אמידה סימולטנית של התנהגות היזם ומחירי קרקע - המקרה של שינויים בשימושי קרקע במטרופולין תל אביב

1. אמידה סימולטנית של התנהגות היזם ומחירי קרקע - המקרה של שינויים בשימושי קרקע במטרופולין תל אביב דניאל פלזנשטיין, אייל אשבל וצבי וינוקור כנס האיגוד הישראלי למדע האזור, אוניברסיטת חיפה, 28.11.10

2. The Motivation • In land use models, developer behavior and land prices modeled independently • In practice, the two occur simultaneously • LU models treat land prices as exogenous. But, developer behavior depends on land prices and vice versa, therefore endogeneity issue. • Prices also fixed by expectations of price (rational expectations world)

3. S' (π+1= π) S'' (π+1> π) A B D Theory Relative Price Quantity

4. (–) (+) Supply Demand Z, X = vectors of variables that cause supply/demand curves to shift general price is sum of parcel prices. Equilibrium

5. Estimation Strategy Maddala (1983): simultaneous equations Use probit two-stage least squares (P2SLS) CDSIMEQ routine (STATA Journal 2003) Land price model (OLS) Developer model (probit)

6. Simultaneous equations • y*2 is not observed, rewrite, (1) and (2) as • Estimate reduced form • Extract predicted values • Plug-in fitted values and adjust covariance matrix

7. Estimated Results – Example1

8. Estimated Results – Example 2 ** p< 0.001; * P<0.05

9. Residential Density (persons per grid cell), 2001-2020

10. Residential Land Values, 2001-2020

11. Residential • Simultaneous estimation predicts more population deconcentration. • Residential land values are estimated to be higher in suburban locations than in CBD (using sim. estimation). • Indiv. estimation gives opposite picture: higher residential prices closer to CBD: opposite trend.

12. Density of Commercial Development (sq.m.) 2001-2020

13. Non-Residential Land Values, 2001-2020

14. Non-residential • Non-resid sq m: development starts later but reaches more extreme values • Similar trends to indiv model estimation. Accentuated suburban non-residential development • Simultaneous estimation makes for more extreme values in non- resid land prices. Less smooth price gradient

15. Differences in Households Attributes due to the Two Methods of Estimation

16. Differences in Grid Cells Attributes: Estimated Commercial Land Use (sq m)

17. Differences in Grid Cells Attributes: Number of Estimated Residential Units

18. Differences in Grid Cells Attributes: Change in Share of Residential Land Use

19. Conclusions • Why is simultaneous estimation more volatile? Technical reason: more noise in estimation due to use of fitted values. No true BLUE estimation- goodness of fit is less robust. • But forecasts less likely to be biased; therefore consistently above or below individ. est. (Table). • Behavioral focus on land users not land uses. Therefore, endogenity becomes an issue. • Past behav and future expectations affect the current. Neighbors behavior- another source of endogeneity.

20. Comparison of Estimated Coefficients for Land Price Model (land conversion from residential to no further development)

21. Actual versus Estimated Population, 2002, 2003, select cities

22. Actual versus Estimated Residential Units, 2002, 2003 select cities

23. Actual versus Estimated Employment 2002, 2003, select cities

24. Actual versus Estimated Commercial Floor Space, 2002, select cities