美联储-房屋及家居用品_购房支出渠道（英）-2025_50页_809kb

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# Research Summary: House Purchase Channel of Expenditure

## Abstract & Main Contribution

This paper examines the **home purchase channel of expenditure**, wherein home purchases significantly increase spending on home-related goods (furniture, renovations, maintenance), while leaving unrelated goods expenditure unchanged. Using household-level U.S. data (1975–), the authors demonstrate that this channel substantially amplifies aggregate spending fluctuations over the housing cycle.

Key findings:
1. Households spend an average of **$7,000 more** on home-related goods around purchase dates, equating to an 80% increase.
2. This effect is larger for first-time buyers and highly persistent.
3. Placebo tests show spending increases only with home purchases, not moves or vehicle buys.
4. Model simulations confirm that the home purchase channel drives significant fluctuations in consumption, accounting for 40–75% of aggregate spending variability during housing booms/busts—with no change in unrelated spending.

## Data & Methodology

### Key Data & Evidence
- Draws from **Panel Study of Income Dynamics (PSID)**, analyzing housing transactions and expenditure changes.
- Employs **event-study regressions** comparing spenders before/after home purchases, with controls for demographics, age, income.
- Controls include **close-matches** (e.g., renters vs. movers) and **placebo tests** (e.g., comparing vehicle vs. home purchases).

### Model
- **Heterogeneous agent life-cycle model** with housing choices, durable goods, and expenditure decisions.
- Calibrated to match empirical findings, with parameters for mismatch shocks (e.g., furniture depreciation when moving).

## Policy Implications

The home purchase channel provides a **new explanation** for housing market-driven economic fluctuations, independent of standard credit or collateral channels. Changes in mortgage constraints or wealth effects explain some fluctuations, but the direct **spending effect** of home purchases nearly doubles the contribution to aggregate demand during booms/busts. This has implications for policies affecting housing markets and consumer credit.

## Technical Notes

The estimated parameters and findings ("$7,000 average increase", "80% rise", "50 quarters persistence") are central to the conclusions and subject to specific calibration and robustness checks in the JEL classifications below.

## Journal of Economic Literature (JEL) Codes

D12, D15, E21, E32, R31

## References *(Selected Key Citations)*

- Benmelech et al. (2023)
- Favara, Graham & Li (2025)
- Kaplan et al. (2020)

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