1. The Determinants of Retail Space Market Dynamics in US MSAs Pat Hendershott, University of Aberdeen Maarten Jennen, Erasmus University in Rotterdam Bryan MacGregor, University of Aberdeen

2. 1. Background Space market dynamics: real rent and vacancy rate System model: one exogenous variable; system of equations Panel data set Error Correction framework: –Time-varying long run equilibrium relationship to which the system tends –Short run movements are driven by shock variables and by lagged adjustments to equilibrium Consider asymmetries in the adjustment processes

3. 2. Literature Rental adjustment model - linking real rental change to deviation of the vacancy rate from its natural level; additional variable for deviation from equilibrium rent in Hendershott (1995); mainly offices. Models with a series of equations - with rental adjustment equation; such as Wheaton, Torto and Evans (1997); Hendershott, Lizieri and Matysiak (1999); offices. Error Correction Model approach for modelling rent: Hendershott, MacGregor and Tse (2002). Panel modelling of rents: Hendershott, MacGregor and White (2002); and cap rates: Hendershott and MacGregor (2005a, 2005b). Introduction of vacancy rate into long run model for a system: Hendershott, MacGregor and Tse (2002); developed by Englund, Gunnelin, Hendershott and Soderberg (2008); used by Hendershott, Lizieri and MacGregor (2009). Consideration of asymmetries: Hendershott, Lizieri and MacGregor (forthcoming) and Brounen and Jennen (forthcoming). Partitions: for UK - Hamelink, Hoesli, Lizieri and MacGregor (2000); Hoesli, Lizieri and MacGregor (1997); for US - Mueller (1993); Hartzell, Heckman and Miles (1986).

4. 3. The long run model Demand is: In equilibrium: Solving for R: Estimated in logs as: Allowing constant to vary in cross-section is required to allow the natural availability rate to vary

5. 4. The short run model The short run equations are: v* is estimated as –α 0 /α 3 and –β 0 /β 3 and -μ 0 /μ 2

6. 5.Data Panel data Thirteen MSAs retail markets: Atlanta; Boston; Chicago; Dallas; Houston; Los Angeles; Minneapolis; New York; Philadelphia; Phoenix; Riverside; Seattle; Washington DC. Quarterly for 1982q4 to 2008q3 Series: real rent; availability rate (analogous to the vacancy rate); real retail sales; supply.

7. 6.Choosing long run models Model: Constant is: Elasticities are λ 1 =1/γ 2 ; λ 2 = γ 1 / γ 2 Let all combinations of the constant, γ 1 and γ 2 vary (8 possibilities) and consider average elasticities and SDs: –Common and separate models produce very different results –‘Retail sales & constant’ & ‘retail sales & supply’ - incorrect signs –‘Retail sales alone’ prevents natural availability rate from varying in CS –‘Fixed effects’ & ‘supply alone’ models similar –Focus on ‘fixed effects’ and ‘supply & constant’ models

8. 7. Long run model Dependent Variable: ln(real rent) Method: Pooled EGLS (Cross-section SUR)Sample: 1982Q4 2008Q3 VariableCoeff.Std. Errt-Stat constant7.6180.047162.561 ln(real retail sales)0.5600.00783.237 ln(supply)-0.6650.006-116.868 Fixed Effects (Cross) Atlanta0.200Minneapolis-0.416 Boston-0.138New York-0.353 Chicago0.026Philadelphia-0.020 Dallas0.057Phoenix0.320 Houston-0.059Riverside0.130 Los Angeles-0.024Seattle-0.211 Washington0.489 Adjusted R-squared0.988

9. 8.Panel system results dln(real rent)d(availability rate)dln(supply) Variablecoeff.t-statcoeff.t-statcoeff.t-stat constant0.0011.8210.009-1.1270.0013.600 dln(real rent) (-1)0.78450.190 d(availability rate) (-1)0.40616.293 dln(supply) (-1)0.89170.105 dln(real retail sales)0.0553.632-0.463-4.890 dln(supply)-0.034-1.1591.1295.099 rent error (-1)-0.014-6.622-0.007-0.250 availability rate (-1)-0.012-2.080 Constrained -0.1512 availability rate (-12) (4q MA)0.00020.105 Adjusted R-squared0.6840.2360.791 Implied natural rate5.8% -343.7

10. 9.Short run rent model VariableCoeff.Std. Errt-Stat constant0.0030.0012.359 dln(real rent) (-1)0.7720.01647.912 dln(real retail sales+)/(av(-1)/av*)0.0810.0165.082 dln(real retail sales-)*(av(-1)/av*)0.0540.0262.085 dln(supply)*(av(-1)/av*)0.0300.0241.248 availability rate (-1)-0.0410.012-3.432 rent error + (-1)-0.0160.003-5.040 rent error - (-1)-0.0100.003-3.724 Adjusted R-squared0.711

11. 10.Short run availability model VariableCoeff.Std. Errt-stat constant0.0310.0065.300 change in availability rate (-1)0.4450.02418.449 dln(real retail sales)+*(av(-1)/av*)-0.2730.099-2.769 dln(real retail sales)-/(av(-1)/av*)-0.3660.151-2.433 dln(supply)/(av(-1)/av*)1.5680.1689.336 availability rate (-1)-0.4410.062-7.104 rent error + (-1)-0.0610.014-4.296 rent error - (-1)-0.0230.015-1.473 Adjusted R-squared (weighted statistics)0.335

12. 11.Change in supply VariableCoeff.Std. Errt-Stat. Constant0.0020.0013.518 dln(supply) (-1)0.8390.01555.336 availability rate 4q MA (-12)-0.0150.007-2.136 Adjusted R-squared0.756

13. 12.Implied natural availability rates RentAvailabilitySupply Atlanta 6.1%7.4%18.1% Boston 2.6%5.3%11.8% Chicago 10.8%9.9%20.1% Dallas 5.3%9.5%14.2% Houston 8.4%9.4%14.7% Los Angeles 6.2%4.7%13.2% Minneapolis 6.9%5.9%13.7% New York 0.6%3.5%8.8% Philadelphia 6.0%7.2%14.9% Phoenix 9.7%9.0%19.8% Riverside 14.3%12.3%26.7% Seattle 2.7%3.8%13.0% Washington 0.9%3.3%10.2%

14. 13.Comparing elasticities for partitions PartitionMeanSDSD rank IncomeReal retail sales growth0.940.125 Supply level0.990.144 Real rental growth0.910.421 Availability rate0.860.046 Supply growth0.890.223 Region1.070.322 PriceReal retail sales growth-1.660.396 Supply level-2.020.733 Real rental growth-1.702.661 Availability rate-1.470.505 Supply growth-1.560.534 Region-1.950.992

15. 14.Conclusions and further work The basic model framework (panel; ECM; system; three equations) works well. Add equation for absorption; alternative supply equation Alternative form of long run models with supply and the constant varying in CS Further consider of asymmetries Development of SR models for the partitions