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4 SUMMARY OUTPUT

6 Regression Statistics
7 Multiple R 0.839306575
8 R square 0.704435526
9 Adjusted R square 0.693752473
10 Standard error 0.079631408
11 Observations 87

13 ANOVA

14 df SS MS F Signi¬cance F
15 Regression 3 1.254399586 0.41813 65.93953 6.66022E-22
16 Residual 83 0.526316376 0.00634
17 Total 86 1.780715963
19 Coef¬cients Std Error t Stat P-value Lower 95% Upper 95%
20 Intercept 0.387231995 0.023 16.5698 7.73E-28 0.340750627 0.433713
21 Debt / MVA98 0.115269034 0.043 2.66025 0.00937 0.029086922 0.201451
22 RYld98 2.29555895 0.320 7.17703 2.75E-10 2.931724028 1.659394
23 TNL 0.07286963 0.022 3.35275 0.001207 0.116098278 0.029641
26 Variable X-Coef¬cient Client Data Regress

27 Debt / MVA98 (B33) 0.115269034 0.0% 0.0%
28 RYld98 (Table 9-4, C12) 2.29555895 0.005528601 1.3%
29 TNL 0.07286963 0 0.0%
30 Subtotal 1.3%
31 Intercept 38.7%
32 Discount before adjustments 37.5%
33 Adjustments:
34 No public registration [2] 15.0%
35 Increased in¬‚uence [3] 5.0%
36 Total adjustments 10.0%
37 Discount 47.5%

39 Calculation of Debt / MVA98
40 Debt 0
41 MVA98 (market value of assets-1998) [4] 1,389,185
42 Debt / MVA98 0.0%

[1] Based on the data in Table 9-6B.
[2] The Partnership Pro¬les LPs are publicly registered, which is not true of the Member interests. Thus, the latter should bear a larger discount for that factor.
[3] The Partnership Pro¬les Limited Partners have no in¬‚uence over the Partnership, while the subject Member interests do. We decrease the discount to account for that difference.
[4] Table 9-2, C22.




¬rms are riskier than equity-¬nanced ¬rms, and the higher the risk, the
higher the discount. The negative signs to the other two variables”yield
and triple-net lease”mean that investors consider LPs with higher cash
yields and triple-net leases to be lower risk, which is also true. Thus, our
regression results make intuitive sense. Also, higher cash yields make up
for some of the disadvantage of lack of marketability.
The yields were signi¬cant in nonlinear forms, that is, natural loga-
rithms, denoted as ln, and inverses. Additionally, the cumulative yield



CHAPTER 9 Sample Appraisal Report 339
since inception was also statistically signi¬cant. While these additional
independent variables did add to the adjusted R 2 and lowered the stan-
dard error of the y-estimate, they did not dramatically improve the re-
gression results, and it is far easier and more practical to work with a
much simpler equation.

Commentary to Table 9-6A: Correlation Matrix
Table 9-6A is a correlation matrix. Looking down column B, we can see
that the average discount is strongly negatively correlated to yields (B7“
B10), the restaurant dummy variable (B15), and triple-net leases (B19).
This means that high cash distributions to LPs drive down discounts,
which is intuitive.
Triple-net leases (TNL) also result in lower discounts, which is also
intuitive, because TNL landlords have far less operating risk than other
landlords. The correlation of discounts to restaurants is really an indirect
relationship, because there is a strong positive correlation of 82% (L19)
between TNL and restaurants. In other words, it means that most restau-
rants are on a TNL.
The average discount is strongly positively related only to leverage
(Debt/MVA98) (B6). Looking down column C, we can see that leverage
is strongly negatively related to yields. This also makes sense, as highly
leveraged partnerships have to worry about making their debt payments
before they consider making cash distributions.
It is signi¬cant that the yields across time are highly correlated. For
example, the 1998 yields are 78%, 81%, and 75% correlated to the 1997,
1996, and 1995 yields, respectively, as can be seen in cells D8 through
D10.
By using the 1998 yield as the only yield appearing as an indepen-
dent variable in the regression equation, we still indirectly pick up the
earlier yields because they are so highly correlated. Using only one year™s
yield has the additional bene¬t of removing the problem of multicolli-
nearity. When the subject interest 1998 and earlier yields are uncorrelated,
then it is necessary to use a more long-run value for the 1998 yields. For
example, if 1998 yields are extraordinarily high (low) and expected to
decrease (increase) in the future, then it is appropriate to eliminate the
extraordinary part of the subject interest™s yield and only use that portion
which one would reasonably expect to continue in the future with normal
growth.

Applying the Regression Equation
We apply the above regression equation to the LLC in Table 9-6, Rows
26 to 32. First, we repeat the regression x-coef¬cients from B21 to B23 in
B27 to B29. The LLC™s data are in C27 to C29. The triple-net-lease dummy
variable equals zero, as the LLC™s properties are not subject to TNLs. We
multiply the x-coef¬cients in B27 to B29 by the LLC™s data in C27 to C29
to come to the regression results for the LLC in D27 to D29, which we
subtotal in D30 as 1.3%. We then repeat the y-intercept of 38.7% from
B20 in D31 and add that to the subtotal, to come to a discount before
adjustments of 37.5% (D32).




PART 3 Adjusting for Control and Marketability
340
T A B L E 9-6A

Correlation Matrix


A B C D E F G H I J K L M N O P Q

4 Avg Disc Debt / MVA98 RYld98 RYld97 RYld96 RYld95 C MF R MH RST Combo Parking Eq Dist TNL Indep
5 Avg disc 1.00
6 Debt / MVA98 0.61 1.00
7 RYld98 0.80 0.61 1.00
8 RYld97 0.64 0.42 0.78 1.00
9 RYld96 0.68 0.48 0.81 0.76 1.00
10 RYld95 0.65 0.47 0.75 0.72 0.88 1.00
11 C 0.07 0.12 0.00 0.11 0.15 0.15 1.00
12 MF 0.00 0.28 0.04 0.14 0.12 0.04 0.19 1.00
13 R 0.01 0.06 0.01 0.02 0.02 0.01 0.08 0.14 1.00
14 MH 0.16 0.13 0.07 0.04 0.01 0.04 0.09 0.16 0.07 1.00
15 RST 0.52 0.35 0.40 0.34 0.43 0.41 0.15 0.28 0.12 0.13 1.00
16 Combo 0.20 0.02 0.21 0.18 0.26 0.15 0.20 0.36 0.15 0.17 0.29 1.00
17 Parking 0.09 0.09 0.01 0.01 0.02 0.02 0.05 0.09 0.04 0.04 0.07 0.09 1.00
18 Eq dist 0.14 0.05 0.09 0.09 0.21 0.11 0.04 0.14 0.08 0.31 0.42 0.29 0.17 1.00
19 TNL 0.51 0.22 0.43 0.36 0.46 0.44 0.09 0.34 0.03 0.16 0.82 0.24 0.09 0.51 1.00
20 Indep 0.20 0.37 0.30 0.16 0.16 0.20 0.27 0.43 0.07 0.07 0.40 0.16 0.14 0.11 0.47 1.00
341
T A B L E 9-6B

Partnership Pro¬les Database: Price-to-Value Discounts”1999


A B

5 Name Avg Disc
6 Aetna Real Estate Associates 23%
7 ChrisKen Partners Cash Income 28%
8 Consolidated Capital Inst. Props. 1 28%
9 Consolidated Capital Inst. Props. 2 35%
10 First Capital Inst. Real Estate 4 21%
11 HCW Pension Real Estate Fund 29%
12 I.R.E. Pension Investors II 40%
13 John Hancock Realty Income Fund II 12%
14 Murray Income Properties I 25%
15 Murray Income Properties II 25%
16 Rancon Income Fund I 39%
17 Realty Parking Properties I 8%
18 Realty Parking Properties II 28%
19 Wells Real Estate Fund II-A 8%
20 Wells Real Estate Fund III-A 31%
21 Wells Real Estate Fund IV-A 38%
22 Wells Real Estate Fund VI-A 26%
23 Wells Real Estate Fund VII-A 25%
24 Wells Real Estate Fund VIII-A 24%
25 Wells Real Estate Fund IX-A 24%
26 Wells Real Estate Fund X-A 20%
27 Windsor Park Properties 6 15%
28 Angeles Income Properties II 30%
29 Angeles Opportunity Properties 37%
30 Angeles Partners XII 34%
31 ChrisKen Growth & Income II 16%
32 Consolidated Capital Inst. Props. 3 25%
33 Consolidated Capital Properties III 28%
34 Davidson Growth Plus 41%
35 Davidson Income Real Estate 38%
36 Multi-Bene¬t Realty Fund ™87-1 (A units) 29%
37 Nooney Income Fund II 42%
38 Shelter Properties VII 35%
39 Uniprop Man. Hous. Com. Inc. Fund I 45%
40 Uniprop Man. Hous. Com. Inc. Fund II 41%
41 Windsor Park Properties 3 38%
42 Windsor Park Properties 5 27%
43 Windsor Park Properties 7 46%
44 Angeles Income Properties III 42%
45 Angeles Income Properties IV 42%
46 Angeles Income Properties 6 29%
47 Angeles Partners IX 36%
48 Angeles Partners XI 25%
49 Consolidated Capital Properties V 52%
50 Davidson Diversi¬ed Real Estate I 62%




Adjustments to the Discount
For Lack of Public Registration. The Partnership Pro¬les database
consists exclusively of ¬rms that are publicly registered, though privately
traded. The lack of public registration of the member interests renders
them less marketable than the Partnership Pro¬les database. Therefore
we must increase the fractional interest discount for that factor. We as-
sume that a 15% increase is reasonable (D34).

PART 3 Adjusting for Control and Marketability
342
T A B L E 9-6B (continued)

Partnership Pro¬les Database: Price-to-Value Discounts”1999


A B

5 Name Avg Disc
51 Davidson Diversi¬ed Real Estate II 61%
52 Davidson Diversi¬ed Real Estate III 38%
53 First Capital Income Properties XI 41%
54 First Capital Income & Growth Fund XII 44%
55 First Dearborn Income Properties 58%
56 Multi-Bene¬t Realty Fund ™87-1 (B units) 57%
57 InLand Capital Fund 47%
58 Inland Land Appreciation Fund I 45%
59 Inland Land Appreciation Fund II 48%
60 Scottsdale Land Trust 46%
61 CNL Income Fund III 9%
62 CNL Income Fund V 9%
63 CNL Income Fund VI 15%
64 CNL Income Fund VII 11%
65 CNL Income Fund VIII 16%
66 CNL Income Fund IX 11%
67 CNL Income Fund X 12%
68 CNL Income Fund XI 17%
69 CNL Income Fund XII 13%
70 CNL Income Fund XIII 15%
71 CNL Income Fund XIV 8%
72 CNL Income Fund XV 6%
73 CNL Income Fund XVI 14%
74 CNL Income Fund XVIII 7%
75 Carey Institutional Properties 28%
76 Corporate Property Associates 10 16%
77 Corporate Realty Income Fund I 27%
78 DiVall Income Properties 3 12%
79 DiVall Insured Income Properties 2 1%
80 John Hancock Realty Income Fund III 12%
81 Net 1 LP 23%
82 Net 2 LP 28%
83 Capital Mortgage Plus 23%
84 Capital Source LP 15%
85 Capital Source LP II 22%
86 Krupp Government Income Trust 10%
87 Krupp Government Income Trust II 15%
88 Krupp Insured Mortgage LP 9%
89 Krupp Insured Plus LP 15%
90 Krupp Insured Plus II 11%
91 Krupp Insured Plus III 2%
92 Paine Webber Insured Mortgage 1-B 21%
93 Max 61.7%
94 Min 0.8%
95 Mean 26.8%
96 Std deviation 14.4%




For Additional In¬‚uence of Private versus Public Interest. The
member interests should have more in¬‚uence than the small LP interests
from which we calculated the regression coef¬cients, and they actually
do have a vote. We reduce the discount by 5% in D35.
The adjustments for lack of public registration and additional in¬‚u-

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