with Fabienne Schneider
We study pseudonymity—an information regime where agents’ histories are perfectly observable, but linked only to pseudonyms rather than to true identities. A key feature is that agents may open and use multiple pseudonyms simultaneously. In a tractable environment with limited commitment, we characterize the set of stationary credit equilibria under pseudonymity, showing that it forms a strict non-empty subset of equilibria attainable under a no anonymity regime, where histories are publicly linked to true identities. Moreover, money is always essential under pseudonymity, yet cannot co-exist with credit. Finally, imposing optimal fees on pseudonym creation generally raises welfare, whereas making pseudonyms tradable never does.
The proposed revision of the Swiss Banking Act introduces a public liquidity backstop (PLB) for distressed systemically important banks (SIBs), in part to facilitate resolution. We examine the impact of the PLB on fiscal balances, societal welfare, and the incentives of bank shareholders and management. A PLB, like too-big-to-fail (TBTF) status, acts as a subsidy for non-convertible bonds, which can create negative externalities. Corrective measures must be implemented before the PLB is activated to align incentives with societal interests. We conservatively estimate that Swiss SIBs’ TBTF status results in funding cost reductions far greater than the proposed ex-ante compensation, with UBS Group AG alone gaining at least USD 2.9 billion in 2022. The risk for Switzerland of hosting SIBs warrants additional precautionary savings.
How do heterogeneous inflation expectations affect the welfare costs of both average inflation and inflation volatility? And how does inflation itself shape the distribution of those expectations? I address these questions in a monetary model where expectation heterogeneity arises endogenously from households’ optimal information acquisition and idiosyncratic shopping in segmented markets, while firms are assumed to be better informed about future inflation. A central result is that, in the presence of heterogeneous expectations, inflation volatility allows firms to sustain higher markups, distorting consumption beyond the classic inflation tax and consumption risk. Quantitatively, the welfare cost of average inflation is 12–24%, while the cost of inflation volatility is 100 to 270 times larger than in a benchmark without heterogeneous expectations. Moreover, average inflation shapes the distribution of expectations both directly—through information acquisition—and indirectly—through its effect on the velocity of money and thus the speed of learning from shopping. Consistent with these mechanisms, I find supporting evidence in survey data.
We provide an example of an equilibrium in which an intrinsically worthless object has no observable role—even as a means of payment—yet still possesses value. The reason is that it can be useful for its liquidity benefits in certain future states of the economy. We show that, for this to be an equilibrium, adopting the object as a payment instrument must be sufficiently costly, but not too costly. Beyond private valuations, we demonstrate that the presence of such an apparently speculative asset can, in theory, be socially beneficial—serving as a disciplining device against future governments tempted to inflate away their debt burden—or socially costly, by raising the cost of holding the current medium of exchange. Applied to cryptocurrencies, a calibration exercise using U.S. and Bitcoin data suggests that these benefits could be substantial.
Money and credit are ubiquitous payment instruments in modern economies, yet co-essentiality—the feature that the use of money and credit outputferoms arrangments with only either- is hard to generate in microfounded models of money. We address this in a heterogeneous New-Monetarist framework where agents differ in expected lifespans. We show that when lifespans are publicly known, co-essentiality does not arise. However, introducing asymmetric information enables co-essentiality: credit becomes essential for young agents without money balances, while money provides a safeguard against default risks. Achieving such an equilibrium requires monetary policy to generate sufficient but limited inflation—high enough to raise debt limits but not so high as to excessively increase the cost of holding money.
I study the effects of monetary policy on both the emergence and the size of pure asset price bubbles— such as cryptoassets—and examine how these effects depend on the liquidity structure of the economy. We develop a standard overlapping-generations model with liquidity frictions in which cryptoassets do not relax liquidity or collateral constraints, but are instead held purely for speculative purposes.
My analysis yields four main results. First, monetary policy affects bubbles only when liquidity frictions are of intermediate severity; when frictions are either too weak or too strong, policy is neutral with respect to bubble formation. Second, the sign of the effect depends critically on the distribution of seigniorage and the economy’s liquidity structure. Third, even though the Friedman Rule is not necessarily optimal in the absence of a bubble, it always is when a bubble exists. Finally, the source of liquidity also matters: when liquidity is predominantly banks inside rather than the government directly, the effect of monetary policy on bubbles is dampened, and both the likelihood and the size of bubbles are increased.
This paper examines the relationship between inflation shocks and inflation uncertainty in Switzerland using a Bayesian GARCH-M-GJR-LEV framework. I test whether unexpected changes in inflation increase uncertainty, whether the effect differs between positive and negative shocks, and whether uncertainty feeds back into the level of inflation. Bayesian estimation reveals strong evidence that inflation shocks raise uncertainty, but little evidence that uncertainty affects inflation levels or that the effect is asymmetric. Out-of-sample forecasting exercises show that incorporating GARCH dynamics improves predictive accuracy for Swiss inflation, underscoring the practical value of modelling time-varying volatility even in a low-inflation, high-credibility environment.