1# RECORD b4d90ac556c12775841d148b92b32c2089b062dd2# TITLE: The Effects of Landfills on Rural Residential Property Values: Some Empirical Evidence3# YEAR: 2000.0 VENUE: Journal of Regional Analysis & Policy DOI: 10.68479/001c.93454# AUTHORS: R. Bouvier; J. M. Halstead; K. Conway; A. Manalo5# PAGES: 15 CANDIDATE TABLE PAGES (1-based): [9]6# ABSTRACT: The question of whether solid waste landfills affect residential property values has long been a subject of debate. Past research has resulted in mixed conclusions. The current study examines six landfills, which differ in size, operating status, and history of contamination. The effect of each landfill is estimated by the use of multiple regression. In five of the landfills, no statistically significant evidence of an effect was found. In the remaining case, evidence of an effect was found, indicating that houses in close proximity to this landfill suffered an average loss of about six percent in value.789===== PAGE 1 (score 5, numeric-paren 0, table-words 0, var-words 5) =====1011 12The Effect of Landfills on Rural Residential 13Property Values: Some Empirical Evidence 14 15Rachel A. Bouvier, John M. Halstead, Karen S. Conway, and 16Alberto B. Manalo* 17 18Abstract. The question of whether solid waste landfills affect residential 19property values has long been a subject of debate. Past research has re-20sulted in mixed conclusions. The current study examines six landfills, 21which differ in size, operating status, and history of contamination. The 22effect of each landfill is estimated by the use of multiple regression. In 23five of the landfills, no statistically significant evidence of an effect was 24found. In the remaining case, evidence of an effect was found, indicating 25that houses in close proximity to this landfill suffered an average loss of 26about six percent in value. 27 281. Introduction 29 30The United States is one of the leading solid waste generators in the 31world. Estimates from the Environmental Protection Agency predict that by 32the year 2010, the United States will be generating municipal solid wastes at 33the unprecedented rate of 250 million tons per year (US EPA, 1990). Despite 34recent improvements in recycling and incinerating techniques, the sanitary 35landfill remains the most widely used method of disposal. 36The question of whether solid waste landfills affect residential property 37values has long been a subject of debate. The hedonic technique, which at-38tempts to infer people’s preferences by the way they behave in the market, 39has been used in the past for this purpose, with widely differing results. This 40 41* Rachel Bouvier is graduate research assistant, Department of Economics, University of Massa-42chusetts and Lecturer, Mount Holyoke College; John M. Halstead is Professor, Department of 43Resource Economics and Development, University of New Hampshire; Karen Conway is Asso-44ciate Professor of Economics, University of New Hampshire; and Alberto Manalo is Associate 45Professor, Department of Resource Economics and Development, University of New Hamp-46shire. 47 48 49JRAP (2000)30:2 50 515253===== PAGE 9 (score 169, numeric-paren 136, table-words 5, var-words 2) =====5455Effects of Landfills on Rural Residential Property Values 31 56 57rate, but if the structure of the housing markets differs, the intercept would 58not necessarily capture the difference. 59 60 61Table 3. Results of Landfill Property Value Model 62TOWN 63PEPPERELL 64HUDSON 65BELCHERTOWN 66CLINTON 67LEICESTER 68WARE 69Adj. R2 700.5506 710.7335 720.7034 730.5466 740.4127 750.6215 76F stat: 775.737 7811.275 7916.881 805.662 813.115 828.225 83Prob> F: 840.0001 850.0001 860.0001 870.0001 880.0033 890.0001 90Number 91of obs. 9259 9347 94101 9559 9646 9767 98 99Variable 100 101Coefficient Variable (Standard Error)a 102Intercept 10310.0756*** 104(0.3842) 1059.8012*** 106(0.3795) 10710.4123*** 108(0.2798) 10911.0511* 110(0.5332) 11110.8524*** 112(0.4942) 1139.9469*** 114(0.3218) 115MILF1 116-0.0627* 117(0.0354) 118-0.0280 119(0.0486) 120-0.0065 121(0.0271) 122-0.0099 123(0.0207) 1240.2558 125(0.1588) 1260.0073 127(0.0309) 128MICBD1 1290.0386 130(0.0367) 1310.0522*** 132(0.0193) 133-0.0085*** 134(0.0265) 1350.0298*** 136(0.0167) 137-0.0082 138(0.0238) 139-0.0139 140(0.0249) 141MIHWY1 1420.0001 143(0.0008) 144-0.0017 145(0.0016) 146-0.0008 147(0.0010) 148-0.0012 149(0.0022) 150-0.0038** 151(0.0018) 152-0.0012 153(0.0022) 154AGE 155-0.0021 156(0.0050) 157-0.0057*** 158(0.0015) 159-0.0045*** 160(0.0014) 161-0.0083*** 162(0.0047) 163-0.0086** 164(0.0032) 165-0.0028 166(0.0018) 167AGE2 1680.0000 169(0.0002) 1700.00002** 171(0.00001) 1722.16e-04*** 173(7.15e-05) 1740.000053 175(0.000039) 1760.0004* 177(0.0002) 1784.86e-05 179(1.00e-04) 180BDRM 1810.0650** 182(0.0315) 1830.1063** 184(0.0403) 1850.0730*** 186(0.0246) 1870.0576*** 188(0.0323) 189-0.0178 190(0.0234) 1910.0920*** 192(0.0326) 193OTHRM 1940.0169 195(0.0246) 1960.0213 197(0.0180) 1980.0843*** 199(0.0191) 2000.1069* 201(0.0348) 2020.0078 203(0.0314) 2040.0445* 205(0.0244) 206BTHRM 2070.1236*** 208(0.0345) 2090.0041 210(0.0471) 2110.1191*** 212(0.0381) 213-0.036 214(0.0611) 2150.1610 216(0.0819) 2170.0235 218(0.0406) 219LNLTSZ 2200.1171*** 221(0.0316) 2220.1639*** 223(0.0370) 2240.0601** 225(0.0265) 2260.0255 227(0.05122) 2280.0056 229(0.0419) 2300.01066*** 231(0.0305) 232GRACE 2330.1107*** 234(0.0316) 2350.0397 236(0.0427) 2370.0183 238(0.0351) 2390.1298** 240(0.0552) 2410.0629 242(0.0679) 2430.1602*** 244(0.0547) 245FPLACE 2460.0896** 247(0.0414) 2480.0624** 249(0.0284) 2500.0008 251(0.0330) 2520.0842 253(0.0625) 2540.0935* 255(0.0534) 2560.0633 257(0.0477) 258POOL 2590.0194 260(0.0661) 2610.0901* 262(0.0522) 2630.0660 264(0.0599) 265-0.0160 266(0.1040) 2670.2151* 268(0.1118) 2690.0564 270(0.0781) 271SOLD92 272-0.0086 273(0.0427) 2740.1888** 275(0.0767) 2760.1039** 277(0.0478) 2780.1018 279(0.0955) 280-0.0268 281(0.2175) 2820.0681** 283(0.0787) 284SOLD93 2850.0262 286(0.0526) 2870.0759 288(0.0549) 2890.0260 290(0.0453) 291-0.0284 292(0.0756) 293-0.0078 294(0.2233) 2950.0336 296(0.0843) 297SOLD94 2980.0528 299(0.0430) 3000.0756 301(0.0527) 3020.0344 303(0.0445) 304-0.0992 305(0.0775) 306-0.0243 307(0.2156) 308-0.1101 309(0.0795) 310aWhite corrected standard errors 311 ***statistically significant at the 99% level 312 **statistically significant at the 95% level 313 *statistically significant at the 90% level 314 315 316317318===== PAGE 10 (score 26, numeric-paren 0, table-words 12, var-words 2) =====31932032 321 Bouvier, Halstead, Conway & Manalo 3227. Results of Individual Regressions 323 324Results of each regression are summarized in Table 3. F-statistics for all 325six models indicate that all were significant at the one percent level. The 326more salient features of the regressions are highlighted here. Three of the 327data sets (Pepperell, Clinton and Hudson) showed evidence of model mis-328specification when Ramsey ReSET tests were performed. Some ex post tests 329were then performed on the functional form of the model to determine if the 330Ramsey ReSET tests would yield different results under different functional 331forms. However, the results did not change significantly. Therefore, the 332model remains in its current form, with a cautionary word as to the presence 333of misspecification in three of the models. 334The Pepperell data set generated an adjusted R2 of 0.5506 and an F statis-335tic of 5.737, indicating that the null hypothesis (the model explains none of 336the variation in housing price) can be decisively rejected. As noted below, 337since Pepperell was the only model where heteroskedasticity was present, 338corrected (White) standard errors are reported with the results in Table 3. 339All of the variable coefficients had the hypothesized sign. The landfill vari-340able coefficient is negative, as hypothesized, and it is statistically significant 341at the ten percent level. 342 In Hudson, although the adjusted R2 of 0.7335 attests to the predictive 343power of the model, the distance to the landfill variable coefficient was not 344statistically significant at the five or ten percent level (although it did have 345the hypothesized sign). There is nothing unexpected in the model; most of 346the estimated coefficients were statistically significant and had the hypothe-347sized sign. 348The Belchertown data set yielded an adjusted R2 of 0.7034. Of the nine 349structural characteristics, six were significant at the five percent level and 350had the hypothesized sign. Although the estimated coefficient on the landfill 351variable is the hypothesized sign, a 95 percent confidence interval around the 352estimated coefficient does include zero. Thus, there is no statistically signifi-353cant evidence of an effect of the Belchertown landfill on the surrounding 354property values. 355In the Clinton data set, only two variable coefficients emerged statisti-356cally significant at the five percent level and three more variables were sig-357nificant at the ten percent level. The Clinton model’s adjusted R2 is 0.5466. 358Again, the distance from the landfill variable coefficient is of the hypothe-359sized sign, but statistically insignificant. 360Leicester’s regression resulted in an adjusted R2 of only 0.4125. This 361means that the model has the weakest explanatory power of the six towns; 362however, it is still statistically significant at the five percent level. The coeffi-363cient on the landfill variable is positive, which is contrary to expectations 364(although it is statistically insignificant at the five percent level). Two of the 365variable coefficients in Leicester's regression are statistically significant at the 366five percent levels; four are statistically significant at the ten percent level. 367