This report examines the role that the use of alternative documentation of income (ADOI) plays in driving racial disparities in access to Income-Driven Repayment (IDR) for student loan borrowers. In doing so, it underscores how breakdowns in IDR are a clear civil rights issue. In order to enroll in IDR, borrowers must document income and family size by either (1) providing a tax return or (2) work with their servicer to submit an ADOI. While there is no publicly available data on the IDR application process and resulting outcomes, research shows Black borrowers disproportionately struggle in paying back federal student loans than their white peers, contributing to disparities in delinquency and default. By drawing parallels between borrower experiences avoiding default in via IDR and the Home Affordable Modification Program (HAMP), the paper questions whether ADOI is providing a viable path for student debt relief for vulnerable federal borrowers.
{"title":"Driving Inequity: Are IDR’s Documentation Requirements Hurting Borrowers of Color?","authors":"J. Pearl","doi":"10.2139/ssrn.3933430","DOIUrl":"https://doi.org/10.2139/ssrn.3933430","url":null,"abstract":"This report examines the role that the use of alternative documentation of income (ADOI) plays in driving racial disparities in access to Income-Driven Repayment (IDR) for student loan borrowers. In doing so, it underscores how breakdowns in IDR are a clear civil rights issue. In order to enroll in IDR, borrowers must document income and family size by either (1) providing a tax return or (2) work with their servicer to submit an ADOI. While there is no publicly available data on the IDR application process and resulting outcomes, research shows Black borrowers disproportionately struggle in paying back federal student loans than their white peers, contributing to disparities in delinquency and default. By drawing parallels between borrower experiences avoiding default in via IDR and the Home Affordable Modification Program (HAMP), the paper questions whether ADOI is providing a viable path for student debt relief for vulnerable federal borrowers.","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131544862","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 a field experiment that constructs a randomized credit limit shock, participants borrow to spend 11 cents on the dollar in the first quarter and 28 cents by the third year. Effects extend to those far from the limit, those who had the new limits as available credit, and those with a liquid asset buffer. In the short-run, flexible and installment contracts are used in tandem, with unconstrained using installments more. Long-run borrowing is predominantly using installments. Near limits, participants borrow when credit expands but save out of constraints when limits are tight. Findings support a buffer-stock interpretation emphasizing precautionary saving. (JEL C93, E21, G21, G51, O12, O16)
{"title":"Consumption Response to Credit Expansions: Evidence from Experimental Assignment of 45,307 Credit Lines","authors":"Deniz Aydin","doi":"10.2139/ssrn.3794759","DOIUrl":"https://doi.org/10.2139/ssrn.3794759","url":null,"abstract":"In a field experiment that constructs a randomized credit limit shock, participants borrow to spend 11 cents on the dollar in the first quarter and 28 cents by the third year. Effects extend to those far from the limit, those who had the new limits as available credit, and those with a liquid asset buffer. In the short-run, flexible and installment contracts are used in tandem, with unconstrained using installments more. Long-run borrowing is predominantly using installments. Near limits, participants borrow when credit expands but save out of constraints when limits are tight. Findings support a buffer-stock interpretation emphasizing precautionary saving. (JEL C93, E21, G21, G51, O12, O16)","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127297455","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}
A successful long-term financial plan depends on the correspondence of projected returns and actual returns. Simulation results are subject to the effects of differences between implementation fund(s) attributes and asset class attributes used in the simulation. Thus, simulation outcomes and portfolio outcomes may be materially different. We would like to know that if the forecasted returns in our simulations are correct, the actual returns will be the same as the forecasted returns. β1 Indexing® addresses these issues with a guideline that uses reasonably available information: Best-Fit β and R-squared. β1-Indexing® and Beta1-Indexing® are registered trademarks of Vernon V Chatman III, CFP®.
一个成功的长期财务计划取决于预期收益和实际收益的一致性。模拟结果受到实施基金属性和模拟中使用的资产类别属性之间差异的影响。因此，模拟结果和投资组合结果可能有本质上的不同。我们想知道，如果我们模拟中的预测收益是正确的，那么实际收益将与预测收益相同。β1 Indexing®通过使用合理可用信息的指南来解决这些问题:Best-Fit β和R-squared。β1-Indexing®和Beta1-Indexing®是Vernon V Chatman III, CFP®的注册商标。
{"title":"β1-Indexing®: Making Financial Simulation Relevant in Practice","authors":"Vernon V Chatman III","doi":"10.2139/ssrn.3609505","DOIUrl":"https://doi.org/10.2139/ssrn.3609505","url":null,"abstract":"A successful long-term financial plan depends on the correspondence of projected returns and actual returns. Simulation results are subject to the effects of differences between implementation fund(s) attributes and asset class attributes used in the simulation. Thus, simulation outcomes and portfolio outcomes may be materially different. We would like to know that if the forecasted returns in our simulations are correct, the actual returns will be the same as the forecasted returns. β1 Indexing® addresses these issues with a guideline that uses reasonably available information: Best-Fit β and R-squared. β1-Indexing® and Beta1-Indexing® are registered trademarks of Vernon V Chatman III, CFP®.","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124251739","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 have performed a series of five strategic analyses of Japanese Megabanks. This paper is the last analysis in the series, where we compare RUFG and key competitors using a ‘strategy canvas’ to assess competitiveness. Furthermore we evaluate the prospect of finding ‘blue ocean’ opportunities to exploit, where profit margins are wider and markets are not congested.
{"title":"Strategic Analysis of Japanese Megabanks – Strategy Canvas Analysis & Competitor Benchmarking","authors":"N. Burgess","doi":"10.2139/ssrn.3660679","DOIUrl":"https://doi.org/10.2139/ssrn.3660679","url":null,"abstract":"We have performed a series of five strategic analyses of Japanese Megabanks. This paper is the last analysis in the series, where we compare RUFG and key competitors using a ‘strategy canvas’ to assess competitiveness. Furthermore we evaluate the prospect of finding ‘blue ocean’ opportunities to exploit, where profit margins are wider and markets are not congested.","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"1984 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125462094","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}
Nowadays, financial education in a developing country believed to be important as it affects the individual well-being, the national economic growth and the stability of financial markets. Supporting financial education conveys youth empowerment through increasing their income as entrepreneurs, managing their money (incomes, salaries or other benefits) through planning spending and savings, fostering financial inclusion through recognition of financial products, risk management and protection from asymmetric information. Albanians continue to be among people who love education and invest in professions that might enable them to make more money, but they have little or no opportunities to learn about managing their money. Today, almost 4 years after the approval of the National Strategy for Development and Integration (NSDI), this paper based on data analysis of young Albanians perceptions conclude that the national objective of “empowering youth” is considered over 60% unattained, affected also by an outdated strategy on education and on development of a supporting financial education for Albanian youngsters in particular. Government, regulators and private organizations must collaborate and invest in the financial education of youth, for the future will be the product of such efforts that are made today.
{"title":"Issues Related to Financial Education of Youth in a Developing Country (The Case of Albanian Youth)","authors":"Artur Ribaj","doi":"10.2139/ssrn.3598539","DOIUrl":"https://doi.org/10.2139/ssrn.3598539","url":null,"abstract":"Nowadays, financial education in a developing country believed to be important as it affects the individual well-being, the national economic growth and the stability of financial markets. Supporting financial education conveys youth empowerment through increasing their income as entrepreneurs, managing their money (incomes, salaries or other benefits) through planning spending and savings, fostering financial inclusion through recognition of financial products, risk management and protection from asymmetric information. Albanians continue to be among people who love education and invest in professions that might enable them to make more money, but they have little or no opportunities to learn about managing their money. Today, almost 4 years after the approval of the National Strategy for Development and Integration (NSDI), this paper based on data analysis of young Albanians perceptions conclude that the national objective of “empowering youth” is considered over 60% unattained, affected also by an outdated strategy on education and on development of a supporting financial education for Albanian youngsters in particular. Government, regulators and private organizations must collaborate and invest in the financial education of youth, for the future will be the product of such efforts that are made today.","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133761254","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 direct measures of capital costs, equal to the product of the required rate of return on capital and the value of the capital stock. The capital share, equal to the ratio of capital costs and gross value added, does not offset the decline in the labor share. Instead, a large increase in the share of pure profits offsets declines in the shares of both labor and capital. Industry data show that increases in concentration are associated with declines in the labor share.
{"title":"Declining Labor and Capital Shares","authors":"Simcha Barkai","doi":"10.2139/ssrn.3489965","DOIUrl":"https://doi.org/10.2139/ssrn.3489965","url":null,"abstract":"This paper presents direct measures of capital costs, equal to the product of the required rate of return on capital and the value of the capital stock. The capital share, equal to the ratio of capital costs and gross value added, does not offset the decline in the labor share. Instead, a large increase in the share of pure profits offsets declines in the shares of both labor and capital. Industry data show that increases in concentration are associated with declines in the labor share.","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115438491","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}
Pub Date : 2019-05-01DOI: 10.5089/9781498314428.001
Majid Bazarbash
Recent advances in digital technology and big data have allowed FinTech (financial technology) lending to emerge as a potentially promising solution to reduce the cost of credit and increase financial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credit have remained largely a black box for the nontechnical audience. This paper contributes to the literature by discussing potential strengths and weaknesses of ML-based credit assessment through (1) presenting core ideas and the most common techniques in ML for the nontechnical audience; and (2) discussing the fundamental challenges in credit risk analysis. FinTech credit has the potential to enhance financial inclusion and outperform traditional credit scoring by (1) leveraging nontraditional data sources to improve the assessment of the borrower’s track record; (2) appraising collateral value; (3) forecasting income prospects; and (4) predicting changes in general conditions. However, because of the central role of data in ML-based analysis, data relevance should be ensured, especially in situations when a deep structural change occurs, when borrowers could counterfeit certain indicators, and when agency problems arising from information asymmetry could not be resolved. To avoid digital financial exclusion and redlining, variables that trigger discrimination should not be used to assess credit rating.
{"title":"Fintech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk","authors":"Majid Bazarbash","doi":"10.5089/9781498314428.001","DOIUrl":"https://doi.org/10.5089/9781498314428.001","url":null,"abstract":"Recent advances in digital technology and big data have allowed FinTech (financial technology) lending to emerge as a potentially promising solution to reduce the cost of credit and increase financial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credit have remained largely a black box for the nontechnical audience. This paper contributes to the literature by discussing potential strengths and weaknesses of ML-based credit assessment through (1) presenting core ideas and the most common techniques in ML for the nontechnical audience; and (2) discussing the fundamental challenges in credit risk analysis. FinTech credit has the potential to enhance financial inclusion and outperform traditional credit scoring by (1) leveraging nontraditional data sources to improve the assessment of the borrower’s track record; (2) appraising collateral value; (3) forecasting income prospects; and (4) predicting changes in general conditions. However, because of the central role of data in ML-based analysis, data relevance should be ensured, especially in situations when a deep structural change occurs, when borrowers could counterfeit certain indicators, and when agency problems arising from information asymmetry could not be resolved. To avoid digital financial exclusion and redlining, variables that trigger discrimination should not be used to assess credit rating.","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124846182","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 step-by-step guide, we show you how to use the Free Rent Calculator, which provides an accurate, visual means to quantify the impact of concessions in commercial leases based on the market conditions and landlord’s risk profile. The calculator allows both landlords and tenants to benchmark the impact of free rent, tenant improvements, and moving allowance on a given set of the asking and offering rents. The calculator determines the resulting effective rent, which is equivalent to the tenant paying a constant base rent over the entire lease term.1 The effective rent serves as a comparison benchmark, allowing users to quickly see the impact of changes to the asking rent and concession package. The tool works by allowing users to specify the structure of the rental payments, tenant improvements (TIs), and the moving allowance, and then computes the maximum free rent period in light of the specified lease terms and concessions. Landlords can use the tool to fine-tune the concession package by determining the appropriate level of free rent that seems attractive without increasing exposure to tenant default. Tenants can use the tool to optimize the free rent and concession structure to create the most desirable pattern of monthly cash outflows from the available options.
{"title":"Guide to Using the Free Rent Calculator","authors":"Peng Liu, Luoyi Su, Jan A. Deroos","doi":"10.2139/ssrn.3743068","DOIUrl":"https://doi.org/10.2139/ssrn.3743068","url":null,"abstract":"In this step-by-step guide, we show you how to use the Free Rent Calculator, which provides an accurate, visual means to quantify the impact of concessions in commercial leases based on the market conditions and landlord’s risk profile. The calculator allows both landlords and tenants to benchmark the impact of free rent, tenant improvements, and moving allowance on a given set of the asking and offering rents. The calculator determines the resulting effective rent, which is equivalent to the tenant paying a constant base rent over the entire lease term.1 The effective rent serves as a comparison benchmark, allowing users to quickly see the impact of changes to the asking rent and concession package. The tool works by allowing users to specify the structure of the rental payments, tenant improvements (TIs), and the moving allowance, and then computes the maximum free rent period in light of the specified lease terms and concessions. Landlords can use the tool to fine-tune the concession package by determining the appropriate level of free rent that seems attractive without increasing exposure to tenant default. Tenants can use the tool to optimize the free rent and concession structure to create the most desirable pattern of monthly cash outflows from the available options.","PeriodicalId":340287,"journal":{"name":"FinPlanRN: Other Finance Planning Fundamentals (Topic)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115187007","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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