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1、<p><b>  中文5640字</b></p><p><b>  外文翻譯</b></p><p>  The Determinants of Consumer Credit:A Review of the Literature</p><p>  Material Source: Consumer Cre

2、dit in Europe Author: Daniela Vandone</p><p>  1 Introduction</p><p>  The literature of consumer credit is sizeable. Such a body of work reflects notonly the composite nature of unsecured

3、 debt, but also the fact that differentmethodological approaches exist depending on the research questions under analysis and the objectives sought.Four main approaches can be seen: a management approach, which focuses o

4、n the characteristics of the credit industry, its workings and the policies adopted by supply-side players; a legal approach, which investigates the impact the reg</p><p>  In this chapter we will discuss th

5、e economic approach with the aim of providing an outline of the individual and institutional factors that are considered in the literature as determinants of consumer credit.The economic models referred to are based on t

6、he economic rationality of individuals, who seek to increase living standards by smoothing consumption over different periods of their lives through saving and borrowing decisions. According to these models, consumer cre

7、dit demand and supply is d</p><p>  2 The Life-Cycle and Permanent Income Theories</p><p>  The theoretical economic framework for consumption, saving and indebtedness decisions is developed wit

8、hin the Life-Cycle theory, developed by Modigliani and Brumberg in 1954, and the Permanent Income Hypothesis, proposed by Friedman in 1957. The central idea of these intertemporal consumption choice models is that househ

9、olds make their consumption choices (and consequently those relating to saving and indebtedness) on the basis of their wealth, current disposable income and future income expecta</p><p>  The underlying assu

10、mption of these models is that income is generally low in an individual’s early working life and tends to rise towards retirement. Individuals at the start of their working life, expecting higher future income receipts,

11、finance the purchase of assets in order to raise consumption over the level offered by current income. Nearing the end of their working lives, inversely, individuals raise savings levels in preparation for retirement whe

12、n spending will be greater than earnings.</p><p>  In the "standard theory",named as such by Modigliani himself, the economic model posits that choices regarding households’ consumption levels over

13、 different periods of their life are subject to an intertemporal budget constraint.Considerable further empirical analyses of the theory have stressed the need for the standard model to take into account two additional a

14、spects:</p><p>  ——Households demand for debt is subject to factors other than income and wealth;</p><p>  ——households may be "liquidity constrained".</p><p>  Encompassi

15、ng these aspects effectively implies the model should address variables that influence both the demand and supply sides of the credit market (Table 1.1).</p><p>  Table 1.1 Consumer credit demand and supply

16、factors</p><p>  2.1 Credit Demand Factors</p><p>  With regards to individual factors, empirical analysis has extended the standard model by examining to what extent socio-demographic variables

17、, such as the age of the head of the household, the size and make up of the family, and levels of education, influence individuals’ spending, saving and borrowing choices.</p><p>  Consistent with the life-c

18、ycle, young people, characterised by expectations of rising income receipts, have a strong demand for credit which, over time, drops because income is sufficient to cover spending and with age individuals become more adv

19、erse to indebtedness.Indebtedness is higher or the capacity to save is lower also in the case of large families with children at pre-school or school age when in this life-cycle phase spending is typically high. This bei

20、ng said, however, the presence of </p><p>  Turning to institutional factors, the literature identifies three in particular: the extent of information-sharing amongst financial institutions regarding the lev

21、el of borrowers’ credit risk, the efficiency of the justice system in taking steps against insolvent individuals, and the size of the informal credit market.Institutional factors influence the demand for credit by creati

22、ng the conditions for the market to sanction opportunistic behaviour. The decision to repay a loan depends in fact no</p><p>  2.2 Credit Supply Factors</p><p>  The standard model assumes that

23、there are no constraints on the part of the household to obtain credit. The amount of the loan, however, is either subject to a ceiling or the level of interest rates applied by lenders may reduce or cancel the demand fo

24、r credit, so forcing households to limit their spending to the resources available.</p><p>  Credit constraints are widely viewed in the literature as deriving from the existence of asymmetric information be

25、tween borrowers and lenders; such informational imperfections force lenders to take steps to avoid approving loans that will subsequently not be repaid. In turn, credit availability by financial intermediaries depends on

26、 an individual’s socio-demographic and economic characteristics as well as his/her institutional setting. As to individual factors, high income and wealth levels comb</p><p>  With regards to the impact of i

27、nstitutional factors on the supply side, two of the three factors previously mentioned in the analysis of the demand side are particularly significant: the efficiency of the justice system and the existence of informatio

28、n-sharing mechanisms. An efficient justice system allows lenders to recover non-performing loans rapidly at contained costs. This is clearly the case with secured debt exposures: delays and difficulties in obtaining the

29、repossession of mortgaged pro</p><p>  The same institutional factor may also have an impact on the supply of unsecured credit: in this case, the disciplinary effect on insolvent individuals is represented b

30、y information concerning them and collected by credit bureaus that may damage their prospects of accessing the credit market again in the future. In such a scenario, the availability of credit is affected by the existenc

31、e amongst lenders of information-sharing mechanisms which are used in building up customer credit-risk profiles </p><p>  3 Empirical Findings</p><p>  Empirical analyses aimed at studying the d

32、eterminants of household credit markets and their coherence with Life-Cycle and Permanent Income models focus on the following areas, according to the research questions they investigate:</p><p>  —— Partici

33、pation in the credit market</p><p>  —— Level of borrowing</p><p>  —— Cross-country characteristics</p><p>  —— Risk of over-indebtedness</p><p>  —— Credit constraint

34、s</p><p>  Work across these areas examines both individual and institutional variables. Analysis has typically concentrated on the demand side, though a branch of study has used economic models to investiga

35、te the determinants of the supply of consumer credit (Table 1.2).</p><p>  Table 1.2 The literature of household credit</p><p>  3.1 Participation in the Credit Market</p><p>  Empi

36、rical analyses in this area indicate the determinants of households’ participation in the credit market.</p><p>  Amongst socio-economic factors examined within the individual category, the age profile as a

37、determinant of having unsecured debt is consistent with the lifecycle model of consumption: young people are more likely to borrow than members of older age groups (Crook 2006; Fabbri and Padula 2004), with the percentag

38、e of individuals with unsecured debt peaking for individuals aged between 30 and 40 years of age (Del Rio and Young 2005a; Magri 2007). With regards to household size, Fabbri and Padula (</p><p>  Turning to

39、 economic factors, the income variable is of significant importance. Demand for credit is positively influenced by expectations of increased future receipts, as posited by the life-cycle theory: if there were no expectat

40、ions of increased income in the future, there would be no need to advance spending via debt (Ferri and Simon 2000; Crook 2005; Cox and Jappelli 1993). Findings differ with regards to low income as a factor for indebtedne

41、ss: Del Rio and Young (2005a) show that there is l</p><p>  Moving to institutional factors, analysis has focused on the probability of lenders’ having their loans repaid. Studies show how the probability of

42、 default is negatively correlated with the level of efficiency of the justice system and the existence of effective information-sharing mechanisms, whilst positively correlated with the existence of informal credit marke

43、ts.</p><p>  3.2 Level of Borrowing</p><p>  As far as this second research area, i.e. the amount of debt held by households, among individual factors age does not appear to influence the level

44、of borrowing, whilst the level of educational qualifications is positively correlated. As regards economic variables, Fabbri and Padula (2004) show that income and wealth levels have a positive effect on the amount of un

45、secured debt an individual is likely to have. With reference to labour market status, Magri (2007) finds that the amount of consume</p><p>  3.3 Cross-Country Analyses</p><p>  The third researc

46、h area consists of spatial analyses of the determinants of unsecured debt with the aim of investigating the existence of any factors that are specific to a country or geographical area. Crook (2006) points out that as re

47、gards age, although the probability of having debt in all countries is greater for young people, the maximum percentage is reached in the United Kingdom and Germany (those aged 30–40) and later (those aged 40–50) in the

48、United States, Japan and the Netherlands.</p><p>  The percentage of households having unsecured debt is positively correlated with income. Evidence supporting this position is particularly strong in the Uni

49、ted Kingdom and the United States, where the share of middle-to-high income earners with debt is very high, whilst only at marginal levels in Italy. With reference to employment status, though the retired have a generall

50、y low probability of having debt, the share of those with debt is higher in the United Kingdom and Germany. There is less pr</p><p>  Cross-country analyses reveal the effect of institutional factors. Studie

51、s show that though the set of individual variables influencing demand for credit are common across countries, significant differences emerge regarding how individuals respond to negative shocks: the same event, for insta

52、nce job loss, is met by default in certain institutional environments, typically those characterised by inefficient justice systems, and repayment in others. Such differences cannot be explained solely on th</p>&

53、lt;p>  3.4 Over-Indebtedness</p><p>  This field of research attempts to identify institutional factors that may determine situations of financial fragility or over-indebtedness which increase the probabi

54、lity that individuals will not be able to repay their debts. Such situations of financial tension or difficulty are described in the literature as adverse events that can transform a performing loan into one the borrower

55、 finds difficult to repay. Such negative shocks to household finances include job loss, illness or divorce.</p><p>  The most significant statistical variable for identifying critical repayment difficulties

56、is the level of debt to income. Del Rio and Young (2005b) show that there is a positive relation between the level of debt to income and the probability of repayment difficulties. Similarly, Rinaldi and Sanchez-Arellano

57、(2006) report that a rise in the debt income ratio is associated with an increase in payment arrears. The same authors however also point out that if a rise in the debt/income ratio is accom</p><p>  The mod

58、els referred to generally include dummy variables in order to capture unexpected events that may have a negative economic impact. The effects such events can have on a borrower’s financial position vary noticeably from c

59、ountry to country and depend on institutional factors which, as already seen, can influence a household’s willingness to repay a loan.</p><p>  3.5 Credit Constraints</p><p>  The last research

60、area analyses the existence of credit constraints as a means of identifying both the socio-economic profile of individuals most at risk of having their application for a loan turned down and the effect institutional fact

61、ors have on lenders’ credit supply. As regards individual factors, empirical evidence concurs that the supply of credit rises with increases in age and educational qualifications; it also tends to rise for married couple

62、s and large families (Crook 2006; Cox and </p><p>  With reference to economic variables, as one may expect, the probability of having a loan application rejected is negatively correlated with income and wea

63、lth levels. Loan applications from the self-employed have a greater probability of rejection than those presented by the employed (Fabbri and Padula 2004; Ferri and Simon 2000).</p><p>  Empirical analyses i

64、nto the effect institutional variables have on the credit supply side concentrate principally on the specific features of the justice system and the existence of information-sharing mechanisms in a particular country or

65、geographic area. Casolaro et al. (2006) analyse the availability of credit in Italy and show that supply is influenced by a set of formal and informal mechanisms that determines repayment. As regards formal mechanisms, i

66、n line with Fabbri and Padula’s findings</p><p>  4 Summary of the Determinants of the Demand for and Supply of Consumer Credit</p><p>  The economic models of the Permanent Income and Life-Cycl

67、e theories continue to be used as a framework for analysis of households’ consumption, saving and indebtedness decisions. However, work in behavioural economics has made an important contribution in drawing attention to

68、the role played not only by socio-demographic and economic variables, but also psychological factors as determinants of the demand for unsecured debt. It has also been shown how psychological factors have an impact on th

69、e e</p><p>  Table 1.3 provides a summary of the factors influencing the demand for and supply of consumer credit. As can be seen, the signs (+) and (-) are not always homogeneous and have varying degrees of

70、 intensity.</p><p>  Table1.3 Summary of the determinants of consumer credit</p><p>  消費信貸的決定因素研究:基于文獻(xiàn)的回顧</p><p>  資料來源:歐洲消費信貸 作者:萬多內(nèi)丹妮拉</p><p>

71、;<b>  1概要</b></p><p>  關(guān)于消費信貸研究的文獻(xiàn)是相當(dāng)多的,如此大量的成果不僅僅反應(yīng)出非擔(dān)保債務(wù)的種類之繁多,也說明了由于調(diào)查分析以及調(diào)查目的的不同,對于消費信貸的研究就產(chǎn)生了不同的角度。這里有四種主要的角度:從管理學(xué)的角度,這是一種重點關(guān)注信貸產(chǎn)業(yè)特性的方法,采用這種方法的多為信貸的供應(yīng)方;從法律的角度,主要從法律框架上研究對產(chǎn)業(yè)競爭和消費者保護(hù)的影響;從社會心理學(xué)

72、角度,它分析個體是如何受到消費行為和債務(wù)選擇的影響的;從經(jīng)濟(jì)學(xué)角度,主要研究關(guān)于消費信貸供給與需求的決定因素,并分析個人或家庭的債務(wù)特征。</p><p>  這里我們主要討論經(jīng)濟(jì)學(xué)角度的研究,目的是為了提供一份個人的提綱以及那些在研究文獻(xiàn)中提及的消費信貸決定因素。這種經(jīng)濟(jì)模型基于個人的經(jīng)濟(jì)理性,即人們希望在不同的生命周期中通過儲蓄和負(fù)債的決策實現(xiàn)相對平滑的消費來提高他們的生活水平。從這些模型來看,消費信貸的供給

73、和需求取決于個體因素。</p><p>  2生命周期理論與持久收入假說</p><p>  消費、儲蓄以及債務(wù)決策的經(jīng)濟(jì)學(xué)理論框架是在由Modigliani和Brumberg(1954)提出的生命周期理論與Freidman(1957)提出的持久收入假說中形成的。這些跨時期的消費選擇方式的中心思想是家庭所作出的消費選擇取決于其自身家庭的財富,可支配收入以及未來收入預(yù)期,以此保障其一生均衡的

74、消費水平。</p><p>  上述模型建立的基本假定是在個人工作生涯的早期收入普遍較低并隨著臨近退休而逐漸增加。人們會在工作生涯的早期,預(yù)期更高的未來收入,為了提高消費水平融入資金購買資產(chǎn)進(jìn)行超前消費,相反的,在工作生涯的后期,人們則更傾向于提高儲蓄的水平為將來退休做準(zhǔn)備。在這種框架下,儲蓄和債務(wù)通過使消費變得平滑保證了其經(jīng)濟(jì)福利的提高。</p><p>  在Modigliani所說的

75、“標(biāo)準(zhǔn)理論”中,經(jīng)濟(jì)模型假定在關(guān)于家庭消費水平在不同時期的選擇受跨時期的預(yù)算約束。以此理論更進(jìn)一步的實證分析還強(qiáng)調(diào)了這一標(biāo)準(zhǔn)模型還需考慮另外兩個方面:</p><p>  ——家庭對債務(wù)的需求還受收入和家庭現(xiàn)有財富的支配</p><p>  ——家庭還可能受到“流動性約束”</p><p>  這實際上意味著模型應(yīng)從信貸市場需求和供給兩個方面確定變量對它的影響(表1

76、.1)。</p><p>  表1.1 消費信貸需求與供給因素</p><p><b>  2.1信貸需求因素</b></p><p>  在個體因素方面,實證分析通過對人口統(tǒng)計學(xué)變量的審計擴(kuò)展了標(biāo)準(zhǔn)理論,例如戶主的年齡、家庭結(jié)構(gòu)、受教育程度,都影響了個體對消費、儲蓄以及債務(wù)的選擇。</p><p>  在生命周期中,年

77、輕人預(yù)期未來收入是增加的,他們對信貸的需求是巨大的,隨著時間的推移,當(dāng)收入逐漸能夠覆蓋支出的時候,這種需求就會慢慢減少。大部分家庭在子女教育階段的花費也是非常高的,他們往往具有較高的負(fù)債水平或是低弱得儲蓄能力。然而子女的存在也是大量儲蓄的動機(jī),人們?yōu)榱速Y產(chǎn)向下一代的轉(zhuǎn)移而提高他們的儲蓄比例。受教育程度對信貸需求也有著積極的影響,因為它反映了個人未來收入提高的預(yù)期和工作保障,同時,它也降低了進(jìn)入信貸市場以及做出債務(wù)決策的成本。</p

78、><p>  除了包含于原框架之內(nèi)的經(jīng)濟(jì)因素外,實證分析指出該模型還應(yīng)該包括不確定因素,即將來收入的可變性。這種不確定性使人們必須保持必要的流動性防止未來收入的下降或是非預(yù)期的債務(wù)支出,從而導(dǎo)致儲蓄的增加和對信貸需求的減少。</p><p>  在制度因素方面,文獻(xiàn)定義出三個主要因素:金融機(jī)構(gòu)中關(guān)于借款人信用風(fēng)險的信息共享程度、法律制度在應(yīng)對個人破產(chǎn)所采取措施的效用以及非正式信貸市場的程度。制

79、度因素通過為市場創(chuàng)造條件制約機(jī)會主義行為來影響信貸需求。償還債務(wù)不僅僅取決于償債能力,還取決于個人遵從合約條款履行義務(wù)的意愿。換句話說,家庭的借款可能不是基于預(yù)期收入增加所進(jìn)行的預(yù)先消費,而是他/她認(rèn)為這筆債務(wù)是不需要償還的,這一現(xiàn)象被稱為“戰(zhàn)略性破產(chǎn)”(Gropp等人1997)。貸款人間的信息共享機(jī)制使貸款人能夠系統(tǒng)的了解降申請人的情況從而降低了家庭超額負(fù)債的可能性。對于效率的司法系統(tǒng),逾期付款或是破產(chǎn)的概率增加則其信用的恢復(fù)是一個漫

80、長而昂貴的過程。轉(zhuǎn)到第三制度性因素——非正式信貸市場的作用,若個人能在親戚和朋友間得到信貸資產(chǎn),就會排除尋求正規(guī)金融機(jī)構(gòu)的動機(jī)。</p><p><b>  2.2信貸供給因素</b></p><p>  標(biāo)準(zhǔn)模型假設(shè)家庭在獲得信貸方面沒有約束。然而,實際貸款的數(shù)額受到了貸款上限或者是利率水平的管制,由此貸款人可能減少或者取消家庭對信貸的需求,從而強(qiáng)迫他們限制消費以獲

81、取可得資金。</p><p>  文獻(xiàn)中廣泛認(rèn)為信貸約束的存在來源于借貸雙方的信息不對稱;這種信息瑕疵促使貸款人采取措施避免批準(zhǔn)將來可能沒有回報的貸款。反過來,金融機(jī)構(gòu)的信貸資金可獲得性取決于個體的社會經(jīng)濟(jì)特點以及他所在的制度環(huán)境。在個體因素中,高的收入和財富水平以及穩(wěn)定的工作狀態(tài)都增加了貸款人愿意提供的信貸供給。</p><p>  關(guān)于供給方面制度性影響因素中,在需求因素分析中預(yù)先提到

82、的那倆個因素也有其重要的意義:法律制度建設(shè)的效率和機(jī)構(gòu)間共享信息平臺的存在。有效地司法系統(tǒng)使貸款人能夠迅速收回不良貸款的成本。如在抵押擔(dān)保債務(wù)中,延遲或是不能夠贖回抵押財產(chǎn)將會限制貸款人抵押擔(dān)保貸款的提供或推廣程度。</p><p>  同樣,制度性因素也可能影響無擔(dān)保貸款的供給。在這里,信用咨詢機(jī)構(gòu)所收集到得破產(chǎn)者的信息很可能損害其未來再次進(jìn)入信貸市場的前景。在這種情況下,貸款的可獲得性就受到了貸款人間機(jī)構(gòu)信息

83、共享平臺的影響,這一平臺被用于建設(shè)顧客信用風(fēng)險評級,以此減少信息不對稱所產(chǎn)生的風(fēng)險。</p><p><b>  3實證研究結(jié)果</b></p><p>  實證分析旨在研究消費信貸市場的決定因素以及它們與生命周期和永久收入理論的相關(guān)性,從調(diào)查研究的問題來看,主要集中在以下幾個模型領(lǐng)域:</p><p><b>  ——信貸市場結(jié)構(gòu)&

84、lt;/b></p><p><b>  ——借款水平</b></p><p><b>  ——社會特征</b></p><p><b>  ——過度負(fù)債的風(fēng)險</b></p><p><b>  ——信貸約束</b></p><

85、p>  對這些模型領(lǐng)域的調(diào)查包括了個體因素和制度因素變量。分析一般都集中在需求方面,雖然研究的一個分支使用的是經(jīng)濟(jì)模型來調(diào)查消費信貸供給的決定因素(表1.2)。</p><p>  表1.2 關(guān)于消費信貸的文獻(xiàn)</p><p><b>  3.1信貸市場結(jié)構(gòu)</b></p><p>  這方面的實證分析表明了在信貸市場中家庭參與的決定因素

86、。</p><p>  在個體范疇的社會經(jīng)濟(jì)因素檢驗中,檢查判定年齡剖面作為擁有無擔(dān)保債務(wù)的決定因素與消費生命周期模型是一致的:年輕人往往比老年人有更大的借款需求(Crook2006,F(xiàn)abbri和Padula2004),其個人無擔(dān)保債務(wù)比率占比在30-40歲的人群中達(dá)到巔峰(Del Rio和Young2005,Magri2007)。在家庭類型方面,F(xiàn)abbri和Padula發(fā)現(xiàn)家庭成員數(shù)目與負(fù)債水平是成正比的。

87、Similarly,Del Rio和Young (2005) ,Crook(2006)已婚家庭相對于未婚家庭來說,有更高的非擔(dān)保債務(wù)需求。此外,擁有更高的學(xué)歷也與更高幾率的無擔(dān)保債務(wù)有關(guān)。一般認(rèn)為教育水平對個人財務(wù)意識有積極的影響:受教育程度越高,就越容易獲得和評估金融產(chǎn)品的服務(wù)。</p><p>  而在經(jīng)濟(jì)因素中,收入變量具有十分重要的意義。信貸需求明顯受未來預(yù)期收入的影響,在生命周期理論中:若沒有未來收入增

88、加預(yù)期,也就沒有必要通過負(fù)債進(jìn)行提前消費(Ferri和Simon 2000,Crook 2005,Cox和Jappelli 1993)。研究結(jié)果表明,收入水平低下并不是負(fù)債的主要因素:Del Rio和Young(2005)指出由于高度不穩(wěn)定的就業(yè)條件而伴隨的低收入減少了信貸需求和供應(yīng),貧困家庭負(fù)債的比率是很小的。凈資產(chǎn)也是一個重要的因素。那些負(fù)債較高的家庭往往只有有限的凈資產(chǎn)。事實上,文獻(xiàn)觀點表明,那些凈資產(chǎn)較高的家庭能夠不通過負(fù)債滿足

89、其消費需求。而那些擁有中等財富水平的家庭更有可能為了改善生活方式而通過參與消費信貸市場來增加其消費的模式。Del Rio和Young(2005)關(guān)注擁有金融資產(chǎn)組合的家庭并發(fā)現(xiàn)那些沒有這類組合的家庭比其更可能需求無擔(dān)保負(fù)債。</p><p>  再來看制度因素的分析,對制度因素的分析主要集中討論貸款人得到還款的概率。研究表明,違約的可能性與司法系統(tǒng)的效率和機(jī)構(gòu)間有效地信息共享存在著負(fù)相關(guān)的關(guān)系,與非正規(guī)信貸市場存

90、在著正相關(guān)關(guān)系。</p><p><b>  3.2借款水平</b></p><p>  就持有一定負(fù)債的家庭來說,在個體因素中年齡的變量似乎并不會影響借款的水平,同時,受教育程度水平則與其存在明顯的正相關(guān)關(guān)系。而至于經(jīng)濟(jì)變量來說,收入和財富水平與個人可能擁有無擔(dān)保債務(wù)存在著正相關(guān)關(guān)系。關(guān)于勞動力市場的情況,Magri(2007)發(fā)現(xiàn)對于個體經(jīng)營戶來說其消費信貸數(shù)額較

91、高,這主要是因為這一類群體運用無擔(dān)保債務(wù)作為資助其經(jīng)營的一種方式。此外,制度因素的影響與上文中的描述并無不同(1.3.1部分):無效的司法系統(tǒng),無效的機(jī)構(gòu)信息共享以及廣泛的非正式信貸市場不僅僅增加了參與信貸市場的概率,同時增加了家庭的債務(wù)數(shù)量。</p><p><b>  3.3社會特性</b></p><p>  第三個研究領(lǐng)域包括空間分析決定因素的無擔(dān)保債務(wù),我們

92、的目標(biāo)是調(diào)查任何因素的存在,具體到一個國家或地理區(qū)域。Crook指出,雖然就全部國家而言,年輕人擁有債務(wù)的概率是最大的,但是在英國和德國(那些年齡在30-40的之間)達(dá)到了最高的百分比,接著是美國、日本和荷蘭(那些年齡在40-50的之間)。</p><p>  具有無擔(dān)保債務(wù)的家庭比率與其收入是成正相關(guān)的。在美國和英國,這一觀點得到有力地證實,在那里擁有中上收入水平的人們有著很高的負(fù)債,而意大利只處于邊緣水平。而

93、關(guān)于就業(yè)狀況,雖然退休群體擁有負(fù)債的概率一般較低,但是在美國與德國,這一概率是較高的。在意大利與荷蘭,個體經(jīng)營戶擁有負(fù)債的概率較小,反之在美國與西班牙,失業(yè)者群體卻在獲取信貸方面存在很大的問題。</p><p>  跨國分析揭示這種效應(yīng)的制度性因素的影響。研究表明,雖然套變量對信貸的需求是常見的影響在不同國家,有顯著差異的出現(xiàn)對于個體如何回應(yīng)負(fù)面沖擊:相同的事件,比如失業(yè),就會默認(rèn)情況下,在特定的制度環(huán)境通常那些

94、倡導(dǎo)低效的司法系統(tǒng),償還他人。這種差異是不能解釋的完全根據(jù)個人的行為偏差關(guān)于債務(wù),但在此基礎(chǔ)上的區(qū)別在效率和效果的制度性因素(Bianco等人2002,Crook 2006)。</p><p><b>  3.4過度負(fù)債</b></p><p>  在這一領(lǐng)域的研究嘗試定義這樣的制度性因素,這些因素可以判定其財務(wù)脆弱性情況或者是增加個人無法償還其債務(wù)可能性的過度負(fù)債情

95、況。在文獻(xiàn)描述中,這種情況的財務(wù)緊張或困難作為一個消極事件,能夠把一個正在履行的貸款變成借款人發(fā)現(xiàn)難以償還的負(fù)債。這種對家庭財務(wù)的負(fù)面沖擊包括失業(yè)、疾病或者是離婚。</p><p>  識別鑒定還款困難的最顯著的統(tǒng)計變量是收入負(fù)債比。Del Rio和Young(2005)指出收入負(fù)債比與償還貸款困難的概率成正相關(guān)關(guān)系。類似的,Rinaldi和Sanchez-Arellano (2006)的報告指出,一個上升的收入

96、負(fù)債比與增長的還款拖欠是相聯(lián)系的。然而同樣的,作者也指出,如果一個上升的收入負(fù)債比是伴隨著可支配收入而增長的,則增加負(fù)債帶來的負(fù)面影響就會被取消。Bridges和Disney(2004)定義低收入是過度負(fù)債與破產(chǎn)的主要原因。</p><p>  為了捕捉有可能產(chǎn)生負(fù)面經(jīng)濟(jì)影響的不可預(yù)料事件,這些被提及的模型通常包含一些虛擬變量。這些事件的影響,有可能使借款人財務(wù)狀況發(fā)生明顯變化,正如已經(jīng)見過的,這些事件依靠制度性

97、因素,能夠影響家庭還款的意愿。</p><p><b>  3.5信貸約束</b></p><p>  對信貸約束的研究作為一種手段,確認(rèn)了個人社會經(jīng)濟(jì)層面申請貸款被拒絕的風(fēng)險和制度因素層面對貸款人貸款供給的影響。在個體因素研究方面,實證研究一致認(rèn)為信貸供給與年齡、學(xué)歷呈同向增長;這種增長也可能是由于家庭結(jié)構(gòu)是已婚家庭或者大家族(Crook2006,Cox和Jappe

98、lli1993)。所在城市或鄉(xiāng)鎮(zhèn)的情況,也是決定信貸需求的一個重要因素,但在供給方面并沒有特別重大的影響(Magri2007)。</p><p>  關(guān)于經(jīng)濟(jì)變量,貸款申請被拒絕的概率是與收入和財富水平呈負(fù)相關(guān)的。來自個體經(jīng)營戶的貸款申請相對于那些受雇于公司的貸款申請來說更容易被拒絕(Fabbri和Padula 2004,F(xiàn)erri和Simon 2000)。</p><p>  關(guān)于制度性

99、變量影響信貸供給方面的實證分析主要集中于在不同國家或地區(qū)司法系統(tǒng)的某些特性和信息共享機(jī)制的存在。Casolaro等人(2006)在對意大利的信貸可獲得性調(diào)查研究中發(fā)現(xiàn)信貸供給受一套正式與非正式機(jī)制的影響,這種機(jī)制決定了借款人對債務(wù)的償還。關(guān)于正規(guī)機(jī)制,F(xiàn)abbri和Padula(2004)、Magri(2007)以及Bianco等人(2002)都認(rèn)為越有效地司法體系,信用恢復(fù)的成本就越低,存在信貸配給的概率也就越低。同時,貸款的可獲得性

100、也取決于非正規(guī)信貸體制,這一體系取決于一個地區(qū)的基礎(chǔ)社會資本。對這一資源的衡量一般包括人均家族捐贈數(shù)目,在團(tuán)體社區(qū)中的個人信譽(yù)以及政治選舉的參與情況(Guiso等人2004)。高水平的社會資本與公民意思和社會關(guān)系網(wǎng)絡(luò)有關(guān),這決定了人們對其個人承諾的履行。Bicacova(2007)分析了信息不對稱(道德風(fēng)險和逆向選擇)的存在以及其對消費信貸市場的影響。她通過對信貸產(chǎn)品違約率的不同(那些用于購買摩托車、二手汽車和手機(jī)的貸款的違約率要高于購

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