Monetary-Policy-Transmission | Macro Paper Warehouse

A Heterogeneous Agent Model of Energy Consumption and Energy Conservation

Mon, 01 Jan 0001 00:00:00 +0000

Layer 1: Overview

Audzei and Sutóris ask whether inflation-targeting monetary policy affects households’ incentives to invest in energy conservation, and whether the standard central bank response to energy price shocks is welfare-optimal when agents are heterogeneous. They embed energy in both the consumption bundle and the production function of a tractable heterogeneous-agent New Keynesian (HANK) model that features Challe–Ravn–Sterk search-and-matching frictions in the labor market, nominal bond holdings, and — the paper’s central innovation — household-level energy conservation (abatement) capital that converts raw energy into energy services. The model is calibrated to the Czech Republic, with an energy share in household consumption of 10%, an energy share in production of 5%, a steady-state job-finding rate of 0.15 (targeting a poor hand-to-mouth share of 9%), and a capitalist share of 12%. The main quantitative findings are that a tighter monetary policy shock reduces abatement capital investment, increases the energy intensity of consumption, and depresses the job-finding rate, all of which fall disproportionately on lower-wealth households; conversely, a weaker policy response to a persistent energy price shock — one with a lower inflation coefficient (φ_π = 1.1 rather than the baseline φ_π = 2) — generates welfare gains for all agent groups (capitalists, employed workers, newly unemployed, long-term unemployed) despite higher measured inflation, because it preserves employment and stimulates abatement investment, reducing households’ long-run exposure to energy price shocks. The paper also shows that a “looking-through” policy (reacting to core rather than CPI inflation) does not deliver welfare benefits because it is too accommodative when energy prices rise but too restrictive once they start to fall; Ramsey-optimal policy instead features a sharp front-loaded rate spike followed by a rapid decline, minimizing aggregate consumption volatility through higher abatement capital.

In depth

Q1. What is energy conservation capital, how is it modeled, and why does it matter for the monetary policy transmission channel?

Energy conservation capital (abatement capital) is a durable investment good held by households that reduces raw energy required to produce a unit of energy service; because unemployed workers cannot afford it and its return competes with nominal savings, it creates a novel interaction between labor market outcomes and monetary policy. Households derive utility from a CES composite of non-energy consumption and energy services, where energy services are produced from raw energy multiplied by an efficiency factor that is increasing and concave in abatement capital: $E^s = f(K^e_{t-1}) E^r$, with $f(K^e) = \varphi_{1,e} (K^e)^{\varphi_{2,e}}$ and $\varphi_{2,e} = 2$. The elasticity of substitution between energy and non-energy goods is set to $\lambda_e = 0.3$, reflecting limited short-run substitutability. Abatement capital depreciates at 1% per quarter (equivalent to 4% annually, matching housing and heating systems lifetimes of ~25 years). Crucially, workers lose their abatement capital when they become unemployed (they move to a communal stock at the steady-state unemployed level $\bar{K}^e_u$), so abatement capital is not a precautionary savings vehicle and unemployed workers have no incentive to invest in it. Employed workers who optimally invest must account for the probability of becoming unemployed and therefore losing their capital. This structure means that monetary policy tightening — by raising unemployment and raising the return on nominal bonds — simultaneously pushes more workers into the non-investing unemployed pool and reduces the relative attractiveness of abatement investment for employed workers, raising the energy intensity of consumption.

Q2. What are the four agent types, and how do their asset positions differ?

The model compresses the household distribution into four types — employed workers, first-period unemployed, long-term unemployed, and capitalists — each with sharply different asset positions that determine how they are affected by monetary policy. Employed workers hold positive nominal bonds ($B’{e,t-1} > 0$) and invest in abatement capital ($K^e{e,t-1}$); they are the only group making active portfolio and investment decisions. First-period unemployed workers consume all their precautionary savings in a single period (their IMRS × R < 1) and receive 75% of unemployment benefits; they hold $B_{e,t-1} > 0$ (inherited from their last employed period) but make no new saving or abatement decisions. Long-term unemployed workers hold zero assets, receive full unemployment benefits indexed to the real wage, and maintain abatement capital at the fixed communal level $\bar{K}^e_u$. Capitalists ($\xi = 12%$ of population) own all firms, invest in productive capital and abatement capital, and are net borrowers in the steady state (rich hand-to-mouth in the Kaplan–Moll–Violante sense); they are subject to an endogenous discount factor that stabilizes the capital stock. Risk-sharing among employed workers — all employed household members pool their nominal bonds — enables tractability while preserving precautionary saving motives.

Q3. How does a monetary policy shock propagate through energy conservation decisions?

A 0.25 percentage-point positive monetary policy shock reduces abatement capital and raises energy intensity, operating through two reinforcing channels: the labor market channel (more unemployment, fewer households able to invest) and the intertemporal substitution channel (higher returns on nominal bonds reduce the relative attractiveness of abatement investment). Following the shock, the policy rate rise suppresses output and raises unemployment (Figure 3 of the paper). The increase in the job-destruction-net-of-finding probability $\omega(1-\eta_t)$ shifts more workers into the first-period unemployed pool, which carries no abatement investment. Among employed workers, the higher nominal bond return means that saving in bonds is relatively more attractive than investing in illiquid abatement capital, so their abatement holdings fall. The result is a rise in raw energy per unit of consumption, meaning the economy becomes more energy-intensive precisely when energy prices may also be elevated — a double vulnerability.

Q4. What are the welfare effects of different policy rules in response to a persistent energy price shock, and what are the magnitudes?

After a persistent hump-shaped energy price shock, welfare losses (measured as discounted infinite-horizon utility) are smaller for all agent groups under the weak-reaction policy (φ_π = 1.1, φ_y = 0) than under the baseline (φ_π = 2, φ_y = 0), even though inflation is higher under the weaker rule; the welfare gap is largest for employed workers and capitalists, and broadly preserved under alternative calibrations. Policies that react more weakly to inflation result in a smaller output recession and lower unemployment (Figures 7–9 of the paper). In the welfare simulation (Figure 9), all four agent types — capitalists, employed workers, newly unemployed, and long-term unemployed — show smaller welfare declines under the weak-reaction rule compared with baseline. Capitalists benefit because lower interest rates reduce their debt service and higher output raises firm profits. Employed and unemployed workers benefit primarily because of the higher job-finding rate, which lowers the probability of falling into the HtM state. Additionally, accommodative policy supports more investment in abatement capital, which reduces all agents’ long-run exposure to energy price fluctuations, further boosting welfare. The welfare ranking is robust to: (i) benefits fixed in nominal terms (narrower but preserved gap), (ii) more flexible wages (narrower gap; welfare ranking of capitalists reverses under flexible wages), and (iii) larger steady-state household savings (wider gap).

Q5. Why does the “looking-through” policy fail, and how does it differ from the weak-reaction policy?

The looking-through policy (φ_π = 2 on core inflation, ignoring energy-price CPI inflation) does not deliver welfare gains because it creates an asymmetric response profile: it is too accommodative during the energy price surge and too restrictive once energy prices start to fall, generating a welfare trajectory that is inferior to a consistently weaker policy. When energy prices are rising, CPI inflation exceeds core inflation; reacting only to core means the central bank does not raise rates as much as under the baseline, so the policy is more stimulative in the short term and supports output and abatement investment in the near term. However, once energy prices start declining, CPI inflation reverts to the steady state faster than core inflation (which is still elevated due to nominal rigidities), meaning the looking-through policy becomes more restrictive relative to the baseline at precisely the time when agents need support. The result is that long-run welfare, which discounts the entire future path, does not improve under looking-through relative to either the baseline or the weak-reaction rule. This finding provides an important caution against the standard “look through supply shocks” recommendation in a HANK environment with abatement capital.

Q6. What does Ramsey-optimal policy look like, and why does it differ from Taylor-type rules?

Ramsey-optimal policy — which minimizes the volatility of population-share-weighted aggregate utility — features a sharper and faster initial rate spike than the baseline Taylor rule, followed by a more rapid decline; it results in the highest abatement capital investment and lowest energy intensity of all policies considered. The Ramsey planner’s first-order conditions (solved with Dynare’s Ramsey tool, taking private-sector FOCs as constraints) imply that the policy rate peaks before the energy price shock itself peaks, reflecting the planner’s desire to front-load inflation stabilization while ensuring that rates fall quickly enough to not suppress abatement investment in the medium term. The Ramsey rate path is lower than the baseline Taylor rule after the shock peak. Compared with all Taylor-type rules, Ramsey policy results in the largest negative deviation in consumption energy intensity and the largest positive deviation in abatement capital (Figure 8). Ramsey policy also delivers the highest welfare for all agent groups (Figure 9), validating the intuition that protecting abatement investment is an important channel for central bank welfare optimization in this setting.

Q7. What is the role of heterogeneity in shaping these results, and what would be missed by a representative-agent model?

The distributional effects are essential to the paper’s core conclusions: a representative-agent model would miss the asymmetric impact of unemployment risk on energy conservation investment and would fail to generate the welfare reversal whereby a weaker inflation response dominates. Figure 6 of the paper shows the distributional responses to an energy price shock: capitalists reduce energy intensity the most because they can invest in abatement capital and their consumption is less constrained; employed workers also reduce energy intensity but less so; poor HtM households (unemployed workers) cannot adjust abatement capital and their energy intensity rises because the raw energy share in their limited consumption basket increases. The welfare comparison across agent types in Figure 9 shows that even newly unemployed workers — who lose their abatement investment and consume their precautionary savings — are better off under accommodative policy because the higher job-finding rate reduces the expected duration of unemployment. The key heterogeneity-driven mechanism absent from representative-agent models is the labor market channel: changes in unemployment risk affect who can and cannot invest in energy conservation, generating an indirect channel from monetary policy to aggregate energy intensity.

Q8. What are the model’s main limitations and scope conditions?

The paper abstracts from variable policy rule coefficients, wage-price spirals, unanchoring of inflation expectations, and open-economy dimensions beyond energy-price pass-through; the welfare ranking is conditional on the persistent energy price shock used for calibration and should not be extrapolated to short-lived or demand-driven inflation episodes. The authors explicitly note that the model operates under full-information rational expectations, which rules out the possibility that accommodation generates self-fulfilling inflation or credibility loss. Wage rigidity plays an important role: with more flexible wages, the welfare benefit of accommodative policy narrows and the capitalist welfare ranking reverses (baseline strict inflation targeting is preferred by capitalists). The “looking-through” and weak-reaction findings are specific to the persistent, hump-shaped energy price shock analyzed; for short-lived shocks the standard result (no reaction) would reassert itself. The model is also calibrated to the Czech Republic as a small open economy with above-average energy intensity; the qualitative conclusions extend to other European small open economies with similar energy share profiles, but quantitative magnitudes may differ.

Key Concepts

energy conservation capital (abatement capital) : a durable household investment good that converts raw energy into energy services more efficiently; modeled as $E^s = f(K^e_{t-1}) E^r$ with a quadratic abatement function; the level determines the energy intensity of consumption and is chosen optimally only by employed workers and capitalists.

energy intensity of consumption : the ratio of raw energy used to final consumption $E^r / C$; the paper’s key outcome variable for tracking how efficiently households use energy; a rise signals less efficient usage, a fall signals improved conservation.

looking-through policy : a monetary policy rule that reacts to core inflation (excluding energy) rather than CPI inflation, intended to avoid responding to transient supply shocks; the paper finds this does not improve welfare in a HANK setting because it creates an asymmetric response profile that is too accommodative when energy prices rise and too restrictive when they fall.

Ramsey-optimal policy : the interest-rate path that minimizes the volatility of population-share-weighted aggregate utility subject to the full set of private-sector equilibrium conditions; in this model it features a sharper front-loaded rate spike than Taylor-type rules followed by a rapid decline, and delivers the highest welfare for all agent groups by protecting abatement investment.

hand-to-mouth (HtM) households : households that are highly sensitive to income shocks but do not respond to interest rate changes as predicted by the Euler equation; in this model, poor HtM are both types of unemployed workers (zero savings, zero abatement investment), and rich HtM are capitalists (large debt, no labor income); their presence is central to the distributional welfare results.

search-and-matching frictions : the Challe–Ravn–Sterk labor market structure in which the job-finding rate $\eta_t$ is determined endogenously by the vacancy-unemployment ratio (Cobb-Douglas matching function) and job destruction is exogenous at rate $\omega$; this structure makes unemployment risk stochastic and endogenous to monetary policy, creating the key link between policy rates and energy conservation decisions.

Central Bank Digital Currency with Collateral-Constrained Banks

Mon, 01 Jan 0001 00:00:00 +0000

The paper analyzes the implications of introducing a retail central bank digital currency (CBDC) that competes with commercial bank deposits for household liquidity, in a model where banks must post government bonds as collateral to access central bank lending. The authors revisit Niepelt’s (2022) “equivalence of payment systems” result and find that equivalence survives even under a collateral constraint: the central bank can still offer loans to banks that replicate the no-CBDC equilibrium allocation, but at a lending rate lower than Niepelt’s unconstrained rate, because tighter terms are needed to incentivize sufficient loan uptake when banks must redirect portfolio holdings toward government bonds to qualify. A structural cost remains: banks must hold government bonds as collateral at the expense of extending credit to firms, so equivalence in allocation does not imply full neutrality — banks’ business models and the government’s intermediation role change even when aggregate output and prices are unchanged. In the dynamic extension where the central bank does not sterilize the CBDC introduction, banks respond by narrowing deposit spreads to attract inflows, with the result that a CBDC ramp-up to 5 percent of steady-state output expands rather than contracts bank credit to firms.

In depth

Q1. What is the equivalence of payment systems result and how does the collateral constraint change it?

Brunnermeier and Niepelt (2019) and Niepelt (2022) established that the central bank can neutralize the real effects of CBDC introduction by lending to banks at an appropriate rate to replace lost deposit funding, a result the present paper revisits by adding a collateral requirement on central bank lending — specifically, that banks must hold eligible government bonds up to a fraction θb of their central bank loan value. Under this constraint, Proposition 1 shows that equivalence survives: there exists a central bank lending rate that replicates the no-CBDC equilibrium allocation and price system. However, this lending rate is lower than Niepelt’s unconstrained rate by a factor increasing in the restrictiveness of the constraint (lower θb requires a lower lending rate), because when banks are collateral-constrained, cheaper terms are needed to induce them to borrow enough from the central bank to offset deposit outflows.

Q2. What is Corollary 1 and why does “full neutrality” fail?

Corollary 1 states that even when the central bank achieves allocation equivalence by setting the appropriate lending rate, banks must redirect portfolio holdings from firm loans to government bonds to meet the collateral requirement — crowding out bank credit to firms by an amount equal to the bond uptake, with the crowding-out diminishing as the collateral constraint becomes less restrictive (higher θb). This is the sense in which “full neutrality” fails under the collateral constraint: aggregate output and prices are unchanged, but the composition of credit changes — banks extend less to firms and hold more government bonds — and the government or household sector must absorb the gap in firm financing. In the limiting case where CBDC and deposits are equally valuable to households (λ = 1), the government alone compensates for the reduction in bank loans, effectively expanding its own intermediation role.

Q3. What does the dynamic extension show about bank disintermediation?

Simulating a gradual and near-permanent increase in CBDC to 5 percent of steady-state output without central bank sterilization, the paper finds that banks respond by narrowing their deposit interest spread to attract deposit inflows, such that total deposits do not fall and bank loans to firms expand rather than contract — the opposite of the disintermediation hypothesis. The mechanism relies on the assumption that banks have market power in their regional deposit markets (each bank is a monopsonist): in response to CBDC competition, the bank voluntarily reduces the rent it extracts on deposits (the spread between the risk-free rate and the deposit rate), attracting more deposit inflows. This deposit inflow, combined with central bank loan uptake, expands the bank’s balance sheet and increases credit extension to firms. The result stands in contrast to models with competitive deposit markets, where banks cannot respond to CBDC competition through deposit pricing.

Q4. What changes even if credit is not reduced?

Even when the dynamic model shows credit expansion rather than contraction, the paper establishes that CBDC introduction alters banks’ balance sheet composition and business model: banks shift toward holding more government bonds and away from firm loans, the government assumes a larger credit intermediation role, and the aggregate distribution of capital ownership changes — constituting the form of non-neutrality that survives even when total credit is unchanged. This is what Corollary 1 calls the failure of “full neutrality”: the real allocation equivalence holds at the aggregate level, but the sectoral distribution of who provides credit to firms shifts from the banking sector toward the public sector. The paper interprets this as a structural consequence of the collateral requirement on central bank lending that is absent in the frictionless equivalence benchmark.

Key concepts

equivalence of payment systems : the theoretical result (from Brunnermeier-Niepelt 2019 and Niepelt 2022) that the central bank can ensure the same equilibrium allocation whether or not CBDC exists, by adjusting its lending terms to banks; this paper revisits and extends the result to environments with a collateral constraint.

collateral constraint (θb) : the requirement in this model that banks hold eligible government bonds as a fraction of the central bank loans they take on; adding this friction to Niepelt’s framework preserves equivalence in allocation but requires a lower central bank lending rate and crowds out bank loans to firms.

disintermediation : the concern that CBDC adoption would cause households to shift en masse from bank deposits to CBDC, reducing bank funding and contracting bank credit; the paper finds this does not occur in either the equivalence analysis or the dynamic extension.

monopsony in deposits : the market structure assumption that each regional bank is the sole deposit provider in its region, giving it pricing power over deposit rates; this is what enables banks in the dynamic model to narrow the deposit spread in response to CBDC competition, generating deposit inflows rather than outflows.

full neutrality : a stronger invariance result requiring that not only the equilibrium allocation but also banks’ balance sheet composition and business model are unchanged by CBDC introduction; the paper shows this fails under the collateral constraint even when allocation equivalence holds.

Credit Easing versus Quantitative Easing: Evidence from Corporate and Government Bond Purchase Programs

Mon, 01 Jan 0001 00:00:00 +0000

Using security-level data on individual corporate bond prices and the Bank of England’s published purchase quantities across its gilt purchase programs (QE1: £200bn, QE2: £125bn, QE3: £50bn, QE4: £60bn) and Corporate Bond Purchase Scheme (CBPS: £10bn of investment-grade sterling corporate bonds), this paper estimates supply effects of QE and CE on UK corporate bond prices, credit spreads, and new issuance separately, exploiting cross-sectional variation in quantities purchased as identifying variation via an instrumental variables approach. In the case of QE alone, supply effects on corporate bond prices are significant at announcement and larger over the full stock-effect horizon, but pass-through to credit spreads is found to be limited to the default-free component of corporate yields under normal market conditions — an exception is QE1 during the financial crisis, when QE’s cross-asset supply effects also significantly lowered credit spreads in the longer run. CE via the CBPS is found to be more effective than QE in reducing credit spreads for higher-rated investment-grade bonds even under normal conditions, and is the only program that generates a statistically significant increase in sterling corporate bond issuance. The results are consistent with QE and CE working through partially distinct channels — QE primarily affecting the default-free component of corporate yields, CE additionally compressing the credit-spread component — and complementing each other for higher-rated bonds.

In depth

Q1. What is the empirical strategy and why use a security-level approach?

The paper uses a two-stage instrumental variables (IV) approach at the individual corporate bond level, with pre-program bond characteristics — maturity, yield-curve fitting errors, the BoE’s prior ownership share in the gilt bucket — serving as instruments for the expected distribution of purchases across bonds, allowing isolation of the supply channel from signaling and duration channels. The security-level approach offers three advantages over aggregate or event-study methods: it enables construction of “substitute buckets” (bonds whose maturity is close to the purchased bonds’) to estimate cross-asset supply effects; it permits direct comparison of the price elasticity with respect to gilt purchases (cross-asset effect) versus corporate bond purchases (within-asset effect); and it allows estimation of both the announcement-day effect and the stock effect — the cumulative price and spread change over the life of each program — which captures the longer-run portfolio-rebalancing contribution separately from the initial market reaction.

Q2. What are QE’s effects on corporate bond prices and credit spreads?

For QE alone (QE1–3), the instrumented gilt substitute purchases have positive and statistically significant effects on corporate bond prices at announcement across all three programs — in the case of QE1, the average 30 basis-point decline in corporate yields on the announcement day is attributed in full to QE supply effects in the paper’s regression. The stock effect — estimated over the full life of each program — is significantly larger than the announcement-day effect, consistent with gradual portfolio rebalancing as predicted by Greenwood, Hanson, and Liao (2018). However, except for QE1, the supply effects do not carry through to credit spreads in either the short run or the longer run, which the paper interprets as consistent with QE working primarily through the default-free component of the corporate yield: corporate yields fell in line with gilt yields, but spreads over gilts were unchanged.

Q3. When does QE affect credit spreads?

QE1’s cross-asset supply effects significantly lowered credit spreads in the longer run, even though QE2 and QE3 do not generate significant credit spread compression in either the short or long run, suggesting that the supply channel interacts with the liquidity channel specifically under conditions of financial market distress. The paper interprets the QE1 exception as reflecting the severe disruption during the 2008–09 financial crisis: when capital mobility across markets is constrained and liquidity premia are elevated, central bank purchases of safe assets may also improve trading conditions in indirectly targeted, less liquid markets such as the corporate bond market, reducing the liquidity component of corporate spreads. This interaction does not appear to be operative in the more normal market conditions of QE2 and QE3.

Q4. How does CE compare to QE in reducing credit spreads and stimulating issuance?

CE via the CBPS is found to be more effective than QE in reducing credit spreads for higher-rated investment-grade bonds even under normal financial market conditions, and a corporate bond’s price sensitivity to its own CBPS purchases is substantially higher than its price sensitivity to gilt substitute purchases; CE is also the only program with a statistically significant positive effect on new sterling corporate bond issuance. Across QE1–3, there is no statistically significant impact of gilt purchases on sterling corporate issuance, while CBPS purchases have positive and statistically significant effects on new sterling corporate bond issuance. The paper characterizes CE and QE as complementary for higher-rated bonds: CE’s credit-spread reduction layers on top of QE’s default-free component effect, making the total stock effect larger than either program alone.

Q5. What happens for lower-rated investment-grade bonds?

For lower-rated investment-grade bonds, the evidence for both cross-asset QE supply effects and within-asset CE supply effects is weaker, and the paper suggests that CE’s stimulation of new bond issuance may have counterbalanced its positive price effects for these bonds through the dilutive effect of new supply. The mechanism is that CE’s reduction in the cost of corporate bond issuance for lower-rated firms induced enough new bond issuance to partially offset the price increase from CBPS purchases, consistent with the issuance channel being most active for the market segment where CBPS created the largest pricing improvement. This dilution effect implies that the net price benefit of CE for lower-rated bonds is smaller than the gross supply-effect estimate.

Key concepts

stock effect : the cumulative effect of the total quantity of bonds purchased under a program on bond prices and spreads, estimated over the full life of the program; in this paper the stock effect is significantly larger than the announcement-day effect, consistent with gradual portfolio rebalancing.

cross-asset supply effect : the pass-through of government bond (gilt) purchase supply shocks to the prices of corporate bonds — an asset class not directly targeted by QE; the paper provides the first estimates of this cross-market supply channel at the security level.

credit spread : the difference between the yield on a corporate bond and the yield on a risk-free government bond of the same maturity; the paper finds QE pass-through is generally limited to the default-free component of corporate yields rather than the credit spread.

default-free component : the part of a corporate bond’s yield attributable to the risk-free interest rate rather than credit risk; the paper finds that QE supply shocks affect this component but generally leave the credit spread unchanged in normal market conditions.

within-asset substitution effect : the price effect of CE purchases on the bonds directly purchased and their corporate bond substitutes, as distinct from cross-asset effects; the paper finds this effect is substantially larger in magnitude than the cross-asset QE effect on corporate bonds.

issuance channel : the mechanism by which lower corporate borrowing costs induced by CE stimulate new corporate bond issuance; the paper finds this channel operates under CE (CBPS) but not under QE (gilt purchases).

Inflation Expectations and the Slope of the Phillips Curve: Evidence from Firm Surveys

Mon, 01 Jan 0001 00:00:00 +0000

Do the inflation expectations of firms — rather than households or financial markets — shift the slope of the Phillips curve? Using a new panel of firm-level surveys matched to price-setting behavior, the authors find that firms with higher expected inflation adjust prices more aggressively in response to demand shocks, steepening the local Phillips curve slope. The effect is concentrated among firms that review prices frequently, suggesting a mechanism through the frequency of price adjustment rather than through the level of markups.

In depth

Q1. What is the main empirical finding on expectations and the Phillips curve slope?

Firms with higher measured inflation expectations exhibit a steeper relationship between demand conditions and price adjustment — the estimated Phillips curve slope is roughly 40% larger in the high-expectations tercile than in the low-expectations tercile, conditional on the authors’ controls and sample. The authors interpret this as evidence that expectations are not merely a level shift in inflation but alter the sensitivity of prices to real activity, consistent with forward-looking pricing theories.

Q2. What is the mechanism, and how do the authors identify it?

The authors argue that expectations work through the frequency of price review: firms expecting higher inflation are more likely to be in an active review window, and so respond more to a given demand shock within that window. Identification relies on cross-firm variation in survey-measured expectations within narrow industry-time cells, so that aggregate demand shocks are held approximately fixed. The authors acknowledge this strategy absorbs industry-specific inflation trends and may understate the full expectational effect.

Q3. What does this imply for monetary policy?

If the Phillips curve slope varies with expectations, then a credible disinflation — by lowering expected inflation — flattens the curve and makes the output cost of reducing inflation larger, not smaller. The authors present this as a potential mechanism behind the observed flattening of the curve in low-inflation regimes, though they stop short of a structural welfare calculation.

Key concepts

Phillips curve slope: The coefficient linking excess demand (or unemployment gap) to inflation in the short-run Phillips curve — steeper means a given demand shortfall has a larger disinflationary effect.
price review frequency: How often a firm actively reconsiders its prices; firms that review more often are more likely to adjust in response to new information within any given period.
firm-level survey expectations: Inflation expectations measured directly from firms (rather than households or markets), which may better capture the beliefs that drive actual price-setting decisions.

Liquidity Traps, Prudential Policies, and International Spillovers

Mon, 01 Jan 0001 00:00:00 +0000

The paper develops a tractable open-economy New Keynesian model with nominal rigidities and an occasionally binding zero lower bound (ZLB) to study how monetary policy and macroprudential policy (modeled as a tax on capital flows) jointly transmit to output, capital flows, and the exchange rate, and what this implies for international spillovers and global welfare. An analytical decomposition identifies three transmission channels — intertemporal substitution, expenditure switching, and aggregate income — and the calibration finds that capital controls operate almost entirely through intertemporal substitution (about 95%), whereas expenditure switching accounts for roughly a quarter to a third of the effect of monetary policy. On the normative side, the authors show that, absent capital controls, monetary policy faces a tradeoff between stabilizing output today and curbing capital flows to lower the likelihood of a future liquidity trap, but that ’leaning against the wind’ (pre-emptively raising rates) is not necessarily optimal and can be counterproductive when tradables and non-tradables are highly substitutable. Quantitatively, adding capital controls lowers the average unemployment rate conditional on a liquidity trap from about 6% to about 1.5% and cuts the unconditional welfare cost of liquidity traps from about 0.4% to about 0.1% of permanent consumption, with an average ex-ante tax on inflows of about 0.2% and an average ex-post tax on outflows of about -0.05%. Finally, contrary to ‘currency war’ concerns, the authors argue that capital controls are not beggar-thy-neighbor: a country can use them to insulate itself from adverse foreign-policy spillovers (which operate through the world real interest rate), and coordination is beneficial only during a liquidity trap and works by stimulating rather than restricting flows. All results hold within their small-open-economy model under its calibration.

In depth

Q1. What is the model, and which policies does it study?

The paper studies an infinite-horizon small open economy with nominal rigidities and an occasionally binding zero lower bound on the nominal interest rate, in which the government has two instruments — the nominal interest rate (monetary policy) and a tax on capital flows (macroprudential policy). The economy has a tradable final good and a non-tradable good with sticky prices, and features aggregate demand externalities. The authors use this setting to ask three questions: how interrelated are the transmission channels of the two policies; how should monetary policy be used jointly with macroprudential policy; and what happens to global welfare when many countries adopt prudential policies simultaneously.

Q2. What are the three transmission channels, and how much does each matter?

An analytical decomposition (extending Kaplan, Moll and Violante 2018 and Auclert 2019 to an open economy) identifies three channels — intertemporal substitution, expenditure switching, and aggregate income — and the calibration shows monetary policy and capital controls operate through very different channels. The intertemporal substitution channel accounts for about 95% of the effect of capital controls, while expenditure switching (operating through exchange-rate depreciation that shifts demand toward non-tradables) accounts for a substantial share of the effect of monetary policy — the paper states ‘about one-third’ in its introduction and ‘about one-quarter’ in its conclusion. The expenditure-switching channel and the role of the exchange rate are what distinguish the open-economy decomposition from its closed-economy antecedents.

Q3. Do open capital markets amplify or dampen monetary policy?

Capital flows may either amplify or attenuate the output effects of monetary policy, depending on the relative sizes of the elasticity of substitution over time and the elasticity across sectors. If the intertemporal elasticity exceeds the intratemporal one, an open capital account amplifies monetary policy (a monetary expansion raises total consumption more than output, so households borrow from abroad); the result reverses when the intratemporal elasticity is larger, in which case a closed capital account produces the larger output expansion.

Q4. Is ’leaning against the wind’ the optimal prudential use of monetary policy?

Contrary to a widespread policy view, leaning against the wind is not necessarily optimal: when the elasticity of substitution across sectors is higher than across time, raising the interest rate ahead of a liquidity trap can be counterproductive. In that case a rate hike generates a large negative expenditure-switching effect and a sharp income drop while only modestly reducing consumption, so in general equilibrium it leads to capital inflows and more external debt — exacerbating the aggregate demand externality and making a future contraction more likely. The implication is that a prudential monetary policy may require lowering, not raising, the interest rate ahead of a liquidity trap.

Q5. How should monetary and macroprudential policy be combined, and how pre-emptively?

When capital controls are available, the central bank uses monetary policy to stabilize output and uses the capital-flow tax to manage flows, with the macroprudential tax on debt positive only if the ZLB is likely to bind next period; monetary policy, by contrast, must be used prudentially even when the ZLB binds only in some distant future. Because monetary policy is a blunter instrument, it has to be used more pre-emptively than capital controls. The authors also show the central bank may restrict outflows during a liquidity trap when that trap is either temporary or very severe.

Q6. What are the quantitative welfare and unemployment gains from capital controls?

Adding capital controls substantially improves macroeconomic stabilization: average unemployment conditional on a liquidity trap falls from about 6% to about 1.5%, and the unconditional welfare cost of liquidity traps falls from about 0.4% to about 0.1% of permanent consumption — more than a fourfold reduction. The average ex-ante prudential tax on inflows is about 0.2% and the average ex-post tax on outflows is about -0.05%. The authors also note that, with capital controls, liquidity traps are less frequent and less severe but — perhaps surprisingly — tend to last longer.

Q7. Are capital controls beggar-thy-neighbor, and how do international spillovers work?

The authors argue that, contrary to emerging policy concerns, capital controls are not beggar-thy-neighbor and can enhance global macroeconomic stability; international spillovers operate through the world real interest rate, and a country can use capital controls to insulate itself from adverse foreign policies. In their multi-country extension, a country can remain insulated from negative spillovers of a change in the foreign monetary stance through capital controls, which can help prevent the outbreak of a currency war.

Q8. When is international policy coordination desirable?

The authors provide conditions under which a regime of uncoordinated capital controls can dominate laissez-faire, and they find that coordination is desirable only during a liquidity trap — where, notably, it calls for stimulating capital flows rather than preventing them. This stands against the view that uncoordinated capital-control policies necessarily produce a global paradox of thrift.

Q9. How do these results differ from prior open-economy liquidity-trap models?

The paper’s more benign view of spillovers contrasts with contributions such as Caballero, Farhi and Gourinchas (2021), Eggertsson et al. (2016), and Fornaro and Romei (2019), and the authors trace the difference to two features of their model: positive liquidity and the presence of ex-post capital controls. Because goods subject to nominal rigidities are consumed only domestically, foreign policies that favor savings (lowering the world interest rate) raise demand for domestic goods through asset markets and can be stabilizing at the ZLB; and ex-post controls let the central bank actively manage flows during a trap to offset adverse spillovers.

Key concepts

aggregate demand externality : the externality (as in Schmitt-Grohe and Uribe 2016 and Farhi and Werning 2016) by which an individual agent’s borrowing raises external debt and, given nominal rigidities and the ZLB, makes the economy more vulnerable to a future demand-driven contraction; it is the market failure that prudential policy targets in this model.

expenditure switching channel : the open-economy transmission channel through which an exchange-rate depreciation makes non-tradables relatively cheaper, shifting demand toward domestically produced goods; the paper finds it accounts for a substantial share (roughly a quarter to a third) of monetary policy’s effect.

intertemporal substitution channel : the channel through which a change in the intertemporal price shifts consumption between present and future; it accounts for about 95% of the effect of capital controls in the calibration.

liquidity trap / occasionally binding ZLB : a state in which the zero lower bound on the nominal interest rate binds, so conventional monetary policy cannot stabilize output; the risk of entering such a state in the future is what makes pre-emptive prudential policy valuable here.

capital controls (prudential tax on flows) : the macroprudential instrument in the model — a tax on capital inflows (ex ante) or outflows (ex post) — used to manage the level and timing of capital flows and to insulate the economy from foreign spillovers.

beggar-thy-neighbor : a policy that improves one country’s outcomes at others’ expense; the paper argues capital controls are, contrary to common concern, not beggar-thy-neighbor in its setting and can raise global stability.

Long-Term Debt and Short-Term Rates: Fixed-Rate Mortgages and Monetary Transmission

Mon, 01 Jan 0001 00:00:00 +0000

This paper uses instrumental-variable local projections (IV-LP) on an unbalanced panel of up to 35 countries over approximately two decades to establish two interconnected findings about fixed-rate mortgages (FRMs) and monetary policy. First, monetary policy affects mortgage type selection: a 100 basis point tightening increases the share of adjustable-rate mortgages (ARMs) in new originations by approximately 10 percentage points after one year, while easing generates the reverse shift toward FRMs. The mechanism is budget constraints: ARM rates move nearly one-for-one with policy rates while FRM rates respond by only about 0.5 percentage points per 100 bps, so after tightening the FRM-ARM spread narrows but both products become more expensive — households facing tighter budgets select the cheaper ARM option, irrespective of spread comparisons. Second, the prevailing stock composition of outstanding ARMs determines how strongly monetary policy transmits to real activity: for every additional percentage point of household debt held as ARMs, the same 100 bps policy change produces approximately 0.05 percentage points more impact on real private consumption at six quarters ahead, controlling for the level of household debt-to-GDP. A back-of-the-envelope calculation implies that the same 100 bps change induces a consumption response approximately 5 percentage points stronger in an economy with 100 percent ARMs versus one with only FRMs. These two findings jointly imply that FRMs create both path-dependency (past easing cycles populate the stock with FRMs, weakening future transmission) and state-dependency (current FRM prevalence determines how much a given rate change moves consumption and GDP) in monetary policy.

In depth

The paper draws on two data sources: flow data covering new mortgage originations in 27 countries and stock data on the outstanding mortgage composition in 35 countries, spanning approximately two decades of quarterly observations. A mortgage is classified as fixed-rate (FRM) if the contractual interest rate is fixed for 12 months or more from origination; below that threshold it is classified as adjustable-rate (ARM). This definition aligns with ECB and Eurostat conventions and is consistent across the panel, though note that some “fixed-rate” mortgages in the sample include hybrid products with initial fixed periods that eventually reprice. The FRM share in new flows (used in the path-dependency analysis, equation 2) captures how the composition of new originations responds to monetary policy. The FRM share in outstanding stock — expressed as a proportion of household debt-to-GDP (ARMdebt) — is the state variable in the state-dependency analysis (equation 3). Countries’ time-series for both measures display the expected patterns: in the long period of ultra-low rates following the GFC, the FRM share in stock increased substantially across the sample.

Q2. How are monetary policy shocks identified and why are information effects excluded?

Monetary policy shocks are constructed from Bloomberg high-frequency financial market surprises around central bank announcement windows, then orthogonalized with respect to the central bank’s private information component using the Bauer and Swanson (2023) procedure. The Bauer-Swanson orthogonalization removes the portion of policy surprises that is correlated with the central bank’s assessment of the economic outlook — the “Fed information effect” identified by Nakamura and Steinsson (2018). Without this purification, a policy surprise that partly reflects the central bank’s private negative news about growth would confound the identification: the estimated consumption response would reflect both the direct policy-rate effect and the information revelation, making it impossible to isolate the transmission mechanism through mortgage types. The first-stage Kleibergen-Paap Wald F statistics are 34 or above for the path-dependency regression (equation 2) and 12.9 or above for the state-dependency interaction regression (equation 3), satisfying standard relevance thresholds.

Q3. What is the path-dependency mechanism and what does Figure 3 show?

Figure 3 plots impulse responses of FRM rates, ARM rates, 10-year and 1-year government bond yields, the FRM-ARM spread, and the ARM share in new flows to a one percentage point policy rate change instrumented with the Bauer-Swanson-cleaned shocks. FRM rates respond by approximately 0.5 percentage points per 100 bps of policy change, similar to the response of 10-year government bond yields, with full reversion after about 4–6 quarters. ARM rates respond approximately one-for-one, similar to 1-year yields, also reverting after 4–6 quarters. Since ARM rates respond more than FRM rates, the FRM-ARM spread narrows by about 0.5 percentage points after a 100 bps tightening — making ARMs relatively cheaper compared to FRMs. Despite this narrowing of the spread (which should theoretically discourage ARM selection), the paper finds that ARM share in new flows increases significantly: a 100 bps tightening raises the ARM share by approximately 10 percentage points after one year, a large effect corresponding to about two thirds of a within-country standard deviation. The paper attributes this to budget constraints: even though the FRM-ARM spread narrows, both products become more expensive in absolute terms, and cash-constrained borrowers choose the cheaper option (ARM) to minimize initial monthly payments, rather than comparing relative spreads. The converse holds during loosening: as borrowing costs decline and budget constraints ease, borrowers show a revealed preference for the interest rate risk protection of FRMs, consistent with a general preference for payment certainty when affordability is not binding.

Q4. How does the mortgage stock composition affect monetary policy transmission (state-dependency)?

The state-dependency analysis (equation 3, Figure 4) regresses macroeconomic outcomes on the interaction of a policy rate change and the ex-ante ARM debt share (ARMs as a proportion of household debt-to-GDP), using country and quarter fixed effects with Driscoll-Kraay standard errors and IV identification. The left column of Figure 4 shows that the marginal effect of a 100 bps policy change on real private consumption increases by approximately 0.05 percentage points for each additional percentage point of ARMs in outstanding stock, a differential that becomes noticeable after about six quarters. The differential response for durables consumption appears earlier (around two quarters), while the real GDP differential is roughly half the consumption differential (about 0.02 percent per percentage point of ARM debt). The right column of Figure 4 separates the state variable into the pure ARM share and household debt-to-GDP by including both interaction terms in a horse-race specification. The paper finds that the ARM share (not the debt level) drives the transmission differences for real GDP and both measures of consumption, consistent with a cash-flow channel interpretation: it is interest rate resets on existing ARM contracts that affect disposable income flows and spending, not the debt level per se. Household debt-to-GDP is relevant for durables consumption, potentially reflecting wealth and collateral effects on credit-intensive spending categories. The 100 percent ARM versus 0 percent ARM back-of-the-envelope calculation implies a 5 percentage point consumption difference per 100 bps, corresponding exactly to one standard deviation in cumulative real private consumption changes at 6 quarters in this sample.

Q5. Why is the shift toward ARMs after tightening paradoxical given the standard relative pricing model, and what channels can explain it?

The standard framework predicts that borrowers choose FRMs when the FRM-ARM spread is low (ARMs relatively less attractive) and ARMs when the spread is high; a tightening that narrows the spread should therefore shift borrowers toward FRMs, not ARMs. The paper finds the opposite and offers two channels. First, a budget constraint channel: after tightening, both FRM and ARM rates rise in absolute terms, but ARMs remain cheaper at origination because they carry lower initial payments; liquidity-constrained borrowers facing higher total borrowing costs choose the cheaper option regardless of the spread direction, consistent with evidence in Andersen et al. (2023) that ARM adoption is more prevalent among liquidity-constrained borrowers. Second, a cost-minimization channel with short-run focus: some borrowers choose the product that minimizes current-period mortgage payments, not lifetime payments; after tightening, ARMs minimize the monthly payment even though they expose borrowers to future rate risk. The paper notes that the converse — FRM adoption after loosening despite rising FRM-ARM spreads — cannot be explained by short-run cost minimization and suggests a preference for rate certainty when affordability is non-binding.

Q6. Is the state-dependency effect asymmetric between tightening and loosening cycles?

The paper tests an asymmetric specification and finds that FRMs are a greater impairment to monetary transmission during tightening relative to loosening cycles, especially when free prepayment options are available. During tightening, a high FRM share means few borrowers face rate resets on their existing debt, so the cash-flow channel is weak; simultaneously, prepayment refinancing into new mortgages is unattractive (locking in a higher rate) so the existing FRM stock remains insulated. During loosening, a high FRM share means borrowers can refinance into lower FRM rates or into ARMs at lower cost, partially restoring the transmission channel. This asymmetry is consistent with findings in Berger, Milbradt, Tourre, and Vavra (2021) on mortgage prepayment and path-dependent monetary policy effects in the US, and suggests that the FRM-induced weakening of transmission is particularly binding precisely during contractionary cycles when central banks most need the transmission mechanism to be operative.

Q7. What are the implications for central bank transmission assessment and policy?

The two findings together imply that monetary policy transmission capacity is endogenous to the history of the policy cycle. A prolonged loosening phase (such as the post-GFC decade of ultra-low rates) shifts new originations toward FRMs, which accumulate in the outstanding stock; the resulting high FRM share means that subsequent tightening operates through a weakened transmission channel. The central bank’s policy instrument affects the transmission mechanism’s own strength. This endogeneity has at least two practical implications. First, central banks that have conditioned borrowers into expecting prolonged low rates may face amplified instrument-calibration uncertainty: the same 100 bps tightening has systematically weaker real effects in economies where prior easing locked in high FRM shares, requiring larger policy moves to achieve the same macroeconomic stabilization. Second, cross-country heterogeneity in the FRM-ARM mix — itself partly endogenous to the history of monetary policy — explains a significant portion of the observed heterogeneity in monetary policy transmission strength across countries, complementing structural explanations based on financial market depth, indebtedness levels, and household balance sheet composition.

Key concepts

fixed-rate mortgage (FRM): a mortgage with a contractual interest rate fixed for 12 months or more; holders are contractually insulated from subsequent policy rate changes, reducing the pass-through of monetary policy to household debt service costs through the cash-flow channel; in the paper’s framework, FRM prevalence is both a consequence of past policy (path-dependency) and a determinant of current transmission strength (state-dependency).

adjustable-rate mortgage (ARM): a mortgage where the interest rate resets with market rates (at intervals shorter than 12 months for the paper’s classification); holders feel policy rate changes immediately in their monthly payments, amplifying the cash-flow channel; the paper finds ARM share in new flows rises after monetary tightening due to budget constraint effects.

path-dependency: the property that the current effectiveness of monetary policy depends on the accumulated history of prior policy rate changes, through their effect on the outstanding mortgage stock composition; specifically, prolonged easing cycles generate high FRM shares that reduce future transmission potency.

state-dependency: the variation in monetary policy transmission strength with the prevailing share of ARMs in outstanding mortgage debt; the same policy rate change produces a consumption response approximately 5 percentage points larger in a 100 percent ARM economy than in a 100 percent FRM economy (per 100 bps), controlling for debt-to-GDP.

cash-flow channel of monetary policy: the mechanism by which changes in policy rates affect households’ disposable income through resets in the interest payments on their existing variable-rate debt; the dominant channel in the paper’s state-dependency results — ARM share (not debt level) drives transmission differences for consumption and GDP, consistent with income flow effects on spending propensity.

IV local projections (IV-LP): the estimation framework combining Jordà (2005) local projections — a flexible, model-free method for estimating impulse responses at multiple horizons — with instrumental variable identification using Bauer-Swanson-cleaned monetary policy shocks; used for both the path-dependency regressions (equation 2, ARM flow response) and the state-dependency regressions (equation 3, interaction with ARM stock).

Bauer-Swanson (2023) information effect correction: the procedure for removing the component of high-frequency monetary policy surprises that is correlated with the central bank’s private information about economic conditions; applied here to prevent the estimated transmission effects from conflating pure rate changes with information revelation about the macroeconomic outlook.

Money Markets, Collateral and Monetary Policy

Mon, 01 Jan 0001 00:00:00 +0000

The paper studies the euro area interbank money markets during the global financial crisis (2007–09) and sovereign debt crisis (2010–15), documenting four empirical regularities and building a quantitative general equilibrium model to evaluate their macroeconomic impact and the role of central bank policy. The central finding is that the ECB’s collateral policy — lending to banks at haircuts more favorable than private markets — prevented output and investment from falling roughly twice as much as they would have under a passive constant-balance-sheet policy.

Four empirical observations (Section 2, 2003–2015):

The share of unsecured interbank borrowing declined throughout the euro area; banks substituted toward secured (repo) transactions — the secured share rose from roughly 42% to 90% of turnover
Private market haircuts on Southern sovereign bonds (IT, ES, PT) rose dramatically during the sovereign debt crisis, peaking at 25.16% in 2012–2013 (vs 3% in 2010) — while the ECB kept its haircuts nearly unchanged, creating a “haircut gap”
Bank borrowing from the ECB increased eight-fold in Southern regions as the haircut gap widened
Household deposits at banks remained stable throughout

Model architecture (Section 3): Two regions (North: DE/FR; South: IT/ES/PT) share a common central bank. Each period is divided into a morning and afternoon. In the morning, banks choose portfolios subject to a Gertler-Karadi (2011) leverage constraint (fraction λ of assets can be diverted by the manager) and a central bank collateral constraint (CB loans require bonds pledged at CB haircut η). In the afternoon, banks face idiosyncratic liquidity shocks ω~iid F(ω) on deposits. Connected banks (fraction ξ) can borrow unsecured in the afternoon interbank market. Unconnected banks (fraction 1−ξ) must cover their maximum possible payment outflow ωmaxD by holding reserves or pledging bonds as collateral in the private secured market (at haircut 1−η̃^γ). Five inequality constraints — the morning leverage constraint, a CB collateral constraint, and three short-sale constraints (bonds, deposits, capital) — can each switch between binding and slack; the model requires a non-linear solution (Dynare Levenberg-Marquardt mixed complementarity solver).

Calibration (Table 2, quarterly frequency):

Standard: capital share θ = 0.33, depreciation δ = 0.02, discount factor β = 0.994, Frisch inverse ε = 0.40, government spending g = 0.566
Bond maturity 1/κ = 5.952 years; dividend fraction φ = 0.025; leverage constraint λ = 0.701
Pre-crisis interbank structure: ξ = 0.42 (42% connected), haircuts η̃ = η = 0.97 (3%)
Maximum liquidity shock ωmax = 0.10; foreign sector bond demand elasticity ρ = 1.757
6 targeted moments (Table 3, exact fit): Govt/GDP = 0.20; bank leverage = 6; annual bond spread = 0.2%; bank share of bond holdings = 23%; foreign sector share = 64%; annual inflation = 2%
Non-targeted moments broadly matched: central bank bond holdings/GDP, government debt/GDP

Two shock processes (Section 5.2):

ξ shock (permanent, onset t=1 corresponding to 2009 Q1): connected share log(ξt) transitions from ξ−1 = 0.42 to ξ∞ = 0.10 with AR(1) persistence ρξ = 0.95
η̃S shock (temporary-persistent, onset t=13 corresponding to 2012 Q1): Southern private haircut recovery factor follows AR(2) with ρη1 = 1.65, ρη2 = −0.70 and an initial impulse ε13 = −0.11; model haircuts peak at 25%, matching the data peak of 25.16%

Comparative statics (Section 6.1):

ξ shock alone: As the share of unconnected banks rises from 0.58 to 0.89 (pre- to post-2008 average), the capital stock falls 10% on aggregate and output declines 1.8% in the new steady state; no CB intervention occurs because CB and private haircuts are equal — banks have no incentive to use CB funding
η̃S shock alone (without prior ξ shift): Output falls only 0.15% even as private haircuts reach 40% in comparative statics; the muted effect arises because collateral markets are segmented in the baseline — Northern banks hold only Northern bonds (unaffected haircuts), fully counteracting Southern banks’ investment decline

Dynamic analysis (Section 6.2): In the full simulation combining both shocks:

The ξ shock causes an immediate output and investment overshoot below the new steady-state: anticipating future crowding-out of capital (unconnected banks hold bonds/reserves rather than investing), bank net worth falls immediately and leverage declines, pushing output below the eventual new steady state before gradual recovery
The η̃S shock (at t=13) additionally tightens collateral constraints for unconnected banks in the South; they endogenously switch to holding money as collateral, which integrates money markets across regions and creates a pecuniary externality on Northern banks (all banks now face the same higher collateral price for money) — a sharp contrast to the segmented-market comparative statics where Northern banks were unaffected
CB take-up peaks at 2.5% of total bank assets under CO policy, closely matching the data

CO policy vs CB policy counterfactual (Section 6.2.3, Figure 10):

Under the CO policy (benchmark: ECB keeps CB haircut at 3% while private market haircuts rise to 25%), unconnected banks in the South substitute expensive deposit funding for cheaper CB funding, reducing the collateral premium for money and directly benefiting Northern unconnected banks (pecuniary externality channel)
Under the CB policy (counterfactual: constant balance sheet, CB haircut = 100%), this substitution is impossible; collateral scarcity is unmitigated; the Northern banks’ spillover is larger
Main result: output and investment fall around twice as much on impact under the CB policy; the CB policy also produces a stronger post-crisis rebound as higher initial capital returns raise bank leverage
Conclusion: the ECB’s collateralized lending operations were crucial in containing the crisis, working through a haircut-gap channel that reduced the premium on collateral and attenuated the pecuniary externality between North and South

Scope conditions: Sovereign default risk on government bonds is treated as exogenous (the model does not endogenize default); the paper notes this would require a separate analysis linking haircuts to default probabilities. Prices are set one period in advance (not a full NK model), which disciplines inflation dynamics but is not a full monetary policy analysis. The model abstracts from the ECB’s Securities Markets Programme (sterilized asset purchases, not in scope). The two-region framework aggregates heterogeneous countries into North and South. Results depend on the perfect-foresight assumption; uncertainty about the path of shocks would introduce additional precautionary effects.

In depth

Q1. Why did the decline in unsecured interbank lending harm the real economy?

Unsecured interbank borrowing allows banks to pool idiosyncratic liquidity shocks without holding any liquid buffer; when unconnected banks (unable to borrow unsecured) must instead cover their maximum possible afternoon deposit outflow ωmaxD by holding bonds or reserves, they divert balance sheet capacity away from capital investment, crowding it out. As the share of unconnected banks rises from 42% to 90%, this crowding-out effect operates through two channels: (i) direct diversion of assets from productive capital to unproductive liquidity buffers; (ii) higher demand for collateral raises the collateral premium on bonds, increasing the effective cost of deposit funding and inducing all banks — even connected ones — to downsize their balance sheets through the leverage constraint.

Q2. Why was the steady-state impact of Southern haircuts muted while the dynamic impact was large?

In the baseline steady-state, collateral markets are segmented: Northern unconnected banks hold only Northern bonds (unaffected by Southern haircuts) and Southern unconnected banks hold only Southern bonds; in comparative statics, Northern banks absorb the capital freed by Southern banks’ disinvestment and the aggregate effect is small (−0.15% output for haircuts rising to 40%). In the dynamic model, however, the prior ξ shock has already pushed Northern unconnected banks to hold money as collateral (since high bond demand from all unconnected banks raises bond prices until money becomes the cheaper alternative); when Southern haircuts then spike, Southern banks also switch to money as collateral — and since money is a non-regional collateral, its price spike affects all unconnected banks simultaneously, integrating the previously segmented collateral markets and transmitting the Southern shock to the North.

Q3. How does the CO policy’s “haircut gap” channel work?

Under CO policy, the ECB maintains its haircut at 3% while private markets charge 25%; for each unit of collateral, a bank can access (1−0.03)=0.97 units from the ECB but only (1−0.25)=0.75 units from the private repo market — a 22-percentage-point haircut gap that makes ECB funding more efficient per unit of collateral pledged. When private haircuts rise, unconnected Southern banks face a collateral scarcity that makes deposit funding more expensive (higher afternoon constraint tightening); under CO policy, they optimally substitute toward CB funding, reducing their dependence on expensive deposits and mitigating the collateral premium spike. This directly benefits Northern unconnected banks because the reduced collateral premium for money (driven by Southern banks switching out of money as collateral) relaxes their own afternoon constraints without any direct exposure to Southern bonds.

Q4. Why does the CB policy produce a stronger post-crisis rebound?

The CB policy’s larger initial output and investment decline implies a larger undershoot below the new (post-ξ) steady state; during the recovery phase, banks face elevated returns on capital investment because capital is below its steady-state level; these higher returns raise bank net worth and allow more aggressive leverage, producing a steeper rebound than under the CO policy where the downturn was mitigated. This “larger crisis, faster recovery” tradeoff means the CB policy does not necessarily produce lower total welfare than the CO policy over the full cycle — the welfare comparison requires integrating the entire path, not just comparing the initial impact.

Q5. What makes the model require a non-linear solution?

The model features five inequality constraints that each can switch between binding and slack as parameters change: the morning leverage constraint, a collateral constraint on CB loans, and three short-sale constraints (kt,i ≥ 0, Bt,i ≥ 0, Dt,i ≥ 0). Standard linearized DSGE methods assume constraints are either always binding or always slack; here, for instance, connected banks begin holding positive money balances only when the share of unconnected banks rises past a threshold (0.61 in comparative statics), at which point the collateral premium rises enough to equalize returns on bonds and money — a kink that requires tracking which constraints are active. The Dynare Levenberg-Marquardt mixed complementarity solver handles these transitions, with T=400 periods imposed to ensure convergence to steady state.

Q6. What is the role of the leverage constraint in transmitting interbank frictions to the real economy?

The leverage constraint (Gertler-Karadi 2011) limits each bank’s total assets to Vt,i/λ; when money market frictions reduce the bank’s value Vt,i — either directly (collateral premia reduce bond prices and thus net worth) or through lower expected future net worth — the binding leverage constraint forces a proportional reduction in all assets including capital. This is the channel through which a purely financial friction in interbank markets (collateral scarcity) translates into a real investment decline: the leverage constraint links bank net worth to lending capacity, and interbank frictions that depress net worth also shrink investment. The result that “output and investment fall around twice as much” under CB policy is quantitatively driven by this chain: CB policy mitigates the collateral premium, preserving net worth and thus the lending capacity of banks.

Q7. Why do household deposits remain stable even as interbank markets are disrupted?

The model’s equilibrium has banks absorbing shocks through their balance sheet structure (switching between deposit funding, CB funding, bonds, and money) rather than through deposit supply; household deposits Dt,i are determined by households’ intertemporal optimization and the deposit rate, both of which are relatively insulated from the interbank friction. The friction operates within the banking system (between banks, or between banks and the CB), not in the retail deposit market; the afternoon liquidity shocks are interbank in nature (payment flows between banks) and are settled without household involvement. This matches Observation 4 from the data (stable household deposits) and is consistent with the mechanism: banks’ portfolio recomposition toward CB funding or bonds is a liability-side substitution that leaves retail deposits intact.

Key concepts

haircut gap channel : the mechanism through which the ECB’s policy of maintaining favorable haircuts (3%) on collateral while private market haircuts spike (to 25%) provides effective relief from collateral scarcity; banks can access more liquidity per unit of pledged collateral from the ECB than from the private repo market, inducing substitution from deposit funding to CB funding when the private haircut gap widens.

connected vs. unconnected banks : the model’s key bank heterogeneity; connected banks (fraction ξ) can borrow unsecured in the afternoon interbank market and therefore need no liquidity buffer; unconnected banks must cover their maximum afternoon payment outflow ωmaxD with reserves or pledged bond collateral, crowding out capital investment — the shift from ξ = 0.42 to ξ = 0.10 is the model’s representation of the euro area secured-market shift.

pecuniary externality (North-South spillover) : the channel through which a rise in Southern bond haircuts affects Northern banks even though Northern bonds are not repriced; when Southern banks switch to holding money as collateral, the demand for money rises, pushing up its collateral price; Northern unconnected banks (already holding money after the ξ shock) pay the higher price, tightening their afternoon constraint and reducing their capital investment indirectly.

collateral premium : the shadow price on bonds arising from their dual role as investment assets (in the morning) and collateral for afternoon liquidity (in the private repo or CB markets); when the afternoon constraint is binding, the collateral premium is positive — bonds are valued above their pure investment return — and determines how much of a bank’s balance sheet is diverted from capital to liquidity buffers.

CO policy vs CB policy : the paper’s two scenarios for the ECB’s response; CO policy (benchmark) maintains collateralized lending at a fixed (favorable) CB haircut, allowing CB balance sheet expansion as private haircuts rise; CB policy (counterfactual) keeps the balance sheet constant (CB haircut = 100%, no CB lending), forcing all liquidity needs to be met through private markets — the comparison isolates the macroeconomic value of the ECB’s lender-of-last-resort function.

Mussa Puzzle Redux

Mon, 01 Jan 0001 00:00:00 +0000

The Mussa (1986) puzzle is the empirical observation of a sharp, simultaneous increase in the volatility of both nominal and real exchange rates following the end of the Bretton Woods fixed exchange rate system in 1973 — a fact commonly interpreted as evidence for monetary non-neutrality. This paper resolves the puzzle by developing a model in which the dominant driver of nominal exchange rate fluctuations is a “financial shock” — a shock to the international demand for a country’s assets that is orthogonal to goods market fundamentals. Under a fixed rate, the central bank offsets financial shocks through reserve intervention, preventing them from moving the exchange rate; under a float, financial shocks freely move the nominal and real exchange rate simultaneously. The same framework also reconciles the Meese-Rogoff disconnect (exchange rates are unpredictable from macro fundamentals), the Backus-Smith puzzle, and the forward premium puzzle within a single unified model, with the financial shock accounting for the dominant share of exchange rate variance in each case.

In depth

Q1. What is the financial shock and how does it differ from standard macro shocks?

The financial shock is an orthogonal disturbance to international portfolio demand — the preference of foreign investors for holding domestic versus foreign assets — that is disconnected from productivity, monetary policy, and goods-market conditions. Because it is uncorrelated with macro fundamentals, it generates exchange rate movements without corresponding movements in output, prices, or interest rate differentials, producing the observed disconnect between exchange rates and macro variables.

Q2. Why does the Mussa pattern arise from regime switching?

Under a fixed rate, the central bank absorbs financial shocks via reserve intervention, sterilizing their exchange rate effects; the real exchange rate is equally insulated because the nominal rate is fixed and prices adjust slowly. Under a float, the same financial shocks freely move the nominal exchange rate, and with sticky prices this passes through to the real exchange rate. The variance of the real exchange rate therefore jumps discontinuously at the regime switch, matching the sharp Mussa empirical finding without requiring any change in the shock process.

Q3. How unified is the resolution across exchange rate puzzles?

A single model with the financial shock, sticky prices, and a standard asset pricing kernel simultaneously matches the Mussa pattern (regime-switching real volatility), the Meese-Rogoff disconnect (exchange rates unpredictable from fundamentals), the Backus-Smith puzzle (exchange rates and relative consumption uncorrelated), and the forward premium puzzle (high-interest-rate currencies appreciate). The financial shock accounts for the majority of exchange rate variance in each application.

Key concepts

Mussa puzzle : the discrete jump in real exchange rate volatility at the Bretton Woods breakdown (1973); resolved in this paper as the change in the central bank’s absorption of financial shocks between fixed and floating regimes.

financial shock : a disturbance to international portfolio demand orthogonal to goods-market fundamentals; the paper’s key mechanism for exchange rate disconnect, the Mussa pattern, and several other exchange rate puzzles.

Self-Fundamentals, Cross-Fundamentals, and Exchange Rate Predictions

Mon, 01 Jan 0001 00:00:00 +0000

This paper proposes incorporating both self-fundamentals (the macroeconomic conditions of the two economies in a given currency pair) and cross-fundamentals (the macroeconomic conditions of other major economies, motivated by third-country effects) into exchange rate forecasting. A Mallows model averaging approach optimally combines predictions from multiple fundamental sub-models. The approach significantly outperforms the random walk benchmark for one-month-ahead exchange rate predictions, with both self- and cross-fundamentals contributing independently to forecast accuracy. The paper also reports economically meaningful investment profits from a strategy exploiting the forecasts in currency and bond markets.

In depth

Q1. What are cross-fundamentals and why do they improve forecasts?

Cross-fundamentals are macroeconomic variables from economies outside the bilateral currency pair — motivated by Berg and Mark’s (2015) theory of third-country effects, which shows that trade patterns, interest rate differentials, and capital flows create bilateral exchange rate linkages beyond the direct bilateral relationship. By including cross-country macro indicators alongside bilateral fundamentals, the model captures information that bilateral-only models discard. The paper finds both self- and cross-fundamentals contribute independently to forecast accuracy, confirming that third-country effects are empirically relevant beyond their theoretical motivation.

Q2. How does Mallows model averaging improve forecasts relative to single models?

Rather than selecting a single exchange rate fundamental model, Mallows model averaging assigns optimal weights to multiple sub-models by minimizing a criterion that balances in-sample fit and model complexity, avoiding the model-uncertainty problem that plagues individual exchange rate forecasting models. No single fundamental model robustly predicts exchange rates, but a weighted combination that allows each model’s information to contribute in proportion to its predictive power significantly outperforms both individual models and the random walk at one-month horizons.

Key concepts

self-fundamentals : macroeconomic variables of the two economies forming a bilateral currency pair; the standard ingredient of exchange rate forecasting models.

cross-fundamentals : macroeconomic variables of major economies outside the bilateral pair; the paper’s novel addition, motivated by third-country effects, that improves exchange rate forecasts.

Mallows model averaging : an optimal linear combination of forecasts from multiple sub-models minimizing a Mallows-type criterion; used to aggregate self- and cross-fundamental information without requiring a single correctly specified model.

The Effects of an Aging Population on the Structure of Bank Assets and Liabilities

Mon, 01 Jan 0001 00:00:00 +0000

Using 2001-2022 annual data on U.S. commercial and savings banks matched with county-level demographic data, this paper shows that banks operating in areas with older populations—measured by the deposit-weighted proportion of seniors (individuals over 65) in the counties where the bank has branches—issue more retail deposits and less wholesale funding, pay relatively lower retail deposit rates with greater stickiness across maturities, and experience smaller deposit withdrawals when market interest rates rise. On the asset side, these banks hold significantly more securities and fewer loans (particularly small business and residential mortgage loans) with longer maturities, substantially raising their asset-liability maturity gap. These findings are consistent with a lifecycle model in which seniors demand risk-free retail deposits as an investment vehicle while exhibiting lower borrowing demand, combined with the localization of banks’ deposit-taking and lending. The paper instruments for a bank’s senior exposure using projected county-level senior population shares constructed from historical state-level fertility rates and county-level cohort change rates by race and sex, mitigating concerns about endogenous bank location relative to contemporaneous economic conditions.

In depth

Q1. How is a bank’s exposure to seniors measured, and why is this measure preferred?

A bank’s ’exposure to seniors’ is defined as the deposit-weighted senior population share of all counties where the bank operates branches, using each county’s deposits at that bank as weights; this measure is preferred because it captures the bank’s actual demographic exposure to older depositors while accounting for the relative importance of each local market to the bank. The paper instruments for this measure using projected county-level senior population shares derived from historical demographic data (state-level fertility rates by race, historical county-level cohort change rates by race and sex), which are orthogonal to the contemporaneous economic conditions that could cause population migration and confound the results.

Q2. How does senior exposure affect retail deposit rates and stickiness?

Banks with greater senior exposure pay significantly lower interest rates on retail time deposits, and the spread between an equivalent-maturity competitive market rate and the bank’s retail deposit rate widens by more as market rates rise, indicating greater deposit rate stickiness; this effect is especially pronounced at longer maturities (24- and 60-month CDs), where seniors’ preference for deposits as an investment vehicle rather than a transaction account gives banks greater market power. Moreover, these banks’ deposits are less likely to be withdrawn when the Federal Funds Rate rises, despite lower and slower-adjusting deposit rates, consistent with seniors’ lesser sensitivity to interest rate differentials (limited recall in monitoring rates, as in Kahn, Pennacchi, and Sopranzetti 1999).

Q3. How does senior exposure affect the composition and maturity of assets?

Banks exposed to more seniors hold significantly more securities and fewer loans—particularly small business loans and residential mortgages—and choose securities and loans with much longer maturities, which substantially raises their asset-liability maturity gap. The lifecycle model predicts this: in markets with older populations, the demand for loans is lower (seniors are net savers, and local businesses benefit from greater labor supply in younger areas), leaving the bank’s retail deposit surplus to be invested in securities. The long-maturity asset allocation is supported by the bank’s stable retail deposit base, which is less sensitive to market rate movements (increasing the effective duration of deposits beyond their stated maturity).

Q4. What are the macroeconomic implications as populations age?

The paper’s findings predict economically important changes in banks’ future asset-liability structures as U.S. populations age: aggregate bank loan-to-asset ratios should decline, security-to-asset ratios rise, retail deposit shares increase, wholesale funding shares decrease, and the banking system’s aggregate asset-liability maturity gap should widen—with corresponding implications for banks’ interest rate risk exposure and the transmission of monetary policy through the bank lending channel. The demographic shift is projected to continue: the U.S. share of the population over 65 is predicted to reach 22% by 2050, while the EU’s share is projected at 28% and China’s share of those over 60 is projected at 40% in 2050, making these dynamics relevant across advanced economies.

Key concepts

bank exposure to seniors : the deposit-weighted proportion of individuals over age 65 in the counties where a bank has branches; the paper’s key explanatory variable, capturing how much of the bank’s deposit base is drawn from an older population. deposit rate stickiness : the slower adjustment of retail deposit rates to changes in equivalent-maturity competitive market interest rates; greater stickiness implies a widening of the deposit rate spread as market rates rise; found here to be more pronounced for banks with higher senior exposure. asset-liability maturity gap : the difference between the bank’s asset average maturity and its deposit average maturity; measures the bank’s exposure to interest rate risk; found here to be significantly larger for banks with higher senior exposure due to longer-maturity assets and stable retail deposit funding.

Trade with Nominal Rigidities: Understanding the Unemployment and Welfare Effects

Mon, 01 Jan 0001 00:00:00 +0000

Standard international trade models assume perfectly flexible prices and full employment. This paper introduces nominal rigidities (downward wage rigidity) into a quantitative trade model and asks how this changes the welfare gains from trade liberalization. The central finding is that standard flexible-price estimates overstate the welfare gains by approximately one-third: trade liberalization can generate unemployment in import-competing sectors when wages cannot fall, and the forgone output from these workers is a welfare cost that flexible-price models miss entirely. The paper calibrates the degree of downward wage rigidity to cross-country data on unemployment volatility and shows that the magnitude of the overstatement is robust across a range of calibrations. An analytical decomposition separates the allocative efficiency gains (which standard models capture) from the employment losses (which they miss), clarifying when the overstatement is large versus small.

In depth

Q1. How does downward wage rigidity create unemployment from trade liberalization?

When import competition reduces demand for domestic labor in an affected sector, wages cannot fall fast enough to clear the labor market under downward rigidity; workers are priced out of re-employment in the short run, generating cyclical unemployment in the import-competing sector that persists until real wages adjust through inflation erosion. The unemployment is involuntary and represents forgone production — a social cost that flexible-price models attribute to zero by assumption.

Q2. Why is the overstatement approximately one-third?

The one-third figure comes from the ratio of the employment-loss welfare cost to the total flexible-price welfare gain in the paper’s benchmark calibration; the rigidity-driven employment loss is large enough relative to the allocative efficiency gain to reduce net welfare gains substantially, but not so large as to eliminate them. This ratio is not universal — it depends on the degree of wage rigidity, the sectoral composition of trade exposure, and the speed of labor reallocation — but the paper shows it is robust across plausible parameter ranges.

Q3. Does trade liberalization still generate net welfare gains?

Yes, on net the welfare gains from trade remain positive even with downward wage rigidity — the overstatement of one-third means the true gains are positive but smaller than flexible-price models predict, not negative. The paper does not argue against trade liberalization but against using flexible-price welfare estimates without adjustment for unemployment costs.

Key concepts

downward wage rigidity : the empirical constraint that nominal wages adjust slowly downward; the key friction this paper adds to the quantitative trade model, generating unemployment in sectors hit by import competition.

welfare overstatement : the gap between the flexible-price welfare gain from trade liberalization (the standard model’s prediction) and the true gain once unemployment costs from nominal rigidity are accounted for; approximately one-third in the paper’s benchmark calibration.

Monetary-Policy-Transmission | Macro Paper Warehouse

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Layer 1: Overview

In depth

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Q4. What are the welfare effects of different policy rules in response to a persistent energy price shock, and what are the magnitudes?

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Q6. What does Ramsey-optimal policy look like, and why does it differ from Taylor-type rules?

Q7. What is the role of heterogeneity in shaping these results, and what would be missed by a representative-agent model?

Q8. What are the model’s main limitations and scope conditions?

Key Concepts

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In depth

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Q4. What changes even if credit is not reduced?

Key concepts

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In depth

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Q3. When does QE affect credit spreads?

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Key concepts

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In depth

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Q2. What is the mechanism, and how do the authors identify it?

Q3. What does this imply for monetary policy?

Key concepts

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In depth

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Q2. What are the three transmission channels, and how much does each matter?

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Q4. Is ’leaning against the wind’ the optimal prudential use of monetary policy?

Q5. How should monetary and macroprudential policy be combined, and how pre-emptively?

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Q7. Are capital controls beggar-thy-neighbor, and how do international spillovers work?

Q8. When is international policy coordination desirable?

Q9. How do these results differ from prior open-economy liquidity-trap models?

Key concepts

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In depth

Q1. What dataset is used and how is the FRM share measured?

Q2. How are monetary policy shocks identified and why are information effects excluded?

Q3. What is the path-dependency mechanism and what does Figure 3 show?

Q4. How does the mortgage stock composition affect monetary policy transmission (state-dependency)?

Q5. Why is the shift toward ARMs after tightening paradoxical given the standard relative pricing model, and what channels can explain it?

Q6. Is the state-dependency effect asymmetric between tightening and loosening cycles?

Q7. What are the implications for central bank transmission assessment and policy?

Key concepts

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In depth

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Q4. Why does the CB policy produce a stronger post-crisis rebound?

Q5. What makes the model require a non-linear solution?

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Q7. Why do household deposits remain stable even as interbank markets are disrupted?

Key concepts

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In depth

Q1. What is the financial shock and how does it differ from standard macro shocks?

Q2. Why does the Mussa pattern arise from regime switching?

Q3. How unified is the resolution across exchange rate puzzles?

Key concepts

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In depth

Q1. What are cross-fundamentals and why do they improve forecasts?

Q2. How does Mallows model averaging improve forecasts relative to single models?

Key concepts

The Effects of an Aging Population on the Structure of Bank Assets and Liabilities

In depth

Q1. How is a bank’s exposure to seniors measured, and why is this measure preferred?