## wpiea2021049-print-pdf - References

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### I. INTRODUCTION — context and motivation
- Regulatory reforms after the global financial crisis left banks with sizable capital buffers; the Bank of International Settlements estimated banks globally entered the COVID-19 crisis with roughly US$5 trillion of capital above their Pillar 1 regulatory requirements (Lewrick and others, 2020).
- Policymakers enacted a wide-ranging easing of regulatory measures in response to COVID-19; almost half of these financial regulation measures were prudential in nature and aimed to ensure credit flow and mitigate amplification effects from binding regulatory constraints.
- Prior literature emphasized effects of regulatory tightening, with relatively less understanding of easing; the COVID-19 response offers a unique opportunity to analyze regulatory easing effects.
- This study analyzes effects of regulatory easing (mainly prudential policy) on financial conditions during COVID-19 using an intraday event study framework focused on stock prices.
- Data assembly and sample:
  - Initial information from the Yale COVID-19 Policy Tracker (CFRT).
  - Sample restricted to isolated financial policy announcements (excluding announcements that are part of a package or occur within the same day as other policy announcements) and augmented with precise announcement hour.
  - This process identifies 240 financial policy announcements—regulatory and non-regulatory related—from 42 jurisdictions from February 1 and July 31, 2020.
  - Due to data limitations, only 26 jurisdictions are included in the analysis (see Section III in source).
- Rationale for intraday event study:
  - Stock prices are central to global financial conditions; efficient-markets/rational-expectations framework implies prices reflect new information at announcement time.
  - High-frequency (hourly) event study helps isolate announcements over narrow time windows, mitigating reverse causality and simultaneity concerns.
  - Controls include global and country-specific covariates, overlapping announcements, and systemic-jurisdiction announcements (China, Euro Area, Hong Kong S.A.R., Switzerland, United Kingdom, and United States).
- Theoretical considerations:
  - Regulatory relaxation can mitigate asset-price externalities and amplification from binding borrowing constraints by facilitating credit flow.
  - Effects depend on investor perceptions of risk-taking incentives: optimistic investors expect higher future cash flows from increased lending; pessimistic investors expect excessive risk-taking, higher leverage, weaker underwriting, and increased crash risk.
  - Historical evidence: Greenwood, Iverson, and Thesmar (2020) estimate business bankruptcies can be expected to increase by 140 percent relative to their 2019 level under COVID-19–related distress.

### Key empirical findings (summary)
- Intraday event study results:
  - News about regulatory easing led to a statistically significant reduction in financial sector stock returns in the hour immediately after the official announcement.
  - Excess returns for non-financial stocks increased following regulatory easing announcements.
  - The increase in non-financial returns was particularly larger in industries that depend more on bank credit, suggesting regulatory easing may have facilitated greater credit flow to the economy through banks.
  - Markets reacted negatively to announcements related to easier bank capital regulation and positively to those about liquidity regulation.
  - For liquidity-based regulations:
    - Effects on financial stock returns are negligible.
    - Positive effect on non-financial stocks is positive and significant.
  - Non-regulatory financial measures (e.g., asset purchases, government credit guarantees, emergency liquidity programs) did not have a statistically significant effect on equity valuations.
- PVAR and financial conditions analysis:
  - Impulse-response functions (IRFs) of financial condition indices (FCIs) to regulation policy announcements were constructed using a PVAR framework to assess economic significance beyond intraday windows.
  - Results are consistent with intraday analysis:
    - Easing of liquidity regulations supported FCIs.
    - Easing of capital regulations caused FCIs to tighten in a 30 day window following the announcement.
  - Effects of liquidity and capital announcements on FCIs were particularly large in emerging market economies.
- Interpretation:
  - Net effect of regulatory easing on financial conditions appears overall positive in the near term.
  - Market reactions signal tradeoffs down the road—consistent with expected increased risk-taking, deterioration in underwriting standards, or continued lending to zombie firms by financial sector firms.
  - Drop in equity returns is mostly associated with easing of capital-related prudential regulation.
  - Historical and theoretical literature suggests bank shareholders can gain from tighter capital regulation since higher capital forces banks to shift capital structure to equity; looser capital requirements can reduce equity valuations.

### II. EMPIRICAL STRATEGY — identification, variables, and estimations
- Identification strategy (three key elements):
  - Focus exclusively on isolated events—those that are neither part of a package nor within the same day of any other announcements. (Note: announcements of policy packages consisting of similar prudential measures are included.)
  - Utilize high-frequency hourly data with a narrow intraday window: one hour before and three hours after the announcement.
    - Inclusion of the one hour prior accounts for information already priced in by markets.
    - High-frequency identification mitigates reverse causality because prudential norms are unlikely to be adjusted in response to hourly stock price movements.
  - Tight event window makes it feasible to control for confounding external events; controls include overlapping announcements occurring at the same time in any other jurisdiction and all regulatory announcements from systemic jurisdictions.
- Dependent variable construction:
  - ExcessReturn_{i,c,t} = SectorReturn_{i,c,t} − MarketReturn_{c,t} ∀h
  - CumulativeExcessReturn_{i,c,t+h} = ExcessReturn_{i,c,t+h} − ExcessReturn_{i,c,t−1} ∀h
  - Sectoral returns use MSCI sectoral indices; sectoral focus is chosen to better capture effects on financial conditions than firm-level returns.
- Estimation method:
  - Event study implemented via Jordà (2005) local projections method to estimate cumulative excess stock return responses at various horizons.
  - Baseline specification:
    - CumulativeExcessReturn_{i,c,t+h} = β^{h} Announcement_{c,t} + δ^{h} X_{i,c,t} + α_{c,h} + γ_{i,t,h} + ε_{i,c,t+h} ∀h
  - Announcement_{c,t} is an event dummy equal to one at the hour of the announcement and zero otherwise; announcement hour is obtained by rounding the exact time stamp to the closest full hour.
  - X_{c,t} includes global and country-specific covariates:
    - Overlapping announcements occurring at the same time in any other jurisdiction.
    - All announcements on the same day occurring in systemic jurisdictions (China, Euro Area, Hong Kong S.A.R., Switzerland, United Kingdom, and United States).
    - Lagged return of the excess return measure.
  - Controls aim to ensure capture of domestic policy announcement effects and to mitigate mismeasurement due to confounding events.

### Policy implications and recommendations (as framed by the study)
- In designing a roadmap for roll-back of regulatory support:
  - Results could suggest rolling back capital-related regulations first to help rebuild buffers, once recovery is on a firm footing—this assumes symmetry in effects during tightening and easing.
  - Unwinding of regulatory easing should be done gradually to reduce the risk of a sudden tightening of financial conditions.
- Tradeoff highlighted:
  - Regulatory easing can improve near-term financial conditions and facilitate credit to non-financial firms, but may lower valuations of financial firms and raise concerns about future risk-taking and underwriting deterioration.
  - Policy composition matters: liquidity regulatory easing appears less detrimental to financial equity valuations while capital regulatory easing is associated with negative equity responses.

### Limitations and caveats noted
- High-frequency intraday event studies aid statistical identification but have limited scope beyond the observation window.
- Economic impact of regulatory actions is likely observed over longer horizons; strict exogeneity of regulation to market developments may be violated when analysis window goes beyond a day.
- Sample selection and data limitations:
  - Although 240 announcements from 42 jurisdictions were identified for February 1 to July 31, 2020, only 26 jurisdictions are included in the analysis due to data limitations.

*Source: wpiea2021049-print-pdf - References*

### Section V — robustness exercises using alternative equity return measures
- Robustness overview:
  - Section V performs robustness checks comprising:
    - expanding the sample to include jurisdictions with at least one non-financial industry stock market index;
    - using alternative measures of equity returns;
    - using bank-level stock returns instead of an aggregate financial sector index.
  - Conclusion: All the results remain broadly unchanged.
- Expanded sample (robustness A):
  - Expanded sample includes all jurisdictions with at least one non-financial industry sector index.
  - Findings:
    - The response of financial sector equity becomes more significant than in the baseline.
    - For non-financial industries, the response is considerably more limited on impact, and becomes negative one hour after the announcement—albeit not significantly.
    - Interpretation: Tradeoffs stemming from COVID-19 related financial regulations were more intense in jurisdictions with smaller and less liquid financial sectors.
- Alternative equity return measures (robustness B):
  - Alternative metrics considered:
    - equity prices measured in hourly percent changes;
    - a market model for abnormal returns where EquityReturn_i,t = α_t + β_i MarketReturn_i,t + ε_i,t and ε_i,t is the abnormal return.
  - Findings for hourly percent changes:
    - "equity prices, measures in hourly percent changes, declined by almost 2 percent in the hour after announcements of regulatory easing for financial sector firms."
    - In line with the baseline, equity prices for non-financial industries also significantly increase on impact.
  - Findings for the market-model abnormal returns:
    - Regulatory easing announcements lead to decline in abnormal returns in the hour after impact.
    - Estimates for the effect on abnormal returns of non-financial firms are very noisy, with very wide confidence bands, explained in part by large heterogeneity across industries and economies.
- Bank equity returns (robustness C):
  - Rationale: In some jurisdictions non-bank financial institutions materially contribute to financial sector indices; isolating banks tests whether bank stocks drive the aggregate result.
  - Finding:
    - The average response of banks’ excess stock return is very similar to the responses of the financial equity indices used in the baseline specification: a significant negative excess return one hour after the announcement.
    - Interpretation: Responses of financial sector equity indices were mainly driven by bank stock prices.
- Key quantitative robustness takeaways:
  - Equity prices (hourly percent changes): declined by almost 2 percent for financial sector firms one hour after regulatory easing announcements.
  - Market-model abnormal returns: regulatory easing announcements lead to declines in abnormal returns in the hour after impact, though non-financial abnormal-return estimates are noisy.
  - Bank-level results: negative excess returns for banks one hour after announcements are consistent with aggregate financial-index results.

*Source: Section V (Robustness) of wpiea2021049-print-pdf.*

### Selected methodological and literature references (as listed)
- Jordà, Òscar, 2005, “Estimation and inference of impulse responses by local projections,” American economic review, Vol. 95, No. 1, pp. 161–182.
- Lewrick, Ulf, Christian Schmieder, Jhuvesh Sobrun, and Elod Takats, 2020, “Releasing bank buffers to cushion the crisis-a quantitative assessment,” .
- Greenwood, Robin, Benjamin Iverson, and David Thesmar, 2020, “Sizing Corporate Restructuring in the COVID Crisis,” National Bureau of Economic Research, Vol. Working Paper 28104.
- Additional references on monetary policy, macroprudential policy, COVID-19 effects, asset prices, and econometric methods are listed in the source.

*Source: wpiea2021049-print-pdf - REFERENCES*

### References .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .

### wpiea2021049-print-pdf - References .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .

### I. INTRODUCTION — context and motivation
- Regulatory reforms after the global financial crisis left banks with sizable capital buffers; the Bank of International Settlements estimated banks globally entered the COVID-19 crisis with roughly US$5 trillion of capital above their Pillar 1 regulatory requirements (Lewrick and others, 2020).
- Policymakers enacted a wide-ranging easing of regulatory measures in response to COVID-19; almost half of these financial regulation measures were prudential in nature and aimed to ensure credit flow and mitigate amplification effects from binding regulatory constraints.
- Prior literature emphasized effects of regulatory tightening, with relatively less understanding of easing; the COVID-19 response offers a unique opportunity to analyze regulatory easing effects.
- This study analyzes effects of regulatory easing (mainly prudential policy) on financial conditions during COVID-19 using an intraday event study framework focused on stock prices.
- Data assembly and sample:
  - Initial information from the Yale COVID-19 Policy Tracker (CFRT).
  - Sample restricted to isolated financial policy announcements (excluding announcements that are part of a package or occur within the same day as other policy announcements) and augmented with precise announcement hour.
  - This process identifies 240 financial policy announcements—regulatory and non-regulatory related—from 42 jurisdictions from February 1 and July 31, 2020.
  - Due to data limitations, only 26 jurisdictions are included in the analysis (see Section III in source).
- Rationale for intraday event study:
  - Stock prices are central to global financial conditions; efficient-markets/rational-expectations framework implies prices reflect new information at announcement time.
  - High-frequency (hourly) event study helps isolate announcements over narrow time windows, mitigating reverse causality and simultaneity concerns.
  - Controls include global and country-specific covariates, overlapping announcements, and systemic-jurisdiction announcements (China, Euro Area, Hong Kong S.A.R., Switzerland, United Kingdom, and United States).
- Theoretical considerations:
  - Regulatory relaxation can mitigate asset-price externalities and amplification from binding borrowing constraints by facilitating credit flow.
  - Effects depend on investor perceptions of risk-taking incentives: optimistic investors expect higher future cash flows from increased lending; pessimistic investors expect excessive risk-taking, higher leverage, weaker underwriting, and increased crash risk.
  - Historical evidence: Greenwood, Iverson, and Thesmar (2020) estimate business bankruptcies can be expected to increase by 140 percent relative to their 2019 level under COVID-19–related distress.

### Key empirical findings (summary)
- Intraday event study results:
  - News about regulatory easing led to a statistically significant reduction in financial sector stock returns in the hour immediately after the official announcement.
  - Excess returns for non-financial stocks increased following regulatory easing announcements.
  - The increase in non-financial returns was particularly larger in industries that depend more on bank credit, suggesting regulatory easing may have facilitated greater credit flow to the economy through banks.
  - Markets reacted negatively to announcements related to easier bank capital regulation and positively to those about liquidity regulation.
  - For liquidity-based regulations:
    - Effects on financial stock returns are negligible.
    - Positive effect on non-financial stocks is positive and significant.
  - Non-regulatory financial measures (e.g., asset purchases, government credit guarantees, emergency liquidity programs) did not have a statistically significant effect on equity valuations.
- PVAR and financial conditions analysis:
  - To assess economic significance beyond intraday windows, impulse-response functions (IRFs) of financial condition indices (FCIs) to regulation policy announcements were constructed using a PVAR framework.
  - Results are consistent with intraday analysis:
    - Easing of liquidity regulations supported FCIs.
    - Easing of capital regulations caused FCIs to tighten in a 30 day window following the announcement.
  - Effects of liquidity and capital announcements on FCIs were particularly large in emerging market economies.
- Interpretation:
  - Net effect of regulatory easing on financial conditions appears overall positive in the near term.
  - Market reactions signal tradeoffs down the road—consistent with expected increased risk-taking, deterioration in underwriting standards, or continued lending to zombie firms by financial sector firms.
  - Drop in equity returns is mostly associated with easing of capital-related prudential regulation.
  - Historical and theoretical literature suggests bank shareholders can gain from tighter capital regulation since higher capital forces banks to shift capital structure to equity; looser capital requirements can reduce equity valuations.

### II. EMPIRICAL STRATEGY — identification, variables, and estimations
- Identification strategy (three key elements):
  - Focus exclusively on isolated events—those that are neither part of a package nor within the same day of any other announcements. (Note: announcements of policy packages consisting of similar prudential measures are included.)
  - Utilize high-frequency hourly data with a narrow intraday window: one hour before and three hours after the announcement.
    - Inclusion of the one hour prior accounts for information already priced in by markets.
    - High-frequency identification mitigates reverse causality because prudential norms are unlikely to be adjusted in response to hourly stock price movements.
  - Tight event window makes it feasible to control for confounding external events; controls include overlapping announcements occurring at the same time in any other jurisdiction and all regulatory announcements from systemic jurisdictions.
- Dependent variable construction:
  - ExcessReturn_{i,c,t} = SectorReturn_{i,c,t} − MarketReturn_{c,t} ∀h
  - CumulativeExcessReturn_{i,c,t+h} = ExcessReturn_{i,c,t+h} − ExcessReturn_{i,c,t−1} ∀h
  - Sectoral returns use MSCI sectoral indices; sectoral focus is chosen to better capture effects on financial conditions than firm-level returns.
- Estimation method:
  - Event study implemented via Jordà (2005) local projections method to estimate cumulative excess stock return responses at various horizons.
  - Baseline specification:
    - CumulativeExcessReturn_{i,c,t+h} = β^{h} Announcement_{c,t} + δ^{h} X_{i,c,t} + α_{c,h} + γ_{i,t,h} + ε_{i,c,t+h} ∀h
  - Announcement_{c,t} is an event dummy equal to one at the hour of the announcement and zero otherwise; announcement hour is obtained by rounding the exact time stamp to the closest full hour.
  - X_{c,t} includes global and country-specific covariates:
    - Overlapping announcements occurring at the same time in any other jurisdiction.
    - All announcements on the same day occurring in systemic jurisdictions (China, Euro Area, Hong Kong S.A.R., Switzerland, United Kingdom, and United States).
    - Lagged return of the excess return measure.
  - Controls aim to ensure capture of domestic policy announcement effects and to mitigate mismeasurement due to confounding events.

### Policy implications and recommendations (as framed by the study)
- In designing a roadmap for roll-back of regulatory support:
  - Results could suggest rolling back capital-related regulations first to help rebuild buffers, once recovery is on a firm footing—this assumes symmetry in effects during tightening and easing.
  - Unwinding of regulatory easing should be done gradually to reduce the risk of a sudden tightening of financial conditions.
- Tradeoff highlighted:
  - Regulatory easing can improve near-term financial conditions and facilitate credit to non-financial firms, but may lower valuations of financial firms and raise concerns about future risk-taking and underwriting deterioration.
  - Policy composition matters: liquidity regulatory easing appears less detrimental to financial equity valuations while capital regulatory easing is associated with negative equity responses.

### Limitations and caveats noted
- High-frequency intraday event studies aid statistical identification but have limited scope beyond the observation window.
- Economic impact of regulatory actions is likely observed over longer horizons; strict exogeneity of regulation to market developments may be violated when analysis window goes beyond a day.
- Sample selection and data limitations:
  - Although 240 announcements from 42 jurisdictions were identified for February 1 to July 31, 2020, only 26 jurisdictions are included in the analysis due to data limitations.

*Source: wpiea2021049-print-pdf - References .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . .*

### Section V presents robustness exercises using alternative equity return measures.

### wpiea2021049-print-pdf - Section V presents robustness exercises using alternative equity return measures.

### Robustness overview
- Section V performs robustness checks comprising:
  - expanding the sample to include jurisdictions with at least one non-financial industry stock market index;
  - using alternative measures of equity returns;
  - using bank-level stock returns instead of an aggregate financial sector index.
- Conclusion: All the results remain broadly unchanged.

### Expanded sample (robustness A)
- Expanded sample includes all jurisdictions with at least one non-financial industry sector index.
- Findings:
  - The response of financial sector equity becomes more significant than in the baseline.
  - For non-financial industries, the response is considerably more limited on impact, and becomes negative one hour after the announcement—albeit not significantly.
  - Interpretation: Tradeoffs stemming from COVID-19 related financial regulations were more intense in jurisdictions with smaller and less liquid financial sectors.

### Alternative equity return measures (robustness B)
- Alternative metrics considered:
  - equity prices measured in hourly percent changes;
  - a market model for abnormal returns where EquityReturn_i,t = α_t + β_i MarketReturn_i,t + ε_i,t and ε_i,t is the abnormal return.
- Findings for hourly percent changes:
  - "equity prices, measures in hourly percent changes, declined by almost 2 percent in the hour after announcements of regulatory easing for financial sector firms."
  - In line with the baseline, equity prices for non-financial industries also significantly increase on impact.
- Findings for the market-model abnormal returns:
  - Regulatory easing announcements lead to decline in abnormal returns in the hour after impact.
  - Estimates for the effect on abnormal returns of non-financial firms are very noisy, with very wide confidence bands, explained in part by large heterogeneity across industries and economies.

### Bank equity returns (robustness C)
- Rationale: In some jurisdictions non-bank financial institutions materially contribute to financial sector indices; isolating banks tests whether bank stocks drive the aggregate result.
- Finding:
  - The average response of banks’ excess stock return is very similar to the responses of the financial equity indices used in the baseline specification: a significant negative excess return one hour after the announcement.
  - Interpretation: Responses of financial sector equity indices were mainly driven by bank stock prices.

### Key quantitative robustness takeaways
- Equity prices (hourly percent changes): declined by almost 2 percent for financial sector firms one hour after regulatory easing announcements.
- Market-model abnormal returns: regulatory easing announcements lead to declines in abnormal returns in the hour after impact, though non-financial abnormal-return estimates are noisy.
- Bank-level results: negative excess returns for banks one hour after announcements are consistent with aggregate financial-index results.

*Source: Section V (Robustness) of wpiea2021049-print-pdf.*

### REFERENCES

### REFERENCES

### Monetary policy, central banking, and communication
- Adrian, Tobias, and Nellie Liang, 2018, “Monetary Policy, Financial Conditions, and Financial Stability,”International Journal of Central Banking, Vol. 14(1), pp. 73–131.
- Cieslak, Anna, and Andreas Schrimpf, 2019, “Non-monetary news in central bank communication,”Journal of International Economics, Vol. 118, pp. 293–315.
- Gürkaynak, Refet S, Brian Sack, and Eric T Swanson, 2005, “Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements,” International Journal of Central Banking.
- Huang, Qiubin, Jakob de Haan, and Bert Scholtens, 2020, “Does bank capitalization matter for bank stock returns?”The North American Journal of Economics and Finance, Vol. 52, p. 101171.
- Arslan, Yavuz, Mathias Drehmann, and Boris Hofmann, 2020, “Central bank bond purchases in emerging market economies,” Techn. rep., Bank for International Settlements.

### Banking sector performance, capitalization, and regulatory responses
- Berger, Allen N, and Christa HS Bouwman, 2013, “How does capital affect bank performance during financial crises?”Journal of Financial Economics, Vol. 109, No. 1, pp. 146–176.
- Huang, Qiubin, Jakob de Haan, and Bert Scholtens, 2020, “Does bank capitalization matter for bank stock returns?”The North American Journal of Economics and Finance, Vol. 52, p. 101171.
- Demirgüç-Kunt, Asli, Alvaro Pedraza, and Claudia Ruiz-Ortega, 2020, “Banking sector performance during the covid-19 crisis,”The World Bank.
- Lewrick, Ulf, Christian Schmieder, Jhuvesh Sobrun, and Elod Takats, 2020, “Releasing bank buffers to cushion the crisis-a quantitative assessment,” .
- Narain, Aditya, Nigel Jenkinson, Alfonso Garcia Mora, Yira J Mascaro, Dirk Jan Grolleman, and Hee Kyong Chon, 2020, “COVID-19: The Regulatory and Supervisory Implications for the Banking Sector,”Joint IMF-World Bank Staff Position Note.
- IMF, 2020a, “Banking Sector: Low Rates, Low Profits?”Global Financial Stability Report, Vol. April.
- IMF, 2020b, “Financial Conditions Have Eased, but Insolvencies Loom Large,”Global Financial Stability Report Update, Vol. June.

### Macroprudential policy, credit cycles, and crisis management
- Araujo, Juliana Dutra, Manasa Patnam, Adina Popescu, Fabian Valencia, and Weijia Yao, 2020, “Effects of Macroprudential Policy: Evidence from Over 6,000 Estimates,”IMF Working Paper No. 20/67.
- Bianchi, Javier, and Enrique G. Mendoza, 2018, “Optimal Time-Consistent Macroprudential Policy,”Journal of Political Economy, Vol. 126.
- Jeanne, Olivier, and Anton Korinek, 2010, “Managing Credit Booms and Busts: A Pigouvian Taxation Approach,”NBER, Vol. Working Paper no. 16377, pp. Cambridge, MA.
- Cappelletti, Giuseppe, Aurea Ponte Marques, Carmelo Salleo, and Diego Vila Martin, 2020, “How do banking groups react to macroprudential policies? Cross-border spillover effects of higher capital buffers on lending, risk-taking and internal markets,”Eurpean Central Bank Working Paper Series.
- Lewrick, Ulf, Christian Schmieder, Jhuvesh Sobrun, and Elod Takats, 2020, “Releasing bank buffers to cushion the crisis-a quantitative assessment,” .

### COVID-19 economic effects and policy responses
- Altavilla, Carlo, Francesca Barbiero, Miguel Boucinha, and Lorenzo Burlon, 2020, “The great lockdown: pandemic response policies and bank lending conditions,”CEPR Discussion Paper No. DP15298.
- Gormsen, Niels Joachim, and Ralph SJ Koijen, 2020, “Coronavirus: Impact on stock prices and growth expectations,”University of Chicago, Becker Friedman Institute for Economics Working Paper No.2020-22.
- Greenwood, Robin, Benjamin Iverson, and David Thesmar, 2020, “Sizing Corporate Restructuring in the COVID Crisis,”National Bureau of Economic Research, Vol. Working Paper 28104.
- Sever, Can, Dimitris Drakopoulos, Rohit Goel, and Evan Papageorgiou, 2020, “Effects of Emerging Market Asset Purchase Program Announcements on Financial Markets During the COVID-19 Pandemic,”IMF Working Paper, forthcoming.
- Demirgüç-Kunt, Asli, Alvaro Pedraza, and Claudia Ruiz-Ortega, 2020, “Banking sector performance during the covid-19 crisis,”The World Bank.
- Narain, Aditya, Nigel Jenkinson, Alfonso Garcia Mora, Yira J Mascaro, Dirk Jan Grolleman, and Hee Kyong Chon, 2020, “COVID-19: The Regulatory and Supervisory Implications for the Banking Sector,”Joint IMF-World Bank Staff Position Note.

### Asset prices, stock returns, and market reactions
- Gandhi, Priyank, 2018, “The relation between bank credit growth and the expected returns of bank stocks,”European Financial Management, Vol. 24, No. 4, pp. 610–649.
- Baron, Matthew, and Wei Xiong, 2017, “Credit expansion and neglected crash risk,”The Quarterly Journal of Economics, Vol. 132, No. 2, pp. 713–764.
- Gormsen, Niels Joachim, and Ralph SJ Koijen, 2020, “Coronavirus: Impact on stock prices and growth expectations,”University of Chicago, Becker Friedman Institute for Economics Working Paper No.2020-22.
- Cieslak, Anna, and Andreas Schrimpf, 2019, “Non-monetary news in central bank communication,”Journal of International Economics, Vol. 118, pp. 293–315.
- Gürkaynak, Refet S, Brian Sack, and Eric T Swanson, 2005, “Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements,” International Journal of Central Banking.

### Macroeconomic models, credit constraints, and theoretical foundations
- Brunnermeier, Markus K., and Yuliy Sannikov, 2014, “A Macroeconomic Model with a Financial Sector,”American Economic Review, Vol. 104, pp. 379–421.
- Kiyotaki, Nobuhiro, and John Moore, 1997, “Credit Cycles,”Journal of Political Economy, Vol. 105, pp. 211–48.
- Bernanke, Ben, and Mark Gertler, 1989, “Agency Costs, Net Worth, and Business Fluctuations,”American Economic Review, Vol. 79, pp. 14–31.
- Mendoza, Enrique G., 2010, “Sudden Stops, Financial Crises, and Leverage,”American Economic Review, Vol. 100, pp. 1941–66.
- Elenev, Vadim, Tim Landvoigt, and Stijn Van Nieuwerburgh, Forthcoming, “A Macroeconomic Model With Financially Constrained Producers and Intermediaries,”Econometrica.
- Burnside, C., M. Eichenbaum, and J. Fisher, 2004, “Fiscal Shocks and Their Consequences,”Journal of Economic Theory, Vol. 115, pp. 89–117.

### Econometric methods and inference
- Jordà, Òscar, 2005, “Estimation and inference of impulse responses by local projections,” American economic review, Vol. 95, No. 1, pp. 161–182.
- Montiel Olea, Jose L., and Mikkel Palgborg-Møller, 2020, “Local Projection Inference is Simpler and More Robust Than You Think,” .
- Driscoll, John C, and Aart C Kraay, 1998, “Consistent covariance matrix estimation with spatially dependent panel data,”Review of economics and statistics, Vol. 80, No. 4, pp. 549–566.
- Runkle, David E, 1987, “Vector autoregressions and reality,”Journal of Business & Economic Statistics, Vol. 5, No. 4, pp. 437–442.

### Market efficiency, price theory, and regulation effects
- Fama, Eugene F, 1970, “Efficient capital markets: A review of theory and empirical work,” The journal of Finance, Vol. 25, No. 2, pp. 383–417.
- Muth, John F, 1961, “Rational expectations and the theory of price movements,”Econometrica: Journal of the Econometric Society, pp. 315–335.
- Schwert, G William, 1981, “Using financial data to measure effects of regulation,”The Journal of Law and Economics, Vol. 24, No. 1, pp. 121–158.
- Sever, Can, Dimitris Drakopoulos, Rohit Goel, and Evan Papageorgiou, 2020, “Effects of Emerging Market Asset Purchase Program Announcements on Financial Markets During the COVID-19 Pandemic,”IMF Working Paper, forthcoming.

### Exchange rates, external vulnerabilities, and sovereign exposure
- Towbin, Pascal, and Sebastian Weber, 2013, “Limits of floating exchange rates: The role of foreign currency debt and import structure,”Journal of Development Economics, Vol. 101, pp. 179–194.

*Content from wpiea2021049-print-pdf - REFERENCES*

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_Source: https://www.imf.org/-/media/files/publications/wp/2021/english/wpiea2021049-print-pdf.pdf_