AI and Employment: So Far, So Good

By Alex Tabarrok. 

"In September 2023, the Census Bureau added questions about AI to its Business Trends and Outlook Survey. Census asked hundreds of thousands of businesses whether they had used AI in the previous two weeks to produce goods and services. At that time, 3.7% said yes; by late 2025 the figure had reached about 10%. (In November 2025 Census broadened the question to ask about AI use in any business function, producing a jump in measured adoption to about 18%.)

Twice the Bureau has asked a key question:

In the last six months, how did the use of Artificial Intelligence affect this business’s total employment?

In Dec. 2023 to Feb 24, when ~5% of firms were using AI the answers were 2.8% increased, 2.6% decreased and 94.6% reported no change. Two years later, in the Nov 2025–Feb 2026 supplement, the answers were: 2.3% increased, 2.0% decreased, and 95.7% reported no change. The answers were similar by firm size.

Some sectors reported more action. Information is the one sector where fewer than 92% report no change. But overall, almost all firms report no change and of those reporting change it’s about evenly divided between increasing and decreasing employment.

 

The supplement also asked about tasks. Among firms using AI, 44% say it supplemented or enhanced work an employee already does. Ten percent say it performed a task an employee used to do. Eleven percent say it introduced a task no one had been doing.

Among those using generative AI, 85% of firms cited writing or editing documents and email as the biggest uses, half cite searching for information, 45% summarizing documents, and 13% coding. Sixty-four percent of adopters say they changed nothing about the business in order to use AI, 15% trained existing staff, another 15% built new workflows, and just over one percent hired anyone with AI skills.

Among firms where AI has taken over some employee tasks, the degree of substitution is growing. The share reporting that AI took over “a large number” of tasks rose from 2.4% to 7.1%, while the share reporting “a moderate number” rose from 13% to 22%. But this group is still small: only about a tenth of AI adopters, who themselves make up about a fifth of firms.

I have reported firm-weighted estimates but employment-weighting gives essentially the same result. Thus, we have unusually direct evidence from a very large sample, and it says that the overwhelming majority of firms using AI do not yet report any effect on total employment. Very consistent with what Tyler and I said in our talk to OpenAI."

Other recent AI posts:

AI is moderately heating up today’s economy while we wait for the likely bumpy rollout of productivity gains 

General Purpose Technologies like AI can increase productivity more than expected 

The age of the solopreneur: More solo founders, growing faster, powered by AI 

The AI Backlash Has Tech Executives Fearing for Their Lives (a case of modern day Luddites?): Violent threats against AI companies are rising and spilling over into real-world security incidents 

Primitive communism: Marx’s idea that societies were naturally egalitarian and communal before farming is widely influential and quite wrong (plus Ruth Benedict on property rights)

By Manvir Singh. He is a professor of anthropology at the University of California, Davis. Excerpts: 

"It was on that first trip that [anthropologist Kim] Hill saw the Aché share their meat. A man returning from a hunt dropped an animal in the middle of camp. Another person, the butcher, prepared piles for each family. A third person distributed. ‘At the time, it seemed kind of logical to me,’ Hill said. The scene reminded him of a family barbecue where everyone gets a plate.

Yet the more he lived among the Aché, the more astonishing food-sharing seemed. Men were forbidden from eating meat they’d acquired. Their wives and children received no more than anyone else. When he later built detailed genealogies, he discovered that, contrary to his expectations, bandmates were often unrelated. Most importantly, food-sharing didn’t just happen on special days. It was a daily occurrence, a psychological and economic centrepiece of Aché society.

What he started to see, in other words, was ‘almost pure economic communalism – and I really didn’t think that was possible.’"

"In 1985, he started working with another group, the Hiwi of Venezuela. He didn’t expect dramatic differences from the Aché. The Hiwi, too, were hunter-gatherers."

"Then, there was food-sharing. In the primitive communism of the Aché, hunters had little control over distributions: they couldn’t favour their families, and food flowed according to need. None of these applied to the Hiwi. When meat came into a Hiwi village, the hunter’s family kept a larger batch for themselves, distributing shares to a measly three of 36 other families. In other words, as Hill and his colleagues wrote in 2000 in the journal Human Ecology, ‘most Hiwi families receive nothing when a food resource is brought into the village.’

By exercising control over distributions, hunters convert meat into relationships

Hiwi sharing tells us something important about primitive communism: hunter-gatherers are diverse. Most have been less communistic than the Aché. When we survey forager societies, for instance, we find that hunters in many communities enjoyed special rights. They kept trophies. They consumed organs and marrow before sharing. They received the tastiest parts and exclusive rights to a killed animal’s offspring.

The most important privilege hunters enjoyed was selecting who gets meat. Selective sharing is powerful. It extends a bond between giver and recipient that the giver can pull on when they are in need. Refusing to share, meanwhile, is a rejection of friendship, an expression of ill will. When the anthropologist Richard Lee lived among the Kalahari !Kung, he noticed that a hunter named N!eisi once ignored his sister’s husband while passing out warthog meat. When asked why, N!eisi replied harshly: ‘This one I want to eat with my friends.’ N!eisi’s brother-in-law took the hint and, three days later, left camp with his wives and children. By exercising control over distributions, hunters convert meat into relationships.

To own something, we say, means excluding others from enjoying its benefits. I own an apple when I can eat it and you cannot. You own a toothbrush when you can use it and I cannot. Hunters’ special privileges shifted property rights along a continuum from fully public to fully private. The more benefits they could monopolise – from trophies to organs to social capital – the more they could be said to own their meat.

Compared with the Aché, many mobile, band-living foragers lay closer to the private end of the property continuum. Agta hunters in the Philippines set aside meat to trade with farmers. Meat brought in by a solitary Efe hunter in Central Africa was ‘entirely his to allocate’. And among the Sirionó, an Amazonian people who speak a language closely related to the Aché, people could do little about food-hoarding ‘except to go out and look for their own’. Aché sharing might embody primitive communism. Yet, Hill admits, ‘the Aché are probably the extreme case.’

Hunters’ privileges are inconvenient for narratives about primitive communism. More damning, however, is a starker, simpler fact. All hunter-gatherers had private property, even the Aché.

Individual Aché owned bows, arrows, axes and cooking implements. Women owned the fruit they collected. Even meat became private property as it was handed out. Hill explained: ‘If I set my armadillo leg on [a fern leaf] and went out for a minute to take a pee in the forest and came back and somebody took it? Yeah, that was stealing.’

Some proponents of primitive communism concede that foragers owned small trinkets but insist they didn’t own wild resources. But this too is mistaken. Shoshone families owned eagle nests. Bearlake Athabaskans owned beaver dens and fishing sites. Especially common is the ownership of trees. When an Andaman Islander man stumbled upon a tree suitable for making canoes, he told his group mates about it. From then, it was his and his alone. Similar rules existed among the Deg Hit’an of Alaska, the Northern Paiute of the Great Basin, and the Enlhet of the arid Paraguayan plains. In fact, by one economist ’s estimate, more than 70 per cent of hunter-gatherer societies recognised private ownership over land or trees.

The respect for property rights is clearest when someone violates them. To appreciate this, consider the Mbuti, one of the short-statured (‘pygmy’) hunter-gatherers of Central Africa.

The Ute of Colorado whipped thieves. The Ainu of Japan sliced their earlobes off

Much of what we know about Mbuti society comes from Colin Turnbull, a British-American anthropologist who stayed with them in the late 1950s."

"his writings still undermine claims of primitive communism. He described a society in which theft was prohibited, and where even the most desperate members suffered for violating property rights.

Take, for instance, Pepei, a Mbuti man who in 1958 was 19 years old and still unmarried. Unlike most bachelors, who slept next to the fire, Pepei lived in a hut with his younger brother. But instead of collecting building materials, he swiped them. He snuck around at night, plucking a leaf from this hut and a sapling from that. He also filched food. He was an orphan after all, and a bachelor, so he had few people to help him prepare meals. When food mysteriously disappeared, Pepei always claimed to have seen a dog snatch it.

‘Nobody really minded Pepei’s stealing,’ wrote Turnbull, ‘because he was a born comic and a great storyteller. But he had gone too far in stealing from old Sau.’

Old Sau was a skinny, feisty widow. She lived a couple of huts down from Pepei, and one night caught him skulking around in her hut. As he lifted the lid of a pot, she smacked him with a pestle, grabbed his arm, twisted it behind his back, and shoved him into the open.

Justice was brutal. Men ran out and held Pepei, while youths broke off thorny branches and thrashed him. Eventually Pepei broke away and ran into the forest crying. After 24 hours, he returned to camp and went straight to his hut unseen. ‘His hut was between mine and Sau’s,’ wrote Turnbull, ‘and I heard him come in, and I heard him crying softly because even his brother wouldn’t speak to him.’

Other foragers punished stealing, too. The Ute of Colorado whipped thieves. The Ainu of Japan sliced their earlobes off. For the Yaghan of Tierra del Fuego, accusing someone of robbery was a ‘deadly insult’. Lorna Marshall, who spent years living with the Kalahari !Kung, reported that a man was once killed for taking honey. Through violence towards offenders, foragers reified private property.

Is primitive communism another seductive but incorrect anthropological myth? On the one hand, no hunter-gatherer society lacked private property. And although they all shared food, most balanced sharing with special rights. On the other hand, living in a society like the Aché’s was a masterclass in reallocation. It’s hard to imagine farmers engaging in need-based redistribution on that scale.

Whatever we call it, the sharing economy that Hill observed with the Aché does not reflect some lost Edenic goodness. Rather, it sprang from a simpler source: interdependence. Aché families relied on each other for survival. We share with you today so that you can share with us next week, or when we get sick, or when we are pregnant. Hill once saw a man fall from a tree and break his hip. ‘He couldn’t walk for three months, and in those three months, he produced zero food,’ Hill said. ‘And you would think that he would have starved to death and his family would have starved to death. But, of course, nothing happened like that, because everybody provisioned him the whole time.’

This is partly about reciprocity. But it’s also about something deeper. When people are locked in networks of interdependence, they become invested in each other’s welfare. If I rely on three other families to keep me alive and get me food when I cannot, then not only do I want to maintain bonds with them – I also want them to be healthy and strong and capable.

Interdependence might seem enviable. Yet it begets a cruelty often overlooked in talk about primitive communism. When a person goes from a lifeline to a long-term burden, reasons to keep them alive can vanish. In their book Aché Life History (1996), Hill and the anthropologist Ana Magdalena Hurtado listed many Aché people who were killed, abandoned or buried alive: widows, sick people, a blind woman, an infant born too soon, a boy with a paralysed hand, a child who was ‘funny looking’, a girl with bad haemorrhoids. Such opportunism suffuses all social interactions. But it is acute for foragers living at the edge of subsistence, for whom cooperation is essential and wasted efforts can be fatal.

Once that need to survive dissipated, even friends could become disposable

Consider, for example, how the Aché treated orphans. ‘We really hate orphans,’ said an Aché person in 1978. Another Aché person was recorded after seeing jaguar tracks:

    Don’t cry now. Are you crying because you want your mother to die? Do you want to be buried with your dead mother? Do you want to be thrown in the grave with your mother and stepped on until your excrement comes out? Your mother is going to die if you keep crying. When you are an orphan nobody will ever take care of you again.

The Aché had among the highest infanticide and child homicide rates ever reported. Of children born in the forest, 14 per cent of boys and 23 per cent of girls were killed before the age of 10, nearly all of them orphans. An infant who lost their mother during the first year of life was always killed.

(Since acculturation, many Aché have regretted killing children and infants. In Aché Life History, Hill and Hurtado reported an interview with a man who strangled a 13-year-old girl nearly 20 years earlier. He ‘asked for our forgiveness’, they wrote, ‘and acknowledged that he never should have carried out the task and simply “wasn’t thinking”.’)

Hunter-gatherers shared because they had to. They put food into their bandmates’ stomachs because their survival depended on it. But once that need dissipated, even friends could become disposable.

The popularity of the idea of primitive communism, especially in the face of contradictory evidence, tells us something important about why narratives succeed. Primitive communism may misrepresent forager societies. But it is simple, and it accords with widespread beliefs about the arc of human history. If we assume that societies went from small to big, or from egalitarian to despotic, then it makes sense that they transitioned from property-less harmony to selfish competition, too. Even if the facts of primitive communism are off, the story feels right.

More important than its simplicity and narrative resonance, however, is primitive communism’s political expediency. For anyone hoping to critique existing institutions, primitive communism conveniently casts modern society as a perversion of a more prosocial human nature. Yet this storytelling is counterproductive. By drawing a contrast between an angelic past and our greedy present, primitive communism blinds us to the true determinants of trust, freedom and equity. If we want to build better societies, the way forward is neither to live as hunter-gatherers nor to bang the drum of a make-believe state of nature. Rather, it is to work with humans as they are, warts and all."

Singh's article reminded me of a passage about the Kwakiutl from Ruth Benedict's book "Patterns of Culture." Click here to go to a link that has her entire book online. It indicates that they may have had strong property rights

"The tribes of the North-West Coast had great possessions, and these possessions were strictly owned. They were property in the sense of heirlooms, but heirlooms, with them, were the very basis of society. There were two classes of possessions. The land and sea were owned by a group of relatives in common and passed down to all its members. There were no cultivated fields, but the relationship group owned hunting territories, and even wild-berrying and wild-root territories, and no one could trespass upon the property of the family. The family owned fishing territories just as strictly. A local group often had to go great distances to those strips of the shore where they could dig clams, and the shore near their village might be owned by another lineage. These grounds had been held as property so long that the village-sites had changed, but not the ownership of the clam-beds. Not only the shore, but even deep-sea areas were strict property. For halibut fishing the area belonging to a given family was bounded by sighting along double landmarks. The rivers, also, were divided up into owned sections for the candlefish hauls in the spring, and families came from great distances to fish their own section of the river."

AI is moderately heating up today’s economy while we wait for the likely bumpy rollout of productivity gains

See How is AI influencing interest rates? Investment, productivity, prices, and more by Jeff Horwich of the Federal Reserve Bank of Minneapolis. Excerpts:

"From $200 billion in 2024, capital spending by the five largest investors in AI data centers—Alphabet, Amazon, Meta, Microsoft, and Oracle—is projected to approach $1 trillion by 2027. “For reference, total private investment in the economy is about $5.5 trillion dollars,” said Minneapolis Fed Monetary Advisor Alisdair McKay. “We’re talking about 20 percent of investment coming from this one category.”

All else equal, this surge in data center spending and demand for investment funding would constitute strong macroeconomic forces pushing real interest rates higher.¹ But for all the lofty projections, AI-related investment is not moving the needle much at an economy-wide level.

Despite an unmistakable leap in an AI-relevant category like information processing equipment (Figure 1, right axis), the growth path of U.S. aggregate private investment looks similar to the trend since 2010 (Figure 1, left axis). 

 

As a proportion of U.S. GDP, McKay notes that private investment remains roughly flat since 2018. So far, the AI boom does not resemble prior periods of investment growth in the 1990s and 2010s. Breaking investment down into its four primary components shows part of the reason: The shares of housing investment—and, to a lesser extent, investment in nonresidential construction—are falling (Figure 2).

 

Current nominal interest rates are elevated from the ongoing battle to vanquish inflation, which depresses or postpones investment in those rate-sensitive construction categories. Intense investment demand for AI data centers also drives up costs for construction inputs and could attract funds that might otherwise go into housing. The net result is something of a wash from a macroeconomic perspective. “You would think that if you have this great opportunity” to achieve future growth by investing in AI, McKay said, “you would increase the amount you invest. But we have not done that in the aggregate.”

Minneapolis Fed Monetary Advisor and Assistant Director of Policy Cristina Arellano notes that while the technology sector represents about 15 percent of U.S. output, it comprises only 7 percent of U.S. consumption. As many economists understand it, this investment-driven economic growth puts less pressure on underlying interest rates than if spending were driven by a more consumption-heavy category.

“The natural rate [of interest] is more linked to the consumption growth rate, in terms of the frameworks we use to think about this,” Arellano said. Growth focused in the tech sector “may have a smaller effect on the natural rate because it’s not affecting consumption so much.”

In many economic models, household and investor expectations of the future can make a big difference today. If people expect to be richer down the road, they spend more today and even borrow against that future income. This would tend to increase real interest rates as the supply of savings shrinks, especially in the context of high investment demand.

If, on the other hand, people worry about their jobs or the prospects for their children, they might tend to save more as a precautionary measure, having the opposite economic effect. Pessimism about the future tends to keep rates in check today.

This classic “consumption smoothing” dynamic comes up often in speeches and papers about the macroeconomic impact of AI. Researchers analyzing significant movements of bond yields around major AI announcements interpret them under this theory.

For all the utopian-to-existential talk about AI around American dinner tables, Arellano and McKay are skeptical that households are behaving like the economic models. “I don’t think there are that many people who connect that future—where all of us, where the economy is richer—with, ‘I’m going to be richer,’” said McKay. 

As for the scenario of fear-based savings pushing rates down, Americans are showing no evidence of precautionary saving. The U.S. personal saving rate has been generally falling since AI hit the public consciousness and sits now near historically low levels.

However, beliefs about the future of AI are likely influencing current consumption and interest rates through another channel: Soaring stock wealth. Since ChatGPT debuted to the general public in November 2022, the S&P 500 stock index has risen 80 percent (as of late July 2026), driven by shares of tech companies associated with AI. “We think that the marginal propensity to consume out of stock wealth is about 3 cents on the dollar,” said McKay. “So that would mean, ballpark, one-half to 1 percent of GDP in consumption each year from this extra wealth. That’s pretty big.”

The wealthiest 10 percent of U.S. households own almost 90 percent of American stock and mutual fund holdings; the richest households also account for a disproportionate amount of spending. Their consumption, supported by these equity gains, has helped sustain demand despite low sentiment among consumers overall."

"optimism . . . could motivate relatively stronger U.S. consumption from AI-related wealth. This demand keeps the economy and inflation running hotter, an argument for higher policy rates.

Aggregate consumer demand is held somewhat in check, however, by the concentrated nature of AI-based wealth and by caution among consumers with lower wealth and income. AI-inspired spending is “not for every segment,” Arellano said, “especially for young people graduating from college.”"

"Relative price changes happen all the time; they do not necessarily portend general inflation. But with core consumer inflation persistently above the Fed’s 2 percent annual target, policymakers might take note of categories where price increases are not only above historic averages but accelerating—as is the case for computer-related equipment. Rising prices for metals, power, and information technology could pass more widely into the business costs for firms.

Policymakers generally “look through” supply shocks expected to temporarily affect relative prices, such as a one-time increase in tariffs or the war in Iran. “The AI impact seems like it could be more persistent,” said McKay, with data center investment possibly reaching into trillions of dollars and stretching years into the future. If so, this might incline policymakers toward higher interest rates to contain wider price increases and keep inflation expectations anchored."

"AI tools could bring a leap forward in helping companies adjust prices more frequently and precisely. AI could turbocharge what economists call “price discrimination”—think of it as personalized pricing—“by facilitating the real-time analysis of consumer demand and price elasticities,”"

"a world of instantaneous price adjustments and pass-through of costs could amplify inflationary events. It could also make central banks’ jobs more difficult. “Those frictions shape the transmission of monetary policy,” said Arellano. What economists call “nominal rigidities” of prices (and wages) are understood to play a crucial role in translating the Fed’s policy moves into reactions across the economy."

"there is a prominent counterargument that AI will restrain price increases or even drive many prices down. Recent findings by European researchers found that a higher share of AI adoption by firms corresponded with lower inflation in those sectors, with the productivity gains from AI a possible “structural force dampening inflation.”" 

Some Fed members think "productivity gains associated with AI adoption would eventually reduce production costs and increase aggregate supply, which should put downward pressure on inflation" 

"these effects are not yet meaningfully apparent at a macroeconomic level, where headline and core price indexes remain elevated. Nor are they evident for the task where AI has been most immediately and heavily put into action: computer coding. The consumer and producer price indexes for software, historically deflationary, instead show flat-to-rising prices since generative AI came on the scene. Importantly, these measures also reflect AI-driven hardware price pressures.² Nonetheless, they display no ground-level signal of productivity leading to disinflation—quite the opposite."

"For the information services sector and the subsector that includes software, rough calculations of productivity through 2025 (real output-per-worker) are consistent with levels over the past 20 years. A large jump in 2023 coincides with the introduction of ChatGPT. But that is followed by four quarters of productivity declines. Rising productivity through 2025 is tantalizing, but within normal, historic fluctuations."

"“If you look back at other types of technological adoption—electricity, computers—they took decades to manifest in terms of changing production processes and getting the productivity benefits,” said McKay. “From a macro perspective, the main thing we are doing right now is ‘building the machine.’”

McKay points out a disconnect between the tasks most likely to benefit initially from AI and the physical investment that puts demand-side pressure on the economy. “I don’t see that the productivity benefits are going to show up in a way that makes it easier to build a data center,” he said.

Researchers have documented a J-shaped pattern to the adoption of general-purpose technologies. Measured productivity actually decreases at first, as companies implement investments in retraining, reorganization, and updating equipment. Although AI awareness and experimentation are arguably spreading faster across the economy than prior technologies, similar frictions are already appearing."

"The unemployment rate has held steady amid a persistent “low-hire, low-fire” labor market. AI has been cited for some notable layoffs in the tech sector, even as a broader study of 21,000 U.S. firms found AI adoption is associated with additional hiring."

"monetary policy has little influence over structural changes wrought by technology. Nor do central banks tend to respond to scenarios in the uncertain future. Fed policymakers are focused on today’s data, where productivity gains are a work in progress and jobs are holding steady. Data center investment, wealth-driven consumption, and possibly pricing forces are creating heat—but this appears moderate in the aggregate, for now.

“In the near term, whatever increase in the productive capacity of the economy AI has brought, AI has brought a larger increase in demand,” McKay said. Big changes could still be on the way for the economy, maybe sooner than later given the speed of AI investment, awareness, and diffusion. But we are still near the start of the journey.

“It’s hard to just implement things really quickly, then adapt and change,” said Arellano. “These processes are sort of slow. But I do think there will be a lot of gains in the medium term.”"

General Purpose Technologies like AI can increase productivity more than expected

See The Productivity J-Curve: How Intangibles Complement General Purpose Technologies by Erik Brynjolfsson, Daniel Rock & Chad Syverson.

Abstract 

"General purpose technologies (GPTs) like AI enable and require significant complementary investments. These investments are often intangible and poorly measured in national accounts. We develop a model that shows how this can lead to underestimation of productivity growth in a new GPTs early years and, later, when the benefits of intangible investments are harvested, productivity growth overestimation. We call this phenomenon the Productivity J-curve. We apply our method to US data and find that adjusting for intangibles related to computer hardware and software yields a TFP level that is 15.9 percent higher than official measures by the end of 2017."  

Whiskey taxes, revenue and voting by members of Congress in history

See Revenue over reason: A case for home distilling by Ben Semark of the Competitive Enterprise Institute. After an excerpt from Semark's article, I discuss how this relates to voting by congressmen on bills during the Federalist period, the subject of my Ph. D. dissertation.

Excerpt from Semark:

"Creating home-brewed spirits was not a niche or commercial practice in early America; it was an everyday routine. Alcoholic beverages were a staple of the early American diet and were often much safer than local water sources. Wives were often responsible for the process and used various crops distilled into safe beverages to quench the thirst of their households. Stills were treated as ordinary kitchen appliances, like a butter churn or wood oven. In the late 18^th century, 25 percent of households in Augusta County, Virginia owned and operated home stills.

Distilling was not just a household chore; it was also a primary source of income for many farmers. Common crops, such as barley, corn, apples, and peaches, were all vulnerable to spoilage even across short distances. Where travel was especially difficult, distilling these crops provided a more resilient product and a steady source of income for many.

After the Revolutionary War, Alexander Hamilton proposed an excise tax on distilled spirits to tackle the extreme debt the country had accumulated. Excise taxes operate by taxing the manufacture of a targeted good rather than the income generated from sales. Many farmers reacted in outrage, sparking the famed Whiskey Rebellion, during which George Washington led a militia of 13,000 troops to quell the unrest.

The rebellion represented the first violent domestic challenge under the new American Constitution. Hamilton’s enforcement of the tax required every still, no matter how small, to be registered with the federal government. The upheaval underscored the importance of distilling culture in early America. Citizens felt betrayed by their newly formed government, not only due to the tax, but also government intrusion into routine household activities.

Distillation remained common in the home despite the tax, and Jefferson later repealed it, much to the delight of many Americans. Soon after the distilling culture exploded. The early 19^th century came with many advancements in distilling, making the practice accessible to non-farmers. An author at the time noted “we find men of science, men of capital, lawyers, doctors and merchants abandoning other pursuits to learn the art of extracting spirit from grain.” Distilling was no longer merely a household chore or a farmer’s practice; it had become a hobby." 

For my Ph. D. dissertation in 1991 I analyzed how both ideology and economic factors influenced the way congressmen voted on bills during the Federalist period (1789-1801). Some bills were labeled "specific" because they were about a specific issue, like the whiskey tax. Others were labeled "general" because they were about how strong the national government should be in general.

See Ideology versus Economics during the Federalist Period (a paper which covers the topic of my dissertation). This is an MS Word file.  

There were many bills that I looked at and I used statistical regression techniques. Many variables were used to predict how congressman voted on bills. One important variable was

WHIS) The average annual per capita gross revenue collected in each state from domestic distilled spirits and stills.

Another one was  

DIST) The distance from the center of a congressional district to the nearest navigable coastline.

I will discuss DIST after I discuss WHIS.  

In the House of Representatives, out of 28 bills, the variable WHIS was associated with an anti-national stance 23 times. Basically, that means that the more whiskey produced in a state, the more likely, in general, that its representatives were to vote to limit the strength of the national government. On most of these votes in the House WHIS was statistically significant. 

The results were not as strong in the Senate. WHIS was anti-national on only 3 of 6 votes. But on 2 of the 3 anti-national cases it was significant.

Some of these bills dealt directly with a whiskey tax or requiring a license to operate a still. 

On Vote 10 in the Senate, WHIS had a negative relationship with voting and it was significant.

Vote 10.  To pass the House bill, repealing after the last day of June next, the duties heretofore laid upon distilled spirits imported from abroad and laying others in their stead, and also upon spirits distilled in the United States.  This is also known as the Whiskey Tax.  It is pro-national because it raised revenue for the national government.  Passed February 12, 1791, 20-5.  Specific legislation. 

On Vote 20 in the Senate, WHIS had a pogative relationship with voting but it was not significant. 

Vote 20.  To amend H.R. 32, an act to amend the several acts for laying duties on spirits distilled within the United States, and stills; by restoring the section which provides for taking out licenses on stills.  This bill is pro-national because it required a license for stills used to make whiskey.  Failed January 23, 1798, 9-15. Specific legislation.

The next 5 bills were in the House. WHIS had a negative relationship in all 5 cases and was significant on 2 of them. 

Vote 6.  To pass H.R. 110, an act to impose import duties and taxes on distilled spirits.  This bill is also known as the Whiskey Tax.  This bill is pro-national because it is a revenue raiser.  Passed January 27, 1791, 35-21.  Specific legislation.

Vote 11.  To amend H.R. 191, a bill concerning the duties on spirits distilled within the United States; to place a duty of eight cents on certain distilled spirits.  This bill is pro-national because it is a revenue raiser.  Failed April 30, 1792, 26-27.  Specific legislation.

Vote 17.  To pass H.R. 56, a bill to lay duties on licenses for selling wines and distilled spirits, by retail.  This bill is pro-national because it is a revenue raiser.  Passed May 31, 1794, 53-23.  Specific legislation.

Vote 20.  To pass H.R. 12, a bill to lay a duty on Licenses for the sale of wines by retail, and also foreign distilled spirits.  This bill is pro-national because it is a revenue raiser.  Passed June 27, 1797, 56-27.  Specific legislation.

Vote 31.  To pass H.R. 276,  a bill to continue in force the acts laying duties on licenses for selling wines and foreign distilled spirits, on property sold at auction, and on carriages for the conveyance of persons. This bill is pro-national because it is a revenue raiser.  Passed January 16, 1801, 46-31.  Specific legislation.

Now back to the DIST variable.

DIST) The distance from the center of a congressional district to the nearest navigable coastline.

Generally, people who lived farther away from the coast and who also liked to produce whiskey, tended to be against a strong national government. On 25 bills about the size and scope of government, DIST had a negative relationship with building a strong national government on 19 of them. Congressman who tended to live farther away from the coast had a strong tendency to vote against a strong national government. DIST was significant on 15 of these bills.

See my paper linked above for more details and discussion of the issues and the legislation.