# RECORD 84a6e8ef31bf481e52cb738679f636c9a2fcc69f # TITLE: Loss of Value in House Properties due to Air Pollution in Map Ta Phut Industrial Area of Thailand # YEAR: 2016.0 VENUE: nan DOI: 10.35762/aer.2016.38.3.1 # AUTHORS: Nararuk Boonyanam # PAGES: 13 CANDIDATE TABLE PAGES (1-based): [8, 9, 10] # ABSTRACT: Air pollution in the Map Ta Phut Industrial Estate in Thailand, has caused increasing risk of death, injury and health problems for local residents. Existing control measures are ineffective due to weak law enforcement. Although the problem has drawn a lot of attention, the monetary value of the impacts of air pollution in Map Ta Phut is not known. The objective of this paper was to estimate the economic cost of air pollution damage in Map Ta Phut using the Hedonic Pricing Method, with 192 house samples. The results showed that the marginal willingness to pay (MWTP) for a one unit reduction of AQI level was THB 2,815 or around USD 80, or each unit increase in air pollution would result in an estimated loss of THB 2,815 or around USD 80 in house price. The total value of losses to housing from one unit of air pollution in Map Ta Phut which is comprise of 38 communities was THB 119.3 million (about USD 3.4 million). Detection of the loss of value has implications for local residents, housing development investors, factories, and government and environmental institutions to manage air pollution as their top priority as well as to evaluate the efficiency of existing measures and budget to deal with the problem more appropriately. ===== PAGE 1 (score 5, numeric-paren 0, table-words 0, var-words 5) ===== App. Envi. Res. 38 (3): 1-13 Loss of Value in House Properties due to Air Pollution in Map Ta Phut Industrial Area of Thailand Nararuk Boonyanam Faculty of Economics at Sri-racha Kasetsart University, Sri-racha, Chonburi 20230, Thailand * Corresponding author: Email: noaratc@gmail.com; Phone: +66895312079 Article History Submitted: 8 June 2016/ Accepted: 2 August 2016/ Published online: 17 October 2016 Abstract Air pollution in the Map Ta Phut Industrial Estate in Thailand, has caused increasing risk of death, injury and health problems for local residents. Existing control measures are inef- fective due to weak law enforcement. Although the problem has drawn a lot of attention, the monetary value of the impacts of air pollution in Map Ta Phut is not known. The objective of this paper was to estimate the economic cost of air pollution damage in Map Ta Phut using the Hedonic Pricing Method, with 192 house samples. The results showed that the marginal willing- ness to pay (MWTP) for a one unit reduction of AQI level was THB 2,815 or around USD 80, or each unit increase in air pollution would result in an estimated loss of THB 2,815 or around USD 80 in house price. The total value of losses to housing from one unit of air pollution in Map Ta Phut which is comprise of 38 communities was THB 119.3 million (about USD 3.4 million). Detection of the loss of value has implications for local residents, housing development in- vestors, factories, and government and environmental institutions to manage air pollution as their top priority as well as to evaluate the efficiency of existing measures and budget to deal with the problem more appropriately. Keywords: Hedonic pricing method; Home price, Air pollution; Map Ta Phut Introduction Map Ta Phut residents have suffered from various forms of pollution, especially air pollu- tion caused by frequent chemical leaks and emis- sions from factories in the Map Ta Phut Indus- trial Estate, located in Rayong province, Thailand. Operations began in 1990, and the estate now hosts 140 industrial plants, including 45 petro- chemical factories, 8 coal-fired power plants, 12 chemical fertilizer factories and 2 oil refineries [10]. A total of 56,591 residents (excluding a large non-registered population of 102,362), live Applied Environmental Research Journal homepage : http://www.tci-thaijo.org/index.php/aer ===== PAGE 8 (score 23, numeric-paren 0, table-words 4, var-words 11) ===== 8 App. Envi. Res. 38 (3): 1-13 Results Descriptive statistics are presented in Table 4, which shows that the average house price in Map Ta Phut was THB 1,750,461 where the average house age was 13 years, and contained an ave- rage three bedrooms and two bathrooms. Ave- rage land size was 191.63 m2. Average distance to the district center was around 7 km. In addi- tion, less than half of the sample houses were located on the main road. Half of the sample houses were detached, and the other half was townhouses which provided a representative sample of each house type. All these attributes showed that the houses in the Map Ta Phut area belonged to middle to upper-middle class families. Table 4 Descriptive statistics Variable Unit Mean TD.DEV. Dependent variable PH House price THB 1,750,461.00 867,495.30 Structural Characteristics Detach House type 1=house, 0=townhouse 0.49 0.50 Age House age Year 12.84 14.02 Bed Number of bedroom rooms 2.47 0.62 Bath Number of bathroom rooms 1.84 0.57 Area Utilization area square meter 141.49 146.64 Lot Land size square meter 191.63 219.12 Neighborhood Characteristics Discbd Distance to district center meter 6,740.13 7,978.17 Main Main road location 1=main road, 0=otherwise 0.29 0.46 Air Pollution SO2 Hourly average concentration of SO2 ppb 5.05 3.91 NO2 Hourly average concentration of NO2 ppb 19.29 2.93 CO 8 hour average concentration of CO ppm 0.99 0.10 O3 Hourly average concentration of O3 ppb 32.14 1.47 PM10 Daily average concentration of PM10 ug/m3 82.57 32.76 VC Daily average concentration of VC ug/m3 0.21 0.04 BT Daily average concentration of BT ug/m3 1.20 0.77 DM Daily average concentration of DM ug/m3 0.79 0.01 CF Daily average concentration of CF ug/m3 0.19 0.01 DE Daily average concentration of DE ug/m3 0.56 0.10 BZ Daily average concentration of BZ ug/m3 2.15 0.20 AQI Daily average concentration of AQI - 43.30 13.20 Note: 1 The air pollution level of AQI between 0-50 = Excellent, 51-100 = good, 101-150 = lightly polluted, 151-200 = moderately polluted, 201-300 = heavily polluted and 300+ = severely polluted A correlation test showed perfect correlation between the air pollution criteria variables as well as VOCs substances, therefore only AQI was used to represent the ambient level of air pollution and the remaining air pollution criteria along with the VOCs were therefore omitted from the ana- lysis to avoid multicollinearity problems that may reduce the precision of the estimate. The non-nor- mality problem was corrected using a boxplot to identify data outliers; eight outliers were removed from the analysis. After removal of these out- liers, the total sample was 192. The results of Box- cox transformations are presented in Table 5. ===== PAGE 9 (score 87, numeric-paren 72, table-words 1, var-words 2) ===== App. Envi. Res. 38 (3): 1-13 9 Table 5 Hypothesis test for Box-Cox transformation Characteristic Variables Box Cox Transformation lhsonly Model rhsonly Model Lambda Model Theta Model Structural Characteristics Detach 434.886*** 391,533.500** 3.048** 10.738* (26.884) (5.373) (5.310) (3.356) Age -0.398 -45,908.140 -0.247 -2.656 (0.033) (0.300) (0.751) (0.265) Bed 156.273*** 286,382.10 3.289** 17.640 (6.852) (0.976) (4.344) (2.115) Bath 262.351*** 569,925.700*** 4.093*** 22.805*** (17.368) (7.381) (10.071) (7.779) Area -0.408* -166,003.900 -0.178 0.131 (3.087) 0.427 (0.302) (0.000) Lot 0.440*** 1,561,252.000*** 1.480*** 241.498*** (7.316) (9.930) (14.003) (19.346) Neighborhood Characteristics Discbd -0.029 -80,836.090 -0.035 -13.424 (1.765) (0.106) (0.027) (0.080) Main -73.568 -184,539.000* -1.488* -6.970 (1.094) (3.260) (2.703) (2.265) Air Pollution AQI 9.955 -1,144,197.000 -2.144 -144.509* (0.590) (1.101) (0.511) (3.582) Constant 596.9216 2488.723 58.813 0.810 AIC 2180.956 2187.270 2175.152 2170.988 BIC 2183.286 2189.601 2177.483 2175.649 Lambda - -0.178 0.175 -0.461* s.e. - (0.295) (0.172) (0.324) Theta 0.476*** - 0.175 0.288** s.e (0.171) - (0.172) (0.160) Loglikelihood -1089.478 -1092.6351 -1086.5762 -1083.494 LR chi-square 103.740 107.750 109.54 115.710 Chi-square for reject Ho when X = -1 65.790*** 4.750** 51.670*** 57.830*** when X = 0 7.680*** 0.350 1.130 7.290*** when X = 1 9.120*** 2.810* 14.930*** 21.090*** The Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were used to select the most suitable Box-Cox model from the four functional forms. The theta model had the lowest AIC and BIC value, suggesting that it provides the best transformation. The theta model produced a value of θ of 0.288 and the value of λ was -0.461 and yielded the best transformation. The rejection of parameters test of the theta model under the null of θ = λ = 1, 0, or -1 indicated that linear and log-log linear mo- del were not suitable functional forms. In addi- tion, the lhsononly model test result also sug- gested that the semi-log functional form should be rejected although the model was not of the best fit. Since all simpler functional forms were rejected, a Box-Cox transformation was used as a func- tional form for this study. The use of the Box- Cox transformation as a functional form (not just as a test) of choice in hedonic regression has ===== PAGE 10 (score 21, numeric-paren 2, table-words 3, var-words 10) ===== 10 App. Envi. Res. 38 (3): 1-13 generally received strong support in the litera- ture [25-26]. The final regression model was as shown in Eq.10. The regression result showed that four out of nine variables were significant, namely: house type, number of bathrooms, air quality and land size. The signs of the significant variables were as expected. The air pollution level was nega- tively correlated with house price, while house type, number of bathrooms and land size were positively correlated, confirming both our re- search hypotheses. The negative sign of the air pollution variable indicated that people are concerned about air pollution levels. The impli- cit price for significant continuous characteris- tics and non-transformed or dummy variables can be calculated using equations (8) and (9). y(0.288) = 0.810 + 10.738Detach + 22.805Bath-0.461 + 241.498Area-0.461 – 144.509AQI-0.461 (Eq. 10) where y(0.288) = y0.288 – 1, xi-0.461 = x-0.461i – 1, xi = Detach, Bath, Area and AQI 0.288 -0.461 The implicit price in Table 6 indicates that the greatest effect on house price is house type. The price difference between detached houses and townhouses was around THB 300,000. The second highest effect was from number of bath- rooms, followed by air pollution. It was surpri- sing to find that the effect of air pollution was greater than that of the land size variable. (Air pollution factors are typically found to have less impact on house price compared to physical com- ponents and location of the house). The coeffi- cient of the AQI variable suggested that better air quality is associated with a higher house price. The result is straightforward. The margi- nal effect of a change in one unit of AQI or it can be interpreted as the marginal willingness to pay (MWTP) for a one unit level reduction in AQI or air pollution of THB 2,815 or around USD 80. The land size variable had the smallest effect on house price. One additional square me- ter of land size will increase the house price by THB 2,221. The result is consistent with the land price appraisal report of the Treasury Depart- ment which indicated that the land price per 4 m2 in the Mapchalood-Charkklang community which has a high polluted air quality index was THB 10,000, while the land price per 4 m2 in the Sanam Pao and Kangamphur-Tangpai commu- nities which have a low polluted air quality in- dex was between THB 40,000 and THB 60,000. The model can be used to calculate average house prices that have certain structural and environ- mental characteristics which benefit both local residents and housing development agents. Table 6 Implicit price of significant variables Significant variable Variable type Coefficient (βi, γi) xiλ-1 y 1-θ Implicit price Detach Dummy 10.738 27869.2022 299,259.4933 Bath Continuous 22.805 0.010373 27869.2022 6,592.8421 Lot Continuous 241.498 0.000330 27869.2022 2,221.2702 AQI Continuous -144.509 0.000699 27869.2022 -2,814.5760 Discussion The study results confirm an association be- tween air pollution and house price in Map Ta Phut. The MWTP for a one unit reduction of AQI level was calculated as THB 2,815 or around USD 80. The result was similar to that found by [24] for Jakarta city in Indonesia which reported that the MWTP for better air quality was in the ===== PAGE 11 (score 17, numeric-paren 0, table-words 0, var-words 17) ===== App. Envi. Res. 38 (3): 1-13 11 range USD 28.34-USD 85.39 or around THB 995 to THB 2,998. The result obtained from Map Ta Phut was quite low in the range com- pared with evidence from a developed country such as the USA (reported by Boyle and Kiel [4] as in the SO2 range of USD 58 to USD 328/ μg/m3). There are 38 communities in the Map Ta Phut Municipality, comprising 42,392 house- holds. Therefore, the total loss of value in house property from air pollution damage in the Map Ta Phut Municipality per unit of AQI is around THB 119.3 million or about USD 3.4 million. This figure is in the housing sector only and is a result of one unit change or a marginal change in the air pollution damage level. Therefore, in rea- lity, the actual monetary loss should be much higher, as normally the air pollution level changes by more than the marginal value. The huge eco- nomic loss identified by this study indicates that the problem should be treated as a top priority over public health and safety to avoid tremen- dous accumulation of economic loss in the fu- ture. Better budget allocation, better law enforce- ment and better cooperation should be adopted immediately before the crisis grows beyond our capability to deal with it. Conclusions and implications House property values in Map Ta Phut de- pend on their structural characteristics and air pollution levels. The structural characteristics that affect house price are house type, number of bathrooms, air quality and land size. Only an aggregate parameter in the form of Air Quality Index (AQI) was tested due to the multicolli- nearity problem between air pollution criteria variables as well as VOCs. The type of house contributes the highest effect to house price com- pared to the effect of additional bathrooms, air quality and lot size, indicating that people in the study area were more concerned about house type than number of bathrooms, air quality and lot size. Factors such as utility area, house age, number of bedrooms, distance to district center and location of the house were found to have no effect on house price. Housing development agents should take the variables with a large effect on house price into account–house type, number of bathrooms, air quality level and lot size. –when developing a housing project. Local residents should consider relocating or selling their house in Map Ta Phut area to prevent further loss to their house value if air pollution levels show no sign of improvement. By recognizing the large loss from air pollution damage in Map Ta Phut, the government, environmental institutions and industrial factories should be able to better ma- nage their priorities and be more concerned about dealing with the air pollution level more appro- priately. References [1] Ara, S., Tekes, C. 2016. The monetary va- luation of acute respiratory illness from air pollution in Turkey. Atmospheric Pollu- tion Research, 7(2016): 82–91. [2] Aungudompukdee, P. 2009. Factors re- lated to neurobehavioral effects in young children residing near petrochemical in- dustrial estate: A community-based cross- sectional study in Map Ta Phut sub-dis- trict, Rayong province, Thailand. Ph.D. dissertation, Chulalongkorn University. [3] Boonpraderm, C. 2010. The implementa- tion effectiveness of the air pollution con- trol policy of the Map Ta Phut Industrial Estate. Ph.D. dissertation, Ramkhamheang University. [4] Boyle, M.A., Kiel, K.A., 2001. A survey of house price hedonic studies of the impact of environmental externalities. Journal of Real Estate Literature, 9(2): 117–144. [5] Chomkrod, J. 2009. Legal measure for the protection and control of air pollution from petrochemical industrial factories: Case study of Map Ta Phut Industrial Es- tate. Thesis, Thammasat University.