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This dataset, Negative Equity in the US Housing Market, provides an in-depth look into the negative equity occurring across the United States during this single quarter. Included are metrics such as total amount of negative equity in millions of dollars, total number of homes in negative equity, percentage of homes with mortgages that are in negative equity and more. These data points provide helpful insights into both regional and national trends regarding the prevalence and rate of home mortgage delinquency stemming from a diminishment of value from peak levels.
Home types available for analysis include 'all homes', condos/co-ops, multifamily units containing five or more housing units as well as duplexes/triplexes. Additionally, Cash buyers rates for particular areas can also be determined by referencing this collection. Further metrics such as mortgage affordability rates and impacts on overall indebtedness are readily calculated using information related to Zillow's Home Value Index (ZHVI) forecast methodology and TransUnion data respectively.
Other variables featured within this dataset include characteristics like region type (i.e city, county ..etc), size rank based on population values , percentage change in ZHVI since peak levels as well as loan-to-value ratio greater than 200 across all regions constituted herein (NE). Moreover Zillow's own Secondary Mortgage Market Survey data is utilized to acquire average mortgage quote rates while correlative Census Bureau NCHS median household income figures represent typical assessable proportions between wages and debt obligations . So whether you're looking to assess effects along metro lines or detailed buffering through zip codes , this database should prove sufficient for insightful explorations! Nonetheless users must strictly adhere to all conditions encompassed within Terms Of Use commitments put forth by our lead provider before accessing any resources included herewith
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
- Analyzing regional and state trends in negative equity: Analyze geographic differences in the percentage of mortgages “underwater”, total amount of negative equity, number of homes at least 90 days late, and other key indicators to provide insight into the factors influencing negative equity across regions, states and cities.
- Tracking the recovery rate over time: Track short-term changes in numbers related to negative equity (e.g., region or area ZHVI Change from Peak) to monitor recovery rates over time as well as how different policy interventions are affecting homeownership levels in affected areas.
- Exploring best practices for promoting housing affordability: Compare affordability metrics (e.g., mortgage payments, price-to-income ratios) across different geographic locations over time to identify best practices for empowering homeowners and promoting stability within the housing market while reducing local inequality impacts related to availability of affordable housing options and access to credit markets like mortgages/loans etc
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: NESummary_2017Q1_Public.csv | Column name | Description | |:------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| | RegionType | The type of region (e.g., city, county, metro etc.) (String) | | City | Name of the city (String) | | County | Name of the county (String) | | State | Name of the state (String) | | Metro ...
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TwitterAmount of debt outstanding as of June 30 of each year. SOURCES: IBO; New York City Comprehensive Annual Financial Report of the Comptroller (various years); Annual Report of the Comptroller on Capital Debt and Obligations (various years); New York City Municipal Water Finance Authority Comprehensive Annual Financial Reports (various years) NOTES: 1In determining what to include as outstanding debt of the City of New York, IBO considered: (1) the city's obligation (contractual and moral) to repay the debt, (2) whether the revenues pledged toward the repayment of the debt would have otherwise accrued to the city, and (3) whether the proceeds of the debt issuance accrue directly to the city. 2GO debt is net of bonds held for debt service on other city-related obligations, referred to in the Comptroller's Comprehensive Annual Financial Report (CAFR) as Treasury Obligations. The 2000–2002 CAFRs show outstanding general obligation debt, before Treasury Obligations, in 2000 and 2001 as $26,892 million and $26,836 million, respectively. However, CAFRs from 2003 on show higher GO debt for the two years, $353 million more for 2000 and $311 million more for 2001; the 2003 CAFR does not provide a note explaining the revisions. IBO uses the numbers reported from 2003 forward. 3Fiscal years 2000, 2002, and 2003 include short-term bond anticipation notes outstanding at year-end of $515 million, $2.2 billion, and $1.1 billion, respectively. 4For fiscal year 2000, Capital Lease Obligations to HHC and PCDC are reported jointly. 5In FY 2008, JSDC bonds outstanding were redeemed with GO bond proceeds, resulting in the elimination of JSDC debt, a reduction in conduit debt outstanding and partially accounting for the increase in GO debt from 2007 to 2008 General Obligation: General obligation bonds are backed by the full faith and credit of the city. City property tax collections are pledged first to pay the principal and interest on these bonds. Treasury Obligations: Treasury obligations are New York City bonds held as investments by the city or by the related entities covered here, including MAC and SFC. They are netted out in order to avoid double counting of the city's obligations. Transitional Finance Authority: Created in 1997, the Transitional Finance Authority (TFA) is a separate legal entity from the City of New York. TFA General Purpose Bonds are secured by the city's collections of personal income tax and, if necessary, sales tax. Recovery Bonds, issued in response to the events of September 11, 2001 differ from general purpose bonds in that they are excluded from the calculation of outstanding TFA debt allowed under the debt limit. TFA Building Aid Revenue Bonds: In fiscal year 2006, the city was authorized by the state Legislature to assign to the TFA all or any portion of the state building aid payable to the city or its school district. The TFA in turn is authorized to issue bonds secured by the aid and dedicated to financing a portion of the city's educational facilities capital plan. TSASC: TSASC Inc. (formerly known as the Tobacco Settlement Asset Securitization Corporation) is a separate legal entity from the City of New York. TSASC bonds are secured by the corporation's purchase from the city of the future revenue stream under a settlement agreement resolving cigarette smoking-related litigation between the settling states and participating manufacturers. Municipal Assistance Corporation for the City of New York: The Municipal Assistance Corporation (MAC) was a separate legal entity from the City of New York, created in 1975 and formally dissolved in 2008. With New York City experiencing a severe fiscal crisis in 1975, MAC allowed the city continued access to credit markets and assisted in the prevention of a default of city general obligation bonds. MAC bonds were secured by state collections of
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Both climate risk and race are factors that may affect municipal bond yields, yet each has received relatively limited empirical research attention. We analyzed > 712,000 municipal bonds representing nearly 2 trillion USD in par outstanding, focusing on credit spread or the difference between a debt issuer’s interest cost to borrow and a benchmark “risk-free” municipal rate. The relationship between credit spread and physical climate risk is significant and slightly positive, yet the coefficient indicates no meaningful spread penalty for increased physical climate risk. We also find that racial composition (the percent of a community that is Black) explains a statistically significant and meaningful portion of municipal credit spreads, even after controlling for a variety of variables in domains such as geographic location of issuer, bond structure (e.g., bond maturity), credit rating, and non-race economic variables (e.g., per capita income). Assuming 4 trillion USD in annual outstanding par across the entire municipal market, and weighting each issuer by its percent Black, an estimated 19 basis point (bp) penalty for Black Americans sums to approximately 900 million USD annually in aggregate. Our combined findings indicate a systemic mispricing of risk in the municipal bond market, where race impacts the cost of capital, and climate does not.
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Facebook
TwitterBy Zillow Data [source]
This dataset, Negative Equity in the US Housing Market, provides an in-depth look into the negative equity occurring across the United States during this single quarter. Included are metrics such as total amount of negative equity in millions of dollars, total number of homes in negative equity, percentage of homes with mortgages that are in negative equity and more. These data points provide helpful insights into both regional and national trends regarding the prevalence and rate of home mortgage delinquency stemming from a diminishment of value from peak levels.
Home types available for analysis include 'all homes', condos/co-ops, multifamily units containing five or more housing units as well as duplexes/triplexes. Additionally, Cash buyers rates for particular areas can also be determined by referencing this collection. Further metrics such as mortgage affordability rates and impacts on overall indebtedness are readily calculated using information related to Zillow's Home Value Index (ZHVI) forecast methodology and TransUnion data respectively.
Other variables featured within this dataset include characteristics like region type (i.e city, county ..etc), size rank based on population values , percentage change in ZHVI since peak levels as well as loan-to-value ratio greater than 200 across all regions constituted herein (NE). Moreover Zillow's own Secondary Mortgage Market Survey data is utilized to acquire average mortgage quote rates while correlative Census Bureau NCHS median household income figures represent typical assessable proportions between wages and debt obligations . So whether you're looking to assess effects along metro lines or detailed buffering through zip codes , this database should prove sufficient for insightful explorations! Nonetheless users must strictly adhere to all conditions encompassed within Terms Of Use commitments put forth by our lead provider before accessing any resources included herewith
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
- Analyzing regional and state trends in negative equity: Analyze geographic differences in the percentage of mortgages “underwater”, total amount of negative equity, number of homes at least 90 days late, and other key indicators to provide insight into the factors influencing negative equity across regions, states and cities.
- Tracking the recovery rate over time: Track short-term changes in numbers related to negative equity (e.g., region or area ZHVI Change from Peak) to monitor recovery rates over time as well as how different policy interventions are affecting homeownership levels in affected areas.
- Exploring best practices for promoting housing affordability: Compare affordability metrics (e.g., mortgage payments, price-to-income ratios) across different geographic locations over time to identify best practices for empowering homeowners and promoting stability within the housing market while reducing local inequality impacts related to availability of affordable housing options and access to credit markets like mortgages/loans etc
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: NESummary_2017Q1_Public.csv | Column name | Description | |:------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| | RegionType | The type of region (e.g., city, county, metro etc.) (String) | | City | Name of the city (String) | | County | Name of the county (String) | | State | Name of the state (String) | | Metro ...