lihtc-calc 0.1.0

LIHTC transaction calculator — qualified basis, applicable fraction, 4%/9% credit, 15-year compliance, recapture, and investor IRR

lihtc-calc

Professional-grade Low-Income Housing Tax Credit (LIHTC) calculator for Python.

Model LIHTC transactions end-to-end: eligible and qualified basis, QCT/DDA 30% boost, 4% vs 9% applicable percentage, 10-year credit delivery, investor IRR, 15-year compliance tracking, and IRC §42(j) recapture math — all with type hints and structured result objects.

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Why lihtc-calc?

LIHTC is the primary federal subsidy for affordable housing in the United States, allocating ~$10 billion in annual tax credits. Transactions involve layers of IRC §42 math that are easy to mis-model in spreadsheets. lihtc-calc provides auditable, tested Python functions that match IRS and state-agency conventions.

Installation

pip install lihtc-calc

No external dependencies — pure Python 3.9+.

Quickstart

from datetime import date
from lihtccalc import (
    LIHTCDeal,
    build_credit_result,
    ComplianceTracker,
    recapture_amount,
    investor_irr,
    build_investor_cash_flows,
    gp_lp_split,
)

# Define a 9% new-construction deal in a QCT
deal = LIHTCDeal(
    project_name="Riverside Commons",
    total_dev_cost=12_000_000,
    eligible_basis_adjustment=0.82,       # 82% of TDC is eligible basis
    applicable_fraction_units=0.95,
    applicable_fraction_floor_area=0.93,  # floor-area fraction is binding
    credit_type="9pct",
    placed_in_service_date=date(2024, 3, 1),
    qct_or_dda=True,                      # 130% basis boost applied
    low_income_set_aside_pct=0.40,
    total_units=80,
    low_income_units=76,
)

# Credit summary
result = build_credit_result(deal)
print(result.summary())
# === LIHTC Credit Summary: Riverside Commons ===
#   Credit type          : 9pct
#   QCT/DDA boost        : Yes (130%)
#   Eligible basis       : $9,840,000
#   Boosted basis        : $12,792,000
#   Applicable fraction  : 93.00%
#   Qualified basis      : $11,896,560
#   Annual credit        : $1,070,690
#   10-year credits      : $10,706,904

# Investor IRR
annual = result.annual_credit
equity = result.total_credits_10yr * 0.95    # 95-cent credit price
flows = build_investor_cash_flows(equity, annual, residual_value=100_000)
irr = investor_irr(flows)
print(f"Investor IRR: {irr:.2%}")

# GP/LP equity split (standard 99.99% LP structure)
gp, lp = gp_lp_split(equity)
print(f"LP equity: ${lp:,.0f}  |  GP equity: ${gp:,.0f}")

# 15-year compliance tracking
tracker = ComplianceTracker(deal=deal)
for yr in range(1, 6):
    cy = tracker.track_year(yr, low_income_units=76, total_units=80)
print(tracker.summary())

# Recapture if compliance breaks in year 5
event = recapture_amount(deal, violation_year=5)
print(event.summary())

Key Features

Feature	Detail
Basis math	Eligible basis, QCT/DDA 130% boost, qualified basis via lower of unit/floor-area fraction
4% vs 9% credit	Fixed applicable percentages (3.64% / 9.00%) matching IRS 2024 guidance
10-year delivery	Level annual credit schedule, summed total credits
Equity modeling	Credit-price-to-equity, 99.99% LP / 0.01% GP split
Investor IRR	Newton-Raphson IRR with arbitrary cash-flow vectors
Compliance tracker	Year-by-year set-aside and AMI verification over 15-year period
Recapture (IRC §42(j))	Declining recapture schedule, interest penalty, bond-disposition analysis
Result objects	CreditResult, RecaptureEvent with .summary() methods

Use Cases

• Syndicators & investors — Quickly model credit delivery and investor return sensitivity.
• Developers & consultants — Validate qualified basis before submitting state tax credit applications.
• Compliance officers — Track annual set-aside and AMI tests; flag violation years automatically.
• Asset managers — Model recapture exposure for portfolio risk reporting.
• Policy researchers — Batch-analyze LIHTC economics across geographies and deal types.

API Reference

Core Functions

eligible_basis(deal)          # total_dev_cost × adjustment factor
applicable_fraction(deal)     # min(unit_fraction, floor_area_fraction)
boosted_basis(deal)           # eligible_basis × 1.30 if QCT/DDA
qualified_basis(deal)         # boosted_basis × applicable_fraction
annual_credit(deal)           # qualified_basis × applicable_percentage
total_credits_10yr(deal)      # annual_credit × 10
credit_price_to_equity(deal, price)
build_credit_result(deal)     # → CreditResult with .summary()

investor_irr(cash_flows)      # Newton-Raphson IRR
gp_lp_split(equity, lp_pct)  # → (gp_equity, lp_equity)
build_investor_cash_flows(equity, annual_credit, residual_value)

ComplianceTracker(deal)
  .track_year(year, low_income_units)
  .set_aside_compliance(year)
  .ami_verification(household_income, ami, limit_pct)
  .any_violation()
  .violation_years()
  .summary()

recapture_amount(deal, violation_year)   # → RecaptureEvent
accelerated_credits(deal)                # 15-year at-risk schedule
bond_disposition(deal, disposition_year) # § 42(j)(6) analysis

License

MIT © Jay Patel