The Unemployment Map: Where Jobs Are Scarce

When the Bureau of Labor Statistics publishes the national unemployment rate each month, it delivers a single number that purports to describe the condition of 168 million workers spread across 3.8 million square miles. The January 2025 reading is 4.1%, seasonally adjusted. It is a reasonable number. It suggests a labor market that is cooling but not contracting, normalizing but not deteriorating. Politicians cite it. Markets react to it. Economists parse the decimal points.

But a single national number is an average — and averages are the enemies of understanding. A person living in Sioux Falls, South Dakota, inhabits a fundamentally different labor market than a person living in Las Vegas, Nevada. One lives in an economy where employers post signs begging for workers. The other lives in an economy where layoffs in hospitality and gaming can leave thousands searching for months. The national rate does not distinguish between them. It never can.

The BLS publishes state-level unemployment data through the Local Area Unemployment Statistics (LAUS) program, a cooperative effort with state employment agencies that produces estimates for every state, every metropolitan area, and more than 7,000 counties. The state-level data for January 2025, seasonally adjusted, tells a story that the national figure obscures entirely: unemployment rates range from 1.9% to 5.8%, a spread of 3.9 percentage points that represents a 3:1 ratio between the most and least distressed labor markets in the country.

This episode maps that variation. Where are jobs scarcest? Where are labor markets tightest? And what patterns — geographic, industrial, demographic — explain the divide?

The ten states with the highest unemployment rates in January 2025 are not random. They follow recognizable patterns that recur in every business cycle, every labor market survey, and every geographic analysis the BLS has ever produced. These are states where structural forces — industry concentration, seasonal volatility, population growth that outruns job creation — push unemployment persistently above the national average.

Nevada leads the nation at 5.8%, a full 1.7 percentage points above the national rate. This is not new. Nevada has ranked among the highest-unemployment states for over a decade, a legacy of the state’s extreme dependence on tourism, gaming, and hospitality. The leisure and hospitality sector accounts for roughly 28% of Nevada’s nonfarm employment — more than double the national share. When consumer spending dips, when conventions cancel, when travel slows, Nevada’s unemployment rate responds with disproportionate force. During the Great Recession, Nevada’s rate hit 13.7%. During the pandemic, it exceeded 30% on a monthly basis. Even in good times, the state’s seasonal swings and the inherent volatility of its dominant industry keep unemployment elevated.

California comes second at 5.4%, and its ranking surprises those who think of the Golden State as an economic powerhouse. California’s economy is the fifth-largest in the world — larger than India’s was a decade ago. But size does not guarantee tight labor markets. California’s unemployment problem is structural: the state has among the highest costs of living in the nation, a regulatory environment that constrains certain types of business formation, and large populations in the agricultural Central Valley and the Inland Empire where educational attainment is lower and industry is more cyclical. The tech sector, concentrated in the Bay Area, creates enormous wealth but employs a relatively small share of the state’s 19 million workers. Meanwhile, the retail, food service, and logistics sectors that employ far more Californians are subject to greater volatility.

Kentucky (5.3%) represents a different kind of challenge. The decline of coal mining — once the backbone of eastern Kentucky’s economy — has left entire communities without a replacement industry. Coal employment in Kentucky has fallen from over 40,000 in the early 1980s to fewer than 4,000 today. The transition to other industries has been slow, complicated by geographic isolation, lower educational attainment, and infrastructure deficits in Appalachian counties. Western Kentucky has fared better, with manufacturing and logistics operations, but the state average reflects the ongoing economic dislocation in its eastern third.

Michigan (5.3%) carries the legacy of deindustrialization. The state that once employed 400,000 auto workers now employs fewer than 150,000 in that sector, and the shift from internal combustion to electric vehicles threatens further disruption. Detroit’s metropolitan unemployment rate remains well above the state average. The state has made progress in diversifying — Grand Rapids and Ann Arbor have become technology and healthcare hubs — but the structural transition from a manufacturing-dominated economy to a service-and-knowledge economy is incomplete.

The District of Columbia (5.3%) is a special case. It is not a state but a city, and its unemployment rate reflects the extreme inequality of a jurisdiction where federal employees and lobbyists coexist with some of the highest poverty rates east of the Mississippi. The unemployment rate in DC’s wealthiest wards is below 2%. In its poorest, it exceeds 15%. The aggregate figure masks a bimodal distribution that is more extreme than anywhere else in the country.

The remaining five states in the top ten — Illinois (4.9%), Alaska (4.7%), Colorado (4.7%), Rhode Island (4.6%), and New Jersey (4.6%) — each carry their own structural explanations. Illinois is dominated by Chicago, a global city with deep inequality and a public sector that has shed jobs through fiscal austerity. Alaska’s economy is tied to oil and fishing, both seasonal and volatile. Colorado’s rapid population growth has created labor supply that at times outpaces demand, particularly in the service sector around Denver. Rhode Island, the nation’s smallest state, never fully recovered its manufacturing base after the 2008 crisis. And New Jersey, despite its wealth and proximity to New York City, has persistent unemployment in its southern counties and former industrial corridors.

What unites these ten states is not geography alone — they span the West, South, Midwest, and Northeast. What unites them is structural vulnerability: dependence on a single volatile sector, incomplete economic transitions, or sharp internal inequality that pushes the state average above the national line.

At the other end of the spectrum, ten states report unemployment rates so low that they challenge the very concept of unemployment. When the rate drops below 3%, economists describe the labor market as “functionally full employment” — a condition where virtually everyone who wants a job has one, and the remaining unemployment is largely frictional, reflecting normal job transitions rather than involuntary joblessness.

South Dakota leads the nation at 1.9%, a figure so low that it barely registers as unemployment at all. In a labor force of roughly 470,000, a 1.9% rate means fewer than 9,000 people in the entire state are looking for work. Employers in Sioux Falls, Rapid City, and rural communities across the state report chronic labor shortages. Help-wanted signs are permanent fixtures. Businesses adjust to the scarcity by raising wages, automating, reducing hours, or simply accepting that they will operate below full capacity.

South Dakota’s ultra-low rate reflects several reinforcing factors. The state has no personal income tax, which attracts both workers and businesses. Its economy is diversified across agriculture, financial services (Sioux Falls is a major credit card processing hub), healthcare, and government. Its population is small (roughly 920,000) and relatively stable, so labor supply and demand stay closely matched. And its cost of living is low enough that even moderate wages provide a comfortable standard of living, which reduces the search time between jobs.

Vermont and North Dakota tie at 2.6%, both exemplifying the small-state, low-population model. Vermont’s economy runs on tourism, specialty food and beverage production, healthcare, and a small but growing technology sector. North Dakota has benefited enormously from the Bakken shale oil boom, which transformed the state’s labor market in the early 2010s and left a lasting infrastructure of high-paying extraction jobs. Both states have labor forces under 400,000, meaning small changes in employment create large percentage swings — but the consistent pattern is one of perpetual tightness.

Montana (2.8%) and Nebraska (2.9%) continue the Plains pattern. Montana has emerged as a relocation destination, drawing workers from higher-cost states, but its economy — anchored by ranching, tourism, and a growing tech community around Bozeman — has so far absorbed the inflow. Nebraska’s economy is perhaps the most stable in the country, built on agriculture, insurance (Omaha is a national center), and Warren Buffett’s Berkshire Hathaway ecosystem. The state has not had an unemployment rate above 5% since 1986.

New Hampshire (2.9%) is the lone northeastern state in the bottom ten. Its proximity to Boston creates a labor market where many New Hampshire residents commute to Massachusetts for work but are counted in New Hampshire’s statistics, which pushes the rate down. The state also has no income or sales tax, attracting businesses and residents from neighboring states.

Hawaii (3.0%), Virginia (3.0%), Minnesota (3.0%), and Maryland (3.0%) round out the bottom ten, all exactly at the 3.0% threshold. Hawaii benefits from a tourism economy that, unlike Nevada’s, operates year-round and is supplemented by a large military presence. Virginia’s labor market is anchored by the federal government and the enormous defense and technology corridor in northern Virginia. Minnesota has the most diversified economy of any midwestern state, with major employers in healthcare (Mayo Clinic, UnitedHealth), retail (Target), financial services (U.S. Bancorp), and food production (General Mills, Cargill). Maryland, like Virginia, benefits from federal employment and the concentration of government contractors and research institutions around the Baltimore-Washington corridor.

The horizontal bar chart below displays unemployment rates for all 50 states plus the District of Columbia, ranked from highest to lowest. The color gradient runs from green (lowest rates) through yellow (middle) to red (highest), providing an immediate visual read on where each state falls in the national distribution.

Several patterns emerge at a glance. The green cluster at the bottom — the Plains states, the upper Midwest, northern New England — is tightly packed between 1.9% and 3.5%. The red cluster at the top is more dispersed, with Nevada standing visibly apart from even the second-highest state. And the middle band, where most states sit, spans a relatively narrow range from 3.5% to 4.5%. The national rate of 4.1% falls roughly in the middle of this central cluster, confirming that the national average does, at least, represent the center of the distribution — even if it describes no individual state’s reality.

The middle of the distribution — the 31 states between 3.0% and 4.5% — contains the majority of the American population. These are states where the labor market roughly mirrors the national condition: not overheated, not distressed, but somewhere in the zone that economists consider normal. States like Florida (3.4%), Texas (4.2%), Georgia (3.5%), and Pennsylvania (4.4%) — four of the six most populous states — all fall within a percentage point of the national average.

This concentration is important. It means that the extremes — South Dakota’s 1.9% and Nevada’s 5.8% — are genuinely outliers, not representatives of large populations. The typical American lives in a state where unemployment is within shouting distance of 4%. The dramatic variation at the tails affects millions of people, but it is not the dominant experience.

Yet outliers matter. Nevada’s 3.2 million people live in a very different labor market reality than South Dakota’s 920,000. California’s 39 million experience a 5.4% rate that touches more people than the bottom ten states combined. The number of people affected by high unemployment is not proportional to the number of high-unemployment states — it is proportional to the population of those states. And some of America’s highest-unemployment states are also among its most populous.

Examining the distribution as a histogram — how many states fall into each unemployment rate band — reveals the shape of America’s state-level labor market. The distribution is not uniform. It clusters heavily in the middle, with the 3.0%–3.5% band containing the most states.

The histogram below groups all 51 jurisdictions into half-percentage-point bands. The resulting shape tells a clear story: the American labor market is moderately right-skewed. Most states cluster between 3.0% and 4.5%, with a long tail extending toward higher unemployment rates. Only five states sit below 3.0%, and only five sit above 5.0%. The fat middle — 36 states between 3.0% and 5.0% — represents the American norm.

The distribution numbers are instructive:

The median state unemployment rate is approximately 3.7%, which is below the national average of 4.1%. This discrepancy arises because the national rate is a population-weighted average, and high-population states like California (5.4%, 39M people) and Illinois (4.9%, 12.5M people) pull the national figure up relative to the unweighted state median. If every state had equal population, the national rate would be closer to 3.7% than 4.1%.

The distribution also reveals that 61% of states (31 of 51) are below the national average. This is not a contradiction — it is a mathematical consequence of a skewed distribution where a few high-population, high-unemployment states exert outsized influence on the population-weighted mean. It means that the “typical” state has a tighter labor market than the national rate suggests.

The geographic pattern of state unemployment is among the most persistent features of the American labor market. It is not random. It is not new. It has repeated, with variations, in every LAUS release for decades. The pattern can be summarized in a single sentence: the Plains and Mountain West have the lowest unemployment; coastal urban centers and the industrial Midwest have the highest.

This geographic divide reflects deep structural differences in state economies:

The Plains and Mountain West states — South Dakota, North Dakota, Nebraska, Montana, Wyoming, Idaho — share a common economic DNA. Their populations are small and stable, reducing the labor market frictions that come with rapid growth or decline. Their economies are diversified at a local level, even if individual industries are not large by national standards. Agriculture provides a floor of economic activity. And their cost of living is low enough to keep labor force participation high — when basic expenses are manageable, fewer people withdraw from the workforce.

The West Coast and Sun Belt present a different model. California, Nevada, and Arizona combine rapid population growth with economies heavily tilted toward sectors that are either seasonal (tourism, agriculture) or cyclical (construction, entertainment). California’s tech sector is dynamic but employs a small share of the total workforce. Nevada’s gaming industry is highly concentrated geographically. These states experience larger swings in employment, and their larger populations mean that even small percentage-point increases translate into hundreds of thousands of affected workers.

The industrial Midwest occupies a middle ground. States like Michigan and Illinois still carry the weight of manufacturing decline, while states like Minnesota and Wisconsin have diversified more successfully. The regional average masks significant variation — Minnesota at 3.0% and Michigan at 5.3% are in the same census region but inhabit entirely different labor market realities.

The Northeast shows its own divide: the small northern New England states (Vermont, New Hampshire, Maine) have tight labor markets driven by low population and tourism-based economies, while the more urbanized mid-Atlantic states (New Jersey, Rhode Island, Connecticut) have higher rates reflecting deindustrialization, higher costs, and more complex labor markets.

The South is the most heterogeneous region. Virginia and Maryland benefit from federal employment. Florida’s tourism and migration-driven economy keeps unemployment moderate. But Kentucky’s Appalachian counties and Mississippi’s Delta region represent some of the most chronically underemployed areas in the country. The South’s average rate of 3.6% conceals a wider internal range than any other region.

Raw state counts treat South Dakota (population 920,000) the same as California (population 39 million). But the labor market experience of 42 times as many people depends on California’s rate, not South Dakota’s. To understand what the “typical” American worker actually faces, it is essential to look at the most populous states.

The table reveals a striking fact: California alone accounts for roughly 15% of all unemployed Americans. The state has 12% of the national population but 15% of its unemployment, a direct consequence of its above-average rate. Add Illinois and Michigan, and three states account for nearly a quarter of all American unemployment. This is why the national rate is pulled above the state median — the highest-unemployment states are among the largest.

Conversely, the tight-labor-market states are mostly small. South Dakota, Vermont, North Dakota, Montana, and Nebraska have a combined population of roughly 4.5 million — barely more than the Phoenix metropolitan area. Their ultra-low unemployment rates, while remarkable for those who live there, barely register in the national calculation.

The population-weighted view suggests that the national rate of 4.1%, while a reasonable average, understates the unemployment challenge in the places where most Americans actually live and work. The largest states tend to have rates at or above the national figure. The tightest labor markets tend to exist in the smallest states. There is a structural inverse relationship between state population and labor market tightness that has persisted for decades.

One of the most striking features of state unemployment data is its persistence. The states at the top and bottom of the ranking in January 2025 are largely the same states that have occupied those positions for years — and in some cases, for decades.

Nevada has ranked in the top five for unemployment in nearly every year since 2008. California has been above the national average for most of the past two decades. Michigan’s structural challenges predate the Great Recession by a generation. On the other end, South Dakota, Nebraska, and North Dakota have been in the bottom ten continuously since the BLS began publishing comparable LAUS data.

This persistence tells us something important about the nature of state-level unemployment. It is not primarily a cyclical phenomenon — if it were, states would rotate in and out of the extremes as business cycles turn. Instead, the ranking reflects structural features of state economies that change slowly if at all: industry composition, population dynamics, educational attainment, regulatory environment, cost of living, and geographic connectivity.

The implication for policymakers is sobering. States with persistently high unemployment cannot simply wait for the business cycle to solve their problems. Nevada’s dependence on gaming, Kentucky’s coal transition, Michigan’s manufacturing legacy — these are structural conditions that require structural solutions. And the evidence from decades of LAUS data suggests that such solutions are difficult, slow, and often incomplete.

Conversely, the persistently tight labor markets in the Plains states are not the result of any particular policy triumph. They are the product of demographic stability, economic diversification that happened organically over decades, and the inherent advantages of small economies where supply and demand stay naturally balanced. Other states can learn from these conditions, but they cannot easily replicate them.

The unemployment map of America, as of January 2025, carries several lessons that the national rate alone cannot convey.

First, the range matters. A 3.9 percentage point spread between the lowest and highest states represents a 3:1 ratio. In practical terms, the probability of being unemployed in Nevada is three times higher than in South Dakota. This is not a marginal difference. It is a different labor market reality — different search times, different employer power, different wage dynamics, different economic anxiety.

Second, geography predicts unemployment better than almost any other variable. Knowing that a worker lives in the Great Plains tells you more about their unemployment risk than knowing their age, education level, or occupation. Geography is not destiny, but it is a powerful sorting mechanism that concentrates labor market advantage and disadvantage in predictable patterns.

Third, the national rate is a useful fiction. It is useful because it provides a benchmark, a reference point, a single number that markets and policymakers can track. It is a fiction because no one experiences the national labor market. Workers experience local labor markets — state markets, metropolitan markets, county markets. The LAUS data exist precisely to bridge the gap between the national fiction and the local reality.

Fourth, industry concentration is the common thread among high-unemployment states. Nevada (gaming), California (tech concentration in a narrow geographic band while the rest of the state lacks it), Kentucky (coal legacy), Michigan (auto manufacturing), Alaska (oil/fishing) — these are states where a single sector or a single sector’s decline defines the labor market. Diversification is the structural antidote to volatility, and the states that have achieved it — Minnesota, Virginia, Nebraska — are the ones with the most stable, lowest unemployment rates.

Fifth, size works against labor market tightness. The tightest labor markets are in the smallest states. As population grows, labor markets become more complex, more stratified, and more prone to mismatches between the skills workers have and the skills employers need. There may be an inherent trade-off between economic scale and labor market tightness that no policy can fully overcome.

For reference, here are all 51 jurisdictions ranked by unemployment rate from highest to lowest, grouped by rate band.

Behind the numbers lies a structural story about what makes state labor markets work — or not work. The data points to four factors that explain most of the variation across states.

Industry diversification. States with broadly diversified economies — where no single sector accounts for more than 15% of employment — tend to have lower, more stable unemployment. Minnesota, Virginia, Nebraska, and Maryland exemplify this pattern. States where a single sector dominates — Nevada (gaming), Alaska (oil), Kentucky (coal legacy) — are more vulnerable to sector-specific shocks and tend to rank higher on the unemployment list.

Population stability. States with stable or slowly growing populations tend to have tighter labor markets because labor supply and demand evolve at similar rates. The Plains states — South Dakota, North Dakota, Nebraska — grow slowly if at all. Their economies do not need to generate new jobs at a furious pace to keep up with population growth. By contrast, states experiencing rapid in-migration — Nevada, Colorado, Arizona, Texas — must create hundreds of thousands of new jobs per year just to maintain their unemployment rates, a task that becomes more difficult during economic slowdowns.

Educational attainment. States with higher educational attainment tend to have lower unemployment, though the relationship is not linear. The connection works through multiple channels: educated workers are more adaptable, more mobile, and more likely to work in sectors with lower cyclical volatility. States like Massachusetts, Minnesota, and Colorado have among the highest educational attainment in the nation. But educational attainment alone does not guarantee low unemployment — California and New York have high educational attainment and above-average unemployment, because their labor markets are complex enough that other factors dominate.

Cost of living. States with lower costs of living tend to have lower unemployment, in part because lower costs reduce the reservation wage — the minimum wage a worker requires to accept a job. When housing, food, and transportation are affordable, workers accept jobs more quickly, employers can offer more positions at attainable wage levels, and the frictional unemployment that comes from extended job searches is minimized. The Plains states benefit enormously from this dynamic. California and New York are penalized by it.

The state unemployment map carries practical implications for both sides of the labor market.

For workers, the data underscores the power of geographic mobility. A worker who moves from Nevada (5.8%) to South Dakota (1.9%) does not just change addresses — they change their probability of employment by a factor of three. This is, of course, an oversimplification: the specific jobs available, the cost of moving, the social ties left behind, and the industries in each state all matter enormously. But the raw probability shift is real, and for workers in high-unemployment states with portable skills, geographic arbitrage remains one of the most effective labor market strategies available.

For employers, the map inverts the desirability index. A company seeking abundant, affordable labor should look to the high-unemployment states where job seekers outnumber openings. A company seeking to minimize turnover and find deeply committed workers should look to the tight-labor-market states where every hire is hard-won and retention is paramount. The trade-offs are real: tight labor markets mean higher wages and more competition for talent, but they also mean lower absenteeism, higher engagement, and a workforce that values stability.

For policymakers, the persistence of the state ranking is the most important finding. States that have been at the top of the unemployment list for years or decades cannot expect cyclical recovery to solve their structural problems. They need targeted interventions: workforce retraining, industry attraction, infrastructure investment, educational improvement. And these interventions take years or decades to produce measurable results, which creates a political challenge — the payoffs arrive long after the officials who approved them have left office.

The LAUS data will not change any of these realities. But it makes them visible. And visibility is the first requirement of any solution.