Hi everyone:
I´d like to compare results of censored model (tobit) with OLS regression. For this, I´ve prepared the following hypothetical data, that I´ve copied below. The censoring point for y is 1000. I´d estimated the following models:
ols Y const X
ols YCENS const X
And I´d like to estimate intreg with upper limit of 1000 (equivalent to Stata´s command: tobit YCENS X, ul(1000)). But, I´ve problems to define the variables minvar and maxvar. The model do not converge with Y_cens_minvar and Ycens_maxvar and X as independent variable. Are they correct?
Additional question: Is there any equivalent to Stata´s command: truncreg YTRUNC XTRUNC, ul(1000)?
Thanks in advance for any help.
Maria Dolores Montoya Diaz
The database is:
Y | X | YCENS | YTRUNC | XTRUNC | Ycens_minvar | Ycens_maxvar | |
1 | 150 | 2 | 150 | 150 | 2 | 150 | |
2 | 150 | 4 | 150 | 150 | 4 | 150 | |
3 | 160 | 4 | 160 | 160 | 4 | 160 | |
4 | 192 | 4 | 192 | 192 | 4 | 192 | |
5 | 230.4 | 4 | 230.4 | 230.4 | 4 | 230.4 | |
6 | 276.48 | 3 | 276.48 | 276.48 | 3 | 276.48 | |
7 | 331.776 | 3 | 331.776 | 331.776 | 3 | 331.776 | |
8 | 398.131 | 4 | 398.131 | 398.1312 | 4 | 398.1312 | |
9 | 477.757 | 4 | 477.757 | 477.7574 | 4 | 477.7574 | |
10 | 573.309 | 4 | 573.309 | 573.3089 | 4 | 573.3089 | |
11 | 687.971 | 6 | 687.971 | 687.9707 | 6 | 687.9707 | |
12 | 825.565 | 6 | 825.565 | 825.5649 | 6 | 825.5649 | |
13 | 990.678 | 6 | 990.678 | 990.6778 | 6 | 990.6778 | |
14 | 1188.813 | 8 | 1000 | 1000 | |||
15 | 1426.576 | 8 | 1000 | 1000 | |||
16 | 1711.891 | 8 | 1000 | 1000 | |||
17 | 1700 | 8 | 1000 | 1000 | |||
18 | 1700 | 8 | 1000 | 1000 | |||
19 | 1500 | 7 | 1000 | 1000 | |||
20 | 1200 | 6 | 1000 | 1000 | |||
21 | 1440 | 7 | 1000 | 1000 | |||
22 | 1728 | 8 | 1000 | 1000 | |||
23 | 2073.6 | 8 | 1000 | 1000 | |||
24 | 2488.32 | 8 | 1000 | 1000 | |||
25 | 2985.984 | 8 | 1000 | 1000 | |||
26 | 3583.181 | 18 | 1000 | 1000 | |||
27 | 4299.817 | 18 | 1000 | 1000 | |||
28 | 210 | 4 | 210 | 210 | 4 | 210 | |
29 | 210 | 4 | 210 | 210 | 4 | 210 | |
30 | 224 | 4 | 224 | 224 | 4 | 224 | |
31 | 268.8 | 4 | 268.8 | 268.8 | 4 | 268.8 | |
32 | 322.56 | 4 | 322.56 | 322.56 | 4 | 322.56 | |
33 | 387.072 | 6 | 387.072 | 387.072 | 6 | 387.072 | |
34 | 464.486 | 7 | 464.486 | 464.4864 | 7 | 464.4864 | |
35 | 557.384 | 8 | 557.384 | 557.3837 | 8 | 557.3837 | |
36 | 668.86 | 9 | 668.86 | 668.8604 | 9 | 668.8604 | |
37 | 802.632 | 11 | 802.632 | 802.6325 | 11 | 802.6325 | |
38 | 963.159 | 11 | 963.159 | 963.159 | 11 | 963.159 | |
39 | 1155.791 | 15 | 1000 | 1000 | |||
40 | 1386.949 | 15 | 1000 | 1000 | |||
41 | 1664.339 | 15 | 1000 | 1000 | |||
42 | 1997.207 | 15 | 1000 | 1000 | |||
43 | 2396.648 | 15 | 1000 | 1000 | |||
44 | 2380 | 15 | 1000 | 1000 | |||
45 | 2380 | 14 | 1000 | 1000 | |||
46 | 2100 | 15 | 1000 | 1000 | |||
47 | 1680 | 15 | 1000 | 1000 | |||
48 | 2016 | 15 | 1000 | 1000 | |||
49 | 2419.2 | 15 | 1000 | 1000 | |||
50 | 2903.04 | 16 | 1000 | 1000 |