Ohio Economy Dashboard

Conditions and a one-year statistical outlook for Ohio, its large metros, and the U.S.

Data through Sep 2026 · Updated Oct 2, 2026

At a glance

Snapshot for Aug 2026: a mid-cycle expansion with a still-tight labor market. Currently: labor still tight; activity on the firm side; inflation near normal; ordinary house-price growth. That reading is backed by low unemployment, low UI claims, firm activity growth. Over the next year the central paths lean toward a bit more cooling in activity, with labor still relatively steady. No clear recession-style warning in the major labor and activity paths. Further regional detail is available from the Federal Reserve Bank of Cleveland, including its SORCE survey and the Fourth District Beige Book.

Scorecard

One-glance read aligned with the summary above. Green = favorable, yellow = caution, red = concerning.

Labor market

Strong

Growth

Solid

Inflation

Moderate

Housing

Steady

Ohio & regional indicators

Ohio Real GDP Growth

Latest data	Forecast	Average (since 2005)	Average (since 2008)
1.88% 2026 Q2	1.66% 2026 Q3	1.19% since 2005	1.31% since 2008

As of 2026 Q2, Ohio Real GDP Growth is a bit off its long-run pace: growth is a bit firmer than its long-run norm. Over the coming year growth is projected to moderate—cooler expansion rates, not a labeled recession path. In step with the headline view’s firm activity theme.

Ohio real GDP (all industries), year-over-year percent growth. Broad measure of state output. Source: FRED (OHRQGSP).

Ohio Coincident Index Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.56% Aug 2026	3.53% Sep 2026	1.56% since 2000	1.74% since 2008

As of Aug 2026, Ohio Coincident Index Growth is clearly unusual versus history: growth looks unusually strong by historical standards. On the one-year path, activity growth eases from recent rates. Supports the overall story that activity is firm.

Philadelphia Fed Ohio coincident index, year-over-year percent growth. Monthly summary of state labor-market and income conditions. Source: FRED (OHPHCI).

Midwest CPI Inflation

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.55% Aug 2026	3.58% Sep 2026	2.32% since 2000	2.32% since 2008

As of Aug 2026, Midwest CPI Inflation sits slightly outside the usual range: inflation is still a bit warm versus its long-run norm. Over the coming year inflation eases toward a more normal pace on the central path. That runs hotter than the big picture’s overall inflation read.

Midwest consumer price inflation (all items), year-over-year. Regional price proxy for Ohio households and businesses. Source: FRED (CUUR0200SA0).

Ohio House Price Index Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
4.21% 2026 Q2	4.36% 2026 Q3	3.31% since 2000	3.56% since 2008

In the latest data (2026 Q2), Ohio House Price Index Growth looks ordinary: home/rent price growth looks near a normal pace. Over the coming year price/rent growth cools on the central path. In line with the big picture on housing (normal).

FHFA Ohio house price index, year-over-year percent growth. Statewide home-price momentum. Source: FRED (OHSTHPI).

Ohio Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
0.17% Aug 2026	0.40% Sep 2026	0.03% since 2000	0.24% since 2008

In the latest data (Aug 2026), Ohio Nonfarm Employment Growth looks ordinary: growth is near a normal expansion pace. Over the coming year the central path looks like more of the same—no sharp break from current conditions. Less extreme than the headline view’s firm activity read.

Ohio total nonfarm payroll employment, year-over-year percent growth. Source: FRED (OHNA).

Ohio Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.30% Aug 2026	3.29% Sep 2026	5.86% since 2000	6.02% since 2008

As of Aug 2026, Ohio Unemployment Rate is a notable outlier: the labor market looks unusually tight (unemployment well below its long-run norm). Looking ahead, the model holds near recent readings rather than a big turn. That coheres with the overall story (a mid-cycle expansion with a still-tight labor market): labor is tight.

Seasonally adjusted unemployment rate for Ohio (percent of the labor force). Source: FRED (OHUR).

Ohio Initial Unemployment Claims

Latest data	Forecast	Average (since 2000)	Average (since 2008)
4,281 claims Sep 2026	4,754 claims Oct 2026	13,427 claims since 2000	13,462 claims since 2008

In the latest data (Sep 2026), Ohio Initial Unemployment Claims is clearly unusual versus history: claims look exceptionally low by historical standards. Over the coming year the central path looks like more of the same—no sharp break from current conditions. In line with the headline view: labor remains tight.

Initial unemployment insurance claims in Ohio: average per week, computed as the monthly mean of complete weeks of the weekly FRED/DOL data. The current month appears only once its last week has been published. Source: FRED (OHICLAIMS).

Ohio Continued Unemployment Claims

Latest data	Forecast	Average (since 2000)	Average (since 2008)
38,347 claims Aug 2026	33,702 claims Sep 2026	99,722 claims since 2000	96,923 claims since 2008

Latest reading (Aug 2026), Ohio Continued Unemployment Claims is a notable outlier: claims look exceptionally low by historical standards. Looking ahead, claims edge lower in the projection. In line with the headline view: labor remains tight.

Continued (insured) unemployment claims in Ohio: average weekly level over complete weeks of the month (a stock, so averaged rather than summed). How many people remain on benefits. Source: FRED (OHCCLAIMS).

Midwest Core CPI Inflation

Latest data	Forecast	Average (since 2000)	Average (since 2008)
2.64% Aug 2026	2.55% Sep 2026	2.17% since 2000	2.32% since 2008

As of Aug 2026, nothing unusual in Midwest Core CPI Inflation: price growth looks close to a normal historical pace. Looking ahead, the model holds near recent readings rather than a big turn. Matches the statewide read’s take on inflation (normal).

Midwest CPI excluding food and energy, year-over-year. Core regional consumer price growth. Source: FRED (CUUR0200SA0L1E).

Ohio Manufacturing Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
1.83% Aug 2026	1.84% Sep 2026	-1.59% since 2000	-0.68% since 2008

In the latest data (Aug 2026), Ohio Manufacturing Employment Growth is a notable outlier: growth looks unusually strong by historical standards. Looking ahead, growth cools on the central path without a sharp break. In step with the overall story’s firm activity theme.

Ohio manufacturing payroll employment, year-over-year percent growth. Source: FRED (OHMFG).

Ohio Industry Composition (GDP shares)

As of 2025, Ohio’s largest GDP contributors include Finance, insurance & real estate, Manufacturing, Professional & business services. Manufacturing alone is about 14% of Ohio GDP versus roughly 9% nationally—Ohio remains a goods-heavy state. Finance/real estate and health care are large service anchors alongside professional services and government. Shares are current-dollar BEA GDP by industry (structural snapshot, not a monthly cycle gauge).

Annual GDP by industry, current dollars (BEA Regional table SAGDP2N). Bars show each sector’s share of statewide (or U.S.) GDP for the latest available year (2025). Top sectors by Ohio share; U.S. shares shown for comparison. Source: BEA GDP by State.

Ohio Goods Trade Trends

In 2025, Ohio shipped about $57 billion in goods exports. Exports were about -2% versus 2024. Goods imports were about $87 billion the same year (merchandise trade deficit of roughly $31 billion). Manufactured goods account for the bulk of shipments (about 94% of exports). On the latest detailed partner snapshot (2022), the largest markets include Canada (34%), Mexico (13%), Japan (6%), China (5%). Trade data are merchandise only (not services), concentrated in vehicles, machinery, and other industrial products.

Annual totals of monthly Census goods trade for Ohio (FRED EXPTOTOH / IMPTOTOH), calendar years with full 12 months. Partner shares use Census/Origin-of-Movement annual series via FRED (latest detailed year). Source: FRED / U.S. Census Bureau.

Fourth District Business Survey (Cleveland Fed SORCE)

As of the Sep 2026 survey wave, Cleveland Fed SORCE diffusion indexes summarize whether more Fourth District contacts report increases than decreases in current conditions, employment, and expected conditions (positive = net expansion among respondents). These timely survey readings complement the hard data above. Coverage is the Federal Reserve’s Fourth District (all of Ohio plus parts of PA, KY, and WV).

Seasonally adjusted diffusion indexes from the Cleveland Fed Survey of Regional Conditions and Expectations (SORCE) for the Total sector. Index = percent reporting increases minus percent reporting decreases (range −100 to +100; zero ≈ balance). Released about eight times per year. Source: Federal Reserve Bank of Cleveland — SORCE (doi:10.26509/frbc-sorce). Shown for context; the survey is not a model input.

Experimental downturn signal (not a calibrated probability) — click to expand

Experimental Ohio downturn signal (not a calibrated probability)

As of Sep 2026, the signal for a current coincident-index decline reads 0%. This is a model score, not a calibrated probability: in pseudo-real-time evaluation it ranked downturn months much worse than in-sample and was no better than the historical base rate (12% of months since 2000). The coincident index is published through Aug 2026.

A probit model of an Ohio downturn month, defined as a fall in the Philadelphia Fed Ohio coincident index over the previous three months (shaded), on the 3-month average of the model's national and Ohio factors (national1, national2, ohio1, ohio2), for the current month only. COVID months are excluded from estimation and blanked in the chart. In-sample fit uses smoothed factors and greatly overstates real-time accuracy (see Methods §5b); this is an experimental signal, not a calibrated probability.

Cleveland, OH (MSA)

In Cleveland as of Aug 2026, local labor looks tight with soft payroll growth—matching the statewide labor theme (a mid-cycle expansion with a still-tight labor market). Housing: house prices firm; rents ordinary. Local paths (lower unemployment, cooler job growth) cohere with the statewide cooling bias.

Cleveland Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
2.80% Aug 2026	2.66% Sep 2026	5.45% since 2000	5.76% since 2008

Latest reading (Aug 2026), Cleveland Unemployment Rate is clearly unusual versus history: the labor market looks unusually tight (unemployment well below its long-run norm). Looking ahead, unemployment drifts a little lower on the central path. In line with the headline view: labor remains tight.

Unemployment rate for the Cleveland, OH metro area. Source: FRED (LASMT391741000000003).

Cleveland Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
0.43% Aug 2026	0.54% Sep 2026	-0.30% since 2000	-0.08% since 2008

In the latest data (Aug 2026), Cleveland Nonfarm Employment Growth is only mildly unusual: growth is a bit firmer than its long-run norm. Through the forecast horizon, little change is expected on the central path. In step with the headline view’s firm activity theme.

Total nonfarm payroll employment in the Cleveland metro, year-over-year percent growth. Source: FRED (SMS39174100000000001).

Cleveland Manufacturing Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
1.69% Aug 2026	2.11% Sep 2026	-2.00% since 2000	-1.07% since 2008

Through Aug 2026, Cleveland Manufacturing Employment Growth is clearly unusual versus history: growth looks unusually strong by historical standards. On the one-year path, activity growth eases from recent rates. Supports the big picture that activity is firm.

Manufacturing payroll employment in the Cleveland metro, year-over-year percent growth. Source: FRED (SMU39174103000000001).

Cleveland Case-Shiller Home Price Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
4.13% Jul 2026	4.22% Aug 2026	2.71% since 2000	3.01% since 2008

Latest reading (Jul 2026), Cleveland Case-Shiller Home Price Growth is a bit off its long-run pace: housing-cost growth is a bit elevated versus history. Over the coming year price/rent growth cools on the central path. Versus the headline view (normal housing), this is more hot.

S&P Case-Shiller home price index for Cleveland, year-over-year percent growth. Source: FRED (CEXRSA).

Cleveland Labor Force Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
-1.96% Aug 2026	-2.17% Sep 2026	-0.12% since 2000	-0.12% since 2008

In the latest data (Aug 2026), Cleveland Labor Force Growth is a bit off its long-run pace: growth is a bit soft versus its long-run norm—expansion, but not boom-like. Over the coming year growth is projected to firm somewhat. That contrasts with the headline view’s firm activity read—here growth looks more soft.

Civilian labor force in the Cleveland metro, year-over-year percent growth. Source: FRED (LASMT391741000000006).

Cleveland Rent Growth (Zillow)

Latest data	Forecast	Average (since 2015)	Average (since 2015)
4.38% Aug 2026	4.22% Sep 2026	5.08% since 2015	5.08% since 2015

As of Aug 2026, Cleveland Rent Growth (Zillow) looks ordinary: home/rent price growth looks near a normal pace. Over the coming year the central path looks like more of the same—no sharp break from current conditions. In line with the overall story on housing (normal).

Zillow Observed Rent Index for the Cleveland metro — smoothed asking rents, year-over-year percent growth. Source: Zillow Research.

Cleveland Home Value Growth (Zillow)

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.84% Aug 2026	3.80% Sep 2026	2.77% since 2000	2.88% since 2008

Through Aug 2026, Cleveland Home Value Growth (Zillow) is a bit off its long-run pace: housing-cost growth is a bit elevated versus history. Looking ahead, housing-cost growth eases in the projection. Versus the statewide read (normal housing), this is more hot.

Zillow Home Value Index for the Cleveland metro, year-over-year percent growth. Source: Zillow Research.

Columbus, OH (MSA)

Columbus (Aug 2026): tight labor market, soft job growth (in line with the statewide picture (a mid-cycle expansion with a still-tight labor market)). Manufacturing and total jobs are not moving together locally—a contrast within the metro. Housing: house prices ordinary; rents cooler. Local one-year paths look mostly steady.

Columbus Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.10% Aug 2026	3.13% Sep 2026	5.15% since 2000	5.27% since 2008

As of Aug 2026, Columbus Unemployment Rate stands out: the labor market looks unusually tight (unemployment well below its long-run norm). Through the forecast horizon, little change is expected on the central path. This matches the overall story, where labor is tight.

Unemployment rate for the Columbus metro area. Source: FRED (COLU139UR).

Columbus Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
-0.28% Aug 2026	-0.33% Sep 2026	0.95% since 2000	1.16% since 2008

As of Aug 2026, Columbus Nonfarm Employment Growth sits slightly outside the usual range: growth is a bit soft versus its long-run norm—expansion, but not boom-like. Looking ahead, the central path has growth picking up a little. That contrasts with the statewide read’s firm activity read—here growth looks more soft.

Total nonfarm payroll employment in Columbus, year-over-year percent growth. Source: FRED (COLU139NA).

Columbus Manufacturing Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
0.39% Aug 2026	0.39% Sep 2026	-1.20% since 2000	-0.15% since 2008

Latest reading (Aug 2026), Columbus Manufacturing Employment Growth is a bit off its long-run pace: growth is a bit firmer than its long-run norm. Over the coming year growth is projected to moderate—cooler expansion rates, not a labeled recession path. In step with the statewide read’s firm activity theme.

Manufacturing payroll employment in Columbus, year-over-year percent growth. Source: FRED (COLU139MFGN).

Columbus House Price Index Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.29% 2026 Q2	3.52% 2026 Q3	3.94% since 2000	4.29% since 2008

Latest reading (2026 Q2), nothing unusual in Columbus House Price Index Growth: home/rent price growth looks near a normal pace. Looking ahead, the model holds near recent readings rather than a big turn. In line with the statewide read on housing (normal).

FHFA house price index for Columbus, year-over-year percent growth. Source: FRED (ATNHPIUS18140Q).

Columbus Rent Growth (Zillow)

Latest data	Forecast	Average (since 2015)	Average (since 2015)
2.54% Aug 2026	2.93% Sep 2026	4.89% since 2015	4.89% since 2015

Latest reading (Aug 2026), Columbus Rent Growth (Zillow) is a bit off its long-run pace: housing-cost growth is a bit cooler than its long-run average (that average includes past boom years). Over the coming year price/rent growth picks up on the central path. That is cooler than the big picture’s housing theme.

Zillow Observed Rent Index for the Columbus metro — smoothed asking rents, year-over-year percent growth. Source: Zillow Research.

Columbus Home Value Growth (Zillow)

Latest data	Forecast	Average (since 2000)	Average (since 2008)
1.36% Aug 2026	1.37% Sep 2026	3.62% since 2000	3.92% since 2008

Latest reading (Aug 2026), Columbus Home Value Growth (Zillow) is only mildly unusual: housing-cost growth is a bit cooler than its long-run average (that average includes past boom years). Over the coming year price/rent growth picks up on the central path. That is cooler than the big picture’s housing theme.

Zillow Home Value Index for the Columbus metro, year-over-year percent growth. Source: Zillow Research.

Cincinnati, OH-KY-IN (MSA)

In Cincinnati as of Aug 2026, local labor looks tight with soft payroll growth—in line with the statewide picture (a mid-cycle expansion with a still-tight labor market). Manufacturing and total jobs are not moving together locally—a contrast within the metro. Housing: house prices ordinary; rents cooler. Local one-year paths look mostly steady.

Cincinnati Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.40% Aug 2026	3.45% Sep 2026	5.42% since 2000	5.61% since 2008

In the latest data (Aug 2026), Cincinnati Unemployment Rate is a notable outlier: the labor market looks unusually tight (unemployment well below its long-run norm). On the one-year path, conditions look set to stay in a similar range. Consistent with the big picture’s tight labor theme.

Unemployment rate for the Cincinnati metro area. Source: FRED (CINC139UR).

Cincinnati Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
0.15% Aug 2026	0.32% Sep 2026	0.55% since 2000	0.60% since 2008

In the latest data (Aug 2026), Cincinnati Nonfarm Employment Growth looks ordinary: growth is near a normal expansion pace. Over the coming year growth is projected to firm somewhat. Less extreme than the big picture’s firm activity read.

Total nonfarm payroll employment in Cincinnati, year-over-year percent growth. Source: FRED (CINC139NA).

Cincinnati Manufacturing Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
1.21% Aug 2026	1.67% Sep 2026	-0.72% since 2000	0.08% since 2008

In the latest data (Aug 2026), Cincinnati Manufacturing Employment Growth is only mildly unusual: growth is a bit firmer than its long-run norm. On the one-year path, activity growth eases from recent rates. That coheres with the statewide read: activity is firm.

Manufacturing payroll employment in Cincinnati, year-over-year percent growth. Source: FRED (CINC139MFG).

Cincinnati House Price Index Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.70% 2026 Q2	3.86% 2026 Q3	3.55% since 2000	3.71% since 2008

As of 2026 Q2, Cincinnati House Price Index Growth is near historical norms: home/rent price growth looks near a normal pace. Over the coming year the central path looks like more of the same—no sharp break from current conditions. In line with the headline view on housing (normal).

FHFA house price index for Cincinnati, year-over-year percent growth. Source: FRED (ATNHPIUS17140Q).

Cincinnati Rent Growth (Zillow)

Latest data	Forecast	Average (since 2015)	Average (since 2015)
2.61% Aug 2026	2.82% Sep 2026	5.21% since 2015	5.21% since 2015

In the latest data (Aug 2026), Cincinnati Rent Growth (Zillow) is only mildly unusual: housing-cost growth is a bit cooler than its long-run average (that average includes past boom years). Looking ahead, housing-cost growth firms modestly. Softer housing growth than the headline housing read.

Zillow Observed Rent Index for the Cincinnati metro — smoothed asking rents, year-over-year percent growth. Source: Zillow Research.

Cincinnati Home Value Growth (Zillow)

Latest data	Forecast	Average (since 2000)	Average (since 2008)
2.35% Aug 2026	2.24% Sep 2026	3.29% since 2000	3.39% since 2008

In the latest data (Aug 2026), Cincinnati Home Value Growth (Zillow) is near historical norms: home/rent price growth looks near a normal pace. Over the coming year the central path looks like more of the same—no sharp break from current conditions. In line with the big picture on housing (normal).

Zillow Home Value Index for the Cincinnati metro, year-over-year percent growth. Source: Zillow Research.

Other Ohio metros: Akron, Dayton, Toledo, Youngstown, Canton

Unemployment and payroll growth for five further Ohio metros. In the model these series share one pooled residual factor (after the national and Ohio factors) rather than one factor per metro, so read their forecasts as regional tendencies. Dayton uses CBSA 19430 series; its unemployment rate is not seasonally adjusted.

Akron Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.60% Aug 2026	3.62% Sep 2026	5.93% since 2000	6.09% since 2008

In the latest data (Aug 2026), Akron Unemployment Rate stands out: the labor market looks unusually tight (unemployment well below its long-run norm). Through the forecast horizon, little change is expected on the central path. This matches the headline view, where labor is tight.

Unemployment rate for the Akron, OH metro area. Source: FRED (AKRO439UR); typical release lag ~5-6 weeks.

Akron Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
-0.56% Aug 2026	-0.12% Sep 2026	0.09% since 2000	-0.03% since 2008

Latest reading (Aug 2026), Akron Nonfarm Employment Growth is only mildly unusual: growth is a bit soft versus its long-run norm—expansion, but not boom-like. Looking ahead, the central path has growth picking up a little. That contrasts with the statewide read’s firm activity read—here growth looks more soft.

Total nonfarm payroll employment in the Akron metro, year-over-year percent growth. Source: FRED (AKRO439NA); typical release lag ~4-5 weeks.

Dayton Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.70% Aug 2026	3.68% Sep 2026	6.04% since 2000	6.18% since 2008

Through Aug 2026, Dayton Unemployment Rate is clearly unusual versus history: the labor market looks unusually tight (unemployment well below its long-run norm). Looking ahead, the model holds near recent readings rather than a big turn. That coheres with the headline view (a mid-cycle expansion with a still-tight labor market): labor is tight.

Unemployment rate for the Dayton, OH metro area (not seasonally adjusted). Source: FRED (LAUMT391943000000003); typical release lag ~5-6 weeks.

Dayton Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
0.20% Aug 2026	0.20% Sep 2026	-0.24% since 2000	0.09% since 2008

Through Aug 2026, nothing unusual in Dayton Nonfarm Employment Growth: growth is near a normal expansion pace. Over the coming year the central path looks like more of the same—no sharp break from current conditions. Less extreme than the overall story’s firm activity read.

Total nonfarm payroll employment in the Dayton metro, year-over-year percent growth. Source: FRED (SMS39194300000000001); typical release lag ~4-5 weeks.

Toledo Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
4.00% Aug 2026	4.06% Sep 2026	6.55% since 2000	6.68% since 2008

As of Aug 2026, Toledo Unemployment Rate is a notable outlier: the labor market looks unusually tight (unemployment well below its long-run norm). Looking ahead, the model holds near recent readings rather than a big turn. This matches the big picture, where labor is tight.

Unemployment rate for the Toledo, OH metro area. Source: FRED (TOLE739UR); typical release lag ~5-6 weeks.

Toledo Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
-1.09% Aug 2026	-0.92% Sep 2026	-0.38% since 2000	-0.19% since 2008

Through Aug 2026, Toledo Nonfarm Employment Growth is a bit off its long-run pace: growth is a bit soft versus its long-run norm—expansion, but not boom-like. Looking ahead, the central path has growth picking up a little. Unlike the headline view (firm activity), this series looks more soft.

Total nonfarm payroll employment in the Toledo metro, year-over-year percent growth. Source: FRED (TOLE739NA); typical release lag ~4-5 weeks.

Youngstown Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
4.80% Aug 2026	4.85% Sep 2026	7.16% since 2000	7.34% since 2008

In the latest data (Aug 2026), Youngstown Unemployment Rate is clearly unusual versus history: the labor market looks unusually tight (unemployment well below its long-run norm). On the one-year path, conditions look set to stay in a similar range. Consistent with the statewide read’s tight labor theme.

Unemployment rate for the Youngstown, OH metro area. Source: FRED (YOUN639UR); typical release lag ~5-6 weeks.

Youngstown Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
-0.72% Aug 2026	-0.53% Sep 2026	-0.84% since 2000	-0.71% since 2008

Latest reading (Aug 2026), nothing unusual in Youngstown Nonfarm Employment Growth: growth is near a normal expansion pace. Looking ahead, the model holds near recent readings rather than a big turn. This is closer to normal than the headline view’s firm activity theme.

Total nonfarm payroll employment in the Youngstown metro, year-over-year percent growth. Source: FRED (YOUN639NA); typical release lag ~4-5 weeks.

Canton Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.70% Aug 2026	3.79% Sep 2026	6.29% since 2000	6.44% since 2008

Latest reading (Aug 2026), Canton Unemployment Rate is clearly unusual versus history: the labor market looks unusually tight (unemployment well below its long-run norm). Over the coming year the central path looks like more of the same—no sharp break from current conditions. That coheres with the overall story (a mid-cycle expansion with a still-tight labor market): labor is tight.

Unemployment rate for the Canton, OH metro area. Source: FRED (CANT939UR); typical release lag ~5-6 weeks.

Canton Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
-0.70% Aug 2026	-0.50% Sep 2026	-0.35% since 2000	-0.05% since 2008

In the latest data (Aug 2026), nothing unusual in Canton Nonfarm Employment Growth: growth is near a normal expansion pace. Over the coming year the central path looks like more of the same—no sharp break from current conditions. Less extreme than the statewide read’s firm activity read.

Total nonfarm payroll employment in the Canton metro, year-over-year percent growth. Source: FRED (CANT939NA); typical release lag ~4-5 weeks.

National (U.S.) indicators

U.S. context for the Ohio outlook—activity, prices, jobs, and interest rates.

U.S. Real GDP Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
2.17% 2026 Q2	2.14% 2026 Q3	2.12% since 2000	1.99% since 2008

Latest reading (2026 Q2), U.S. Real GDP Growth looks ordinary: growth is near a normal expansion pace. Over the coming year the central path looks like more of the same—no sharp break from current conditions. This is closer to normal than the overall story’s firm activity theme.

U.S. real GDP, year-over-year percent growth. Source: FRED (GDPC1).

U.S. Industrial Production Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
1.41% Aug 2026	1.29% Sep 2026	0.38% since 2000	0.02% since 2008

In the latest data (Aug 2026), U.S. Industrial Production Growth is a bit off its long-run pace: growth is a bit firmer than its long-run norm. On the one-year path, activity growth eases from recent rates. Supports the overall story that activity is firm.

Federal Reserve industrial production index, year-over-year percent growth. Source: FRED (INDPRO).

U.S. CPI Inflation

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.30% Aug 2026	3.42% Sep 2026	2.52% since 2000	2.47% since 2008

Through Aug 2026, U.S. CPI Inflation is only mildly unusual: inflation is still a bit warm versus its long-run norm. Through the forecast horizon, little change is expected on the central path. Price growth here looks higher than the headline inflation theme.

U.S. consumer price inflation (all items), year-over-year. Source: FRED (CPIAUCSL).

U.S. Housing Starts Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
-1.25% Aug 2026	-4.30% Sep 2026	-0.61% since 2000	0.04% since 2008

In the latest data (Aug 2026), U.S. Housing Starts Growth sits slightly outside the usual range: housing starts growth is a bit soft versus its long-run norm. Looking ahead, units-started growth eases in the projection. That is cooler than the big picture’s housing theme.

New U.S. housing units started, year-over-year percent growth (quantity of units begun—not house prices or rents). Source: FRED (HOUST).

U.S. Nonfarm Employment Growth

Latest data	Forecast	Average (since 2000)	Average (since 2008)
0.31% Sep 2026	0.49% Oct 2026	0.72% since 2000	0.75% since 2008

In the latest data (Sep 2026), nothing unusual in U.S. Nonfarm Employment Growth: growth is near a normal expansion pace. Looking ahead, the central path has growth picking up a little. This is closer to normal than the overall story’s firm activity theme.

U.S. total nonfarm payroll employment, year-over-year percent growth. Source: FRED (PAYEMS).

U.S. Unemployment Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
4.20% Sep 2026	4.18% Oct 2026	5.60% since 2000	5.85% since 2008

As of Sep 2026, U.S. Unemployment Rate is clearly unusual versus history: the labor market looks unusually tight (unemployment well below its long-run norm). On the one-year path, conditions look set to stay in a similar range. In line with the overall story: labor remains tight.

U.S. civilian unemployment rate (percent). Source: FRED (UNRATE).

U.S. Core CPI Inflation

Latest data	Forecast	Average (since 2000)	Average (since 2008)
2.42% Aug 2026	2.52% Sep 2026	2.38% since 2000	2.46% since 2008

In the latest data (Aug 2026), nothing unusual in U.S. Core CPI Inflation: price growth looks close to a normal historical pace. On the one-year path, conditions look set to stay in a similar range. That coheres with the headline view’s normal inflation theme.

U.S. CPI excluding food and energy, year-over-year. Source: FRED (CPILFESL).

Federal Funds Effective Rate

Latest data	Forecast	Average (since 2000)	Average (since 2008)
3.75% Sep 2026	3.79% Oct 2026	2.05% since 2000	1.47% since 2008

Latest reading (Sep 2026), Federal Funds Effective Rate is clearly unusual versus history: this rate looks unusually high by post-1990 standards. On the one-year path, conditions look set to stay in a similar range. National rates are context for Ohio financing conditions; the statewide read remains a mid-cycle expansion with a still-tight labor market.

Effective federal funds rate (policy interest rate). Source: FRED (FEDFUNDS).

10-Year Treasury Yield

Latest data	Forecast	Average (since 2000)	Average (since 2008)
4.99% Sep 2026	5.18% Oct 2026	3.35% since 2000	2.78% since 2008

Through Sep 2026, 10-Year Treasury Yield stands out: this rate looks unusually high by post-1990 standards. Over the coming year the central path looks like more of the same—no sharp break from current conditions. National rates are context for Ohio financing conditions; the overall story remains a mid-cycle expansion with a still-tight labor market.

Market yield on 10-year U.S. Treasury securities. Source: FRED (GS10).

Methodology & model details

This dashboard reports forecasts from a hierarchical mixed-frequency dynamic factor model (MF-DFM) estimated on Ohio, Midwest, and national series from FRED and other public sources. The state unit is monthly. Quarterly series are observed only in quarter-end months (March, June, September, December); other months are missing for those series. Charts show rate levels or year-over-year percent growth only (never QoQ/MoM).

Cleveland MSA geography: Cleveland series follow the current OMB delineation (Bulletin 23-01), Cleveland, OH (CBSA 17410; BLS area 391741). Series for the former Cleveland-Elyria definition are not used.

1. Observation equation (estimation space)

Let $i$ index series and $t$ months. After transform and standardization, the observation equation is

z_{i,t} = \alpha_i + \Lambda_i' F_t + \varepsilon_{i,t}

where $z_{i,t}$ is the demeaned/scaled estimation-space series, $F_t$ is the vector of latent factors active for series $i$ (see loading table), $\Lambda_i$ are free loadings on those factors (zeros elsewhere), and $\varepsilon_{i,t}$ is idiosyncratic noise. Fourier seasonal terms (annual and semi-annual harmonics) are residualized from the panel before factor extraction so latent factors are non-seasonal; the same terms re-enter the observation regression and series forecasts. Optional COVID dummies may also enter in sample; forecasts set COVID dummies to zero.

Transforms into estimation space:

Growth / index series: $g_t = 100\,\log(Y_t / Y_{t-1})$ (monthly) or QoQ log growth at quarter ends.
Rate series (unemployment, yields, fed funds): $\Delta r_t = r_t - r_{t-1}$ (first difference; avoids mean-reversion of levels to the long historical average).

Each transformed series is standardized using means and standard deviations computed from 2000-01-01 onward (hard COVID window excluded from location/scale).

2. Factor hierarchy and extraction

Factors are extracted stagewise by residualized EM-PCA, then loadings are estimated by OLS with the hierarchy mask:

National factors $F_t^{\mathrm{N}}$ from the national panel only. Residualize all series on $F^{\mathrm{N}}$.
Ohio residual factors $F_t^{\mathrm{OH}}$ from non-national residuals. Residualize non-national series on $F^{\mathrm{OH}}$.
MSA residual factors $F_t^{m}$ for each metro $m$ in {cleveland, columbus, cincinnati, other Ohio metros (pooled)} from that metro’s residual panel. Residualize those series on $F^{m}$. Akron, Dayton, Toledo, Youngstown and Canton share a single pooled factor (othermetros1); their series are too few and too noisy for one factor each.
Sector block factors $F_t^{b}$ for $b$ in {labor, prices, housing, activity, consumption} from residualized series in each block.

National factors: 2
Ohio residual factors: 2
MSA residual factors: 1 each for cleveland, columbus, cincinnati, other Ohio metros (pooled)
Block factors: 1 per block (labor, prices, housing, activity, consumption)
Total factors: 13 — national1, national2, ohio1, ohio2, cleveland1, columbus1, cincinnati1, othermetros1, labor1, prices1, housing1, activity1, consumption1

Estimated factor paths (history and short-horizon forecasts) for each layer of the hierarchy are plotted on a companion page: factor paths.

3. Which series load on which factors

✓ = free loading estimated; blank / — = restricted to zero. “Own block” is the series’ sector block (labor, prices, housing, activity or consumption).

Series group	National `national*`	Ohio residual `ohio*`	MSA residual	Sector block `labor*` etc.
National (US GDP, CPI, UNRATE, FEDFUNDS, …)	✓	—	—	—
Ohio state / regional (OHUR, OHRQGSP, Midwest CPI, …)	✓	✓	—	own block
Cleveland MSA series	✓	✓	own only `cleveland*`	own block
Columbus MSA series	✓	✓	own only `columbus*`	own block
Cincinnati MSA series	✓	✓	own only `cincinnati*`	own block
Other Ohio metros (pooled) series	✓	✓	own only `othermetros*`	own block

Compactly, for a series with allowed factor set $S_i$:

z_{i,t} = \alpha_i + \sum_{k \in S_i} \lambda_{i,k} f_{k,t} + \varepsilon_{i,t}

$S_i$ = national factors only for national series; national + Ohio residual + own block for state/regional series; national + Ohio + own MSA residual + own block for MSA series.

4. Factor dynamics (sparse VARX)

Factors follow a sparse hierarchical VARX (not independent ARs):

F_t = c + \sum_{j=1}^{p} \Phi_j F_{t-j} + \Gamma X_{t-1} + u_t

Lag order: $p = 1$ (selected by sparse-VARX BIC over candidates [1, 2, 3, 4]; common sample, hierarchical lag restrictions; picks by criterion on this run: BIC p=1, AIC p=4, HQIC p=1; candidates with a companion root of 1 or more are rejected; re-selected at every estimation)
Sparsity: national factors depend only on national lags; Ohio on national+Ohio; each MSA on national+Ohio+own MSA; blocks on national+Ohio+own block.
Exogenous $X$ (national financial and activity indicators, lag 1, in Ohio/MSA/block equations): FEDFUNDS, GS10, INDPRO, PAYEMS, UNRATE (AR(1) for multi-step $X$ paths). Broader national cycle indicators (CFNAI, leading and financial-conditions indexes, the term spread, the Sahm rule, the NY Fed WEI) are not model inputs: in pseudo-real-time evaluation they did not improve short-horizon accuracy and reduced 12-month accuracy.
Stability: if the fitted VARX has a companion root at or above 1, its lag matrices are shrunk until the system is stationary.
Kalman smoother: factors refined by a joint linear Gaussian filter/smoother given hierarchical loadings and the VARX law (Mariano–Murasawa poly for quarterly series).
Extraction weights: majors up-weighted in EM-PCA (×3).

5. Idiosyncratic residual, direct multi-horizon, and forecasts

Let $\hat\varepsilon_{i,T}$ be the last in-sample residual in estimation space. Forecasts add a decaying AR(1) residual path so short-horizon forecasts do not jump from the last data point to the pure common component:

\hat\varepsilon_{i,T+h} = \rho_i^{h} \hat\varepsilon_{i,T}, \qquad \hat z_{i,T+h} = \alpha_i + \Lambda_i' \hat F_{T+h} + \hat\varepsilon_{i,T+h}

Direct multi-horizon: for major indicators, also estimate $z_{i,T+h} = a_{i,h} + b_{i,h}' F_T$ by OLS for $h \in \{1,2,3,4,5,6,9,12\}$ and blend with the iterated VARX common-component path.

Unpublished months: series are released with different lags, so the panel ends at $T$ while many series stop earlier. Each series is forecast from the month after its own last release, anchored on that release: step $k$ is dated $k$ months after the last published value and uses the VARX factor forecast from $T$ (in pseudo-real-time evaluation this anchoring was more accurate than filling the unpublished months from the smoothed factors). On the charts, the forecast line therefore starts at the first unpublished month.

Factors are iterated with the sparse VARX (Monte Carlo draws of shocks for bands). Mapping back to levels ($Y_T$ is the last published value):

Growth series: compound from last level, $Y_{T+h} = Y_T \cdot \exp\!\big(\sum \hat g / 100\big)$; quarterly growth is applied as $g/3$ per month for a monthly latent path (MM used in Kalman measurement).
Rate series: $r_{T+h} = r_T + \sum \widehat{\Delta r}$.

Dashboard display for indexes is year-over-year growth of the level path, $100\,\log(Y_t / Y_{t-12})$. Confidence bands: 350 Monte Carlo simulations; 68% (16th–84th) and faint outer 95% (2.5th–97.5th) percentiles. Chart history ≈ 3 years, January-aligned; forecast horizon 12 months.

5b. Experimental turning-point (downturn) signal

An Ohio downturn month is defined as $D_t = 1$ when the Philadelphia Fed Ohio coincident index (OHPHCI) is below its level three months earlier. A probit $\Pr(D_t=1 \mid F_t) = \Phi(a + b' \bar F_t)$ is estimated, where $\bar F_t$ is the 3-month average of the national and Ohio factors (national1, national2, ohio1, ohio2). Because the factors are Kalman-smoothed to the edge of the panel, the signal extends to months the coincident index has not yet reached. COVID months (March 2020 to June 2021) are excluded; an L1-regularized probit is used if separation occurs. Real-time caveat: in a pseudo-real-time (vintage) backtest, 2000–2026, the nowcast's ability to rank downturn months fell from an in-sample AUC of about 0.95 to about 0.74, and its Brier score was no better than always predicting the historical base rate. The output is therefore shown only as an experimental current-month signal, not a calibrated probability, and is not used in the headline summary.

Latest estimate (factors through Sep 2026; coincident index through Aug 2026): 0%. In-sample McFadden pseudo-R²: 0.84. Share of downturn months since 2000: 12%.

6. Sample & robustness

Weekly data: Ohio initial claims, continued claims and the insured unemployment rate (OHINSUREDUR) enter as the monthly mean of complete weeks; the current month is missing until its last week is published.
Data vintage: every estimation uses the latest published values, including revisions.
Estimation sample: 2000-01-31 to 2026-09-30 (177 series after filters)
Factor sample start: 2000-01-01
COVID handling: dummies (2020-03-01–2020-12-31; soft tail to 2021-06-30)
Growth / Δr winsorization: 0.5% tails; standardized inputs are then clipped at ±5 standard deviations
Metro charts: Cleveland, Columbus and Cincinnati show unemployment, payrolls, manufacturing payrolls, a house price index and Zillow rents and home values (Cleveland also the labor force); Akron, Dayton, Toledo, Youngstown and Canton show unemployment and payrolls.

7. Data sources

Series used in estimation and on this page (free public APIs and open data files):

FRED (Federal Reserve Bank of St. Louis) — fred.stlouisfed.org · API docs: docs (Ohio/MSA/national labor, housing, GDP, CPI, rates, weekly UI claims and insured unemployment rate, etc.)
BLS Job Openings and Labor Turnover Survey (JOLTS) — bls.gov/jlt · Public API: developers (U.S. job openings rate; state JOLTS are released only annually and are not used)
EIA electricity retail sales — eia.gov/opendata (Ohio total and industrial sales, MWh)
BEA Regional Economic Accounts — bea.gov regional · API: API signup (Ohio real GDP and personal income; metro regional price parities)
Zillow Research public data — zillow.com/research/data (ZORI rents and ZHVI home values for Cleveland, Columbus, Cincinnati metros; attribution to Zillow Research required)
Census / BLS via FRED — high-propensity business applications and other formation series where available (e.g. BAHBATOTALSAOH on FRED)
BEA GDP by State (industry) — bea.gov (annual current-dollar GDP by industry for Ohio industry-composition panel)
U.S. Census goods trade (via FRED) — EXPTOTOH / IMPTOTOH monthly goods exports and imports for Ohio (annualized on the trade-trends panel; partner shares from Census SCEN series)
Federal Reserve Bank of Cleveland — SORCE (Survey of Regional Conditions and Expectations) — SORCE page · doi:10.26509/frbc-sorce (Fourth District diffusion indexes; all of Ohio plus parts of PA, KY, WV; plotted on this dashboard; not a model input)

7b. Additional regional series

Further open-data series enter the model: payrolls, unemployment and housing indicators for Akron, Dayton, Toledo, Youngstown and Canton; Cleveland house prices, permits and listings; FHFA purchase-only house price indexes; quarterly QCEW wages, BEA wages and salaries and Census tax collections (Mariano–Murasawa); and an Ohio consumption/fiscal block with the S-1 county sales-tax base (validated against published county totals; metro aggregates load on their metro factor), Census state retail sales and Ohio OBM monthly tax receipts. OBM employer withholding changes basis in July 2023; that month's growth rate is treated as a level shift (missing), and the source gap in August 2018 is left to the Kalman filter. Series that are not seasonally adjusted are adjusted within each estimation by removing calendar-month (quarterly: calendar-quarter) means of their growth rates, estimated on that estimation's sample, in addition to the model's Fourier terms.

BLS CES via FRED: 5 series (monthly; block labor; other Ohio metros); typical release lag ~4-5 weeks.
BLS LAUS via FRED: 5 series (monthly; block labor; other Ohio metros); typical release lag ~5-6 weeks.
FHFA HPI master file: 8 series (monthly, quarterly; block housing; Cleveland, Ohio, other Ohio metros, regional); typical release lag ~2 months; ~2 months after quarter.
Zillow Research: 4 series (monthly; block housing; other Ohio metros); typical release lag mid-following month.
Census BPS metro files: 2 series (monthly; block housing; Cleveland, other Ohio metros); typical release lag ~3 weeks.
Realtor.com Residential Data: 3 series (monthly; block housing; Cleveland); typical release lag first week of following month.
BLS QCEW open data: 1 series (quarterly; block activity; Ohio); typical release lag ~5-6 months after quarter.
BEA via FRED: 1 series (quarterly; block activity; Ohio); typical release lag ~3 months after quarter.
Census QTAX via FRED: 1 series (quarterly; block activity; Ohio); typical release lag ~3 months after quarter.
Ohio Dept. of Taxation S-1 (county permissive sales tax): 5 series (monthly; block consumption; Cincinnati, Cleveland, Columbus, Ohio, other Ohio metros); typical release lag ~2.5-3 months (collections in m mostly reflect sales in m-1).
Census Monthly State Retail Sales (experimental): 1 series (monthly; block consumption; Ohio); typical release lag ~2.5-3 months.
Ohio OBM Monthly Financial Report (GRF receipts): 3 series (monthly; block consumption; Ohio); typical release lag ~10 days.

Cleveland charts use the current Cleveland, OH metro definition (BLS area 17410). Geography details are in the Cleveland note above.

8. Selected references (methods)

Core published work that introduces or surveys methods used in this dashboard (dynamic factors, mixed frequency, nowcasting, Kalman/EM estimation, multi-horizon projection). Links point to publisher or stable open versions where available.

Stock, J. H., & Watson, M. W. (2002). Macroeconomic forecasting using diffusion indexes. Journal of Business & Economic Statistics, 20(2), 147–162. doi · PDF
Stock, J. H., & Watson, M. W. (2011). Dynamic factor models. In Oxford Handbook of Economic Forecasting. doi · PDF
Bai, J., & Ng, S. (2002). Determining the number of factors in approximate factor models. Econometrica, 70(1), 191–221. doi
Forni, M., Hallin, M., Lippi, M., & Reichlin, L. (2000). The generalized dynamic-factor model: Identification and estimation. Review of Economics and Statistics, 82(4), 540–554. doi
Doz, C., Giannone, D., & Reichlin, L. (2011). A two-step estimator for large approximate dynamic factor models based on Kalman filtering. Journal of Econometrics, 164(1), 188–205. doi · PDF (staff report)
Doz, C., Giannone, D., & Reichlin, L. (2012). A quasi–maximum likelihood approach for large, approximate dynamic factor models. Review of Economics and Statistics, 94(4), 1014–1024. doi
Giannone, D., Reichlin, L., & Small, D. (2008). Nowcasting: The real-time informational content of macroeconomic data. Journal of Monetary Economics, 55(4), 665–676. doi · PDF (ECB WP)
Mariano, R. S., & Murasawa, Y. (2003). A new coincident index of business cycles based on monthly and quarterly series. Journal of Applied Econometrics, 18(4), 427–443. doi
Marcellino, M., Stock, J. H., & Watson, M. W. (2006). A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series. Journal of Econometrics, 135(1–2), 499–526. doi · PDF
Banbura, M., Giannone, D., & Reichlin, L. (2011). Nowcasting. In Oxford Handbook of Economic Forecasting. doi · PDF (ECB WP)

9. Credits

Model and dashboard by Gabriel Mihalache, The Ohio State University.

Software assistance: xAI Grok Build and Grok Bot. Ohio flag SVG: Wikimedia Commons (public domain).