# Research articles for the 2021-02-10

A Bonus-Malus Framework for Cyber Risk Insurance and Optimal Cybersecurity Provisioning
Qikun Xiang,Ariel Neufeld,Gareth W. Peters,Ido Nevat,Anwitaman Datta
arXiv

The cyber risk insurance market is at a nascent stage of its development, even as the magnitude of cyber losses is significant and the rate of cyber risk events is increasing. Existing cyber risk insurance products as well as academic studies have been focusing on classifying cyber risk events and developing models of these events, but little attention has been paid to proposing insurance risk transfer strategies that incentivize mitigation of cyber loss through adjusting the premium of the risk transfer product. To address this important gap, we develop a Bonus-Malus model for cyber risk insurance. Specifically, we propose a mathematical model of cyber risk insurance and cybersecurity provisioning supported with an efficient numerical algorithm based on dynamic programming. Through a numerical experiment, we demonstrate how a properly designed cyber risk insurance contract with a Bonus-Malus system can resolve the issue of moral hazard and benefit the insurer.

A New Approach to Risk Attribution and its Application in Credit Risk Analysis
Frei, Christoph
SSRN
How can risk of a company be allocated to its divisions and attributed to risk factors? The Euler principle allows for an economically justified allocation of risk to different divisions. We introduce a method that generalizes the Euler principle to attribute risk to its driving factors when these factors affect losses in a nonlinear way. The method splits loss contributions over time and is straightforward to implement. We show in an example how this risk decomposition can be applied in the context of credit risk.

A Note of Caution on Quantifying Banks' Recapitalization Effects
Schmidt, Kirsten,Noth, Felix,Tonzer, Lena
SSRN
Unconventional monetary policy measures like asset purchase programs aim to reduce certain securities' yield and alter financial institutions' investment behavior. These measures increase the institutions' market value of securities and add to their equity positions. We show that the extent of this recapitalization effect crucially depends on the securities' accounting and valuation methods, country-level regulation, and maturity structure. We argue that future research needs to consider these factors when quantifying banks' recapitalization effects and consequent changes in banks' lending decisions to the real sector.

An Empirical Investigation of the Volatility Spill-over and Asymmetries between Nifty Index and Rupee- Dollar Exchange Rate
Shahani, Rakesh,TOMAR, PRATEEK
SSRN
The present study is an attempt to investigate the conditional volatility of returns of the two major segments of Indian financial markets viz. Re/$Exchange Rate and Nifty Index Stock Index using GARCH (p,q) methodology. The period of the study has been taken to be April 2007-March 2017 and the data has been collected as monthly closing prices of the two variables, namely rupee dollar exchange rate and NSE Nifty. The analysis has been carried on first differenced (log transformed) prices. For studying the spill-over of volatility from a market to another, squared residuals (after standardization) from another market have been included as variance regressors. Further to find out whether or not there was any asymmetric returns of the markets under study, Threshold GARCH (T-GARCH) Model has been employed. The results of the study revealed the presence of conditional volatility of returns. The optimal model was identified as ARCH (1) when Re/$ Exchange Rate was the dependent variable while it was GARCH (1,1) when Nifty Index was taken as dependent variable. The bi-directional volatility spill-over (contemporaneous) was clearly evident by the two models and the same was captured by the variance regressors i.e. the standardized squared residuals. Further the results showed no sign of any asymmetry in volatility as reflected by the T-GARCH coefficients.

An alternative quality of life ranking on the basis of remittances
Dóra Gréta Petróczy
arXiv

Remittances provide an essential connection between people working abroad and their home countries. This paper considers these transfers as a measure of preferences revealed by the workers, underlying a ranking of countries around the world. In particular, we use the World Bank bilateral remittances data of international salaries and interpersonal transfers between 2010 and 2015 to compare European countries. The suggested least squares method has favourable axiomatic properties. Our ranking reveals a crucial aspect of quality of life and may become an alternative to various composite indices.

An analysis of Uniswap markets
Guillermo Angeris,Hsien-Tang Kao,Rei Chiang,Charlie Noyes,Tarun Chitra
arXiv

Uniswap -- and other constant product markets -- appear to work well in practice despite their simplicity. In this paper, we give a simple formal analysis of constant product markets and their generalizations, showing that, under some common conditions, these markets must closely track the reference market price. We also show that Uniswap satisfies many other desirable properties and numerically demonstrate, via a large-scale agent-based simulation, that Uniswap is stable under a wide range of market conditions.

Asymptotic expansion for the Hartman-Watson distribution
Dan Pirjol
arXiv

The Hartman-Watson distribution with density $f_r(t)$ is a probability distribution defined on $t \geq 0$ which appears in several problems of applied probability. The density of this distribution is expressed in terms of an integral $\theta(r,t)$ which is difficult to evaluate numerically for small $t\to 0$. Using saddle point methods, we obtain the first two terms of the $t\to 0$ expansion of $\theta(\rho/t,t)$ at fixed $\rho >0$. An error bound is obtained by numerical estimates of the integrand, which is furthermore uniform in $\rho$. As an application we obtain the leading asymptotics of the density of the time average of the geometric Brownian motion as $t\to 0$. This has the form $\mathbb{P}(\frac{1}{t} \int_0^t e^{2(B_s+\mu s)} ds \in da) = (2\pi t)^{-1/2} g(a,\mu) e^{-\frac{1}{t} J(a)} (1 + O(t))$, with an exponent $J(a)$ which reproduces the known result obtained previously using Large Deviations theory.

Automated and Distributed Statistical Analysis of Economic Agent-Based Models
Andrea Vandin,Daniele Giachini,Francesco Lamperti,Francesca Chiaromonte
arXiv

We propose a novel approach to the statistical analysis of simulation models and, especially, agent-based models (ABMs). Our main goal is to provide a fully automated and model-independent tool-kit to inspect simulations and perform counterfactual analysis. Our approach: (i) is easy-to-use by the modeller, (ii) improves reproducibility of results, (iii) optimizes running time given the modeller's machine, (iv) automatically chooses the number of required simulations and simulation steps to reach user-specified statistical confidence, and (v) automatically performs a variety of statistical tests. In particular, our framework is designed to distinguish the transient dynamics of the model from its steady-state behaviour (if any), estimate properties of the model in both "phases", and provide indications on the ergodic (or non-ergodic) nature of the simulated processes -- which, in turns allows one to gauge the reliability of a steady-state analysis. Estimates are equipped with statistical guarantees, allowing for robust comparisons across computational experiments. To demonstrate the effectiveness of our approach, we apply it to two models from the literature: a large scale macro-financial ABM and a small scale prediction market model. Compared to prior analyses of these models, we obtain new insights and we are able to identify and fix some erroneous conclusions.

Canary in the Coal Mine: COVID-19 and Soybean Futures Market Liquidity
Peng, Kun,Hu, Zhepeng,Robe, Michel A.,Adjemian, Michael
SSRN
We document the impact of the early stages of the COVID-19 pandemic on liquidity in U.S. agricultural markets. Soybean futures liquidity is affected the earliest, the most, and the longest. Soybean depth drops by half for outright futures and by over nine tenths for calendar spreads, and soybean bid-ask spreads increase significantly, starting on the night of February 12 to 13, 2020â€"a full two weeks before (i) liquidity evaporates in U.S. bond and equity markets and (ii) soybean prices start to fall sharply. The timing of the soybean liquidity drop coincides with overnight news of bleak COVID-19 developments in China (a key source of world demand for oilseeds). Following a series of emergency interventions by the U.S. Federal Reserve, liquidity recovers in the outright marketâ€"but depth remains abnormally low for calendar spreads. These patterns cannot be explained by other factors, such as changes in soybean futures trading volume or price volatility: the COVID-19 shock was novel, and it destroyed soybean-market liquidity in a way that foretold financial-market developments two weeks later. In contrast to soybeans, we find little evidence of a drop in corn or wheat futures liquidity until U.S. financial and crude oil markets sink in early March. Soybeans were truly the canary in the coal mine.

Combination of window-sliding and prediction range method based on LSTM model for predicting cryptocurrency
Yifan Yao,Lina Wang
arXiv

The present study aims to establish the model of the cryptocurrency price trend based on financial theory using the LSTM model with multiple combinations between the window length and the predicting horizons, the random walk model is also applied with different parameter settings.

Concealed Carry
Andrews, Spencer,Colacito, Ric,Croce, Mariano (Max) Massimiliano,Gavazzoni, Federico
SSRN
The slope carry consists of taking a long (short) position in the long-term bonds of countries with steeper (flatter) yield curves. The traditional carry is a long (short) position in countries with high (low) short-term rates. We document that: (i) the slope carry risk premium is negative (positive) in the pre (post) 2008 period, whereas it is concealed over longer samples; (ii) the traditional carry risk premium is lower post-2008; and (iii) there has been a sharp decline in expected global growth and global inflation post-2008. We connect these empirical findings through an equilibrium model in which investors price news shocks, financial markets are complete, and countries feature heterogeneous exposure to news shocks about both global output expected growth and global inflation.

Do Credit Rating Agencies Care About Our International Tax Planning Strategy When Assigning Credit Ratings?
Ma, Zhiming,Stice, Derrald,Wang, Danye
SSRN
International tax planning strategies, by their very nature, increase firmsâ€™ free cash flows, which could improve companiesâ€™ creditworthiness. However, these strategies also bring information and agency problems, which may reduce their creditworthiness. To understand which of these effects dominates, this study examines the effect of international tax planning on credit ratings. We find that credit analysts incorporate information related to international tax planning when analyzing a firmâ€™s credit risk and that high international tax planning is associated with less favorable credit ratings. We also find that this effect is mitigated by a higher conflict of interest for the bond rating agencies. Furthermore, we find that the effect of international tax planning operates through the channels of future cash flow effects, agency costs, and information risk. Our results are robust to a difference-in-differences research design using The American Jobs Creation Act of 2004 as an exogenous shock to the benefits from international tax planning, and we document that the effect of international tax planning is different from and incremental to overall tax avoidance.

Do the propensity and drivers of academics' engagement in research collaboration with industry vary over time?
Giovanni Abramo,Francesca Apponi,Ciriaco Andrea D'Angelo
arXiv

This study is about public-private research collaboration. In particular, we want to measure how the propensity of academics to collaborate with their colleagues from private firms varies over time and whether the typical profile of such academics change. Furthermore, we investigate the change of the weights of main drivers underlying the academics' propensity to collaborate with industry. In order to achieve such goals, we apply an inferential model on a dataset of professors working in Italian universities in two subsequent periods, 2010-2013 and 2014-2017. Results can be useful for supporting the definition of policies aimed at fostering public-private research collaborations, and should be taken into account when assessing their effectiveness afterwards.

Does Bank Efficiency Affect the Bank Lending Channel in China?
FungÃ¡ÄovÃ¡, Zuzana,Kerola, Eeva,Weill, Laurent
SSRN
This work examines the impact of bank efficiency on the bank lending channel in China. Using a sample of 175 Chinese banks over the period 2006â€"2017, we investigate how the reaction of the loan supply to monetary policy actions depends on a bankâ€™s efficiency. While bank efficiency does not exert an impact on the effectiveness of monetary policy transmission overall, it does favor the transmission of monetary policy for banks with low loan-to-deposit ratios. In addition, the expansion of shadow banking activities has been associated with a positive impact of bank efficiency on monetary policy transmission. These results suggest that bank efficiency may influence the bank lending channel in certain cases.

Dynamic Structural Impact of the COVID-19 Outbreak on the Stock Market and the Exchange Rate: A Cross-country Analysis Among BRICS Nations
Rupam Bhattacharyya,Sheo Rama,Atul Kumar,Indrajit Banerjee
arXiv

COVID-19 has impacted the economy of almost every country in the world. Of particular interest are the responses of the economic indicators of developing nations (such as BRICS) to the COVID-19 shock. As an extension to our earlier work on the dynamic associations of pandemic growth, exchange rate, and stock market indices in the context of India, we look at the same question with respect to the BRICS nations. We use structural variable autoregression (SVAR) to identify the dynamic underlying associations across the normalized growth measurements of the COVID-19 cumulative case, recovery, and death counts, and those of the exchange rate, and stock market indices, using data over 203 days (March 12 - September 30, 2020). Using impulse response analyses, the COVID-19 shock to the growth of exchange rate was seen to persist for around 10+ days, and that for stock exchange was seen to be around 15 days. The models capture the contemporaneous nature of these shocks and the subsequent responses, potentially guiding to inform policy decisions at a national level. Further, causal inference-based analyses would allow us to infer relationships that are stronger than mere associations.

Empowering Patients Using Smart Mobile Health Platforms: Evidence From A Randomized Field Experiment
Anindya Ghose,Xitong Guo,Beibei Li,Yuanyuan Dang
arXiv

With today's technological advancements, mobile phones and wearable devices have become extensions of an increasingly diffused and smart digital infrastructure. In this paper, we examine mobile health (mHealth) platforms and their health and economic impacts on the outcomes of chronic disease patients. To do so, we partnered with a major mHealth firm that provides one of the largest mobile health app platforms in Asia specializing in diabetes care. We designed and implemented a randomized field experiment based on detailed patient health activities (e.g., steps, exercises, sleep, food intake) and blood glucose values from 1,070 diabetes patients over several months. Our main findings show that the adoption of the mHealth app leads to an improvement in both short term metrics (such as reduction in patients' blood glucose and glycated hemoglobin levels) and longer-term metrics (such as hospital visits, and medical expenses). Patients who adopted the mHealth app undertook higher levels of exercise, consumed healthier food with lower calories, walked more steps and slept for longer times on a daily basis. A comparison of mobile vs. PC enabled version of the same app demonstrates that the mobile has a stronger effect than PCs in helping patients make behavioral modifications with respect to diet, exercise and life style, which ultimately leads to an improvement in their healthcare outcomes. We also compared outcomes when the platform facilitates personalized health reminders to patients vs. generic reminders. We found that personalized mobile message with patient-specific guidance can have an inadvertent effect on patient app engagement, life style changes, and health improvement. Overall, our findings indicate the potential value of mHealth technologies, as well as the importance of mHealth platform design in achieving better healthcare outcomes.

Emu Deepening and Sovereign Debt Spreads: Using Political Space to Achieve Policy Space
SSRN
Sovereign spreads within the European Monetary Union (EMU) arise because markets price-in heterogeneous country fundamentals, but also re-denomination risks, given the incomplete nature of EMU. This creates a permanent risk of financial fragmentation within the area. In this paper we claim that political decisions that signal commitment to safeguarding the adequate functioning of the euro area influence investorsâ€™ valuations. We focus on decisions conducive to enhancing the institutional framework of the euro area (â€œEMU deepeningâ€). To test our hypothesis we build a comprehensive narrative of events (decisions) from all documents and press releases issued by the Council of the EU and the European Council during the period January 2010 to March 2020. We categorize the events as dealing with: (i) economic and financial integration; (ii) fiscal policy; (iii) bailouts. With our extremely rich narrative at hand, we conduct event-study regressions with daily data to assess the impact of events on sovereign bond yields and find that indeed decisions on financial integration drive down periphery spreads. Moreover, while decisions on key subjects present a robust effect, this is not the case with prior discussions on those subjects at the Council level. Finally, we show that the impacts arise from reductions in peripheral sovereign spreads, and not by the opposite movement in core countries. We conclude that EU policy-makers have at their disposal significant â€œpolitical spaceâ€ to reduce fragmentation and gain â€œpolicy spaceâ€.

FRM Financial Risk Meter for Emerging Markets
Souhir Ben Amor,Michael Althof,Wolfgang Karl Härdle
arXiv

The fast-growing Emerging Market (EM) economies and their improved transparency and liquidity have attracted international investors. However, the external price shocks can result in a higher level of volatility as well as domestic policy instability. Therefore, an efficient risk measure and hedging strategies are needed to help investors protect their investments against this risk. In this paper, a daily systemic risk measure, called FRM (Financial Risk Meter) is proposed. The FRM-EM is applied to capture systemic risk behavior embedded in the returns of the 25 largest EMs FIs, covering the BRIMST (Brazil, Russia, India, Mexico, South Africa, and Turkey), and thereby reflects the financial linkages between these economies. Concerning the Macro factors, in addition to the Adrian and Brunnermeier (2016) Macro, we include the EM sovereign yield spread over respective US Treasuries and the above-mentioned countries currencies. The results indicated that the FRM of EMs FIs reached its maximum during the US financial crisis following by COVID 19 crisis and the Macro factors explain the BRIMST FIs with various degrees of sensibility. We then study the relationship between those factors and the tail event network behavior to build our policy recommendations to help the investors to choose the suitable market for in-vestment and tail-event optimized portfolios. For that purpose, an overlapping region between portfolio optimization strategies and FRM network centrality is developed. We propose a robust and well-diversified tail-event and cluster risk-sensitive portfolio allocation model and compare it to more classical approaches

Gendered impact of COVID-19 pandemic on research production: a cross-country analysis
Giovanni Abramo,Ciriaco Andrea D'Angelo,Ida Mele
arXiv

The massive shock of the COVID-19 pandemic is already showing its negative effects on economies around the world, unprecedented in recent history. COVID-19 infections and containment measures have caused a general slowdown in research and new knowledge production. Because of the link between R&D spending and economic growth, it is to be expected then that a slowdown in research activities will slow in turn the global recovery from the pandemic. Many recent studies also claim an uneven impact on scientific production across gender. In this paper, we investigate the phenomenon across countries, analysing preprint depositions. Differently from other works, that compare the number of preprint depositions before and after the pandemic outbreak, we analyse the depositions trends across geographical areas, and contrast after-pandemic depositions with expected ones. Differently from common belief and initial evidence, in few countries female scientists increased their scientific output while males plunged.

Group Quantization of Quadratic Hamiltonians in Finance
Santiago Garcia
arXiv

The Group Quantization formalism is a scheme for constructing a functional space that is an irreducible infinite dimensional representation of the Lie algebra belonging to a dynamical symmetry group. We apply this formalism to the construction of functional space and operators for quadratic potentials -- gaussian pricing kernels in finance. We describe the Black-Scholes theory, the Ho-Lee interest rate model and the Euclidean repulsive and attractive oscillators. The symmetry group used in this work has the structure of a principal bundle with base (dynamical) group a semi-direct extension of the Heisenberg-Weyl group by SL(2,R), and structure group (fiber) the positive real line.

Implied Equity Premium and Market Beta
Chow, Victor,Gu, Jiahao,Wang, Zhan
SSRN
Martin (2017) shows that the arbitrage-free measure of return-volatility mimicked by a portfolio of options contracts is a close approximation of ex-ante equity risk premium. We argue, nevertheless, the left-tail volatility-asymmetry downward bias his (symmetric) SVIX approach. This paper provides a simple procedure to correct this bias by adding a risk-neutral measure of volatility-asymmetry (AVIX2) to the SVIX2. The option-implied market beta of individual stocks is a weighted sum of that of SVIX and AVIX. Empirically, our findings suggest these implied betas possess significant predictability of return and the hedging ability against bear/crashing markets.

Information Sharing Among Strategic Traders: The Role of Disagreement
Balasubramaniam, Swaminathan
SSRN
In a duopoly model of informed speculation, I show that competing traders share information when they disagree enough. Traders can lose competitive rents by sharing private information, but with sufficient disagreement, they can engage in profitable belief arbitrage by trading against each other's signal. Traders, however, would gain by over-reporting their signals so that competitors make large opposing trades. When information is verifiable, truthful disclosure emerges due to an â€œunravelingâ€ argument. Mediators (say, sell-side analysts or brokers) could facilitate partial information sharing by aggregating and distributing information in an incentive-compatible manner. Disagreement makes the market more liquid, but information sharing undermines the liquidity benefits.

Moving From â€˜Developmentalâ€™ to â€˜Anti-Developmentalâ€™ Local Financial Models in East Asia: Abandoning a Winning Formula
Bateman, Milford
SSRN
One of the decisive but often overlooked factors in the creation of the East Asian â€˜economic miracleâ€™ was the part played by a variety of heterodox sub-national state, community and cooperatively owned and controlled financial systems, institutions and lending models. Beginning with Japan after 1945, local financial systems were (re)constructed across East Asia in a way that very efficiently operationalised key development policy goals through targeted local enterprise development. Yet in spite of marked success with this â€™developmentalâ€™ local financial model, from the 1980s onwards the international development community, led by the US government and the World Bank, began an effort to discredit and replace it with a new commercially-oriented private sector- led local financial model promoting mass individual entrepreneurship with the help of a for-profit microcredit sector. This article begins by briefly summarising why such â€˜developmentalâ€™ local financial models were important to East Asiaâ€™s economic miracle before I turn to examining why, how and what happened when after 1980 the international development community quietly set out to undermine and destroy them. I conclude from this analysis that the international development communityâ€™s desire to begin to impose its own neoliberal ide- ology and narrow elite-driven enrichment goals in East Asia far outweighed the ongoing development successes registered by the â€˜developmentalâ€™ local financial models that emerged after 1945.

POTENCIAIS APLICAÃ‡Ã•ES DE BLOCKCHAIN NO MERCADO DE CAPITAIS (Potential Applications of Blockchain in Capital Markets)
Schechtman, David
SSRN

Research Methods of Assessing Global Value Chains
Sourish Dutta
arXiv

My study would follow two phases of analysis i.e. the first phase/preliminary view would be developed through the widest range of available and applicable methodologies followed by a second phase/in-depth assessment and discussion of the identified challenges, opportunities, and policy options.

Some results on the risk capital allocation rule induced by the Conditional Tail Expectation risk measure
Nawaf Mohammed,Edward Furman,Jianxi Su
arXiv

Risk capital allocations (RCAs) are an important tool in quantitative risk management, where they are utilized to, e.g., gauge the profitability of distinct business units, determine the price of a new product, and conduct the marginal economic capital analysis. Nevertheless, the notion of RCA has been living in the shadow of another, closely related notion, of risk measure (RM) in the sense that the latter notion often shapes the fashion in which the former notion is implemented. In fact, as the majority of the RCAs known nowadays are induced by RMs, the popularity of the two are apparently very much correlated. As a result, it is the RCA that is induced by the Conditional Tail Expectation (CTE) RM that has arguably prevailed in scholarly literature and applications. Admittedly, the CTE RM is a sound mathematical object and an important regulatory RM, but its appropriateness is controversial in, e.g., profitability analysis and pricing. In this paper, we address the question as to whether or not the RCA induced by the CTE RM may concur with alternatives that arise from the context of profit maximization. More specifically, we provide exhaustive description of all those probabilistic model settings, in which the mathematical and regulatory CTE RM may also reflect the risk perception of a profit-maximizing insurer.

Strength and Weakness in Numbers? Unpacking the Role of Prevalence in the Diffusion of Reverse Mergers
Naumovska, Ivana,Zajac, Edward J.,Lee, Peggy M.
SSRN
A common prediction in research on practice diffusion is a â€œstrength in numbersâ€ effect (i.e., that a growing number of past adopters will increase the number of future adopters). We advance and test a theoretical perspective to explain when and how practice prevalence may also generate a â€œweakness in numbersâ€ effect. Specifically, in seeking to explain the diffusion of reverse mergers (RMs) â€" a controversial practice that allows a private firm to go public by merging with a publicly listed â€œshell companyâ€ â€" we suggest that prevalence affected their diffusion in a complex way, based on two divergent social influence pathways, creating: (1) a direct and positive effect of practice prevalence on potential adopters, who view prevalence as evidence of the practiceâ€™s value, and (2) an indirect and negative effect, mediated through third-party evaluators (i.e., investors, and the media) who view prevalence as a cause for concern and skepticism. We also highlight the utility of this theoretical framework by analyzing how a decline in the status of past adopters exerts a negative effect on diffusion through both social influence pathways. Employing structural equation modeling techniques, we find support for the hypothesized relationships and we discuss the implications of the study for future research on practice diffusion.

The "Fake News" Effect: Experimentally Identifying Motivated Reasoning Using Trust in News
Michael Thaler
arXiv

Motivated reasoning posits that people distort how they process new information in the direction of beliefs they find more attractive. This paper creates a novel experimental design to identify motivated reasoning from Bayesian updating when people enter into the experiment with endogenously different beliefs. It analyzes how subjects assess the veracity of information sources that tell them the median of their belief distribution is too high or too low. A Bayesian would infer nothing about the source veracity from this message, but a motivated reasoner would believe the source were more truthful when it reports the direction that he is more motivated to believe. Experimental results show novel evidence for politically-motivated reasoning about immigration, income mobility, crime, racial discrimination, gender, climate change, gun laws, and the performance of other subjects. Motivated reasoning from messages on these topics leads people's beliefs to become more polarized and less accurate, even though the messages are uninformative.

The Role of a Nation's Culture in the Country's Governance: Stochastic Frontier Analysis
arXiv

What role does culture play in determining institutions in a country? This paper argues that the establishment of institutions is a process originating predominantly in a nation's culture and tries to discern the role of a cultural background in the governance of countries. We use the six Hofstede's Cultural Dimensions and the six Worldwide Governance Indicators to test the strength of the relationship on 94 countries between 1996 and 2019. We find that the strongest cultural characteristics are Power Distance with negative effect on governance and Long-Term Orientation with positive effect. We also determine how well countries transform their cultural characteristics into institutions using stochastic frontier analysis.

The effects of citation-based research evaluation schemes on self-citation behavior
Giovanni Abramo,Ciriaco Andrea D'Angelo,Leonardo Grilli
arXiv

We investigate the changes in the self-citation behavior of Italian professors following the introduction of a citation-based incentive scheme, for national accreditation to academic appointments. Previous contributions on self-citation behavior have either focused on small samples or relied on simple models, not controlling for all confounding factors. The present work adopts a complex statistics model implemented on bibliometric individual data for over 15,000 Italian professors. Controlling for a number of covariates (number of citable papers published by the author; presence of international authors; number of co-authors; degree of the professor's specialization), the average increase in self-citation rates following introduction of the ASN is of 9.5%. The increase is common to all disciplines and academic ranks, albeit with diverse magnitude. Moreover, the increase is sensitive to the relative incentive, depending on the status of the scholar with respect to the scientific accreditation. A further analysis shows that there is much heterogeneity in the individual patterns of self-citing behavior, albeit with very few outliers.

The impact of social influence in Australian real-estate: market forecasting with a spatial agent-based model
Benjamin Patrick Evans,Kirill Glavatskiy,Michael S. Harré,Mikhail Prokopenko
arXiv

Housing markets are inherently spatial, yet many existing models fail to capture this spatial dimension. Here we introduce a new graph-based approach for incorporating a spatial component in a large-scale urban housing agent-based model (ABM). The model explicitly captures several social and economic factors that influence the agents' decision-making behaviour (such as fear of missing out, their trend following aptitude, and the strength of their submarket outreach), and interprets these factors in spatial terms. The proposed model is calibrated and validated with the housing market data for the Greater Sydney region. The ABM simulation results not only include predictions for the overall market, but also produce area-specific forecasting at the level of local government areas within Sydney as arising from individual buy and sell decisions. In addition, the simulation results elucidate agent preferences in submarkets, highlighting differences in agent behaviour, for example, between first-time home buyers and investors, and between both local and overseas investors.

Transaction Cost Analytics for Corporate Bonds
Xin Guo,Charles-Albert Lehalle,Renyuan Xu
arXiv

Electronic platform has been increasingly popular for the execution of large orders among asset managers dealing desks. Properly monitoring each individual trade by the appropriate Transaction Cost Analysis (TCA) is the first key step towards this electronic automation. One of the challenges in TCA is to build a benchmark for the expected transaction cost and to characterize the price impact of each individual trade, with given bond characteristics and market conditions.

Taking the viewpoint of an investor, we provide an analytical methodology to conduct TCA in corporate bond trading. With limited liquidity of corporate bonds and patchy information available on existing trades, we manage to build a statistical model as a benchmark for effective cost and a non-parametric model for the price impact kernel. Our TCA analysis is conducted based on the TRACE Enhanced dataset and consists of four steps in two different time scales. The first step is to identify the initiator of a transaction and the riskless-principle-trades (RPTs). With the estimated initiator of each trade, the second step is to estimate the bid-ask spread and the mid-price movements. The third step is to estimate the expected average cost on a weekly basis via regularized regression analysis. The final step is to investigate each trade for the amplitude of its price impact and the price decay after the transaction for liquid corporate bonds. Here we apply a transient impact model (TIM) to estimate the price impact kernel via a non-parametric method.

Our benchmark model allows for identifying and improving best practices and for enhancing objective and quantitative counter-party selections. A key discovery of our study is the need to account for a price impact asymmetry between customer-buy orders and consumer-sell orders.

What We Do In The Shadows: Chinese Shadow Credit Growth and Monetary Policy
Shieh, Harrison
SSRN
This paper evaluates the effect of Chinese monetary policy shocks on credit creation through the shadow banking sector in mainland China. I identify monetary policy shocks by constructing a measure of monetary policy surprises based on changes to the 1-Year Interest Rate Swaps on the 7-Day Repo Rate on monetary policy announcement dates. A two-stage local projection was then estimated, using the surprise measure as an instrument. The results give two key findings: 1) shadow credit expands in response to contractionary monetary policy, and 2) I provide additional evidence of the transmission of monetary policy through the interest rate channel.

When Does it Pay Off to Learn a New Skill? Revealing the Complementary Benefit of Cross-Skilling
Fabian Stephany
arXiv

This work examines the economic benefits of learning a new skill from a different domain: cross-skilling. To assess this, a network of skills from the job profiles of 14,790 online freelancers is constructed. Based on this skill network, relationships between 3,480 different skills are revealed and marginal effects of learning a new skill can be calculated via workers' wages. The results indicate that learning in-demand skills, such as popular programming languages, is beneficial in general, and that diverse skill sets tend to be profitable, too. However, the economic benefit of a new skill is individual, as it complements the existing skill bundle of each worker. As technological and social transformation is reshuffling jobs' task profiles at a fast pace, the findings of this study help to clarify skill sets required for designing individual re-skilling pathways. This can help to increase employability and reduce labour market shortages.

â€˜Size & Fitâ€™ of Piecemeal Liquidation Processes: Aggravating Circumstances and Side Effects
Cocozza, Rosa,Masera, Rainer
SSRN
This paper investigates the actual impact of new accounting and regulatory requirements on banksâ€™ provisioning policies and earnings management in the context of the capital adequacy of Euro Area (EA) credit institutions. This paper also examines whether loan-loss provisions signal managementsâ€™ expectations concerning future bank profits to investors. Evidence drawn from the 2011-2019 period indicates that earnings management is an important determinant of LLPs for EA intermediaries. During recent years, small bank managers are much more concerned with their credit portfolio quality and do not use LLPs for discretionary purposes apart from income smoothing. The paper gives evidence of a lack of flexibility in the Balance-Sheet of smaller banks and provides some policy refinement to avoid disorderly piecemeal liquidation.