1# RECORD fc9d39b019f0526d9688d6cea3c777de313aea1d2# TITLE: Factors influencing the value of houses: Estimates for the city of Cagliari, Italy3# YEAR: 2015.0 VENUE: nan DOI: 10.1016/j.landusepol.2014.08.0124# AUTHORS: C. Zoppi; M. Argiolas; S. Lai5# PAGES: 45 CANDIDATE TABLE PAGES (1-based): [39, 40, 41, 42, 43, 44]6# ABSTRACT: Abstract The aim of this paper is to analyze the relationship between housing values and a set of determinants, related both to the urban environment and to the structural characteristics of the housing market, in the metropolitan area of Cagliari. In order to achieve this aim, a sample of residential properties spread across the urban context was taken into account. For every single residential unit we study the value of houses, identified as their estimated value, cadastral value, rent value, value supplied by the National Observatory on Real Estate Market, and finally sale value as related to factors which are identified as relevant variables in several studies concerning the real estate market. The adopted approach implies data collection concerning value and characteristics of houses. The resulting dataset is geocoded and spatially analyzed, in order to identify spatial autocorrelation of the value of houses and its correlations with respect to the characteristics of houses through the hedonic approach. The methodological approach can be easily replicated and exported with reference to other Italian and European urban contexts and results could be straightforwardly comparable. Policy implications of the findings could be a point of reference for future Italian and European planning policies concerning housing markets and the improvement of the quality of urban life.789===== PAGE 1 (score 11, numeric-paren 0, table-words 0, var-words 11) =====1011 12 13This is the accepted version of the following article: 14Zoppi C., Argiolas M., Lai S. (2015) Factors influencing the value of houses: Estimates for the city of 15Cagliari, Italy. Land Use Policy, 42, pp. 367-380 ISSN: 0264-8377. 16http://dx.doi.org/10.1016/j.landusepol.2014.08.012 17 181. Introduction 19Our interpretive point of view concerning the value of houses is that this value reflects the 20quality of urban life. The improvement or decline in the quality of urban life determines bene-21fit or damage to homeowners, since they experience a change in the quality of life, and to 22landlords, who receive higher or lower rents. So, in our view the value of a house is essential-23ly related to its character of a composite good, which is bought and sold in the housing market 24as a parcel of characteristics, which determine its market price (among many, Palmquist, 251984, and Cheshire and Sheppard, 1995). 26As a consequence, we propose to study the quality of life concerning an urban context 27through the analysis of the housing market where we observe equilibrium prices concerning 28purchases and sales of parcels of housing values’s determinants. Such determinants are 29grouped into four distinct categories as follows: i. structural characteristics of the residential 30unit (such as unit size, distance from the shoreline, qualitative indexes accounting, inter alia, 31for the building age, the apartment level and the maintenance level); ii. neighborhood demo-32graphic characteristics (such as residential density both in the census ward and in the city dis-33trict in which the property is located, or the number of permanent foreign residents living in 34the district); iii. plan-related characteristics (such as the presence of residential zones within a 35given distance from the property, proximity to parks or other green areas, and to common 36public services), and iv. land cover types. In order to analyze the relationship between housing 37prices and the aforementioned potential constituent characteristics, we pursue an approach 38based on a hedonic model in order to figure out the general willingness to pay for a specific 39commodity among the municipal area of Cagliari (Sardinia). 404142===== PAGE 39 (score 37, numeric-paren 0, table-words 11, var-words 11) =====4344 45 46 47 Variable 48Definition 49Mean 50St.dev. 51 52Characteristics of housing units, vector HUNIT in (5) 53 54AREA 55Finished interior area (m2) (source: 2012 direct survey) 56109.43 5734.89 58 59Q_POS 60Position quality (presence and quality of panoramic views, distance from other buildings and 61structures / daylighting quality, apartment level). 624.52 631.84 64 65Q_TYP 66Typological quality (building and apartment maintenance level, quality of construction, equip-67ment and mechanical system conditions, building age). 684.19 691.41 70 71DISCOAST 72Distance from the coastline (m) (source: Spatial Dataset of the Regional Geographic Infor-73mation System of Sardinia7) 741788.15 75877.80 76 77Demographic characteristics of the neighborhood where a house is located, vector DEMOG in (5) 78 79DENSITY 80Population density in the Census tract (residents/km2) (source: 2001 National Survey of the 81Italian National Institute of Statistics concerning population and houses) 8221704.12 8310632.79 84 85 86FOR_2012 87Permanent foreign residents in the neighborhood (foreign residents) (source: 2012 Survey of 88the Municipality of Cagliari) 89354.17 90203.23 91 92 93RES_2012 94Residents in the neighborhood (residents) (source: 2012 Survey of the Municipality of Cagliari) 957645.28 962978.05 97 98Plan-related characteristics of the neighborhood where a house is located, vector PLANREL in (5) 99 100PL_ZONE 101Dummy, location in a residential completion area (source: Masterplan of the City of Cagliari, 102available on the Internet at: http://www.comune.cagliari.it/portale/it/puc.wp [last accessed: Au-103gust 1, 2014]) 1040.12 1050.33 106 107A_ZONE 108Area of the “A” zone in a buffer of 150 m around the location of a house (m2) (source: 109Masterplan 110of 111the 112City 113of 114Cagliari, 115available 116on 117the 118Internet 119at: 120http://www.comune.cagliari.it/portale/it/puc.wp [last accessed: August 1, 2014]) 1214753.14 12211935.82 123 124B_ZONE 125Area of the “B” zone in a buffer of 150 m around the location of a house (m2) (source: 126Masterplan 127of 128the 129City 130of 131Cagliari, 132available 133on 134the 135Internet 136at: 137http://www.comune.cagliari.it/portale/it/puc.wp [last accessed: August 1, 2014]) 13833033.85 13914514.09 140 141C_ZONE 142Area of the “C” zone in a buffer of 150 m around the location of a house (m2) (source: 143Masterplan 144of 145the 146City 147of 148Cagliari, 149available 150on 151the 152Internet 153at: 154http://www.comune.cagliari.it/portale/it/puc.wp [last accessed: August 1, 2014]) 155400.78 1562262.48 157 158EZ_ZONE 159Area of the “EZ” zone in a buffer of 150 m around the location of a house (m2) (source: 160Masterplan 161of 162the 163City 164of 165Cagliari, 166available 167on 168the 169Internet 170at: 171http://www.comune.cagliari.it/portale/it/puc.wp [last accessed: August 1, 2014]) 172678.98 1733287.24 174 175MIXUSE 176Percent area of the “IS” zone in a buffer of 150 m around the location of a house (percent) 177(source: 178Masterplan 179of 180the 181City 182of 183Cagliari, 184available 185on 186the 187Internet 188at: 189http://www.comune.cagliari.it/portale/it/puc.wp [last accessed: August 1, 2014]) 19012.66 19111.78 192 193PARKS 194Area of the “S3”and recreational “G” zones in a buffer of 800 m around the location of a house 195(m2) (source: Masterplan of the City of Cagliari, available on the Internet at: 196http://www.comune.cagliari.it/portale/it/puc.wp [last accessed: August 1, 2014]) 19724.17 19813.68 199 200Artificial land cover of the neighborhood where a house is located, variable LANDCOV in (5) 201 202LC_URB 203Artificial surfaces, urban fabric in 2008 (m2) (source: CORINE Land Cover Map of Sardinia – 2042008 Edition, level 2, code 1.1) 20564577.89 2069560.18 207 208 209Spatially-lagged dependent variables (see paragraph 4.1.1) 210 211CAD_LAG 212Spatially-lagged dependent variable, spatial lags of variables reported in Table 2, CAD_VAL 213706.25 214132.22 215 216EST_LAG 217Spatially-lagged dependent variable, spatial lags of variables reported in Table 2, EST_VAL 2182261.10 219327.11 220 221OMI_LAG 222Spatially-lagged dependent variable, spatial lags of variables reported in Table 2, OMI_VAL 2232313.08 224264.05 225 226RENT_LAG 227Spatially-lagged dependent variable, spatial lags of variables reported in Table 2, RENT_VAL 2287.79 2290.78 230 231SUPP_LAG 232Spatially-lagged dependent variable, spatial lags of variables reported in Table 2, SUPP_VAL 2332497.37 234346.92 235 236Table 3. Definition of characteristics of houses and of neighborhoods where houses area located, and 237descriptive statistics. 238 239 2407 Available on the Internet from the Regional Geoportal, at: http://www.sardegnageoportale.it/index.html [last 241accessed: August 1, 2014]. 242243244===== PAGE 40 (score 23, numeric-paren 0, table-words 6, var-words 5) =====245246 247 248 249Variable 250Coefficient Stand.error t-statistic Hypothesis test: coefficient=0 251Constant 252542.2240 253203.9922 2542.658 2550.0083 256AREA 2570.4507 2580.4957 2590.909 2600.3640 261Q_POS 2627.8002 2639.0757 2640.859 2650.3908 266Q_TYP 26713.5892 26811.9822 2691.134 2700.2577 271DISCOAST 272-0.0371 2730.0297 274-1.248 2750.2130 276DENSITY 277-0.0021 2780.0017 279-1.270 2800.2052 281FOR_2012 2820.1165 2830.1406 2840.829 2850.4077 286RES_2012 287-0.0037 2880.0086 289-0.433 2900.6651 291PL_ZONE 292-200.8341 293147.2615 294-1.364 2950.1737 296A_ZONE 297-0.0035 2980.0045 299-0.784 3000.4337 301B_ZONE 302-0.0050 3030.0030 304-1.687 3050.0927 306C_ZONE 307-0.0018 3080.0089 309-0.206 3100.8370 311EZ_ZONE 3120.0076 3130.0057 3141.325 3150.1863 316MIXUSE 317-2.2312 3181.9821 319-1.126 3200.2612 321PARKS 3228.80E-05 3230.0001 3240.588 3250.5572 326LC_URB 3270.0016 3280.0022 3290.713 3300.4763 331CAD_LAG 3320.3395 3330.1458 3342.329 3350.0205 336Adjusted R-squared= 0.0900 337 338Table 4. OLS results, dependent variable CAD_VAL: the regression model includes the covariates of 339Table 3. 340341342===== PAGE 41 (score 23, numeric-paren 0, table-words 6, var-words 5) =====343344 345 346 347Variable 348Coefficient Stand.error t-statistic Hypothesis test: coefficient=0 349Constant 3501549.8007 351224.0705 3526.917 3530.0000 354AREA 355-2.8768 3560.4852 357-5.929 3580.0000 359Q_POS 36071.3490 3618.9995 3627.928 3630.0000 364Q_TYP 36543.0423 36611.8714 3673.626 3680.0003 369DISCOAST 370-0.0822 3710.0305 372-2.696 3730.0074 374DENSITY 375-0.0048 3760.0017 377-2.903 3780.0040 379FOR_2012 3800.3796 3810.1425 3822.663 3830.0082 384RES_2012 385-0.0164 3860.0086 387-1.912 3880.0569 389PL_ZONE 390-237.8951 391146.9027 392-1.619 3930.1065 394A_ZONE 395-0.0060 3960.0045 397-1.348 3980.1787 399B_ZONE 400-0.0059 4010.0030 402-1.990 4030.0475 404C_ZONE 405-0.0179 4060.0088 407-2.039 4080.0423 409EZ_ZONE 410-0.0088 4110.0056 412-1.557 4130.1205 414MIXUSE 415-5.7069 4161.9711 417-2.895 4180.0041 419PARKS 4200.0002 4210.0001 4221.524 4230.1287 424LC_URB 425-0.0002 4260.0022 427-0.081 4280.9357 429EST_LAG 4300.4775 4310.0630 4327.577 4330.0000 434Adjusted R-squared= 0.5208 435 436Table 5. OLS results, dependent variable EST_VAL: the regression model includes the covariates of 437Table 3. 438439440===== PAGE 42 (score 23, numeric-paren 0, table-words 6, var-words 5) =====441442 443 444 445Variable 446Coefficient Stand.error t-statistic Hypothesis test: coefficient=0 447Constant 4481941.9215 449110.8157 45017.524 4510.0000 452AREA 453-0.4112 4540.2190 455-1.878 4560.0614 457Q_POS 45821.5585 4594.0668 4605.301 4610.0000 462Q_TYP 4631.9950 4645.3698 4650.372 4660.7105 467DISCOAST 468-0.0838 4690.0140 470-5.986 4710.0000 472DENSITY 473-0.0009 4740.0008 475-1.168 4760.2436 477FOR_2012 4780.1709 4790.0633 4802.698 4810.0074 482RES_2012 483-0.0190 4840.0039 485-4.934 4860.0000 487PL_ZONE 488-171.1874 48966.2100 490-2.586 4910.0102 492A_ZONE 493-0.0034 4940.0020 495-1.679 4960.0943 497B_ZONE 498-0.0025 4990.0013 500-1.861 5010.0637 502C_ZONE 503-0.0077 5040.0040 505-1.936 5060.0538 507EZ_ZONE 508-0.0066 5090.0026 510-2.603 5110.0097 512MIXUSE 513-3.7663 5140.8908 515-4.228 5160.0000 517PARKS 5180.0003 519.67E-04 5204.638 5210.0000 522LC_URB 523-0.0006 5240.0010 525-0.637 5260.5245 527OMI_LAG 5280.3096 5290.0353 5308.780 5310.0000 532Adjusted R-squared= 0.6725 533 534Table 6. OLS results, dependent variable OMI_VAL: the regression model includes the covariates of 535Table 3. 536537538===== PAGE 43 (score 23, numeric-paren 0, table-words 6, var-words 5) =====539540 541 542 543Variable 544Coefficient Stand.error t-statistic Hypothesis test: coefficient=0 545Constant 5467.2509 5470.3599 54820.148 5490.0000 550AREA 551-0.0017 5520.0007 553-2.492 5540.0133 555Q_POS 5560.0852 5570.0129 5586.618 5590.0000 560Q_TYP 5610.0138 5620.0170 5630.814 5640.4163 565DISCOAST 566-0.0002 5674.31E-05 568-4.187 5690.0000 570DENSITY 571-2.91E-07 5722.38E-06 573-0.122 5740.9029 575FOR_2012 5760.0005 5770.0002 5782.680 5790.0078 580RES_2012 581-8.04E-05 5821.22E-05 583-6.591 5840.0000 585PL_ZONE 586-0.5894 5870.2092 588-2.817 5890.0052 590A_ZONE 591-4.33E-06 5926.36E-06 593-0.681 5940.4965 595B_ZONE 596-1.01E-05 5974.24E-06 598-2.385 5990.0177 600C_ZONE 601-3.22E-05 6021.26E-05 603-2.558 6040.0111 605EZ_ZONE 606-2.52E-05 6078.06E-06 608-3.131 6090.0019 610MIXUSE 611-0.0089 6120.0028 613-3.149 6140.0018 615PARKS 6167.25E-07 6172.09E-07 6183.479 6190.0006 620LC_URB 621-4.73E-06 6223.10E-06 623-1.523 6240.1289 625RENT_LAG 6260.2300 6270.0347 6286.629 6290.0000 630Adjusted R-squared= 0.5810 631 632Table 7. OLS results, dependent variable RENT_VAL: the regression model includes the covariates of 633Table 3. 634635636===== PAGE 44 (score 23, numeric-paren 0, table-words 6, var-words 5) =====637638 639 640 641Variable 642Coefficient Stand.error t-statistic Hypothesis test: coefficient=0 643Constant 6441851.8704 645131.5397 64614.078 6470.0000 648AREA 6490.3880 6500.2667 6511.454 6520.1469 653Q_POS 654-2.3448 6554.9547 656-0.473 6570.6364 658Q_TYP 659-2.0876 6606.5567 661-0.318 6620.7504 663DISCOAST 664-0.0849 6650.0179 666-4.738 6670.0000 668DENSITY 669-0.0019 6700.0009 671-2.052 6720.0411 673FOR_2012 6740.2017 6750.0775 6762.602 6770.0098 678RES_2012 679-0.0191 6800.0047 681-4.078 6820.0001 683PL_ZONE 684-128.3240 68580.6387 686-1.591 6870.1126 688A_ZONE 689-0.0026 6900.0025 691-1.072 6920.2844 693B_ZONE 694-0.0046 6950.0016 696-2.805 6970.0054 698C_ZONE 699-0.0080 7000.0048 701-1.652 7020.0997 703EZ_ZONE 704-0.0092 7050.0031 706-2.966 7070.0033 708MIXUSE 709-5.0426 7101.0845 711-4.650 7120.0000 713PARKS 7140.0006 715.88E-04 7166.936 7170.0000 718LC_URB 719-0.0011 7200.0012 721-0.891 7220.3736 723SUPP_LAG 7240.4332 7250.0383 72611.319 7270.0000 728Adjusted R-squared= 0.7514 729 730Table 8. OLS results, dependent variable SUPP_VAL: the regression model includes the covariates of 731Table 3. 732733734===== PAGE 45 (score 11, numeric-paren 0, table-words 3, var-words 5) =====735736 737 738 739Covariate 740Dependent variable 741EST_VAL 742OMI_VAL 743RENT_VAL 744SUPP_VAL 745Sign (+/-) 746Significance 747(5%-10%-NO) Sign (+/-) 748Significance 749(5%-10%-NO) Sign (+/-) 750Significance 751(5%-10%-NO) Sign (+/-) 752Significance 753(5%-10%-NO) 754AREA 755- 7565% 757- 75810% 759- 7605% 761+ 762NO 763Q_POS 764+ 7655% 766+ 7675% 768+ 7695% 770- 771NO 772Q_TYP 773+ 7745% 775+ 776NO 777+ 778NO 779+ 780NO 781DISCOAST 782- 7835% 784- 7855% 786- 7875% 788- 7895% 790DENSITY 791- 7925% 793- 794NO 795- 796NO 797- 7985% 799FOR_2012 800+ 8015% 802+ 8035% 804+ 8055% 806+ 8075% 808RES_2012 809- 81010% 811- 8125% 813- 8145% 815- 8165% 817PL_ZONE 818- 81910% 820- 8215% 822- 8235% 824- 825NO 826A_ZONE 827- 828NO 829- 83010% 831- 832NO 833- 834NO 835B_ZONE 836- 8375% 838- 83910% 840- 8415% 842- 8435% 844C_ZONE 845- 8465% 847- 84810% 849- 8505% 851- 85210% 853EZ_ZONE 854- 855NO 856- 8575% 858- 8595% 860- 8615% 862MIXUSE 863- 8645% 865- 8665% 867- 8685% 869- 8705% 871PARKS 872+ 873NO 874+ 8755% 876+ 8775% 878+ 8795% 880LC_URB 881- 882NO 883- 884NO 885- 886NO 887- 888NO 889EST_LAG 890+ 8915% 892 893 894 895 896 897 898OMI_LAG 899 900 901+ 9025% 903 904 905 906 907RENT_LAG 908 909 910 911 912+ 9135% 914 915 916SUPP_LAG 917 918 919 920 921 922 923+ 9245% 925 926Table 9. Synthesis of regression models’ estimates: sign and significance. If a coefficient’s estimate is 927not significant either at 5% or at 10%, then we put a “NO” in the significance column. 928