1# RECORD 7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a82# TITLE: NET BENEFITS OF URBAN SLUMS REDEVELOPMENT POLICIES ON THE VALUE OF ADJACENT RESIDENTIAL PROPERTY3# YEAR: 2021.0 VENUE: nan DOI: 10.3846/ijspm.2021.145704# AUTHORS: Touseef Hussain; Wei Zou5# PAGES: 12 CANDIDATE TABLE PAGES (1-based): [7, 8, 9]6# ABSTRACT: Over time, the government of Pakistan introduced several strategies to deal with the issue of slums in its capital city, Islamabad. Contrary to the traditional strategies that primarily focus on the tenure security of occupants, the strategy of slum redevelopment is more composite. It involves the up-gradation of slums in their existing sites as well as the demolition of slums from the posh areas. The present study is first to empirically investigates the outcomes of the slums redevelopment policies on the value of adjacent residential properties. Using a rental valuation based hedonic price model, the study examined the spillover effects of an urban slum up-gradation and eviction projects on the nearby housing values. The results show that the redevelopment of slums reduces the adverse effects on residential value. It is essential for the urban planners to cautiously include the slum redevelopment projects spillover effects on the adjacent property value in different geographical locations, to maximize the net positive effects of improvements on the neighborhood.789===== PAGE 1 (score 8, numeric-paren 1, table-words 0, var-words 7) =====1011Copyright © 2021 The Author(s). Published by Vilnius Gediminas Technical University12This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unre-13stricted use, distribution, and reproduction in any medium, provided the original author and source are credited.14NET BENEFITS OF URBAN SLUMS REDEVELOPMENT POLICIES ON THE 15VALUE OF ADJACENT RESIDENTIAL PROPERTY16Touseef HUSSAIN, Zou WEI*17College of Public Administration, Nanjing Agricultural University, 210095 Nanjing, China18Received 06 May 2020; accepted 20 January 202119Abstract. Over time, the government of Pakistan introduced several strategies to deal with the issue of slums in its capital 20city, Islamabad. Contrary to the traditional strategies that primarily focus on the tenure security of occupants, the strategy 21of slum redevelopment is more composite. It involves the up-gradation of slums in their existing sites as well as the demo-22lition of slums from the posh areas. The present study is first to empirically investigates the outcomes of the slums rede-23velopment policies on the value of adjacent residential properties. Using a rental valuation based hedonic price model, the 24study examined the spillover effects of an urban slum up-gradation and eviction projects on the nearby housing values. The 25results show that the redevelopment of slums reduces the adverse effects on residential value. It is essential for the urban 26planners to cautiously include the slum redevelopment projects spillover effects on the adjacent property value in different 27geographical locations, to maximize the net positive effects of improvements on the neighborhood.28Keywords: slums, up-gradation, demolition, hedonic price model, property value, Pakistan.29Introduction30The fast-growing urbanization has consistently been a dis-31tinctive characteristic of the process of development and 32has almost been continuously accompanying by the simi-33larly fast growth of informal settlements, squatter settle-34ments, slums, and other uncontrolled settlements (Asian 35Development Bank and Inter-American Development 36Bank, 2014; Malik et al., 2020). Slums had always been 37considered an essential component of cities globally since 38the outgrowth of urbanization and cities of Pakistan is not 39an exceptional case; the slums are locally known as Katchi 40abadis. Governments around the world have recognized 41the issue of slums as many economic, social, and envi-42ronmental problems are linked with the creation of slums 43(Nijman, 2008). In Pakistan, the government has taken 44several steps to resolve the issue of slums. Over time, the 45policies of the state have gone through paradigm shifts 46from emphatic demolition to the provision of housing 47units to the urban poor. Currently, in Islamabad, there are 48almost 34 slums out of which the government owns only 49ten slums as authorized and takes responsibility for the 50development of infrastructure (Hussain et al., 2019). The 51government rehabilitated the slums using the three con-52cepts application of Urban Renewal, which includes slums 53Up-gradation at the present site in existing form, Slums 54relocation to the Model Urban Shelter Project (MUSP), 55and Slums Up-gradation at the site in the form of planned 56plots. In comparison, the rest of the slum settlements are 57unauthorized or illegal and faced eviction or demolition 58over time (Malik et al., 2020). The current study attempts 59to investigate the outcomes of several government initia-60tives for the improvement of urban infrastructure and the 61redevelopment of slum areas.62One of the critical arguments about adopting urban 63redevelopment is that it brings positive externalities to the 64real estate in the neighborhood (Newell, 2010). Further-65more, redevelopment supports the improvement process 66of the urban environment, boosts the property values in 67the locality, and improves life standard, public security, 68and overall image of the city. Supporters of urban renewal 69believe that redevelopment results in a win-win situation 70for all the stakeholders by creating positive externali-71ties beyond the borders (Newell, 2010). Moreover, they 72consider redevelopment as an essential tool for bringing 73positive externalities to augment the values of the prop-74erty (such as land and building) for the owners of the 75property, whereas increasing the chances for authorities 76in raising the tax base. A few studies also depict that re-77development schemes on a large scale enhance the prop-78erty values in the neighborhood, such as (De Sousa et al., 79International Journal of Strategic Property Management80ISSN: 1648-715X / eISSN: 1648-9179812021 Volume 25 Issue 3: 228–23982https://doi.org/10.3846/ijspm.2021.1457083*Corresponding author. E-mail: zw@njau.edu.cn848586===== PAGE 7 (score 67, numeric-paren 13, table-words 18, var-words 12) =====878823489T. Hussain, Z. Wei. Net benefits of urban slums redevelopment policies on the value of adjacent...904. Results and discussion91Tables 4, 5, and 6 show the estimations of the regressions 92function of existing slum areas, up-gradated slums, and 93the evicted slum sites, respectively. These tables have re-94sults of both linear and log-linear or semi-log functional 95forms of the model. For the estimation of the effects of 96existing slums, upgraded slums, and evicted slum sites 97on house rental value, the study used three indicators: 98distance to existing slums, distance to upgraded slums, 99and distance to evicted slum sites. Thus, each table has 100two models, and each table is with different indicators, 101whereas each model is assessed with both semi-log and 102linear specifications.1034.1. Effects of existing slums on the rental price104The values of the adjusted R2 are from 0.9416 to 0.9504 105in the log-linear and linear model that shows the model’s 106independent variables can explain around 94 to 95 percent 107fluctuation of the dependent variable and be able to indi-108cate the models goodness of fit.109The results of the linear model demonstrate that the 110house located a distance of one kilometer away from exist-111ing slums enjoys more rental value of PKR 5894. It means 112the housing units with the same attributes located one kil-113ometer closer to slum areas lost their rental value around 114PKR 5894 for existing near to slum areas. On the other 115hand, the log-liner model results also reveal rent price 116discount for the dwellings situated within a kilometer dis-117tance from the slum sites, housing units lost almost 18.6% 118rental value for being located nearby slum areas as com-119pared to those similar houses located a kilometer away 120from such slum sites (see Table 4). Furthermore, dwelling 121units located very close to slum sites are affected the most, 122the visibility of the nearest slums from the house also de-123creases the rental value by around 15%.1244.2. Effects of slum up-gradation on the rental price125Table 5 presents the regression results estimation of both 126linear and log-linear models. General, the signs of the co-127efficients seem as expected, however statistically few vari-128ables are not significant. The R2 (demonstrates the sum of 129the fluctuation in the dependent variable due to independ-130ent variables) is 93% in the linear model and 91% in the 131Semi-log or log-linear model, which is highly satisfactory.132The results show the gap between residential housing 133units and up-graded slum areas are positively correlated 134with each other, as distance increases from the up-graded 135slum sites, the rental prices also increase. Meanwhile, the 136rental prices decrease as distance decreases from the up-137graded slums. The distance to the up-graded slum site, we 138observe that its parameter estimate is positive and highly 139significant statistically at the 99 percent level in both mod-140els. The coefficient estimated with the semi-log functional 141form shows that the housing unit located 1 km away from 142the up-graded slums, rental prices of residential housing 143units increase by between 12.5% (see Table 5). That means 144houses located one kilometer closer to up-graded slums 145lose the rental value of 12.5% as compare to those housing 146Table 4. Presenting estimates of a linear and log-linear model with data from existing slums147Variables148Linear model149Log-linear model150Coefficients151Std. Err.152t-value153Coefficients154Std. Err.155t-value156House age15766.18976*15833.642221591.97160.0018017*161.00088231622.04163House unit size16479.99556**1654.55154116617.58167.0013917**168.000119416911.66170Bedrooms1711690.173**172554.191733.05174.0420453**175.01453491762.89177Drawing room1782549.089**179852.24141802.99181.0834143**182.02235191833.73184Bathrooms185734.8915186620.73611871.18188.0181466189.01628021901.11191TV lounge1922003.42*193953.26021942.10195.087841**196.02500141973.51198Garage199977.9888200707.97992011.38202.0537868**203.01856842042.90205Servant quarter2062646.275**207671.71682083.94209.0585302**210.01761732113.32212Lawn2131815.562**214679.32892152.67216.0913645**217.01781692185.13219Distance to CBD2201113.781**221142.38012227.82223.0122385**224.00373422253.28226Distance to school2271324.7272281594.8242290.83230.0751735231.04182782321.80233Distance to park2343562.901**235999.74772363.56237.1086817**238.02622062394.14240Distance to slums2415894.832**2421632.2322433.61244.1864864**245.04280892464.36247Visibility2485985.225**2491228.7312504.87251.151787**252.03222622534.71254_cons25514133.57**2562084.1272576.782589.837591**259.0546609260179.97261R-squared2620.95472630.9466264Adj R-squared2650.95042660.9416267Prob > F2680.00002690.0000270Note: *, ** denotes significance at 5% and 1% levels.271272273===== PAGE 8 (score 55, numeric-paren 13, table-words 10, var-words 16) =====274275International Journal of Strategic Property Management, 25(3): 228–239276235277units situated a kilometer away from up-graded slum ar-278eas. Furthermore, the linear model shows PKR 4921, and 279the log-linear model reveals a 10.8% less rental price for 280housing units close enough to visible to up-graded slums.2814.3. Effects of slum eviction/demolition on the 282rental price283Table 6 represents the estimation results of the eviction of 284slum areas’ effects on house rental value by using linear 285and log-linear models. The satisfactory level of adjusted 286R2 of both models demonstrates the model’s goodness of 287fit. The distance to the evicted slum sites (the critical vari-288able in this model) is associated with an increase in rental 289price at a rate of 6.7% per kilometer, keeping other vari-290ables in the model constant. That means houses situated a 291kilometer closer to evicted slum sites have a discount on 292the rental price of 6.7%.293The findings of the current study reveal the significant 294positive effect of both the up-gradation and eviction of 295slum areas on the residential housing rental value. It sug-296gests that slum up-gradation and eviction of unauthorized 297katchi abadis has brought improvements to the neighbor-298ing environment, and the public anticipation regarding 299the advantages of improved environment and amenities 300trigger the appreciation of the residential prices. The find-301ings of the current study are somehow comparable with 302the findings of some urban development studies such as 303De Sousa et al. (2009) and Ki and Jayantha (2010) even 304though Zhang et al. (2016) study are about evictions of 305inferior settlements (urban villages) on residential prices. 306However, the comparability needs to be done much care-307fully as the redevelopment of slums is unmatchable with 308the previous research. The evidence of a study conducted 309by Zhang et al. (2016) found the net benefits of the evic-310tion of the urban villages on residential property prices in 311Beijing, China. The study showed that an average urban 312village negatively affects residential prices of around 2.5% 313of nearby housing societies, and the removal or demoli-314tion of an urban village enhances the value of neighbor-315ing housing up to 3.4%. The study showed lower adverse 316effects of urban villages on the residential properties as 317compared to slums or katchi abadis. The reason for this is 318might be because of the difference in characteristics of ur-319ban villages and katchi abadis. The urban villages in China 320are different from the slums in Pakistan. Urban villages are 321formal settlements with tenure security, and the govern-322ment is responsible for the development.323In contrast, slums or katchi abadis are informal set-324tlements and do not have land ownership rights, and the 325government is not responsible for the development. The 326situation in katchi abadis is more deteriorated and causes 327several socio-economic, political, and environmental is-328sues as compared to the urban villages. The evidence of 329the study conducted by De Sousa et al. (2009) on the im-330pact of the redevelopment of Brownfields on the residen-331tial value in Milwaukee and Minneapolis, United States, 332revealed the net benefit of urban brownfield redevelop-333ment increased the residential property value by around 334Table 5. Showing estimates of a linear and semi-log model with data from upgraded slums335Variables336Linear model337Log-linear model338Coefficients339Std. Err.340t-value341Coefficients342Std. Err.343t-value344House age345166.016**34645.901043473.62348.0045487**349.0010464350–4.35351House unit size35265.67229**3534.54888935414.44355.0009076**356.00010373578.75358Bedrooms3592041.083**360718.72923612.84362.0488116**363.01638493642.98365Drawing room3663378.79*3671378.3573682.45369.067677*370.03142243712.15372Bathrooms373894.3884374678.33053751.32376.0122106377.01546393780.79379TV lounge3801652.7423811157.7463821.43383.0591468*384.02639323852.24386Garage3871545.1443881140.9483891.35390.0643446*391.02601023922.47393Servant quarter3943936.82**3951136.2993963.46397.088549**398.02590433993.42400Lawn4012333.943*4021089.4344032.14404.0558746*405.02483594062.25407Distance to CBD4084085.165**409808.89754105.05411.1300239**412.0184405413–7.05414Distance to school4152238.825*4161076.8434172.08418.0511055*419.0245488420–2.08421Distance to park4222816.003*4231211.2154242.32425.086923**426.0276121427–3.15428Distance to upgraded slums4296568.099**4302070.6754313.17432.1258162**433.04720524342.67435Visibility4364921.391**4371451.894383.39439–.1080642**440.0330988441–3.26442_cons44338553.44**4446267.5954456.1544610.82699**447.142882644875.78449R-squared4500.94414510.9193452Adj R-squared4530.93924540.9121455Prob > F4560.00004570.0000458Note: *, ** denotes significance at 5% and 1% levels.459460461===== PAGE 9 (score 61, numeric-paren 14, table-words 11, var-words 18) =====462463236464T. Hussain, Z. Wei. Net benefits of urban slums redevelopment policies on the value of adjacent...4652.7% in Minneapolis and 11.4% in Milwaukee. The net 466benefit of the redevelopment of brownfields in the Mil-467waukee region is nearly matching with the net benefit of 468the eviction of katchi abadis of the current study.469The functions of regression in Tables 4, 5, and 6 dis-470play the figures, as well as the estimated sign of neigh-471borhood and structural characteristics in existing slum 472sites, up-gradated slums, and the evicted slum site data, 473are as expected in all model specifications of both linear 474and log-linear models. The log-linear model showed more 475significant results as compared to the linear model. The 476study more precisely included the results of the log-linear 477specification to explain the structural and accessibility 478variables of the study. The variables for physical attributes 479of dwellings have the anticipated coefficient signs and are 480mostly coherent with the outcomes of immense literature 481of hedonic modeling. For instance, the additional bed-482room surges the rental value of the house by 4.2% in the 483existing slum site.484Nevertheless, the enhancement in rental price due to 485the existence of an additional bedroom is 4.4% in the case 486of evicted slum site areas. The presence of a servant quarter 487in the house increases the rental value by up to 5.8% in the 488existing slum areas and 8.8% in the up-graded slum areas. 489It is 7.9% in the evicted slum site. The size of the dwell-490ing unit is the most influential independent variable to 491forecast the rental price, with the highest t-value of 11.66, 4928.75, and 12.01, respectively, among all other independent 493variables. Against anticipations, the additional bathroom 494does not significantly affect the rental price in all data sets 495of the log-linear model. Furthermore, the presence of ga-496rage or parking space was given equal importance by both 497models, with an approximate t-value of 2.90 in the existing 498slum sites, 2.47 in the up-graded slum sites, and 2.33 in 499the evicted slums sites data set. The results also show that 500the presence of lawn enhances the rental price by approxi-501mately 9% in existing slum sites, 5% in up-graded slum 502areas, and 2% in evicted slum sites data set (see Tables 4, 5035, 6). The presence of public facilities enhances the rental 504value of nearby houses, distance increases between public 505services and housing units significantly reduces the rental 506value of residential property in the market.507Conclusions and policy implications508The study aimed to examine the value enhancement im-509pact of urban slums improvement and redevelopment pol-510icies on the rental prices of residential property. This study 511used slum up-gradation and eviction projects to evaluate 512this issue empirically. The results of the study depict that 513redevelopment resulted in substantial value enhancement 514to neighboring residential property. Notably, the rental 515prices of residential units in the vicinity of evicted and 516upgraded slum sites have been increased significantly. The 517results suggest that potential house residents seem more 518willing to spend for a house that is situated nearer to the 519redeveloped locality.520Table 6. Showing estimates of a linear and semi-log model with data from evicted slum sites521Variables522Linear model523Log-linear model524Coefficients525Std. Err.526t-value527Coefficients528Std. Err.529t-value530House age53171.6843753238.280945331.87534.0013215535.0010493536–1.26537House unit size53877.49149**5395.6424254013.73541.001857**542.000154754312.01544Bedrooms5451596.682**546413.72855473.86548.0443812**549.01134035503.91551Drawing room552950.7497553585.32365541.62555.033505*556.01604375572.09558Bathrooms559951.5119*560460.76685612.07562.0222714563.01262965641.76565TV lounge5661137.778*567511.80095682.22569.0327429*570.01402855712.33572Garage5731375.326*574527.77945752.61576.0337009*577.01446645782.33579Servant quarter5802524.987**581631.12665824.00583.0794629**584.01729925854.59586Lawn5871034.311*588502.44335892.06590.0295001*591.0137725922.14593Distance to CBD594809.7306*595330.36235962.45597.0184054*598.0090552599–2.03600Distance to school6011809.456**602688.35236032.63604–.0361071605.0188677606–1.91607Distance to park6082949.794**6091098.344610–2.69611–.0778371*612.0301056613–2.59614Distance to evicted slums6152930.03*6161490.8826171.97618.0792828*619.04086516201.94621Visibility6222237.263*6231077.658624–2.08625–.0676483*626.0295386627–2.29628_cons62920617.66**6303801.1816315.4263210.05659**633.104190363496.52635R-squared6360.88176370.8683638Adj R-squared6390.87096400.8563641Prob > F6420.00006430.0000644Note: *, ** denotes significance at 5% and 1% levels.645646647===== PAGE 10 (score 16, numeric-paren 0, table-words 0, var-words 15) =====648649International Journal of Strategic Property Management, 25(3): 228–239650237651From these findings, we can draw various conclusions. 652Firstly, for landlords and developers, an enhanced envi-653ronment neighborhood quality can undoubtedly be seen 654as a vital selling point. Those slum development projects 655which are well planned and implemented are capable of 656enhancing the environment of the vicinity and support 657the marketability and value of surrounding properties. 658Hence, an enhanced environment of the vicinity is like 659a guarantee or promise from the authorities of urban de-660velopment. Therefore, the residential property values will 661reach to highest standards. Finally, it helps to surge the 662competitiveness and marketability of the properties.663Consequently, the authorities of urban development 664and planning possibly will consider the actual benefits that 665slum redevelopment creates in the market in particular 666and the society in a broad-spectrum. Secondly, the aware-667ness of people about the real benefits of the slum redevel-668opment will be enhanced. The positive perception of the 669general public creates a favorable impression of the slum’s 670redevelopment in the society at large. Consequently, the 671negative attitudes in particular segments of society about 672slum redevelopment will be changed.673The findings of the current study indicate specific nec-674essary implications. Considering policymaking bodies, 675this study highlights the main underlying assumptions 676about the implementation of the slums redevelopment 677process: the advantages received by the nearby real estate 678market because of improvement in proximate slum set-679tlements. It is due to the slum redevelopment capability 680for enhancing the environment of urban living, hence in-681creases the life quality, city image, and safety of the public. 682Additionally, it also helps to improve the property values 683in the vicinity that will result in an increase of tax base for 684relevant authorities. Though slum redevelopment projects 685incur high costs, developers and authorities think that 686the measures taken for raising public awareness about 687the slum redevelopment will be a business opportunity 688for them. It could also assist in enhancing redevelopment 689policies and implications and increasing redevelopment 690demand in the market.691Moreover, the findings could also help bring the atti-692tude of Islamabad to improve the environment at a higher 693standard. Due to a lack of awareness of the potential ben-694efits of slum redevelopment, several segments of society 695are reluctant to support the slum area’s redevelopment. So 696these findings will also be helpful for those sections and 697authorities to understand the real benefits of slum rede-698velopment. This will help authorities to make decisions 699when to go for redeveloping a slum area as it should be 700taken place when the worth of property/land of a new 701expansion surpasses the worth of properties outstanding 702in its present use. The present study has some limitations 703which need to be acknowledged. The lack of housing sales 704transaction data is one of the limitations of the study. The 705function of hedonic price modeling is based on the self-706reported rental price of housing units, related research is 707usually done with the sale price of the residential unit. 708The study is limited to the influences of slum improve-709ment or redevelopment policies on the residential prices 710only; the studies in the future may include the value of 711properties in the commercial and industrial areas. Hence, 712further research requires more precise data for testing and 713consolidating the findings of this study.714Acknowledgements715Authors are thankful to College of Public Administration, 716Nanjing Agricultural University (NJAU).717Funding718The APC was funded by Nanjing Agricultural University, 719China.720Author contributions721T. H. has conceptualized, drafted methodology, data col-722lected and analyzed, while Z. W. supervised and reviewed 723the edited manuscript.724Disclosure statement725The authors have no competing interests.726References727Akinjare, O. A., Ayedun, C. A., Oluwatobi, A. O., & Iroham, O. C. 728(2011). Impact of sanitary landfills on urban residential prop-729erty value in Lagos State, Nigeria. Journal of Sustainable De-730velopment, 4(2), 48–60. https://doi.org/10.5539/jsd.v4n2p48731Asian Development Bank and Inter-American Development 732Bank. (2014). Sustainable urbanization in Asia and Latin 733America. 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