单位特定趋势和R平方接近1

时间:2018-03-22 17:33:30

标签: regression stata correlation difference

我目前正在制作一个国家/地区面板数据集,其中我正在运行差异化反差,包括Stata中的单位特定趋势

我主要担心的是,调整后的R平方值非常高,有时甚至是0.99。我假设这是某种错误的迹象,但我不知道如何纠正它。

对于模型,我有近5000个观测值。国家数量为201,我有36年和5个控制变量,那么参数的数量将在450左右。

这里我附上了使用的代码:

xtset id_num year // id_num = id_country

reg `outcome' i.treatment i.year i.id_num c.year#i.id_num `controls' if id_country!="USA" & `subgroup'==1, cluster(id_num)

如果有用,这是输出的第一部分

    note: 201.id_num#c.year omitted because of collinearity

Linear regression                               Number of obs     =      4,789
                                                F(39, 174)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9994
                                                Root MSE          =     .20753

                            (Std. Err. adjusted for 175 clusters in id_country)
-------------------------------------------------------------------------------
              |               Robust
   obesity_as |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
  1.treatment |   .1847802   .1341994     1.38   0.170     -.080088    .4496483
              |
         year |
        1981  |   .2162895   .0156983    13.78   0.000      .185306    .2472731
        1982  |   .4461132   .0224864    19.84   0.000     .4017319    .4904944
        1983  |   .6690157   .0281392    23.78   0.000     .6134777    .7245538
        1984  |    .915047   .0311529    29.37   0.000     .8535609    .9765332
        1985  |   1.177176   .0344991    34.12   0.000     1.109085    1.245266
        1986  |   1.421679   .0389734    36.48   0.000     1.344758    1.498601
        1987  |    1.68354   .0413294    40.73   0.000     1.601969    1.765112
        1988  |   1.963494   .0440206    44.60   0.000     1.876611    2.050377
        1989  |   2.236331   .0472635    47.32   0.000     2.143048    2.329615
        1990  |    2.52923   .0498206    50.77   0.000       2.4309     2.62756

0 个答案:

没有答案