Macro Paper Warehouse Forthcoming macro & monetary research
Forthcoming [Journal of Money, Credit and Banking] doi:10.1111/jmcb.13232

The Macroeconomic Effects of a European Deposit (Re-)Insurance Scheme

Marius Clemens

Stefan Gebauer

Tobias König

What this paper finds — and why it matters

Layer 1: Overview

Research question and motivation: The first two pillars of the European Banking Union (single supervision and single resolution) are in place, but the third pillar — a European deposit insurance scheme (EDIS) — is still missing. Recent policy proposals favor a reinsurance design, where European deposit insurance steps in only after national deposit insurance (DI) funds are depleted. The paper asks how well such a deposit reinsurance scheme absorbs macroeconomic and financial shocks relative to alternatives, and quantifies its stabilization, welfare, and moral-hazard implications.

Model and method: The authors build a two-country regime-switching open-economy DSGE model with bank default, calibrated to Germany (home) and the euro area excluding Germany (foreign). Banks face idiosyncratic log-normal asset-return shocks and limited liability, so they can default and leave depositors (facing state-verification/monitoring costs) with losses. National DI funds collect risk-weighted contributions from banks and compensate insured depositors; when a fund is exhausted (DI_t <= 0), the share of insured deposits drops to zero and the economy enters a “constrained” regime. Four regimes capture whether home and/or foreign national DI is unconstrained or constrained, with Markov-switching transition probabilities (sigmoid functions). Two bank-government linkages are modeled: banks finance sovereign debt, and the fiscal authority provides tax/debt-financed guarantees on bank insolvencies. Three reinsurance arrangements are compared once national DI is exhausted: (A) no backstop, (B) national fiscal backstop, (C) EDIS. Most series are calibrated for 1999:Q1-2019:Q4 using ECB/Eurostat/OECD, Bundesbank, IMF, and micro data (Bloomberg, Eikon, Datastream). Key preset parameters: capital share 0.3, household habit 0.8, trade elasticity 1.5, home bias in traded goods 0.6, Basel III steady-state bank capital requirement 10.5 percent, LTV ratio 0.35, bank monitoring costs 0.3, DI and EDIS contribution sensitivity 0.45. Twelve remaining parameters are set by first-moment matching (total distance 2.836). The EDIS fund target is 0.8 percent of insured deposits; the simulated bank risk shock doubles the standard deviation of idiosyncratic bank asset returns to deplete national DI.

Main quantitative findings: In response to an adverse home bank risk shock that depletes national DI (regime switch in period three), EDIS stabilizes the affected economy better than the fiscal or no backstop. Peak-to-trough GDP declines 0.3-0.4 percent across scenarios (deepest under no-backstop). Home output decline is about 10-20 percent smaller with EDIS; home consumption falls about 0.4 percent peak-to-trough with EDIS; investment declines are 30-40 percent smaller and bank loans 30-50 percent smaller with EDIS versus the other scenarios. The abstract/intro summarize the investment/consumption/loan gains as roughly 20-35 percent lower in the trough. The debt-to-GDP ratio rises markedly under the fiscal backstop but stays broadly stable under EDIS, since costs are covered by bank contributions rather than public debt. Costs of EDIS: banks contribute to both national DI and EDIS, raising the total burden and making national-fund recovery slowest under EDIS; foreign banks must contribute more, reducing margins and foreign lending. In a robustness analysis taking IRF differences one year after the shock, the baseline EDIS effect on home GDP is +0.1 ppt (range 0.05 to above 0.3 ppt across parameters) and on foreign GDP +0.06 ppt (range 0.02-0.2 ppt). Welfare (consumption equivalents, 100 x lambda_w, vs fiscal backstop baseline): differences are small but EDIS benefits savers in constrained economies, with the largest union-wide gains when both economies are constrained (regime 4). Risk-weighting contributions by country-specific default costs (baseline home share ~32 percent, foreign ~68 percent) renders EDIS risk-neutral in the long run so it does not foster additional moral hazard; only non-risk-weighted contributions induce structurally higher risk-taking that macroprudential policy can correct. The link between steady-state capital requirements and activity is hump-shaped with an optimum at 12 percent; the best stabilization comes when both EDIS and macroprudential policy are active and capital requirements are at 10.5 percent. A novel bank-run extension (state-dependent monitoring costs of 0.3 vs 0.6, plus a sunspot shock) shows runs deepen the output trough by about 40 percent relative to the no-run case, and that EDIS can prevent a self-fulfilling run by stopping the economy from entering the “in-between” region.

Implications: A European deposit reinsurance scheme can deliver union-wide welfare gains and macro-financial stabilization, but regulators must design contribution and deductibility rules to avoid overburdening banks and constraining credit, ensure EDIS can pay out instantaneously once introduced, and recognize that costs and benefits are unequally distributed across countries, savers, and borrowers.

Layer 2: Deep Dive

What is the modeling/identification strategy and what are its main limitations?

The strategy is a calibrated two-country regime-switching DSGE model (solved with the RISE toolbox), not an empirical causal-identification design. Identification of mechanisms comes from comparing counterfactual policy scenarios (no backstop, national fiscal backstop, EDIS) under the same bank risk shock. The authors themselves flag that the analysis is counterfactual: the euro area has not actually experienced explicitly exhausted national DI funds (the closest episode being October 2008 government deposit pledges). The main limitations are parameter uncertainty (the model is calibrated, not fully estimated) and the fact that the home/foreign calibration to Germany and the rest of the euro area does not imply general validity for other member states, motivating the robustness analysis.

What are the four regimes and how does regime switching work?

Regimes are defined by whether each country’s national DI is unconstrained (fund positive, insured share = kappa-bar) or constrained (fund <= 0, insured share = 0): Regime 1 both unconstrained; Regime 2 home constrained; Regime 3 foreign constrained; Regime 4 both constrained. Transition probabilities follow sigmoid (Markov-switching) functions: the probability of entering the constrained regime is one when the fund level hits zero (scaling alpha2 = 200), and the probability of switching back becomes one when bank default rates drop below a financial-stress threshold (scaling alpha1 = 300).

What are the main mechanisms distinguishing EDIS from the fiscal backstop?

Under the fiscal backstop, depositor losses enter the national government budget constraint, raising the debt-to-GDP ratio and affecting taxes/expenditure. Under EDIS, losses are covered by internationally shared, risk-weighted bank contributions, so public debt stays broadly stable. The trade-off: EDIS imposes a higher total burden on banks (they fund both national DI and EDIS), slows national-fund recovery the most (because EDIS contributions are deductible from national payments, stretching the refilling of two funds), and transmits the contribution burden to foreign banks, reducing their margins and lending. For the foreign economy, EDIS has an expansionary trade/financial channel that dominates in the first ~5-6 quarters and a contractionary higher-contribution channel that dominates in the medium-to-long run.

What heterogeneity is documented across the two countries?

Germany (home) has a higher home bias in bank equity (~80 percent) attributed to Landesbanken, savings and cooperative banks, and lower bank default risk (lower sigma of idiosyncratic asset-return shocks). The rest of the euro area (foreign) is the riskier banking sector with a higher default-shock standard deviation, so under risk-weighted contributions it bears the larger EDIS share (~68 percent vs ~32 percent home). Welfare effects differ: EDIS raises entrepreneurial welfare in the riskier foreign country but lowers it in the safer home country; savers in constrained economies gain.

What robustness checks are run and what do they show?

The authors re-simulate the same home bank risk shock over minimum/maximum plausible ranges for calibrated and matched parameters, taking IRF differences one year out. The positive EDIS effect on home GDP is robust across all ranges where national DI depletes (0.05 to above 0.3 ppt; baseline 0.1 ppt); the foreign GDP effect ranges 0.02-0.2 ppt (baseline 0.06 ppt). Influential parameters include the goods home-bias/openness (more open economies gain less from EDIS), the LTV ratio, bank monitoring costs, and the idiosyncratic asset-return shock standard deviation (larger sigma means a more severe crisis and larger EDIS benefit). Higher fund target rates or insured-deposit shares can prevent depletion, in which case EDIS does not intervene and its effect is zero. Higher household-to-banker transfers and banker survival rates raise net worth, lower default risk, and shrink the EDIS effect. A sensitivity analysis on monitoring costs affects only quantitative, not qualitative, conclusions.

How is welfare measured, and what does the contribution-weight analysis find?

Welfare is computed in the stochastic steady state (Coeurdacier et al., 2011) using a second-order approximation, expressed in consumption equivalents (lambda_w), aggregating borrowers and savers with Pareto weights (welfare weight zeta = 1). Conditional welfare is reported by regime relative to a fiscal-backstop baseline; EDIS gains are largest in regime 4 (both constrained), and deductibility (EDIS 1) is welfare-improving especially in the affected country versus no deductibility (EDIS 2). Varying the contribution split via alpha_RW shows low alpha_RW (contributions falling on the riskier foreign banks) is welfare-optimal union-wide (’excessive risk-sharing’), but deviations toward a more moderate split impose negligible welfare cost. Higher contributions in a country raise intermediation costs, cut loans and deposits, and lower borrower welfare there.

What does the paper conclude about EDIS and moral hazard?

Because individual bank contributions are weighted by aggregate observable default risk, the steady-state default threshold is unaffected by deposit-insurance coverage, so under risk-weighted contributions EDIS does not induce additional moral hazard in the long run (defaults, firm loans, and corporate borrowing rates are unchanged by higher insurance shares in steady state). Moral hazard arises only if contributions are not risk-weighted or if long-run insurance payments do not match contributions, in which case low capital regulation fosters extra risk-taking and long-run macroprudential policy can correct it. Cyclically, EDIS can still temporarily foster risk-taking because insurance payouts are large during a crisis while contributions accrue with a lag, enlarging the complementary role for macroprudential policy.

How does the bank-run extension work and what is the key result?

The RS-FF (regime-switching financial friction) model makes monitoring costs state-dependent (0.3 in low distress, 0.6 in high distress, with the high-distress threshold set at a 2.5 percent quarterly default rate, following Linde et al. 2016). A sunspot shock can trigger a partial run in an ‘in-between’ state where depositors wrongly believe they are in high distress; non-fundamental beliefs raise the default threshold above its fundamental level (omega* > omega), some sound banks face liquidity problems and default, making beliefs self-fulfilling. A run amplifies the recession: in the no-backstop run scenario the output trough is about 40 percent lower than the no-run case (default costs roughly double, deposits about one ppt lower), a relative magnitude (ratio ~2.7) close to Gertler et al. (2020). Crucially, EDIS, by compensating depositor losses, keeps the economy out of the ‘in-between’ region and can prevent the self-fulfilling run.

How does this paper differ from closely related prior work?

It extends Mendicino et al. (2018) — a closed-economy model with bank default, deposit insurance, and optimal capital regulation — to an open two-country setting with a detailed government sector and a bank-financed deposit fund (rather than direct household transfers). Unlike Dedola et al. (2013), where financial-friction degrees are equal across countries, it allows heterogeneous bank riskiness. Unlike representative-global-bank models (Mendoza-Quadrini 2010; Kollmann et al. 2011; Kollmann 2013), it allows heterogeneous national banking sectors. Unlike Dubois (2021), which has a linear two-country bank-run model, its regime-switching nonlinearity permits an explicit reinsurance/backstop comparison. Relative to Amador and Bianchi (2022) (partial runs, U.S., no deposit insurance), it adds deposit insurance and EDIS risk-sharing and models runs as a combination of financial-regime switches and sunspot shocks.

What are the short-term implementation costs of EDIS and how can they be mitigated?

Filling the EDIS fund requires up-front bank contributions over about 3.5 years in the baseline. With deductibility, payments into national DI fall, temporarily lowering national coverage; households then demand higher deposit risk premia, reducing intermediation and activity. Removing deductibility keeps national coverage on target but the double burden lowers bank margins, lending, and raises defaults, though stress is shorter-lived. Extending the implementation horizon (e.g., to 7.5 years) lowers per-period contributions and mitigates peak default rates, but leaves coverage lower for longer, protracting the downturn. Policy options include ensuring EDIS pays out instantaneously once introduced and temporarily suspending contributions during acute distress.

Key Concepts

EDIS reinsurance scheme: In this paper, a European deposit insurance arrangement that acts as a second line of defense, paying out only once a country’s national deposit insurance fund is exhausted (the constrained regime), financed by risk-weighted bank contributions deductible from national DI payments.

Constrained vs unconstrained regime: States distinguished by whether a national DI fund is positive (unconstrained, insured deposit share = kappa-bar) or depleted (constrained, insured share = 0); the model has four such regimes across home and foreign and switches between them via Markov sigmoid transition probabilities.

Risk-weighted contributions (‘polluter-pays’): EDIS contributions allocated across countries in proportion to country-specific expected bank-default costs, so the riskier banking sector pays more; this design renders EDIS risk-neutral in the long run and prevents additional steady-state moral hazard.

Deductibility of contributions: The assumption that banks can subtract their EDIS payments from contributions to national DI funds, keeping total bank contributions from exceeding the no-EDIS level but slowing the refilling of both funds.

Bank default threshold (omega): The realization of a bank’s idiosyncratic asset-return shock below which the bank defaults on depositors; its steady-state value is shown to be independent of deposit-insurance coverage, which is the analytical basis for the no-long-run-moral-hazard result.

In-between state / sunspot-driven partial bank run: A region where a bank risk shock is large enough to bring the economy near the high-distress (high monitoring cost) state but not into it; a sunspot shock then makes depositors wrongly believe in high distress, raising the non-fundamental default threshold (omega* > omega) and triggering a self-fulfilling partial run that EDIS can prevent.

Hump-shaped capital-requirement effect: The relationship between steady-state bank capital requirements and long-run output/intermediation/welfare, peaking at an optimum of 12 percent: below it, higher default costs dominate; above it, the equity-crowding-out of lending dominates.

How this summary was made. Bibliographic fields are pulled from Crossref and OpenAlex and are not model-generated. The summary was drafted from the open-access manuscript , checked by a claim-grounding and calibration review pass, and approved before publishing. Found an error or a misrepresentation? Flag it here — corrections are welcome, especially from the authors.