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Dillon County, South Carolina

Single-family vs. condo trends, market pressure signals, and 5-year price history. Source: Redfin.

Low transaction volume. Dillon County, South Carolina averaged 5 sales in the latest reporting month, so YoY price moves can swing wildly between months and don't necessarily reflect market direction. Inventory + DOM + price-drop signals stay informative; the % change badges are suppressed below 10 monthly sales.
Median Sale Price
$195,000
low-volume — YoY suppressed
Active Inventory
43
Days on Market
98 days
Price Drops
27.9%

Single-Family vs. Condo

Source: Redfin (property-type breakdown)
Single-Family Median
$195,000
Condo / Co-op Median
$190,500
SFR vs. Condo YoY Gap
+25.8%
SFR outperforming condos
DOM: SFR vs. Condo
98d / 2d
SFR / Condo

Buyer vs. Seller Market Indicators

Latest month — Redfin
Months of Supply
8.6 mo
Buyer market

Inventory ÷ monthly sales. Below 3 = strong seller market; 3-6 balanced; above 6 = buyer market.

Sale-to-List Ratio
98.4%
At asking

Median closing price ÷ original list price. Above 100% = homes routinely closing above asking.

% Sold Above List
0%
Buyer-favorable

Share of closed sales priced above asking. The single cleanest read on bidder competition.

What does your sqft target cost in Dillon County, South Carolina?

$141/sqft median (Redfin)
+$0 adj
+$0 adj
optional
Estimated price
$281,052
Above median range (+44% vs median)
Region median
$195,000
all homes
Price-tier reverse lookup — what sqft does each price band buy?
$600,000
≈ 4,270 sqft
$1,200,000
≈ 8,539 sqft
$2,000,000
≈ 14,232 sqft
$5,000,000
≈ 35,581 sqft

Estimate = (median $/sqft × your sqft) + bed/bath/lot adjustments. Bed and bath adjustments use Appraisal Institute / Fannie Mae standard rules of thumb (~$15K/extra bedroom, ~$20K/extra bathroom vs. a 3bd/2ba baseline; half-bath = half adj). Lot premium is a $1.50/sqft heuristic beyond a 6,000 sqft baseline — accuracy varies sharply by urban infill vs. acreage market. Quality, condition, year built, and HOA are not modeled here. For a deeper county-level hedonic AVM, see AVM Lite.

Rent + invest vs. buy + own — backtested

15-yr rolling history · S&P 500
Property type:
Upfront capital committed (both paths): $45K = 20% down + 3% closing on a $195K home
BUY + OWN
Median ending wealth $171K $105K real
Net gain on $45K upfront: $126K
Range: $171K → $171K
Wealth = home value (appreciated at 3%/yr) − remaining mortgage − 6% selling cost. Gain = wealth − upfront. Leveraged appreciation on full $195K asset comes from the 20% down.
RENT + INVEST
Median ending portfolio $388K $275K real
Net gain on $132K contributed: $256K
Range: $181K → $1.03M
Same upfront cash + each year's (own − rent) surplus invested in S&P 500 at actual annual returns. Median renter contributed $132K total.
Median wealth delta: $217K in favor of RENT + INVEST
What if you'd started in a recent year? (most-recent 15yr window: 2011–2025)
WindowBuy wealthBuy gainRent wealthRent gainWealth delta
2011–2025$171K$126K$580K$448K$408K rent
2010–2024$171K$126K$592K$460K$421K rent
2009–2023$171K$126K$570K$438K$399K rent
2008–2022$171K$126K$388K$256K$217K rent
2007–2021$171K$126K$502K$370K$331K rent
2006–2020$171K$126K$430K$298K$259K rent
2005–2019$171K$126K$386K$254K$215K rent
2004–2018$171K$126K$318K$186K$147K rent

Educational tool, not investment or real-estate advice. Past performance does not guarantee future results. Backtests use actual annual total returns including dividends from S&P 500 (Damodaran (NYU Stern) annual total return (with dividends), 1957-present.).

Buyer model: 30-yr fixed mortgage, P&I + property tax + insurance + maintenance (1% of value/yr) + HOA. Selling cost = 6%. Investor model: down payment + annual cashflow surplus invested in the chosen index at that calendar year's actual return.

Tax model: pre-tax comparison. Toggle "after-tax mode" to apply MID, SALT, LTCG, and the Sec 121 capital-gains exclusion.

This calculator does not adjust for: PMI (assumed 20%+ down), differential transaction costs by state, lifestyle factors (commute, schools, kids), illiquidity / forced-sale risk, or insurance availability constraints (e.g., FL/CA wildfire). Consult a fiduciary advisor and tax professional before acting on any of this.

Market Pressure Signals

Derived from Redfin trend
Inventory vs. Long-Term Avg
+0.9%
roughly balanced
DOM vs. 24-Mo Avg
-0.5%
currently 98 days
Long-Term Avg Inventory
43
Long-Term Avg DOM
99 days

Mortgage & Price Stress

State HPI + national delinquency
State HPI YoY
+3.8%
positive — appreciating
State HPI vs. Peak
0.0%
at or near peak peak 2026-04-01
National Mortgage Delinquency
1.86%
benchmark — 2026-04-01 county-grain delinquency requires paid data

State-grain HPI YoY + drawdown from peak is the cleanest free price-stress proxy. The national delinquency rate gives the macro mortgage-stress backdrop. True county-level mortgage delinquency lives in paid datasets (MBA NDS, CoreLogic LP).

Getting a Mortgage Here

CFPB HMDA 2025
Applications Denied
45.4%
21.0 pts harder than South Carolina
Loans Actually Made
315
262 turned down
Average Loan Made
$160,746
what lenders here actually wrote
National Denial Rate
23.4%
benchmark — all 51 states

Every lender above a size threshold has to report each application and what they did with it. The denial rate here counts only applications a lender actually ruled on — approved or denied. Files the applicant withdrew, and files closed as incomplete, are left out of both halves, so this runs higher than tables that bury them in the denominator. Compare every state and county →

Value Ratios

Median home price ÷ county median income
Value / Income
4.4×
stretched
Median Household Income
$44,038
Census ACS B19013

Historically affordable markets sit at 3–4× income; over 5× is stretched, over 6× is severely overvalued. Lower ratios point to bargain opportunities.

Housing Stock & Owners

Census ACS 5-year (B19013, B01003, B25002, B25003, B25034, B25007)
Population
28,031
total residents
Total Housing Units
12,879
all units, occupied + vacant
Vacancy Rate
17.8%
high vacancy
Homeownership Rate
60.3%
of occupied units owner-occupied
Boomer Owners (65+)
23.7%
of homeowner households
Millennial / Gen-X Owners (35-54)
5.4%
of homeowner households
Pre-1949 Housing Stock
8.7%
structures built before 1949

When boomer-owner share is high, expect more inventory hitting the market over the next decade as homes transition. High vacancy + high old-stock often signals deferred-maintenance markets where buyers can negotiate.

Net Migration (IRS Tax Returns)

IRS Statistics of Income — Migration Data
Net Migration
-45
losing people (2022–2023)
Inbound Returns
246
479 people moved in
Outbound Returns
253
524 people moved out
Net Returns
-7
household-filer basis

Top 5 Origins (where movers came from)

  1. Marion, South Carolina — 83 returns
  2. Florence, South Carolina — 66 returns
  3. Horry, South Carolina — 40 returns
  4. Robeson, North Carolina — 30 returns
  5. Marlboro, South Carolina — 27 returns

Top 5 Destinations (where movers went)

  1. Marion, South Carolina — 76 returns
  2. Florence, South Carolina — 69 returns
  3. Robeson, North Carolina — 45 returns
  4. Horry, South Carolina — 39 returns
  5. Marlboro, South Carolina — 24 returns

IRS Statistics of Income tracks county-to-county migration via tax-return change-of-address. Net migration uses the exemption count (a proxy for people, including dependents). True net flow can lag by 1–2 years vs. real-time movements.

Who's Moving In (Census ACS)

Source: Census ACS B07001 (5-year)
Inbound Movers (1 yr)
1,415
5.14% of pop. — moved here from outside the county
From Other States
605
2.2% of pop. — interstate inbound
From Abroad
—
moved into the county from outside the U.S.
Same House 1 Year Ago
89%
stable residents

Census ACS asks where people lived 1 year ago, so this counts inbound movers but does not show outbound — true net migration would require IRS SOI parsing.

Trends

Up to 5 years of monthly data

Median Sale Price

Trailing 12 months

Active Inventory

Trailing 12 months

Days on Market

Trailing 12 months

Looking for state-level data? See South Carolina statewide stats →

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