上海市能源消費(fèi)量的計(jì)量分析

1、上海市能源消費(fèi)量的計(jì)量分析一、前言在當(dāng)今的國(guó)與國(guó)競(jìng)爭(zhēng)中,能源問題已經(jīng)成為非常重要的影響因素,在某種意義上說能源決定了一個(gè)國(guó)家的未來發(fā)展。能否獲得有效能源保障關(guān)系到很多國(guó)家的生存和發(fā)展。在本文主要通過1985-2003年的一些數(shù)據(jù),應(yīng)用計(jì)量經(jīng)濟(jì)學(xué)的分析方法,來分析影響上海市的能源消費(fèi)量的一些因素,并對(duì)未來的消費(fèi)量進(jìn)行粗略的預(yù)測(cè)。通過分析,在掌握和熟練計(jì)量分析方法的同時(shí),對(duì)上海市的能源問題進(jìn)行分析,并提出一些自己的看法。二、理論背景在近期,我國(guó)相繼采取了一系列的解決未來能源問題的行動(dòng),例如:中國(guó)在巴西購(gòu)買鋁土,在智利購(gòu)買銅,在澳大利亞購(gòu)買鋅,向哈薩克斯坦購(gòu)買石油,與日本爭(zhēng)奪“安大線”等等都表明能源

2、對(duì)我國(guó)的重大意義。能否保證能源的供需平衡是我國(guó)未來的一個(gè)巨大挑戰(zhàn)。而能源消費(fèi)則成為此問題的重要因素。鑒于此我選擇中國(guó)經(jīng)濟(jì)發(fā)展的一個(gè)代表我國(guó)經(jīng)濟(jì)最發(fā)達(dá)城市上海作為分析的對(duì)象,分析影響能源消費(fèi)量的因素,來探究我國(guó)能源問題的過去、現(xiàn)在和未來。三、模型建立與選擇本文選擇一些宏觀因素從總體和宏觀的角度來分析能源消費(fèi)量的問題。本文選擇了6個(gè)解釋變量來解釋能源消費(fèi)量的變化,被解釋變量-能源消費(fèi)量是總體的能源消耗量,包括多種能源。X1年末戶籍人口表示人口數(shù)量,人口越多則對(duì)能源的需求量越多,消耗也越多。GDP表示上海市國(guó)內(nèi)生產(chǎn)總值,是上海市經(jīng)濟(jì)規(guī)模和活躍程度的一個(gè)體現(xiàn)。用于教育的財(cái)政支出表示上海市對(duì)教育的主要投

3、入,教育投入越多則表示人們素質(zhì)就應(yīng)該相對(duì)較高,科技人才就越多,科技水平就越高,相應(yīng)能節(jié)省越多的能源。人均可支配收入表示人們平均所擁有的消費(fèi)能力,人均可支配收入越多則能源的消費(fèi)越多。全市財(cái)政收入主要包括全市企業(yè)所得和全市的稅收收入,因此財(cái)政收入也表示上海市的經(jīng)濟(jì)規(guī)模和發(fā)展?fàn)顩r,財(cái)政收入越高則對(duì)能源的消費(fèi)需求就越高。本文利用Eviews軟件對(duì)每個(gè)解釋變量的組合進(jìn)行最小二乘法回歸分析,建立一個(gè)合適有效的估計(jì)方程。然后,再利用夸特法對(duì)方程進(jìn)行異方差檢驗(yàn),若存在異方差則利用加權(quán)最小二乘法進(jìn)行修正。若DW檢驗(yàn)值表示存在自相關(guān)則利用廣義差分法對(duì)其修正。最終找到一個(gè)較準(zhǔn)確有效的估計(jì)方程,繼而對(duì)2004年上海市

4、能源消費(fèi)量進(jìn)行預(yù)測(cè)。四、數(shù)據(jù)來源分析本文選擇了6個(gè)解釋變量(X1、X2、X3、X4、X5、 X6,來解釋能源消費(fèi)量(Y其數(shù)據(jù)表格如下:能源消費(fèi)量(萬噸標(biāo)準(zhǔn)煤Y年末戶籍人口(萬人X1GDP(億元X2工業(yè)總產(chǎn)值(億元X3用于教育的財(cái)政支出(億元X4人均可支配收入(元X5全市財(cái)政收入(億元X6消費(fèi)價(jià)格指數(shù)(以1952年價(jià)格1985 2553.21 1216.69 466.75 862.73 6.58 1075 263.86 134.8 1986 2783.66 1232.33 490.83 952.21 7.51 1293 257.72 143.3 1987 2868.06 1249.51 545.

5、46 1073.84 7.47 1437 241.36 154.9 1988 2980.64 1262.42 648.3 1304.66 8.6 1723 261.69 186.00 1989 3111.03 1276.45 696.54 1524.67 10.25 1975 297.25 215.60 1990 3191.06 1283.35 756.45 1642.75 11.35 2182 284.36 229.20 1991 3466.52 1287.2 893.77 1947.18 12.48 2486 324.66 253.20 1992 3656.92 1289.37 1114.

6、32 2429.96 14.93 3009 340.13 278.50 1993 3946.73 1294.74 1511.61 3327.04 20.06 4277 439.53 334.80 1994 4176.64 1298.81 1971.92 4255.19 31.21 5868 615.91 414.821995 4465.87 1301.37 2462.57 5349.53 39.44 7172 702.46 492.39 1996 4626.21 1304.43 2902.2 5126.22 49.89 8159 873.76 537.69 1997 4758.82 1305.

7、46 3360.21 5649.93 63.59 8439 1070.95 552.74 1998 4874.11 1306.58 3688.2 5763.67 76.01 8773 1146.00 552.74 1999 5119.19 1313.12 4034.96 6213.24 84.27 10932 1390.58 561.03 2000 5492.08 1321.63 4551.15 6968.18 93.79 11718 1752.70 575.00 2001 5818.28 1327.14 4950.84 7656.96 111.06 12883 1995.62 575.00

8、2002 6118.53 1334.23 5408.76 8476.05 116.07 13250.17 2202.25 577.90 2003 6697.6 1341.77 6250.81 11266.62 131.37 14867.49 2828.87 578.50 以上所有數(shù)據(jù)的原始數(shù)據(jù)都得來源于上海統(tǒng)計(jì)局網(wǎng)站公布的上海2000-2004統(tǒng)計(jì)年鑒具體來源如下:能源消費(fèi)量Y來源于15.1 能源消耗基本情況(19852003,是指上海市全市對(duì)于所有能源的消費(fèi)量,主要包括煤、石油、天然氣等能源的總消費(fèi)量,衡量單位為萬噸標(biāo)準(zhǔn)煤。年末戶籍人口X 13.1 歷年戶數(shù)、人口及人口密度,指上海市年末以戶

9、籍衡量的人口數(shù)。GDP X22.1 歷年上海市生產(chǎn)總值,上海市各年的國(guó)內(nèi)生產(chǎn)總值。工業(yè)總產(chǎn)值X311.2 歷年工業(yè)總產(chǎn)值及指數(shù),上海市各年的工業(yè)生產(chǎn)總值。用于教育的財(cái)政支出X49.4 主要年份用于文教、衛(wèi)生、科學(xué)部門的財(cái)政支出,上海市財(cái)政支出中對(duì)教育的支出。人均可支配收入X54.16 城市居民家庭人均可支配收入(19852003,上海市居民人均可支配收入。全市財(cái)政收入X69.1 歷年財(cái)政收入,上海市全市財(cái)政收入數(shù)額居民消費(fèi)價(jià)格指數(shù)5.1 歷年居民消費(fèi)價(jià)格指數(shù),上海市歷年的以1952年價(jià)格為基期價(jià)格計(jì)算的居民消費(fèi)價(jià)格指數(shù)。下表為通過居民消費(fèi)價(jià)格指數(shù)(以1952年價(jià)格為基期調(diào)整為不變價(jià)格后的數(shù)據(jù):

10、年份能源消費(fèi)量(萬噸標(biāo)準(zhǔn)煤Y年末戶籍人口(萬人X1GDP(億元X2工業(yè)總產(chǎn)值X3用于教育的財(cái)政支出(億元X4人均可支配收入X5全市財(cái)政收入X62002 6118.53 1334.23 935.93 1466.7 20.0848 2292.81 381.08 20036697.61341.771080.5 1947.5622.70872570.01 489.00 以上數(shù)據(jù)除人口外都已換算為不變價(jià)計(jì)量的數(shù)據(jù)。Y 與X 的散點(diǎn)圖如下:2000300040005000600070001200125013001350X1Y 2000300040005000600070002004006008001000

11、1200X2Y20003000400050006000700050010001500 2000X32000300040005000600070005101520 25X4Y700060005000400030002000X5Y700060005000400030002000X6五、模型的估計(jì)和分析對(duì)上面六個(gè)解釋變量對(duì)被解釋變量Y的所有組合作最小二乘法回歸,結(jié)果如下:F-statistic 六元回歸 C -6219.0700 2975.2830 -2.090245 0.0585 518.8512 X1 6.0628 2.4225 2.502728 0.0278X2 3.3718 1.6646 2

12、.025537 0.0656X3 0.5673 0.4224 1.342969 0.2041X4 19.6407 53.0613 0.370151 0.7177X5 0.5486 0.3372 1.626708 0.1298X6 -3.6912 1.1815 -3.124087 0.0088五元回歸C -13262.2200 2511.9410 -5.279671 0.0001 370.8058X1 11.6964 2.0928 5.58893 0.0001X2 4.0102 2.1374 1.876252 0.0832X3 -0.2636 0.4246 -0.620829 0.5454X4

13、-65.6935 58.8543 -1.116205 0.2845X5 0.7741 0.4262 1.816386 0.0924C -7378.3360 3066.1210 -2.406407 0.0317 552.1712X1 7.0912 2.4822 2.856819 0.0135X2 4.3286 1.6529 2.61881 0.0212X3 0.6522 0.4449 1.465775 0.1665X4 29.3237 55.9652 0.523964 0.6091X6 -4.1027 1.2250 -3.349016 0.0052C -6692.1210 2596.1150 -

14、2.577745 0.0230 666.8629X1 6.4064 2.1620 2.963154 0.0110X2 3.8818 0.9024 4.301767 0.0009X3 0.4445 0.2527 1.759141 0.1021X5 0.5626 0.3238 1.737491 0.1059X6 -3.4661 0.9788 -3.54131 0.0036C -8575.5190 2475.9570 -3.463517 0.0042 586.0363X1 7.9110 2.0543 3.850938 0.0020X2 4.8336 1.2978 3.724631 0.0025X4

15、-36.3216 33.8491 -1.073044 0.3028X5 0.6045 0.3449 1.753058 0.1031X6 -2.6922 0.9459 -2.846185 0.0138C -4529.9180 3178.6360 -1.425114 0.1777 501.9880X1 4.8495 2.6124 1.856351 0.0862X3 1.1268 0.3557 3.167939 0.0074X4 108.6100 33.1317 3.278127 0.0060X5 0.7900 0.3511 2.249854 0.0424X6 -3.9850 1.3051 -3.0

16、53542 0.0092C 1214.5360 206.0175 5.895304 0.0001 442.2882X2 2.3417 1.9118 1.224844 0.2424X3 1.1679 0.4120 2.834352 0.0141X4 70.5278 58.0919 1.214073 0.2463X5 0.7689 0.3859 1.992483 0.0677X6 -5.8924 0.9351 -6.301145 0.0000四元回歸C -13064.4100 2527.5930 -5.168715 0.0001 455.2000X1 11.6965 2.1111 5.540497

17、 0.0001X2 1.8663 0.9458 1.973197 0.0686X3 0.0646 0.3090 0.208983 0.8375X5 0.7730 0.4299 1.79803 0.0938C -16137.7700 2104.3480 -7.668774 0.0000 397.4140X1 14.1460 1.7267 8.192333 0.0000X2 5.5306 2.1220 2.606302 0.0207X3 -0.2750 0.4581 -0.600435 0.5578X4 -65.4408 63.5034 -1.030509 0.3202C -8138.3520 2

18、630.3960 -3.093964 0.0079 727.8623X1 7.6504 2.1822 3.505864 0.0035X2 5.1368 0.5786 8.877735 0.0000X3 0.4698 0.2698 1.74097 0.1036X6 -3.7781 1.0292 -3.671045 0.0025C -12915.6700 2394.7740 -5.393273 0.0001 484.6877X1 11.4475 2.0084 5.699754 0.0001X2 3.0179 1.3874 2.175173 0.0472X4 -40.3923 41.5187 -0.

19、97287 0.3471X5 0.7781 0.4167 1.867248 0.0829C -10267.3300 2443.1370 -4.20252 0.0009 637.3884X1 9.3712 2.0121 4.657436 0.0004X2 6.1492 1.1345 5.420277 0.0001X4 -34.8555 36.2578 -0.96132 0.3527X6 -2.9853 0.9975 -2.9927 0.0097C -8754.1040 2483.6810 -3.524649 0.0034 724.4222X1 8.1834 2.0496 3.992741 0.0

20、013X2 3.8993 0.9675 4.0304 0.0012X5 0.5954 0.3466 1.717809 0.1079X6 -2.7350 0.9501 -2.878585 0.0121C -11899.4600 2612.1360 -4.555453 0.0004 392.0493X1 10.7728 2.2096 4.875501 0.0002X3 0.3322 0.3062 1.084858 0.2963X4 33.5393 28.0465 1.195847 0.2516X5 1.0873 0.4260 2.552367 0.0230C -5648.6810 3565.969

21、0 -1.584052 0.1355 485.3919X1 5.9751 2.9124 2.051648 0.0594X3 1.5277 0.3496 4.36936 0.0006X4 166.0875 23.9619 6.931324 0.0000X6 -4.7993 1.4242 -3.369815 0.0046C -8351.5920 3851.2580 -2.168536 0.0478 368.3625 X1 7.6617 3.2136 2.384129 0.0318X3 0.4565 0.3790 1.204306 0.2484X5 1.6775 0.2912 5.76121 0.0

22、000X6 -0.8105 1.1394 -0.71137 0.4885C 728.3924 370.6392 1.965233 0.0695 144.2209 X2 1.2004 3.6927 0.325087 0.7499X3 0.1911 0.7407 0.25802 0.8001X4 -65.6980 104.6171 -0.627984 0.5401X5 2.3091 0.5793 3.9859 0.0014C 1367.3460 210.5172 6.495174 0.0000 455.2830 X2 3.5179 2.0020 1.75722 0.1007X3 1.4487 0.

23、4263 3.398541 0.0043X4 98.0711 62.1204 1.578726 0.1367X6 -7.0727 0.7966 -8.878208 0.0000C 996.6806 102.9117 9.684815 0.0000 534.3994 X2 4.2427 1.1152 3.804343 0.0019X3 0.7943 0.2786 2.850558 0.0128X5 0.8803 0.3811 2.310078 0.0366X6 -5.4699 0.8825 -6.197946 0.0000C 939.7948 222.8231 4.217672 0.0009 3

24、66.6487 X2 5.8307 1.7929 3.25208 0.0058X4 -52.4270 47.3584 -1.107026 0.2869X5 1.1430 0.4444 2.57176 0.0222X6 -4.8953 1.0620 -4.609452 0.0004C 1363.6310 169.1538 8.061486 0.0000 533.4250 X3 1.4928 0.3208 4.652863 0.0004X4 128.8066 33.9183 3.797558 0.0020X5 0.9148 0.3735 2.449142 0.0281X6 -5.7839 0.94

25、74 -6.104941 0.0000C -10165.7200 3378.9490 -3.008545 0.0094 379.8284 X1 9.4376 2.7889 3.383946 0.0045X4 48.2687 34.7739 1.388072 0.1868X5 1.3473 0.3898 3.456313 0.0039X6 -0.9602 1.1412 -0.841433 0.4142三元回歸C -15936.5500 2099.5910 -7.59031 0.0000 527.3534X1 14.1425 1.7303 8.173454 0.0000X2 3.3927 0.44

26、70 7.589868 0.0000X3 0.0519 0.3311 0.15669 0.8776C -15791.3100 1980.0890 -7.975053 0.0000 553.3558X1 13.8991 1.6409 8.470249 0.0000X2 4.5029 1.2274 3.668559 0.0023X4 -39.0335 44.8213 -0.870869 0.3975C -13191.6500 2373.6670 -5.5575 0.0001 648.2479X1 11.8136 1.9693 5.998894 0.0000X2 1.9447 0.8400 2.31

27、5047 0.0352X5 0.7710 0.4159 1.853791 0.0835C -10414.2500 2432.1790 -4.281859 0.0007 853.8613X1 9.6115 1.9915 4.826394 0.0002X2 5.2329 0.6137 8.526367 0.0000X6 -3.0223 0.9943 -3.039662 0.0083C 1006.4510 513.8279 1.958732 0.0690 93.8516X2 5.9542 4.9331 1.206981 0.2461X3 0.6185 1.0346 0.59783 0.5589X4

28、-64.4138 147.6724 -0.436194 0.6689C 926.2613 191.1974 4.844529 0.0002 200.2482X2 -0.9436 1.3781 -0.684704 0.5040X3 0.5193 0.5142 1.009878 0.3286X5 2.3080 0.5675 4.066934 0.0010C 1078.8880 109.6362 9.840616 0.0000 551.3577X2 6.5715 0.5416 12.13437 0.0000X3 0.9581 0.3060 3.131508 0.0069X6 -6.7022 0.79

29、83 -8.396072 0.0000C -15812.7300 2473.2300 -6.393557 0.0000 380.6276X1 14.2557 2.0324 7.014217 0.0000X3 0.6879 0.3188 2.157475 0.0476X4 96.3698 15.7173 6.131443 0.0000C -10491.4900 2364.9290 -4.43628 0.0005 507.7000X1 9.4628 1.9462 4.862135 0.0002X3 0.3065 0.3098 0.989473 0.3381X5 1.5344 0.2070 7.41

30、1181 0.0000C -24804.0900 4583.2720 -5.411874 0.0001 152.5971 X1 21.3518 3.8375 5.563981 0.0001X3 0.6983 0.6681 1.045156 0.3125X6 3.7239 1.4613 2.548372 0.0223C -11926.1300 2627.3790 -4.539174 0.0004 516.2512 X1 10.8312 2.2219 4.874719 0.0002X4 31.4080 28.1421 1.11605 0.2820X5 1.2977 0.3815 3.401055

31、0.0039C -17279.0200 3524.5480 -4.902479 0.0002 290.4806 X1 15.7176 2.7827 5.648221 0.0000X4 130.2567 33.4413 3.89509 0.0014X6 -0.3637 1.4836 -0.245112 0.8097C -10477.0100 3474.0880 -3.01576 0.0087 476.3644 X1 9.4925 2.8735 3.303463 0.0048X5 1.7164 0.2937 5.84401 0.0000X6 -0.0474 0.9611 -0.049365 0.9

32、613C 691.7005 331.4527 2.086875 0.0544 205.0310 X2 1.9024 2.4180 0.786749 0.4437X4 -84.7426 71.7962 -1.180322 0.2563X5 2.3308 0.5551 4.198813 0.0008C 1085.8370 252.5881 4.298843 0.0006 354.1245 X2 9.2238 1.4232 6.481108 0.0000X4 -55.8362 55.4960 -1.00613 0.3303X6 -6.4788 1.0144 -6.386933 0.0000C 115

33、8.2060 104.3347 11.10087 0.0000 481.2219 X2 4.5115 1.3496 3.342807 0.0045X5 1.1568 0.4476 2.584413 0.0207X6 -5.0693 1.0582 -4.790633 0.0002C 810.1494 264.0181 3.068537 0.0078 204.4487 X3 0.3685 0.4857 0.75873 0.4598X4 -34.2531 38.6505 -0.886228 0.3895X5 2.3700 0.5317 4.457466 0.0005C 1663.1150 134.9

34、527 12.32369 0.0000 531.9707 X3 2.0769 0.2478 8.380618 0.0000X4 203.5353 17.1051 11.89913 0.0000X6 -7.2646 0.8423 -8.625244 0.0000C 826.4596 127.6843 6.47268 0.0000 372.8309 X3 0.8839 0.3825 2.310723 0.0355X5 2.1908 0.2246 9.756107 0.0000X6 -2.9507 0.8038 -3.670934 0.0023C 1248.8030 257.9816 4.84066

35、9 0.0002 296.2275 X4 49.9382 45.2915 1.102596 0.2876X5 2.2066 0.3852 5.728405 0.0000X6 -3.2536 1.1960 -2.720442 0.0158C 995.4189 118.0188 8.434408 0.0000 437.8304 X5 2.5937 0.1596 16.2564 0.0000X6 -2.3229 0.8529 -2.723402 0.0150C 2620.8990 165.6514 15.82178 0.0000 143.1977 X4 286.4097 32.2134 8.8910

36、18 0.0000X6 -5.8986 1.9072 -3.092772 0.0070C 857.0190 253.2630 3.383909 0.0038 314.7321 X4 -37.0270 37.9635 -0.975332 0.3439X5 2.6112 0.4205 6.210404 0.0000C 673.7650 332.5406 2.026114 0.0598 74.2999 X3 3.7817 0.6326 5.978105 0.0000X6 -0.9041 2.0362 -0.444007 0.6630X3 0.4092 0.4803 0.852088 0.4067 3

37、10.4442 X5 1.9757 0.2892 6.831677 0.0000C 1499.7470 315.8331 4.748543 0.0002 136.1616 X3 1.6632 0.5747 2.894052 0.0106X4 109.9018 31.2455 3.51737 0.0029C 1320.5090 96.9836 13.61579 0.0000 530.2730 X2 7.8613 0.4378 17.95507 0.0000X6 -6.6847 0.9939 -6.725533 0.0000C 1038.0730 155.9749 6.655384 0.0000

38、299.4907 X2 -0.5086 1.3099 -0.388239 0.7030X5 2.4233 0.5562 4.356546 0.0005C 893.7828 468.3203 1.908486 0.0744 146.4818 X2 8.4216 2.6472 3.181278 0.0058X4 -127.3237 101.5018 -1.254398 0.2277C -28686.0600 2693.0250 -10.65199 0.0000 227.0390 X1 24.6784 2.1500 11.47854 0.0000X6 5.0684 0.6952 7.290919 0

39、.0000C -10599.1900 2360.8760 -4.489514 0.0004 762.0579 X1 9.5942 1.9404 4.944364 0.0001X5 1.7032 0.1174 14.51139 0.0000C -17859.8000 2531.4350 -7.05521 0.0000 462.8829 X1 16.1681 2.0270 7.976162 0.0000X4 122.5518 11.0703 11.07031 0.0000C -18331.1700 4421.8270 -4.14561 0.0008 167.9699 X1 15.7852 3.65

40、70 4.316476 0.0005X3 2.1973 0.3673 5.981395 0.0000C -16032.7100 1945.7330 -8.23993 0.0000 842.3736X1 14.2315 1.5839 8.98536 0.0000X2 3.4525 0.2256 15.304 0.0000C 1200.3220 251.2173 4.778023 0.0002 148.1815X2 3.8497 1.0028 3.838944 0.0014X3 0.9401 0.7072 1.329238 0.2024 在所有通過t、F檢驗(yàn)的估計(jì)結(jié)果中,我認(rèn)為Y、X1、X2組合的

41、回歸方程具有最好的經(jīng)濟(jì)解釋,故選擇YX1 X2組合模型(上表中加的估計(jì)結(jié)果進(jìn)行分析。六、模型的估計(jì)和分析1、利用夸特法對(duì)YX1X2模型進(jìn)行異方差檢驗(yàn):(通過Eviews軟件首先按X1升序排列Y、X1、X2的數(shù)據(jù),去除中間3年(1993-1995的數(shù)據(jù),分別以1985-1992年數(shù)據(jù)和1996-2003年數(shù)據(jù)對(duì)YX1X2進(jìn)行最小二乘法回歸,得到1985-1992年數(shù)據(jù)回歸的離差平方和ie為30263.58,1996-2003年數(shù)據(jù)的離差平方和i e為10941.56,則: ii30263.588215F10941.565821ee=-大小(+(+-2.765935.05=(0.05F5,5因此,

42、認(rèn)為本模型沒有異方差性。2、自相關(guān)性檢驗(yàn):由于YX1X2模型的最小二乘估計(jì)結(jié)果中:Durbin-Watson stat = 0.5139170.05(顯著性水平,因此模型還需調(diào)整。對(duì)模型進(jìn)行二階廣義差分回歸,結(jié)果如下:VariableCoefficient Std. Error t-Statistic Prob. C -12216.86 1405.631 -8.691373 0.0000 X1 11.26357 1.112390 10.12556 0.0000 X2 3.547767 0.330678 10.72877 0.0000 AR(1 1.058217 0.263407 4.017422 0.0017 AR(2-0.3519130.272399-1.2919030.2207 R-squared0.996202 Mean dependent var 4376.651 Adjusted R-squared 0.994935 S.D. dependent var 1235.339 S.E. of regr