first. It is not a zero-sum game, but diminishing returns are certainly a reality.
The second requires investments in basic research that almost certainly will have to come from public initiatives. Private entities will willingly invest in the specialized research and development needed to bring marketable products into production. They will not, however, invest in the basic research and scientific progress that underpin their specialized research activities. Basic research results in knowledge available to any private entity. An individual corporation cannot engage in basic research because the successful results of that research do not accrue specifically to the corporation. The results might actually give competing corporations an edge in the marketplace.
Without public investment, basic research falters. Without basic research, productivity falters.
Unfortunately, in both North America and Western Europe, the cores of the world’s basic research infrastructure, levels of funding for basic research are falling. The public appetite for funding basic research through the expenditure of tax revenues has diminished. As a result, it will be very difficult to significantly increase the efficiency with which we transform resources into income and wealth as the world depopulates and ages. This does not augur well for the future.
In addition to funding, increasing basic research capabilities requires maintaining and improving the quality of students entering the various fields of basic research. This fits hand in hand with the third means of increasing productivity: increasing the skills of the population engaged in the transformation of resources.
Both the second and the third means of increasing economic productivity require continuous improvement in basic education. This should drive increasing commitments to and investments in education. As the working-age population diminishes, it is absolutely necessary that the skillset of the working-age population expands. This is immediately true in the developed world, where populations are aging rapidly, and working-age populations are shrinking rapidly. It is also necessary in the less developed world, which will inevitably be asked to replenish the shortfalls in developed nations’ productive workforces.
Unfortunately, public investments in education are also in decline in the United States and across Western Europe. The simple truth is that all three of the necessary components for increasing productivity and maintaining incomes in a depopulating and aging world are going in the wrong direction in the only areas of the world with the resources to improve them.
It gets worse. Even if the developed world invests in domestic education and research to improve productivity, it is almost certain that domestic productivity cannot be raised fast enough. The rapid declines in productive populations juxtaposed against the rising economic needs of an expanding elderly population will almost certainly outstrip even extraordinary productivity improvements. Additionally, the ability to raise the productivity of what are already the highest productivity populations in the world will be limited.
The simple fact of the matter is that maintaining income and wealth for the developed world will require augmenting the developed world’s labor force with imported labor, immigrants. In a world where most available immigrants lack the basic skillsets to be productive participants in a technical industrial and service economy, those skills will have to be improved before they immigrate.
This will require the developed world to invest in the educational advancement of less developed nations which can provide immigrants. This will have to be done by developed nations for two reasons. First, less developed nations simply cannot afford to upgrade their educational systems and human capital fast enough to address the immigration requirements of depopulation and aging in the developed world. Second, educating potential immigrants from the less developed world, like basic research discussed above, will not generate value that the host countries can directly capture. In fact, the very premise, here, is that the people educated will migrate from their less developed home countries to the developed world.
If they desire to maintain their income levels in the face of depopulation and aging, developed countries will have to invest heavily in improving both their own education and human capital development systems and education and human capital development in the less developed world. In addition to maintaining their own income levels, this will have an impact on improving income levels for the world as a whole.
Not all newly educated youth in the less developed world will migrate out. That will improve the productive human capacity of their home countries. It can also be expected that a substantial proportion of the immigrants to developed countries will remit earnings to their home countries. This may not sound familiar, but it has parallels to the situation discussed above concerning the twin catastrophes of the 14th century. By increasing the productivity of the workforce in less developed countries and providing additional capital to that workforce (through both external investments in education and emigrant remittances), we might create conditions for at least some of those less developed countries to take off.
Conclusion
The coming world depopulation appears to be set in stone. Over half of the people in the world live in countries where fertility rates fall below replacement rates. All four of the most populous nations in the world (India, China, the United States, and Indonesia) fall within this group. Only three broad regions on Earth have fertility rates above the replacement level: Africa, the Middle East, and South Asia. Fertility rates are falling in every nation on Earth, even in countries where fertility remains above replacement levels.
Depopulation due to declining fertility rates inevitably means populations will age significantly. Rising proportions of elderly people juxtaposed against declining productive populations will result in declining incomes unless rates of economic productivity increase substantially.
The central component to increasing economic productivity is education. Maintaining income levels in the coming depopulation will require an immediate commitment to increase investments in education. This will be necessary but not sufficient in the developed world. It is also imperative that the developed world make an immediate commitment to increase educational investments in less developed countries. This is necessary because the developed world will be dependent upon technically proficient immigrants to augment its labor force as its populations shrink and age.
Regional Strategic, Ltd. engages in issues of regional economics: economic impact studies for existing enterprises and new initiatives, business planning and pro forma financial projections for new and growing businesses, and market and policy analyses (they are pretty much the same animal, really). We like project work. Every challenge is somewhat unique.
Almost all of our clients are looking to persuade someone: investors, taxpayers, development boards, potential clients, etc. We help them find, create, and interpret the information and data needed to support their interests. Upon occasion, we are asked to evaluate analytical studies done by others that our clients would like to challenge. It is still a persuasion game. It is just sometimes adversarial.
A term that often comes up when I talk to clients is the “Movable Middle.” The idea is that if a client can pull some of the middle of a population in their direction, they can generate sustainable growth or drive sustainable changes in policy.
In marketing situations where the client is only a small fraction of an industry made up of similar small players, this is healthy competition. It is reflective of Adam Smith’s 18th century observation of the “Invisible Hand” – where the individual actions of many small participants will continually move the marketplace towards a better solution for all – a mutually beneficial movement of the middle as a whole. In this case, small movements at the middle or average will be offset by multiple other small movements. The overall middle may actually move, but trends in the middle will reflect trends in the population as a whole. The population remains stable.
The situation can be very different where there are major players with market power. They can peel off so many participants in the middle that other market participants cannot accommodate within the existing population distribution. In these cases, moving participants away from the moveable middle affects the existence of the middle, itself. This can make the population less stable.
This is a particular issue in politics, where individual parties are actively attempting to split the middle in order to attain dominance. In political contexts the idea is that a group will never win over the core members of the other persuasion, but they should be able to whittle away at the population in the middle – to draw these denizens of the middle towards the clients’ points of view. This becomes increasingly critical as the number of competing entities diminishes.
You don’t have to remember much of your college statistics course to visualize this. Most of you remember the graphic below – the infamous bell curve. It is a standard normal population distribution where the mean (average) and the median are the same. They sit in the center (at the peak) and two-thirds of the population sits in close proximity to the mean. This is the starting point for an introduction to statistics course, and this type of population is the basis for most of the statistical analysis any of us has done.
In a marketing context, it may represent public perceptions of an industry-standard product where most people are generally satisfied with the product, some people really love it, and a few people really hate it. In a political context, it might represent a population where the majority of members generally wants the same things but sees multiple ways of getting to those things. It is easy to survey a standard normal population. With a normal population, a random survey of the population is sufficient as long as enough inquiries are made to assure reasonable representation of the central core and the outliers.
The center of the bell is the “Moveable Middle.” The term generally does not mean moving the entire middle. It means moving some members of the population away from the middle. A client might want to move someone slightly right of center to slightly left of center or move someone slightly left of center to farther left of center. This flattens the bell curve, increasing the variance and, perhaps, moving the mean away from the median and the highest point on the bell. The graphic below shows what this might look like.
Our population is no longer uniformly distributed around the mean. We have encouraged distinctions among the members that may depend on several specific factors (age, income, sex, gender, religion, etc.) We can no longer look at the population as homogenous. Also, since we actively advocated for and encouraged this movement, we can no longer look at population members as independent. The answer or perspective of any member we survey may be directly dependent upon the attitudes and perspective of other members we survey. We can no longer assume that each member sampled generates an independent data point for analysis.
At this point, we can no longer just pull a random sample from the population and survey the sample because members of our population are no longer randomly distributed or independent. We need to develop a sample frame. A sample frame is a set of rules regarding what we think we know about the distribution of the population. Do we expect that suburban middle-aged males, in general, have a common worldview? If so, we might treat them as a pool to sample. Do we expect that retired folks living on Social Security have the same interests and needs? Ditto. The more observable actionable distinctions we see within the population, the more detailed or complex the sample frame becomes.
Once we identify our frames of reference, we decide what a given group’s weight is within the population. We sample each group in accordance with the perceived weights. Then we combine our sampling responses to simulate the interests and opinions of the entire population.
Setting up and weighting the sample frame is not scientific. It is based on insights derived from science and observable facts on the ground, but it is not scientific. It requires some special insights and knowledge regarding the non-normal non-independent populations to be surveyed. This is why multiple seemingly redundant surveys of what appear to be the same populations regarding what appear to be the same questions and preferences often generate different results.
So-called “Gold Standard” pollsters or survey firms are “Gold Standard” because they have a track record of correctly setting up and weighting sample frames for evaluating non-normal non-independent populations. None of them are perfect, but they are regarded as consistently better than the rest. This is based on their ability to translate insights and facts on the ground into sampling frames that consistently mirror results revealed after the fact.
In any event, the difficulty in constructing sampling frames increases as we continue to move people away from the middle of the population. The graphic below might show a continuing population movement away from the middle. It may actually be a case where the population has split into two populations. In that case, if each population has a normal distribution and its members are independent, surveying either population becomes simpler, again. If both populations are of interest, however, from a political or marketing perspective, we still have the growing problem of developing accurate and informative sampling frames to evaluate the interests of the two populations together.
These issues are real regardless of whether we are marketing goods and services or political ideas. The wider implications are different in the two cases, however.
If we are trying to move the middle when marketing goods, we want to differentiate the market into two populations (ours and everyone else’s). For decades, Mercedes Benz attempted to split the automobile market. They tried to create a distinction between driving a car and driving a Mercedes Benz. Splitting the population would have made their information gathering easier. Two distinct populations could be polled separately, because they would be clearly identied. Mercedes drivers could be polled to find out what would enhance their experience. Car drivers could be queried regarding what it would take to move up. Separate polls would drive separate marketing campaigns. Successfully splitting the market would, in many ways, simplify the marketing game.
This has very few society-wide downsides when marketing goods and services, because we can each acquire the goods and services we want, regardless of the purchases of others. In the political marketplace, however, the population as a whole decides to buy one package of policies. Determining which package of society will “Buy” would ideally be made by an educated and informed electorate, similar to the assumption of perfect information in the theory of competitive markets. Unfortunately, the attempt to “Move the middle” in politics effectively reduces the amount of useful information in two ways.
The first of these is passive. As we move from a normal distribution in the first graphic above to the double-peaked population of the last graphic, it becomes harder to effectively poll or survey the population with regard to their community interests or to weight the importance of these interests across groups within the population. As discussed above, this is a result of the split in the population no matter how the split came about. The result, however, is that different polls regarding the same issue or group of issues will give significantly different results depending upon how the pollster designed the sample frame. Individual poll results will increasingly depend on the subjective insights of the individual pollster. The information provided to the electorate and to policy makers will be inconsistent. Decisions made on the basis of that information will become increasingly inconsistent. Governance on the basis of these decisions will become increasingly inconsistent.
The second of these is active. If we assume the population is differentiating because of an active information campaign to draw members of the population away from the middle, we almost have to assume this information is not representative of the population as a whole. We also might assume that some of this information is developed in the form of opinion surveys where sample frames were defined in such a manner as to generate favorable results. As we discussed above, in a differentiated or split population, the accuracy of polls has a lot to do with the pollster’s definition of the sample frame. All-star pollsters are those who are adept at correctly reading the population and developing appropriate sample frames. Policy influencers, however, can also be adept at defining sample frames that generate directed results, even while utilizing acceptable statistical techniques and avoiding the use of leading questions.
Regardless of whether the active or the inactive effects predominate, the erosion of useful information caused by moving population members away from the “Moveable Middle” will decrease the value of information provided to the electorate and policy makers. As a result, decisions made by the electorate and policy makers will be increasingly inconsistent. Governance based on these decisions will become increasingly erratic and ineffective.
This will go beyond politics. It will inevitably affect economic planning, investment, and growth.
Increasingly erratic and ineffective governance generates environments where it is increasingly difficult to plan. An inability to plan generally results in a reluctance to take risks. Increasing risk aversion tends to retard productive investment. A dearth of productive investment reduces production. Reduced production restricts income.
Remember that the expected return on any investment is the product of potential returns and the probability of attaining potential returns. A major determinant in that probability is government stability. Long-term productive investment tends to be made where there is an expectation of government stability over the lifetime of the investment.
In uncertain environments, investable funds tend to fine their way into financialization (placing bets on future policy direction by buying and leveraging shares or derivatives of existing productive assets), or the pursuit of returns directly through the exploitation of favorable government policies (rent seeking). While both may generate income for the participants involved, neither generates productive value or wealth for the economy as a whole.
None of these observations changes the fact that it is in the client’s best interest to try peeling the population in the middle away and towards the client’s ends. The society-wide implications, however, particularly in a political context, are important issues to consider.
P.S.
All of the images in this post were taken from an online article by Andrey Akinshin, “Normality is a Myth,” dated October 9, 2019 and downloaded from https://aakinshin.net/posts/normality-is-a-myth/ on November 20, 2024.
We are doing some work on farm and farmer value streams here at Regional Strategic, Ltd. The pilot work is using Iowa, but the intent is to take what is found and expand the work across the Upper Midwest.
One of the first major questions regards farmland valuation and appreciation. The graph below shows a simple relationship that leads to a number of complex questions. The graph shows cumulative inflation-adjusted value streams for ag land appreciation (from Iowa State University’s Farmland Value Survey), direct government payments (from the Bureau of Economic Analysis), and farm income net of government payments (derived from the Bureau of Economic Analysis) per acre of farmland (from the Census of Agriculture).
The period runs from 1993 to 2022. The scenario assumes that an acre of land is purchased in 1992 and the purchaser initiates production in 1993. The three lines show accumulations of income and land appreciation over a 30-year period. The endpoint is set as the last year in which complete stable information was available from the Bureau of Economic Analysis.
The first thing that jumps out is that accumulated land value appreciation outruns operating income and direct government payments. Accumulated land appreciation separates from the other two streams in 2002. In addition, Operating income breaks out above direct government payments in 2007.
Over the thirty years, the three inflation-adjusted value streams generated an average of $458 per year. Averages for each of the components were
Of this average value stream, only 38 percent came from income, and nearly a third of this income was in the form of direct government payments. Operating income accounted for only a little over 26 percent of the value stream generated by an average acre of Iowa agricultural land.
Average farm earnings net of government payments (operating income) was only sufficient to pay a 4.72 percent return on the 1992 purchase price of $2,559. Operating income plus direct government payments were only sufficient to pay 6.86 percent return to purchase price. This is all barely enough to cover interest or carrying cost on the investment.
Given these low production returns, what makes land price appreciation average 11.5 percent per year?
What caused land appreciation rates to break away from operating income and direct government payments in 2002?
What caused operating income to break away from direct government payments in 2007?
A portion of these relationships might simply be the result of the period being observed, but the size and consistency of the breaks suggest there is something more. There appears to be a confidence in the value of Iowa farmland that overrides observed farmland productivity. Why is that?
Is it due to indirect subsidies?
Is it due to the conviction that subsidies and relief will always maintain farm income?
Is it because of a belief that the removal or reduction of farm subsidies, both direct and indirect, will inordinately affect other production areas and concentrate production and value in Iowa?
We honestly don’t know the answers to these questions. That is the point of the inquiry. More will come as we noodle this out.
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