with Fabienne Schneider
This paper extends the analysis of pure-credit equilibria in limited-commitment environments by introducing pseudonymous record-keeping. In this regime, only the borrowing history tied to a pseudonym (e.g., a wallet address or online identity) is publicly observable, and agents may freely create and operate multiple pseudonyms. We characterize the entire set of credit equilibria under pseudonymity and show that they form a strict subset of those attainable under no-anonymity record-keeping, where borrowing histories are publicly linked to true identities (e.g., personal names). We show that history-dependent credit contracts—where accounts with longer repayment records receive more favorable terms—can discipline behavior by deterring both voluntary default and the use of multiple pseudonyms. Yet these contracts remain generally inefficient compared to allocations under no-anonymity. In particular, while money (or collateral) is not essential under no-anonymity, it becomes essential with pseudonymous record-keeping. Finally, we examine two extensions: (i) charging a fee for creating new pseudonyms and (ii) allowing accounts to be transferred across agents. Our theoretical insights bear directly on the design of credit in decentralized lending platforms and on the role of cryptocurrency/assets on blockchains.
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.
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.
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.
Money, such as cash, is valuable because it reduces payment frictions. With advances in payment technology, however, these frictions diminish, raising the question of whether the value of money will collapse or whether it will nevertheless persist. Moreover, are such technological improvements necessarily welfare-enhancing? We address these questions in an OLG model with a cash-in-advance constraint. Our analysis shows that money retains value despite vanishing payment frictions only if the economy is dynamically inefficient (for instance, when the demand for savings is sufficiently large). Furthermore, improvements in payment technology can reduce welfare if they are not fully anticipated, as they may redistribute across agents and induce costly hedging behavior.
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.