MIT CRE — 11.S969 Commercial Real Estate Investment Strategy

Group Presentation #1

Assignment

Your team is launching an investment vehicle to acquire and manage open-air retail (neighborhood centers and strip centers) in a single U.S. metropolitan statistical area (MSA). The fund has an indefinite hold period similar to a public Real Estate Investment Trust (REIT).

Open-Air Retail

Your fund targets neighborhood centers (typically grocery-anchored or drugstore-anchored multi-tenant centers) and strip centers (smaller open-air centers, anchored or unanchored). These two formats represent the largest retail subtypes by square footage nationally and have demonstrated consistent vacancy compression over the past decade.

Excluded: Enclosed malls, lifestyle centers, power centers, and single-tenant/NNN. Suggested format overview & recent history:

• Retail Format Divergence: Seven Asset Classes Under One Label
• E-Commerce & The Oversold Retail Apocalypse

Deliverables

Each team delivers an in-class presentation (PowerPoint style) with a 3-page (max) bullet point memo outlining key points. Each team member is expected to prepare and present at least one slide.

MSA Selection & Thesis

Present the demographic, economic, and supply-side case for your chosen MSA over a 10–20 year investment horizon. Your thesis should address:

• Population growth and migration trends. Is the MSA gaining or losing people? From where? Is growth driven by domestic migration, international immigration, or natural increase? How sustainable are those drivers?
• Employment and income dynamics. What industries drive the local economy? Is household income growing? Are there concentrations of employment that create risk?
• Retail supply context. What is the existing retail inventory per capita? How does recent construction activity compare to absorption? Is the market building new competitive supply or is it constrained?
• Growth vs. mature market positioning. Where does your MSA fall on the growth-to-mature spectrum, and what does that mean for your strategy?

Suggested Materials

• Domestic Migration & Regional Growth — Sun Belt population dynamics, state-level flows, sustainability of migration patterns
• U.S. Demographics and Economic Forces — Generational sizing, fertility decline, immigration trends
• Growth vs. Mature Markets: Retail Supply & Demand Divergence — How growth and mature metros achieve vacancy compression through different mechanisms
• National CRE Supply Trends vs. Population and GDP — Cross-asset supply dynamics; retail construction collapse in national context
• U.S. States Population Pyramid Comparison Tool — Visual comparison of state by state demographic profiles

▶ Explore Population Pyramids by State, 1969–2024

Notes

Source. NCI SEER U.S. County Population Data, 1969–2024 release (February 2026), Katrina/Rita-adjusted, 20 age groups. SEER population files are produced under interagency agreement with the U.S. Census Bureau and are the Census county population estimates in bridged form. All 17.5 million county records were aggregated to the 51 state-level geographies, summing across race, origin and registry. Population is measured as of 1 July each year.

Validation. Summed across the 51 geographies, the 2024 total of 340,110,988 reproduces the Census Bureau national figure exactly; California at 39,431,263 likewise matches the published state estimate.

Bands. Eighteen five-year bands, 0–4 through 80–84 plus 85 and over. SEER resolves to 90 and over, but the top two bands are combined so the band structure matches the national chart above exactly and the two can be read against each other.

Katrina and Rita. The adjusted file carries a pseudo-geography coded KR for 2005 only, holding 203,937 persons displaced by the 2005 hurricanes whose destination county could not be assigned. It is excluded here because it is not a place, so the 2005 national sum across states runs approximately 204,000 light. State-level figures for Louisiana and Mississippi in 2005 and 2006 reflect the SEER adjustment.

Statistics. Because 15 and 65 fall on band boundaries, the dependency ratios are exact; median age is interpolated within the five-year band containing the midpoint. Generation boundaries follow Pew Research Center definitions and match the national chart above.

Submarket Targeting

Identify a target submarket and explain why it is positioned for above-market rent growth. Consider:

• Household income and density. What are the demographics of the trade areas you’re targeting? Higher income supports higher rents and more resilient tenancy.
• Supply constraints. Are there barriers to new construction (zoning, land cost, entitlement timelines) that protect your assets from competitive supply?
• Anchor tenant quality. What types of tenants dominate the submarket? Grocery, medical, restaurant, and service tenants are more e-commerce-resistant than discretionary goods retailers.
• Infill vs. suburban growth corridors. Are you targeting established infill locations with replacement-cost barriers, or newer suburban corridors following rooftop growth?

Suggested Sources

• CoStar Analytics
• U.S. Census Bureau — American Community Survey
• FRED — Federal Reserve Economic Data
• Placer.ai — Retail Foot Traffic Analytics
• CBRE / JLL / Cushman & Wakefield / Colliers

Rent Growth Thesis

Why will rents grow faster than inflation? This is the core of your investment case. Identify the structural factors that support above-inflation rent growth in your target submarkets over a long hold period:

• Supply constraints. Rising construction costs, limited available land, and the post-2017 retail construction collapse mean very little new competitive supply is being delivered nationally. Is this true in your market specifically?
• Population growth driving demand. Net in-migration and household formation create incremental demand for retail-serving goods and services. Quantify the population growth trajectory for your MSA.
• Tenant category resilience. Grocery, restaurant, medical, and personal services tenants are resistant to e-commerce displacement. Is your target submarket anchored by these categories?
• Below-replacement-cost rents. In many markets, existing retail rents are well below the cost of building new competitive product. This gives landlords pricing power as leases roll.

Suggested Materials

• E-Commerce & The Oversold Retail Apocalypse
• Home Affordability Crisis
• Senior Population Growth and Senior Living Demand
• CoStar Analytics

General Economic and Other Conditions

• Demographics: Required for this case; age cohorts and demographic dispersion suggested
• Inflation & Interest Rates
• Trade & Trade Policy
• Climate Change
• Technology

Scope & Constraints

Parameter	Constraint
Target format	Neighborhood centers and strip centers only
Geography	Single MSA & CoStar submarket (your choice)
Hold period	Indefinite (perpetual-life REIT structure)
Capital structure	Assume 100% equity (no leverage)
Excluded	No individual deal proformas; no tenant-level underwriting

Suggested Data Sources

• CoStar — MSA and submarket-level vacancy, absorption, deliveries, rent, and inventory data by retail subtype (available through MIT CRE)
• U.S. Census Bureau — Population estimates, American Community Survey (household income, age distribution, migration)
• Brokerage research (Q4 2025) — CBRE, JLL, Cushman & Wakefield, Colliers national and MSA-level retail market reports
• FRED / BLS — Employment data, CPI components, wage growth by MSA
• ICSC / NAREIT — Retail REIT performance data; shopping center metrics

Evaluation Criteria

Presentations will be evaluated on:

• Clarity of thesis
• Data discipline
• Supply-demand reasoning
• Counterpoint analysis
• Presentation quality and group participation

Scope: This is a first-class exercise. The goal is not a comprehensive fund pitch—it’s to practice thinking about market selection through the lens of long-term supply-demand dynamics. Keep the analysis focused.