Papers and Topics That Could Cite This Research

Chen, Zhengyang. 2025. “From Disruption to Integration: Cryptocurrency Prices, Financial Fluctuations, and Macroeconomy” Journal of Risk and Financial Management 18, no. 7: 360. https://doi.org/10.3390/jrfm18070360

This study on cryptocurrency’s macroeconomic transmission effects could be cited across multiple academic disciplines and research areas. Here’s a detailed breakdown of potential citing opportunities:

Monetary Economics and Central Banking

Monetary Policy Research

• Inflation targeting in the digital age: Papers examining how central banks should modify inflation targeting frameworks to account for cryptocurrency-driven price pressures

• Monetary transmission mechanism studies: Research updating traditional transmission channels to include digital asset pathways

• Central Bank Digital Currency (CBDC) research: Studies comparing CBDC effects with private cryptocurrency impacts on monetary policy effectiveness

• Unconventional monetary policy: Papers on quantitative easing effects when alternative assets like crypto provide portfolio substitution

Central Banking Practice

• Financial stability monitoring: Research on incorporating cryptocurrency metrics into financial stability frameworks

• Macroprudential policy: Studies on whether crypto markets require specific regulatory tools

• Monetary policy communication: Papers on how central banks should communicate about cryptocurrency risks and opportunities

Financial Economics

Asset Pricing and Portfolio Theory

• Modern portfolio theory extensions: Research updating Markowitz (1952) frameworks to include cryptocurrency correlation structures

• Risk factor models: Studies incorporating cryptocurrency as a systematic risk factor (building on Chen’s 18% equity variance contribution finding)

• Alternative investment strategies: Papers on optimal cryptocurrency allocation in institutional portfolios

• Volatility spillover studies: Research on contagion mechanisms between crypto and traditional assets

Financial Integration and Contagion

• Systemic risk assessment: Studies using Chen’s methodology to quantify crypto’s systemic importance in different markets

• Crisis transmission: Research on how cryptocurrency markets amplify or dampen financial crises

• Cross-border financial spillovers: Papers on how cryptocurrency transmission varies across countries

• Market microstructure: Studies on high-frequency transmission mechanisms between crypto and traditional markets

Macroeconomics

Business Cycle Research

• Real business cycle models: Papers incorporating cryptocurrency wealth effects into DSGE (Dynamic Stochastic General Equilibrium) models

• Investment and growth: Studies on how cryptocurrency price volatility affects business investment decisions through the channels Chen identifies

• Consumption smoothing: Research on how cryptocurrency wealth affects household consumption patterns

• Economic forecasting: Papers improving macroeconomic forecasts by including cryptocurrency variables

International Economics

• Exchange rate determination: Studies on how cryptocurrency markets affect traditional currency relationships

• Capital flows: Research on cryptocurrency’s role in international capital mobility

• Global economic integration: Papers on whether cryptocurrency creates new forms of economic interdependence

• Emerging market dynamics: Studies on cryptocurrency adoption in developing economies and macroeconomic effects

Financial Regulation and Policy

Regulatory Economics

• Optimal cryptocurrency regulation: Papers using Chen’s findings to design regulatory frameworks that balance innovation with stability

• Cross-border regulatory coordination: Studies on international policy coordination for systemically important crypto markets

• Market surveillance: Research on monitoring tools for cryptocurrency’s macroeconomic effects

• Prudential regulation: Papers on bank exposure limits to cryptocurrency-related assets

Financial Stability

• Stress testing methodologies: Studies incorporating cryptocurrency shocks into bank and system stress tests

• Early warning systems: Research on cryptocurrency indicators for predicting financial instability

• Resolution frameworks: Papers on how to handle failures of systemically important crypto institutions

• Deposit insurance: Studies on whether crypto-exposed institutions require different insurance frameworks

Behavioral and Experimental Economics

Market Psychology

• Sentiment transmission mechanisms: Papers expanding on Chen’s sentiment findings using experimental or survey methods

• Investor behavior: Studies on how retail vs. institutional investors differently transmit crypto shocks

• Herding and momentum: Research on behavioral factors amplifying cryptocurrency’s macroeconomic effects

• Risk perception: Papers on how cryptocurrency volatility affects broader risk appetite

Technology Adoption

• Innovation diffusion: Studies on how technological developments in crypto markets affect economic adoption patterns

• Network effects: Research expanding on Chen’s network effect findings in cryptocurrency ecosystems

• Digital transformation: Papers on cryptocurrency’s role in broader economic digitization

Development Economics

Financial Inclusion

• Cryptocurrency and financial access: Studies on how crypto markets affect financial inclusion and development outcomes

• Remittances and payments: Research on cryptocurrency’s macroeconomic effects in remittance-dependent economies

• Monetary sovereignty: Papers on how cryptocurrency adoption affects developing country monetary policy

• Dollarization studies: Research comparing cryptocurrency adoption to traditional currency substitution

Economic Development

• Infrastructure and growth: Studies on how cryptocurrency infrastructure affects economic development

• Institutional development: Research on cryptocurrency’s interaction with traditional financial institutions in developing markets

• Capital formation: Papers on how cryptocurrency markets affect savings and investment in emerging economies

Econometric Methodology

Time Series Analysis

• VAR methodology improvements: Papers refining structural identification techniques for cryptocurrency analysis

• Pandemic econometrics: Studies applying or improving Chen’s Pandemic Priors methodology to other research questions

• Narrative identification: Research extending narrative approaches to other asset classes or economic shocks

• Forecast evaluation: Papers comparing traditional vs. crypto-augmented forecasting models

Causal Inference

• Shock identification: Studies using alternative identification strategies to validate Chen’s transmission mechanism findings

• Natural experiments: Research using regulatory changes or technological events as instruments for cryptocurrency effects

• Machine learning approaches: Papers using AI methods to identify cryptocurrency transmission patterns

Technology and Innovation Studies

Financial Technology

• Blockchain economics: Studies on how blockchain adoption affects traditional economic relationships

• Digital asset ecosystem: Research on interactions between different cryptocurrency platforms and economic effects

• Decentralized finance (DeFi): Papers on how DeFi protocols interact with traditional financial transmission mechanisms

• Stablecoin research: Studies on how different cryptocurrency types have varying macroeconomic effects

Innovation Policy

• Technology regulation: Research on optimal policies for emerging financial technologies

• Innovation spillovers: Studies on how cryptocurrency innovation affects other sectors

• Digital infrastructure: Papers on the macroeconomic effects of financial technology infrastructure

International Finance

Global Financial Markets

• Safe haven assets: Studies comparing cryptocurrency to traditional safe havens during crises

• Reserve asset diversification: Research on cryptocurrency’s potential role in central bank reserves

• Global liquidity: Papers on how cryptocurrency markets affect international liquidity transmission

• Financial globalization: Studies on cryptocurrency’s role in financial market integration

Exchange Rate Economics

• Currency substitution: Research on cryptocurrency adoption’s effects on traditional currencies

• Purchasing power parity: Studies incorporating cryptocurrency markets into exchange rate models

• Capital controls: Papers on how cryptocurrency markets circumvent or interact with capital restrictions

Environmental and Energy Economics

Sustainability Studies

• Energy consumption: Papers citing Chen’s findings while examining environmental costs of cryptocurrency’s economic integration

• Sustainable finance: Research on how cryptocurrency’s macroeconomic role affects ESG investing

• Green monetary policy: Studies on incorporating environmental considerations into crypto-aware monetary frameworks

Economic History and Comparative Studies

Historical Perspectives

• Monetary history: Papers comparing cryptocurrency adoption to historical monetary innovations

• Financial innovation: Studies comparing cryptocurrency’s economic integration to past financial innovations

• Crisis comparisons: Research comparing cryptocurrency’s role in recent vs. historical financial crises

Cross-Country Studies

• Comparative monetary systems: Research comparing cryptocurrency effects across different monetary regimes

• Institutional differences: Studies on how institutional quality affects cryptocurrency’s macroeconomic transmission

• Policy regime comparisons: Papers comparing cryptocurrency effects under different regulatory approaches

Specialized Applications

Insurance and Risk Management

• Catastrophe modeling: Studies incorporating cryptocurrency volatility into disaster risk models

• Pension fund management: Research on cryptocurrency exposure in long-term institutional portfolios

• Sovereign risk: Papers on how cryptocurrency markets affect country risk assessments

Real Estate and Housing

• Housing market dynamics: Studies on cryptocurrency wealth effects on real estate markets

• Urban economics: Research on how cryptocurrency industries affect local economic development

• Property investment: Papers on cryptocurrency’s interaction with real estate as alternative investments

Labor Economics

• Employment effects: Studies expanding on Chen’s unemployment findings with sectoral or demographic detail

• Wage dynamics: Research on how cryptocurrency markets affect wage setting and labor bargaining

• Gig economy: Papers on cryptocurrency’s role in alternative work arrangements

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Papers Relevant to Chen (2025)

Chen, Zhengyang. 2025. “From Disruption to Integration: Cryptocurrency Prices, Financial Fluctuations, and Macroeconomy” Journal of Risk and Financial Management 18, no. 7: 360. https://doi.org/10.3390/jrfm18070360

Foundational Portfolio and Asset Pricing Theory

Markowitz, H. (1952). Portfolio Selection. Journal of Finance, 7(1), 77-91.

Chen’s findings on cryptocurrency spillovers to equity markets (18% variance contribution) directly validate and extend Markowitz’s modern portfolio theory by demonstrating how portfolio rebalancing mechanisms operate in practice with emerging asset classes. The paper provides empirical evidence for the theoretical prediction that assets with similar systematic risk exposures exhibit stronger comovement patterns.

Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk. Journal of Finance, 19(3), 425-442.

Chen’s research confirms CAPM predictions by showing that cryptocurrency shocks primarily affect equity markets while notably excluding bonds, reflecting the risk characteristics of cryptocurrencies as speculative growth assets rather than safe havens as predicted by systematic risk theory.

Tobin, J. (1958). Liquidity Preference as Behavior Towards Risk. Review of Economic Studies, 25(2), 65-86.

The delayed industrial production response (0.15%) found in Chen’s study strongly supports Tobin’s Q theory, where cryptocurrency price movements influence investment through relative capital costs, with timing reflecting real options effects where firms optimize irreversible investment decisions.

Behavioral Finance and Market Sentiment

Baker, M., & Wurgler, J. (2006). Investor Sentiment and the Cross‐Section of Stock Returns. Journal of Finance, 61(4), 1645-1680.

Chen’s narrative analysis revealing sentiment as the strongest driver of cryptocurrency shocks (coefficient = 1.36) directly validates Baker and Wurgler’s investor sentiment framework, demonstrating how mood-driven trading creates systematic factors affecting multiple asset classes beyond individual stocks.

De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise Trader Risk in Financial Markets. Journal of Political Economy, 98(4), 703-738.

Chen’s findings on sentiment-driven cryptocurrency transmission mechanisms provide modern empirical validation of the noise trader model, showing how sentiment shocks propagate across asset classes and affect real economic variables like unemployment and industrial production.

Financial Contagion and Spillover Effects

Forbes, K. J., & Rigobon, R. (2002). No Contagion, Only Interdependence: Measuring Stock Market Comovements. Journal of Finance, 57(5), 2223-2261.

Chen’s methodology using structural VAR with pandemic priors builds on Forbes and Rigobon’s contagion framework, but finds evidence of true spillover effects rather than just correlation, with cryptocurrency shocks explaining substantial variance in traditional financial markets even after controlling for common factors.

Diebold, F. X., & Yilmaz, K. (2012). Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers. International Journal of Forecasting, 28(1), 57-66.

Chen’s variance decomposition results (18% equity, 27% commodities) complement Diebold-Yilmaz spillover methodology by providing structural identification of cryptocurrency as a source rather than recipient of financial market volatility, establishing directional causality through narrative validation.

Monetary Economics and Central Banking

Bernanke, B. S., & Blinder, A. S. (1992). The Federal Funds Rate and the Channels of Monetary Transmission. American Economic Review, 82(4), 901-921.

Chen’s findings on monetary policy responses to cryptocurrency shocks (initial M4 expansion followed by contraction) extend Bernanke-Blinder’s monetary transmission framework to include how central banks respond to alternative asset price movements that generate inflationary pressures.

Christiano, L. J., Eichenbaum, M., & Evans, C. L. (1999). Monetary Policy Shocks: What Have We Learned and to What End? Handbook of Macroeconomics, 1, 65-148.

Chen adopts the Christiano-Eichenbaum-Evans recursive identification strategy while extending it to cryptocurrency markets, demonstrating how their established VAR methodology can be applied to understand transmission mechanisms of emerging financial innovations to macroeconomic variables.

Romer, C. D., & Romer, D. H. (2004). A New Measure of Monetary Shocks: Derivation and Implications. American Economic Review, 94(4), 1055-1084.

Chen’s narrative identification approach directly builds on Romer and Romer’s pioneering work by applying their narrative regression methodology to cryptocurrency markets, using historical events to validate structural shock identification and provide economic interpretation of estimated shock series.

Financial Accelerator and Credit Channels

Bernanke, B., Gertler, M., & Gilchrist, S. (1999). The Financial Accelerator in a Quantitative Business Cycle Framework. Handbook of Macroeconomics, 1, 1341-1393.

Chen’s finding that financial stress indicators improve following positive cryptocurrency shocks provides empirical support for financial accelerator mechanisms, where asset price changes affect balance sheets and credit conditions, subsequently influencing real economic activity through enhanced credit availability.

Kiyotaki, N., & Moore, J. (1997). Credit Cycles. Journal of Political Economy, 105(2), 211-248.

The simultaneous improvement in financial stress and real economic variables in Chen’s results aligns with Kiyotaki-Moore credit cycle theory, suggesting cryptocurrency appreciation strengthens balance sheets and relaxes borrowing constraints, amplifying the initial wealth effect through credit mechanisms.

Wealth Effects and Consumption

Case, K. E., Quigley, J. M., & Shiller, R. J. (2005). Comparing Wealth Effects: The Stock Market versus the Housing Market. Advances in Macroeconomics, 5(1), 1-32.

Chen’s findings on unemployment reduction (0.02%) following cryptocurrency shocks provide new evidence for wealth effect channels similar to Case-Quigley-Shiller’s housing wealth effects, though the magnitude suggests cryptocurrency wealth effects may be smaller than traditional asset wealth effects.

Ludvigson, S. C., Steindel, C., & Lettau, M. (2002). Monetary Policy Transmission Through the Consumption-Wealth Channel. FRBNY Economic Policy Review, 8(1), 117-133.

Chen’s identification of persistent inflationary pressure (0.15% PCE increase) following cryptocurrency shocks extends Ludvigson et al.’s consumption-wealth channel analysis to digital assets, showing how alternative asset appreciation can generate demand-driven inflation through household spending.

Cryptocurrency-Specific Literature

Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Bitcoin.org.

Chen’s research provides the first comprehensive macroeconomic analysis of Nakamoto’s innovation, demonstrating that Bitcoin has evolved from its original conception as electronic cash to become a systemically important financial asset with measurable effects on inflation, employment, and financial stability.

Yermack, D. (2015). Is Bitcoin a Real Currency? An Economic Appraisal. Handbook of Digital Currency, 31-43.

Chen’s findings directly challenge Yermack’s skeptical assessment of Bitcoin’s economic significance by providing empirical evidence that cryptocurrency markets now exhibit transmission mechanisms characteristic of systemically important assets, contradicting the view of Bitcoin as economically marginal.

Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of Exchange or Speculative Assets? Journal of International Financial Markets, Institutions and Money, 54, 177-189.

Chen’s sentiment-driven shock findings support Baur et al.’s characterization of Bitcoin as primarily speculative, while extending their analysis to show how speculative dynamics create real macroeconomic effects through financial market integration and wealth channels.

Regulatory and Policy Framework

Böhme, R., Christin, N., Edelman, B., & Moore, T. (2015). Bitcoin: Economics, Technology, and Governance. Journal of Economic Perspectives, 29(2), 213-238.

Chen’s findings on the limited role of regulatory shocks in driving cryptocurrency prices provide nuanced evidence for Böhme et al.’s analysis of Bitcoin governance, suggesting that technological and sentiment factors may be more important than regulatory developments in determining market outcomes.

Pieters, G., & Vivanco, S. (2017). Financial Regulations and Price Inconsistencies Across Bitcoin Markets. Information Economics and Policy, 39, 1-14.

Chen’s methodology for identifying regulatory shocks builds on Pieters and Vivanco’s work on regulatory arbitrage, but finds that regulatory events are less systematically important for cryptocurrency transmission than previously thought, suggesting markets may have developed resilience to regulatory uncertainty.

International Finance and Capital Flows

Obstfeld, M., & Taylor, A. M. (2004). Global Capital Markets: Integration, Crisis, and Growth. Cambridge University Press.

Chen’s findings on cryptocurrency spillovers across asset classes contribute to Obstfeld-Taylor’s analysis of global financial integration by documenting how digital assets create new channels for international financial transmission that operate independently of traditional banking and capital flow mechanisms.

Rey, H. (2013). Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence. Proceedings - Economic Policy Symposium - Jackson Hole, 285-333.

Chen’s evidence of cryptocurrency’s role in financial market integration provides a new dimension to Rey’s global financial cycle framework, suggesting that decentralized digital assets may create additional challenges for monetary policy independence beyond traditional capital flow channels.

Asset Pricing Anomalies and Market Efficiency

Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.

Chen’s finding that sentiment shocks are the strongest driver of cryptocurrency markets relates to Jegadeesh-Titman’s momentum effects, suggesting that sentiment-driven price movements in crypto markets may create systematic momentum patterns that transmit to traditional asset classes.

Fama, E. F., & French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, 33(1), 3-56.

Chen’s identification of cryptocurrency as a systematic risk factor (explaining 18% of equity variance) suggests the need to extend the Fama-French factor model to include digital asset factors, as cryptocurrency appears to represent a new common risk factor affecting traditional asset returns.

Crisis and Financial Stability

Brunnermeier, M. K. (2009). Deciphering the Liquidity and Credit Crunch 2007-2008. Journal of Economic Perspectives, 23(1), 77-100.

Chen’s use of pandemic priors to handle COVID-19 disruptions builds on Brunnermeier’s crisis analysis methodology, while the finding that cryptocurrency markets maintained transmission mechanisms during the pandemic suggests they may be more resilient to liquidity crises than traditional markets.

Adrian, T., & Shin, H. S. (2010). Liquidity and Leverage. Journal of Financial Intermediation, 19(3), 418-437.

Chen’s evidence of financial stress reduction following positive cryptocurrency shocks provides a counterpoint to Adrian-Shin’s procyclical leverage framework, suggesting that cryptocurrency appreciation may actually improve rather than worsen financial intermediary balance sheets and leverage capacity.

Econometric Methodology

Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48.

Chen’s structural VAR approach builds directly on Sims’ foundational methodology while extending it to incorporate cryptocurrency variables and pandemic-specific econometric adjustments, demonstrating the continued relevance of VAR methods for analyzing emerging economic phenomena.

Stock, J. H., & Watson, M. W. (2001). Vector Autoregressions. Journal of Economic Perspectives, 15(4), 101-115.

Chen’s implementation of Bayesian VAR with pandemic priors represents a methodological advancement over Stock-Watson’s framework, showing how traditional VAR techniques can be adapted to handle extreme observations while preserving structural relationships during crisis periods.

Uhlig, H. (2005). What Are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure. Journal of Monetary Economics, 52(2), 381-419.

Chen’s recursive identification strategy could be complemented by Uhlig’s sign restriction approach, as the clear theoretical predictions about cryptocurrency transmission mechanisms provide natural candidates for sign restrictions that could validate or extend Chen’s identification results.

Innovation and Technology Economics

Schumpeter, J. A. (1942). Capitalism, Socialism and Democracy. Harper & Brothers.

Chen’s finding that technology shocks are significant drivers of cryptocurrency markets provides modern empirical validation of Schumpeterian innovation theory, demonstrating how technological developments create economic value that transmits through financial markets to affect real economic activity.

Arrow, K. J. (1962). The Economic Implications of Learning by Doing. Review of Economic Studies, 29(3), 155-173.

Chen’s identification of network effects in cryptocurrency markets relates to Arrow’s learning-by-doing framework, as the growth of cryptocurrency networks creates positive feedback loops that enhance utility and economic value, leading to broader macroeconomic transmission effects.

Development Economics and Financial Inclusion

Demirgüç-Kunt, A., Klapper, L., Singer, D., Ansar, S., & Hess, J. (2018). The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. World Bank Policy Research Working Paper.

Chen’s findings on cryptocurrency’s macroeconomic transmission mechanisms provide crucial evidence for understanding how digital financial innovations like those measured in the Global Findex can have economy-wide effects, suggesting that financial inclusion through cryptocurrency adoption may generate broader economic impacts than previously recognized.

Beck, T., Demirgüç-Kunt, A., & Levine, R. (2007). Finance, Inequality and the Poor. Journal of Economic Growth, 12(1), 27-49.

Chen’s identification of wealth effects from cryptocurrency appreciation offers a new perspective on Beck et al.’s finance-inequality relationship, as decentralized digital assets may provide alternative wealth accumulation channels that bypass traditional financial institutions, potentially affecting inequality through different transmission mechanisms.

Banerjee, A. V., & Duflo, E. (2014). Do Firms Want to Borrow More? Testing Credit Constraints Using a Directed Lending Program. Review of Economic Studies, 81(2), 572-607.

Chen’s evidence of improved financial stress indicators following cryptocurrency shocks suggests that digital asset appreciation may relax credit constraints similar to Banerjee-Duflo’s directed lending programs, providing an alternative mechanism for enhancing credit access in developing economies.

Morduch, J. (1999). The Microfinance Promise. Journal of Economic Literature, 37(4), 1569-1614.

Chen’s documentation of cryptocurrency’s real economic effects (industrial production, unemployment) provides macroeconomic validation for Morduch’s microfinance framework, suggesting that decentralized financial innovations may achieve similar development outcomes through different channels than traditional microfinance institutions.

Environmental and Energy Economics

de Vries, A. (2018). Bitcoin’s Growing Energy Problem. Joule, 2(5), 801-805.

Chen’s findings on cryptocurrency’s significant macroeconomic effects (18% of inflation variance) must be weighed against de Vries’ energy consumption analysis, creating important policy trade-offs between the documented economic benefits of cryptocurrency integration and environmental costs of energy-intensive mining operations.

Krugman, P. (2013). Bitcoin is Evil. New York Times.

Chen’s empirical evidence of cryptocurrency’s systematic economic importance directly challenges Krugman’s dismissive assessment, providing quantitative evidence that Bitcoin has achieved the scale and integration necessary to affect real economic variables, contradicting the view that it represents a wasteful energy sink.

Mora, C., Rollins, R. L., Taladay, K., et al. (2018). Bitcoin Emissions Alone Could Push Global Warming Above 2°C. Nature Climate Change, 8(11), 931-933.

Chen’s documentation of cryptocurrency’s macroeconomic transmission mechanisms adds complexity to Mora et al.’s climate analysis by demonstrating that cryptocurrency provides measurable economic benefits that must be considered alongside environmental costs in policy cost-benefit calculations.

Stoll, C., Klaaßen, L., & Gallersdörfer, U. (2019). The Carbon Footprint of Bitcoin. Joule, 3(7), 1647-1661.

Chen’s findings on cryptocurrency’s role in economic forecasting and monetary policy suggest that Stoll et al.’s carbon footprint analysis should incorporate the economic value of cryptocurrency’s contribution to financial stability and macroeconomic management when assessing net social costs.

Digital Economics and Platform Theory

Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform Revolution: How Networked Markets Are Transforming the Economy and How to Make Them Work for You. W. W. Norton & Company.

Chen’s identification of network effects as drivers of cryptocurrency shocks validates Parker et al.’s platform theory in the context of decentralized financial networks, demonstrating how network externalities in cryptocurrency ecosystems create macroeconomic transmission effects similar to traditional platform businesses.

Rochet, J. C., & Tirole, J. (2003). Platform Competition in Two-Sided Markets. Journal of the European Economic Association, 1(4), 990-1029.

Chen’s evidence of cryptocurrency’s financial market integration relates to Rochet-Tirole’s two-sided market framework, as cryptocurrency platforms facilitate interactions between different types of users (investors, developers, merchants) while creating economy-wide spillover effects through network growth.

Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company.

Chen’s findings on technology shocks as significant drivers of cryptocurrency markets provide empirical support for Brynjolfsson-McAfee’s digital transformation thesis, showing how technological innovations in blockchain systems create measurable macroeconomic effects through financial market channels.

Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs.

Chen’s analysis of cryptocurrency’s decentralized transmission mechanisms offers an alternative to Zuboff’s surveillance capitalism framework, suggesting that decentralized digital assets may provide economic value creation without the centralized data extraction that characterizes traditional digital platforms.

Labor Economics and Future of Work

Autor, D. H., Levy, F., & Murnane, R. J. (2003). The Skill Content of Recent Technological Change: An Empirical Exploration. Quarterly Journal of Economics, 118(4), 1279-1333.

Chen’s evidence of unemployment reduction following cryptocurrency shocks provides a new perspective on Autor et al.’s skill-biased technological change hypothesis, suggesting that blockchain technologies may create employment effects through financial wealth channels rather than direct skill substitution.

Acemoglu, D., & Restrepo, P. (2018). The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment. American Economic Review, 108(6), 1488-1542.

Chen’s findings on cryptocurrency’s real economic transmission complement Acemoglu-Restrepo’s automation analysis by showing how financial innovations create employment effects through aggregate demand channels, potentially offsetting job displacement from other technological changes.

Katz, L. F., & Krueger, A. B. (2019). The Rise and Nature of Alternative Work Arrangements in the United States, 1995-2015. ILR Review, 72(2), 382-416.

Chen’s documentation of cryptocurrency’s macroeconomic effects provides important context for Katz-Krueger’s gig economy analysis, as digital asset appreciation may affect the financial stability and economic security of alternative work arrangements through wealth and portfolio effects.

Frey, C. B., & Osborne, M. A. (2017). The Future of Employment: How Susceptible Are Jobs to Computerisation? Technological Forecasting and Social Change, 114, 254-280.

Chen’s evidence that cryptocurrency shocks affect unemployment through wealth rather than technological displacement channels offers a different perspective on Frey-Osborne’s automation concerns, suggesting that blockchain innovations may create employment through financial rather than technological mechanisms.

Urban Economics and Regional Development

Glaeser, E. L., & Gottlieb, J. D. (2009). The Wealth of Cities: Agglomeration Economies and Spatial Equilibrium in the United States. Journal of Economic Literature, 47(4), 983-1028.

Chen’s findings on cryptocurrency’s real economic effects could have important implications for Glaeser-Gottlieb’s urban agglomeration analysis, as cryptocurrency wealth concentration in specific geographic areas may affect local economic development and spatial equilibrium through the transmission mechanisms Chen identifies.

Moretti, E. (2012). The New Geography of Jobs. Houghton Mifflin Harcourt.

Chen’s evidence of cryptocurrency’s impact on industrial production and employment relates to Moretti’s analysis of innovation clusters, as blockchain industry development may create similar agglomeration effects and local economic spillovers through the macroeconomic channels Chen documents.

Autor, D., Dorn, D., & Hanson, G. (2013). The China Syndrome: Local Labor Market Effects of Import Competition in the United States. American Economic Review, 103(6), 2121-2168.

Chen’s methodology for identifying cryptocurrency transmission effects could be extended to analyze regional variation in cryptocurrency adoption, potentially providing insights into how digital asset markets affect local labor markets differently than the trade shocks analyzed by Autor-Dorn-Hanson.

Public Finance and Taxation

Mankiw, N. G., Weinzierl, M., & Yagan, D. (2009). Optimal Taxation in Theory and Practice. Journal of Economic Perspectives, 23(4), 147-174.

Chen’s findings on cryptocurrency’s macroeconomic importance raise questions about optimal taxation of digital assets, as the 18% contribution to inflation variance suggests that cryptocurrency taxation policies could have significant macroeconomic effects beyond traditional revenue considerations.

Saez, E., & Zucman, G. (2019). The Triumph of Injustice: How the Rich Dodge Taxes and How to Make Them Pay. W. W. Norton & Company.

Chen’s evidence of cryptocurrency wealth effects provides important context for Saez-Zucman’s wealth inequality analysis, as digital asset appreciation may represent a new form of wealth accumulation that requires consideration in progressive taxation frameworks.

Piketty, T. (2014). Capital in the Twenty-First Century. Harvard University Press.

Chen’s documentation of cryptocurrency as a new asset class with significant economic transmission effects adds complexity to Piketty’s r > g framework, as digital assets may represent a new form of capital that exhibits different accumulation dynamics than traditional assets.

Corporate Finance and Investment

Modigliani, F., & Miller, M. H. (1958). The Cost of Capital, Corporation Finance and the Theory of Investment. American Economic Review, 48(3), 261-297.

Chen’s findings on cryptocurrency’s effect on industrial production through investment channels relate to Modigliani-Miller’s capital structure theory, as cryptocurrency price movements may affect firms’ cost of capital and investment decisions through balance sheet effects and alternative financing mechanisms.

Myers, S. C., & Majluf, N. S. (1984). Corporate Financing and Investment Decisions When Firms Have Information That Investors Do Not Have. Journal of Financial Economics, 13(2), 187-221.

Chen’s evidence of cryptocurrency’s transmission to real economic activity through financial stress channels relates to Myers-Majluf’s pecking order theory, as cryptocurrency appreciation may provide alternative financing sources that affect firms’ capital structure decisions and investment timing.

Jensen, M. C. (1986). Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers. American Economic Review, 76(2), 323-329.

Chen’s documentation of cryptocurrency’s wealth effects on corporate investment relates to Jensen’s free cash flow hypothesis, as cryptocurrency appreciation may provide firms with additional financial resources that affect investment efficiency and agency relationships.

Insurance and Risk Management

Arrow, K. J. (1963). Uncertainty and the Welfare Economics of Medical Care. American Economic Review, 53(5), 941-973.

Chen’s findings on cryptocurrency’s role in financial stress reduction relate to Arrow’s analysis of uncertainty and insurance, as digital assets may provide portfolio diversification benefits that reduce systemic risk, though the transmission mechanisms Chen identifies suggest they may also create new sources of systematic risk.

Rothschild, M., & Stiglitz, J. (1976). Equilibrium in Competitive Insurance Markets: An Essay on the Economics of Imperfect Information. Quarterly Journal of Economics, 90(4), 629-649.

Chen’s evidence of cryptocurrency’s correlation with traditional financial markets challenges Rothschild-Stiglitz’s risk pooling framework, as the spillover effects Chen documents suggest that cryptocurrency may not provide the independent risk diversification that traditional insurance theory assumes.

Health Economics and Social Welfare

Grossman, M. (1972). On the Concept of Health Capital and the Demand for Health. Journal of Political Economy, 80(2), 223-255.

Chen’s methodology for analyzing cryptocurrency transmission effects could be extended to examine health impacts of financial stress reduction, as the improvement in financial conditions following cryptocurrency appreciation may affect health outcomes through the mechanisms Grossman identifies.

Case, A., & Deaton, A. (2015). Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century. Proceedings of the National Academy of Sciences, 112(49), 15078-15083.

Chen’s evidence of unemployment reduction following cryptocurrency shocks may relate to Case-Deaton’s analysis of mortality trends, as improved labor market conditions through cryptocurrency wealth effects could potentially affect health outcomes in affected populations.

Political Economy and Institutions

Acemoglu, D., & Robinson, J. A. (2012). Why Nations Fail: The Origins of Power, Prosperity, and Poverty. Crown Business.

Chen’s findings on cryptocurrency’s macroeconomic transmission raise important questions about Acemoglu-Robinson’s institutional framework, as decentralized digital assets may provide alternative economic development paths that operate independently of traditional extractive or inclusive political institutions.

North, D. C. (1990). Institutions, Institutional Change and Economic Performance. Cambridge University Press.

Chen’s evidence of cryptocurrency’s economic integration relates to North’s institutional analysis, as blockchain technologies represent new institutional arrangements for conducting economic transactions that may affect macroeconomic performance through the transmission mechanisms Chen identifies.

Olson, M. (1965). The Logic of Collective Action: Public Goods and the Theory of Groups. Harvard University Press.

Chen’s analysis of network effects in cryptocurrency markets relates to Olson’s collective action framework, as decentralized networks must overcome coordination problems to achieve the scale necessary for macroeconomic transmission effects, suggesting new solutions to collective action challenges.

Economic History and Long-term Development

Kindleberger, C. P. (1978). Manias, Panics, and Crashes: A History of Financial Crises. Basic Books.

Chen’s evidence of cryptocurrency’s sentiment-driven nature and financial market integration provides a modern case study for Kindleberger’s analysis of financial manias, though the persistent real economic effects Chen documents suggest cryptocurrency markets may exhibit different dynamics than historical bubbles.

Rajan, R. G., & Zingales, L. (2003). The Great Reversals: The Politics of Financial Development. Journal of Financial Economics, 69(1), 5-50.

Chen’s documentation of cryptocurrency’s role in financial development relates to Rajan-Zingales’ analysis of financial system evolution, as decentralized digital assets may represent a new form of financial development that operates independently of traditional political economy constraints.

Ferguson, N. (2008). The Ascent of Money: A Financial History of the World. Penguin Press.

Chen’s findings on cryptocurrency’s macroeconomic transmission provide a contemporary chapter for Ferguson’s financial history framework, demonstrating how new forms of money and financial innovation continue to shape economic development and macroeconomic relationships.

Game Theory and Mechanism Design

Myerson, R. B. (1991). Game Theory: Analysis of Conflict. Harvard University Press.

Chen’s analysis of cryptocurrency network effects relates to Myerson’s game theory framework, as the coordination required for cryptocurrency adoption and the resulting macroeconomic effects represent solutions to complex coordination games with multiple equilibria.

Hurwicz, L. (1973). The Design of Mechanisms for Resource Allocation. American Economic Review, 63(2), 1-30.

Chen’s evidence of cryptocurrency’s economic transmission relates to Hurwicz’s mechanism design theory, as blockchain protocols represent decentralized mechanisms for resource allocation that achieve macroeconomic effects without traditional centralized coordination.