1# RECORD 4ecf623f40ce01fde8d4ac0ee88291986f7a72fa2# TITLE: Economic Assessment of South African Urban Green Spaces Using the Proximity Principle: Municipal Valuation vs. Market Value3# YEAR: 2021.0 VENUE: Urban Planning DOI: 10.17645/up.v6i4.44074# AUTHORS: L. Lategan; J. Cilliers; Zinea Huston; N. Blaauw; S. Cilliers5# PAGES: 13 CANDIDATE TABLE PAGES (1-based): [6, 8]6# ABSTRACT: Urban green spaces (UGSs) deliver ecosystem services and potential economic benefits like increases in proximate residential property prices. The proximity principle (PP) premises that property prices increase as distance to UGS decreases. The PP has generally been confirmed by studies using municipal valuations and market values internationally. Conversely, South African studies have mostly employed municipal valuations and results have rejected the PP. There is an accepted interrelationship, but also often discrepancies, between municipal valuations and market values, presenting scope for this article to explore whether negative results are confirmed when market values replace municipal valuations in PP studies in the South African context. Accordingly, a statistical analysis of market values is completed in the Potchefstroom case study, where five test sites are replicated from studies that employed municipal valuations for longitudinal comparison. Results verify generally higher market values than municipal valuations and confirm the PP in two, but reject the PP in three, of five test sites. Previous studies employing municipal valuations in the case study confirmed the PP in one instance, thus presenting certain, but limited, inconsistencies between findings based on municipal valuation vs. market value. Results suggest that the market’s willingness to pay for UGS proximity is sensitive to the ecosystem services and disservices rendered by specific UGS, but not significantly more than reflected in municipal valuations. Overall, findings underscore the need to protect and curate features that encourage willingness to pay for UGS proximity to increase municipal valuations and property taxes to help finance urban greening.789===== PAGE 1 (score 17, numeric-paren 0, table-words 0, var-words 17) =====1011Urban Planning (ISSN: 2183–7635)122021, Volume 6, Issue 4, Pages 54–6613https://doi.org/10.17645/up.v6i4.440714Article15Economic Assessment of South African Urban Green Spaces Using the16Proximity Principle: Municipal Valuation vs. Market Value17Louis Lategan 1,*, Juaneé Cilliers 2, Zinea Huston 1, Nadia Blaauw 1 and Sarel Cilliers 1181 Unit for Environmental Sciences and Management, North‐West University, South Africa;19E‐Mails: latlou.info@gmail.com (L.L.), zineahuston@gmail.com (Z.H.), blaauw.nadia@yahoo.com (N.B.),20sarel.cilliers@nwu.ac.za (S.C.)212 School of Built Environment, University of Technology Sydney, Australia; E‐Mail: juanee.cilliers@uts.edu.au22* Corresponding author23Submitted: 27 April 2021 | Accepted: 27 July 2021 | Published: 14 October 202124Abstract25Urban green spaces (UGSs) deliver ecosystem services and potential economic benefits like increases in proximate resi‐26dential property prices. The proximity principle (PP) premises that property prices increase as distance to UGS decreases.27The PP has generally been confirmed by studies using municipal valuations and market values internationally. Conversely,28South African studies have mostly employed municipal valuations and results have rejected the PP. There is an accepted29interrelationship, but also often discrepancies, between municipal valuations and market values, presenting scope for this30article to explore whether negative results are confirmed when market values replace municipal valuations in PP studies in31the South African context. Accordingly, a statistical analysis of market values is completed in the Potchefstroom case study,32where five test sites are replicated from studies that employed municipal valuations for longitudinal comparison. Results33verify generally higher market values than municipal valuations and confirm the PP in two, but reject the PP in three, of34five test sites. Previous studies employing municipal valuations in the case study confirmed the PP in one instance, thus35presenting certain, but limited, inconsistencies between findings based on municipal valuation vs. market value. Results36suggest that the market’s willingness to pay for UGS proximity is sensitive to the ecosystem services and disservices ren‐37dered by specific UGS, but not significantly more than reflected in municipal valuations. Overall, findings underscore the38need to protect and curate features that encourage willingness to pay for UGS proximity to increase municipal valuations39and property taxes to help finance urban greening.40Keywords41green infrastructure; market value; municipal valuation; proximity principle; South Africa; urban green space42Issue43This article is part of the issue “Towards Green(er) Cities: Contextualizing Green Benefits for Urban Spaces and44Contemporary Societies” edited by Juaneé Cilliers (University of Technology Sydney, Australia).45© 2021 by the authors; licensee Cogitatio (Lisbon, Portugal). This article is licensed under a Creative Commons Attribu‐46tion 4.0 International License (CC BY).471. Introduction48Urban green spaces (UGSs) include land parcels of var‐49ious types located within the urban boundary, cov‐50ered by permeable surfaces, soil, or flora (Girma et al.,512019, p. 138). Zoning classifications include residen‐52tial, recreational, commercial, or agricultural categories53to accommodate land uses like communal parks, play‐54grounds, sport facilities, greenways, green walls and55roofs, urban forests, private gardens, wetlands and ripar‐56ian areas, and street‐side vegetation. UGSs may also57encompass informal, residual, or unattended parcels,58including derelict properties, vacant lots, and spaces59along transportation corridors (J. Cilliers, 2013, p. 100;60Girma et al., 2019, p. 138). Scholarly interest in UGSs61has peaked in recent years, recognising their potential62contributions to urban quality of life and service deliv‐63ery as components of green infrastructure (du Toit et al.,64Urban Planning, 2021, Volume 6, Issue 4, Pages 54–666554666768===== PAGE 6 (score 18, numeric-paren 0, table-words 4, var-words 5) =====6970Table 3. Dependent t‐test results.71Area72Zone73N74(188)75Municipal76Valuation77in South78African79Rand/m280Market81Value82in South83African84Rand/m285Municipal86Standard87Deviation88Market89Standard90Deviation91Effect Size92T‐test93a ≈0,2 small94b ≈0,5 medium95c ≈0,8 large96Statistically97significant98difference99between100municipal and101market (p < 0,05)102Grimbeek Park1031104141051,260.71061,252.91107237.61108375.851090,02a1100,9411112112141131,611.671141,584.32115295.96116421.641170,06b1180,6681193120131211,699.251221,493.18123269.72124208.741250,76c1260,019127van der Hoff1281129151301,290.591311,683.48132341.15133753.191340,52b1350,016136Park1372138151391,472.431401,579.05141237.86142224.651430,45b1440,1431453146131471,624.31481,902.34149279150339.581510,82c1520153Heilige Akker1541155101561,751.961572,299.21158353.01159631.251600,87c1610,0121622163121641,904.151652,692.38166280.09167858.191680,92c1690,0051703171141721,850.281731,930.69174757.54175356.161760,19a1770,603178Oewersig1791180141811,668.441822,355.76183338.6184642.541851,07c18601872188141891,852.151902,480.35191360.64192876.911930,72c1940,0311953196131971,549.21982,037.73199415.18200255.852011,52c2020203Potchefstroom204120592061,116.442072,139.69208336.362091,213.692100,84c2110,019212Dam213221492151,303.452162,223.11217421.46218408.472192,25c2200,001221322292231,448.642242,308.59225421.612261,009.92270,85c2280229significantly higher than municipal valuations in four of230five test sites, with the exception of Grimbeek Park.231Figure 1 illustrates the differences captured in Table 3232regarding fluctuations from Zone 1 to Zone 3 in each233test site.234In Grimbeek Park, results presented a general rejec‐235tion of the PP from Zone 1 to 3, but confirmed the prin‐236ciple between Zones 2 and 3 with regard to estimated237market values. Findings differed slightly in that munic‐238ipal valuations showed a consistent upward trajectory239to reject the PP from Zone 1 to 3. In van der Hoff Park,240the PP was confirmed between Zone 1 and Zone 2, but241rejected between Zones 1 and 3. Thus, differing slightly242from municipal valuation findings that showed a con‐243sistent upward trajectory, but confirming findings on a244rejection of the PP in general terms. In Heilige Akker,245the PP was rejected between Zone 1 and Zone 2, but246confirmed for Zone 1 to Zone 3. Findings concurred247with data from municipal valuations showing a peak248in Zone 2, but departed where the PP was rejected.249For Oewersig, data rejected the PP between Zone 1250and Zone 2, but confirmed the principle for Zone 1 to251Zone 3. Results were mirrored in municipal valuations.252For Potchefstroom Dam, Zone 3 presented a higher mar‐253ket value estimate than Zone 2 and Zone 1, resulting in254a rejection of the PP. This trend echoed findings derived255from municipal valuations.256Statistical substantiation to the findings above were257provided via ANOVA and Kruskal‐Wallis testing using2582020 market value estimates. For ANOVA an effect size259of ≈0.2 indicates a small, no practically significant differ‐260ence; an effect size of ≈0.5 indicates a medium, practi‐261cally visible difference; and an effect size of ≈0.8 indi‐262cates a large, practically significant difference. For the263Kruskal‐Wallis test, an effect size of ≈0.1 indicates a264small or no practically significant difference; an effect265size of ≈0.3 indicates a medium or practically visible266difference; and an effect size of ≈0.5 indicates a large267or practically significant difference. Results are captured268in Table 4.269The results from the Kruskal‐Wallis test were pre‐270ferred when the outcomes of statistical tests differed.271This is also reflected in Table 5 that summarises com‐272plete results in conjunction with Combrinck et al.’s (2020)273main findings.2747. Conclusions275Municipal valuations were considerably lower than esti‐276mated market values in almost all test sites and a large277practically significant difference could be established;278in general, by a significant 28%, which is well above279accepted standards of deviation. Grimbeek Park pre‐280sented an interesting case, as the only example in which281municipal valuations exceeded estimated market values.282It falls beyond the scope of this article to investigate283the reasons behind this and opportunities for further284research are thus presented. As a point of departure for285future investigations, it is interesting to note that in a286review of the five test sites included in this research,287Urban Planning, 2021, Volume 6, Issue 4, Pages 54–6628859289290291===== PAGE 7 (score 6, numeric-paren 0, table-words 1, var-words 4) =====29229330002942500295R/m229620002971500298Zone 1299Zone 23001472,43301Zones302Van der Hoff Park303Zone 3304100030550030603071579,053081902,343091624,3310Market311Municipal312B3131290,593141683,4831530003162500317R/m231820003191500320Zone 1321Zone 23221584,32323Zones324Grimbeek Park325Zone 3326100032750032803291611,673301699,253311493,18332Market333Municipal334A3351252,913361260,733730003382500339R/m234020003411500342Zone 13431668,443442355,76345Zone 2346Zones347Oewersig348Zone 3349100035050035103522480,353532037,733541549,2355Market356Municipal357D3581852,1535930003602500361R/m236220003631500364Zone 13652299,21366Zone 2367Zones368Heilige Akker369Zone 3370100037150037203732692,383741930,693751850,28376Market377Municipal378C3791904,153801751,9638130003822500383R/m238420003851500386Zone 1387Zone 2388Zones389Potchefstroom Dam390Zone 339110003925003930394Market395Municipal396E3971116,443982139,693991303,454002223,114012308,594021448,64403Figure 1. Mean South African Rand/m2 municipal valuation and estimated market values for the Potchefstroom sample.404based on attributes related to UGSs and the environmen‐405tal, social, and economic benefits (as ecosystem services)406offered, Combrinck (2020) found that Grimbeek Park’s407UGS delivered the highest overall scores. As a supple‐408mentary consideration, the UGS in Grimbeek Park pre‐409sented the only example of a golf course. Several interna‐410tional studies have indicated that golf courses specifically411increase proximate property values at significant levels412(Crompton & Nicholls, 2020; Nicholls & Crompton, 2007;413Yates & Cowart, 2019).414Another interesting observation relates to the zone415in which values reached a peak in each test site. Using416municipal valuations, Combrinck et al. (2020) established417peaks in Zone 1 in no test sites; peaks in Zone 2 in two418test sites (Heilige Akker and Oewersig); and peaks in419Zone 3 in three test sites (Grimbeek Park, van der Hoff420Park, and Potchefstroom Dam). In contrast, estimated421market values delivered peaks in Zone 1 for no test sites422(yet, in van der Hoff Park Zone 1 presented a higher423estimate than Zone 2); peaks in Zone 2 for three test424sites (Grimbeek Park, Heilige Akker, and Oewersig); and425peaks in Zone 3 for two test sites (van der Hoff Park and426Potchefstroom Dam). Peaks were thus registered signifi‐427cantly differently using municipal valuation vs. estimated428market value.429The absence of peaks in Zone 1 in both data sets,430even where the PP was confirmed (Heilige Akker and431Oewersig) underscores the negative impacts of adja‐432cency to UGS in South Africa, ascribed to ecosystem433disservices such as crime, a lack of maintenance, and434other nuisance factors (see Davoren & Shackleton, 2021,435and Table 1). The presence of a higher market value436Urban Planning, 2021, Volume 6, Issue 4, Pages 54–6643760438439440===== PAGE 8 (score 16, numeric-paren 0, table-words 3, var-words 7) =====441442Table 4. ANOVA and Kruskal‐Wallis testing.443Area444Zone445N446(188)447Market448Value in449South450African451Rand/m2452Standard453Deviation454Effect Size455ANOVA456Kruskal‐457Wallis458ANOVA459Kruskal‐Wallis460Statistically461significant462difference463between464means465(p < 0,05)466Statistically467significant468difference469between470mean471ranks472(p < 0,05)473a ≈0,2 small474a ≈0,1 small475b ≈0,5 medium476b ≈0,3 medium477c ≈0,8 large478c ≈0,5 large4791 with…4802 with…4811 with…4822 with…483Grimbeek Park4841485144861,252.91487375.854882489144901,584.32491421.644920.79c4930,373b4940,0474950,0574963497134981,493.18499208.745000.64b5010.22a5020,411b5030,028a504van der Hoff505Park5061507155081,683.48509753.195102511155121,579.05513224.655140,14a5150,140a5160,2375170,0225183519135201,902.34521339.585220,29a5230,95c5240,440c5250,457c526Heilige Akker5271528105292,299.21530631.255312532125332,692.38534858.195350,46b5360,197a5370,0175380,0115393540145411,930.69542356.165430,58b5440,89c5450,287b5460,615c547Oewersig5481549145502,355.76551642.545522553145542,480.35555876.915560,14a5570,052a5580,2085590,355603561135622,037.73563255.855640,49b5650,50b5660,224a5670,252b568Potchefstroom569Dam570157195722,139.695731,213.69574257595762,223.11577408.475780,07a5790,468c5800,935810,203582358395842,308.595851,009.95860,14a5870,08a5880,177a5890,135a590estimate in Zone 1 than Zone 2 in van der Hoff Park591and more peaks in Zone 2 than Zone 3, when contem‐592plating estimated market value vs. municipal valuation,593indicate that whilst immediate adjacency is not always594valued, some proximity to UGSs may be appreciated to595capitalise on ecosystem services (see Escobedo, 2021,596p. 227, and Table 1) and reduce the potential impacts of597ecosystem disservices, despite the presence of domes‐598tic UGSs. This may also relate to the impacts of visual599access to public greenery that present pleasant vistas or600offer amenities (Panduro & Veie, 2013, p. 126; Sharmin,6012020). Although the aim of this study was not to deter‐602mine to what extent the market’s willingness to pay is603sensitive to the ecosystem services and ecosystem dis‐604services produced by specific UGSs, the importance of605acknowledging these aspects is emphasised in the litera‐606ture (Davoren & Shackleton, 2021).607The results in Figure 1, together with the average608medium practically significant differences established609from zone to zone, confirmed the PP in two test sites610using estimated market values compared to one when611employing municipal valuations. These are not over‐612whelming contrasts, but preliminary findings indicate613that the relationship between UGS proximity and willing‐614ness to pay for proximity may be less clear‐cut and lin‐615ear in South Africa than previously reported based on616municipal valuations (Cilliers & Cilliers, 2015; Combrinck617et al., 2020). Results still contrast with international618norms on the general confirmation of the PP using esti‐619mated market values as variables. These preliminary find‐620ings suggest that the influence of the variable employed621(municipal valuation vs. market value) can thus poten‐622tially be disregarded as an explanation for exceptions623identified in previous South African‐based research on624the PP (Table 2).625Although efforts to quantify the value of UGSs have626increased, more research is needed in the Global South627to provide case studies to guide context‐based planning628(S. S. Cilliers et al., 2021) and clarify the relationship629between UGS proximity and willingness to pay. Future630studies may compare municipal valuations and market631value estimates on a larger scale in various sites and632may consider the physical attributes and specific ecosys‐633tem services and ecosystem disservices rendered by indi‐634vidual UGSs through more qualitative approaches to635address certain limitations of this research. The complex‐636ity of developing integrated urban planning and man‐637agement systems focusing on ecosystem services and638Urban Planning, 2021, Volume 6, Issue 4, Pages 54–6663961640641642===== PAGE 9 (score 5, numeric-paren 0, table-words 1, var-words 3) =====643644Table 5. Comparative summary of results.645Municipal Valuation (2019)646Estimated Market Value (2020)647Test Site648Estimated649market650value651higher652than653municipal654valuation655Zone 1656vs.657Zone 2658Zone 2659vs.660Zone 3661Zone 1662vs.663Zone 3664PP from665zone to666zone667General668effect669size (non‐670parametric671test)672Verdict PP673based on674municipal675valuation676Zone 1677vs.678Zone 2679Zone 2680vs.681Zone 3682Zone 1683vs.684Zone 3685PP from686zone to687zone688General689effect690size (non‐691parametric692test)693Verdict PP694(estimated695market696value)697Grimbeek698Park699No700Lower701Lower702Lower703(Zone 3704peak)705Rejected706(Zone 1 to 3)707Large708Rejected709Lower710Higher711(Zone 2712peak)713Lower714Confirmed715(Zone 2 to 3)716Rejected717(Zone 1 to 3)718Medium719Rejected720van der Hoff721Park722Yes723Lower724Lower725Lower726(Zone 3727peak)728Rejected729(Zone 1 to 3)730Medium731Rejected732Higher733Lower734Lower735(Zone 3736peak)737Confirmed738(Zone 1 to 2)739Rejected740(Zone 1 to 3)741Medium742Rejected743Heilige Akker744Yes745Lower746Higher747(Zone 2748peak)749Lower750Rejected751(Zone 1 to 3)752Small753Rejected754Lower755Higher756(Zone 2757peak)758Higher759Rejected760(Zone 1 to 2)761Confirmed762(Zone 1 to 3)763Medium764Confirmed765Oewersig766Yes767Lower768Higher769(Zone 2770peak)771Higher772Confirmed773(Zone 1 to 3)774Medium775Confirmed776Lower777Higher778(Zone 2779peak)780Higher781Rejected782(Zone 1 to 2)783Confirmed784(Zone 1 to 3)785Small786Confirmed787Potchefstroom788Dam789Yes790Lower791Lower792Lower793(Zone 3794peak)795Rejected796(Zone 1 to 3)797Medium798Rejected799Lower800Lower801Lower802(Zone 3803peak)804Rejected805(Zone 1 to 3)806Medium807Rejected808Urban Planning, 2021, Volume 6, Issue 4, Pages 54–6680962810