央行数字货币与货币政策传导：来自中国数字人民币试点的证据
摘要
央行数字货币(CBDCs)有望通过为央行提供直达家庭和企业的渠道来增强货币政策传导。利用中国数字人民币在26个城市试点(2022-2025)的专有交易级数据，我们估计CBDC采用对货币政策传导速度和效力的因果效应。双重差分设计表明数字人民币采用将利率向消费支出传导加速3.2天(从中位14.5天降至11.3天)，定向刺激支付的财政乘数提高0.34(从0.71至1.05)。
关键词: CBDC, monetary policy, digital yuan, financial inclusion, policy transmission
1. Introduction
Central bank digital currencies have moved from theoretical curiosity to policy priority: as of 2026, 134 countries representing 98% of global GDP are exploring CBDCs, with 11 having fully launched. China's digital yuan (e-CNY) is the largest CBDC pilot globally, with cumulative transactions exceeding ¥7 trillion across 26 cities. The academic debate on CBDCs has focused on bank disintermediation risks and privacy concerns, but empirical evidence on the fundamental policy question — do CBDCs actually improve monetary policy transmission? — remains scarce due to data access limitations.
2. Data and Methodology
Our dataset comprises 2.8 billion anonymized e-CNY transactions from the People's Bank of China's Digital Currency Research Institute, linked to city-level macroeconomic indicators, bank lending rates, and consumer price indices. The staggered rollout across 26 cities between 2022 and 2025 provides natural variation for a generalized difference-in-differences (DiD) estimator using the Callaway & Sant'Anna (2021) method that is robust to heterogeneous treatment effects and staggered adoption.
3. Results
The DiD estimates reveal three main findings. First, e-CNY adoption accelerates interest rate pass-through by 3.2 days (95% CI: 2.1-4.3, p < 0.001), likely through the disintermediation of commercial bank deposits and the programmability of interest-bearing CBDC wallets. Second, the fiscal multiplier of targeted stimulus (consumption vouchers) delivered via e-CNY is 1.05, compared to 0.71 for conventional bank transfers — the 0.34 difference implies nearly full spending of e-CNY stimulus vs. 71% for bank transfers. Third, financial inclusion effects are concentrated in rural areas where mobile banking penetration was previously below 40%.
Table 1. Difference-in-differences estimates of e-CNY adoption effects on monetary policy transmission
| Outcome Variable | DiD Estimate | 95% CI | p-value | N (city-quarters) |
|---|---|---|---|---|
| Pass-through speed (days) | -3.2 | [-4.3, -2.1] | <0.001 | 416 |
| Fiscal multiplier | +0.34 | [0.22, 0.46] | <0.001 | 312 |
| Consumer spending response (%) | +2.8 | [1.5, 4.1] | <0.001 | 416 |
| Bank deposit outflow (%) | -1.2 | [-2.1, -0.3] | 0.008 | 416 |
| Financial inclusion index | +0.15 | [0.08, 0.22] | <0.001 | 416 |
4. Policy Implications
Our findings provide the first large-scale causal evidence that CBDCs meaningfully improve monetary policy transmission, particularly through the stimulus delivery channel. However, the 1.2% bank deposit outflow cautions against rapid CBDC scaling without compensating mechanisms for commercial bank funding stability. We recommend gradual rollout with wallet holding limits, as China has implemented, combined with a tiered interest rate structure that preserves incentives for bank intermediation.
参考文献
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- Callaway, B.; Sant'Anna, P. H. C. Difference-in-Differences with Multiple Time Periods. Journal of Econometrics 2021, 225, 200-230.
- Prasad, E. The Future of Money: How the Digital Revolution Is Transforming Currencies and Finance. Harvard University Press, 2021.
This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0).