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Mr. Dong He, Annamaria Kokenyne, Xavier Lavayssière, Ms. Inutu Lukonga, Nadine Schwarz, Nobuyasu Sugimoto, and Jeanne Verrier

panel regression model confirms the relative importance of macroeconomic and demographic factors in driving crypto-asset adoption (Appendix 2; see also Feyen, Kawashima, and Mittal 2022 ). Empirical results show that volatile macroeconomic conditions (such as currency depreciation and high inflation) and a younger population age structure tend to boost crypto-asset adoption. Continued growth and adoption of crypto assets could also induce new macrofinancial risks such as “cryptoization.” Crypto assets may be regarded by some as a new asset class with distinct

Ms. Marwa Alnasaa, Nikolay Gueorguiev, Mr. Jiro Honda, Eslem Imamoglu, Mr. Paolo Mauro, Keyra Primus, and Mr. Dmitriy L Rozhkov
Empirical investigation of the factors underlying the growing usage of crypto-assets is in its infancy, owing to data limitations. In this paper, we present a simple cross-country analysis drawing on recently released survey-based data. We explore the correlation of crypto-asset usage with indicators of corruption, capital controls, a history of high inflation, and other factors. We find that crypto-asset usage is significantly and positively associated with higher perception of corruption and more intensive capital controls. Notwithstanding the data limitations, the results support the case for regulating crypto-assets, including know-your-customer approaches, as opposed to taking a laissez-faire stance.
Mr. Dong He, Annamaria Kokenyne, Xavier Lavayssière, Ms. Inutu Lukonga, Nadine Schwarz, Nobuyasu Sugimoto, and Jeanne Verrier

Circumvent CFMs A. “What Kind of Creature Are They?” B. Who Are the Asset Holders and Where Are They Located? C. Can Intermediaries Be Held Responsible for Compliance? D. Using Crypto Assets to Circumvent CFMs: An Illustration of Mechanisms IV. Strategies to Preserve the Effectiveness of CFMs A. Strengthening Legal and Regulatory Frameworks B. Leveraging Regtech and Suptech for CFM V. Conclusions VI. References VII. Appendixes Appendix 1. Drivers of Crypto Asset Adoption in Selected Countries Appendix 2. Empirical Analysis of the Drivers of Crypto

Ms. Marwa Alnasaa, Nikolay Gueorguiev, Mr. Jiro Honda, Eslem Imamoglu, Mr. Paolo Mauro, Keyra Primus, and Mr. Dmitriy L Rozhkov

@imf.org Title Page WORKING PAPERS Crypto, Corruption, and Capital Controls: Cross-Country Correlations Prepared by Marwa Alnasaa, Nikolay Gueorguiev, Jiro Honda, Eslem Imamoglu, Paolo Mauro, Keyra Primus, and Dmitriy Rozhkov Contents Introduction Data Description and Methodology Results Conclusion References Appendix I. Alternative Data on Crypto Adoption FIGURE 1. Crypto-Asset Adoption and Potential Explanatory Factors TABLES 1. Descriptive Statistics 2. Pairwise Correlations 3. Multivariate Regressions (general-to-specific) with Crypto

Mr. Dong He, Annamaria Kokenyne, Xavier Lavayssière, Ms. Inutu Lukonga, Nadine Schwarz, Nobuyasu Sugimoto, and Jeanne Verrier

VII. Appendixes Appendix 1. Drivers of Crypto Asset Adoption in Selected Countries This note highlights the drivers of crypto adoption by country and how they differ by level of development. ADVANCED ECONOMIES US Bitcoin mining, trading, and DeFi transactions in the US are among the highest in the world. Retail investors dominated the market, driven by speculative investment motives, but institutional investors searching for yield amid low interest rates contributed to recent price rallies. The launch of Bitcoin futures

Mr. Dong He, Annamaria Kokenyne, Xavier Lavayssière, Ms. Inutu Lukonga, Nadine Schwarz, Nobuyasu Sugimoto, and Jeanne Verrier
Capital flow management measures (CFMs) can be part of the broader policy toolkit to help countries reap the benefits of capital flows while managing the associated risks. Their implementation typically requires that financial intermediaries verify the nature of transactions and the identities of transacting parties but is facing the rising challenge of crypto assets. Indeed, crypto assets have become a significant instrument for payments and speculative investments in some countries. They can be traded pseudonymously and held without identification of the residency of the asset holder. Many crypto service providers operate across borders, making supervision and enforcement by national authorities more difficult. The challenges posed by the attributes of crypto assets are compounded by gaps in the legal and regulatory frameworks. This paper aims to discuss how crypto assets could impact the effectiveness of CFMs from a structural and longer-term perspective. To preserve the effectiveness of CFMs against crypto-related challenges, policymakers need to consider a multifaceted strategy whose essential elements include clarifying the legal status of crypto assets and ensuring that CFM laws and regulations cover them; devising a comprehensive, consistent, and coordinated regulatory approach to crypto assets and applying it effectively to CFMs; establishing international collaborative arrangements for supervision of crypto assets; addressing data gaps and leveraging technology (regtech and suptech) to create anomaly-detection models and red-flag indicators that will allow for timely risk monitoring and CFM implementation.
Tara Iyer

, and design appropriate regulatory policies to mitigate systemic risks emanating from crypto price spillovers. The analysis in this note extends the burgeoning literature on the interlinkages between crypto assets and other asset classes in several ways. First, while most of the studies have focused on the pre-pandemic period, the analysis here considers potential spillovers between crypto and equity markets in the post-pandemic period given the exponential growth in crypto asset adoption since the first quarter of 2020. Second, in contrast to earlier literature

Ms. Marwa Alnasaa, Nikolay Gueorguiev, Mr. Jiro Honda, Eslem Imamoglu, Mr. Paolo Mauro, Keyra Primus, and Mr. Dmitriy L Rozhkov

check, all simple correlations remain significant when we remove significant outliers. In view of the high correlations among explanatory variables, multicollinearity is a methodological challenge ( Table 2 ). Specifically, relatively high correlations are present between control of corruption indicators and real GDP per capita and capital controls. Figure 1. Crypto-Asset Adoption and Potential Explanatory Factors (continued) Source: Statista, Worldwide Governance Indicators, IMF World Economic Outlook, IMF Global Debt Database, IMF Annual Report on

Tara Iyer
Crypto assets have emerged as an increasingly popular asset class among retail and institutional investors. Although initially considered a fringe asset class, their increased adoption across countries—in emerging markets, in particular—amid bouts of extreme price volatility has raised concerns about their potential financial stability implications. This note examines the extent to which crypto assets have moved to the mainstream by estimating the potential for spillovers between crypto and equity markets in the United States and in emerging markets using daily data on price volatility and returns. The analysis suggests that crypto and equity markets have become increasingly interconnected across economies over time. Spillovers from price volatility of the oldest and most popular crypto asset, Bitcoin, to the S&P 500 and MSCI emerging markets indices have increased by about 12-16 percentage points since the onset of the COVID-19 pandemic, while those from its returns have increased by about 8-10 percentage points. Spillovers from the most traded stablecoin, Tether, to these indices have also increased by about 4-6 percentage points. In absolute terms, spillovers from Bitcoin to global equity markets are significant, explaining about 14-18 percent of the variation in equity price volatility and 8-10 percent of the variation in equity returns. These findings suggest that close monitoring of crypto asset markets and the adoption of appropriate regulatory policies are warranted to mitigate potential financial stability risks.
Mrs. Sarwat Jahan, Ms. Elena Loukoianova, Mr. Evan Papageorgiou, Ms. Natasha X Che, Ankita Goel, Mike Li, Umang Rawat, Yong Sarah Zhou, and Ankita Goel

failure of the crypto asset Luna and its associated algorithmic stablecoin, TerraUSD, which were administered by Terraform Labs. Figure 10. Crypto Transaction Volumes Source: Chainalysis and IMF staff calculations. The survey also yielded some interesting results: Crypto asset adoption in most emerging markets and LICs kept pace with advanced economies in Asia . While it is not surprising that advanced economies such as Australia, Hong Kong SAR, Korea, and Singapore, have a large volume of transactions in crypto, several emerging markets and LICs, such