Research articles for the 2021-01-26

A Certainty Equivalent Merton Problem
Nicholas Moehle,Stephen Boyd

The Merton problem is the well-known stochastic control problem of choosing consumption over time, as well as an investment mix, to maximize expected constant relative risk aversion (CRRA) utility of consumption. Merton formulated the problem and provided an analytical solution in 1970; since then a number of extensions of the original formulation have been solved. In this note we identify a certainty equivalent problem, i.e., a deterministic optimal control problem with the same optimal value function and optimal policy, for the base Merton problem, as well as a number of extensions. When time is discretized, the certainty equivalent problem becomes a second-order cone program (SOCP), readily formulated and solved using domain specific languages for convex optimization. This makes it a good starting point for model predictive control, a policy that can handle extensions that are either too cumbersome or impossible to handle exactly using standard dynamic programming methods.

A comprehensive theoretical analysis of soccer penalty shootout designs
László Csató,Dóra Gréta Petróczy

The standard rule of soccer penalty shootouts has received serious criticism due to its bias towards the team kicking the first penalty in each round. Therefore, the rule-making body of the sport has decided in 2017 to try alternative designs. This paper offers an extensive overview of eight penalty shootout mechanisms, one of them first introduced here. Their fairness is analysed under three possible mathematical models of psychological pressure. We also discuss the probability of reaching the sudden death stage, as well as the complexity and strategy-proofness of the rules. In the case of stationary scoring probabilities considered here, it remains sufficient to use static rules in order to improve fairness. However, it is worth compensating the second-mover by making it first-mover in the sudden death stage. Our work has the potential to impact decision-makers who can save valuable resources by choosing only theoretically competitive policy options for field experiments.

Absolute Value Constraint: The Reason for Invalid Performance Evaluation Results of Neural Network Models for Stock Price Prediction
Yi Wei,Cristian Tiu,Vipin Chaudhary

Neural networks for stock price prediction(NNSPP) have been popular for decades. However, most of its study results remain in the research paper and cannot truly play a role in the securities market. One of the main reasons leading to this situation is that the prediction error(PE) based evaluation results have statistical flaws. Its prediction results cannot represent the most critical financial direction attributes. So it cannot provide investors with convincing, interpretable, and consistent model performance evaluation results for practical applications in the securities market. To illustrate, we have used data selected from 20 stock datasets over six years from the Shanghai and Shenzhen stock market in China, and 20 stock datasets from NASDAQ and NYSE in the USA. We implement six shallow and deep neural networks to predict stock prices and use four prediction error measures for evaluation. The results show that the prediction error value only partially reflects the model accuracy of the stock price prediction, and cannot reflect the change in the direction of the model predicted stock price. This characteristic determines that PE is not suitable as an evaluation indicator of NNSPP. Otherwise, it will bring huge potential risks to investors. Therefore, this paper establishes an experiment platform to confirm that the PE method is not suitable for the NNSPP evaluation, and provides a theoretical basis for the necessity of creating a new NNSPP evaluation method in the future.

Asymmetric Solutions to Asymmetric Information Problems
Dari‐Mattiacci, Giuseppe,Onderstal, Sander,Parisi, Francesco
This paper studies markets plagued with asymmetric information on the quality of traded goods. In Akerlof’s setting, sellers are better informed than buyers. In contrast, we examine cases where buyers are better informed than sellers. This creates an inverse adverse selection problem: the market tends to disappear from the bottom rather than from the top. In contrast to the traditional model, it is the high-value goods (gems) that are traded on the market, rather than the low-value goods (lemons). We refer to this asymmetric information scenario as the “market for gems.” We investigate the consequences of this undisclosed knowledge of hidden qualities â€" which we refer to as inverse adverse selection â€" and the reasons why legal theorists have given this form of asymmetric information substantially less consideration. Conventional legal and contractual solutions to the lemons problem are often ineffective in the gems case: the uninformed buyer in a traditional market for lemons experiences the quality of the good he purchased; in a market for gems, instead, the uninformed seller may never know the quality of the good that he sold. We study three alternative solutions to the gems problem â€" auctions, suppression of information, and inverse warranties â€" and identify the condition under which each of them is feasible. We then show how the theory sheds light on real-life gems problems arising in the multi-million dollar transactions involving soccer players, artworks, M&As, Hollywood movies, and diamonds.

Commercial Real Estate Prices and Covid-19
Hoesli, Martin,Malle, Richard
The article analyzes the effects of the Covid-19 pandemic on commercial real estate prices. We start by highlighting caveats to bear in mind when referring to direct real estate indices. We then analyze the behavior of commercial real estate prices during the pandemic, emphasizing differences across property types. For that purpose, we use data for both direct and listed real estate. We further discuss changes in the main factors affecting commercial real estate pricing. The article then turns to discussing the likely trajectory of commercial real estate prices in the future. We report that retail and hospitality properties and to a lesser extent office buildings have been affected the most by Covid-19. The other sectors, in particular the residential and industrial sectors, have shown more resilience. We maintain that the future trajectory of real estate prices will vary across sectors and that the type and location of assets will become increasingly important in their valuation.

Communication and Social Preferences: An Experimental Analysis
Cabrales, Antonio,Feri, Francesco,Gottardi, Piero,Meléndez-Jiménez, Miguel
This paper reports on experiments regarding cheap talk games where senders attempt deception when their interests are not in conflict with those of the receiver. The amount of miscommunication is higher than in previous experimental findings on cheap talk games in situations where senders’ and receivers’ interests are not in conflict. We obtain this even though, as in previous literature, some participants appear to feature a cost of lying. We argue our findings could be attributed to distributional preferences of senders who lie to avoid the receiver getting a higher payoff than herself.

Confidence as a Driver of Private Investment in Selected Countries of Central America
Janada, Carlos,Ruxandra Teodoru, Iulia
This paper argues that structural weaknesses may make private investment particularly sensitive to business confidence relative to other traditional investment drivers and global shocks. It gauges the importance of confidence over recent years in selected countries in Central America, including Costa Rica, the Dominican Republic, El Salvador, and Guatemala. Using a vector error correction model to carry out the empirical work, a system representing global activity and the domestic economy, including a set of investment drivers (interest rates, unit labor costs, and confidence) is analyzed. The findings suggest that confidence has been, on average, the most important driver of investment in these countries, exceeded only by global factors. Since confidence, arguably, can be influenced by policymakers' decisions, structural reforms to improve the business climate and reduce uncertainty play an important role in promoting investment and economic growth.

Contagion of Fear: Is the Impact of COVID-19 on Sovereign Risk Really Indiscriminate?
Cevik, Serhan,Ozturkkal, Belma
This paper investigates the impact of infectious diseases on the evolution of sovereign credit default swap (CDS) spreads for a panel of 77 advanced and developing countries. Using annual data over the 2004-2020 period, we find that infectious-disease outbreaks have no discernible effect on CDS spreads, after controlling for macroeconomic and institutional factors. However, our granular analysis using high-frequency (daily) data indicates that the COVID-19 pandemic has had a significant impact on market-implied sovereign default risk. This adverse effect appears to be more pronounced in advanced economies, which may reflect the greater severity of the pandemic and depth of the ensuing economic crisis in these countries as well as widespread underreporting in developing countries due to differences in testing availability and institutional capacity. While our analysis also shows that more stringent domestic containment measures help lower sovereign CDS spreads, the macro-fiscal cost of efforts aimed at curbing the spread of the disease could undermine credit worthiness and eventually push the cost of borrowing higher.

Crossing the Credit Channel: Credit Spreads and Firm Heterogeneity
Anderson, Gareth,Cesa-Bianchi, Ambrogio
Credit spreads rise after a monetary policy tightening, yet spread reactions are heterogeneous across firms. Exploiting information from a panel of corporate bonds matched with balance sheet data for U.S. non-financial firms, we document that firms with high leverage experience a more pronounced increase in credit spreads than firms with low leverage. A large fraction of this increase is due to a component of credit spreads that is in excess of firms' expected default. Our results suggest that frictions in the financial intermediation sector play a crucial role in shaping the transmission mechanism of monetary policy.

Debt Buildup and Currency Vulnerability: Evidence from Global Markets
Park, Donghyun,Ramayandi, Arief,Tian, Grace
In this study, we examine how public and private debt buildup is related to currency depreciation pressure. Our empirical analysis of a panel dataset of 59 advanced and emerging markets reveals that both private and public debt exacerbate currency vulnerability. However, the evidence of a significant effect on currency depreciation pressure is more robust and consistent for private debt than public debt. Furthermore, we find that excessive private debt buildup can be particularly harmful in emerging markets. In addition, our evidence suggests that greater dependence on external financing exacerbates the impact of debt buildup on currency stress. Overall, the evidence highlights the importance of a comprehensive debt surveillance framework which monitors both public and private debt buildup, especially in emerging markets.

Effects of Emerging Market Asset Purchase Program Announcements on Financial Markets During the COVID-19 Pandemic
Sever, Can,Goel, Rohit,Drakopoulos, Dimitrios,Papageorgiou, Evan
The COVID-19 pandemic led many emerging market central banks to adopt, for the first time, unconventional policies in the form of asset purchase programs. In this study, we analyze the effects of these announcements on domestic financial markets using both event studies and local projections methodology. We find that these asset purchase announcements lowered bond yields, did not lead to a depreciation of domestic currencies, and did not have much effect on equities. While the immediate effect of asset purchases appears positive, further consideration of the risks and longer-term effects of unconventional monetary policies is needed. We highlight the trade-offs involved with the implementation of these measures, and discuss their risks. This working paper adds to the debate on how asset purchase programs should be a regular part of the emerging market policy toolkit.

Estimation of future discretionary benefits in traditional life insurance
Florian Gach,Simon Hochgerner

In the context of traditional life insurance, the future discretionary benefits ($FDB$), which are a central item for Solvency~II reporting, are generally calculated by computationally expensive Monte Carlo algorithms. We derive analytic formulas for lower and upper bounds for the $FDB$. This yields an estimation interval for the $FDB$, and the average of lower and upper bound is a simple estimator. These formulae are designed for real world applications, and we compare the results to publicly available reporting data.

Exploring the Complicated Relationship Between Patents and Standards, With a Particular Focus on the Telecommunications Sector
Nikolaos Athanasios Anagnostopoulos

While patents and standards have been identified as essential driving components of innovation and market growth, the inclusion of a patent in a standard poses many difficulties. These difficulties arise from the contradicting natures of patents and standards, which makes their combination really challenging, but, also, from the opposing business and market strategies of different patent owners involved in the standardisation process. However, a varying set of policies has been adopted to address the issues occurring from the unavoidable inclusion of patents in standards concerning certain industry sectors with a constant high degree of innovation, such as telecommunications. As these policies have not always proven adequate enough, constant efforts are being made to improve and expand them. The intriguing and complicated relationship between patents and standards is finally examined through a review of the use cases of well-known standards of the telecommunications sector which include a growing set of essential patents.

Feeling the Heat: Climate Shocks and Credit Ratings
Cevik, Serhan,Jalles, João Tovar
Climate change is an existential threat to the world economy like no other, with complex, evolving and nonlinear dynamics that remain a source of great uncertainty. There is a bourgeoning literature on the economic impact of climate change, but research on how climate change affects sovereign risks is limited. Building on our previous research focusing on the impact of climate change on sovereign risks, this paper empirically investigates how climate change may affect sovereign credit ratings. By means of binary-choice models, we find that climate change vulnerability has adverse effects on sovereign credit ratings, after controlling for conventional macroeconomic determinants of credit worthiness. On the other hand, with regards to climate change resilience, we find that countries with greater climate change resilience benefit from higher (better) credit ratings. These findings, robust to a battery of sensitivity checks, also show that impact of climate change is disproportionately greater in developing countries due largely to weaker capacity to adapt to and mitigate the consequences of climate change.

Financial Banking Performance in January - November 2020
Zubov, Sergey
Due to the epidemiological situation, the structure and dynamics of financial performance in the banking sector have experienced changes. Amid declining margins, instability of financial markets and the unstable position of borrowers, the Russian credit institutions were forced to significantly adjust their market strategies. This resulted in a decrease of profitability of the banking system compared to the previous year.

Financial Markets in 2020: Preliminary Outcomes
Abramov, Alexander E.,Chernova, Maria,Kosyrev, Andrey,Radygin, Alexander
Despite the pandemic and economic fallout, the year 2020 can be regarded as quite successful for a host of financial markets in terms of appreciation of various currencies against the US Dollar and equity indices’ positive yield. The Russian ruble was among the weakest currencies and the RTS index yield was negative. With the Russian ruble and Russian companies’ equities being undervalued in 2020, one can expect the strengthening of the Russian national currency and equities’ positive rate of return in 2021.Stimulus measures implemented by a host of countries have been instrumental in mitigating the pandemic’s implications and hold out a hope of growth revival in 2021. However, after the pandemic most major economies will face the challenge of raising their global competitive edge and carrying out structural reforms. As seen from China’s experience, in dealing with the specified challenges they give preference explicitly to the idea of the state’s greater interference into the economy. It remains to be seen to what extent such a policy is effective and needed in other countries.

Government Insurance Against Natural Disasters: An Application to the ECCU
Guerson, Alejandro
This paper estimates insurance requirements against natural disasters (NDs) in the Eastern Caribbean Currency Union (ECCU) using an insurance layering framework. The layers include a government saving fund, as well as market instruments. Each layer is calibrated to cover estimated fiscal cost of NDs according to intensity and expected damage. The results indicate that ECCU countries could target saving fund stocks for relativelly smaller and more frequent events in the range of 6-12 percent of GDP, enough to cover 95 percent of NDs' fiscal costs. To ensure financially-sustainable saving funds with a low probability of depletion, this requires annual budget savings in the range os 0.5 to 1.9 percent of GDP per year. Additional coverage could be obtained with market instruments for large and less frequent events, albeit at a significant cost.The results are based on a Monte-Carlo experiment that simulates natural disaster shocks and their impact on output and government finances.

Government Intervention and Bank Market Power: Lessons from the Global Financial Crisis for the COVID-19 Crisis
Tan, Brandon,Igan, Deniz,Martinez Peria, Maria Soledad,Pierri, Nicola,Presbitero, Andrea
The COVID-19 pandemic could result in large government interventions in the banking industry. To shed light on the possible consequences on market power, we rely on the experience of the global financial crisis and exploit granular data on government interventions in more than 800 banks across 27 countries between 2007 and 2017. For identification, we use a multivariate matching method. We find that intervened banks experience a significant decline in market power with respect to matched non-intervened banks. This effect is more pronounced for larger and longer interventions and is driven by a rise in costs-mostly because of higher loan impairment charges-which is not followed by a similar increase in prices.

Hang in There: Stock Market Reactions to Withdrawals of COVID-19 Stimulus Measures
Chan-Lau, Jorge A.,Zhao, Yunhui
The COVID-19 pandemic prompted unprecedented economic stimulus worldwide. We empirically examine the impact of a withdrawal of fiscal stimulus policies on the stock markets. After constructing a database of withdrawal events, we use event study analysis and cross-country regressions to assess the difference between the pre- and post-event stock price returns. We find that markets react negatively to premature withdrawals-defined as withdrawals at a time when the daily COVID cases are high relative to their historical average-likely reflecting concerns about the withdrawal impact on the prospects for economic recovery. The design of a successful exit strategy from COVID-19 policy responses should account for these concerns.

Hedging Demand and Market Intraday Momentum
Baltussen, Guido,Da, Zhi,Lammers, Sten,Martens, Martin
edging short gamma exposure requires trading in the direction of price movements,thereby creating price momentum. Using intraday returns on over 60 futures on equities,bonds, commodities, and currencies between 1974 and 2020, we document strong “marketintraday momentum” everywhere. The return during the last 30 minutes before the marketclose is positively predicted by the return during the rest of the day (from previous marketclose to the last 30 minutes). The predictive power is economically and statistically highlysignificant, and reverts over the next days. We provide novel evidence that links marketintraday momentum to the gamma hedging demand from market participants such as marketmakers of options and leveraged ETFs.

House Prices and Macroprudential Policies: Evidence from City-Level Data in India
Singh, Bhupal
This paper examines the efficacy of macroprudential policies in addressing housing prices in a developing country while underscoring the importance of fundamental factors. The estimated models using city-level data for India suggest a strong influence of fundamental factors in driving housing prices. There is compelling evidence of the effectiveness of macroprudential tools viz., Loan-to-value (LTV) ratio, risk weights, and provisioning requirements, in influencing housing price movements. A granular analysis suggests an even stronger impact on housing prices of a change in the regulatory LTV ratio for large-sized visà-vis small-sized mortgages, which buttresses their potency in fighting house price speculations. A tightening of the risk weights on the housing assets of banks causes significant downward pressure on house prices. Similarly, regulatory changes in standard asset provisioning on housing loans also influence house prices.

How COVID-19 influences healthcare workers' happiness: Panel data analysis in Japan
Eiji Yamamura,Yoshiro Tsutsui

Healthcare workers are more likely to be infected with the 2019 novel coronavirus (COVID-19) because of unavoidable contact with infected people. Although they are equipped to reduce the likelihood of infection, their distress has increased. This study examines how COVID-19 influences healthcare workers' happiness, compared to other workers. We constructed panel data via Internet surveys during the COVID-19 epidemic in Japan, from March to June 2020, by surveying the same respondents at different times. The survey period started before the state of emergency, and ended after deregulation. The key findings are as follows. (1) Overall, the happiness level of healthcare workers is lower than that of other workers. (2) The biggest disparity in happiness level, between healthcare workers and others, was observed after deregulation and not during the state of emergency. After deregulation, the difference was larger by 0.26 points, on an 11-point scale, than in the initial wave before the state of emergency.

Identifying Reform Priorities: The Role of Non-Linearities
Hellwig, Klaus-Peter
Can countries improve their business climate through reforms in specific policy areas? Kraay and Tawara (2013) find that the answer depends on how we measure the business climate. When regressing seven different business climate indices on 38 policy indicators, they find little agreement among the seven models as to which of those policy indicators matter most. I revisit this puzzle using the same data but replacing their linear models with a Random Forest algorithm. I find a strong consensus across models on the importance ranking of policy indicators: No matter which business climate index is considered, the top ten contributors to a better business climate always include high recovery rates in insolvency proceedings (i.e., cents on the dollar for creditors), shorter border formalities for both importers and exporters, and low costs for starting a business. I show that the marginal effect of reforms is heterogeneous across countries and document how reform priorities depend on country specific circumstances.

Identifying and Estimating Perceived Returns to Binary Investments
Clint Harris

I describe a method for estimating agents' perceived returns to investments that relies on cross-sectional data containing binary choices and prices, where prices may be imperfectly known to agents. This method identifies the scale of perceived returns by assuming agent knowledge of an identity that relates profits, revenues, and costs rather than by eliciting or assuming agent beliefs about structural parameters that are estimated by researchers. With this assumption, modest adjustments to standard binary choice estimators enable consistent estimation of perceived returns when using price instruments that are uncorrelated with unobserved determinants of agents' price misperceptions as well as other unobserved determinants of their perceived returns. I demonstrate the method, and the importance of using price variation that is known to agents, in a series of data simulations.

Incomplete Financial Markets and the Booming Housing Sector in China
Bayoumi, Tamim,Zhao, Yunhui
Housing is by far the most important asset in Chinese households' balance sheets. However, despite forceful and frequent government interventions, the rise in Chinese housing prices has not been contained as much as intended, a trend that has not been reversed by the COVID-19 shock. In this paper, we first provide some stylized facts and then a DSGE model (encompassing both demand and supply channels) to highlight the impact of a 'slow-moving' structural vulnerability-financial market incompleteness-on China's housing prices. The model implies that to eradicate the root causes of the rising housing price, policymakers need to go beyond the housing market itself; instead, it would be desirable to deepen financial markets because these markets would help channel financial resources to productive sectors rather than to housing speculation. This is particularly important in the COVID era because without addressing this structural vulnerability, the higher household savings and the government stimulus may fuel the housing bubble and sow seeds for a future crisis. The paper can also shed light on the housing markets in other economies that face similar vulnerabilities.

International Taxation and Luxembourg's Economy
De Mooij, Ruud A.,Prihardini, Dinar,Pflugbeil, Antje,Stavrev, Emil
Luxembourg receives ample investment from multinational corporations, in part due to some attractive features in its international tax rules. Around 95 percent of these foreign investments pass through Luxembourg via companies performing holding and/or intra-group financing activities. While their contribution to Luxembourg's economy is modest relative to their large overall balance sheets, they still generate around 3 percent of GDP in tax revenue, create almost 4500 direct jobs, and spend almost 3 percent of GDP on salaries and purchases of business services. Ongoing changes in the international corporate tax framework pose risks to these economic contributions, which this paper attempts to quantify. It also discusses options for reforms in Luxembourg's tax system that could help offset adverse revenue and economic effects.

Least Squares Monte Carlo applied to Dynamic Monetary Utility Functions
Hampus Engsner

In this paper we explore ways of numerically computing recursive dynamic monetary risk measures and utility functions. Computationally, this problem suffers from the curse of dimensionality and nested simulations are unfeasible if there are more than two time steps. The approach considered in this paper is to use a Least Squares Monte Carlo (LSM) algorithm to tackle this problem, a method which has been primarily considered for valuing American derivatives, or more general stopping time problems, as these also give rise to backward recursions with corresponding challenges in terms of numerical computation. We give some overarching consistency results for the LSM algorithm in a general setting as well as explore numerically its performance for recursive Cost-of-Capital valuation, a special case of a dynamic monetary utility function.

Leverage Shocks: Firm-Level Evidence on Debt Overhang and Investment
Cevik, Serhan,Miryugin, Fedor
The global economy is in the midst of an unprecedented slump caused by the coronavirus pandemic. This systemic risk like no other at a time of record-breaking debt levels, especially among nonfinancial firms across the world, could exacerbate corporate vulnerabilities, deepen macro-financial instability, and cause long-lasting damage to economic potential. Using data on more than 2.8 million nonfinancial firms from 52 countries during the period 1997-2018, we develop a two-pronged approach to investigate the relationship between corporate leverage and fixed investment spending. The empirical analysis, robust to a battery of sensitivity checks, confirm corporate leverage is highly vulnerable to disruptions in profitability and cash flow at the firm level and economic growth at the aggregate level. These findings imply that corporate debt overhang could become a strenuous burden on nonfinancial firms, especially if the COVID-19 pandemic lingers and global downturn becomes protracted.

Liquidations: DeFi on a Knife-edge
Daniel Perez,Sam M. Werner,Jiahua Xu,Benjamin Livshits

The trustless nature of permissionless blockchains renders overcollateralization a key safety component relied upon by decentralized finance (DeFi) protocols. Nonetheless, factors such as price volatility may undermine this mechanism. In order to protect protocols from suffering losses, undercollateralized positions can be liquidated. In this paper, we present the first in-depth empirical analysis of liquidations on protocols for loanable funds (PLFs). We examine Compound, one of the most widely used PLFs, for a period starting from its conception to September 2020. We analyze participants' behavior and risk-appetite in particular, to elucidate recent developments in the dynamics of the protocol. Furthermore, we assess how this has changed with a modification in Compound's incentive structure and show that variations of only 3% in an asset's dollar price can result in over 10m USD becoming liquidable. To further understand the implications of this, we investigate the efficiency of liquidators. We find that liquidators' efficiency has improved significantly over time, with currently over 70% of liquidable positions being immediately liquidated. Lastly, we provide a discussion on how a false sense of security fostered by a misconception of the stability of non-custodial stablecoins, increases the overall liquidation risk faced by Compound participants.

Mind the wealth gap: a new allocation method to match micro and macro statistics for household wealth
Michele Cantarella,Andrea Neri,Maria Giovanna Ranalli

The financial and economic crisis recently experienced by many European countries has increased demand for timely, coherent and consistent distributional information for the household sector. In the Euro area, most of the NCBs collect such information through income and wealth surveys, which are often used to inform their decisions. These surveys, however, can often suffer from biases, usually caused by non-response and under-reporting behaviours, leading to a mismatch with macroeconomic aggregates. In this paper, we develop a novel allocation method which combines information from a power law (Pareto) model and imputation procedures so to address these issues simultaneously, when only limited external information is available. We provide two important contributions: first, we adjust the weights of observed survey households for non-response bias, then, we correct for measurement error. Finally, we produce distributional indicators for four Euro-Area countries.

Motivating Banks to Lend? Understanding Bank Participation in the Main Street Lending Program
Minoiu, Camelia,Zarutskie, Rebecca,Zlate, Andrei
We examine bank participation in the Main Street Lending Program (MSLP), an emergency lending program aimed at supporting the flow of credit to small and medium-sized businesses in response to the COVID-19 pandemic. Consistent with the incentives created by the program, we find that participating banks are larger, have lower capital buffers, less deposit funding, and more commercial loans on their balance sheets. MSLP lending is higher in states more impacted by the pandemic, as measured by number of COVID cases per capita, unemployment insurance claims, or changes in unemployment. Importantly, we find that the MSLP had positive spillover effects on banks’ willingness to lend more generally. Banks participating in the MSLP tightened their lending standards and terms on C\&I loans relatively less following the introduction of the program. Finally, we present evidence that key parameters of the program have served to restrain the overall supply of MSLP loans by banks, as well as the demand for MSLP loans by borrowers, resulting in relatively subdued total lending volumes through the program to date.

Pandemics and Firms: Drawing Lessons from History
Cevik, Serhan,Miryugin, Fedor
The global economy is in the midst of an unprecedented slump caused by the COVID-19 pandemic. To assess the likely evolution of nonfinancial corporate performance going forward, this paper investigates empirically the impact of past pandemics using firm-level data on more than 537,000 companies from 14 developing countries during the period 1998-2018. The analysis indicates that the prevalence of infectious diseases has an economically and statistically significant negative effect on nonfinancial corporate performance. This adverse impact is particularly pronounced on smaller and younger firms, compared to larger and more established corporations. We also find that a higher number of infectious-disease cases in population increases the probability of failure among nonfinancial firms, particularly for small and young firms. In the case of COVID-19, the magnitude of these effects will be much greater, given the unprecedented scale of the outbreak and strict policy responses to contain its spread.

Predicting Macroeconomic and Macrofinancial Stress in Low-Income Countries
Weisfeld, Hans,de Carvalho Filho, Irineu,Comelli, Fabio,Giri, Rahul,Hellwig, Klaus-Peter,Huang, Chengyu,Liu, Li,Lizarazo Ruiz, Sandra,Mayer Cirkel, Alexis,Presbitero, Andrea
In recent years, Fund staff has prepared cross-country analyses of macroeconomic vulnerabilities in low-income countries, focusing on the risk of sharp declines in economic growth and of debt distress. We discuss routes to broadening this focus by adding several macroeconomic and macrofinancial vulnerability concepts. The associated early warning systems draw on advances in predictive modeling.

Pricing Financial Derivatives with Exponential Quantum Speedup
Javier Gonzalez-Conde,Ángel Rodríguez-Rozas,Enrique Solano,Mikel Sanz

Pricing financial derivatives, in particular European-style options at different time-maturities and strikes, is a relevant financial problem. The dynamics describing the price of vanilla options when constant volatilities and interest rates are assumed, is governed by the Black-Scholes model, a linear parabolic partial differential equation with terminal value given by the pay-off of the option contract and no additional boundary conditions. Here, we present a digital quantum algorithm to solve Black-Scholes equation on a quantum computer for a wide range of relevant financial parameters by mapping it to the Schr\"odinger equation. The non-Hermitian nature of the resulting Hamiltonian is solved by embedding the dynamics into an enlarged Hilbert space, which makes use of only one additional ancillary qubit. Moreover, we employ a second ancillary qubit to transform initial condition into periodic boundary conditions, which substantially improves the stability and performance of the protocol. This algorithm shows a feasible approach for pricing financial derivatives on a digital quantum computer based on Hamiltonian simulation, technique which differs from those based on Monte Carlo simulations to solve the stochastic counterpart of the Black Scholes equation. Our algorithm remarkably provides an exponential speedup since the terms in the Hamiltonian can be truncated by a polynomial number of interactions while keeping the error bounded. We report expected accuracy levels comparable to classical numerical algorithms by using 10 qubits and 94 entangling gates on a fault-tolerant quantum computer, and an expected success probability of the post-selection procedure due to the embedding protocol above 60\%.

Public Debt Dynamics and Intra-Year Exchange Rate Fluctuations
Acosta Ormaechea, Santiago
The public sector, in carrying out its operations, often incurs foreign currency denominated liabilities and, as such, is exposed to exchange rate fluctuations that could affect the value of public debt to GDP ratios over time. This paper shows that converting foreign currency denominated flows and stocks into local currency using the average and the end-of-period exchange rates, respectively, as envisaged in public finance manuals, gives rise to an identifiable stock-flow adjustment term-due to intra-year exchange rate fluctuations-that affects public debt accumulation. Importantly, the inclusion of this often-ignored stock-flow adjustment term is critical to accurately project public debt levels and any related indicator that could in turn inform about the risk of debt distress. Using a novel dataset covering 82 countries during 2008-19, the paper shows that this stock flow adjustment term is sizable in countries experiencing large exchange rate depreciations, namely above the 99th percentile of the full sample, reaching 1.2 percent of GDP. Interestingly, the measurement of policy-related concepts such as interest rate-growth differentials and debt stabilizing primary balances are also affected by intra-year exchange rate fluctuations, and in non-negligible ways.

Small and Vulnerable: Small Firm Productivity in the Great Productivity Slowdown
Chen, Sophia,Lee, Do
We provide broad-based evidence of a firm size premium of total factor productivity (TFP) growth in Europe after the Global Financial Crisis. The TFP growth of smaller firms was more adversely affected and diverged from their larger counterparts after the crisis. The impact was progressively larger for medium, small, and micro firms relative to large firms. It was also disproportionally larger for firms with limited credit market access. Moreover, smaller firms were less likely to have access to safer banks: those that were better capitalized banks and with a presence in the credit default swap market. Horseraces suggest that firm size may be a more important and robust vulnerability indicator than balance sheet characteristics. Our results imply that the tightening of credit market conditions during the crisis, coupled with limited credit market access especially among micro, small, and medium firms, may have contributed to the large and persistent drop in aggregate TFP.

Sovereign Debt Standstills
Hatchondo, Juan Carlos,Martinez, Leonardo,Sosa‐Padilla, César
As a response to economic crises triggered by COVID-19, sovereign debt standstill proposals emphasize debt payment suspensions without haircuts on the face value of debt obligations. We quantify the effects of standstills using a standard default model. We find that a one-year standstill generates welfare gains for the sovereign equivalent to a permanent consumption increase of between 0.1% and 0.3%, depending on the initial shock. However, except when it avoids a default, the standstill also implies capital losses for creditors of between 9% and 27%, which is consistent with their reluctance to participate in these operations and indicates that this reluctance would persist even without a free-riding or holdout problem. Standstills also generate a form of 'debt overhang' and thus the opportunity for a 'voluntary debt exchange': complementing the standstill with haircuts could reduce creditors' losses and simultaneously increase welfare gains. Our results cast doubts on the emphasis on standstills without haircuts.

The Estimation Risk and the IRB Supervisory Formula
Casellina, Simone ,Landini, Simone,Uberti, Mariacristina
In many standard derivation and presentations of risk measures like the Value-at-Risk or the Expected Shortfall, it is assumed that all the model’s parameters are known. In practice, however, the parameters must be estimated and this introduces an additional source of uncertainty that is usually not accounted for. The Prudential Regulators have formally raised the issue of errors stemming from the internal model estimation process in the context of credit risk, calling for margins of conservatism to cover possible underestimation in capital. Notwithstanding this requirement, to date, a solution shared by banks and regulators/supervisors has not yet been found. In our paper, we investigate the effect of the estimation error in the framework of the Asymptotic Single Risk Factor model that represents the baseline for the derivation of the credit risk measures under the IRB approach. We exploit Monte Carlo simulations to quantify the bias induced by the estimation error and we explore an approach to correct for this bias. Our approach involves only the estimation of the long run average probability of default and not the estimation of the asset correlation given that, in practice, banks are not allowed to modify this parameter. We study the stochastic characteristics of the probability of default estimator that can be derived from the Asymptotic Single Risk Factor framework and we show how to introduce a correction to control for the estimation error. Our approach does not require introducing in the Asymptotic Single Risk Factor model additional elements like the prior distributions or other parameters which, having to be estimated, would introduce another source of estimation error. This simple and easily implemented correction ensures that the probability of observing an exception (i.e. a default rate higher than the estimated quantile of the default rate distribution) is equal to the desired confidence level. We show a practical application of our approach relying on real data.

The Market Measure of Carbon Risk and its Impact on the Minimum Variance Portfolio
Théo Roncalli,Théo Le Guenedal,Frédéric Lepetit,Thierry Roncalli,Takaya Sekine

Like ESG investing, climate change is an important concern for asset managers and owners, and a new challenge for portfolio construction. Until now, investors have mainly measured carbon risk using fundamental approaches, such as with carbon intensity metrics. Nevertheless, it has not been proven that asset prices are directly impacted by these fundamental-based measures. In this paper, we focus on another approach, which consists in measuring the sensitivity of stock prices with respect to a carbon risk factor. In our opinion, carbon betas are market-based measures that are complementary to carbon intensities or fundamental-based measures when managing investment portfolios, because carbon betas may be viewed as an extension or forward-looking measure of the current carbon footprint. In particular, we show how this new metric can be used to build minimum variance strategies and how they impact their portfolio construction.

The Two-Sided Market Network Analysis Based on Transfer Entropy & Labelr
Seung Bin Baik

This study more complex digital platforms in early stages in the two-sided market to produce powerful network effects. In this study, I use Transfer Entropy to look for super users who connect hominids in different networks to achieve higher network effects in the digital platform in the two-sided market, which has recently become more complex. And this study also aims to redefine the decision criteria of product managers by helping them define users with stronger network effects. With the development of technology, the structure of the industry is becoming more difficult to interpret and the complexity of business logic is increasing. This phenomenon is the biggest problem that makes it difficult for start-ups to challenge themselves. I hope this study will help product managers create new digital economic networks, enable them to make prioritized, data-driven decisions, and find users who can be the hub of the network even in small products.