Florida · November 11, 2026

Real GDP Growth by County, 2017–2022

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Which Florida counties’ economies grew fastest from 2017 to 2022, after adjusting for inflation? Map the change.

Real GDP growth by Florida county, 2017 to 2022

I measured growth with BEA's real GDP for all industries combined, in chained 2017 dollars. BEA builds this figure to remove inflation, so no hand adjustment is needed. Florida's own BEA figure grew 22.8%, from about $1.01 trillion to $1.25 trillion. BEA published figures for all 67 counties, with none withheld.

Real GDP Growth by County, 2017–2022⬇ Image

Legend: darker green means faster real growth. The darkest green is 40% or more, then 30–40%, 20–30% (the band that holds the state's 22.8%), 10–20%, and pale yellow for 0–10%. Red marks the one county whose real GDP fell. Click a county to see its 2017 and 2022 real GDP and the percent change.

Fastest-growing counties, real GDP 2017–2022 (millions of chained 2017 $)

Rank	County	2017	2022	Change
1	Sumter	3,208	5,085	+58.5%
2	Okeechobee	1,254	1,874	+49.5%
3	Liberty	183	263	+43.7%
4	Walton	3,073	4,396	+43.1%
5	St. Johns	8,971	12,811	+42.8%
6	Flagler	2,695	3,694	+37.0%
7	Nassau	2,647	3,518	+32.9%
8	Pasco	12,597	16,683	+32.4%
9	Citrus	3,704	4,903	+32.4%
10	Brevard	24,133	31,677	+31.3%

⬇ CSV

What the map shows

The fastest growth is on the edges of the big metros. Around Jacksonville: St. Johns, Nassau and Flagler. North of Tampa: Pasco, Citrus and Hernando. Around Orlando and The Villages: Sumter, Osceola and Lake. On the Space Coast: Brevard. On the Emerald Coast: Walton, Okaloosa and Santa Rosa.
The large urban counties grew close to the state rate. Hillsborough grew 26.8%, Palm Beach 24.0%, Duval 23.3%, Orange 22.1% and Broward 22.0%. Miami-Dade grew more slowly, at 17.6%.
Liberty (+43.7%) and Okeechobee (+49.5%) are small economies. Their percentages are large, but the dollar gains behind them are small.
The slowest growth was in rural North Florida and parts of the interior. Taylor is the only county where real GDP fell (−7.8%). Gadsden (+1.1%), Dixie (+1.4%), Bradford (+2.5%) and Jackson (+4.3%) grew the least.

Caveats

These are BEA's latest revised figures. Chained dollars should only be compared over time within one county, not added across counties.
The 2017–2022 window includes the 2020 downturn and the recovery after it, so a county's growth depends partly on how hard 2020 hit it.
GDP measures output where it is produced, not residents' income. Per-capita income growth (from fl_bea_county_income) could rank the counties differently.

Layers

Click anything on the map for its details.

The transcript below the answer shows every query it ran. Shapefiles of every layer, at full detail, can be downloaded in State Planner: sign up to ask your own question and export any map.

Data sets used

Transcript

What follows is the transcript of this chat as State Planner generated it. It is here to show how the answer above was arrived at: every query State Planner ran, what each one returned, and where the data came from.

transcript.md

↑ Contents

State Planner chat · https://stateplanner.com

State: Florida (FL)
Started: November 11, 2026, 2:53 PM UTC
Runtime: 28 sec
Status: completed

Prompt

Which Florida counties’ economies grew fastest from 2017 to 2022, after adjusting for inflation? Map the change.

Model: Anthropic: Claude Opus 5.5 (anthropic/claude-opus-5.5, via openrouter)

Response

Real GDP growth by Florida county, 2017 to 2022

Real GDP Growth by County, 2017–2022

Fastest-growing counties, real GDP 2017–2022 (millions of chained 2017 $)

Rank	County	2017	2022	Change
1	Sumter	3,208	5,085	+58.5%
2	Okeechobee	1,254	1,874	+49.5%
3	Liberty	183	263	+43.7%
4	Walton	3,073	4,396	+43.1%
5	St. Johns	8,971	12,811	+42.8%
6	Flagler	2,695	3,694	+37.0%
7	Nassau	2,647	3,518	+32.9%
8	Pasco	12,597	16,683	+32.4%
9	Citrus	3,704	4,903	+32.4%
10	Brevard	24,133	31,677	+31.3%

What the map shows

The fastest growth is on the edges of the big metros. Around Jacksonville: St. Johns, Nassau and Flagler. North of Tampa: Pasco, Citrus and Hernando. Around Orlando and The Villages: Sumter, Osceola and Lake. On the Space Coast: Brevard. On the Emerald Coast: Walton, Okaloosa and Santa Rosa.
The large urban counties grew close to the state rate. Hillsborough grew 26.8%, Palm Beach 24.0%, Duval 23.3%, Orange 22.1% and Broward 22.0%. Miami-Dade grew more slowly, at 17.6%.
Liberty (+43.7%) and Okeechobee (+49.5%) are small economies. Their percentages are large, but the dollar gains behind them are small.
The slowest growth was in rural North Florida and parts of the interior. Taylor is the only county where real GDP fell (−7.8%). Gadsden (+1.1%), Dixie (+1.4%), Bradford (+2.5%) and Jackson (+4.3%) grew the least.

Caveats

These are BEA's latest revised figures. Chained dollars should only be compared over time within one county, not added across counties.
The 2017–2022 window includes the 2020 downturn and the recovery after it, so a county's growth depends partly on how hard 2020 hit it.
GDP measures output where it is produced, not residents' income. Per-capita income growth (from fl_bea_county_income) could rank the counties differently.

Exploratory Queries

Query 1 — Compute real GDP change 2017-2022 by county.

   SELECT a.geoid,
          a.name,
          round(a.real_gdp / 1e6, 2) rgdp17_bn,
          round(b.real_gdp / 1e6, 2) rgdp22_bn,
          round(100 * (b.real_gdp / a.real_gdp -1), 1) pct,
          b.codes,
          (c.geoid IS NOT NULL) in_census
     FROM fl_bea_county_gdp a
     JOIN fl_bea_county_gdp b ON a.geoid = b.geoid
      AND b.line_code = 1
      AND b.year = 2022
LEFT JOIN fl_census_counties c ON c.geoid = a.geoid
    WHERE a.line_code = 1
      AND a.year = 2017
 ORDER BY pct DESC

geoid	name	rgdp17_bn	rgdp22_bn	pct	in_census
12119	Sumter, FL	3208.20	5085.27	58.5	true
12093	Okeechobee, FL	1253.57	1873.79	49.5	true
12077	Liberty, FL	183.22	263.29	43.7	true
12131	Walton, FL	3072.67	4395.86	43.1	true
12109	St. Johns, FL	8970.72	12810.50	42.8	true
12035	Flagler, FL	2695.38	3693.58	37.0	true
12089	Nassau, FL	2646.89	3518.30	32.9	true
12101	Pasco, FL	12596.63	16682.89	32.4	true
12017	Citrus, FL	3704.39	4902.95	32.4	true
12009	Brevard, FL	24133.06	31676.92	31.3	true
12097	Osceola, FL	10505.77	13744.82	30.8	true
12021	Collier, FL	18972.22	24257.79	27.9	true
12081	Manatee, FL	14216.89	18164.12	27.8	true
12091	Okaloosa, FL	11313.09	14458.11	27.8	true
12113	Santa Rosa, FL	4429.46	5625.51	27.0	true
12057	Hillsborough, FL	87528.49	111012.38	26.8	true
12111	St. Lucie, FL	9305.42	11773.47	26.5	true
12115	Sarasota, FL	20195.02	25555.59	26.5	true
12053	Hernando, FL	4036.62	5088.88	26.1	true
12015	Charlotte, FL	5181.24	6512.05	25.7	true
12117	Seminole, FL	20979.51	26183.24	24.8	true
12071	Lee, FL	31283.53	38894.72	24.3	true
12069	Lake, FL	9661.01	11988.78	24.1	true
12099	Palm Beach, FL	82713.43	102539.99	24.0	true
12083	Marion, FL	9763.72	12089.34	23.8	true

25 out of 68 are listed here.

data/turn-1-query-1.csv

Map Layer Queries

Real GDP change 2017–2022 (chained 2017 $) — colored by "cls": 40% or more (#00441b), 30–40% (#238b45), 20–30% (state: 22.8%) (#74c476), 10–20% (#c7e9c0), 0–10% (#fff7bc), Decline (#d7301f)

   SELECT c.geom,
          c.name AS "County",
          round(a.real_gdp / 1e6) AS "Real GDP 2017 ($M, 2017 $)",
          round(b.real_gdp / 1e6) AS "Real GDP 2022 ($M, 2017 $)",
          round(100 * (b.real_gdp / a.real_gdp -1), 1) AS "Change(%)",
          CASE
                    WHEN b.real_gdp / a.real_gdp -1 >= 0.40 THEN '40%+'
                    WHEN b.real_gdp / a.real_gdp -1 >= 0.30 THEN '30-40%'
                    WHEN b.real_gdp / a.real_gdp -1 >= 0.20 THEN '20-30%'
                    WHEN b.real_gdp / a.real_gdp -1 >= 0.10 THEN '10-20%'
                    WHEN b.real_gdp / a.real_gdp -1 >= 0 THEN '0-10%'
                    ELSE 'Decline'
          END AS cls
     FROM fl_census_counties c
     JOIN fl_bea_county_gdp a ON a.geoid = c.geoid
      AND a.line_code = 1
      AND a.year = 2017
     JOIN fl_bea_county_gdp b ON b.geoid = c.geoid
      AND b.line_code = 1
      AND b.year = 2022

Picture: maps/turn-1-real-gdp-growth-county.png

Used Data Sets

fl_bea_county_gdp — last synced 2026-10-16 · 55,488 rows
fl_census_counties — last synced 2026-09-27 · 67 rows

data/turn-1-query-1.csv

↑ Contents

geoid	name	rgdp17_bn	rgdp22_bn	pct	in_census
12119	Sumter, FL	3208.20	5085.27	58.5	true
12093	Okeechobee, FL	1253.57	1873.79	49.5	true
12077	Liberty, FL	183.22	263.29	43.7	true
12131	Walton, FL	3072.67	4395.86	43.1	true
12109	St. Johns, FL	8970.72	12810.50	42.8	true
12035	Flagler, FL	2695.38	3693.58	37.0	true
12089	Nassau, FL	2646.89	3518.30	32.9	true
12101	Pasco, FL	12596.63	16682.89	32.4	true
12017	Citrus, FL	3704.39	4902.95	32.4	true
12009	Brevard, FL	24133.06	31676.92	31.3	true
12097	Osceola, FL	10505.77	13744.82	30.8	true
12021	Collier, FL	18972.22	24257.79	27.9	true
12081	Manatee, FL	14216.89	18164.12	27.8	true
12091	Okaloosa, FL	11313.09	14458.11	27.8	true
12113	Santa Rosa, FL	4429.46	5625.51	27.0	true
12057	Hillsborough, FL	87528.49	111012.38	26.8	true
12111	St. Lucie, FL	9305.42	11773.47	26.5	true
12115	Sarasota, FL	20195.02	25555.59	26.5	true
12053	Hernando, FL	4036.62	5088.88	26.1	true
12015	Charlotte, FL	5181.24	6512.05	25.7	true
12117	Seminole, FL	20979.51	26183.24	24.8	true
12071	Lee, FL	31283.53	38894.72	24.3	true
12069	Lake, FL	9661.01	11988.78	24.1	true
12099	Palm Beach, FL	82713.43	102539.99	24.0	true
12083	Marion, FL	9763.72	12089.34	23.8	true
12031	Duval, FL	62868.21	77538.84	23.3	true
12045	Gulf, FL	387.08	476.24	23.0	true
12000	Florida	1014866.86	1245927.56	22.8	false
12085	Martin, FL	7438.58	9116.93	22.6	true
12105	Polk, FL	25742.49	31529.24	22.5	true
12095	Orange, FL	95077.00	116081.63	22.1	true
12011	Broward, FL	104703.41	127700.08	22.0	true
12103	Pinellas, FL	48499.27	58605.29	20.8	true
12129	Wakulla, FL	705.27	851.60	20.7	true
12019	Clay, FL	5191.43	6255.33	20.5	true
12087	Monroe, FL	4924.21	5879.93	19.4	true
12041	Gilchrist, FL	330.71	394.69	19.3	true
12043	Glades, FL	277.23	329.68	18.9	true
12049	Hardee, FL	1037.68	1231.58	18.7	true
12127	Volusia, FL	17886.66	21194.61	18.5	true
12001	Alachua, FL	13230.63	15670.82	18.4	true
12047	Hamilton, FL	472.19	556.11	17.8	true
12059	Holmes, FL	349.94	411.71	17.7	true
12086	Miami-Dade, FL	159539.07	187545.72	17.6	true
12061	Indian River, FL	6355.42	7452.88	17.3	true
12005	Bay, FL	8391.38	9812.47	16.9	true
12079	Madison, FL	408.98	477.83	16.8	true
12051	Hendry, FL	1192.86	1380.02	15.7	true
12037	Franklin, FL	337.90	390.45	15.6	true
12133	Washington, FL	560.28	646.89	15.5	true
12125	Union, FL	314.46	363.09	15.5	true
12023	Columbia, FL	2136.95	2454.90	14.9	true
12073	Leon, FL	14927.97	17144.73	14.8	true
12067	Lafayette, FL	150.81	172.51	14.4	true
12013	Calhoun, FL	271.09	309.00	14.0	true
12121	Suwannee, FL	1217.08	1373.21	12.8	true
12033	Escambia, FL	15781.40	17684.41	12.1	true
12003	Baker, FL	664.45	740.60	11.5	true
12065	Jefferson, FL	250.29	274.49	9.7	true
12055	Highlands, FL	2482.12	2704.88	9.0	true
12027	DeSoto, FL	932.06	1010.09	8.4	true
12107	Putnam, FL	2125.36	2280.28	7.3	true
12075	Levy, FL	922.16	985.42	6.9	true
12063	Jackson, FL	1312.52	1369.07	4.3	true
12007	Bradford, FL	654.60	670.87	2.5	true
12029	Dixie, FL	280.62	284.48	1.4	true
12039	Gadsden, FL	1225.49	1238.89	1.1	true
12123	Taylor, FL	759.47	700.39	-7.8	true

68 rows.

maps/turn-1-real-gdp-growth-county.png

↑ Contents

provenance/fl_bea_county_gdp.md

↑ Contents

Provenance: `fl_bea_county_gdp`

This file describes how the rows in PostgreSQL table fl_bea_county_gdp were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: fl_bea_county_gdp
Family: BEA
Display name: BEA County GDP by Industry
Source URL: https://apps.bea.gov/regional/zip/CAGDP2.zip, https://apps.bea.gov/regional/zip/CAGDP9.zip, https://apps.bea.gov/regional/zip/CAGDP8.zip, https://apps.bea.gov/regional/zip/CAGDP11.zip
Geometry (source / stored): none / none
Update cycle: Yearly

Pipeline

BEA publishes each regional table as one national zip holding a CSV per state (and one of every area). The BEA sync downloads each zip once into its input store, when a HEAD request shows BEA changed it, and every state reads its own CSV from the stored file.

Four tables are read from Florida's CSVs, one value column each: CAGDP2 (GDP in current dollars), CAGDP9 (real GDP), CAGDP8 (the chain-type quantity index) and CAGDP11 (contributions to the percent change in real GDP). They share their line numbers, so a row is one area, line and year with the four figures side by side. The line's description, NAICS codes and whether it is a total come from CAGDP2: a line is a total where the next line is indented below it, and lines 87–92, BEA's alternative groupings, are totals too.

Each cell is BEA's figure scaled from its unit (thousands of dollars) to dollars as exact decimal text, or, where BEA wrote a code in parentheses, a null with the code kept in codes; (NA) is a null with no code. The files are Latin-1. The stage checks the header, every unit and the table names it reads, counts the rows it expects, and dates the load by the "Last updated" line in the CSV's footer.

Changed from the source: cut to Florida; reshaped from one row per area and line with a column per year to one row per area, line and year with a column per table; figures converted to dollars; BEA's codes stored as nulls with the code beside them; footnote marks dropped from names and descriptions; the indent recorded as is_total.

Public domain; BEA asks to be cited as the source.

Field → column mapping

Source field	Column	Type	Description
GeoFIPS	`geoid`	text	Leading space and quotes dropped
GeoName	`name`	text	Footnote mark (`*`) dropped
LineCode	`line_code`	smallint
Description	`industry`	text	Indent and footnote marks dropped
IndustryClassification	`naics`	text	`...` stored as null
Region, TableName, Unit	(dropped)		TableName and Unit checked
`2001` …	`year`	smallint	One row per year column
CAGDP2 cells	`gdp`	numeric	As published, with thousands or millions of dollars scaled to dollars
CAGDP9 cells	`real_gdp`	numeric	As published, with thousands or millions of dollars scaled to dollars
CAGDP8 cells	`quantity_index`	numeric	As published, with thousands or millions of dollars scaled to dollars
CAGDP11 cells	`real_gdp_contribution`	numeric	As published, with thousands or millions of dollars scaled to dollars

provenance/fl_census_counties.md

↑ Contents

Provenance: `fl_census_counties`

This file describes how the rows in PostgreSQL table fl_census_counties were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: fl_census_counties
Family: Census
Display name: Census Counties (Florida)
Source URL: https://tigerweb.geo.census.gov/arcgis/rest/services/TIGERweb/tigerWMS_Current/MapServer/82
Also from: https://www2.census.gov/programs-surveys/cfs/technical-documentation/geographies/list2022.xlsx
Geometry (source / stored): polygon / geometry(MultiPolygon, 4326)
Update cycle: Yearly

Pipeline

Two Census Bureau sources, joined on the county's 5-digit FIPS code:

Boundaries: TIGERweb tigerWMS_Current layer 82 ("Counties"), where=STATE='12', GeoJSON, outSR=4326, keyset-paged on GEOID.
CFS areas: sheet CFSAreas of the 2022 Commodity Flow Survey county list, the Florida rows (ST = 12). Only the 2022 columns are kept.

The two must name the same counties, or the sync fails. FAF's fl_faf_county_xwalk is built from this table: each county's cfs_geoid is the CFS22_ID of one FAF6 zone.

Field → column mapping

Source field	Column	Type	Description
TIGER `GEOID`	`geoid`	varchar(5)	state + county FIPS
TIGER `GEOID`, last 3	`county_fips`	varchar(3)	county FIPS
TIGER `NAME`	`name`	varchar(60)	e.g. `Miami-Dade County`
CFS `CFS22_AREA`	`cfs_area`	varchar(5)	CSA/MSA code, or `99999`
CFS `CFS22_TYPE`	`cfs_area_type`	varchar(1)	C, M or R
CFS `CFS22_NAME`, whitespace collapsed	`cfs_area_name`	varchar(120)	the workbook pads some names with doubled and trailing spaces
CFS `CFS22_GEOID`	`cfs_geoid`	varchar(19)	e.g. `E330000US1237000000`
TIGER `AREALAND`	`aland_m2`	bigint	square meters
TIGER `AREAWATER`	`awater_m2`	bigint	square meters
TIGER `INTPTLAT`	`intptlat`	double precision	internal point
TIGER `INTPTLON`	`intptlon`	double precision	internal point
geometry	`geom`	geometry(MultiPolygon, 4326)	`ST_Multi(ST_GeomFromGeoJSON)`

Geometry

SRID 4326 (WGS84). GIST index on geom.

Change detection

The Census sync's check compares the layer's vintage ("January 1, 2026 vintage") and Florida's row count, and the county list's Last-Modified and length. A change to either marks Census stale, and the next Census sync rebuilds this table, then FAF's crosswalk.

Attribution

US Census Bureau. TIGER products are free to use with acknowledgement of the U.S. Census Bureau as the source; the CFS county list states no terms.

Real GDP Growth by County, 2017–2022

Layers

Data sets used

Ask your own question about Florida

Transcript

State Planner chat · https://stateplanner.com

Prompt

Response

Exploratory Queries

Query 1 — Compute real GDP change 2017-2022 by county.

Map Layer Queries

Real GDP change 2017–2022 (chained 2017 $) — colored by "cls": 40% or more (#00441b), 30–40% (#238b45), 20–30% (state: 22.8%) (#74c476), 10–20% (#c7e9c0), 0–10% (#fff7bc), Decline (#d7301f)

Used Data Sets

Provenance: fl_bea_county_gdp

Identity

Pipeline

Field → column mapping

Provenance: fl_census_counties

Identity

Pipeline

Field → column mapping

Geometry

Change detection

Attribution

Provenance: `fl_bea_county_gdp`

Provenance: `fl_census_counties`