Background. By decoupling economic growth from an intensive use of resources, preventing the impairment of natural capital, and enhancing resilience to system-wide shocks, Circular Economy (CE) is a powerful opportunity for economic agents willing to hedge against “sustainability” risk factors. In fact, it helps shielding against the risk of assets becoming stranded, can generate fresh and non-speculative demand for investments, and can improve companies’ results at both individual and portfolio levels. Problem. Therefore, equity investors into circular un- dertakings could benefit from (H1) reduced stock return volatility, as well as (H2) a greater ability to withstand exogenous negative events. Approach. For testing these hypotheses, we constructed a sample of ~600 listed com- panies across EU-15 countries, plus Switzerland, and 17 resource intensive industries. We retrieved their market data in 2019-20, as well as their accounting fundamentals in 2018-19. By controlling for the latter, we investigated whether market-based risk — either in total terms (i.e., the standard deviation of returns) or circumscribed to the systematic component thereof (i.e., the Beta against both a European and global market index) — may be explained by a company’s degree of circularity, measured by the Circularity Score (CS). This is a novel indicator originally proposed by Zara et al. (2020), based on selected indicators included in the Refinitiv ESG dataset. As a core improvement, in weighting an entity’s circular performance, we assessed the latter’s ‘financial materiality’ (i.e., relevance to the company’s business) at sub-industry level, applying the SASB Materiality Map. Methodology. Via OLS estimation, we tested our hypotheses (i) over the whole-time horizon, in a pooled model;(ii) on specific timeframes, in a standard cross-sectional model. The latter was applied to either the entire 2020 or subperiods thereof: namely, with respect to the COVID-19 outbreak, we distinguished between a pre-shock, a shock and a post-shock phase, as proposed in Ramelli and Wagner, 2020. Our quest was refined to conduct a deeper investi- gation into the Oil & Gas industry, which is intrinsically the most exposed to sustainability risks and, also, did experience the widest volatility in 2020. Findings. Both H1 and H2 received widespread confirmation. The CS was found to exert a widespread negative, significant and robust effect on all the risk measures, regardless of the timespan considered. Also, amplifying effects were recorded as of the Oil & Gas industry. Conclusions. Our results lend remarkable support to the idea that the CE can be a powerful de-risking strategy, also in case of a severe shock, with a view to mitigating the negative consequences and building back better. They call on firms and policymakers to foster the circular transition, thereby accelerating economic recovery in the aftermath of the pandemic crisis.
{"title":"Circular Economy, Stock Volatility and Resilience to the COVID-19 Shock: Evidence from European Companies","authors":"Claudio Zara, Luca Bellardini, Margherita Gobbi","doi":"10.2139/ssrn.3947722","DOIUrl":"https://doi.org/10.2139/ssrn.3947722","url":null,"abstract":"Background. By decoupling economic growth from an intensive use of resources, preventing the impairment of natural capital, and enhancing resilience to system-wide shocks, Circular Economy (CE) is a powerful opportunity for economic agents willing to hedge against “sustainability” risk factors. In fact, it helps shielding against the risk of assets becoming stranded, can generate fresh and non-speculative demand for investments, and can improve companies’ results at both individual and portfolio levels. Problem. Therefore, equity investors into circular un- dertakings could benefit from (H1) reduced stock return volatility, as well as (H2) a greater ability to withstand exogenous negative events. Approach. For testing these hypotheses, we constructed a sample of ~600 listed com- panies across EU-15 countries, plus Switzerland, and 17 resource intensive industries. We retrieved their market data in 2019-20, as well as their accounting fundamentals in 2018-19. By controlling for the latter, we investigated whether market-based risk — either in total terms (i.e., the standard deviation of returns) or circumscribed to the systematic component thereof (i.e., the Beta against both a European and global market index) — may be explained by a company’s degree of circularity, measured by the Circularity Score (CS). This is a novel indicator originally proposed by Zara et al. (2020), based on selected indicators included in the Refinitiv ESG dataset. As a core improvement, in weighting an entity’s circular performance, we assessed the latter’s ‘financial materiality’ (i.e., relevance to the company’s business) at sub-industry level, applying the SASB Materiality Map. Methodology. Via OLS estimation, we tested our hypotheses (i) over the whole-time horizon, in a pooled model;(ii) on specific timeframes, in a standard cross-sectional model. The latter was applied to either the entire 2020 or subperiods thereof: namely, with respect to the COVID-19 outbreak, we distinguished between a pre-shock, a shock and a post-shock phase, as proposed in Ramelli and Wagner, 2020. Our quest was refined to conduct a deeper investi- gation into the Oil & Gas industry, which is intrinsically the most exposed to sustainability risks and, also, did experience the widest volatility in 2020. Findings. Both H1 and H2 received widespread confirmation. The CS was found to exert a widespread negative, significant and robust effect on all the risk measures, regardless of the timespan considered. Also, amplifying effects were recorded as of the Oil & Gas industry. Conclusions. Our results lend remarkable support to the idea that the CE can be a powerful de-risking strategy, also in case of a severe shock, with a view to mitigating the negative consequences and building back better. They call on firms and policymakers to foster the circular transition, thereby accelerating economic recovery in the aftermath of the pandemic crisis.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123890014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using an estimated DSGE model with monetary and fiscal policy interactions and allowing for equilibrium indeterminacy, I find that a passive monetary and passive fiscal policy regime fits Chinese economy best. However, if money is introduced in the economy, things would be different before and after 2012. Specifically, the active monetary and passive fiscal policy prevailed before 2012 and passive monetary and passive fiscal policy fitted after 2012 in China. Besides, government spending has different impact before and after 2012 according to the model.
{"title":"Policy Regime Shifts In China","authors":"Hao-yang Jia","doi":"10.2139/ssrn.3845448","DOIUrl":"https://doi.org/10.2139/ssrn.3845448","url":null,"abstract":"Using an estimated DSGE model with monetary and fiscal policy interactions and allowing for equilibrium indeterminacy, I find that a passive monetary and passive fiscal policy regime fits Chinese economy best. However, if money is introduced in the economy, things would be different before and after 2012. Specifically, the active monetary and passive fiscal policy prevailed before 2012 and passive monetary and passive fiscal policy fitted after 2012 in China. Besides, government spending has different impact before and after 2012 according to the model.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121197979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I analyze time series momentum along the Treasury term structure. Past bond returns predict future returns because of autocorrelation in both bond carry and yield changes. Yield curve momentum can largely be captured using a single bond return or yield change factor. Because yield changes are partly induced by changes in the federal funds rate, yield curve momentum is related to FOMC post announcement drift. The momentum factor is unspanned by the information in the term structure today and is hence inconsistent with standard term structure, macrofinance and behavioural models, including models designed to explain momentum. I propose a potential resolution.
{"title":"Yield Curve Momentum","authors":"M. Sihvonen","doi":"10.2139/ssrn.3840915","DOIUrl":"https://doi.org/10.2139/ssrn.3840915","url":null,"abstract":"I analyze time series momentum along the Treasury term structure. Past bond returns predict future returns because of autocorrelation in both bond carry and yield changes. Yield curve momentum can largely be captured using a single bond return or yield change factor. Because yield changes are partly induced by changes in the federal funds rate, yield curve momentum is related to FOMC post announcement drift. The momentum factor is unspanned by the information in the term structure today and is hence inconsistent with standard term structure, macrofinance and behavioural models, including models designed to explain momentum. I propose a potential resolution.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132091924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lauren Stagnol, C. Lopez, T. Roncalli, Bruno Taillardat
After decades of sound performance, doubts have been raised on the ability of the equity value factor to continue to deliver a positive performance in the aftermath of the 2008 Global Financial Crisis. Indeed, in a context dominated by low yields, sluggish growth and subdued inflation combined with an accelerating digitalization of the economy, the performance of value strategies struggled over the past decade. In this paper, we investigate potential drivers behind this performance lag, such as macroeconomic and microeconomic determinants, ESG characteristics or credit-borrowed components. Based on European and American data, we find that inflation and tightening credit spread levels are the most supportive factors for value stocks. As far as interest rates are concerned, their sustained low levels prevented the value stock universe from clearing its most distressed issuers, also known as "deep value", and thus dampened value performance. As a matter of fact, we show that value has not been systematically an investment strategy bearing a heightened default risk. Our ESG analysis corroborates the "transatlantic divide", the historical gap between the U.S. and Europe on this front, and shows that value and growth stocks are not necessarily all brown and green stocks. In addition, we demonstrate that the small cap segment has not been the magical cure to value underperformance. Finally, we conclude that value is not dead yet, and might even have bright days ahead considering the current improvements in market sentiment, especially if inflation does materialize. Nevertheless, we also emphasize that the current value risk factor is probably different in nature from the one we observed during the golden age of value investing at the beginning of the 2000s. Indeed, trading facilities, ease of access to fundamental data for a large number of investors, ESG investing and the digitalization of the economy may have changed the rules of the game.
{"title":"Understanding the Performance of the Equity Value Factor","authors":"Lauren Stagnol, C. Lopez, T. Roncalli, Bruno Taillardat","doi":"10.2139/ssrn.3813572","DOIUrl":"https://doi.org/10.2139/ssrn.3813572","url":null,"abstract":"After decades of sound performance, doubts have been raised on the ability of the equity value factor to continue to deliver a positive performance in the aftermath of the 2008 Global Financial Crisis. Indeed, in a context dominated by low yields, sluggish growth and subdued inflation combined with an accelerating digitalization of the economy, the performance of value strategies struggled over the past decade. In this paper, we investigate potential drivers behind this performance lag, such as macroeconomic and microeconomic determinants, ESG characteristics or credit-borrowed components. Based on European and American data, we find that inflation and tightening credit spread levels are the most supportive factors for value stocks. As far as interest rates are concerned, their sustained low levels prevented the value stock universe from clearing its most distressed issuers, also known as \"deep value\", and thus dampened value performance. As a matter of fact, we show that value has not been systematically an investment strategy bearing a heightened default risk. Our ESG analysis corroborates the \"transatlantic divide\", the historical gap between the U.S. and Europe on this front, and shows that value and growth stocks are not necessarily all brown and green stocks. In addition, we demonstrate that the small cap segment has not been the magical cure to value underperformance. Finally, we conclude that value is not dead yet, and might even have bright days ahead considering the current improvements in market sentiment, especially if inflation does materialize. Nevertheless, we also emphasize that the current value risk factor is probably different in nature from the one we observed during the golden age of value investing at the beginning of the 2000s. Indeed, trading facilities, ease of access to fundamental data for a large number of investors, ESG investing and the digitalization of the economy may have changed the rules of the game.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124972186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents empirical models of Mexican government bond (MGB) yields based on monthly macroeconomic data. The current short-term interest rate has a decisive influence on MGB yields, after controlling for inflation and growth in industrial production. John Maynard Keynes claimed that government bond yields move in lockstep with the short-term interest rate. The models presented in the paper show that Keynes’s claim holds for MGB yields. This has important policy implications for Mexico. The empirical findings of the paper are also relevant for ongoing debates in macroeconomics.
{"title":"The Empirics of Long-Term Mexican Government Bond Yields","authors":"Tanweer Akram, Syed Al-Helal Uddin","doi":"10.2139/ssrn.3780186","DOIUrl":"https://doi.org/10.2139/ssrn.3780186","url":null,"abstract":"This paper presents empirical models of Mexican government bond (MGB) yields based on monthly macroeconomic data. The current short-term interest rate has a decisive influence on MGB yields, after controlling for inflation and growth in industrial production. John Maynard Keynes claimed that government bond yields move in lockstep with the short-term interest rate. The models presented in the paper show that Keynes’s claim holds for MGB yields. This has important policy implications for Mexico. The empirical findings of the paper are also relevant for ongoing debates in macroeconomics.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115030720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study proposes a new measure of the tradability of 120+ commodities based on price dispersion. This approach is used to construct price indices of tradables and non-tradables for 150+ countries. The expenditure share of tradables is lower for richer countries, while the relative price of non-tradables, which plays an important role in the determination of real exchange rates, is higher. Secondly, a common-factor approach (based on principal components) is introduced to compress the large volume of information on prices and quantities consumed globally. We find that cross-commodity correlations are higher for prices than for consumption. In addition, income is responsible for 98% of the variation in the first principal component of consumption but explains only 24% of the first price component. This suggests consumption are driven primarily by domestic factors, while prices are determined by factors outside the country, along the lines of the Purchasing Power Parity theory.
{"title":"Understanding International Price and Consumption Disparities","authors":"Long Hai Vo","doi":"10.2139/ssrn.3759091","DOIUrl":"https://doi.org/10.2139/ssrn.3759091","url":null,"abstract":"This study proposes a new measure of the tradability of 120+ commodities based on price dispersion. This approach is used to construct price indices of tradables and non-tradables for 150+ countries. The expenditure share of tradables is lower for richer countries, while the relative price of non-tradables, which plays an important role in the determination of real exchange rates, is higher. Secondly, a common-factor approach (based on principal components) is introduced to compress the large volume of information on prices and quantities consumed globally. We find that cross-commodity correlations are higher for prices than for consumption. In addition, income is responsible for 98% of the variation in the first principal component of consumption but explains only 24% of the first price component. This suggests consumption are driven primarily by domestic factors, while prices are determined by factors outside the country, along the lines of the Purchasing Power Parity theory.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127444766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We show that the cross-autocorrelation also exists in the global CDS markets and develop an econometric model to capture the global correlation structure. We study implications on the credit risk transmission and contagion risk. We find four main results: (i) credit risk transmission is through the cross-correlation at regional rather than sectoral level; (ii) time-variation in financial sector's importance is caused by asymmetric responses to the positive and negative macro news; (iii) autocorrelation reduces the contagion risk in Asia while has little impact on other regions; (iv) contagion risks in the US and EU originate from sectors with international influence.
{"title":"Cross-Autocorrelation, Risk Transmission and Contagion in the Global CDS Markets","authors":"Charlie X. Cai, May Hu, Xiaoxia Ye","doi":"10.2139/ssrn.3826385","DOIUrl":"https://doi.org/10.2139/ssrn.3826385","url":null,"abstract":"We show that the cross-autocorrelation also exists in the global CDS markets and develop an econometric model to capture the global correlation structure. We study implications on the credit risk transmission and contagion risk. We find four main results: (i) credit risk transmission is through the cross-correlation at regional rather than sectoral level; (ii) time-variation in financial sector's importance is caused by asymmetric responses to the positive and negative macro news; (iii) autocorrelation reduces the contagion risk in Asia while has little impact on other regions; (iv) contagion risks in the US and EU originate from sectors with international influence.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125631341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I summarize Dr. James Hunton’s research misconduct and then provide economics-based analysis related to some accounting community responses to his misconduct. One change made by some accounting journals was to introduce, highlight, or reinforce policies that spread responsibility for the research integrity of a paper among the paper’s co-authors. To explore this change, I create a model of publication incentives that demonstrates accounting researchers’ incentive to maximize the number of co-authors on each paper and minimize the amount they check each other’s work. From this model, I suggest that journal policy changes that focus on making co-authors responsible for data integrity alone may be too specific to Dr. Hunton’s exact method for research misconduct (i.e. data fabrication). Focusing on data integrity fails to address the incentive for researchers not to check each other’s work in all co-author roles, not just roles related to data integrity.
{"title":"Dr. Hunton’s Research Misconduct, Co-authorship Incentives, and Journal Policies Regarding Co-authors’ Responsibility","authors":"B. Knox","doi":"10.2139/ssrn.3501916","DOIUrl":"https://doi.org/10.2139/ssrn.3501916","url":null,"abstract":"I summarize Dr. James Hunton’s research misconduct and then provide economics-based analysis related to some accounting community responses to his misconduct. One change made by some accounting journals was to introduce, highlight, or reinforce policies that spread responsibility for the research integrity of a paper among the paper’s co-authors. To explore this change, I create a model of publication incentives that demonstrates accounting researchers’ incentive to maximize the number of co-authors on each paper and minimize the amount they check each other’s work. From this model, I suggest that journal policy changes that focus on making co-authors responsible for data integrity alone may be too specific to Dr. Hunton’s exact method for research misconduct (i.e. data fabrication). Focusing on data integrity fails to address the incentive for researchers not to check each other’s work in all co-author roles, not just roles related to data integrity.","PeriodicalId":130158,"journal":{"name":"DecisionSciRN: Econometric Decision Models (Topic)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134547920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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