1# RECORD 2bbdabdc28e5b845377e3ce418d4b3325d2d76ec2# TITLE: Valuing Historical and Open Space Amenities with Hedonic Property Valuation Models3# YEAR: 2016.0 VENUE: Agricultural and Resource Economics Review DOI: 10.1017/age.2016.144# AUTHORS: R. Hicks; Bonnie M. Queen5# PAGES: 24 CANDIDATE TABLE PAGES (1-based): [13, 14, 15, 18, 20, 21]6# ABSTRACT: Impacts of historic and cultural amenities on property values and the economy have not been widely studied in part because of problems isolating statistical effects using nonmarket valuation and lack of study areas. Three jurisdictions in Virginia containing major historic sites provide a unique setting in which to isolate the effects of historical amenities on residential property values using revealed preferences and quantify their economic benefits. We find that historic areas provide both open space and historic amenities. Furthermore, being adjacent to a historical area is not a positive benefit on average, perhaps because of activity and congestion associated with tourism. Residing close to such areas is valuable to buyers.789===== PAGE 1 (score 8, numeric-paren 0, table-words 0, var-words 8) =====1011Valuing Historical and Open Space12Amenities with Hedonic Property13Valuation Models14Robert L. Hicks and Bonnie M. Queen15Impacts of historic and cultural amenities on property values and the economy16have not been widely studied in part because of problems isolating statistical17effects using nonmarket valuation and lack of study areas. Three jurisdictions in18Virginia containing major historic sites provide a unique setting in which to19isolate the effects of historical amenities on residential property values using20revealed preferences and quantify their economic benefits. We find that historic21areas provide both open space and historic amenities. Furthermore, being22adjacent to a historical area is not a positive benefit on average, perhaps because23of activity and congestion associated with tourism. Residing close to such areas24is valuable to buyers.25Key Words: hedonic property models, open space, historic amenities26Historic and cultural sites, like environmental resources, often provide benefits27that are nonexcludable and nonrival to varying degrees and therefore are likely28to be undervalued by traditional markets (Navrud and Ready 2002). The failure29of markets to appropriately value the services flowing from historic amenities30leads to a less-than-efficient amount of historic preservation since the cost of31preservation often falls to private property owners who thus incur private32costs when preserving amenities that provide public benefits. Even when33historical properties are publicly owned, there is potential pressure to use34the areas for additional purposes unrelated to a site’s historic importance. If35those multiple uses impair the flow of historical services, then even publicly36held resources may not be efficiently managed in terms of the economic37benefits they provide. A growing body of literature has demonstrated that38economic value arises from preservation of cultural heritage sites using39environmental valuation techniques (e.g., Garrod and Willis 2002, Riganti and40Willis 2002, Hansen 1997, Bille 2002, Chambers, Chambers, and Whitehead411998, Morey et al. 2002, Bravi, Scarpa, and Sirchia 2002, Carson, Mitchell,42Robert L. Hicks is a professor of economics and marine science at the College of William and43Mary. Bonnie M. Queen is an economist for the Office of State Budget and Management for the44State of North Carolina. Senior authorship is not assigned. Correspondence: Robert L. Hicks ▪45Department of Economics ▪College of William and Mary ▪129 Morton Hall ▪Williamsburg, VA4623187 ▪Phone 757.221.3707 ▪Email rob.hicks@wm.edu.47The views expressed are the authors’ and do not necessarily represent the policies or views of48any sponsoring agencies.49Agricultural and Resource Economics Review 45/1 (April 2016) 44–6750© The Author(s) 2016. This is an Open Access article, distributed under the terms of the Creative51Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits52unrestricted re-use, distribution, and reproduction in any medium, provided the original work is53properly cited.54https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press555657===== PAGE 13 (score 39, numeric-paren 0, table-words 6, var-words 12) =====5859Table 1. Log Linear Models with Contiguity-based Spatial Weight Matrices60Strict Contiguity61200-meter Contiguity62400-meter Contiguity63600-meter Contiguity64Variable65Coefficient66t-Stat67Coefficient68t-Stat69Coefficient70t-Stat71Coefficient72t-Stat73Constant745.84237544.9440766.28357761.4222786.10867952.0860805.75428143.559982Age830.06168415.2607850.06578616.5206870.05308813.5754890.04789012.033191Bathrooms920.0286931.9343940.0169951.1437960.0101970.6857980.0134990.9073100Bedrooms1010.08601025.17461030.10491045.45931050.12001066.31631070.13051087.4568109Dock1100.21541115.59031120.18141134.86531140.22311155.90271160.21981175.6961118Square feet1190.746212041.78341210.681012239.37761230.705312438.75941250.754612642.7783127Central air1280.10351296.46101300.11711317.13241320.09191335.60531340.09261355.6566136Lot size1370.00461381.58061390.00601401.78321410.01201423.43451430.01211443.6175145Adjacent golf1460.01631470.63361480.07031492.42661500.03951511.31481520.00611530.2161154Distance fixed1550.031615616.79661570.028315815.16931590.028916016.06111610.029116216.4908163Adjacent fixed1640.13791652.00831660.09951671.39581680.14981692.34571700.17271712.6857172Distance historic1730.04891746.44151750.04441765.17271770.02651782.57451790.00951800.9130181Adjacent historic1820.51751835.32271840.49341854.84511860.29721872.63451880.13661891.1847190Adjacent adjusted1910.392919225.41331930.366419423.94561950.365719624.61691970.364919824.8259199Distance railroad2000.05682017.33702020.05892036.74632040.04832054.58092060.03942073.6151208Distance water2090.02402104.25662110.01992123.22902130.01852142.64802150.02742163.9995217Adjacent water2180.27402194.51282200.25642213.97742220.26502233.81402240.32462254.7136226λ2270.4550228427.10312290.5510230262.86492310.6970232138.32612330.7439234108.4002235σ22360.122370.122380.122390.13240R22410.562420.572430.572440.55245N24612,33724712,33724812,33724912,337250Log likelihood251603.08252391.58253335.87254523.48255Agricultural and Resource Economics Review25656 April 2016257https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press258259260===== PAGE 14 (score 39, numeric-paren 0, table-words 6, var-words 12) =====261262Table 2. Semi-log Models with Contiguity-based Spatial Weight Matrices263Strict Contiguity264200-meter Contiguity265400-meter Contiguity266600-meter Contiguity267Variable268Coefficient269t-Stat270Coefficient271t-Stat272Coefficient273t-Stat274Coefficient275t-Stat276Constant27711.1270278379.604627911.1744280364.990328111.1345282338.890428311.1345284338.8904285Age2860.00172874.56622880.00152893.78262900.00052911.40552920.00052931.4055294Bathrooms2950.00522960.72222970.00482980.65732990.00343000.46313010.00343020.4631303Bedrooms3040.033630513.06553060.029630711.44723080.035430913.02453100.035431113.0245312Dock3130.27003146.78073150.23263166.07023170.28013187.16153190.28013207.1615321Square feet3220.000232335.84113240.000232529.68743260.000232729.80743280.000232929.8074330Central air3310.14093327.90523330.14123348.07953350.10973366.16353370.10973386.1635339Lot size3400.01643411.47673420.02473432.23783440.01643451.43183460.01643471.4318348Adjacent golf3490.16283506.14773510.20053526.51993530.15733545.02333550.15733565.0233357Distance fixed3581.368235911.73573601.06163619.15113621.05593639.83843641.05593659.8384366Adjacent fixed3670.03743680.52513690.00283700.03813710.04273720.64963730.04273740.6496375Distance historic3760.03643775.89553780.03903795.37523800.03203813.23723820.03203833.2372384Adjacent historic3850.01703860.23893870.02023880.29983890.03743900.57403910.03743920.5740393Adjacent adjusted3940.239939525.41393960.226639724.58713980.221739924.65764000.221740124.6576402Distance railroad4030.04794047.56024050.05204067.07824070.04864084.82124090.04864104.8212411Distance water4120.00054130.03554140.00194150.11944160.00304170.13734180.00304190.1373420Adjacent water4210.15574224.67424230.16704245.12774250.19304265.96764270.19304285.9676429λ4300.4910431137.36394320.5850433199.87234340.72504351813.46474360.72504371813.4647438σ24390.13274400.12764410.12894420.1352443R24440.52364450.54184460.53724470.5145448N44912,33745012,33745112,33745212,337453Log likelihood4541073.6017455818.2522456785.18494571016.8986458Hicks and Queen459Valuing Historical and Open Space Amenities 57460https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press461462463===== PAGE 15 (score 39, numeric-paren 0, table-words 6, var-words 12) =====464465Table 3. Models with Distance-based Spatial Weight Matrices466Log Linear Models467Semi-log Models468600 Meter (1/distance)469600 Meter (1/distance2)470600 Meter (1/distance)471600 Meter (1/distance2)472Variable473Coefficient474t-Stat475Coefficient476t-Stat477Coefficient478t-Stat479Coefficient480t-Stat481Constant4826.345748370.82804846.275648558.374448611.1617487327.043148811.2079489361.9085490Age4910.060349214.94884930.067949416.69134950.00084961.99524970.00154983.7181499Bathrooms5000.01425010.96945020.02135031.44795040.00025050.02885060.00475070.6598508Bedrooms5090.10595105.39715110.08835124.61905130.029951410.69705150.026251610.1092517Dock5180.20085195.34185200.19335215.10925220.25975236.68025240.24945256.3897526Square feet5270.671352838.65855290.684953039.19685310.000253226.42675330.000253430.1076535Central air5360.10665376.42155380.11415396.96475400.11965416.71555420.13405437.7014544Lot size5450.01605463.84395470.00825482.28015490.01865501.57005510.01575521.3638553Adjacent golf5540.03305551.00855560.02785570.95565580.14435594.25115600.16435615.3385562Distance fixed5630.029456415.93055650.031256616.26185671.09725689.56465691.18325709.7271571Adjacent fixed5720.18005732.76165740.16505752.42595760.08835771.31555780.07255791.0310580Distance historic5810.00765820.63015830.04265844.76085850.02605862.13355870.03575884.6262589Adjacent historic5900.10415910.83005920.44105934.17095940.06425950.92765960.05065970.7207598Adjacent adjusted5990.373960024.89956010.390060225.16506030.230460425.07256050.236560625.0276607Distance railroad6080.05246094.04306100.06416116.91136120.05436134.26436140.05166156.6416616Distance water6170.02856183.62116190.02916204.47916210.01856220.68116230.00266240.1546625Adjacent water6260.35986274.71856280.34196295.06456300.19636315.88336320.18106335.3169634λ6350.7880636124.76446370.5670638246.58286390.8070640366.74096410.6020642230.5507643σ26440.11536450.11596460.12346470.1236648R26490.56826500.58406510.55716520.5563653N65412,33765512,33765612,33765712,337658Log Likelihood659123.7629660285.1293661562.5197662734.8791663Agricultural and Resource Economics Review66458 April 2016665https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press666667668===== PAGE 16 (score 23, numeric-paren 0, table-words 1, var-words 12) =====669670Table 4. Estimated Price Changes for Log Linear Models671Variable672Strict673Contiguity674600-meter675Contiguity676400-meter677Contiguity678200-meter679Contiguity680(1/d)681Distance682(1/d2)683Distance684Age685$762.71686$611.43687$647.59688$792.53689$732.31690$830.65691Bathrooms692$1,842.84693$887.58694$641.11695$1,058.20696$897.41697$1,352.58698Bedrooms699$1,835.69700$2,885.71701$2,532.02702$2,184.94703$2,218.88704$1,861.18705Dock706$40,789.34707$43,137.81708$41,852.55709$32,896.39710$37,020.48711$35,729.86712Square feet713$11,393.97714$11,918.29715$10,609.24716$10,109.61717$10,021.70718$10,301.99719Central air720$18,511.52721$17,030.37722$16,112.46723$20,545.29724$18,720.61725$20,262.57726Lot size727$169.92728$467.61729$440.99730$219.97731$585.58732$302.44733Adjacent golf734$2,783.67735$1,061.56736$6,740.19737$12,050.92738$5,590.50739$4,724.02740Distance fixed741$1,442.81742$1,374.04743$1,299.78744$1,257.91745$1,316.29746$1,407.42747Adjacent fixed748$21,854.51749$27,829.88750$23,301.11751$15,660.52752$27,423.09753$25,495.31754Distance755historic756$90.26757$18.13758$48.26759$79.94760$13.74761$77.66762Adjacent763historic764$68,554.09765$22,401.13766$43,054.24767$64,429.91768$16,453.10769$59,765.17770Adjacent771adjusted772$55,132.55773$53,640.10774$51,284.06775$50,743.48776$51,922.04777$54,123.36778Distance779railroad780$127.08781$91.15782$106.71783$128.47784$114.91785$141.64786Distance water787$167.27788$197.05789$127.38790$134.91791$194.52792$200.00793Adjacent water794$53,484.44795$67,283.97796$50,801.19797$48,338.85798$72,084.26799$68,307.48800Hicks and Queen801Valuing Historical and Open Space Amenities 59802https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press803804805===== PAGE 18 (score 31, numeric-paren 0, table-words 6, var-words 3) =====806807Table 6. Companion for Table 1808Strict Contiguity809200-meter Contiguity810400-meter Contiguity811600-meter Contiguity812Variable813Coefficient814t-Stat815Coefficient816t-Stat817Coefficient818t-Stat819Coefficient820t-Stat821whal8220.1384538235.0452528240.1729358255.3120358260.2071238275.1440538280.1607488294.272369830york8310.1259288323.4284678330.0901878342.1127688350.020948360.3842688370.0064738380.110933839wall8400.0098118410.2780738420.0563848431.3974848440.0572218451.0681638460.0087178470.167595848vern8490.0031198500.0976798510.0100658520.269178530.001738540.0360398550.0526668561.100463857cove8580.1091638593.6803488600.1261078613.6040778620.1630078633.4309278640.1539068653.041422866magr8670.0563028681.7353178690.0292368700.7796898710.0240528720.4830018730.069938741.266021875tabb8760.0459788771.3095558780.0708598791.7229738800.0740058811.3924668820.0451858830.822293884ston8850.0231618860.6591848870.036218880.9713158890.0570418901.0977628910.075978921.292011893norg8940.2029058957.247488960.2271458976.9195478980.2050978994.8396229000.142199013.456896902djmo9030.0381749041.469529050.021469060.706739070.0054369080.1436729090.0696269101.960713911rawl9120.086519132.8687749140.0921639152.5710419160.2142729174.6358219180.2382649195.159639920jamr9210.0871969222.6343099230.1365579243.415139250.2154549263.8418789270.1814229282.852349929graf9300.0384759311.4896019320.015639330.5024869340.0020129350.047469360.0582169371.369806938clar9390.0442349401.5996089410.0727459422.2640979430.0879999442.1636779450.0873249462.165224947y19999480.0279419492.4599779500.0277159512.481729520.0268569532.3978519540.026159552.284535956y20009570.059169585.1563329590.0660099605.8562279610.0708059626.2759599630.073679646.401172965y20019660.0868599677.8147719680.0865449697.9066799700.090369718.2595849720.092169738.256438974y20029750.14884697613.7353559770.15610497814.57039790.15799298014.7340829810.15875198214.527972983y20039840.25173198519.4596019860.25218298719.7558629880.25711798920.1410349900.25748199119.790269992y20049930.65899499412.0508429950.64402399611.8838129970.65229999812.1186469990.597727100010.9298611001Hicks and Queen1002Valuing Historical and Open Space Amenities 611003https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press100410051006===== PAGE 19 (score 9, numeric-paren 0, table-words 0, var-words 9) =====10071008average house’s sale price ($1,400 to $2,000). Thus, being located near a fixed1009open space is considered a benefit. Being adjacent to a fixed open space (a golf1010course, resource protection area, or park) had a slight negative effect on home1011sale prices that was not significant. As expected, houses farther from railroads1012were associated with higher sale prices ($150 to $250). Being close to water1013was also a positive amenity even after controlling for parcels that were1014adjacent to water (which command tens of thousands of dollars more). The1015only adjacency measure that was significant in all of the models was1016adjustable open space. Parcels abutting an adjustable open space sold for an1017average of $30,000 to $50,000 less than similar nonadjacent parcels.1018Being located adjacent to a historic area had no significant effect on sale1019prices. As with adjacency to fixed open spaces, some buyers may consider a1020shared border with a historic area as a disamenity, perhaps because of heavy1021tourist traffic (from both pedestrians and cars). Decreasing distance from the1022average parcel to a historic area when controlling for fixed open-space1023amenities led to higher sale prices ($50 to $200). While the gains from1024service flows generated by all forms of fixed open space (including historical1025areas) are modest, these results show that proximity to historical and1026cultural amenities yields benefits unrelated to provision of open space.1027The models we estimate demonstrate the robustness of our core finding that1028historic areas provide economic benefits to nearby residents. In addition, when1029Figure 2. Parcels and Historical Areas1030Agricultural and Resource Economics Review103162 April 20161032https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press103310341035===== PAGE 20 (score 31, numeric-paren 0, table-words 6, var-words 3) =====10361037Table 7. Companion for Table 21038Strict Contiguity1039200-meter Contiguity1040400-meter Contiguity1041600-meter Contiguity1042Variable1043Coefficient1044t-Stat1045Coefficient1046t-Stat1047Coefficient1048t-Stat1049Coefficient1050t-Stat1051whal10520.101210533.152810540.138110553.675010560.160910573.242710580.160910593.24271060york10610.085910622.154610630.066910641.447510650.028210660.463010670.028210680.46301069wall10700.031510710.806710720.010910730.239610740.005810750.092110760.005810770.09211078vern10790.013010800.289010810.032010820.594310830.000510840.006810850.000510860.00681087cove10880.082910891.790110900.104610911.875210920.133710931.679910940.133710951.67991096magr10970.070910981.886810990.049911001.145311010.005411020.089311030.005411040.08931105tabb11060.078411071.468011080.106611091.669111100.081711110.934411120.081711130.93441114ston11150.116211162.131611170.119611181.893311190.077711200.848511210.077711220.84851123norg11240.202111255.840311260.232911275.631611280.202511293.503911300.202511313.50391132djmo11330.090811342.560111350.086811362.084611370.094011381.639811390.094011401.63981141rawl11420.003311430.094311440.006911450.163711460.107811471.920011480.107811491.92001150jamr11510.053411521.463111530.110211542.499611550.188011562.950211570.188011582.95021159graf11600.028111610.880911620.002611630.066111640.002011650.034911660.002011670.03491168clar11690.056511701.564011710.037711720.895011730.048511740.871011750.048511760.87101177y199911780.027711792.334111800.027611812.382211820.025511832.183011840.025511852.18301186y200011870.055811884.652711890.062811905.344611910.067311925.721411930.067311945.72141195y200111960.087911977.550411980.086811997.593212000.088712017.758412020.088712037.75841204y200212050.1510120613.218312070.1549120813.765412090.1560121013.872612110.1560121213.87261213y200312140.2498121518.353412160.2474121718.447312180.2511121918.750912200.2511122118.75091222y200412230.431212247.969012250.406512267.558812270.447812288.427112290.447812308.42711231Hicks and Queen1232Valuing Historical and Open Space Amenities 631233https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press123412351236===== PAGE 21 (score 31, numeric-paren 0, table-words 6, var-words 3) =====12371238Table 8. Companion for Table 31239Log Linear Models1240Semi-log Models1241600 meter (1/distance)1242600 Meter (1/distance2)1243600 meter (1/distance)1244600 Meter (1/distance2)1245Variable1246Coefficient1247t-Stat1248Coefficient1249t-Stat1250Coefficient1251t-Stat1252Coefficient1253t-Stat1254whal12550.207512564.577712570.167512584.999512590.162212602.721312610.136112623.52511263york12640.040412650.595512660.099412672.227012680.014812690.199212700.063812711.31971272wall12730.084112741.346012750.056912761.299612770.012512780.166012790.012412800.25311281vern12820.012212830.212912840.004112850.105512860.028512870.292512880.032212890.56751290cove12910.174212922.920112930.131112943.603712950.109912961.092412970.093812981.60931299magr13000.070013011.102413020.048213031.230813040.022913050.298613060.064613071.41971308tabb13090.071413101.100613110.041313120.976613130.053413140.494913150.077513161.16741317ston13180.084013191.292013200.048313211.162013220.024313230.208813240.103013251.48741326norg13270.195613283.882913290.211613306.169213310.170213322.343613330.216013344.97601335djmo13360.068713371.632513380.054113391.709113400.192213412.726013420.106613432.43511344rawl13450.216913463.912113470.082813482.218413490.102013501.489613510.002513520.05641353jamr13540.227013553.031413560.152413573.628813580.182113592.134813600.128813612.79231362graf13630.014213640.276913650.017413660.536713670.016713680.236913690.002313700.05741371clar13720.076613731.637513740.048313751.445913760.067013771.001513780.052413791.18671380y199913810.029113822.624813830.028313842.551513850.028313862.458213870.030913882.69331389y200013900.072213916.453413920.065813935.908413940.067813955.824613960.063413975.47401398y200113990.088914008.179214010.081514027.527514030.087214047.695814050.083014067.35411407y200214080.1585140914.853414100.1494141114.076514120.1560141313.975214140.1504141513.52011416y200314170.2542141820.108914190.2443142019.405914210.2492142218.808514230.2426142418.37821425y200414260.6090142711.512714280.6218142911.838814300.387314317.407114320.368314337.11101434Agricultural and Resource Economics Review143564 April 20161436https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press143714381439===== PAGE 22 (score 7, numeric-paren 0, table-words 0, var-words 7) =====14401441we consider the results for all other parameters (excluding historical and open1442space amenities), we find a remarkable degree of consistency across models.101443The differences are in the magnitudes of the coefficients, the signs, and the1444significance levels. When we focus on the set of models that are most1445consistent with prior studies (strict contiguity, 200-meter contiguity, and 1/1446d2 weight matrices), the results are even more robust in terms of estimating1447the value of historical and other spatial amenities.1448Conclusion1449This study is the first to demonstrate economic benefits from local historical1450and cultural resources beyond drawing visitors to historic sites, and the1451results confirm that owners of nearby residential properties also benefit from1452historic amenities. Quantification of these benefits using revealed-preference1453nonmarket valuation techniques is an important step in addressing the1454public-policy problem of prioritizing and choosing appropriate levels of1455historic preservation. Our results show that, for historic areas such as1456Williamsburg, Virginia, policies should consider the benefits provided by both1457open space and historical resources to account fully for the flow of services.1458We find significant spatial dependence in the error structure in our model, a1459problem that is common when analyzing spatial amenities. The ordinary least1460squares model was rejected in all of the specifications considered. By using1461several types of spatial weighting matrices, we determine that historic1462amenities are valuable resources for homebuyers and that the amenity value1463is not particularly sensitive to specification of the functional form or the1464error structure. Our results also confirm the presence of spatial heterogeneity1465in1466estimating1467the1468value1469of1470historic1471areas.1472In1473particular,1474the1475average1476homeowner does not consider sharing a border with a historic area as1477beneficial but does value living near one. This result is consistent with the1478large volume of visitors and traffic associated with historic sites in the1479Williamsburg area at certain times of year.1480By carefully considering the services offered by historic areas, we isolate the1481marginal value of the flow of services solely from historical amenities from1482other types of amenities such historic areas may also provide, such as open1483space. We find weak evidence that properties adjacent to a historic area are1484valued less by buyers, indicating that living in a tourism district is viewed as1485a disamenity. We find strong evidence that buyers value living near a1486historical area rather than directly next to one.148710 Bell and Bockstael (2000) reported that such results are sensitive to differences in1488assumptions regarding spatial weight matrices.1489Hicks and Queen1490Valuing Historical and Open Space Amenities 651491https://doi.org/10.1017/age.2016.14 Published online by Cambridge University Press1492