F-Statistic for cluster robust standard error.

[Bilal Hafeez]

The dataset I have has the following characteristics. The data deals with shareholder activism for 13 years, T=13. The cross-sections have sometimes repetitive observations, following table shows the how firms might have repeating values across the time period and with the year.

Cross-section /Time	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016
Firm 3		7	6	9	7	4	6	5	4	6	6	5	6
Firm 4		8	6	11	7	6	6	5		4	3	5	3
Firm 5	1	6	7	7	3	5	7	4		6	5	5	6
Firm 6	1	7	5	9		7	5	5		4	3	4	4
Firm 7		7	5	6	5	1	2	3	2	4	4	8	3
Firm 8					1	1	2	1	3		1		1
Firm 9		1	2	3	1	1	1	1

The dependent variable is Analyst Report (AR) form 'i' at for week 't' whereas Independent is Log( 1+News Articles the week )(lnnews) control variables including Total assets( LnTA) for the previous year, Leverage(LEV) Book to market(Mkbk). I am not sure which is an appropriate manner to run a regression. I am now using

xi: regress AR lnnews lnTA Lev Mkbk i.Year i. Firm


I want to have standard errors clustered at the firm level once I change the command to

xi: regress AR lnnews lnTA Lev Mkbk i.Year i. Firm , vce (cluster Firm)


The F-statistic goes missing.


How to solve the issues, there are a total of 784 unique firms a total of 4564 firm-year observations for 13 years.

[Marcos Almeida]

Carlo gave excellent advice. Just a side note: it seems you have duplicates, according to the way the - xtset - was done. You can check it out with - duplicates - command.

[Carlo Lazzaro]

Bilal:
-please use -dataex- to share example/excerpt of you dataset.
That said:
- -regress- rarely outperforms -xtreg- when it comes to panel data analysis;
- if you do not plan to use time-series commands, such as leads and lags, you can -xtset- your data using the -panelid- only.

[Bilal Hafeez]

Thank you Carlo Lazzaro,

I think the data is already in a long shape, Please see the following table attached. Index_SVI is unique to each observation I have, whereas PERMNO is firm identifier and Year is the respective time period. You can also see the that there are repeated cross-sectional values form each firm in a given year (3007,3008 belong to the firm 10104 for same 2007), this makes it hard to declare it panel using xtset.

Based on my research on various forums and research articles.

i. I could just use the cross-sectional regression but the issue of F-stats I am not sure how to proceed.
ii. Use xtreg, but I cannot declare the data to be panel because of the repeated cross-section in time.


The command and error message for xtset is

xtset PERMNO Year
repeated time values within panel

   
Index_SVI
PERMNO
Year

Arreport
lnews_10
lnta
ReturnonAssets
BooktoMarketRatio
Leverage

3008
10104
2007

8.95
4.19
10.45
13.44
5.85
44.88

3007
10104
2007

8.95
4.19
10.45
13.44
5.85
44.88

3010
10104
2008

8.78
3.83
10.76
13.49
5.11
48.80

3013
10104
2009

10.17
4.25
10.77
11.81
3.91
40.81

3011
10104
2009

10.17
4.25
10.77
11.81
3.91
40.81

3012
10104
2009

10.19
4.25
10.77
11.81
3.91
40.81

3016
10104
2010

11.35
3.89
11.03
11.26
3.68
47.58

3015
10104
2010

11.35
3.89
11.03
11.26
3.68
47.58

3014
10104
2010

11.35
3.89
11.03
11.26
3.68
47.58

7043
10104
2015

8.50
3.18
11.62
9.88
3.88
86.22

7046
10104
2015

8.50
3.18
11.62
9.88
3.88
86.22

7044
10104
2015

8.50
3.18
11.62
9.88
3.88
86.22

7042
10104
2015

8.50
3.18
11.62
9.88
3.88
86.22

7048
10104
2016

7.65
3.26
11.63
7.98
3.51
92.74

2719
10107
2006

0.00
4.36
11.15
17.95
5.85
0.00

2717
10107
2006

0.00
4.36
11.15
17.95
5.85
0.00

2718
10107
2006

0.00
4.36
11.15
17.95
5.85
0.00

2720
10107
2007

0.00
3.30
11.05
21.19
8.89
0.00

2721
10107
2007

0.00
3.30
11.05
21.19
8.89
0.00

2716
10107
2011

15.12
4.25
11.60
23.77
3.82
20.88

5176
10107
2012

14.04
3.99
11.71
14.77
3.86
18.00

6843
10107
2014

15.14
3.74
12.06
14.02
3.83
25.22

6844
10107
2016

11.38
2.77
12.17
9.13
5.55
75.35

2096
10145
2004

17.10
3.33
10.34
4.24
2.67
46.86

2099
10145
2005

13.08
4.13
10.36
4.99
2.87
47.44

2100
10145
2005

13.08
4.13
10.36
4.99
2.87
47.44

2102
10145
2005

13.08
4.13
10.36
4.99
2.87
47.44

2101
10145
2005

13.08
4.13
10.36
4.99
2.87
47.44

2103
10145
2005

13.08
4.13
10.36
4.99
2.87
47.44

2104
10145
2006

12.75
4.29
10.34
6.64
3.73
52.09

2106
10145
2006

12.75
4.29
10.34
6.64
3.73
52.09

6536
10145
2014

10.62
4.06
10.72
9.33
4.43
49.18

6538
10145
2014

10.62
4.06
10.72
9.33
4.43
49.18

6539
10145
2014

10.62
4.06
10.72
9.33
4.43
49.18

6537
10145
2014

10.62
4.06
10.72
9.33
4.43
49.18

6542
10145
2015

10.34
4.39
10.81
10.06
4.36
66.01

6540
10145
2015

10.34
4.39
10.81
10.06
4.36
66.01

Your input is highly valued, thank you very much

[Carlo Lazzaro]

Billal:
the first thing you should do to use -xtreg-, is using -reshape- to convert your data from -wide- to -long- format.

[Bilal Hafeez]

This is a sample output here PERMNO is firm identifier

. xi: regress  ARreport lnews_10 lnta ReturnonAssets BooktoMarketRatio Leverage  i.Year i.PERMNO  ,vce(cl
> uster PERMNO)
i.Year            _IYear_2004-2016    (naturally coded; _IYear_2004 omitted)
i.PERMNO          _IPERMNO_10104-93436(naturally coded; _IPERMNO_10104 omitted)

Linear regression                               Number of obs     =      4,594
                                                F(18, 783)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.6838
                                                Root MSE          =     9.3237

                                    (Std. Err. adjusted for 784 clusters in PERMNO)
-----------------------------------------------------------------------------------
                  |               Robust
          ARreport|      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
         lnews_10 |   .5254691   .3330785     1.58   0.115    -.1283634    1.179302
             lnta |  -.4482952   .9986625    -0.45   0.654    -2.408668    1.512078
   ReturnonAssets |  -.1251285   .0496914    -2.52   0.012    -.2226726   -.0275843
BooktoMarketRatio |  -.0118422   .0174835    -0.68   0.498    -.0461623    .0224779
         Leverage |   .0008755   .0008851     0.99   0.323    -.0008618    .0026129

This is another case where I have excluded the i.PERMNO form equation

  xi: regress  ARreport lnews_10  lnta ReturnonAssets BooktoMarketRatio Leverage  i.Year ,vce(cluster PERM
> NO)
i.Year            _IYear_2004-2016    (naturally coded; _IYear_2004 omitted)

Linear regression                               Number of obs     =      4,594
                                                F(19, 783)        =       6.57
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1589
                                                Root MSE          =     13.845

                                    (Std. Err. adjusted for 784 clusters in PERMNO)
-----------------------------------------------------------------------------------
                  |               Robust
          ARreport |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
         lnews_10 |   1.721232   .4309261     3.99   0.000     .8753245    2.567139
             lnta |  -2.433996   .3273187    -7.44   0.000    -3.076522    -1.79147
   ReturnonAssets |  -.1102286   .0565688    -1.95   0.052    -.2212731    .0008158
BooktoMarketRatio |  -.0819114   .0329707    -2.48   0.013    -.1466329   -.0171899
         Leverage |   .0022335   .0011028     2.03   0.043     .0000687    .0043983

In these case the degree of freedom reported value of F- stat is almost similar but no F-stat in the prior model but in the latter case the F-stat is 6.57.

[Bilal Hafeez]

Thank you for your responses, I had a look at the FAQs and I am hoping that I do a better job this time. The data deals with shareholder activism for 13 years, T=13. The cross-sections have sometimes repetitive observations, following table shows the how firms might have repeating values across the time period and within the same the year. The following table provides information about how the data is distributed across the years. For example firm 3 has 5 Analyst Reports(AR) in 2005 and 6 during 2016.

 
Cross-section /Time
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

Firm 3

7
6
9
7
4
6
5
4
6
6
5
6

Firm 4

8
6
11
7
6
6
5

4
3
5
3

Firm 5
1
6
7
7
3
5
7
4

6
5
5
6

Firm 6
1
7
5
9

7
5
5

4
3
4
4

Firm 7

7
5
6
5
1
2
3
2
4
4
8
3

Firm 8




1
1
2
1
3

1

1

xi: regress AR lnnews lnTA Lev Mkbk i.Year i. Firm

The dependent variable is Analyst Report (AR) form 'i' at for week 't' whereas Independent is Log( 1+News Articles the week )(lnnews) control variables including Total assets( LnTA) for the previous year, Leverage(LEV) Book to market(Mkbk)

I want to include firm and year fixed effects in regression when I use S.E clustered at the firm level there is no reported F-stat.

xi: regress AR lnnews lnTA Lev Mkbk i.Year i. Firm , vce (cluster Firm)

I used 'xi:' as I have to use another string variable 'AR report type' i.e i.ARreportype if I don't use 'xi' it does not work gives an error message.

xi: regress AR lnnews lnTA Lev Mkbk i.Year i. Firm i.ARreportype

Furthermore, I have tried various combinations of fixed effects, whenever I used vce (cluster Firm) in the equation in most cases there is no F-stat.

Is there an alternative modeling method, can I use xtreg for this type of data.

Furthermore, I had read of j_robustsingular, according to that it might be about degree of freedoms but I have no clue about how to calculate it in my case.

[Carlo Lazzaro]

Bilal:
as an aside to Marcos' wise advice, see -help j_robustsingular-.

[Marcos Almeida]

Welcome to the Stata Forum / Statalist,

Please read the FAQ, particularly the topic about sharing data/command/output.

Maybe sharing this information will be helpful to clarify the issue.

That said, unless you're using a very old version of Stata, you won't need the prefix "xi".