# RECORD fdf3432efb95e96e6e45a3ba105603f17a38d366 # TITLE: HEDONIC VALUATION OF MARGINAL WILLINGNESS TO PAY FOR AIR QUALITY IMPROVEMENT # YEAR: 2012.0 VENUE: nan DOI: 10.20885/ejem.v4i2.3318 # AUTHORS: Endah Saptutyningsih; A. Basuki # PAGES: 10 CANDIDATE TABLE PAGES (1-based): [6, 7, 8] # ABSTRACT: Abstract This study aims to identify the highest air pollution areas and to estimate household marginal willingness to pay for air quality improvement. The result of Kriging technique indicates that six sub districts in Yogyakarta City and one sub district in Gunungkidul have highest concentration of particle pollution (PM10). The result of hedonic price method conclude that by adopting a two-stage estimation procedure an 1% increase in the level of PM10 reduced property prices in the study area by 0.32%. Marginal implicit price for reducing PM10 is Rp 957,900.00. The households are willing to pay an additional amount of 1.34 percent for a reduction in PM10 by 1%. Keywords: Air pollution, marginal willingness to pay, hedonic price, implicit price JEL classification numbers: D12, Q53 Abstrak Penelitian ini bertujuan mengidentifikasi daerah polusi udara tertinggi dan untuk memperkirakan kesediaan marginal rumah tangga untuk membayar untuk perbaikan kualitas udara. Dengan menggunakan teknik Kriging, hasil penelitian menunjukkan bahwa enam kecamatan di Kota Yogyakarta dan satu kecamatan di Gunungkidul memiliki konsentrasi tertinggi partikel polusi (PM10). Sementara itu, dengan metode harga hedonik yang mengadopsi prosedur dua tahap, paper ini menyimpulkan bahwa setiap peningkatan PM10 sebesar 1% akan menurunkan harga properti di daerah penelitian sebesar 0.32 persen. Harga implisit marjinal untuk mengurangi PM10 adalah Rp 957,900. Rumah tangga bersedia membayar tambahan 1,34 persen untuk pengurangan PM10 sebesar 1%. Kata kunci: Polusi udara, keinginan membayar marjinal, harga hedonik, SIG, harga implisit JEL classification numbers: D12, Q53 ===== PAGE 1 (score 7, numeric-paren 0, table-words 0, var-words 7) ===== ECONOMIC JOURNAL OF EMERGING MARKETS October 2012 4(2) 163-172 HEDONIC VALUATION HEDONIC VALUATION HEDONIC VALUATION HEDONIC VALUATION OF MARGINAL WILLINGNESS OF MARGINAL WILLINGNESS OF MARGINAL WILLINGNESS OF MARGINAL WILLINGNESS TO PAY TO PAY TO PAY TO PAY FOR AIR QUALITY IMPROVEMENT FOR AIR QUALITY IMPROVEMENT FOR AIR QUALITY IMPROVEMENT FOR AIR QUALITY IMPROVEMENT Endah Saptutyningsih Universitas Muhammadiyah Yogyakarta end_naufal@yahoo.com Agus Tri Basuki Universitas Muhammadiyah Yogyakarta Abstract This study aims to identify the highest air pollution areas and to estimate household marginal will- ingness to pay for air quality improvement. The result of Kriging technique indicates that six sub districts in Yogyakarta City and one sub district in Gunungkidul have highest concentration of particle pollution (PM10). The result of hedonic price method conclude that by adopting a two-stage estimation procedure an 1% increase in the level of PM10 reduced property prices in the study area by 0.32%. Marginal implicit price for reducing PM10 is Rp 957,900.00. The households are willing to pay an additional amount of 1.34 percent for a reduction in PM10 by 1%. Keywords: Air pollution, marginal willingness to pay, hedonic price, implicit price JEL classification n umbers: D12, Q53 Abstrak Penelitian ini bertujuan mengidentifikasi daerah polusi udara tertinggi dan untuk memperkirakan kesediaan marginal rumah tangga untuk membayar untuk perbaikan kualitas udara. Dengan menggunakan teknik Kriging, hasil penelitian menunjukkan bahwa enam kecamatan di Kota Yogyakarta dan satu kecamatan di Gunungkidul memiliki konsentrasi tertinggi partikel polusi (PM10). Sementara itu, dengan metode harga hedonik yang mengadopsi prosedur dua tahap, paper ini menyimpulkan bahwa setiap peningkatan PM10 sebesar 1% akan menurunkan harga properti di daerah penelitian sebesar 0.32 persen. Harga implisit marjinal untuk mengurangi PM10 adalah Rp 957,900. Rumah tangga bersedia membayar tambahan 1,34 persen untuk pengurangan PM10 sebesar 1%. Kata kunci: Polusi udara, keinginan membayar marjinal, harga hedonik, SIG, harga implisit JEL classification n umbers: D12, Q53 INTRODUCTION The increase in per capita income, which has been evidenced in Indonesia in the last few decades, is one of the achievements of Indonesia as a society. This has, as a result, increased the demand for various goods and services, including motor vehicles as means of transportation. The demand for motor vehicle has been so massive that the urban air pollution caused by it has become serious health problems due to the effects on morbidity and mortality and also the loss of environ- mental comfort due to visibility reduction. Therefore, loss assessment caused by air pollution is important in assessing the costs to overcome the pollution. Various types of transportation equipments, especially motor vehicle, every day thronged the streets in cities as centres of economic activities (central business dis- trict). This phenomenon also occurred in Yogyakarta Special Territory (YST) where there are many centres of commerce and ===== PAGE 6 (score 20, numeric-paren 0, table-words 2, var-words 13) ===== 168 ECONOMIC JOURNAL OF EMERGING MARKETS October 2012 4(2) 163-172  Table 2: Description and Statistic Summary of Variables Variable Description Mean Stand.Deviation PPRICE Sales price of house(Rupiahs) 3E+008 243,617,628.2 LANDSIZE Plot area (m2) 206.05 198.288 BUILDSIZE Building area (m2) 124.28 111.246 NUMROOM Number of rooms (units) 4.00 4.614 WSTRUCTDUM Dummy structure of wall 1.15 0.497 DISSCHOOL Distance from school (m) 512.94 555.328 DISHPITAL Distance from hospital (m) 956.26 802.810 DISSPMARKET Distance from supermarket (m) 990.68 867.411 DISREST Distance from restaurant (m) 642.64 785.568 DISCITY Distance from city (m) 2,062.04 1,592.980 DISMSTREET Distance from main- street (m) 192.01 165.511 GARDENDUM Dummy for close to garden or not 1.79 0.407 INCOMEDUM Dummy for level of income 1.88 0.509 FAMEMBER Number of family members (people) 3.92 1.356 PM10 Concentration of PM10 (ppm) 1,223.12 39.612 Among the neighbourhood vari- ables, six major ones namely distance from school, distance from hospital, distance from supermarket, distance from restaurant, distance from the city, distance from main street, are also considered for this analysis. The distance calculated is that from the residence of the household to the nearest location related. The average distance from school is 512.94 meters. The distance from the nearest hospital is 956.26 meters on av- erage. The average distance from main- street is 192 meters. One of the ‘socioeco- nomic variables’ is the number of family member. The average number of family member is four people. In the hedonic price model that we adopt in this study, the con- centration of PM10 is taken as a measure of air quality. The data used comes from am- bient air quality monitoring of Badan Ling- kungan Hidup of YST. Ambient air quality for the year 2010 is 1,223.12 ppm on aver- age. In the estimation of hedonic price equation, we assume a negative relation- ship between environmental characteristic PM10 and the property price, and that the presence of garden near the house is as- sumed to have a positive influence. All the structural parameters included in the model, like plot area and building area, are expected to have positive relations with the property price. Neighbourhood characteris- tics like distance from hospital and restau- rant are inversely related with property price. It is normally expected that as dis- tance from hospital increases, property price decrease, where as distance from main-street increases property price also increases. Applying these assumptions on the model specified above, the parameters are estimated using the method of ordinary least squares and is given in table 3 below. The main inferences of this analysis are given as follows. (1) All the neighbour- hood and structural characteristics except wall structure, number of rooms, distance from school and distance from city are statistically significant at 5 percent level of significance. (2) The environmental characteristic, PM10, is negatively related to house price and it sig- nificant at 1 percent level. The results also confirm that as the level PM10 increases by one percent house price reduces by 0.32 per- cent on the average. (3) Among the neighbourhood characteristics, the presence of garden positively related to property price. (4) Distance from hospital or restau- rant are negatively related to house price, showing that the plots nearer the hospital or restaurant have high property values. (6) Distance from supermarket or main-street are positively related, showing that when distance increases, property price also in- creases. (7) The plot area and building area are also positively related to property price. ===== PAGE 7 (score 40, numeric-paren 22, table-words 5, var-words 3) ===== Hedonic Valuation of Marginal Willingness… (Sapt utyningsih and Basuki) 169 Table 3: Regression Result of Hedonic Price Function Variable Full Model Fit Model (Constant) 17.181 (17.689)*** 17.210 (20.064)*** LnLANDSIZE 0.397 (4.381)*** 0.396 (4.432)*** LnBUILDSIZE 0.353 (3.404)*** 0.393 (3.915)*** LnNUMROOM 0.116 (1.121) - WSTRUCTDUM -0.081 (-1.012) - LnDISSCHOOL -0.046 (-0.895) - LnDISHPITAL -0.163 (-2.936)*** -0.160 (-3.115)*** LnDISSPMARKET 0.103 (1.918)* 0.103 (1.975)** LnDISREST -0.155 (-3.606)*** -0.160 (-3.999)*** LnDISCITY 0.039 (0.680) - LnDISMSTREET 0.091 (3.089)*** 0.092 (3.153)*** GARDENDUM 0.261 (2.637)*** 0.232 (2.377)** LnPM10 -1.355 (-2.355)** -0.320 (-2.806)*** No. Observation Adjusted R2 250 0.606 250 0.606 The regression results of the hedonic price function shows that all the significant esti- mated variables follow the expected rela- tionship pattern. Hence the estimated equa- tion could be written as: ln PPRICE =17.210 + 0.396 lnLANDSIZE + 0.393 ln BUILDSIZE -0.160 ln DISHPITAL + 0.103 ln DISSPMARKET -0.160 ln DISREST + 0.092 ln DISMSTREET + 0.232 GARDENDUM - 0.320 ln PM10 + e The first derivative of the hedonic price function can be interpreted as the im- plicit marginal price function for the envi- ronmental goods. Descriptive statistics of implicit marginal prices for 250 observa- tions is given in the table 4 below. Table 4: Descriptive Statistics of Implicit Marginal Price Descriptive Statis- tics Implicit Marginal Price (Rupiahs) Mean 957912.3 Standard error 87071.6 Median 409600 Mode 352000 Standar deviation 1376723 Minimum 19200 Maximum 1E+007 Hence the marginal implicit price for reducing PM10 is calculated as Rp 957.900. This result clearly identifies air quality as an important factor, along with structural and neighbourhood characteristics, in determin- ing demand for property transaction in Yogyakarta Special Territory. ===== PAGE 8 (score 48, numeric-paren 25, table-words 4, var-words 10) ===== 170 ECONOMIC JOURNAL OF EMERGING MARKETS October 2012 4(2) 163-172  As mentioned earlier, second stage estimation of inverse demand curve is done by regressing the implicit marginal price on the quantity of environmental goods pur- chased and other socio economic features including income level of the individuals. The results are given in Table 5 below. The major inferences are as follows. (1) The first derivative of the implicit mar- ginal price function with respect to PM10 is negative (-1.341) signalling decreasing marginal implicit prices for increasing en- vironmental quality. It means that in the study area, a reduction in PM10 by one percent leads to 1.34 percent increase in property values. (2) The coefficient of number of family members, wall structure, distance from school, and distance from city are not significant. (3) All other vari- ables except number of family members, wall structure, distance from school, and distance from city are significant at 5 per- cent level of significance. It is interesting to note that the distance from the main-street increases by one percent, residential prop- erty value enhances by 0,096 percent. (4) Plot area and building area are positively related to residential property values. So far we have explained the he- donic price function estimation and its im- plications to residential property values. The results indicate very clearly that the households are willing to pay for improved air quality. It is therefore necessary to esti- mate the welfare benefits accruing to them through the purchase of property with re- duced air quality. Table 5: Estimation of Inverse Demand Function Variable Full Model Fit Model (Constant) 16.037 (16.551)*** 16.080 (18.840)*** INCOMELEVEL 0.101 (1.204) 0.143 (1.844)* LnFAMEMBER 0.098 (0.912) - LnLANDSIZE 0.393 (4.337)*** 0.391 (4.387)*** LnBUILDSIZE 0.358 (3.452)*** 0.381 (3.810)*** WALLSTRUCTDUM -0.080 (-0.996) - LnNUMROOM 0.069 (0.650) - LnDISSCHOOL -0.50 (-0.977) - LnDISHOSPITAL -0.168 (-3.025)*** -0.163 (-3.195)*** LnDISSUPERMARKET 0.101 (1.873)* 0.103 (1.981)** LnDISRESTAURANT -0.159 (-3.695)*** -0.165 (-4.129)*** LnDISCITY 0.039 (0.689) - LnDISMAINSTREET 0.096 (3.199)*** 0.100 (3.416)*** GARDENDUM 0.260 (2.590)** 0.221 (2.273)** LnPM10 -1.341 (-10.932)*** -1.355 (-11.784)*** No. Observation Adjusted R2 250 0.752 250 0.754 ===== PAGE 9 (score 15, numeric-paren 0, table-words 0, var-words 15) ===== Hedonic Valuation of Marginal Willingness… (Sapt utyningsih and Basuki) 171 CONCLUSION The primary objective of this study was to establish the relationship between air qual- ity and the residential property values in Yogyakarta Special Territory (YST). By mapping the area which has highest con- centration of PM10 earlier and estimating the hedonic property value in the area, we can establish the relationship between air quality and the residential property values. In the constructed model, we incor- porated a number of structural, neighbour- hood, environmental and socioeconomic variables as determinants of consumer’s willingness to pay for reduced air quality. We hypothesized that the major environ- mental variable PM10 is inversely related to the residential property values. Similarly, the presence of garden, distance from main- street, distance from supermarket, plot area, and building area are positively related to property price while distance from hospital and distance from restaurant are negatively related. By adopting a two-stage estimation procedure to estimate these relationships, we found that, on the average, an increase in the level of PM10 reduced property prices in the study area by 0.32 percent. We estimated the marginal implicit price for reducing PM10 as Rp 957,900.00. Further estimation revealed that the households are willing to pay an additional amount of 1.34 percent for a reduction in PM10. In short, the analysis revealed a positive response of households in YST, which have highest concentration of PM10, between air quality and property prices. REFERENCES Baby, P.K. (2003),“Economic Impacts of Air Pollution on Human Health and Property Values: A Study of Cochin Industrial Agglomeration,” Thesis, Department of Ap- plied Economics, Cochin University of Science and Technology, India. Bayer, P., N. Keohane and C. Timmins (2006), “Migration and Hedonic Valuation: The Case of Air Quality,” NBER Working Papers 12106, National Bureau of Economic Research, Inc. Chu, H., Y. Lin, Y. Huang and Y. Wang (2009),”Detecting the Land-Cover Changes In- duced by Large-physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis,” Sensors, 9, 6670-6700. 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