The Macroeconomics of Digital Money : Household Adoption, Bank Intermediation, and Monetary Policy
Notice bibliographique
Résumé
Essay I: This paper examines how household-targeted government policies influence financial market participation conditional on financial literacy, focusing on potential Central Bank Digital Currency (CBDC) adoption. Due to the lack of empirical CBDC data, I use the introduction of retail Treasury bonds in Italy as a proxy to investigate how financial literacy affects households' likelihood to engage with the new instrument. Using the Bank of Italy's Survey on Household Income and Wealth, I explore how financial literacy influenced households' participation in the Treasury bond market following the 2012 introduction of retail Treasury bonds, showing that households with some but low financial literacy are more likely to participate than other household groups. Based on these findings, I develop a theoretical model to explore the potential implications of financial literacy for CBDC adoption, showing that low-literate households with limited access to risky assets allocate more wealth to CBDC, while high-literate households use risky assets to safeguard against income risk. These results highlight the role of financial literacy in shaping portfolio choices and CBDC adoption. Essay II (with Hanfeng Chen): We analyze the risks to bank intermediation following the introduction of a central bank digital currency (CBDC) competing with commercial bank deposits as households' source of liquidity. We revisit the result in the literature regarding the equivalence of payment systems introducing a collateral constraint on banks borrowing from the central bank. Comparing two equilibria with and without the CBDC, we find that even with this constraint, the central bank can ensure the same equilibrium allocation and price system by offering loans to banks. However, to access loans, banks must hold collateral at the expense of extending credit to firms. Thus, while the CBDC introduction has no real effects on the economy, it does not guarantee full neutrality as it affects banks' business models. In a dynamic model extension, we examine the effects of an increase in the CBDC and show that the CBDC does not cause bank disintermediation or crowd out deposits but may foster an expansion of bank credit to firms. Essay III (with Hanfeng Chen): We study the implications of a central bank digital currency (CBDC) for the transmission of household preference shocks and for welfare in a New Keynesian framework where the CBDC competes with bank deposits for household resources and banks have market power. We show that an increase in the benefit of CBDC has a mildly expansionary effect, weakening bank market power and significantly reducing the deposit spread. As households economize on liquid asset holdings, they reduce both CBDC and deposit balances. However, the degree of bank disintermediation is low, as deposit outflows remain modest. We then examine the welfare implications of CBDC rate setting and find that, compared to a non-interest-bearing CBDC, the gains with standard coefficients for a CBDC interest rate Taylor rule are modest, but they become considerable when the coefficients are optimized. Welfare gains are higher when the CBDC provides a higher benefit.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».