Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float YEAR int(id1 AREA1 AREA2) long AREA3 float AREA4 int YIELD1 float(YIELD2 YIELD3 YIELD4) 1980 407 762 500 332 1.9 368 5.3 0 .1 1981 407 569 500 379 2 450 5.1 0 .1 1982 407 582 1000 389 1.8 389 4.7 0 .1 1983 407 516 0 365 2 450 6.1 0 .1 1984 407 491 1000 483 2.2 455 4.5 0 .2 1985 407 533 1000 433 2.3 304 4.7 0 .2 1986 407 649 0 561 2.2 318 4.6 0 .2 1987 407 535 0 459 2.3 522 4.7 0 .3 1988 407 462 0 481 2.5 560 4.7 0 .4 1989 407 518 0 506 2.6 538 5.4 0 .6 1990 407 685 1000 512 2.75 575 6.47 0 .56 1991 407 621 0 646 2.03 576 7.36 0 .86 1992 407 365 0 563 3.16 601 7.37 0 .67 1993 407 704 0 628 3.13 505 8.44 .01 .84 1994 407 805 0 654 2.9 621 9.52 0 1.1 1995 407 714 1000 494 2.7 481 9.214 .006 1.079 1996 407 804 0 664 2.4 500 9.169 0 1.08 1997 407 514 0 440 2.6 385 8.429 .001 .815 1998 407 622 0 591 4.33 474 8.546 .002 .783 1999 407 0 0 670 1.07 826 9.399 .005 1.125 2000 407 588 0 507 2.59 251 11.681 .001 2.782 2001 407 702 1000 736 2.59 324 13.867 .005 5.194 2002 407 754 1000 638 2.8 303 14.021 .001 9.295 2003 407 779 667 981 2.96 374 15.507 .004 13.12 2004 407 636 1000 501 3.57 341 15.439 0 23.961 2005 407 636 1000 501 3.57 341 15.462 .001 30.107 2006 407 723 0 724 4.29 294 15.957 .043 37.183 2007 407 921 1167 910 3.25 375 18.614 .032 48.909 2008 407 855 1000 857 3.63 340 20.257 .035 61.332 2009 407 898 167 883 3.7 428 24.512 .04 63.689 2010 407 995 778 949 6.09 356 27.677 0 73.916 2011 407 1116 1133 1008 3.84 419 28.441 .101 79.584 2012 407 1087 579 1131 3.77 435 28.285 .147 91.007 2013 407 1043 545 756 3.57 469 26.278 .128 109.003 2014 407 1151 786 1056 3.73 473 28.757 .114 103.116 2015 407 1121 750 755 4.88 494 32.698 .031 106.764 1980 270 1069 0 333 16.7 479 .9 0 0 1981 270 1100 1000 400 14.8 473 .9 0 0 1982 270 1219 1000 435 14.9 423 .7 0 0 1983 270 931 0 409 16.2 469 .7 0 0 1984 270 1071 0 417 16.5 455 .5 0 0 1985 270 1000 0 435 16.5 406 .6 0 0 1986 270 1000 0 333 16.4 366 .6 0 0 1987 270 667 0 333 16.6 560 .7 0 0 1988 270 1071 0 407 16.9 586 .8 0 0 1989 270 1038 0 417 15.9 560 .7 0 0 1990 270 1200 0 474 15.3 639 .68 0 .04 1991 270 1364 0 588 15.26 689 1.03 0 .03 1992 270 1250 0 471 11.99 531 .81 0 .13 1993 270 1444 0 550 12.77 509 .95 0 .08 1994 270 1500 0 632 12.4 573 .85 0 .1 1995 270 1562 0 550 11.7 573 .959 0 .075 1996 270 1650 0 600 11.4 640 .828 0 .075 1997 270 1571 0 643 10.3 534 .962 0 .043 1998 270 1583 0 548 16.2 549 .727 0 .08 1999 270 0 0 591 10.08 1045 .825 0 .079 2000 270 1618 0 555 9.14 336 1.391 0 .074 2001 270 1552 0 789 9.25 369 2.199 0 .064 2002 270 1799 0 655 6.76 246 1.864 0 .081 2003 270 1583 0 918 7.53 452 2.04 0 .068 2004 270 1479 0 683 7.34 413 1.765 0 .061 2005 270 1479 0 683 7.34 413 1.565 0 .049 2006 270 1667 0 728 7.28 260 1.45 0 .04 2007 270 1970 0 928 7.06 402 1.413 0 .055 2008 270 1520 0 740 6.73 331 1.431 0 .083 2009 270 1799 0 1079 6.36 453 1.374 0 .081 2010 270 2000 0 1133 5.9 441 1.29 0 .12 2011 270 1872 0 936 5.03 577 1.085 0 .101 2012 270 1976 0 1306 5 586 1.059 0 .104 2013 270 1804 0 813 4.85 598 .864 0 .115 2014 270 2296 0 1279 4.92 573 .713 0 .126 2015 270 2083 0 881 4.03 640 .747 0 .167 1980 253 1150 0 436 .3 667 9.2 0 .1 1981 253 1006 0 512 .3 667 9.3 0 .1 1982 253 1088 0 510 .2 500 8.3 0 .6 1983 253 641 0 479 .3 667 8.4 0 .3 1984 253 726 0 491 .3 667 6.2 0 .2 1985 253 699 0 537 .3 667 8.7 0 .5 1986 253 1111 0 444 .3 333 6.3 0 .3 1987 253 941 0 429 .4 750 6 0 .6 1988 253 703 0 404 .7 571 4.1 0 .5 1989 253 799 0 494 .6 667 6.4 0 .5 1990 253 1112 0 515 .81 691 8.03 0 .98 1991 253 907 0 669 .9 467 6.25 0 .88 1992 253 988 0 617 2.39 536 7.04 0 1.22 1993 253 1153 0 695 2.37 430 9.72 0 1.83 1994 253 1217 0 770 1.9 474 9.85 0 1.74 1995 253 1226 0 598 1.8 611 7.58 0 1.583 1996 253 1176 0 640 1.7 588 6.497 0 1.285 1997 253 978 0 568 1.5 467 6.608 0 1.137 1998 253 1006 0 595 3.7 541 5.458 0 .962 1999 253 0 0 724 1.46 918 7.061 0 1.016 2000 253 1307 0 658 .94 319 5.509 0 .922 2001 253 1258 0 838 2.33 365 10.772 0 1.696 2002 253 1281 0 723 2.16 319 9.859 0 2.528 2003 253 1233 0 1016 6.92 397 12.337 0 5.994 2004 253 1037 0 564 6.11 363 10.133 0 4.093 2005 253 1037 0 564 6.11 363 9.304 0 5.387 2006 253 929 0 780 6.74 337 8.353 0 4.846 2007 253 1145 0 843 4.62 398 9.124 0 4.765 end
Code:
reshape long AREA, i( YEAR id1 ) j(CROPCAT) egen concatenate = concat( id1 CROPCAT ) destring concatenate, replace xtset YEAR concatenate
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float YEAR int id1 byte CROPCAT float AREA int YIELD1 float(YIELD2 YIELD3 YIELD4) int concatenate 1980 25 1 2333 0 .29 .999 0 251 1980 25 2 1900 0 .29 .999 0 252 1980 25 3 0 0 .29 .999 0 253 1980 25 4 0 0 .29 .999 0 254 1980 26 1 820 179 2.738 .305 .004 261 1980 26 2 1111 179 2.738 .305 .004 262 1980 26 3 0 179 2.738 .305 .004 263 1980 26 4 2.8 179 2.738 .305 .004 264 1980 30 1 2187 500 123.1 .2 .4 301 1980 30 2 500 500 123.1 .2 .4 302 1980 30 3 0 500 123.1 .2 .4 303 1980 30 4 2 500 123.1 .2 .4 304 1980 31 1 1645 250 .084 .006 0 311 1980 31 2 1958 250 .084 .006 0 312 1980 31 3 0 250 .084 .006 0 313 1980 31 4 .4 250 .084 .006 0 314 1980 33 1 1400 0 .811 1.549 0 331 1980 33 2 1200 0 .811 1.549 0 332 1980 33 3 0 0 .811 1.549 0 333 1980 33 4 0 0 .811 1.549 0 334 1980 34 1 2715 792 288.5 .6 4.7 341 1980 34 2 2000 792 288.5 .6 4.7 342 1980 34 3 333 792 288.5 .6 4.7 343 1980 34 4 24 792 288.5 .6 4.7 344 1980 35 1 2045 1000 69.6 0 .1 351 1980 35 2 0 1000 69.6 0 .1 352 1980 35 3 750 1000 69.6 0 .1 353 1980 35 4 1 1000 69.6 0 .1 354 1980 36 1 1431 250 9.977 .198 .072 361 1980 36 2 1340 250 9.977 .198 .072 362 1980 36 3 500 250 9.977 .198 .072 363 1980 36 4 .4 250 9.977 .198 .072 364 1980 37 1 1437 250 2.535 .558 .006 371 1980 37 2 1571 250 2.535 .558 .006 372 1980 37 3 0 250 2.535 .558 .006 373 1980 37 4 .4 250 2.535 .558 .006 374 1980 39 1 1278 429 2.092 .023 .062 391 1980 39 2 1667 429 2.092 .023 .062 392 1980 39 3 269 429 2.092 .023 .062 393 1980 39 4 .7 429 2.092 .023 .062 394 1980 40 1 2455 2000 208 .1 .5 401 1980 40 2 0 2000 208 .1 .5 402 1980 40 3 1000 2000 208 .1 .5 403 1980 40 4 1 2000 208 .1 .5 404 1980 42 1 2194 1000 45.6 .5 .3 421 1980 42 2 1500 1000 45.6 .5 .3 422 1980 42 3 308 1000 45.6 .5 .3 423 1980 42 4 1 1000 45.6 .5 .3 424 1980 43 1 2778 0 90.9 .1 .2 431 1980 43 2 0 0 90.9 .1 .2 432 1980 43 3 0 0 90.9 .1 .2 433 1980 43 4 0 0 90.9 .1 .2 434 1980 44 1 1056 500 3.7 .1 0 441 1980 44 2 1111 500 3.7 .1 0 442 1980 44 3 0 500 3.7 .1 0 443 1980 44 4 .2 500 3.7 .1 0 444 1980 45 1 1275 167 5.475 .191 .051 451 1980 45 2 1611 167 5.475 .191 .051 452 1980 45 3 196 167 5.475 .191 .051 453 1980 45 4 .6 167 5.475 .191 .051 454 1980 46 1 952 1000 2 0 0 461 1980 46 2 1100 1000 2 0 0 462 1980 46 3 0 1000 2 0 0 463 1980 46 4 .1 1000 2 0 0 464 1980 47 1 1281 600 8.546 .953 .193 471 1980 47 2 1436 600 8.546 .953 .193 472 1980 47 3 750 600 8.546 .953 .193 473 1980 47 4 .5 600 8.546 .953 .193 474 1980 48 1 3162 1000 264.2 4.6 .8 481 1980 48 2 1800 1000 264.2 4.6 .8 482 1980 48 3 500 1000 264.2 4.6 .8 483 1980 48 4 1 1000 264.2 4.6 .8 484 1980 49 1 1403 3500 12.6 .1 .1 491 1980 49 2 1360 3500 12.6 .1 .1 492 1980 49 3 750 3500 12.6 .1 .1 493 1980 49 4 .2 3500 12.6 .1 .1 494 1980 50 1 1303 0 3.7 .2 0 501 1980 50 2 1176 0 3.7 .2 0 502 1980 50 3 1000 0 3.7 .2 0 503 1980 50 4 .1 0 3.7 .2 0 504 1980 51 1 1110 500 9.7 .3 0 511 1980 51 2 964 500 9.7 .3 0 512 1980 51 3 0 500 9.7 .3 0 513 1980 51 4 .2 500 9.7 .3 0 514 1980 54 1 2633 400 268.4 5.8 1.2 541 1980 54 2 1875 400 268.4 5.8 1.2 542 1980 54 3 667 400 268.4 5.8 1.2 543 1980 54 4 5 400 268.4 5.8 1.2 544 1980 55 1 3066 545 330.4 11.9 7.4 551 1980 55 2 2000 545 330.4 11.9 7.4 552 1980 55 3 731 545 330.4 11.9 7.4 553 1980 55 4 11 545 330.4 11.9 7.4 554 1980 56 1 1016 500 9.4 .3 0 561 1980 56 2 963 500 9.4 .3 0 562 1980 56 3 0 500 9.4 .3 0 563 1980 56 4 .2 500 9.4 .3 0 564 1980 57 1 940 333 5.1 .2 .1 571 1980 57 2 871 333 5.1 .2 .1 572 1980 57 3 0 333 5.1 .2 .1 573 1980 57 4 .6 333 5.1 .2 .1 574 end
My problems are the following
1) Second Is it ok to run mlogit on a panel data. I saw a thread by Clyde Schechter (https://www.statalist.org/forums/for...for-panel-data) and it mentioned to xtset the data and use femlogit. However in my case it takes a very long time. So I xtset my data and try to use mlogit.
2) I find that several papers mention using ‘land use shares’ as the dependent variables (e.g https://doi.org/10.1111/agec.12551). While I know that the multinomial model requires a categorical variable. Is there any way to account for share as the dependent variable and then link it to the categorical variable (something like the cmmprobit command in Stata 16 does)
3) Following from point 2 evidently I am missing something because when I run the mlogit I get the following result
Array
However if I run a fixed effects regression on the Area variable I get the following resul which seems to indicate that 'yields do impact area under a certain crop'
Array
What am I missing? Any suggestions would be helpful.
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