Financial Intermediation and Aggregate Demand: A Sufficient Statistics Approach
What this paper finds — and why it matters
This paper develops a sufficient statistics approach to measuring the aggregate demand effects of financial intermediation disturbances — shocks to the ability of financial intermediaries to supply credit. The central contribution is characterizing, in a general class of models with heterogeneous firms and financial frictions, the aggregate demand impact of a disruption to intermediary balance sheets as a function of a small set of sufficient statistics observable from data: the elasticity of investment to intermediary net worth, the share of investment financed through intermediaries, and the sensitivity of asset prices to intermediary capacity. The approach does not require full model estimation, allowing model-free measurement of the aggregate demand loss from identified intermediary distress episodes. Applied to the 2008–2009 financial crisis, the paper estimates that the shock to financial intermediary balance sheets generated an aggregate demand reduction of 3–4 percentage points of GDP — substantially larger than estimates from reduced-form regressions that do not account for general equilibrium propagation.
Summary of a forthcoming paper, AI-assisted and human-reviewed. See the linked original for the authoritative claims and full conditions.
Q1. What are the key sufficient statistics?
The three sufficient statistics are: (1) the elasticity of investment to intermediary net worth — how much investment falls per dollar of balance sheet loss; (2) the share of investment financed through intermediaries — how broadly the balance sheet shock propagates; (3) the sensitivity of asset prices to intermediary capacity — how much collateral values fall when intermediaries are distressed. Together these three moments summarize the aggregate demand impact of a balance sheet shock without requiring the researcher to specify the full structural model.
Q2. Why does the sufficient statistics approach give larger estimates than reduced-form regressions?
Reduced-form regressions typically compare investment of firms exposed to distressed versus healthy intermediaries, capturing the partial equilibrium direct effect of credit supply reduction; the sufficient statistics approach accounts for the general equilibrium propagation — the fall in asset prices and investment that affects even firms not directly borrowing from distressed intermediaries. The 3–4 percentage point estimate includes these spillovers; the reduced-form estimate misses them.
Q3. What is the policy implication?
The larger aggregate demand estimate implies that recapitalizing intermediaries during financial crises generates larger macroeconomic benefits than direct-effect estimates would suggest, strengthening the case for bank bailouts, TARP-style capital injections, and central bank emergency lending as counter-recessionary tools. The sufficient statistics framework also provides a natural way to compare intervention magnitudes: a policy that restores $X of intermediary capital generates an aggregate demand boost proportional to the measured elasticity.
Key concepts
sufficient statistics for financial intermediation : the small set of model-free moments (investment elasticity to net worth, intermediary financing share, asset price sensitivity) that summarize the aggregate demand impact of intermediary distress, derived in this paper from a general class of heterogeneous-firm models.
general equilibrium propagation : the amplification of an intermediary balance sheet shock through asset price declines and economy-wide investment responses, which the sufficient statistics approach captures and reduced-form regressions miss; the source of the larger 3–4 pp GDP estimate relative to partial equilibrium benchmarks.