494-504 1998 10 22 1999 3 23
(stock-flow model)
(cobweb theory)
-1985
1994
1989
(1)1987
1989
1 9 9 8
1994
1996
(cobweb theory)
(2)(stock-flow model)
( F i s h e r , 1 9 9 2 ;
DiPasquale et al., 1992, 1994, 1996; Renaud et al.,
1996)
(sub-market)
(3)
(futures)
1996
Chang et al., 1993
Fisher(1992), DiPasquale & Wheaton
(1992, 1994,1996)
1973
1993
(housing service)
(4)(rent)
(Smith, 1974; Smith et al.,1988)
(5)
(space
market)
( a s s e t
market)
(6)(Fisher, 1992; DiPasquale et al., 1992; Renaud
et al., 1996)
DiPasquale & Wheaton (1994)
1963-1990
0.29
0.02
(7) (8) (9)(
)
(10) (11) (12) (13)(
)
(P)
(R)
(i)
( P = R / i )
(futures market)
(forwards market)
(14)
(risk premium)
(15)1996
Chang & Ward,1993
(16)
(
)
1.
2.
3.
(
)
1.
(PS)
(ST)
(PP)
(EXP)
(H)
(Y)
(1)
PS = f (PP, ST, H, Y, EXP)
(1)
+ - + + +
2.
(2)
PP = f (PS, EXP)
(2)
+ +
3.
(QNEW)
(COST)
(3)
QNEW = f (PP, COST, EXP)
(3)
+ - +
4.
( S T
t)
(ST
t-1)
(17)dST
td
ST = ST
t-1+QNEW
t+
QNEW
t-1−
dST
t(4)
ST
t= f (ST
t-1, QNEW
t, QNEW
t-1)
(4)
+ + +
(
)
(P
t*)
(P
t-1)
(
τ
)
(18)P
t- P
t-1=
τ
(P
t *- P
t-1)
(5)
(5)
P
PS
PP
P
t=
τ
P
t*+ (1-
τ
)P
t-1(5)
(6)
(19)PS
*= a
0+ a
1ST + a
2H + a
3Y + a
4EXP +
µ
1(6)
(6)
(5)
(7)
α
PS
t=
α
0+
α
1ST +
α
2H +
α
3Y +
α
4EXP + (1-
α
)PS
t-1(7)
(20)(8)
PP
t *= b
0+ b
1QNEW + b
2COST +
b
3EXP +
µ
2(8)
(8)
(5)
(9)
β
PP
t=
β
0+
β
1COST +
β
2QNEW +
α
3EXP +
(1-
β
)PP
t-1(9)
(
∆
ST
t)
(ST
t *)
(ST
t-1)
(
π
)
(10)
∆
ST
t=
π
(ST
t*- ST
t-1)
(10)
ST
t *= c
0+
c
1PS + c
2H + c
3Y + c
4EXP +
µ
2(10)
(11)
π
QNEW =
γ
0+
γ
1PS +
γ
2H +
γ
3Y +
γ
3EXP +
π
ST
t-1(11)
(
)
1973
1993
(
)
1.
(1)
(4)
(22)(log-log form)
(23) (PS) (1995a) (21) (1971-1993) (PP) (1995a) 1973-1993 (EXP) (1995b) 1971-1994 (ST) 1980 1990 1989 (Y) (H) (COST) (QNEW)(1)
(-1.374)
(2)
1%
0.679%
(2.663
-1.842)
(3)
(1.304
3.155)
1
0
(1996)
(4)
(1.091)
lnPS InPP lnQNEW lnST -21.249** -8.798* 31.337** -1.219* (-3.063) (-2.037) (1.663) (-1.816) lnPP 0.679** -1.374** (9.092) (-3.656) lnPS 1.304** (9.113) lnY -0.118 (-0.589) lnH 2.663** (4.074) lnCOST 1.632 (1.408) lnSTt -1.842** (-3.515) lnSTt-1 1.091** (30.913) InQNEW -0.009 (-0.488) lnQNEWt-1 0.007 (0.348) lnEXP 0.803 3.155* 4.324 (0.803) (2.785) (0.909) System weighted R2: 0.9680 D.W. 1.877 1.041 1.256 1.517 t *5% ** 1%
2.
(7)
(9)
(11)
(24)
(1)
0.132
(25)0.527
DiPasquale et. al. (1994)
0.29
(2)
lnPS lnPP lnQNEW -20.901* -2.840 -4.683 (-2.789) (-0.472) (-0.152) lnPP -0.872 (-1.061) lnPS -0.750 (-0.659) lnPSt-1 0.868** (8.010) lnPPt-1 0.473** (3.174) lnSTt-1 -1.520* -0.521 (-2.786) (-0.174) lnQNEW -0.382* (-2.836) lnH 2.405** 1.949 (3.212) (0.472) lnEXP 2.001 2.348* 1.897 (1.523) (1.955) (0.371) System weight R2: 0.9480 D.W. 1.779 1.094 1.524 0.132** 0.527** 0.52 t *10% ** 1%NSC-86-2415-H-004-024
(1) OECD Renaud (1997) (2) Heckman (1985) (3) (4) (Olsen 1969; Muth 1960) (5) 1996 1994 (6) P R i ST d QNEW COST D (7) (8) (sufficiency condition) (necessity condition) (9) (10) 1990 20% 1995 76.52% (11) 1994 1995b (12) 1981-1990 1 3.5 50 73 QNEW P P / i R D ST ∆ST = QNEW-dST QNEW = f (P, COST) P2% 5% (13) 1982-1996 1988 77,361 1993 43,849 10% (14) (1996) (15) (16) (1996) PP = PS (1 + c(.)) PP PS c(.) 0 0 (17) (18) 1 0 1 (19)
(linear form) (semi-log form) (log-log form) (goodness of fit) (1994) (1990) (6) (8) (7) (9) (11) (20) (21) 1995a (22)
(rank condition) (order
c o n d i t i o n ) (identified) (23) (1) (4) (Durbin-Watson value) (24) DiPasquale et al. (1994) 19 (25) (α) 1 1 - 0.868 = 0.132 (1996) (1994) 2: 49-66 (1994) 68: 295-313 (1996) 5: 1-15 (1995a) (1995b) (NSC-84-301-H-004-001) (1996) (1994) (1998) 26(4) 409-429 (1990) 397-429
Chang, C. & Ward, C. (1993). Forward Pricing and the Housing Market: the Pre-sales Housing System in Taiwan. Journal of Property
Research, 10, 217-227.
DiPasquale, D. & Wheaton, W. C. (1992). The Markets for Real Estate Assets and Space: A Conceptual Framework. AREUEA, 20(1), 181-197.
DiPasquale, D. & Wheaton, W. C. (1994). Housing Market Dynamics and the Future of Housing. Journal of Urban Economics, 35, 1-22.
DiPasquale, D. & Wheaton, W. C. (1996). Urban Economics and Real
Estate Markets, Englewood Cliffs, NJ: Prentice Hall.
Fisher, J. D. (1992). Integrating Research on Markets for Space and Capital. AREUEA, 20(1), 161-180.
Heckman, J. S. (1985). Rental Price Adjustment and Investment in the Office Market. AREUEA, 13(1), 32-47
Olsen, E. O. (1969). A Competitive Theory of the Housing Market.
American Economic Review, 59, 612-22.
Muth, R. F. (1960). The Demand for Non-Farm Housing. In: A. Harberger (ED.), The Demand for Durable Goods (pp.29-96). Chicago: University of Chicago Press.
Renaud, B. M. (1997). The 1985 to 1994 Global Real Estate Cycle: An Overview. Journal of Real Estate Literature, 5, 13-44 Renaud, B. M., Pretorius, F. & Pasadilla, B. O. (1996). The Use of the
Modern Real Estate Paradigm in Comparative Work: A Test for Hong Kong. Presented on the 5th AREUEA Annual International Real Estate Conference.
Smith, L. B., Rosen, K. T. & Fallis, G. (1988). Recent developments in Economic Models of Housing Markets. Journal of Economic
Literature, 26, 29-64
Smith, L. B., (1974). A Note on the Price Adjustment Mechanism for Rental Housing. American Economic Review, 64(3), 478-81.
The Price-Quantity Relationship between
Exist-ing and Pre-sales HousExist-ing Markets: A
Modifica-tion of Housing Stock-Flow Model
C
HING-C
HUNH
UAANDC
HIN-O
HC
HANGDepartment of Land Economics National Chengchi University
Taipei, Taiwan R.O.C.
ABSTRACT
In Taiwan, the housing market can be divided into two sub-markets: existing and pre-sales. The existing market is similar to a spot market. The pre-sales market is like a futures (forward) market since the goods in the pre-sales market are the housing units under construction (Chang and Ward (1993)). We modify the stock-flow model of Fisher (1992) and DiPasquale and Wheaton (1992, 1994, 1996) and use the data obtained from the housing markets in Taiwan to analyze price and quantity relationship between the existing housing market and the pre-sales housing market.
We calculate the rate at which the market price adjusts to the long-run equilibrium in both the existing and the pre-sales markets. The results show that the adjustment rate in the pre-sales market is greater than that in the existing market. In other words, the pre-sales housing price adjusts to the long run equilibrium faster than the existing housing price. Therefore the pre-sales system can improve market efficiency. We also calculate the rate at which the housing supply quantity adjusts to the long-run equilibrium in both the existing and the pre-sales markets. No significant rela-tionship can be detected between these two rates.
