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Financial and market risks of bitcoin adoption as legal tender: evidence from El Salvador

Business

Financial and market risks of bitcoin adoption as legal tender: evidence from El Salvador

G. Msefula, T. C. Hou, et al.

This study, conducted by Griffin Msefula, Tony Chieh-Tse Hou, and Tina Lemesi, delves into the impacts of El Salvador's Bitcoin adoption on financial stability. With revealing insights from a structural vector autoregressive model, discover how Bitcoin affects remittances, the money multiplier, and gold prices, highlighting both promising international business opportunities and risks to monetary policy.

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Playback language: English
Introduction
El Salvador's decision to adopt Bitcoin as legal tender in June 2021 has sparked considerable debate among academics and policymakers. The government's significant financial losses on Bitcoin investments underscore the inherent risks. Existing research on Bitcoin adoption focuses on incentives and network effects, but lacks a comprehensive analysis of the potential financial and market risks associated with its adoption as legal tender. This study aims to fill this gap by exploring the policy-level implications of Bitcoin's adoption in El Salvador. Key concerns include the lack of regulatory frameworks for exchanging Bitcoin into local currencies, the impact on monetary policy due to Bitcoin's fixed supply, and the volatility of Bitcoin's price. The study addresses three primary research questions: 1. Does adopting Bitcoin as legal tender promote economic stability in El Salvador? 2. What is the impact of Bitcoin adoption on international transfers (remittances)? 3. What is the relationship between Bitcoin and gold in influencing monetary policy? The study uses a structural vector autoregressive (SVAR) model to analyze the pass-through effects of Bitcoin price shocks on remittances, the money multiplier, the US Dollar index, and gold prices.
Literature Review
The literature review examines the historical and theoretical underpinnings of money and legal tender. It cites Jevans (1876) on the state's role in defining legal tender, contrasting it with Wicksell's (1962) definition of a common medium of exchange and Kiyotaki and Wright's (1989, 1992) work on acceptability and social conventions in determining the use of money. The role of taxation in creating demand for money (chartalism) is discussed, referencing Coase (1977), Jevans (1876), Wicksteed (1910), and Starr (1989). The authors highlight the existing literature's focus on various aspects of cryptocurrencies, such as risks, arbitrage opportunities, network effects, asset pricing, and price impacts. However, the current study uniquely contributes by examining whether accepting a digital currency for tax payments is sufficient for its acceptance as a currency, considering the implications for monetary policy, international transfers, and the relationship between Bitcoin and gold.
Methodology
This study employs a structural vector autoregressive (SVAR) model using monthly data from September 10, 2010, to February 30, 2022. The dataset includes Bitcoin prices, remittances (in millions of USD), the money multiplier, the US Dollar Index (DXY), and gold prices. The variables are made stationary before estimation. The SVAR model is used to analyze the dynamic relationships between these variables, specifically focusing on the pass-through effects of Bitcoin price shocks. The Blanchard and Quah (1988) long-run restriction identification strategy is used to identify temporary shocks in Bitcoin. The pass-through is measured by dividing the cumulative impulse response of each variable by the cumulative impulse response of Bitcoin prices after a shock. The study also includes two dummy variables to capture the impact of El Salvador's Bitcoin legal tender legislation. Granger causality tests assess the predictive power of the variables. Impulse response functions are used to analyze the dynamic effects of Bitcoin price shocks, and historical and forecast-error variance decompositions provide insights into the contribution of each variable to the overall variance of Bitcoin prices. A robustness check is performed using an alternative SVAR identification strategy (A-model) to validate the results.
Key Findings
The study's key findings reveal complex and sometimes counterintuitive relationships between Bitcoin price shocks and macroeconomic variables in El Salvador. **Bitcoin Price Pass-Through into Remittances (Bt_rem):** Initial findings showed a short-term negative impact (-11% after one month), followed by a moderate long-term positive impact (around 6.1%). The robustness analysis using the A-model, however, showed a significantly different result, with a substantial initial positive impact (46% after one month) that attenuated over time to around 1.95%. **Bitcoin Price Pass-Through into Money Multiplier (Bt_momu):** A consistently negative impact (-8.8% to -7.6%) was observed across both short and long time horizons in the initial model. The A-model corroborated this finding with a similar negative effect (-6.5% to -6.09%). **Bitcoin Price Pass-Through into USD Index (Bt_usd):** A strong negative impact was consistently observed (-25% to -5.95% in the first model and -27.54% to -11.15% in the robustness test) indicating that Bitcoin price shocks negatively impact the US Dollar index. **Bitcoin Price Pass-Through into Gold Prices (Bt_gold):** Both models indicated a negative impact of Bitcoin price shocks on gold prices, although the magnitude of the impact varied greatly (4% to -6.02% initially, and -8.72% to -23.71% in the robustness check). The historical and forecast-error variance decompositions show that gold prices significantly influence the adoption of Bitcoin as legal tender, suggesting that Bitcoin acts as an asset between gold and the dollar. The money multiplier shows a minimal negative contribution to Bitcoin prices.
Discussion
The findings highlight the complex and multifaceted impact of Bitcoin adoption as legal tender on El Salvador's economy and financial markets. The contrasting results from the two SVAR identification strategies (original and robustness check using the A-model) underscore the sensitivity of the analysis to the chosen identification strategy. The significant negative impact on the money multiplier suggests that widespread Bitcoin adoption might impede the central bank's ability to influence monetary policy effectively through traditional channels. The fluctuations in remittances, both positive and negative depending on the model and timeframe, point to the potential risks and uncertainties associated with using Bitcoin for cross-border transactions. The negative correlation between Bitcoin and the USD index indicates that the market perceives Bitcoin as a potential substitute for or competitor to the USD. The relationship with gold highlights the role of Bitcoin as a potential safe haven asset, albeit with more volatility than gold. The study suggests that policymakers should carefully consider these complex interactions and potential risks before adopting Bitcoin as legal tender.
Conclusion
This study provides valuable insights into the financial and market risks associated with adopting Bitcoin as legal tender. The findings demonstrate the complex and sometimes contradictory impacts on remittances, monetary policy, and the relationship between Bitcoin, gold, and the US Dollar. The significant discrepancies between the initial and robustness check results highlight the need for further research using diverse methodologies and longer time horizons. Policymakers should exercise caution and conduct thorough assessments before adopting Bitcoin as legal tender, considering the potential risks to monetary policy and financial stability. Future research could explore the behavioral aspects influencing remittance decisions in the context of Bitcoin volatility and examine other countries' experiences with similar policies.
Limitations
The study is limited by the availability of data, particularly for El Salvador's macroeconomic indicators. The use of monthly data might mask shorter-term fluctuations and higher-frequency dynamics. The analysis focuses on El Salvador's specific context, and the results might not be generalizable to other countries with different economic and institutional environments. The selection of specific SVAR identification strategies can affect the results; the divergence between the initial and robustness results highlights this sensitivity.
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