《英国的金融脆弱性：从英国脱欧到COVID-19大流行.docx》由会员分享，可在线阅读，更多相关《英国的金融脆弱性：从英国脱欧到COVID-19大流行.docx（20页珍藏版）》请在taowenge.com淘文阁网|工程机械CAD图纸|机械工程制图|CAD装配图下载|SolidWorks_CaTia_CAD_UG_PROE_设计图分享下载上搜索。
1、:URBAN I N S T I T U T KBreno Braga, Sig ne-Mary McKernan, and William J. CongdonURBAN INSTITUTEElizabeth Mandiville, Mark Hayward, and Christopher TrepelLOWELLS EUROPEAN CONSUMER RESEARCH LABORATORYMarch 2021Financial well-being is multifaceted-reflecting peoples ability to manage daily finances, r
2、esilience to economic shocks (such as an income drop or unexpected expense), and capacity to pursue financial opportunities to move ahead. This brief provides new insights about the ability of UK families to manage daily finances and buffer against economic shocks. We developed an index that measure
3、s the overall extent of household financial vulnerability in the UK and its individual nations, regions, and parliamentary constituencies. We present our Financial Vulnerability Index findings from the third quarter of 2017 through to the second quarter of 2020, a three-year period covering the Brex
4、it transition and the early months of the COVID-19 pandemia This is the first in a series of ongoing insights.Using both Lowell research and operational data and publicly available data to build our index, we find that households in North East England are consistently more likely to be financially v
5、ulnerable than any other UK region or nation over the reported time period. In contrast, households in South East England are the least vulnerable. Blackpool South, Liverpool Walton, and Middlesbrough are the three most financially vulnerable constituencies in the second quarter (Q2) of 2020. Finall
6、y, we describe a rapid increase in financial distress during the COVID-19 pandemic across all UK nations and regions, with households in London experiencing the highest relative increase in financial vulnerability.What Do These Findings Mean?A households ability to manage daily finances and effectiv
7、ely respond to economic shocks is crucial to both household financial well-being and the economic health of communities (McKernan et al. 2016). During economic crises, financially healthy households can better weather the storm and contribute to economic recovery. But financial health, like economic
8、 recovery, is unevenly distributed. The FVI is designed to help national and local leaders assess the state of their constituentsfinancial health and target resources to advance an inclusive recovery.Financial vulnerability varies significantly across the United Kingdom. Many areas that have histori
9、cally relied on heavy industrial manufacturing (such as North East England and Middlesbrough) and some coastal towns (such as Blackpool South) showed consistently greater financial vulnerability than other parts of the UK from Q3 2017 through Q2 2020. We measure a rapid increase in financial hardshi
10、p in areas of London (such as Tottenham, Walthamstow, and East Ham) during the onset of the COVID-19 pandemic. The increase in household financial vulnerability in these areas might reflect changes in the labor market during the pandemic, as workers in London rely heavily on service jobs.The FVI rev
11、eals that UK household financial vulnerability was relatively stable in the period after Brexit Article 50 triggered, increased as Brexit negotiations and press coverage continued, and accelerated dramatically when the COVID-19 pandemic started. Future research could disentangle the causes of the in
12、crease in financial distress among households in the UK. For example, the descriptive results presented in this brief cannot tell us whether financial vulnerability caused Brexit, vice versa, or if other underlying trends or UK policies are driving the changes we observe.Appendix. Index Construction
13、Here we describe the construction of the Financial Vulnerability Index and provide additional detail on the index components, data sources, and analytic methods.Index ComponentsThe components used in the FVI are selected to capture different aspects offinancial vulnerability, with a focus on two fin
14、ancial well-being concepts: peoples ability to manage their daily finances and their resilience to economic shocks. The selection of specific financial or economic measures corresponding to those concepts depended, in part, on data quality and availability (see discussion of Data Sources below), Sta
15、rting with a list of 12 consumer financial indicators, the resulting index components are (1) carrying defaulted debt, (2) using alternative financial products, (3) claiming social benefits, (4) lacking emergency savings, (5) holding a high-cost loan, and (6) relying heavily on credit (table A.l).Th
16、e first three components capture an individuals ability to manage daily finances. Having debt in default indicates that people could not (or would not) pay certain bills. Using alternative financial products, such as payday loans, suggests that peoples needs are not met by their current incomesource
17、s or the traditional financial sector; it can also signal that people are having trouble managing their daily finances and have less access to safe, affordable loan products to help them weather unexpected financial needs. Applying for government assistance through Universal Credit or Jobseekers All
18、owance is often triggered by job loss or a negative income shock. It also indicates that a household cannot sustain itself without government help.The remaining three components principally capture peoples resilience to economic shocks. People without emergency savings are less likely able to weathe
19、r negative economic shocks. Having a high-cost loan signals low economic resilience and the need to use high-cost credit, while high average credit use reflects borrowing approaching, or at, the limit of the credit available to the consumer (indicating a lack of credit buffer).TABLE A. 1Components o
20、f the Financial Distress IndexTimeComponentDefinitionTypevariationShare of adults who are Lowell consumers in defaultNumber of Lowell consumers with defaulted debt divided by the adult population of the areaAbility to manage daily financesVariantShare of adults using alternative financial productsSh
21、are of adults with one or more of the following: hire purchase, rent-to-own (other than for a motor vehicle), payday loans, shortterm installment loans, home collected loans, pawnbroking, or logbook loansAbility to manage daily finances and resilienceInvariantShare of adults claiming social benefits
22、Number of Universal Credit claimants who are required to seek work plus the number of Jobseekers Allowance claimants divided by the adult population of the areaAbility to manage daily financesVariantShare of adults without emergency savingsShare of adults who have less than 5,000 in savingsResilienc
23、eInvariantShare of Lowell consumers with high- cost loansNumber of Lowell consumers with a subprime loan divided by the number of Lowell consumers in the areaResilienceVariantAverage credit use among Lowell consumersAverage ratio of cred it usage to credit limit for Lowell consumers in the areaAbili
24、ty to manage daily finances and resilienceVariantData SourcesData and measures for index components are from several sources, including Lowells research and operational data as well as publicly available data (table A.2), Lowell is one of the UKs largest firms engaged in the purchase and collection
25、of defaulted consumer debt The FVI relies principally on Lowell data for our measures of credit health, including the number of consumers in default, share of Lowell consumers with high-cost loans (loans with interest rates that are higherthanthe prime rate), and average credit use. These data inclu
26、de information on approximately nine million consumers (approximately 17.6 percent of all UK adults) and span both active accounts (as of July 2020) andaccounts closed after June 2018. These data also include residential postcodes, which we use to construct index values for different geographic regi
27、ons. Lowell consumers are typically in financial distress, having defaulted on at least one unsecured credit account (and often more than one), Lowell has detailed credit records for each consumer from two major credit reference agencies, including data on the balances ofall debt types, credit use,
28、and default indicators from Q3 2017 to Q2 2020.One potential concern with Lowells data is whether they are representative of the overall UK population. Although Lowell does not search for a specific consumer type, its consumers are typically in financial distress. As a result, Lowells consumer-level
29、 data are less likely to reflect the financial wellbeing of financially secure people. However, for the purposes of the index, the geographic distribution of Lowell consumers may well reflect the distribution of financially vulnerable consumers in the UK. To answer this question, we compare the loca
30、tion of Lowell consumers with other consumers in default using May 2020 credit record data grouped up to the NUTS3-level14 from one of the UKs major credit reference agencies.15 We find that Lowell consumers are located in the same local areas as other consumers in default and calculate a very stron
31、g (0.97) correlation between the share of adults who are Lowell consumers in default in a NUTS3 area and the share of consumers whose credit file contains a defaulted debt in the same area.We complement the Lowell data with publicly available data. The Office for National Statistics (ONS) releases n
32、ational and subnational midyear adult population estimates for the UK.16 Estimates are produced using the cohort component method, which updates the population base from census estimates based on population change. We linearly interpolate midyear population estimates to obtain a quarterly measure of
33、 the adult population at the parliamentary constituency level. These population estimates provide the denominator for our index components that are measured as adult population shares.For data on alternative financial products and emergency savings, we draw on the 2017 Financial Lives survey conduct
34、ed by the Financial Conduct Authority.17 This survey was administered in the first half of 2017 and asked approximately 13,000 UK adults about their financial situation and experiences with financial products using a random probability sample design based on respondents addresses. From this survey,
35、we obtain the share of adults who report using alternative financial products and the share without emergency savings at the NUTS2 level.18 Note two complicating features of these data for the purpose of building our index: first, because these data are not available at the parliamentary constituenc
36、y level, we assign values from the NUTS2 level to all parliamentary constituencies within that area. Second, because at the analysis stage ofthis brief we only observe a single observation for these measures, the two components of the FVI based on this source do not vary overtime in our tracking per
37、iod (as described in table A.l), Despite these limitations, we include these two components for two reasons: (1) they measure important aspects of peoples financial well-being from a nationally representative sample of adults that includes adults who are underbanked or credit invisible, which are mi
38、ssing from the Lowell data; (2) a second wave of the Financial Lives survey was released in 2021产 which will allow us to explore the time variation of these measures in future updates of the index.Finally, we use data from the Department of Work and Pensions (accessed via Nomis)20 on the number of p
39、eople who have submitted a claim for Universal Credit who are required to seek work and the number of Jobseekers Allowance claimants, both at the parliamentary constituency level. We combine these figures, expressed as a share of adults, to calculate our component measure: share claiming social bene
40、fits. This statistic seeks to measure the number of people claiming social benefits principally for unemployment, although those claiming unemployment-related benefits (either Universal Credit or the Jobseekers Allowance) may be fully unemployed and seeking work or may be employed but eligible for u
41、nemployment-related benefit support because of low income or low work hours.21 Consequently, while most movement in the claimant count reflects changes in the number of people who are out of work, to a lesser extent it also reflects workers who were furloughed or had their hours reduced.22TABLE A.2D
42、ata SourcesDatasource ComponentGeographic unit Time coverage FrequencyLowell research and operational dataLowell consumers in default, Lowell consumers with high-cost loans, average credit useParliament constituenciesPast three yearsMonthlyONS population estimatesAdult populationParliament constitue
43、ncies2017-18Annually2017 FinancialLives surveyShare using alternative financial products and share without emergency savingsNUTS22017Single observationNomis/Department forUniversal Credit claimants who are required to seek work plusParliament constituencies2017-20QuarterlyWork andJobseekers Allowanc
44、e claimantsPensionsIndex MethodologyTo create the FVI using observations for all parliamentary constituencies from Q3 2017 to Q2 2020, we first standardize each component of the index to create z-scores. This standardization process assures that we can aggregate components measured in different unit
45、s.Next, we select a suitable weighting and aggregation method. We use factor analysis23 to derive the weights for each component. The idea behind factor analysis is to account for the highest possible variation in the set of indicators using the smallest possible number of factors, which we define b
46、elow. This statistical procedure identifies the common variance among a set of observed variables (i.e, the index components) and creates a factor composed of that common variance. The factor scores are calculated with a linear equation that incorporates a weighted contribution of each variable incl
47、uded in the analysis. The weight of each variable is relative to the amount of variance it shares in common with the other variables. To perform the factor analysis, we use parliamentary constituency level observations from Q3 2017 to Q2 2020.Finally, we normalize the index to range from zero to 100
48、. To do that, we implement the following steps:1. Identify the lowest and highest values of each index component observed across all parliamentary constituencies during the period of analysis.2. Set the value of the index when each component is 1.1 times its highest observed value as equal to 100.3.
49、 Set the value of the index when each component is 0.4 times its lowest observed value as equal to zero.4. Normalize the index to all parliamentary constituencies during the period of analysis as the distance between these lowest and highest reference points.By making these adjustments, we ensure that index values calculated during the analysis are between zero and 100 and allow room for future index values, c