Evaluación financiera: VAN, TIR, B/C, PR

Next, I test an effect of backward-looking expectations of capital gains from another perspective in order to show that the effect is robust enough that we should not underestimate it in studying mortgage default and bankruptcy. As a preparation, I assume there are some credit constrained households that can get out of insolvency by selling their homes. Let us first assume the representative household satisfies the conditions as follows:

n

This household can avoid delinquency and the associated financial losses (Equations (2.2) and (2.3)) by selling its home. If the household chooses to sell home, its expected wealth in the next period is described as follows⁴⁴:

[ ] ( ) ( ) ( ) ( ) ( ) (

mt

)

Then I examine the financial profits from mortgage default and filing for bankruptcy by using Equation (2.9) as a base outcome. If the household chooses to default on its mortgage or file for bankruptcy instead of selling its home on the market, the expected wealth in the next period is as follows:

44 Here I assume the household need not to borrow additional money to repay, if it sells its home.

[ ] ^{{ [ (}

t t t

^{) ]}

h

^} (

t

)

household chooses mortgage default or bankruptcy filing, respectively; X_h is the homestead exemption the household can claim in its state of residence. While the outcome of mortgage default never changes, I introduce the two distinct consequences of bankruptcy filing due to one of the remarkable features of the U.S. bankruptcy law: namely, homestead exemption. It relaxes the assumption that I made in the previous section. That is, the home will be liquidated by the bankruptcy trustee, if the household’s home equity is larger than the homestead exemption. In such a case, the household’s home equity would be protected only to the extent of the homestead exemption, at most. Then the subtraction between these outcomes gives;

[ ]

mt

[

t

(

t

)

t

(

mt

) ]

Compared with the previous model in which none of the credit constrained households are allowed to sell their home, these financial profits from mortgage default and bankruptcy have changed. Since this model focuses on insolvent and credit constrained households that sell their homes, their financial profits from mortgage default are not affected by capital gain expectations:

they will lose their homes in both cases. Although, in the financial profit from bankruptcy, the

effects of the terms related to the rates of interest and bankruptcy exemption are not

straightforward to interpret, one significant change occurred due to the possibility of retaining the homes after bankruptcy proceedings. The household that satisfies Equation (2.4) and (2.8) can keep its housing investment and is willing to do so if: (1) its home equity is low enough (below the homestead exemption); and (2) it expects the rate of return for the housing investment will be more preferable than that of non-housing assets (the last parenthesis in Equation (2.10)). This extension of the previous model implies that the larger capital gains (insolvent and credit constrained) households expect from their homes, the more likely the households are to file for bankruptcy, only if their home equity is less than the level of homestead exemption.

We cannot directly test this hypothesis with the dataset of the SCF, because we do not know the homestead exemption that would be applied to each household due to a lack of geographical data in the SCF. However, if we treat the geographical variable (which state the household lives in) and associated homestead exemption as random variables in the model⁴⁵, the marginal effect of the capital gain expectations on the expected financial profit from bankruptcy for this type of credit constrained households is described as follows:

[ ] [ ] ⁽

h t t t t

⁾

where X_h is defined as a random variable which follows a distribution which is known. The distribution of the level of homestead exemption weighted by the population of homeowners is presented in Table 3-3. I will discuss the homestead exemption in Chapter 3 again in more detail.

Now I go back to the estimation. As we can see from Table 3-3, the level of homestead exemption is distributed in a wide range. Nonetheless, there are some values which have

45 However, the level of homestead exemption is unobservable only to us; the household itself is reasonably assumed to know the level of homestead exemption.

considerable frequencies. I pick up one of the highly frequent values, the homestead exemption level of 75,000 dollars (adopted by the state of California) as a breaking point in order to perform the multinomial logit estimation with the same explanatory variables, but allowing the coefficient on capital gain expectation to take a different value for the households with lower home equity from those with higher home equity. Thus we can test if capital gain expectations have a positive effect on bankruptcy decisions when households are likely to keep their homes even after

bankruptcy proceedings.

Table 2-4 shows the result of this estimation. Estimating the coefficients on capital gain expectation separately according to the home equity category clearly makes a difference for nonmortgage delinquency. The coefficient on capital gain expectation in the second column is positive and statistically significant for the group of households with the lower home equity;

these households are likely to be able to protect their homes through bankruptcy proceedings. A similar estimation result is also obtained for the probability of delinquency on both loans. On the other hand, this specification brings about almost no changes in other coefficients. In particular, since the coefficients on household’s income and loan payments remain the same, compared to Table 2-3, introduction of home equity group seems to only affect households’ financial profits, but not the ability-to-pay determinants. This result provides another evidence for the important role of households’ backward-looking expectations in their financial incentives for loan

terminations.

2.4.3. Households’ attitude towards financial risks

When it comes to borrowers’ exercise of mortgage options, Deng, Quigley and Van Order (2000) emphasize the importance of the heterogeneity of their attitude towards financial

risks. They argue that some borrowers are astute enough to take advantage of the opportunities for financial profits, while some of them are less sensitive to such opportunities, and that the exercise of the mortgage default option is one of the primary examples in this context⁴⁶. Their estimation of hazard functions provides strong evidence for the existence of this heterogeneity. If the heterogeneity of attitude towards financial risks is incorporated into the model of this chapter, the default decisions of households who are sensitive to the value of default option are likely to be greatly affected by the current loan-to-value ratio and their expectation of capital gains (see Equation (2.1))⁴⁷. In other words, households who astutely take into account financial profits and risks are expected to exert their default option “ruthlessly”.

In fact, the SCF contains a variable concerning the heterogeneity of attitude towards risks by asking the respondents a hypothetical question of risk-taking behavior⁴⁸. Barsky, Juster, Kimball and Shapiro (1997) study a similar variable in the Health and Retirement Study to check its validity and its effect on risk-taking behaviors, such as holding stock. They find that the variable appropriately describes the heterogeneity of attitude towards risk and has predictive power for risk-taking behavior.

Table 2-5 reports the estimation result of the specification which allows the coefficients on CLTV and capital gains expectations to take different values according to the groups based on attitudes towards financial risks. By this specification, we can test the hypothesis that the

financial profit variables have different effects on households’ decisions on mortgage default due

46 Deng, Quigley and Van Order (2000) study the mortgage options of default and prepayment in a simultaneous framework, and find the effect of the heterogeneity is more remarkable for the exercise of prepayment option.

47 I am still assuming the backward-looking formulation of capital gain expectations.

48 The question is as follows: “Which of the statements on this page comes closest to the amount of financial risk that you and your (husband/wife/partner) are willing to take when you save or make investments?”

The households who answered yes to the following question are labeled “willing to take risk”, otherwise labeled

“risk averse”: “take substantial financial risks”, “take above average financial risks” or “take average financial risks”.

to their heterogeneity of attitudes towards risks. For mortgage delinquency, the coefficients on these variables fit the prediction; it implies the risk-tolerant group will exert the default option particularly based on their equity position in their properties and on expected capital gains. On the contrary, none of the coefficients on CLTV and expected capitals gains are statistically significant for the group of risk-averse households, even though their signs remain same. In addition, the F test cannot reject the null hypothesis that the coefficients for CLTV and CLTV square are jointly zero (p value = 0.263). Nonetheless, this specification does not change the effects of the ability-to-pay variables, such as income and loan payments. Thus we can see a crucial difference only in the financial factors in this specification of the heterogeneity of risk attitudes.

2.5. Conclusion

This chapter tries to disentangle the relationship between the determinants of

households’ decisions on mortgage default, bankruptcy and loan delinquency by focusing on the observable choice between mortgage and nonmortgage delinquency. First, I set up a theoretical model based on financial profits that households could obtain by mortgage default, bankruptcy or delinquency. This model describes well borrowers’ incentives for mortgage default and

bankruptcy, but it turns out to be difficult to explain the effect of loan payments on delinquency decisions. Then a simple type of credit constraint model is introduced to show that for some households, loan delinquency is an unavoidable response due to credit constraints rather than any attempts to gain financial profits. Credit constraints give sound theoretical reasoning to the effects of household’s income and shocks to the ability to pay, or “trigger events”, as well.

This mixture of the financial profit theory and the credit constraint theory is strongly

supported by the results of multinomial logit estimation. The significant effect of CLTV is consistent with the findings of the previous option-based studies. Although the impact of backward-looking expectations has drawn little attention in the traditional mortgage default studies, compared to other fields related to housing, such as housing demand, the estimation results suggest that borrowers’ backward-looking expectations affect their decisions both on mortgage default and on bankruptcy. On the other hand, household’s income, loan payments and trigger events also play an important role in households’ choice between mortgage and

nonmortgage delinquency, supporting the credit constraint model. The effect of the homestead exemption and the importance of borrowers’ heterogeneity towards risks are also found empirically to be important.

In conclusion, the results reported in this chapter imply there are certainly a good number of households that are forced to become delinquent against their will, or regardless of their optimal choice based on financial profits. Moreover, they might be even forced to default on their mortgage or file for bankruptcy beyond temporary loan delinquency, if they cannot escape from financial distress. These findings provide a solid empirical evidence to reconcile two conflicting theories in the literature on mortgage default and personal bankruptcy: the willingness-to-pay theory and the ability-to-pay theory.

Since I make some strong assumptions, such as exogenously fixed expenditures, housing investment and credit constraints, we could derive more profound implications with more general models based on the consumer-choice theory. The model in this chapter also assumes all

mortgages are non-recourse. As for empirical studies, examining households’ decisions between mortgage default and bankruptcy directly rather than their delinquency choice should be done, more effectively and persuasively with datasets of dynamic structure.

Figure 2-1

Mortgage delinquency

Nonmortgage delinquency

Mortgage default

Resume payment

Personal bankruptcy

Resume payment

Effect

Effect

Paying for non-mortgage Non-mortgage delinquency Total

Paying for mortgage 11,962

(95.64)

290 (2.32)

12,252 (97.96)

Mortgage delinquency 185

(1.48)

70 (0.56)

255 (2.04)

Total 12,147

(97.12)

360 (2.88)

12,507 (100.00) Note: percentage points inside parentheses

Table 2-1

Delinquency rates for mortgage and nonmortgage loans

Description Mean Std. Dev.

CLTV current mortgage balance divided by current

housing value 0.5706 0.2557

CLTV squared CLTV squared 0.3909 0.3125

Expected capital gain average annual rate of house price appreciation

times current housing value 21,063 71,773

Debt the amount of debts that could be discharged by

bankruptcy 61,008 944,214

Mortgage payment monthly payment of mortgages 1,471 2,404

Nonmortgage payment monthly payment of nonmortgage loans 1,357 10,955

Income household's total income 291,361 3,652,404

Unemployment monthly payment of mortgages 0.0648 0.2463

Unexpected low income household head experienced unemployment within

12 month 0.1305 0.3369

Credit constraint denial or expected denail of loan applications 0.2154 0.4111

Female household head is female 0.1019 0.3025

Age household head's age 45.49 11.03

Age squared household head's age squared 2190.54 1050.84

Black household head is black 0.0792 0.2700

Hispanic household head is Hispanic 0.0514 0.2208

Children household supporting children 0.6457 0.4783

Willing to take risks answer yes to "take average financial risk" or more 0.8080 0.3939

Observations 12,507

Year 2004 4,699

Year 2001 4,060

Year 1998 3,748

Table 2-2

Summary statistics of explanatory variables

Table 2-3

Borrowers' choice of delinquency: base model

Coefficient t Coefficient t Coefficient t

CLTV -3.589 (-4.82)*** 0.088 (0.10) -2.096 (-1.74)*

CLTV squared 2.799 (6.10)*** 0.294 (0.44) 2.466 (3.83)***

Debt 9.19.E-07 (0.18) 2.05.E-07 (0.68) -2.89.E-06 (-0.56)

Expected capital gain -2.48.E-05 (-2.70)*** 7.89.E-07 (0.20) 6.76.E-07 (0.24) Mortgage payment 2.06.E-04 (3.59)*** -8.03.E-04 (-4.65)*** 3.64.E-05 (0.16) Nonmortgage payment -7.87.E-04 (-2.57)*** 3.31.E-05 (3.22)*** 8.00.E-05 (1.48) Income -1.86.E-05 (-5.69)*** -5.23.E-06 (-2.75)*** -9.95.E-06 (-2.22)**

Unemployment 0.023 (0.10) 0.678 (3.87)*** 1.584 (5.59)***

Unexpected low income 0.541 (2.89)*** -0.513 (-2.57)*** 0.265 (0.86)

Credit constraint 2.130 (11.07)*** 1.805 (13.21)*** 1.670 (5.85)***

Age -0.075 (-1.76)* 0.102 (2.08)** 0.259 (2.19)**

Age squared 0.001 (1.25) -0.001 (-2.30)** -0.003 (-2.40)**

Female -2.12.E-01 (-1.00) -1.84.E-01 (-1.00) 4.96.E-01 (1.57)

Black 0.634 (3.18)*** -0.060 (-0.32) 0.452 (1.33)

Hispanic 0.410 (1.39) 0.108 (0.44) 1.055 (2.84)***

Children 0.832 (4.07)*** 1.013 (5.61)*** 0.310 (1.01)

year 2004 0.048 (0.24) 0.438 (2.79)*** 1.036 (2.68)***

year 2001 -0.229 (-1.17) 0.160 (1.00) 0.927 (2.42)**

Constant -1.441 (-1.46) -6.305 (-5.96)*** -11.115 (-4.61)***

Observations 12,507

Log likelihood -2184.42

Pseudo R square 0.211

Mortgage delinquency Nonmortgage delinqency Delinquency on both

Table 2-4

Borrowers' choice of delinquency: homestead exemption model

Coefficient t Coefficient t Coefficient t

CLTV -4.029 (-5.36)*** -0.784 (-0.88) -2.421 (-1.99)**

CLTV squared 3.007 (6.62)*** 0.764 (1.17) 2.653 (4.10)***

Debt 8.35.E-07 (0.14) 2.97.E-07 (0.89) -2.98.E-06 (-0.58)

Expected capital gain

Home equity <= 75K -1.71.E-06 (-0.13) 3.32.E-05 (4.72)*** 2.76.E-05 (1.94)*

Home equity > 75K -4.13.E-05 (-3.11)*** -1.40.E-05 (-1.75)* -1.33.E-07 (-0.02) Mortgage payment 2.42.E-04 (4.07)*** -7.44.E-04 (-4.17)*** 2.02.E-05 (0.08) Nonmortgage payment -7.71.E-04 (-2.52)** 3.46.E-05 (3.26)*** 8.23.E-05 (1.52) Income -1.85.E-05 (-5.67)*** -4.89.E-06 (-2.52)** -1.01.E-05 (-2.21)**

Unemployment 0.028 (0.11) 0.713 (4.06)*** 1.600 (5.64)***

Unexpected low income 0.529 (2.82)*** -0.567 (-2.81)*** 0.223 (0.72)

Credit constraint 2.138 (11.08)*** 1.808 (13.20)*** 1.671 (5.84)***

Age -0.070 (-1.65)* 0.099 (2.03)** 0.260 (2.19)**

Age squared 0.001 (1.17) -0.001 (-2.20)** -0.003 (-2.39)**

Female -1.77.E-01 (-0.84) -1.21.E-01 (-0.65) 5.37.E-01 (1.69)*

Black 0.607 (3.03)*** -0.074 (-0.40) 0.458 (1.35)

Hispanic 0.471 (1.59) 0.211 (0.85) 1.105 (2.95)***

Children 0.846 (4.13)*** 1.054 (5.81)*** 0.334 (1.09)

year 2004 0.045 (0.23) 0.430 (2.72)*** 0.999 (2.57)***

year 2001 -0.233 (-1.19) 0.151 (0.94) 0.910 (2.37)**

Constant -1.467 (-1.49) -6.138 (-5.82)*** -11.111 (-4.60)***

Observations 12,507

Log likelihood -2168.70

Pseudo R square 0.216

Mortgage delinquency Nonmortgage delinqency Delinquency on both

Table 2-5

Borrowers' choice of delinquency: heterogeneity model

Coefficient t Coefficient t Coefficient t

Willing to take risk

CLTV -4.574 (-6.00)*** -0.025 (-0.03) -0.984 (-0.52)

CLTV squared 3.157 (6.98)*** 0.194 (0.27) 0.956 (0.64)

Expected capital gain -2.96.E-05 (-2.45)** 1.61.E-06 (0.66) 3.24.E-07 (0.11) Risk averse

CLTV -1.415 (-1.36) 0.614 (0.56) -2.654 (-1.80)*

CLTV squared 1.361 (1.59) 0.035 (0.04) 3.430 (3.72)***

Expected capital gain -1.77.E-05 (-1.38) -1.61.E-05 (-1.14) -2.48.E-06 (-0.12)

Debt 1.55.E-06 (0.67) 1.84.E-07 (0.61) -2.84.E-06 (-0.60)

Mortgage payment 1.96.E-04 (3.37)*** -7.61.E-04 (-4.47)*** 9.30.E-05 (0.51) Nonmortgage payment -8.27.E-04 (-2.57)*** 3.19.E-05 (3.12)*** 8.13.E-05 (1.67)*

Income -1.39.E-05 (-4.43)*** -5.05.E-06 (-2.67)*** -1.07.E-05 (-2.27)**

Unemployment -0.004 (-0.02) 0.653 (3.69)*** 1.519 (5.27)***

Unexpected low income 0.491 (2.56)*** -0.509 (-2.55)** 0.311 (1.01)

Credit constraint 2.125 (10.88)*** 1.804 (13.18)*** 1.560 (5.37)***

Age -0.079 (-1.82)* 0.097 (2.00)** 0.253 (2.07)**

Age squared 0.001 (1.21) -0.001 (-2.24)** -0.003 (-2.31)**

Female -2.27.E-01 (-1.06) -2.07.E-01 (-1.12) 5.13.E-01 (1.61)

Black 0.519 (2.56)*** -0.080 (-0.42) 0.496 (1.44)

Hispanic 0.148 (0.49) 0.089 (0.35) 0.962 (2.46)**

Children 0.799 (3.89)*** 1.004 (5.55)*** 0.425 (1.30)

year 2004 -0.144 (-0.72) 0.427 (2.71)*** 0.956 (2.51)**

year 2001 -0.349 (-1.73)* 0.136 (0.85) 0.731 (1.89)*

Constant -1.297 (-1.27) -6.152 (-5.83)*** -10.827 (-4.36)***

Observations 12,507

Log likelihood -2148.71

Pseudo R square 0.224

Mortgage delinquency Nonmortgage delinqency Delinquency on both

Chapter 3: Personal bankruptcy decisions of mortgage borrowers

3.1. Introduction

Americans witnessed an unprecedented more than six-fold increase in the number of personal bankruptcy filings, from 241,000 in 1980 to more than 1.6 million in 2005⁴⁹. While this explosive rise led to an amendment of the bankruptcy law in 2005, which basically made it harder for borrowers to file for bankruptcy, personal bankruptcy filings have drawn serious attention by many researchers from both economics and legal fields. In particular, several seminal empirical studies have been done focusing on borrowers’ decisions on bankruptcy filings. These empirical studies on bankruptcy mostly take advantage of a control variable offered by the legal system of bankruptcy in the United States: namely, bankruptcy exemptions, particularly homestead

exemption, which states set at significantly different levels. For example, the homestead

exemption in Delaware and Maryland is zero, while Arkansas, Florida, Iowa, Kansas, Oklahoma, South Dakota and Texas do not limit homestead exemptions (see Table 3-1⁵⁰).

Recently, the literature on personal bankruptcy decisions is developing remarkably fast, mainly due to increasing availability of household-level bankruptcy filing data. Fay, Hurst and White (2002) describe households’ strategic behavior on filing for bankruptcy by explicitly formulating the financial benefit from bankruptcy. Roughly speaking, it is loans to be discharged less assets to be liquidated in bankruptcy proceedings. They show that the households in the PSID that could obtain greater financial benefit from bankruptcy are more likely to file for bankruptcy, implying the possibility that households in the United States are engaged in strategic

49 Bankruptcy Statistics, U.S. Courts.

50 Table 3-1 summarizes the laws as of 1996 based on Hynes, Malani and Posner (2004).

use of bankruptcy. Bahchieva, Wachter and Warren (2005) find households living in states with high homestead exemptions are likely to have large home equity when they file for bankruptcy by a survey of bankruptcy petitioners. Their result also suggests households’ strategic behavior to protect their homeownerships through the bankruptcy law. On the other hand, another hypothesis has been proposed for personal bankruptcy decisions. Sullivan, Warren and Westbrook (1989) discuss another type of framework to explain the incentive for bankruptcy, namely that

households file for bankruptcy when unexpected adverse events occur which reduce their ability to repay their debts. Fay, Hurst and White (2002) attempt to refute the latter model of borrowers’

ability to pay by their empirical results, but do not completely succeed. Household income, which should be irrelevant in the strategic behavior model, still has a significant effect in discouraging households from filing for bankruptcy. Fisher (2006) reexamines this effect of household income by using a greater number of explanatory variables in the PSID to obtain the same result. These two theories in the field of personal bankruptcy decisions parallel the two theories in the literature on mortgage default: the option-based theory and the theory of trigger events. We can call these two types of theories “the willingness-to-pay theory” and “the ability-to-pay theory”, as I did in Chapter 1.

While the last chapter examined borrowers’ choices between mortgage default and bankruptcy, the present chapter focuses only on households’ bankruptcy decisions and investigates this subject in more detail. The aim of this chapter is to extend the literature by focusing on bankruptcy decisions of households with mortgage debts and on the effects of

homestead exemption and capital gains expectations. As in Chapter 2, I also try to disentangle the two conflicting theories, the willingness-to-pay theory and the ability-to-pay theory, by looking into decisions made by households who are suffering from the combination of severe financial

distress and credit constraints.

This chapter is composed of six sections. The next section develops a model which analyzes households’ decisions on bankruptcy filings. The Section 3 describes the data used in the empirical analysis and presents empirical specifications. The section 4 reports the empirical result. Another empirical result focusing on a smaller subsample of financially distressed

households is examined in Section 5. Lastly, the Section 6 concludes the findings in this chapter.

3.2. Theoretical model for financial benefit from bankruptcy

In this section, I set up a theoretical framework to address the motivation for households to file for bankruptcy. Based on the willingness-to-pay theory, I assume that households file for bankruptcy if they could obtain any financial benefit from bankruptcy, following Fay, Hurst and White (2002). The financial benefit of the representative household from bankruptcy can be represented as follows⁵¹:

[ ] [ ]

[

D H X W X

]

S

FinBen=max −max − _h,0 −max − _w,0,0 − , (3.1)

where D is the value of the household’s unsecured debt that would be discharged in a bankruptcy proceeding, H is the value of the home equity that the household owns, which is defined as the current housing value less the mortgage balance that the household still owes⁵², X_h is the homestead exemption in the household’s state of residence, W is the household’s non-housing wealth net of secured debts such as car loans, X_w is the bankruptcy exemption that could be applied to W in the state where the household resides, and S is the cost of filing bankruptcy, including legal and filing fees, the cost of bankruptcy stigma, and the cost of reduced access to

where D is the value of the household’s unsecured debt that would be discharged in a bankruptcy proceeding, H is the value of the home equity that the household owns, which is defined as the current housing value less the mortgage balance that the household still owes⁵², X_h is the homestead exemption in the household’s state of residence, W is the household’s non-housing wealth net of secured debts such as car loans, X_w is the bankruptcy exemption that could be applied to W in the state where the household resides, and S is the cost of filing bankruptcy, including legal and filing fees, the cost of bankruptcy stigma, and the cost of reduced access to

In document ESTUDIO DE PREFACTIBILIDAD PARA LA ELABORACIÓN DE PLATOS BIODEGRADABLES A BASE DE HOJAS DE PLÁTANO (Musa paradisiaca) (página 129-0)