This chapter is to provide an overview of financial literacy in Asia, describe financial literacy education in Asian countries, and propose recommendations for policy makers. The chapter demonstrates that: 1) Financial literacy is an important factor contributing to consumer financial capability and wellbeing in Asia; 2) Financial literacy national strategies and education programs in Asian countries are beneficial for consumer wellbeing and economic developments; and 3) Public policies promoting financial literacy education can be compatible with the socio-economic development goals of Asian countries.
{"title":"Financial Literacy in Asia: A Scoping Review","authors":"J. Xiao","doi":"10.2139/ssrn.3743345","DOIUrl":"https://doi.org/10.2139/ssrn.3743345","url":null,"abstract":"This chapter is to provide an overview of financial literacy in Asia, describe financial literacy education in Asian countries, and propose recommendations for policy makers. The chapter demonstrates that: 1) Financial literacy is an important factor contributing to consumer financial capability and wellbeing in Asia; 2) Financial literacy national strategies and education programs in Asian countries are beneficial for consumer wellbeing and economic developments; and 3) Public policies promoting financial literacy education can be compatible with the socio-economic development goals of Asian countries.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129857973","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}
The debate on the intrinsic value of the U.S. Dollar has intensified recently and been an ongoing one, ever since 1971, when, President Richard Nixon, announced the abandonment of the Gold standard. In the debate on the intrinsic value of the Dollar, it may be argued, that Gold has been seen as a currency with an 'absolute worth' greater than all fiat currencies, due to Gold's historical acceptance power, and prominence as 'money.' With the abandonment of the Gold standard, and the Dollar, fundamentally, not being pegged to Gold, or any other units of intrinsic value, critics, ever since, have raised concerns regarding the absolute, or intrinsic value of the U.S. Dollar. This paper scrutinizes the intrinsic value of the U.S. Dollar, with an alternative perspective applied to gauge the Dollars' intrinsic value; the evaluation has been carried out through established financial models for a holistic assessment. The paper elaborates an alternative mechanism through which the Dollar derives its intrinsic value, and quantifies the nominal value backing the USD, $1079.3 trillion, and a real value, in 1970 Dollars, of $208.4 trillion; this value, aligned with the Gold standard peg of 1970, stands at 5.95 trillion ounces of Gold.
{"title":"Intrinsic Value of the Dollar: An Evaluation, and Scrutiny of the Absolute Worth of The U.S. Dollar.","authors":"Shahrukh Shafqat","doi":"10.2139/ssrn.3741880","DOIUrl":"https://doi.org/10.2139/ssrn.3741880","url":null,"abstract":"The debate on the intrinsic value of the U.S. Dollar has intensified recently and been an ongoing one, ever since 1971, when, President Richard Nixon, announced the abandonment of the Gold standard. In the debate on the intrinsic value of the Dollar, it may be argued, that Gold has been seen as a currency with an 'absolute worth' greater than all fiat currencies, due to Gold's historical acceptance power, and prominence as 'money.' With the abandonment of the Gold standard, and the Dollar, fundamentally, not being pegged to Gold, or any other units of intrinsic value, critics, ever since, have raised concerns regarding the absolute, or intrinsic value of the U.S. Dollar. This paper scrutinizes the intrinsic value of the U.S. Dollar, with an alternative perspective applied to gauge the Dollars' intrinsic value; the evaluation has been carried out through established financial models for a holistic assessment. The paper elaborates an alternative mechanism through which the Dollar derives its intrinsic value, and quantifies the nominal value backing the USD, $1079.3 trillion, and a real value, in 1970 Dollars, of $208.4 trillion; this value, aligned with the Gold standard peg of 1970, stands at 5.95 trillion ounces of Gold.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114850407","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 newly available data on initial prices, this study is the first to analyze the price updating process associated with corporate bond (CB) offerings. Similar to the case for equity IPOs, the evidence shows that bookbuilding theories help explain the CB offering price. In particular, CB price updates reduce underwriters' pricing errors. The partial adjustment phenomenon exists, and underwriters propose a lower initial price in cases of greater uncertainty. However, the CB price update has a large mean value and is smaller for lower-rated offerings, indicating that part of the CB price update is unrelated to investors' information production.
{"title":"Lifting the Veil: The Price Formation of Corporate Bond Offerings","authors":"Liying Wang","doi":"10.2139/ssrn.3541255","DOIUrl":"https://doi.org/10.2139/ssrn.3541255","url":null,"abstract":"Using newly available data on initial prices, this study is the first to analyze the price updating process associated with corporate bond (CB) offerings. Similar to the case for equity IPOs, the evidence shows that bookbuilding theories help explain the CB offering price. In particular, CB price updates reduce underwriters' pricing errors. The partial adjustment phenomenon exists, and underwriters propose a lower initial price in cases of greater uncertainty. However, the CB price update has a large mean value and is smaller for lower-rated offerings, indicating that part of the CB price update is unrelated to investors' information production.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124149110","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}
Between March and August 2020, S&P and Moody's downgraded approximately 25% of collateral feeding into CLOs and only 2% of tranche values, with rating actions concentrating in junior tranches. Both S&P and Moody's modeling indicate that the impacts should have been considerably larger, especially for higher-rated tranches. Neither changes in correlation nor the accumulation of pre-COVID-19 protective cushions can explain the downgrade asymmetry on upper tranches. Instead, CLO managers repositioned their collateral pools to dampen the negative credit shock and rating agencies incorporated qualitative adjustments in their CLO ratings. Important potential policy and market implications from these findings are discussed.
{"title":"Are CLO Collateral and Tranche Ratings Disconnected?","authors":"J. Griffin, Jordan Nickerson","doi":"10.2139/ssrn.3707557","DOIUrl":"https://doi.org/10.2139/ssrn.3707557","url":null,"abstract":"\u0000 Between March and August 2020, S&P and Moody's downgraded approximately 25% of collateral feeding into CLOs and only 2% of tranche values, with rating actions concentrating in junior tranches. Both S&P and Moody's modeling indicate that the impacts should have been considerably larger, especially for higher-rated tranches. Neither changes in correlation nor the accumulation of pre-COVID-19 protective cushions can explain the downgrade asymmetry on upper tranches. Instead, CLO managers repositioned their collateral pools to dampen the negative credit shock and rating agencies incorporated qualitative adjustments in their CLO ratings. Important potential policy and market implications from these findings are discussed.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123755735","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 construct a new measure of firm-level uncertainty from analyzing the text of mandatory reports filed with the U.S. Securities and Exchange Commission. Using firm and establishment level panel data on investment margins and employment dynamics, we find our uncertainty measure has large effects on investment even after controlling for industry and time-varying shocks. Periods of high firm uncertainty (1) reduce investment rates by 0.5% and attenuate the response to positive sales shocks by about half and (2) reduce employment growth rates by 1.4% and the response to positive sales shocks by 30%. Firms are less responsive to demand shocks at the firm level and across establishments within the firm. Consistent with “wait and see” dynamics, uncertainty affects new investment activity, e.g. plant births and acquisition, more than disinvestment margins.
{"title":"Measuring the Effects of Firm Uncertainty on Economic Activity: New Evidence from One Million Documents","authors":"Kyle Handley, J. Frank Li","doi":"10.3386/W27896","DOIUrl":"https://doi.org/10.3386/W27896","url":null,"abstract":"We construct a new measure of firm-level uncertainty from analyzing the text of mandatory reports filed with the U.S. Securities and Exchange Commission. Using firm and establishment level panel data on investment margins and employment dynamics, we find our uncertainty measure has large effects on investment even after controlling for industry and time-varying shocks. Periods of high firm uncertainty (1) reduce investment rates by 0.5% and attenuate the response to positive sales shocks by about half and (2) reduce employment growth rates by 1.4% and the response to positive sales shocks by 30%. Firms are less responsive to demand shocks at the firm level and across establishments within the firm. Consistent with “wait and see” dynamics, uncertainty affects new investment activity, e.g. plant births and acquisition, more than disinvestment margins.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"203 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132030268","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}
In this study, we estimate the effect of industry distress on recovery rates by using the unconditional quantile regression (UQR) proposed in Firpo, Fortin, and Lemieux (2009). The UQR provides better interpretative and thus policy-relevant information on the marginal effect of the covariates than the conditional quantile regression (CQR, Koenker and Bassett, 1978). To deal with a broad set of macroeconomic and industry variables, we use the LASSO-based double selection to identify the effects of industry distress and select variables.Our sample consists of 5,334 debt and loan instruments in Moody's Default and Recovery Database from 1990 to 2017. The results show that industry distress decreases recovery rates from 15.80% to 2.94% for the 15th to 55th percentile range and slightly increases the recovery rates in the lower and the upper tails. In contrast to the CQR, the UQR provide quantitative measurements to the loss given default during a downturn that the Basel Capital Accord requires.
在本研究中，我们使用Firpo、Fortin和Lemieux(2009)提出的无条件分位数回归(UQR)来估计行业困境对回收率的影响。与条件分位数回归(CQR, Koenker和Bassett, 1978)相比，UQR可以更好地解释协变量的边际效应，从而提供与政策相关的信息。为了处理广泛的宏观经济和行业变量，我们使用基于lasso的双重选择来识别行业困境的影响并选择变量。我们的样本包括穆迪违约和回收数据库中1990年至2017年的5334种债务和贷款工具。结果表明，在第15 ~ 55个百分位范围内，行业困境使回收率从15.80%降低到2.94%，并使下尾和上尾的回收率略有提高。与CQR相比，UQR提供了《巴塞尔资本协议》(Basel Capital Accord)所要求的经济衰退期间违约损失的量化衡量。
{"title":"Industry Distress and Default Recovery Rates: The Unconditional Quantile Regression Approach","authors":"Hui-Ching Chuang, Jau‐er Chen","doi":"10.2139/ssrn.3473161","DOIUrl":"https://doi.org/10.2139/ssrn.3473161","url":null,"abstract":"In this study, we estimate the effect of industry distress on recovery rates by using the unconditional quantile regression (UQR) proposed in Firpo, Fortin, and Lemieux (2009). The UQR provides better interpretative and thus policy-relevant information on the marginal effect of the covariates than the conditional quantile regression (CQR, Koenker and Bassett, 1978). To deal with a broad set of macroeconomic and industry variables, we use the LASSO-based double selection to identify the effects of industry distress and select variables.Our sample consists of 5,334 debt and loan instruments in Moody's Default and Recovery Database from 1990 to 2017. The results show that industry distress decreases recovery rates from 15.80% to 2.94% for the 15th to 55th percentile range and slightly increases the recovery rates in the lower and the upper tails. In contrast to the CQR, the UQR provide quantitative measurements to the loss given default during a downturn that the Basel Capital Accord requires.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125131225","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}
Lorenzo Bretscher, Peter Feldhütter, Andrew Kane, L. Schmid
Models of capital structure and credit risk make predictions about market valuations of debt, but are routinely tested on the basis of book debt from common data sources. In this paper, we propose to close this gap. We construct a rich data set on firm level debt market valuations by carefully matching data on corporate bond and loan secondary market transactions. We document significant discrepancies between market and book values, especially for distressed firms. We use our dataset to i) provide novel rules of thumb on how to adjust leverage and unlever returns using standard datasets, and ii) to revisit a number of prominent empirical patterns involving corporate debt. Using a market-based measure of Tobin's Q, we find little evidence for investment cash-flow sensitivity in our data. We find that using market debt values significantly improves default prediction, and do not detect a credit spread puzzle. In asset pricing tests, we find a leverage premium, but no evidence for a value premium after controlling for market leverage. Moreover, a novel measure of financial distress, namely market-to-book debt, predicts stock returns positively in the cross-section, inconsistent with a financial distress puzzle.
{"title":"Marking to Market Corporate Debt","authors":"Lorenzo Bretscher, Peter Feldhütter, Andrew Kane, L. Schmid","doi":"10.2139/ssrn.3681817","DOIUrl":"https://doi.org/10.2139/ssrn.3681817","url":null,"abstract":"Models of capital structure and credit risk make predictions about market valuations of debt, but are routinely tested on the basis of book debt from common data sources. In this paper, we propose to close this gap. We construct a rich data set on firm level debt market valuations by carefully matching data on corporate bond and loan secondary market transactions. We document significant discrepancies between market and book values, especially for distressed firms. We use our dataset to i) provide novel rules of thumb on how to adjust leverage and unlever returns using standard datasets, and ii) to revisit a number of prominent empirical patterns involving corporate debt. Using a market-based measure of Tobin's Q, we find little evidence for investment cash-flow sensitivity in our data. We find that using market debt values significantly improves default prediction, and do not detect a credit spread puzzle. In asset pricing tests, we find a leverage premium, but no evidence for a value premium after controlling for market leverage. Moreover, a novel measure of financial distress, namely market-to-book debt, predicts stock returns positively in the cross-section, inconsistent with a financial distress puzzle.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117245848","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}
The U.S. Securities and Exchange Commission (SEC) rolled out Market Information Data Analytics System (MIDAS) in 2013 which is:
“…the SEC’s implementation of a new system that combines advanced technologies with empirical data to promote better understanding of markets….”
This paper uses available public, peer-re-viewable data, and operational outcomes to assess SEC MIDAS reported public data. These public data and outcomes demonstrate that SEC MIDAS data is incomplete. In particular, transactions effected otherwise than on an exchange and reported though the three FINRA Trade Reporting Facilities (TRFs) are not included in SEC MIDAS data.
SEC MIDAS is expected to be a comprehensive research facility with collected data from self-regulatory organizations, trading venues, and proprietary sources. Essential SEC rule making offices such as the Division of Economic and Risk Analysis (DERA) and Division of Trading and Markets rely on MIDAS data. Both the public and the academic and economic groups have an expectation that MIDAS data and research using MIDAS data promotes empirical understanding of market hypotheses, market behavior, and market regulation.
{"title":"U.S. Securities and Exchange Commission MIDAS Market Information Data Analytics System: An Observation","authors":"Fred Sommers","doi":"10.2139/ssrn.3692464","DOIUrl":"https://doi.org/10.2139/ssrn.3692464","url":null,"abstract":"The U.S. Securities and Exchange Commission (SEC) rolled out Market Information Data Analytics System (MIDAS) in 2013 which is:<br><br>“…the SEC’s implementation of a new system that combines advanced technologies with empirical data to promote better understanding of markets….”<br><br>This paper uses available public, peer-re-viewable data, and operational outcomes to assess SEC MIDAS reported public data. These public data and outcomes demonstrate that SEC MIDAS data is incomplete. In particular, transactions effected otherwise than on an exchange and reported though the three FINRA Trade Reporting Facilities (TRFs) are not included in SEC MIDAS data. <br><br>SEC MIDAS is expected to be a comprehensive research facility with collected data from self-regulatory organizations, trading venues, and proprietary sources. Essential SEC rule making offices such as the Division of Economic and Risk Analysis (DERA) and Division of Trading and Markets rely on MIDAS data. Both the public and the academic and economic groups have an expectation that MIDAS data and research using MIDAS data promotes empirical understanding of market hypotheses, market behavior, and market regulation.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"62 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132442706","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 public-sourced case describes the latest restructuring efforts by Deutsche Bank (DB) and gives a short history of prior restructuring efforts from the decade before. In July 2019, Christian Sewing, the new CEO of DB, announced a series of measures that included, among others, the elimination of global equity trading, the layoff of 18,000 employees, the creation of a "bad bank" to transfer noncore assets, and the suspension of dividends until 2022. The case describes key decisions a bank CEO makes when a bank needs to change course to return to profitability and growth. The case offers an opportunity to debate these key decisions, as well as discuss some of the prior ones during earlier restructuring efforts, and put the students in the CEO's shoes: What would you do and why? The case also describes key banking performance metrics (e.g., ROE, ROA) and other critical variables such as those reflecting capital health (Tier 1 ratio), as well as gives an overview of the bank business model and factors impacting bank profitability and value. Excerpt UVA-F-1934 Feb. 26, 2020 Deutsche Bank Restart: Goodbye Goldman Sachs of Europe? What is our north star, when reshaping Deutsche Bank? –CEO Christian Sewing In July 2019, on a day of massive employee layoffs at Deutsche Bank—mostly in its equity sales and trading business—two executives made headlines for having new USD1,800 suits fitted at the office. Their out-of-touch leadership behavior did little for the struggling German bank's reputation. And it drew the ire and a phone call from CEO Christian Sewing. "In no way is this behavior in keeping with our values," Sewing said. "I assume in any case that the two colleagues will not forget my telephone call." (See Appendix1 for the company's mission statement.) . . .
{"title":"Deutsche Bank Restart: Goodbye Goldman Sachs of Europe?","authors":"G. Allayannis, Gerry Yemen, P. Holtz","doi":"10.2139/ssrn.3682595","DOIUrl":"https://doi.org/10.2139/ssrn.3682595","url":null,"abstract":"This public-sourced case describes the latest restructuring efforts by Deutsche Bank (DB) and gives a short history of prior restructuring efforts from the decade before. In July 2019, Christian Sewing, the new CEO of DB, announced a series of measures that included, among others, the elimination of global equity trading, the layoff of 18,000 employees, the creation of a \"bad bank\" to transfer noncore assets, and the suspension of dividends until 2022. The case describes key decisions a bank CEO makes when a bank needs to change course to return to profitability and growth. The case offers an opportunity to debate these key decisions, as well as discuss some of the prior ones during earlier restructuring efforts, and put the students in the CEO's shoes: What would you do and why? The case also describes key banking performance metrics (e.g., ROE, ROA) and other critical variables such as those reflecting capital health (Tier 1 ratio), as well as gives an overview of the bank business model and factors impacting bank profitability and value. \u0000 \u0000Excerpt \u0000 \u0000UVA-F-1934 \u0000 \u0000Feb. 26, 2020 \u0000 \u0000Deutsche Bank Restart: Goodbye Goldman Sachs of Europe? \u0000 \u0000What is our north star, when reshaping Deutsche Bank? \u0000 \u0000–CEO Christian Sewing \u0000 \u0000In July 2019, on a day of massive employee layoffs at Deutsche Bank—mostly in its equity sales and trading business—two executives made headlines for having new USD1,800 suits fitted at the office. Their out-of-touch leadership behavior did little for the struggling German bank's reputation. And it drew the ire and a phone call from CEO Christian Sewing. \"In no way is this behavior in keeping with our values,\" Sewing said. \"I assume in any case that the two colleagues will not forget my telephone call.\" (See Appendix1 for the company's mission statement.) \u0000 \u0000. . .","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132615855","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}
Columbia University- Columbia Center on Sustainable Investment, (RMF) The Responsible Mining Foundation
The mining industry, through its extensive activities and prominent presence in developing countries, has strong linkages with issues covered in all 17 of the UN Sustainable Development Goals (SDGs). These linkages are clearly set out in the 2016 Mapping Mining to the Sustainable Development Goals: An Atlas, produced by the Columbia Center on Sustainable Investment, the United Nations Development Programme, the United Nations Sustainable Development Solutions Network and the World Economic Forum. With just ten years left to achieve the Sustainable Development Goals by the target date of 2030 and four years after the publication of the Atlas, this report provides a status update of what large-scale mining companies are currently doing to integrate the SDGs into their business strategies and to take proactive measures that will help deliver these Goals. It is also a reminder of the opportunities that the mining industry has to positively influence achievement of the SDGs, and simultaneously a caution on the inherent risks that mining activities pose that might impede the achievement of the SDGs. This influence that the mining industry can bring to bear is all the more important given the serious implications of the COVID-19 on progress to achieve the SDGs.
{"title":"Mining and the SDGs: A 2020 Status Update","authors":"Columbia University- Columbia Center on Sustainable Investment, (RMF) The Responsible Mining Foundation","doi":"10.2139/ssrn.3726386","DOIUrl":"https://doi.org/10.2139/ssrn.3726386","url":null,"abstract":"The mining industry, through its extensive activities and prominent presence in developing countries, has strong linkages with issues covered in all 17 of the UN Sustainable Development Goals (SDGs). These linkages are clearly set out in the 2016 Mapping Mining to the Sustainable Development Goals: An Atlas, produced by the Columbia Center on Sustainable Investment, the United Nations Development Programme, the United Nations Sustainable Development Solutions Network and the World Economic Forum. With just ten years left to achieve the Sustainable Development Goals by the target date of 2030 and four years after the publication of the Atlas, this report provides a status update of what large-scale mining companies are currently doing to integrate the SDGs into their business strategies and to take proactive measures that will help deliver these Goals. It is also a reminder of the opportunities that the mining industry has to positively influence achievement of the SDGs, and simultaneously a caution on the inherent risks that mining activities pose that might impede the achievement of the SDGs. This influence that the mining industry can bring to bear is all the more important given the serious implications of the COVID-19 on progress to achieve the SDGs.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132110836","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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