Economic Indicators

Real data from U.S. government sources — with plain-English context for every chart.

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Monthly Change in Nonfarm Payrolls

Number of jobs the U.S. economy added or lost each month — the most-watched number in the monthly jobs report.

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  • The BLS CES employment report is one of the most closely watched economic releases, with financial markets often reacting immediately when it is published on the first Friday of each month.
  • What are nonfarm payrolls? Nonfarm payrolls measures total paid employees at all U.S. businesses except farms, private households, nonprofit organizations, and the unincorporated self-employed.
  • Revisions from prior months are common and can be significant.
  • Learn more about the CES Survey

Employment Change by Industry

Nonfarm payroll employment change broken out by major industry sector (roughly 2-digit NAICS), ranked from the largest gain to the largest loss.

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  • Ranks the 14 CES supersectors (BLS's closest approximation to 2-digit NAICS, including Government) by the selected Change Period. These 14 categories don't overlap — summed together, they equal the total change in Nonfarm Payrolls for the same period.
  • Hover any bar for that industry's latest monthly change, a bar chart of its last 12 months of monthly changes, and whether the latest month is running above or below its own recent 3-month trend.
  • YTD (Year-to-Date) shows the cumulative change since December of the prior year — e.g. a July 2026 reading compares to December 2025. 12 Month shows the change over the trailing year — July 2026 compares to July 2025.
  • Learn more about the CES Survey
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Labor Force Participation Rate

The share of the civilian noninstitutional population working or actively job hunting.

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  • Prime-age workers (25–54) are past typical school years and before typical retirement age, making their participation rate the clearest read on core labor market attachment.
  • Overall LFPR peaked near 67% in 2000 and has trended down over two decades, primarily reflecting population aging rather than structural job market weakness.
  • Prime-age LFPR has broadly recovered to near pre-pandemic levels (around 83–84%), suggesting the overall rate decline overstates true labor force disengagement. A rising rate can push unemployment higher as more people enter the job search.
  • Learn more about the Current Population Survey

Measures of Unemployment

Three BLS measures of labor market slack — from the narrow long-term unemployment rate to the official rate to a broad underutilization gauge that captures discouraged workers and the underemployed.

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  • U-1 — Persons unemployed 15 weeks or longer, as a percent of the civilian labor force. The most restrictive measure: only the persistently jobless.
  • U-3 (Official) — The headline rate: jobless people who actively searched for work in the past 4 weeks and are available to start. The Federal Reserve targets full employment using this measure.
  • U-6 — The broadest measure: adds marginally attached workers (including discouraged workers who've given up searching) and people working part-time for economic reasons (involuntary part-time).
  • When U-6 is significantly above U-3, there is substantial underutilization beyond what the headline rate captures — for example, if U-3 is 4% but U-6 is 7.5%, roughly 3.5 percentage points of the workforce is underemployed or discouraged.
  • Below ~5% U-3 is historically considered near full employment; the gap between U-3 and U-6 tends to narrow in tight labor markets.
  • Learn more about the Current Population Survey

Employment-to-Population Ratio

The share of the civilian noninstitutional population that is currently employed — a broad measure of labor market health unaffected by labor force exit.

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  • Unlike the unemployment rate, the Employment-to-Population ratio doesn't change when discouraged workers stop searching.
  • Prime-age workers (25–54) strip out the distorting effects of school enrollment and retirement trends, providing a cleaner signal of whether the core workforce is employed.
  • Overall EPOP fell sharply in 2020 and has gradually recovered, but remains below its pre-2020 peak — partly reflecting continued population aging.
  • Prime-age EPOP has recovered more fully and reached historically high levels in recent years, suggesting underlying labor demand has been strong for core working-age adults even as overall EPOP lags.
  • Learn more about the Current Population Survey

Job Openings, Hires, and Separations

Monthly hiring, quitting, and layoff activity from the JOLTS survey — pick a concept below, shown as either a level or a rate.

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  • BLS' JOLTS survey measures labor market dynamics by tracking the following concepts:
    • Job Openings — all positions open on the last business day of the month that could start within 30 days, for which the employer is actively recruiting.
    • Hires — all additions to payrolls during the month, including new and rehired employees.
    • Total Separations — all separations from employment during the month, broken out into three subcategories:
      • Quits — employees who left voluntarily (excluding retirements). A closely watched gauge of worker confidence: quits rise when workers feel secure enough to leave for something better, and fall when they don't.
      • Layoffs and Discharges — involuntary separations initiated by the employer: layoffs, discharges, and other terminations.
      • Other Separations — separations that are neither quits nor layoffs and discharges, such as retirements, deaths, disability, and transfers to another location.
  • Rates express each concept as a percentage of employment (Job Openings Rate uses employment plus job openings) rather than a raw count, making levels comparable across time even as the size of the workforce changes. The employment concept JOLTS uses for this is the same one CES uses for Total Nonfarm Payroll Employment — the same series behind the "Monthly Change in Nonfarm Payrolls" chart above.
  • Job openings, hires, and separations are all reported with about a month's lag relative to the unemployment rate for the same reference month.
  • Learn more about the Job Openings and Labor Turnover Survey
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Unemployed Persons per Job Opening

The number of unemployed workers for every available job opening — a key gauge of labor market slack and tightness.

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  • A ratio of 1.0 means there is exactly one unemployed worker for each open job — a roughly balanced labor market.
  • Ratios significantly below 1.0 indicate a tight labor market with more openings than job seekers, often putting upward pressure on wages.
  • Ratios above 1.0 indicate slack — more job seekers than openings. Recessions are marked by significantly or persistently higher ratios, with peaks reaching 5–7 during the Great Recession and COVID.
  • Job openings data (JOLTS) is released about a month after the unemployment figure for the same month, so the most recent point may lag.
  • Learn more about the Job Openings and Labor Turnover Survey

U.S. Population by Labor Status (Employed, Unemployed, Not in Labor Force)

The civilian noninstitutional population aged 16+ broken into three mutually exclusive groups that sum to the total population at every point in time.

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  • Labor force = Employed + Unemployed. The unemployment rate measures jobless share of the labor force, not of total population.
  • Employed + Unemployed + Not in Labor Force = Civilian Noninstitutional Population (16+).
  • The "Not in Labor Force" category is large (~105M) and growing with an aging population — retirees, students, caregivers, and discouraged workers all count here.
  • Watch for the blue employed area contracting relative to gray NILF as a sign of structural labor force withdrawal.
  • Learn more about the Current Population Survey
GDP Overview

Real GDP

The inflation-adjusted total value of all goods and services produced in the U.S. in a quarter.

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  • Two consecutive quarters of negative GDP growth is the informal definition of a recession.
  • "Real" GDP removes the effect of inflation, making comparisons across time meaningful.
  • GDP growth above ~2% annually is generally considered healthy for a mature economy like the U.S.

Contribution to Real GDP Growth

How many percentage points each component (C, I, G, NX) added to or subtracted from quarterly GDP growth. Bars sum to total GDP growth.

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  • Consumer spending (C) typically contributes the most to GDP growth in healthy quarters.
  • Net exports (NX) contribution is usually small and often negative due to persistent U.S. trade deficits.
  • Investment (I) is the most volatile component — large swings signal shifting business confidence.
  • Source: BEA NIPA Table 1.1.2 — Contributions to Percent Change in Real GDP.
GDP Components — Detail

Personal Consumption (C)

Household spending on goods and services — the largest single component of GDP (~70%).

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  • Because consumer spending drives roughly 70% of the economy, this is the single most important GDP component to watch for signs of slowing growth.
  • Services (~65% of PCE) — intangible things you consume: doctor visits, rent, streaming subscriptions, haircuts. The largest and most stable slice; it rarely falls sharply even in downturns.
  • Nondurable Goods (~22% of PCE) — physical items used quickly: groceries, gas, clothing. Moderately volatile and sensitive to price changes (especially energy).
  • Durable Goods (~13% of PCE) — big-ticket items expected to last 3+ years: cars, appliances, furniture. The most volatile PCE component — it swoops down in recessions (people delay purchases) and bounces back fast.

Gross Private Investment (I)

Business spending on equipment, structures, and IP, plus residential construction and inventory changes.

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  • Investment is the most volatile GDP component — it falls sharply in recessions and tends to lead recoveries. Businesses cut spending on new equipment and construction long before consumers pull back.
  • Nonresidential Investment — business spending on long-lived productive assets. The broadest measure of private investment in capacity, spanning physical infrastructure, machinery, and knowledge assets.
    • Equipment — machines, computers, vehicles, and industrial tools that businesses use to produce goods and services. Rises when firms are confident about future demand.
    • Structures — factories, warehouses, office buildings, pipelines, and utility installations. Long construction lead times make this a lagging indicator — projects already in progress keep investment elevated even after conditions soften.
    • Intellectual Property Products — software, research & development, and entertainment originals (films, TV shows). The fastest-growing component over the past 30 years, reflecting the shift toward a knowledge-based economy.
  • Residential Investment — single-family homes, apartment buildings, manufactured housing, and renovations. Highly sensitive to mortgage rates; typically the first component to turn at a cycle peak and trough.
  • Inventory Change — the net change in unsold goods held by businesses. Can swing sharply: businesses build inventories in anticipation of demand and run them down in downturns. Negative inventory change subtracts from GDP even if final sales are strong.

Government Spending (G)

Federal, state, and local government spending on goods, services, and investment in infrastructure.

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  • This measures only direct government purchases of goods and services — it does not include transfer payments like Social Security or Medicare. Those programs redistribute income but don't represent government directly buying something produced.
  • Federal Defense — military pay, weapons procurement, operations, and maintenance. Driven by policy decisions and overseas commitments rather than the business cycle. Often counter-cyclical: defense spending has held steady or grown during recessions.
  • Federal Nondefense — spending by civilian agencies: the National Park Service, NASA, federal courts, infrastructure grants, and more. The smallest of the three components and relatively stable year-to-year.
  • State & Local — the largest government component. Covers schools, roads, bridges, police, fire departments, and other services that shape daily life. Unlike the federal government, most states must balance their budgets — so this component tends to be pro-cyclical, shrinking in recessions when tax revenues fall.

Net Exports

The inflation-adjusted value of U.S. exports minus imports — a negative value means the U.S. imports more than it exports (trade deficit).

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  • The U.S. has run a persistent trade deficit for decades, meaning imports exceed exports.
  • A weaker dollar makes U.S. exports cheaper abroad and tends to improve net exports over time.
  • Trade deficits are not inherently bad — they often reflect strong domestic demand for foreign goods.
Income & Savings

Real Disposable Income Per Capita

After-tax personal income per person, adjusted for inflation — what the average American actually has to spend or save.

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  • Real per capita DPI is one of the best single measures of living standards over time.
  • Stagnant or falling real DPI — even with nominal wage gains — signals inflation is outpacing income.
  • Rising real DPI generally supports consumer spending and broad economic growth.

Personal Saving Rate

Personal saving as a percentage of disposable personal income — how much of after-tax income households are saving vs. spending.

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  • A very low saving rate can signal households are financially stretched or spending freely on confidence.
  • Saving rates spiked during COVID-19; the drawdown since drove strong consumer spending in 2021–2023.
  • Structural decline in saving can eventually constrain consumption if households become overleveraged.

Income Growth vs. Inflation

Year-over-year percent change in average hourly earnings vs. headline CPI. When wages grow faster than prices, workers gain purchasing power. When inflation outpaces wages, real incomes shrink.

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Source: Bureau of Labor Statistics · CES & CPI-U (SA)

  • The gap between wage growth and inflation — sometimes called "real wage growth" — is the single clearest indicator of whether workers are getting ahead or falling behind.
  • From 2021 to 2023, inflation surged well above wage growth, eroding purchasing power. The gap has since narrowed significantly.
  • Average hourly earnings are a broad nominal wage measure. They don't account for taxes or benefits, but they're the most timely monthly signal available.
  • BLS series: Avg. Hourly Earnings — CES0500000003 · Headline CPI — CUSR0000SA0. Both seasonally adjusted.
Credit & Debt

Household Debt Service Ratio

The share of after-tax income that households devote to required debt payments — mortgage principal and interest, plus consumer debt (credit cards, auto, student loans, etc.). A rising ratio means more income is going to debt obligations, leaving less to spend or save.

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Source: Federal Reserve · Financial Accounts of the United States · FRED: TDSP

  • A high debt service ratio limits consumer spending and makes households more vulnerable to income shocks like job loss or a recession.
  • The ratio rose sharply before the 2008 financial crisis as mortgage debt ballooned, then fell as households deleveraged and interest rates declined.
  • Rising interest rates push this ratio higher even if debt balances hold steady, as new borrowing costs more to service.
  • FRED series: TDSP — Seasonally adjusted, quarterly.

Delinquency Rates by Loan Type

The percentage of outstanding loans where payments are 30 or more days past due, reported by commercial banks. Rising delinquency signals growing financial stress among borrowers.

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Source: Federal Reserve · Charge-Off and Delinquency Rates · federalreserve.gov

  • Credit card delinquency is the most sensitive and fastest-moving indicator — consumers typically miss card payments before missing mortgage or installment loan payments.
  • Mortgage delinquency is the most economically consequential — it often spills into foreclosures and can destabilize housing markets.
  • Other Consumer Loans covers all non-credit-card consumer installment debt at commercial banks: auto loans, personal loans, and student loans. It provides a broader read on household borrowing stress beyond the credit card signal.
  • Delinquency spikes during recessions (2001, 2008–2009, 2020) are clearly visible; the COVID spike was brief due to widespread forbearance programs.
  • FRED series: Credit Cards — DRCCLACBS · Other Consumer Loans — DROCLACBS · Mortgages — DRSFRMACBS. Quarterly, SA.
Consumer Price Index (CPI)

Consumer Prices — Year-over-Year Change

CPI components shown as a year-over-year percent change — useful for understanding current inflation dynamics. Headline and Core shown by default; click the legend to add Food and Energy.

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Source: Bureau of Labor Statistics · CPI-U (Not Seasonally Adjusted) · bls.gov/cpi

  • Year-over-year (YoY) change compares prices to the same month a year ago, which smooths out seasonal patterns — this is the figure most often cited as "the inflation rate."
  • Cumulative (Change Type toggle above) instead indexes each line to 100 at the same calendar month N years before the latest reading — e.g. at 5Y, June 2026 vs. June 2021 — so you can read off total price growth over that specific window: a value of 112 means prices are 12% higher than they were five years ago. Changing the Time Period re-bases the index to that window's own starting month rather than a fixed calendar date.
  • When headline and core diverge sharply, energy or food is the driver — not broad-based demand-side inflation.
  • Headline CPI (CUUR0000SA0) includes all items in the basket and is the broadest measure of consumer inflation.
  • Core CPI (CUUR0000SA0L1E) excludes food and energy to reveal the underlying inflation trend less distorted by commodity volatility.
  • Food (CUUR0000SAF1) covers groceries (food at home) and restaurant meals (food away from home).
  • Energy (CUUR0000SA0E) includes gasoline, electricity, natural gas, and heating oil — one of the most volatile CPI components, often driving the gap between headline and core inflation.
  • Learn more about the Consumer Price Index

Consumer Price Changes by Category

The Consumer Price Index (CPI) measures the average change in prices paid by U.S. consumers for a basket of goods and services.

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Source: Bureau of Labor Statistics · CPI-U (Not Seasonally Adjusted) · bls.gov/cpi

  • A curated set of detailed expenditure categories, ranked from biggest increase to biggest decrease. Each bar is a category's cumulative price change over the selected period — for example, at 5Y a value of +22% means prices in that category are 22% higher than the same month five years ago. This uses not seasonally adjusted data (CUUR series), standard for comparisons of a year or more since the same calendar month is compared across each period.
  • Relative importance (shown on hover) is the percentage weight a category carries in the overall CPI basket — roughly the share of a typical urban household's spending that goes to it. A high-weight category like shelter moves the headline inflation rate far more than a low-weight one like airline fares, even for the same percent change. Weights are published by the BLS and updated over time as spending patterns shift. Hover any bar to see its full place in the CPI hierarchy.
  • Unlike PPI (see the Producer Price Index section below), CPI reflects prices for both domestically produced and imported goods and services — whatever a U.S. consumer actually buys, regardless of where it was made.
  • See the official BLS Table 2 (all detailed expenditure categories with relative importance)
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Producer Price Index (PPI)

Producer Prices — Year-over-Year Change

The Producer Price Index (PPI) measures the average change over time in the prices received by domestic producers for their output. PPI changes can signal upstream price pressures that may eventually reach consumers.

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Source: Bureau of Labor Statistics · Producer Price Index (Not Seasonally Adjusted) · bls.gov/ppi

  • Because PPI sits earlier in the supply chain, rising producer costs often feed into consumer prices with a lag of one to six months, making PPI a useful leading indicator for CPI trends.
  • Year-over-year (YoY) change compares prices to the same month a year ago, which smooths out seasonal patterns.
  • Cumulative (Change Type toggle above) instead indexes each line to 100 at the same calendar month N years before the latest reading — e.g. at 5Y, June 2026 vs. June 2021 — so you can read off total price growth over that specific window. Changing the Time Period re-bases the index to that window's own starting month rather than a fixed calendar date.
  • Total Final Demand (WPUFD4) is the broadest headline measure.
  • FD less Food, Energy & Trade (WPUFD49116) strips out the three most volatile components — sometimes called "core" PPI — and is watched by the Fed as a signal of underlying producer price pressure.
  • FD Food (WPUFD411) — unprocessed and processed food products sold for final use.
  • FD Energy (WPUFD412) — electricity, natural gas, and petroleum products sold to final users.
  • FD Trade Services (WPUFD423) — retailer and wholesaler margins; measures the change in margins received by trade businesses rather than the price of goods themselves.
  • Learn more about the Producer Price Index

Producer Price Changes by Category

Ranking of the average change in prices received by domestic producers for a variety of goods and services.

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Source: Bureau of Labor Statistics · PPI Commodity & Service Indexes (Not Seasonally Adjusted) · bls.gov/ppi

  • PPI is worth watching as an early-warning signal for where consumer price pressure may be building. For example: a steel producer raises its price → a manufacturer's input costs rise → a wholesaler or retailer passes along the higher cost plus its own margin → the consumer eventually pays more — often with a lag of one to six months.
  • PPI focuses on domestic production only — it captures prices received by U.S.-based producers for their own output. Unlike CPI, it does not reflect the price of imported goods or services.
  • Each bar is a category's cumulative price change over the selected period — for example, at 5Y a value of +22% means producer prices in that category are 22% higher than the same month five years ago.
  • Learn more about the Producer Price Index
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Private Construction Spending by Category

Monthly spending on new private construction projects, split into five closely-watched categories plus an "All Other" catch-all for every other type of private construction.

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Source: U.S. Census Bureau · Value of Construction Put in Place Survey (C30) · census.gov/construction/c30

  • Value of Construction Put in Place is the Census Bureau's own measure of construction activity: the value of construction work actually completed — put in place — during the month, not the total value of contracts signed or materials purchased but not yet installed. That makes it a real-time read on construction activity itself, rather than a backlog of future work. Learn more about the Construction Spending Survey
  • This chart lets you explore private construction spending through three different concepts:
    • Levels shows seasonally adjusted annual rate (SAAR) spending in dollars — the standard way to compare month-to-month levels without the distortion of predictable seasonal patterns (e.g. more construction activity in summer than winter). SAAR (Seasonally Adjusted Annual Rate) takes that month's seasonally adjusted pace of spending and scales it up to what a full year would total if that same pace continued — the standard way construction spending is reported, so any single month's figure is directly comparable to any other month's, without needing to wait for a full year of data.
    • YoY Growth shows the year-over-year percent change in each category, using not-seasonally-adjusted data — comparing the same calendar month across years is already seasonally comparable, so this is the standard growth-rate convention (matching the CPI/PPI charts elsewhere on this page).
    • Index re-bases each category's seasonally adjusted level to 100 at the start of the selected Time Period, so categories of very different sizes (e.g. Residential vs. Data Center) can be compared on the same relative-growth scale.
  • Spending Categories:
    • Residential — new single-family and multifamily construction, plus improvements to existing homes (excludes rental, vacant, and seasonal properties).
    • Data Center — facilities built to house computing and server infrastructure. The fastest-growing category on this chart in recent years, driven by AI and cloud-computing buildouts.
    • Health Care — hospitals, medical office buildings, and other special care facilities.
    • Power — electric power generation and transmission facilities, including gas and oil.
    • Manufacturing — factories and industrial production facilities, spanning sub-sectors like food/beverage, chemical, plastics/rubber, metals, and computer/electronic/electrical.
    • All Other — every other private construction category not listed above: lodging, offices, retail, warehouses, education, religious, amusement/recreation, transportation, and communication. Derived as Total Private Construction minus the five named categories above.
    • See Census's definitions for each construction category
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Housing Starts, Completions & New Home Sales

Seasonally adjusted annual rate (SAAR) of new privately-owned housing units started, completed, and sold — three different stages of the same residential construction pipeline, from ground-breaking to occupancy-ready supply to buyer demand.

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Source: U.S. Census Bureau · New Residential Construction & New Residential Sales Surveys

  • Housing Starts counts new privately-owned housing units at the moment construction begins — when excavation starts for the footings or foundation. All units in a multifamily building are counted as started at once, at that same moment.
  • Housing Completions counts new privately-owned housing units once construction is finished — specifically, once all finished flooring (or carpeting in its place) has been installed, or at the time of occupancy if the building is occupied before construction is fully finished. In multi-unit buildings, every unit is counted as completed once 50% or more of the units are occupied or available for occupancy.
  • New Home Sales (from the separate New Residential Sales survey) counts newly built single-family homes sold — meaning a sales contract is signed or a deposit accepted — regardless of how far along construction is. This includes homes sold from a model or from plans before any work has started, sold while under construction, or sold after completion, making it a leading indicator of buyer demand rather than of construction activity itself.
  • All three series are seasonally adjusted annual rates (SAAR) — see the SAAR explanation in the chart above.
  • See Census's full Survey of Construction definitions
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Ember State Performance Index

A composite index of five indicators measuring each state's economic performance relative to the U.S. average. 100 = U.S. baseline; above 100 indicates stronger performance, below 100 indicates weaker performance.

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  • What it measures: The Ember State Performance Index combines five key indicators into a single score that captures whether a state economy is running faster or slower than the national baseline. A score of 100 indicates that a state's overall economic performance is aligned with the national trend. Scores above 100 reflect stronger relative growth, while scores below 100 reflect weaker growth. Individual indicators may still outperform or underperform the U.S. even when the composite index is near 100.
  • Real GDP Growth
    • Weight: 30%
    • Definition: Percent change in real GDP (chained 2017 dollars). The broadest measure of economic output and the primary driver of the index. Directly comparable across states and to the national accounts.
    • Time Period: Most recent quarter vs. year-ago quarter
    • Source: BEA SQGDP9
    • Latest Update:
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  • Payroll Employment Growth
    • Weight: 25%
    • Definition: Percent change in nonfarm payroll employment (jobs located in the state, not seasonally adjusted). Captures the labor market's absorptive capacity and reflects business investment decisions in real time. A reliable concurrent indicator of consumer spending.
    • Time Period: Most recent month vs. year-ago month
    • Source: BLS State and Area Employment (SAE) / CES
    • Latest Update:
    • Next Update:
  • Personal Income Growth
    • Weight: 20%
    • Definition: Real percent change in personal income, deflated by the national PCE price index. Covers wages, salaries, and transfer payments. Note: the national deflator removes aggregate inflation but does not capture state-level price differences.
    • Time Period: Most recent quarter vs. year-ago quarter
    • Source: BEA SQINC1; PCE deflator: BEA NIPA T20304
    • Latest Update:
    • Next Update:
  • Population Growth
    • Weight: 15%
    • Definition: Percent change in resident population. Sustained in-migration expands the labor force and drives demand for housing, retail, and services — a medium-term signal of structural economic capacity.
    • Time Period: Most recent quarter vs. year-ago quarter
    • Source: BEA SQINC1 LineCode 2
    • Latest Update:
    • Next Update:
  • Residential Building Permits
    • Weight: 10%
    • Definition: Percent change in rolling 12-month total permits issued. A forward-looking indicator of housing construction, developer confidence, and household formation expectations.
    • Time Period: 12-month sum, most recent vs. year-ago
    • Source: Census Bureau BPS via FRED
    • Latest Update:
    • Next Update:
  • Methodology: Each indicator is standardized relative to the U.S. average using z-scores, allowing states to be compared across metrics with different scales and volatility. States performing above the national trend receive positive contributions, while states below trend receive negative contributions. Extreme values are capped to reduce the influence of outliers. The standardized indicators are then combined using the weights above and scaled so that 100 represents the U.S. average.
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State GDP by Industry

Percent change in real GDP (chained 2017 dollars) for each U.S. state and D.C.

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Industry:

  • Real Gross Domestic Product (GDP) is adjusted for inflation and is measured in chained 2017 dollars. Accounting for inflation removes the effect of price changes so that comparisons reflect actual output growth.
  • A state's GDP is influenced by a variety of factors, including population, labor force participation, worker productivity, industry composition, business investment, consumer demand, and availability of natural resources.
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State Industry Snapshot - Real GDP

Comparison of states by an industry's economic importance measured by share of state GDP, growth, and GDP level.

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  • How to read this chart:
    • Position along the horizontal axis — the industry's share of the state's own GDP.
    • Position along the vertical axis — the industry's percent growth over the selected time period.
    • Bubble size — the industry's real GDP level in that state, scaled relative to the largest state shown. Sizes are only comparable within the current industry — switching industries resets the scale, so bubble sizes can't be compared across different industries.
  • The dashed reference lines mark the industry's national share and national growth rate, calculated the same way from the U.S. row, splitting the chart into four quadrants:
    • High Share / High Growth — Leaders: the industry makes up a bigger share of the state's economy than it does of the U.S. economy, and it's growing faster in the state than the U.S. average for this industry.
    • High Share / Low Growth — Mature: the industry makes up a bigger share of the state's economy than it does of the U.S. economy, but it's growing slower in the state than the U.S. average for this industry.
    • Low Share / High Growth — Emerging: the industry makes up a smaller share of the state's economy than it does of the U.S. economy, but it's growing faster in the state than the U.S. average for this industry.
    • Low Share / Low Growth — Lagging: the industry makes up a smaller share of the state's economy than it does of the U.S. economy, and it's growing slower in the state than the U.S. average for this industry.
  • Share is each industry's GDP divided by the sum of all industries in that state, not BEA's official "All Industries" total. We use the sum instead because of a quirk in how BEA calculates inflation-adjusted GDP: the parts don't always add up exactly to the published total. Using the sum keeps every state's industry shares adding up to a clean 100%, though it means the state totals implied here may differ very slightly from the official figures shown elsewhere on this page.
  • Why do some states show a ranking out of a number less than 51? States whose data for the selected industry is suppressed by BEA (see the disclosure note below) are excluded from the chart and its rankings entirely. For example, seven states are suppressed for Agriculture & Forestry, so rankings for that industry only go up to 44.
  • Disclosure of confidential information: when too few establishments make up an industry in a state, BEA suppresses the actual figure to protect the confidentiality of individual companies — shown as "(D)" on BEA's own data tables. Because a suppressed value doesn't mean an industry has no activity (the real figure is simply unpublished), affected states are excluded from this chart and its rankings for the selected industry, and are listed in the red note just below the Industry and Focus Region dropdowns above.
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Real GDP - Head to Head Region Comparison

Real GDP by industry — levels or growth. Click any column header to sort.

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Time Period:

  • Data source: BEA State Quarterly GDP by Industry (SQGDP9), real GDP in chained 2017 dollars.
  • Disclosure issue: for some state/industry combinations, BEA doesn't publish a figure — usually because too few companies operate in that industry in that state, and reporting a number could reveal information about a specific business. When that happens for the current period or the comparison period being measured, the cell shows "N/A" instead of a misleading percentage, and that row's difference column(s) show "N/A" too.
  • Levels and the difference columns: when Levels is selected, comparing a state's dollar GDP level against the United States as a whole isn't meaningful — the U.S. total dwarfs any single state — so Level Diff and Percent Diff both show "N/A" whenever either Focus or Comparison Region is set to United States. Choose two states to see a level and percent difference instead.
  • Total Private and Total Government: BEA doesn't publish these as their own SQGDP9 line items, so they're computed here by summing the underlying industry levels ourselves (Total Government = Federal Civilian + Military + State & Local). Because inflation-adjusted GDP components don't always add up exactly under BEA's chain-weighting methodology, Total Private plus Total Government may not sum precisely to All Industries.
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Real Personal Income by State

Inflation-adjusted percent change in personal income for each U.S. state and D.C.

Concept:
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  • Personal income is the sum of three components, each driven by different economic forces:
    • Earnings — wages and salaries, employer supplements (pension and health-insurance contributions), and proprietors' income. The largest component; moves closely with employment and hours worked.
    • Personal current transfer receipts — government payments such as Social Security, Medicare, Medicaid, unemployment insurance, and veterans' benefits. More stable and countercyclical: they typically rise during downturns.
    • Property income — dividends, interest, and rental income. More concentrated among higher-income households and sensitive to interest-rate cycles and stock market performance.
  • Inflation adjustment: growth rates shown are real — nominal personal income (BEA SQINC1) is deflated by the national PCE price index (BEA NIPA T20304). This removes the national inflation component so comparisons reflect purchasing-power gains rather than price-level increases.
  • Note, however, that state-level inflation differences exist but are not captured here. BEA Regional Price Parities show prices can vary significantly across states, with states like Hawaii and New York roughly 15–20% above the national average, while Mississippi and Arkansas are 13–15% below.
  • States that rely heavily on a few industries (ex: Federal Government in DC) are more likely to experience larger fluctuations in income when those industries perform well or poorly.
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Population Growth by State

Percent change in resident population for each U.S. state and D.C.

Concept:
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  • Population change is attributed natural change (births minus deaths), domestic migration (people moving to/from elsewhere in the U.S.), and international migration.
  • Following the pandemic, Florida and Texas experienced rapid population growth, though the pace has moderated in recent years.
  • Looking ahead, state-level population trends will be shaped by housing affordability, job opportunities, remote work policies, and other economic and demographic factors.
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State Employment by Industry

Percent change in nonfarm payroll employment for each U.S. state and D.C. Not seasonally adjusted. Hover over a state to see employment levels and net change.

Concept:
Time Period:
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Industry:

  • Nonfarm payroll employment, which counts jobs located in the state (an establishment survey), not people who live there. It excludes farm workers, household workers, the self-employed, and military, and is different from civilian/resident employment (LAUS), which some other BLS state employment figures use.
  • Figures are not seasonally adjusted — appropriate here since every comparison is the same month a year (or more) apart, which cancels the seasonal component by construction.
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State Industry Snapshot - Employment

Comparison of states by an industry's economic importance measured by share of state employment, growth, and employment level.

Time Period:

  • How to read this chart:
    • Position along the horizontal axis — the industry's share of the state's own employment.
    • Position along the vertical axis — the industry's percent growth over the selected time period.
    • Bubble size — the industry's employment level in that state, scaled relative to the largest state shown. Sizes are only comparable within the current industry — switching industries resets the scale, so bubble sizes can't be compared across different industries.
  • The dashed reference lines mark the industry's national share and national growth rate, calculated the same way from the U.S. row, splitting the chart into four quadrants:
    • High Share / High Growth — Leaders: the industry makes up a bigger share of the state's employment than it does of U.S. employment, and it's growing faster in the state than the U.S. average for this industry.
    • High Share / Low Growth — Mature: the industry makes up a bigger share of the state's employment than it does of U.S. employment, but it's growing slower in the state than the U.S. average for this industry.
    • Low Share / High Growth — Emerging: the industry makes up a smaller share of the state's employment than it does of U.S. employment, but it's growing faster in the state than the U.S. average for this industry.
    • Low Share / Low Growth — Lagging: the industry makes up a smaller share of the state's employment than it does of U.S. employment, and it's growing slower in the state than the U.S. average for this industry.
  • Share is each industry's employment divided by Total Nonfarm Payroll employment in that state. Unlike real GDP, employment counts add up exactly, so this matches the official state total shown elsewhere on this page.
  • Employment figures are not seasonally adjusted — appropriate here since every comparison is the same calendar month a year (or more) apart, which cancels the seasonal component by construction.
  • Why do some states show a ranking out of a number less than 51? States without a published figure for the selected industry (see the non-disclosure note below) are excluded from the chart and its rankings entirely.
  • BLS non-disclosure rules: not all sub-industries are published for every state — BLS withholds a figure when publishing it could reveal information about a small number of employers. States affected for the currently selected industry are listed in the red note just below the Industry and Focus Region dropdowns above.
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Employment - Head to Head Region Comparison

Nonfarm payroll employment by industry — levels or growth. Not seasonally adjusted. Click any column header to sort.

Concept:
Time Period:

  • Data source: BLS State and Area Employment (SAE) / Current Employment Statistics (CES). Nonfarm payroll employment — excludes farm workers, household workers, self-employed, and military. All figures are not seasonally adjusted — appropriate here since every comparison is the same calendar month a year (or more) apart, which cancels the seasonal component by construction.
  • Year-over-year comparison: each growth value compares the latest available month to the same month one year (or more) prior. A positive value means more jobs than at the anchor period in that sector.
  • Hierarchy: Total Nonfarm Payroll is the broadest measure. Total Private Industries covers all private industries. The Government row is likewise an aggregate — it sums the Federal, State, and Local sub-rows below it.
  • BLS non-disclosure rules: not all sub-industries are published for every state — BLS withholds a figure when publishing it could reveal information about a small number of employers. Those cells show "—".
  • Diff. column (pp): when Growth is selected, the percentage-point gap between Focus and Comparison YoY growth rates. Positive = Focus region growing faster than Comparison in that sector.
  • Levels and the difference columns: when Levels is selected, comparing a state's raw employment count against the United States as a whole isn't meaningful — the U.S. total dwarfs any single state — so Level Diff and Percent Diff both show "N/A" whenever either Focus or Comparison Region is set to United States. Choose two states to see a level and percent difference instead.
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Unemployment Rate

The share of the labor force that is jobless and actively looking for work.

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Concept:

  • From BLS' Local Area Unemployment Statistics (LAUS) survey — seasonally adjusted, the conventional way these rates are reported and compared. Always shows the most recent month available.
  • Unemployment Rate — the share of the labor force that is jobless and actively looking for work.
  • Labor Force Participation Rate — the share of the working-age population that is employed or actively looking for work.
  • Employment-Population Ratio — the share of the working-age population that is employed.
  • Ranking direction depends on which is "better": for Unemployment Rate, the lowest state is #1 and colored blue, the highest is red. For Labor Force Participation Rate and Employment-Population Ratio, it's reversed — the highest state is #1 and colored blue, the lowest is red.
  • Learn more about Local Area Unemployment Statistics
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Residential Building Permits by State

Percent change in 12-month rolling total residential building permits (all structure types) for each U.S. state and D.C. Hover over a state to see permit totals and the net change.

Concept:
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  • 12-month rolling total: rather than showing a single month (which is volatile for smaller states), each value sums the most recent 12 months of permits and compares it to the equivalent 12-month window one year prior — computed as ((Current 12-Month Total ÷ Prior 12-Month Total) − 1) × 100. This smooths seasonal noise and short-term construction lumpiness, giving a clearer picture of the underlying trend.
  • What permits measure: a residential building permit authorizes construction of a new housing unit before a single shovel breaks ground. Permit issuance is a leading indicator of residential investment — typically 1 to 3 months ahead of actual housing starts and 6 to 12 months ahead of completions. Rising permits signal that developers expect sufficient demand to justify new supply.
  • Permit activity is heavily influenced by mortgage rates, local zoning and land-use regulation, and construction input costs. States with restrictive zoning tend to show structurally lower permit volumes relative to population than states with more permissive land-use policies.
  • The growth rate of states with very small permit counts can swing dramatically on a single large multifamily project. Examine both levels and growth rates for a full picture.
  • Per 10,000 Residents: takes the 12-month rolling total of permits for a state and divides by that state's population, then multiplies by 10,000 — in other words, "how many permits per 10,000 people who live there." This puts every state on equal footing regardless of size, so a small state issuing a lot of permits relative to its population can outrank a much larger state with more permits in raw terms. Only the latest period is shown, since population is a point-in-time figure rather than something to compare across a time horizon.
  • Data source: U.S. Census Bureau Building Permits Survey (monthly, not seasonally adjusted) — the same underlying data published on census.gov/construction/bps, distributed via the Federal Reserve Economic Data (FRED) database. Population for the Per 10,000 Residents view comes from BEA's Regional Economic Accounts (SQINC1).
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High-Propensity Business Applications by State

Percent change in 12-month rolling total high-propensity business applications for each U.S. state and D.C. Hover over a state to see application totals and the net change.

Concept:
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  • What a "high-propensity" business application is: the Census Bureau classifies a subset of new business applications as "high-propensity" — those judged likely to become an actual employer business with a payroll. This includes applications from corporations, applications with a planned wage date, applications in industries with historically high startup rates, and applications that hire employees within the first few quarters. It excludes the large volume of sole-proprietor and side-business applications unlikely to ever hire staff, making it a better leading indicator of new job creation than total business applications.
  • 12-month rolling total: rather than showing a single month (which is volatile for smaller states), each value sums the most recent 12 months of high-propensity applications and compares it to the equivalent 12-month window one year prior — computed as ((Current 12-Month Total ÷ Prior 12-Month Total) − 1) × 100. This smooths seasonal noise and short-term filing lumpiness, giving a clearer picture of the underlying trend.
  • Why it matters: rising high-propensity applications signal entrepreneurial activity that is likely to translate into new hiring and business formation in the following months — typically showing up in payroll data within two to four quarters.
  • Per 10,000 Residents: takes the 12-month rolling total of high-propensity applications for a state and divides by that state's population, then multiplies by 10,000 — in other words, "how many applications per 10,000 people who live there." This puts every state on equal footing regardless of size, so a small state with a lot of entrepreneurial activity relative to its population can outrank a much larger state with more applications in raw terms. Only the latest period is shown, since population is a point-in-time figure rather than something to compare across a time horizon.
  • Data source: U.S. Census Bureau Business Formation Statistics (monthly, not seasonally adjusted) — the same underlying data published on census.gov/econ/bfs, distributed via the Federal Reserve Economic Data (FRED) database. Not seasonally adjusted data is appropriate here since the 12-month rolling total already accounts for seasonality. Population for the Per 10,000 Residents view comes from BEA's Regional Economic Accounts (SQINC1).
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Ember Maryland Performance Index

A composite index of five indicators measuring each Maryland county's economic performance relative to the statewide average. 100 = Maryland baseline; above 100 indicates stronger performance, below 100 indicates weaker performance.

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  • What it measures: The Ember Maryland Performance Index combines five key indicators into a single score that captures whether a county economy is running faster or slower than the Maryland statewide average. A score of 100 indicates that a county's overall economic performance is aligned with the statewide trend. Scores above 100 reflect stronger relative growth, while scores below 100 reflect weaker growth. Individual indicators may still outperform or underperform the statewide average even when the composite index is near 100. Same methodology and weights as the Ember State Performance Index on the State Data tab, just benchmarked against Maryland instead of the U.S., and county instead of state.
  • Real GDP Growth
    • Weight: 30%
    • Definition: Percent change in real GDP (chained 2017 dollars), All Industries.
    • Agency: U.S. Bureau of Economic Analysis (BEA)
    • Survey: Regional Economic Accounts
    • Table: CAGDP9 — Real GDP by County and Metropolitan Area
    • Frequency: Annual
    • Time Period:
    • Latest Publication:
    • Next Publication:
  • Employment Growth
    • Weight: 25%
    • Definition: Percent change in total covered employment, all industries and ownership sectors (not seasonally adjusted).
    • Agency: U.S. Bureau of Labor Statistics (BLS)
    • Survey: Quarterly Census of Employment and Wages (QCEW)
    • Table: N/A — this site uses QCEW's own annual-average Total Covered employment figure (all industries, all ownership)
    • Frequency: Annual (matches GDP/Income's own annual cadence; QCEW itself publishes quarterly, but the annual average isn't final until that year's Q4 release)
    • Time Period:
    • Latest Publication:
    • Next Publication:
  • Personal Income Growth
    • Weight: 20%
    • Definition: Real percent change in total personal income, deflated by the national PCE price index (calendar-year average).
    • Agency: U.S. Bureau of Economic Analysis (BEA)
    • Survey: Regional Economic Accounts
    • Table: CAINC1 — County Personal Income Summary; PCE deflator from BEA NIPA T20304
    • Frequency: Annual
    • Time Period:
    • Latest Publication:
    • Next Publication:
  • Population Growth
    • Weight: 15%
    • Definition: Percent change in resident population.
    • Agency: U.S. Census Bureau (distributed via FRED)
    • Survey: Population Estimates Program (county resident population estimates)
    • Table: N/A — one FRED series per county (release 119)
    • Frequency: Annual (Roughly July 1 each year)
    • Time Period:
    • Latest Publication:
    • Next Publication:
  • Residential Building Permits
    • Weight: 10%
    • Definition: Percent change in annual total residential building permits issued.
    • Agency: U.S. Census Bureau
    • Survey: Building Permits Survey (BPS)
    • Frequency: Annual (this file)
    • Time Period:
    • Latest Publication:
    • Next Publication:
  • Methodology: Each indicator is standardized relative to the Maryland statewide average using z-scores, allowing counties to be compared across metrics with different scales and volatility. Extreme values are capped (winsorized) at ±3 standard deviations from the cross-county mean to reduce the influence of outliers. The standardized indicators are then combined using the weights above and scaled so that 100 represents the Maryland statewide average.
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Real GDP by Maryland County

Percent change in real GDP (chained 2017 dollars) for each Maryland county.

Concept:
Time Period:
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  • Real Gross Domestic Product (GDP) is adjusted for inflation and is measured in chained 2017 dollars. Accounting for inflation removes the effect of price changes so that comparisons reflect actual output growth.
  • Select an industry above the map to see how a specific sector's GDP or growth varies across Maryland's counties, rather than just the all-industries total.
  • "Suppressed" counties (shown in white on the map and in the ranked list, with a dashed outline) are ones where BEA didn't publish a figure for the selected industry — usually because too few companies operate in that industry in that county, and reporting a number could reveal information about a specific business. A suppressed county isn't necessarily reporting zero activity; the real figure is simply unpublished, so it's excluded from the color scale and ranking entirely rather than shown as a false zero.
  • Source Notes
    • Agency: U.S. Bureau of Economic Analysis (BEA)
    • Survey: Regional Economic Accounts
    • Table: CAGDP9 — Real GDP by County and Metropolitan Area
    • Frequency: Annual
    • Latest Publication:
    • Next Publication:
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County Industry Snapshot - Real GDP

Comparison of Maryland counties by an industry's economic importance measured by share of county GDP, growth, and GDP level.

Time Period:

  • How to read this chart:
    • Position along the horizontal axis — the industry's share of the county's own GDP.
    • Position along the vertical axis — the industry's percent growth over the selected time period.
    • Bubble size — the industry's real GDP level in that county, scaled relative to the largest county shown. Sizes are only comparable within the current industry — switching industries resets the scale, so bubble sizes can't be compared across different industries.
  • The dashed reference lines mark the industry's statewide share and statewide growth rate, calculated the same way from Maryland's total row, splitting the chart into four quadrants (Leaders / Mature / Emerging / Lagging), same as the State Industry Snapshot chart on the State Data tab.
  • Share is each industry's GDP divided by the sum of all industries in that county, not BEA's official "All Industries" total, for the same chain-weighting reason described on the State Data tab: the parts don't always add up exactly to the published total.
  • Why do some counties show a ranking out of a number less than 24? Counties whose data for the selected industry is suppressed by BEA (see the disclosure note below) are excluded from the chart and its rankings entirely.
  • Disclosure of confidential information: when too few establishments make up an industry in a county, BEA suppresses the actual figure to protect the confidentiality of individual companies — shown as "(D)" on BEA's own data tables. Affected counties are excluded from this chart and its rankings for the selected industry, and are listed in the red note just below the Industry and Focus County dropdowns above.
  • County-level industry detail is coarser than the state-level table: BEA doesn't publish a durable/nondurable manufacturing split or a federal/military/state-local government split at the county level.
  • Source Notes
    • Agency: U.S. Bureau of Economic Analysis (BEA)
    • Survey: Regional Economic Accounts
    • Table: CAGDP9 — Real GDP by County and Metropolitan Area
    • Frequency: Annual
    • Latest Publication:
    • Next Publication:
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Total Employment by Maryland County

Labor force, employment, and unemployment for each Maryland county.

Concept:
Time Period:
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  • Figures come from the BLS Local Area Unemployment Statistics (LAUS) program, which produces monthly labor force, employment, and unemployment estimates for every U.S. county.
  • Use the Series dropdown above the map to switch between:
    • Labor Force Level — everyone employed or actively looking for work.
    • Employment Level — everyone currently working.
    • Unemployment Level — everyone jobless and actively looking for work.
    • Unemployment Rate — unemployment as a percent of the labor force.
  • Figures are not seasonally adjusted, the only form BLS publishes at the county level.
  • Source Notes
    • Agency: U.S. Bureau of Labor Statistics (BLS)
    • Survey: Local Area Unemployment Statistics (LAUS)
    • Frequency: Monthly
    • Latest Publication:
    • Next Publication:
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County Industry Snapshot - Employment

Comparison of Maryland counties by an industry's economic importance measured by share of county employment, growth, and employment level.

Time Period:

  • How to read this chart:
    • Position along the horizontal axis — the industry's share of the county's own total employment.
    • Position along the vertical axis — the industry's percent growth over the selected time period.
    • Bubble size — the industry's employment level in that county, scaled relative to the largest county shown. Sizes are only comparable within the current industry — switching industries resets the scale, so bubble sizes can't be compared across different industries.
  • The dashed reference lines mark the industry's statewide share and statewide growth rate, calculated the same way from Maryland's total row, splitting the chart into four quadrants (Leaders / Mature / Emerging / Lagging), same as the State Industry Snapshot chart on the State Data tab.
  • Industries in this chart are private-sector only (see the note on the map above) — share is each industry's employment divided by the sum of all private-sector industries in that county.
  • Why do some counties show a ranking out of a number less than 24? Counties whose data for the selected industry is suppressed by BLS (see the disclosure note below) are excluded from the chart and its rankings entirely.
  • Disclosure of confidential information: when too few employers make up an industry in a county, BLS suppresses the actual figure to protect the confidentiality of individual businesses. Affected counties are excluded from this chart and its rankings for the selected industry, and are listed in the red note just below the Industry and Focus County dropdowns above.
  • Source Notes
    • Agency: U.S. Bureau of Labor Statistics (BLS)
    • Survey: Quarterly Census of Employment and Wages (QCEW)
    • Frequency: Annual (QCEW itself publishes quarterly; the annual average for a year isn't final until that year's 4th-quarter release)
    • Publication Lag: About 5 months after year-end (e.g. 2025 data finalized with the Q4 2025 release, published June 2026)
    • Latest Publication:
    • Next Publication:
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Population by Maryland County

Percent change in resident population for each Maryland county.

Concept:
Time Period:
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  • Population figures are U.S. Census Bureau midyear population estimates, sourced from Federal Reserve Economic Data (FRED) — one series per Maryland county (e.g. MDHOWA0POP for Howard County), plus a statewide total (MDPOP).
  • Source Notes
    • Agency: U.S. Census Bureau (distributed via FRED, Federal Reserve Bank of St. Louis)
    • Survey: Population Estimates Program (county resident population estimates)
    • Frequency: Annual (as of July 1 each year)
    • Publication Lag: About 9 months after the observation date (e.g. 7/1/2025 estimates published March 2026)
    • Latest Publication:
    • Next Publication:
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Personal Income by Maryland County

Percent change in personal income for each Maryland county.

Concept:
Time Period:
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  • Total personal income comes from BEA's County Personal Income Summary (CAINC1). Per capita personal income is calculated — total income (CAINC1) divided by population (FRED data sourced from Census population estimates).
  • Both Levels and Growth are shown in real (inflation-adjusted) terms whenever possible — nominal (as-published) dollar figures are deflated by the national Personal Consumption Expenditures (PCE) price index, averaged across the calendar year's 4 quarters, the same national deflator used by the State Personal Income map. If that deflator isn't available for a given year (for example, the 10 Year comparison's older anchor year, which currently falls outside the site's PCE price index history), figures fall back to nominal — noted in the chart's subtitle and source line whenever it happens.
  • Select a metric above the map to switch between each county's total personal income and its per capita (per-person) personal income.
  • Source Notes
    • Agency: U.S. Bureau of Economic Analysis (BEA)
    • Survey: Regional Economic Accounts
    • Table: CAINC1 — County Personal Income Summary (Per Capita uses population from FRED release 119, not a BEA table)
    • Frequency: Annual
    • Latest Publication:
    • Next Publication:
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Residential Building Permits by Maryland County

Annual total residential building permits per 10,000 residents by county.

Concept:
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  • Annual totals: each value is a full calendar year's residential building permits (not a rolling 12-month window) — Levels shows the latest published year; Growth compares it to the same calendar year 1, 2, 5, or 10 years prior, matching the year-over-year comparisons already used elsewhere on the Maryland tab (GDP, Labor Market, Personal Income).
  • What permits measure: a residential building permit authorizes construction of a new housing unit before a single shovel breaks ground, across every structure type (single-family through 5+ unit buildings). Permit issuance is a leading indicator of residential investment.
  • The growth rate of counties with very small permit counts can swing dramatically on a single large multifamily project. Examine both levels and growth rates for a full picture.
  • Per 10,000 Residents: takes the annual total of permits for a county and divides by that county's population, then multiplies by 10,000 — "how many permits per 10,000 people who live there." This puts every county on equal footing regardless of size. Only the latest year is shown, since population is a point-in-time figure rather than something to compare across a time horizon. Population comes from FRED's Census population estimates for the SAME year as the latest permits data — see the Population tab.
  • Data source: U.S. Census Bureau Building Permits Survey, county-level ANNUAL files. Not seasonally adjusted.
  • If a county is ever missing from Census's own annual file for a needed year, it's excluded from this map, its rankings, and the copy-data export — marked "Data Unavailable" rather than assumed to be zero — and a note appears above the map naming which counties and years are affected. (As of this writing, Census's annual files contain complete data for all 24 Maryland counties/independent city for every year this map uses, so this note doesn't currently appear.)
  • Source Notes
    • Agency: U.S. Census Bureau
    • Survey: Building Permits Survey (BPS)
    • Table: N/A — county-level annual data files (not a numbered table like BEA's); see census.gov/econ/bps/County
    • Frequency: Annual (this file — Census also publishes monthly national/state/metro permits data, sourced separately via FRED on the National and State Data tabs)
    • Latest Publication:
    • Next Publication:
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Baltimore Region Consumer Prices — Year-over-Year Change

CPI for the Baltimore-Columbia-Towson, MD metro area. Headline and Core shown by default; click the legend to add Food and Energy.

Change Type:
Time Period:
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Source: Bureau of Labor Statistics · CPI-U (Not Seasonally Adjusted) · bls.gov/cpi

  • BLS defines the Baltimore-Columbia-Towson metro area as Baltimore City plus six surrounding counties: Anne Arundel, Baltimore, Carroll, Harford, Howard, and Queen Anne's — not the state as a whole.
  • Adjust the 'Change Types' in the chart above depending on your interest.
    • Year-over-year (YoY) change compares prices to the same month a year ago — this is the figure most often cited as "the inflation rate."
    • Cumulative indexes each line to 100 at the start of whichever Time Period is selected, so you can read off total price growth over that specific window — e.g. at 5Y, a value of 112 means prices are 12% higher than they were five years ago. Changing the Time Period re-bases the index to the new window's own starting point rather than a fixed calendar date.
  • Sampling periods:
    • Baltimore-Columbia-Towson is a smaller index area, so BLS only prices it every other month rather than monthly like the U.S. city average shown on the National Data tab — the lines below connect each actual reading directly across the skipped months in between.
    • BLS also changed which months Baltimore is priced in partway through this chart's history: readings through 2017 were published on odd months (Jan, Mar, May, …); Feb 2018 onward shifted to even months (Feb, Apr, Jun, …). So that year-over-year and cumulative comparisons still land on the correct calendar month across that transition, every reading from before the shift has been relabeled one month earlier as shown here (e.g. a reading BLS originally published for July 2016 appears as June 2016) — only the month label moved; the price value itself is unchanged.
  • Series descriptions:
    • Headline CPI (CUURS35ESA0) includes all items in the basket and is the broadest measure of consumer inflation for the metro area.
    • Core CPI (CUURS35ESA0L1E) excludes food and energy to reveal the underlying inflation trend less distorted by commodity volatility.
    • Food (CUURS35ESAF1) covers groceries (food at home) and restaurant meals (food away from home).
    • Energy (CUURS35ESA0E) includes gasoline, electricity, natural gas, and heating oil — priced monthly even though the other components here are not, since motor fuel is volatile enough that BLS collects it more often even in smaller index areas.
  • Read BLS's write-up of recent Baltimore-area price changes, a regional news release focused specifically on what's driving inflation in this metro area.
  • Source Notes
    • Agency: U.S. Bureau of Labor Statistics (BLS)
    • Survey: Consumer Price Index (CPI)
    • Latest Publication:
    • Next Publication: — the next month this chart's own displayed figure will actually advance to, not necessarily the very next monthly BLS release (see the Sampling Periods note above)

Baltimore Region Consumer Price Changes by Category

A selected set of expenditure categories BLS publishes for the Baltimore-Columbia-Towson metro area, ranked from biggest cumulative price increase to biggest cumulative decrease over the period selected.

Time Period:

Source: Bureau of Labor Statistics · CPI-U (Not Seasonally Adjusted) · bls.gov/cpi

  • Each bar is a category's cumulative price change over the selected period — for example, at 5Y a value of +20% means prices in that category are 20% higher than the same month five years ago. This uses not seasonally adjusted data, standard for comparisons of a year or more since the same calendar month is compared across each period.
  • Unlike the national version of this chart, Baltimore doesn't publish anywhere near the same level of expenditure-category detail — this is a hand-picked set of the categories BLS does publish for this metro area.
  • BLS changed which months Baltimore is priced in partway through this data's history — odd months (Jan, Mar, May, …) through 2017, even months (Feb, Apr, Jun, …) from Feb 2018 on — so pre-2018 readings have been relabeled one month earlier (e.g. a reading BLS originally published for July 2016 appears as June 2016) to keep each Time Period's anchor landing on the correct calendar month across that transition. Only the month label moved; the price value itself is unchanged.
  • Because Baltimore prices most of these categories only every other month, longer time periods can still come up short a category or two whenever that specific item's exact anchor month wasn't published, or wasn't tracked yet — several of the detailed categories here (e.g. Cereals, Meats/Poultry/Fish/Eggs) were only introduced in Dec 2017 and don't have a full 10 years of history regardless of the relabeling above.
  • Read BLS's write-up of recent Baltimore-area price changes, a regional news release focused specifically on what's driving inflation in this metro area.
  • Source Notes
    • Agency: U.S. Bureau of Labor Statistics (BLS)
    • Survey: Consumer Price Index (CPI)
    • Table: N/A — Baltimore-Columbia-Towson, MD area, hand-picked expenditure categories, not a numbered table
    • Frequency: Monthly release; most Baltimore-area categories are only PRICED every other month — see the Sampling Periods note above
    • Latest Publication:
    • Next Publication: — the next month this chart's own displayed figure will actually advance to, not necessarily the very next monthly BLS release
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Maryland Business Conditions

A diffusion index tracks the share of surveyed businesses reporting an increase minus the share reporting a decrease each month — positive means expansion, negative means contraction.

Time Period:
Conditions:
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Source: Federal Reserve Bank of Richmond · Survey of Business Activity

  • The Richmond Fed surveys business leaders across the Fifth Federal Reserve District (Maryland, DC, North Carolina, South Carolina, Virginia, and West Virginia) every month, asking how conditions changed from the prior month (Current) and how they expect conditions to change over the next six months (Expected) — use the toggle above to switch between the two.
  • Each series is a diffusion index: roughly the percent of surveyed firms reporting an increase minus the percent reporting a decrease, so a reading of 0 means increases and decreases offset (conditions unchanged on net), positive means more firms saw improvement than decline, and negative means the opposite. These are not seasonally adjusted.
  • The dashed line is a 3-month moving average of the same series, smoothing out month-to-month noise so the underlying trend is easier to read.
  • Unlike the Richmond Fed's district-wide manufacturing and services data files, this Maryland panel combines both sectors into one number per concept rather than publishing them separately.
  • Typically published on the last Thursday of the survey's own reference month — though the exact date shifts around Thanksgiving, Christmas, and New Year's, so it doesn't follow one clean rule. See the economic calendar for the exact upcoming release dates.
  • Read the Richmond Fed's survey methodology, or view the full data dictionary for every concept the survey tracks.
  • Source Notes
    • Agency: Federal Reserve Bank of Richmond
    • Survey: Survey of Business Activity (Fifth District — Maryland panel)
    • Table: N/A
    • Frequency: Monthly
    • Publication Lag: Same month as the survey's own reference month — typically published the last Thursday of that month (shifts around holidays; see the note above)
    • Latest Publication:
    • Next Publication:
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