University of Groningen, Department of Economic Geography

On real cash flow, credit availa-bility, and Asset price inflation

Dennis Schoenmaker and Arno van der Vlist

Motivation

1991 1995 2001 2005 2008

Office market crisis

Drop in M2 Rental

Cre

dit

influx

Asset Value way to high C

redit

av

aila

ble

Aim & Contribution

1) Credit availability, Asset prices, and Rental price Dynamics. – Ling et al, 2011 – Hendershott et al, 2010– Englund et al, 2008

2) Whereas most contributions use appraisal based data, we use transaction based data for the asset and rental market.

Review of Literature

Rental value

M2 RED

Asset Price

M2 Stock

D = S

III

III IV

PRICE = RENT/ cap-rate

P = f(M2 RED)

ΔS = M2 RED –δS

I= Space Market /

Rent determination

II=Assetmarket/ Asset

price determination

III=Assetmarket /

Construction

IV=Space Market /

Supply response

Rent dynamics

Credit and Asset prices

Englund et al 2008

Hendershott et al 2010, 2002, 1999

Jennen, 2008

Wheaton et al., 1994, 1997

Ling et al 2011

Brunnermeier, 2009

Asset price:

1) Chen (2001) found that availability of bank loans are significant in predicting

movements in real estate assets (Taiwan).

2) Ling, et al (2011) found that credit availability is a significant determinant of Asset

prices.

Rent Dynamics:

1) Hendershott, et al (2010) found that the stock and office employment are significant

determinants of the rent (London office market).

2) Brounen and Jennen (2009) found that the vacancy rate and office employment are

significant determinants of the rent (Ten European Cities).

Review of Literature (1)

Data sources, definitions, and descriptives

Table 1- Data

N x T = 17 x 12

Variable Definition Mean Std.dev.

𝑃𝑗𝑡 Real ASSET PRICE (in Euro sq.m) 1,404 439

𝑅𝑗𝑡 Real RENT (in Euro sq.m) 119 15

𝐾𝑗𝑡 CAPITALIZATION RATE (in %) 7.8 0.8

𝐹𝑗𝑡 Real CREDIT (in Mln Euro) 345 107

𝐸𝑗𝑡 EMPLOYMENT (in jobs) 40,787 40,516

𝑆𝑗𝑡 STOCK (in sq.m) 13,039 13,497

𝑉𝑗𝑡 VACANCY ( % stock) 9.8 5.1

Time series1

00

01

50

02

00

0A

SS

ET

PR

ICE

1995 2000 2005 2010year

100

110

120

130

140

RE

NT

1995 2000 2005 2010Year

6.5

77

.58

8.5

9Y

IELD

1995 2000 2005 2010Year

200

300

400

500

600

CR

ED

IT A

VA

ILA

BIL

ITY

1995 2000 2005 2010Year

Time series (1)2

00

00

300

00

400

00

500

00

600

00

700

00

EM

PL

OY

ME

NT

1995 2000 2005 2010Year

500

00

01

00

00

00

150

00

00

200

00

00

250

00

00

ST

OC

K

1995 2000 2005 2010Year

05

10

15

VA

CA

NC

Y

1995 2000 2005 2010Year

Correlation matrix

Table 2 - Correlation matrix

This table presents the correlation matrix between the variables of table 1 to investigate the dependence between the variabl es of interest. ***, and ** denote

significance at the 1 percent, and 5 percent levels, respectively.

𝑃𝑗𝑡 𝑅𝑗𝑡 𝐾𝑗𝑡 𝐹𝑗𝑡 𝐸𝑗𝑡 𝑆𝑗𝑡 𝑉𝑗𝑡 𝑃𝑗𝑡 1 ----- ----- ----- ----- ----- ----- 𝑅𝑗𝑡 0.60 *** 1 ----- ----- ----- ----- ----- 𝐾𝑗𝑡 -0.32 *** -0.18 *** 1 ----- ----- ----- ----- 𝐹𝑗𝑡 0.35 *** -0.01 -0.54 *** 1 ----- ----- ----- 𝐸𝑗𝑡 0.29 *** 0.51 *** -0.15 ** 0.07 1 ----- ----- 𝑆𝑗𝑡 0.36 *** 0.53 *** -0.12 0.09 0.89 *** 1 ----- 𝑉𝑗𝑡 0.33 *** 0.10 -0.43 *** 0.62 *** 0.10 0.07 1

Empirical model

Some assumptions:

The systems is stable if || < 1 .

The parameter shows the speed of return.

and denotes the coefficients of the determinants at lag length q.

Simultaneous equation model:

(1)

(2)

Time series test

* Based on this outcome and the co-integration outcome we perform the empirical

model (1) and (2).

Table 3 - Results for unit root panel test

This table presents unit-root test (Fisher and Hadri) for the time series we use in the simultaneous equation model. Fisher

Augmented Dickey-Fuller test. Ho: there is unit root; Ha: at least one series is stationary: Hadri unit-root test. Ho: there is no

unit root against theHa: there is unit root. Credit availability(𝐹𝑗𝑡) is a time series that does not vary across cross- sectional

units.

𝑃𝑗𝑡 𝑅𝑗𝑡 𝐾𝑗𝑡 𝐹𝑗𝑡 𝐸𝑗𝑡 𝑆𝑗𝑡 𝑉𝑗𝑡

Fisher test 79 110 52 0.27 53 97 15

p-value 0.00 0.00 0.00 1.00 0.02 0.00 0.99

Hadri test 25 21 21 21 21 20 17

p-value 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Results

Table 4 - Estimation results for the dynamic rent model, corrected LSDV estimates

***, and ** denote significance at the 1 percent, and 5 percent levels, respectively.

(1)

(2)

(3)

(4)

𝑙𝑛𝑅𝑗𝑡−1 0.59 *** 0.64 *** 0.64 *** 0.56 ***

(0.13) (0.14) (0.18) (0.12) 𝑙𝑛𝐸𝑗𝑡 0.15 ** 0.13 0.16 ** 0.15 **

(0.07) (0.07) (0.08) (0.06) 𝑙𝑛𝑆𝑗𝑡 - 0.18 *** -0.17 ***

(0.05) (0.06) 𝑙𝑛𝑆𝑗𝑡−1 -0.15 ***

(0.05) 𝑙𝑛(1−𝑉𝑗𝑡)𝑆𝑗𝑡 -0.19 **

(0.08)

Table 5 - Estimation results for the dynamic asset model, corrected LSDV estimates

Results (1)

***, and ** denote significance at the 1 percent, and 5 percent levels, respectively.

(1) (2) (3) (4) (5) (6) (7)

𝑙𝑛𝑃𝑗𝑡−1 0.19 ** 0.26 *** 0.26 *** 0.16 0.13 0.10 0.12

(0.08) (0.08) (0.09) (0.09) (0.09) (0.09) (0.09) 𝑙𝑛𝑅𝑗𝑡 0.86 *** 0.72 ** 0.68 ** 0.79 ** 0.43 0.48

(0.31) (0.33) (0.34) (0.36) (0.38) (0.38) 𝑙𝑛𝑅𝑗𝑡−1 0.31 0.09 0.10

(0.39) (0.40) (0.41) 𝑙𝑛𝑅𝑗𝑡

𝑙𝑛𝐾𝑗𝑡 -0.13 -0.23 -0.03 -0.15 -0.19

(0.16) (0.15) (0.16) (0.18) (0.15) 𝑙𝑛𝐾𝑗𝑡−1 -0.04 0.07

(0.15) (0.16) 𝑙𝑛𝐾𝑗𝑡 -0.12

(0.19) 𝑙𝑛𝐾𝑗𝑡−1 0.24

(0.21) 𝑙𝑛𝐹𝑗𝑡 0.29 *** 0.23 *** 0.33 *** 0.30 *** -0.76 -0.72

(0.07) (0.08) (0.12) (0.09) (0.39) (0.39) 𝑙𝑛𝐹𝑗𝑡−1 0.28 *** 1.09 *** 1.09 ***

(0.11) (0.41) (0.41)

Conclusion + future research

Main findings:

1) Credit availability is an important determinant of Asset price, whereas the Rent is also an

important determinant. Furthermore, rising asset price not related to rising rents can be

described as asset price inflation.

2) The rent equation gives similar outcomes as the Hendershott and Brounen/Jennen approach.

Furthermore, we find higher price elasticities because of the markets we include in the model,

the income elasticity is almost equal.

Further research:

* Incorporation of measures of transaction activity as proposed in Ling et al. (2009) to measure

regional market liquidity.