/* Using Dummy Variables to model seasonality in the data. */ options pagesize=60 linesize=74 nodate; goptions device=win rotate=landscape border; OPTIONS PAGESIZE=60 LINESIZE=74 NODATE; DATA SALES; INPUT year 2. month 2. SALES BCI67NS JQINDNS JQIND RMMTGNS EEANS EEA HUSTSNS HUSTS; /* BCI67NS = Building and Construction Cost Index (1967 = 100, NSA) JQINDNS = Industrial Production Index (NSA) JQIND = Industrial Production Index (SA) RMMTGNS = 30 yr. mortgage interest rate (NSA) EEANS = Nonagricultral Employment (NSA) EEA = Nonagricultral Employment (SA) HUSTSNS = Housing Unit Starts (NSA) HUSTS = Housing Unit Starts (SA) */ date = mdy(month,1,year); cards; 7902 7245 2.576 0.82922 0.8214 10.41 87.751 88.985 84.5 1.52 7903 8555 2.59 0.83144 0.82368 10.43 88.654 89.426 152.9 1.847 7904 8041 2.593 0.81191 0.81597 10.5 89.193 89.363 161 1.748 7905 9180 2.5986 0.81915 0.82539 10.69 90.012 89.681 189.1 1.876 7906 8696 2.6751 0.83911 0.82559 11.04 90.857 89.955 191.8 1.913 7907 7309 2.704 0.79722 0.8196 11.09 89.869 90.019 164.2 1.76 7908 10084 2.7393 0.81735 0.8163 11.09 89.969 90.159 170.3 1.778 7909 7439 2.799 0.83455 0.81689 11.3 90.521 90.149 163.7 1.832 7910 8990 2.811 0.83455 0.8203 11.64 91 90.36 169 1.681 7911 6781 2.815 0.81779 0.81623 12.83 91.204 90.466 118.7 1.524 7912 4914 2.826 0.80102 0.8145 12.9 91.335 90.617 91.6 1.498 8001 8220 2.809 0.80114 0.8183 12.88 89.553 90.729 73.1 1.341 8002 6642 2.807 0.82581 0.81892 13.04 89.691 90.876 79.9 1.35 8003 5832 2.839 0.8263 0.81868 15.28 90.253 90.995 85.1 1.047 8004 5310 2.826 0.79611 0.80271 16.32 90.603 90.78 96.2 1.051 8005 5497 2.799 0.77357 0.78283 14.26 90.623 90.316 91.7 0.927 8006 6633 2.841 0.78257 0.77291 12.71 90.778 89.974 116.4 1.196 8007 7264 2.891 0.75102 0.76795 12.19 89.436 89.676 120.1 1.269 8008 7033 2.921 0.78279 0.77696 12.56 89.723 89.964 129.9 1.436 8009 6443 2.924 0.8056 0.78846 13.2 90.39 90.046 138.3 1.471 8010 7150 2.925 0.80701 0.79413 13.7 90.985 90.334 152.7 1.523 8011 6136 2.96 0.8084 0.80695 14.21 91.329 90.55 112.9 1.51 8012 5830 2.986 0.79943 0.81095 14.79 91.513 90.774 95.9 1.482 8101 6384 2.982 0.79158 0.80396 14.9 89.688 91.003 84.5 1.547 8102 6702 2.984 0.81487 0.80781 15.13 89.833 91.095 71.9 1.246 8103 8048 2.9805 0.8169 0.81147 15.4 90.368 91.206 107.8 1.306 8104 9013 3.055 0.79806 0.80604 15.58 91.025 91.219 123 1.36 8105 7510 3.073 0.8027 0.81279 16.4 91.512 91.142 109.9 1.14 8106 7268 3.083 0.82721 0.81789 16.7 92.154 91.285 105.8 1.045 8107 6509 3.121 0.80727 0.82513 16.83 91.23 91.41 99.9 1.041 8108 7137 3.135 0.82771 0.82144 17.28 91.232 91.32 86.3 0.94 8109 6553 3.166 0.83095 0.81478 18.16 91.731 91.191 84.1 0.911 8110 7030 3.1912 0.82105 0.80857 18.46 91.905 91.216 87.2 0.873 8111 5738 3.236 0.7983 0.79726 17.82 91.738 91.014 64.6 0.837 8112 5187 3.2329 0.77884 0.78831 16.95 91.403 90.831 59.1 0.91 8201 5413 3.233 0.76797 0.77562 17.48 89.173 90.448 47.2 0.843 8202 5367 3.254 0.80085 0.79235 17.6 89.259 90.474 51.3 0.866 8203 6947 3.244 0.78977 0.78681 17.16 89.55 90.337 78.2 0.931 8204 6001 3.251 0.76972 0.77938 16.89 89.861 90.031 84.1 0.917 8205 5975 3.255 0.76125 0.77341 16.68 90.343 89.965 98.8 1.025 8206 6212 3.294 0.77837 0.77083 16.7 90.531 89.703 91.1 0.902 8207 5782 3.3425 0.74958 0.7645 16.82 89.197 89.38 106.8 1.166 8208 6733 3.343 0.76848 0.76046 16.27 89.069 89.177 96 1.046 8209 7322 3.35 0.77091 0.75488 15.43 89.489 88.995 106.4 1.144 8210 6705 3.348 0.75948 0.74863 14.61 89.455 88.787 110.5 1.173 8211 6339 3.356 0.74741 0.74664 13.82 89.351 88.649 108.9 1.372 8212 6215 3.4 0.73024 0.7405 13.62 89.25 88.675 82.9 1.303 8301 8003 3.4201 0.74752 0.75628 13.25 87.58 88.826 91.3 1.586 8302 6541 3.475 0.76167 0.75453 13.04 87.59 88.758 96.3 1.699 8303 8690 3.481 0.76346 0.76204 12.8 88.192 88.946 134.6 1.606 8304 8486 3.474 0.76242 0.77159 12.78 89.051 89.211 135.8 1.472 8305 8401 3.479 0.76958 0.78089 12.63 89.881 89.497 174.9 1.776 8306 8953 3.535 0.7921 0.78529 12.87 90.703 89.886 173.2 1.733 8307 7107 3.573 0.78339 0.79922 13.43 90.13 90.313 161.6 1.785 8308 8940 3.594 0.81819 0.80995 13.81 89.856 89.973 176.8 1.91 8309 8791 3.597 0.84292 0.82377 13.73 91.578 91.088 154.9 1.71 8310 9044 3.576 0.84205 0.83027 13.54 92.09 91.408 159.3 1.715 8311 8091 3.583 0.82933 0.82945 13.44 92.448 91.727 136 1.785 8312 7268 3.561 0.82435 0.83369 13.42 92.719 92.11 108.3 1.688 8401 8564 3.555 0.84345 0.85102 13.37 91.229 92.524 109.1 1.897 8402 9373 3.562 0.85797 0.84968 13.23 91.795 93.043 130 2.26 8403 9545 3.571 0.86126 0.85906 13.39 92.511 93.312 137.5 1.663 8404 8482 3.585 0.85361 0.86362 13.65 93.472 93.65 172.7 1.851 8405 9341 3.581 0.8541 0.86859 13.94 94.349 93.952 180.7 1.774 8406 8895 3.578 0.88148 0.87251 14.42 95.163 94.325 184 1.843 8407 7514 3.579 0.85808 0.87426 14.67 94.466 94.647 162.1 1.732 8408 10716 3.593 0.88437 0.87415 14.47 94.748 94.885 147.4 1.586 8409 10322 3.597 0.8932 0.87294 14.35 95.672 95.186 148.5 1.698 8410 9869 3.587 0.88068 0.86885 14.13 96.226 95.499 152.3 1.59 8411 9311 3.583 0.86952 0.86956 13.64 96.601 95.829 126.2 1.689 8412 7653 3.562 0.85216 0.86567 13.18 96.658 95.997 98.9 1.612 8501 9486 3.566 0.86073 0.86871 13.08 94.917 96.249 105.4 1.711 8502 8655 3.573 0.88957 0.87618 12.92 95.126 96.397 95.4 1.632 8503 10036 3.528 0.87923 0.8784 13.17 95.92 96.734 145 1.8 8504 9829 3.542 0.8685 0.87982 13.2 96.728 96.896 175.8 1.821 8505 9862 3.5516 0.86637 0.88183 12.91 97.579 97.163 170.2 1.68 8506 10542 3.5928 0.88993 0.87967 12.22 98.128 97.28 163.2 1.676 8507 9900 3.6216 0.85932 0.87583 12.03 97.266 97.465 160.7 1.684 8508 11104 3.6055 0.89214 0.88107 12.19 97.516 97.696 160.7 1.743 8509 10971 3.595 0.90669 0.88638 12.19 98.329 97.878 147.7 1.676 8510 12447 3.5983 0.8886 0.87872 12.14 98.837 98.098 173 1.834 8511 10244 3.6051 0.88118 0.88375 11.78 99.091 98.286 124.1 1.698 8512 8688 3.5949 0.87801 0.8899 11.26 99.205 98.5 120.5 1.942 8601 11088 3.5951 0.88831 0.89612 10.89 97.247 98.599 115.6 1.972 8602 10614 3.6202 0.89826 0.88972 10.71 97.438 98.718 107.2 1.848 8603 12223 3.6227 0.87955 0.88076 10.08 97.987 98.796 151 1.876 8604 12404 3.6384 0.87658 0.88749 9.94 98.822 98.974 188.2 1.933 8605 12454 3.6748 0.87054 0.88551 10.15 99.513 99.096 186.6 1.854 8606 11810 3.6842 0.89592 0.88247 10.69 99.819 98.973 183.6 1.847 8607 11255 3.6928 0.87023 0.88534 10.51 99.064 99.276 172 1.782 8608 12584 3.6884 0.90201 0.88783 10.2 99.236 99.435 163.8 1.807 8609 12734 3.6995 0.90818 0.887 10.01 100.16 99.747 154 1.687 8610 14717 3.7136 0.90621 0.89499 9.98 100.726 99.98 154.8 1.681 8611 11189 3.7134 0.89598 0.89942 9.7 100.983 100.145 115.6 1.623 8612 12179 3.7147 0.89262 0.90772 9.32 101.138 100.394 113 1.833 8701 12411 3.7163 0.89184 0.90196 9.2 99.173 100.543 105.1 1.774 8702 12271 3.7086 0.91768 0.9124 9.08 99.494 100.772 102.8 1.784 8703 14588 3.7196 0.91665 0.91583 9.04 100.202 101.005 141.2 1.726 8704 13555 3.7276 0.90631 0.91958 9.83 101.213 101.367 159.3 1.614 8705 14112 3.7293 0.91115 0.92361 10.6 101.98 101.564 158 1.628 8706 15916 3.7295 0.94823 0.93159 10.54 102.584 101.713 162.9 1.594 8707 14533 3.7572 0.92041 0.93721 10.28 101.831 102.047 152.4 1.575 8708 15846 3.7757 0.95582 0.93828 10.33 102.061 102.266 143.6 1.605 8709 16780 3.7802 0.95986 0.93743 10.89 102.83 102.43 152 1.695 8710 17325 3.8023 0.96303 0.95014 11.26 103.736 102.98 139.1 1.515 8711 14290 3.7956 0.94805 0.9529 10.65 104.074 103.2 118.8 1.656 8712 12248 3.8319 0.94045 0.95855 10.64 104.313 103.544 85.4 1.4 8801 15043 3.8103 0.95046 0.95926 10.38 102.22 103.623 78.2 1.271 8802 15163 3.8128 0.96571 0.96243 9.89 102.791 104.046 90.2 1.473 8803 18117 3.8272 0.96232 0.96259 9.93 103.535 104.311 128.8 1.532 8804 15912 3.835 0.95742 0.96816 10.2 104.427 104.537 153.2 1.573 8805 17345 3.8365 0.95661 0.96891 10.46 105.181 104.811 140.2 1.421 8806 19185 3.8405 0.98611 0.9696 10.46 106.039 105.132 150.2 1.478 8807 13017 3.8462 0.9584 0.97593 10.43 105.143 105.4 137 1.467 8808 16780 3.8654 0.99861 0.98117 10.6 105.304 105.599 136.8 1.493 8809 16393 3.866 1.00059 0.97766 10.48 106.165 105.814 131.1 1.492 8810 16279 3.8663 0.99402 0.98035 10.3 106.838 106.091 135.1 1.522 8811 14904 3.8723 0.98238 0.98771 10.27 107.319 106.368 113 1.569 8812 15334 3.8732 0.97392 0.99275 10.61 107.541 106.691 94.2 1.563 8901 16070 3.877 0.98613 0.99827 10.73 105.56 106.993 100.1 1.621 8902 14492 3.8681 0.99183 0.99038 10.65 105.983 107.244 85.8 1.425 8903 20971 3.8726 0.99159 0.99968 11.03 106.624 107.438 117.8 1.422 8904 16751 3.8774 0.99553 1.00213 11.05 107.427 107.637 129.4 1.339 8905 17452 3.8796 0.98261 0.99583 10.77 108.114 107.738 131.7 1.331 8906 18900 3.8873 1.01146 0.99407 10.2 108.764 107.838 143.2 1.397 8907 14618 3.8938 0.96633 0.98424 9.88 107.682 107.933 134.7 1.427 8908 19122 3.9058 1.00828 0.98824 9.99 107.767 108.048 122.4 1.332 8909 18985 3.949 1.00972 0.98623 10.13 108.571 108.178 109.3 1.279 8910 16831 3.9545 0.99688 0.98171 9.95 109.07 108.29 130.1 1.41 8911 16587 3.9581 0.98173 0.9856 9.77 109.515 108.571 96.6 1.351 8912 15622 3.966 0.9746 0.99032 9.74 109.53 108.692 75 1.251 9001 15888 3.9566 0.97531 0.98572 9.9 107.448 108.946 99.2 1.551 9002 16051 3.9497 0.99033 0.99081 10.2 107.951 109.263 86.9 1.437 9003 19923 3.9564 0.99295 0.99559 10.27 108.606 109.461 108.5 1.289 9004 16351 3.9604 0.97145 0.98959 10.37 109.251 109.499 119 1.248 9005 18713 3.9831 0.98155 0.9935 10.48 110.181 109.79 121.1 1.212 9006 18470 4.0193 1.01187 0.9933 10.16 110.835 109.869 117.8 1.177 9007 15409 4.02 0.97575 0.99284 10.04 109.461 109.707 111.2 1.171 9008 19165 4.0197 1.01552 0.99477 10.1 109.302 109.543 102.8 1.115 9009 18732 4.0407 1.02169 0.99613 10.18 109.88 109.457 93.1 1.11 9010 17134 4.0378 1.00772 0.99064 10.17 110.087 109.274 94.2 1.014 9011 15184 4.0407 0.97404 0.97748 10.01 110.045 109.074 81.4 1.145 9012 14167 4.0255 0.9539 0.97171 9.67 109.785 108.965 57.4 0.969 9101 14300 4.0266 0.95857 0.96693 9.64 107.264 108.759 52.5 0.798 9102 15077 4.0214 0.95751 0.95929 9.37 107.227 108.5 59.1 0.965 9103 18673 4.0203 0.9434 0.95046 9.5 107.507 108.33 73.8 0.921 9104 17090 4.0101 0.94443 0.95379 9.5 107.91 108.145 99.7 1.001 9105 16434 4.0307 0.94899 0.9612 9.47 108.597 108.107 97.7 0.996 9106 17914 4.046 0.98857 0.97244 9.62 109.085 108.2 103.4 1.036 9107 13795 4.0811 0.9581 0.97321 9.58 107.847 108.131 103.5 1.063 9108 17253 4.1327 0.99663 0.97445 9.24 107.936 108.215 94.7 1.049 9109 17972 4.123 1.00845 0.98375 9.01 108.65 108.223 86.6 1.015 9110 18613 4.1232 0.99734 0.9828 8.86 109.018 108.209 101.8 1.079 9111 16561 4.1319 0.97605 0.98143 8.71 109.039 108.115 75.6 1.103 9112 16052 4.1212 0.95682 0.9751 8.5 108.912 108.121 65.6 1.079 9201 19089 4.1204 0.96537 0.97559 8.43 106.516 108.084 71.6 1.176 9202 16336 4.1081 0.98 0.98144 8.76 106.776 108.077 78.8 1.25 9203 19392 4.1435 0.98618 0.98907 8.94 107.3 108.119 111.6 1.297 9204 18387 4.1585 0.9815 0.99654 8.85 108.144 108.301 107.6 1.099 9205 16487 4.1856 0.9878 0.9989 8.67 108.953 108.495 115.2 1.214 9206 18518 4.2 1.01607 0.9974 8.51 109.444 108.541 117.8 1.145 9207 17279 4.2112 0.98481 1.00474 8.13 108.412 108.595 106.2 1.139 9208 20108 4.224 1.02455 1.0021 7.98 108.461 108.741 109.9 1.226 9209 21074 4.2282 1.03123 1.0069 7.92 109.245 108.807 106 1.186 9210 19537 4.2444 1.02923 1.01236 8.09 109.828 108.941 111.8 1.244 9211 17435 4.2524 1.01314 1.01763 8.31 110.072 109.119 84.5 1.214 9212 18931 4.2553 1.00013 1.01734 8.21 110.064 109.266 78.6 1.227 9301 20588 4.2724 1.00823 1.02123 7.99 107.883 109.502 70.5 1.21 9302 20909 4.2713 1.0251 1.02581 7.68 108.496 109.816 74.6 1.21 9303 24914 4.3149 1.02997 1.02815 7.5 108.935 109.749 95.5 1.083 9304 20487 4.4045 1.01739 1.03176 7.46 109.927 110.055 117.8 1.258 9305 20967 4.5455 1.01505 1.02695 7.47 110.885 110.398 120.9 1.26 9306 24292 4.5385 1.04882 1.03011 7.42 111.476 110.539 128.5 1.28 9307 17770 4.4964 1.01186 1.03111 7.21 110.604 110.744 115.3 1.254 9308 22893 4.4609 1.05145 1.0286 7.11 110.713 110.957 121.8 1.3 9309 26245 4.4541 1.06623 1.03973 6.91 111.69 111.204 118.5 1.343 9310 21914 4.664 1.05996 1.04455 6.83 112.371 111.525 123.2 1.392 9311 20650 4.4828 1.04311 1.04865 7.16 112.716 111.78 102.3 1.376 9312 24229 4.5079 1.03594 1.05648 7.17 112.86 112.034 98.7 1.533 9401 19583 4.5458 1.04591 1.05877 7.07 110.586 112.302 76.2 1.272 9402 23451 4.597 1.06087 1.06058 7.15 111.17 112.532 83.5 1.337 9403 26614 4.6119 1.07327 1.06991 7.68 112.141 112.982 134.3 1.564 9404 22476 4.6288 1.0628 1.07581 8.32 113.22 113.35 137.6 1.465 9405 23673 4.6253 1.07106 1.08485 8.6 114.235 113.697 148.8 1.526 9406 31523 4.6111 1.1114 1.09158 8.4 115.04 113.98 136.4 1.409 9407 20989 4.5995 1.06758 1.09519 8.61 114.116 114.333 127.8 1.439 9408 28404 4.6025 1.12345 1.10085 8.51 114.42 114.673 139.8 1.45 9409 30476 4.6125 1.13498 1.10316 8.64 115.472 114.98 130.1 1.474 9410 27360 4.6118 1.12531 1.10946 8.93 116.097 115.235 130.6 1.45 9411 25830 4.602 1.10954 1.11633 9.17 116.717 115.641 113.4 1.511 9412 27310 4.6034 1.10722 1.1269 9.2 116.747 115.918 98.5 1.455 9501 25352 4.6061 1.11657 1.13343 9.15 114.435 116.259 84.5 1.407 9502 25264 4.6055 1.13039 1.13181 8.83 115.093 116.521 81.6 1.316 9503 30237 4.5928 1.13951 1.1344 8.46 115.849 116.687 103.8 1.249 9504 24451 4.5889 1.10997 1.13301 8.32 116.674 116.864 116.9 1.267 9505 26552 4.5832 1.12079 1.13767 7.96 117.409 116.841 130.5 1.314 9506 31398 4.5812 1.16515 1.14284 7.57 118.138 117.05 123.4 1.281 9507 22210 4.6093 1.11331 1.1381 7.61 116.926 117.137 129.1 1.461 9508 29447 4.6193 1.17667 1.15135 7.86 117.18 117.449 135.8 1.416 9509 31890 4.602 1.1924 1.15627 7.64 118.083 117.648 122.4 1.369 9510 27727 4.6142 1.17202 1.15472 7.48 118.665 117.784 126.2 1.369 9511 27817 4.6344 1.15285 1.15801 7.38 118.917 117.942 107.2 1.452 9512 27867 4.6297 1.14051 1.15855 7.2 118.918 118.087 92.8 1.431 9601 24538 4.6282 1.13974 1.15557 7.03 116.21 118.08 90.7 1.467 9602 26188 4.6342 1.16711 1.16903 7.08 117.146 118.534 95.9 1.491 9603 32246 4.6411 1.17039 1.16612 7.62 117.952 118.795 116 1.424 9604 27460 4.66 1.1612 1.17958 7.93 118.779 118.958 146.6 1.516 9605 28808 4.6785 1.17076 1.18976 8.07 119.922 119.288 143.9 1.504 9606 34649 4.7039 1.22175 1.19821 8.32 120.589 119.535 138 1.467 9607 25312 4.7221 1.16995 1.1991 8.25 119.558 119.742 137.5 1.472 9608 33873 4.7629 1.23341 1.20698 8 119.829 120.02 144.2 1.557 9609 36855 4.8053 1.25157 1.21247 8.23 120.569 120.172 128.7 1.475 9610 32274 4.8814 1.23038 1.21181 7.92 121.287 120.413 130.8 1.392 9611 31125 4.8905 1.2153 1.22072 7.62 121.74 120.698 111.5 1.489 9612 34137 4.9012 1.20189 1.22409 7.6 121.716 120.893 93.1 1.37 9701 31489 4.9324 1.20912 1.22966 7.82 119.166 121.131 82.2 1.373 9702 30233 4.9336 1.23477 1.2403 7.65 120.017 121.427 94.7 1.532 9703 36046 4.9183 1.2422 1.24507 7.9 120.903 121.782 120.4 1.471 9704 34225 4.9795 1.24389 1.25236 8.14 121.879 122.065 142.3 1.487 9705 31547 4.9988 1.23998 1.25788 7.94 122.97 122.292 136.3 1.429 9706 40775 5.0269 1.28933 1.26557 7.69 123.615 122.524 140.4 1.502 9707 29249 5.0206 1.25002 1.27171 7.5 122.662 122.822 134.6 1.437 9708 34212 5.0104 1.31044 1.27988 7.48 122.714 122.894 126.5 1.399 9709 40392 5.0007 1.32955 1.28807 7.43 123.703 123.302 139.2 1.534 9710 36934 4.9916 1.31919 1.29609 7.29 124.575 123.626 139 1.519 9711 31837 4.9586 1.29574 1.30173 7.21 124.969 123.949 112.4 1.502 9712 39679 4.9881 1.28331 1.30598 7.1 125.103 124.263 106 1.525 9801 33348 4.9785 1.28287 1.30872 6.99 122.554 124.58 91.2 1.527 9802 33016 4.9917 1.29958 1.30738 7.04 123.335 124.773 101.1 1.644 9803 39423 4.9853 1.31328 1.31082 7.13 124.05 124.961 132.6 1.583 9804 33029 4.9961 1.29295 1.31654 7.14 125.082 125.22 144.9 1.542 9805 34957 4.9941 1.30624 1.32434 7.14 126.139 125.478 143.3 1.541 9806 43540 5.0013 1.33841 1.31481 7 126.804 125.689 159.6 1.626 9807 27026 5.0044 1.29689 1.31291 6.95 125.762 125.808 156 1.719 9808 40268 5.0198 1.36996 1.33593 6.92 125.966 126.17 147.5 1.615 9809 47153 5.054 1.37533 1.33548 6.72 126.769 126.361 141.5 1.576 9810 38514 5.0663 1.36678 1.34108 6.71 127.523 126.567 155.5 1.698 9811 35689 5.0684 1.33022 1.33777 6.87 127.902 126.841 124.2 1.654 9812 43008 5.0611 1.3142 1.33801 6.74 128.028 127.186 119.6 1.75 9901 33841 5.0693 1.31547 1.34052 6.79 125.291 127.378 108 1.82 9902 38418 5.0581 1.33659 1.34509 6.81 126.229 127.73 112.2 1.752 9903 51985 5.0487 1.35439 1.35147 7.04 126.867 127.813 149.3 1.746 9904 41449 5.0641 1.33872 1.35472 6.92 127.99 128.134 146.5 1.577 9905 44073 5.0648 1.34316 1.36215 7.15 128.85 128.162 155.6 1.668 9906 56530 5.0813 1.39432 1.36639 7.55 129.593 128.443 152.4 1.607 9907 33963 5.1213 1.35056 1.37363 7.63 128.802 128.816 155.2 1.68 9908 45210 5.1429 1.41556 1.37736 7.97 128.753 128.945 155 1.655 9909 55389 5.186 1.4215 1.37974 7.82 129.451 129.048 143.3 1.637 9910 42409 5.1875 1.41909 1.39126 7.85 130.19 129.311 145 1.637 ; PROC GPLOT DATA=SALES; Title height=1 'SALES: 1979:2 - 1999:10'; axis2 LABEL=(F=DUPLEX 'SALES'); AXIS1 label=(f=duplex 'Date'); SYMBOL1 i=join; PLOT SALES*DATE=1/vaxis=axis2 haxis=axis1; format date monyy5.; run; proc arima data=sales; identify var=sales nlag=24; identify var=sales(1) nlag=24; run; DATA SALES; SET SALES; Lsales=log(sales); rmmtgns = rmmtgns/100; t = _n_; if month = 1 then d1 = 1; else d1 = 0; if month = 2 then d2 = 1; else d2 = 0; if month = 3 then d3 = 1; else d3 = 0; if month = 4 then d4 = 1; else d4 = 0; if month = 5 then d5 = 1; else d5 = 0; if month = 6 then d6 = 1; else d6 = 0; if month = 7 then d7 = 1; else d7 = 0; if month = 8 then d8 = 1; else d8 = 0; if month = 9 then d9 = 1; else d9 = 0; if month = 10 then d10 = 1; else d10 = 0; if month = 11 then d11 = 1; else d11 = 0; if month = 12 then d12 = 1; else d12 = 0; run; DATA SALES; SET SALES; rmmt1 = lag(rmmtgns); rmmt2 = lag2(rmmtgns); rmmt3 = lag3(rmmtgns); rmmt4 = lag4(rmmtgns); rmmt5 = lag5(rmmtgns); rmmt6 = lag6(rmmtgns); ljqind = log(jqindns); ljqind1 = lag(ljqind); ljqind2 = lag2(ljqind); ljqind3 = lag3(ljqind); ljqind4 = lag4(ljqind); ljqind5 = lag5(ljqind); ljqind6 = lag6(ljqind); lbci = log(bci67ns); lbci1 = lag(lbci); lbci2 = lag2(lbci); lbci3 = lag3(lbci); lbci4 = lag4(lbci); lbci5 = lag5(lbci); lbci6 = lag6(lbci); lhusts = log(hustsns); lhusts1 = lag(lhusts); lhusts2 = lag2(lhusts); lhusts3 = lag3(lhusts); lhusts4 = lag4(lhusts); lhusts5 = lag5(lhusts); lhusts6 = lag6(lhusts); PROC GPLOT DATA=SALES; Title height=1 ' LOG SALES: 1979:2 - 1999:10'; axis2 LABEL=(F=DUPLEX 'Log(Sales)'); AXIS1 label=(f=duplex 'Date'); SYMBOL1 i=join; PLOT Lsales*DATE=1/vaxis=axis2 haxis=axis1; format date monyy5.; run; /* Here we test for the presence of seasonality in the log of oak flooring by three equivalent dummy variable representations, first using OLS and then GLS. */ /* First Parametrization */ proc autoreg data=sales; model lsales = t d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12/ nlag=4 dw=1 method=ml; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; /* Second Parametrization */ proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 / nlag=4 dw=1 method=ml noint; test d1 - d2, d2 - d3, d3 - d4, d4 - d5, d5 - d6, d6 - d7, d7 - d8, d8 - d9, d9 - d10, d10 - d11, d11 - d12; /* Third Parametrization */ proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 / nlag=4 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; /* Now let's run some regressions with ONE causal variable (and possibly) a few lags to see what causal variables (or their lags) are important. */ /* First let's try the interest rate variable and its lags. */ proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns rmmt1 rmmt2 rmmt3 rmmt4 rmmt5 rmmt6/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; /* It appears that the contemporaneous value to the interest rate is the only value that is statistically significant. */ /* Now let's investigate the importance of the macroeconomy as proxied by the industrial production index */ proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind / nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind ljqind1 ljqind2 ljqind3 ljqind4 ljqind5 ljqind6 / nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; /* The contemporaneous value of industrial production is significant and carries the expected positive sign. The other lags are either insignificant are of the wrong sign. */ /* Let's now entertain, in addition to our previously chosen variables, housing starts both contemporaneous and lagged values. */ proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind lhusts/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind lhusts lhusts1 lhusts2 lhusts3 lhusts4 lhusts5 lhusts6/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; /* Let's now add the cost index and some of its lags. */ proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind lhusts lbci/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind lhusts lbci lbci1 lbci2 lbci3 lbci4 lbci5 lbci6/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind lhusts lbci3 lbci4/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; test lbci3 + lbci4; /* It looks like that it is the CHANGE in the inflation of costs (lagged 3 periods) that is important. */ data sales; set sales; infl3 = lbci3 - lbci4; proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind lhusts infl3/ nlag=1 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; /* Let's try an overfit to AR=2 error before choosing our final model. */ proc autoreg data=sales; model lsales = t d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 rmmtgns ljqind lhusts infl3/ nlag=2 dw=1 method=ml; restrict d1 + d2 + d3 + d4 + d5 + d6 + d7 + d8 + d9 + d10 + d11 + d12; test d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12; data sales; set sales; dsales12 = lsales - lag12(lsales); drmmt12 = rmmtgns - lag12(rmmtgns); dind12 = ljqind - lag12(ljqind); dhusts12 = lhusts - lag12(lhusts); dinfl3 = infl3 - lag12(infl3); proc means data=sales; var dsales12 drmmt12 dind12 dhusts12 dinfl3; run;