如何用stata计算性别的herfindal（blau）系数，或者需要哪条命令，我可以自学

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我需要得到管理层性别异质性的数据，数据是09-16上市公司，部分数据如下，希望有人指教我如何计算性别的herfindal（blau）系数，或者告诉我应该用哪条命令，谢谢大家了~

1. Example generated by -dataex-. To install: ssc install dataex
   
2. clear
   
3. input long stkcd str13 stknme byte indcd str14 indnme int year str54 name byte(age degree) float gender str13 funback byte(markettype 是否st) str19 statco str16 statdt
   
4. 2 "万科A" 3 "房地产" 2015 "陈玮"    54 4 1 "4,5"   4 0 "A" "2018-05-31"
   
5. 2 "万科A" 3 "房地产" 2015 "陈鹰"    46 4 1 "2,5,6" 4 0 "A" "2018-05-31"
   
6. 2 "万科A" 3 "房地产" 2015 "张利平" 58 4 1 "5,7"   4 0 "A" "2018-05-31"
   
7. 2 "万科A" 3 "房地产" 2015 "海闻"    64 5 1 "2,5,8" 4 0 "A" "2018-05-31"
   
8. 2 "万科A" 3 "房地产" 2015 "谭华杰" 43 3 1 "5,6"   4 0 "A" "2018-05-31"
   
9. 2 "万科A" 3 "房地产" 2015 "乔世波" 62 3 1 "4,5"   4 0 "A" "2018-05-31"
   
10. 2 "万科A" 3 "房地产" 2015 "王石"    65 3 1 "5"     4 0 "A" "2018-05-31"
    
11. 2 "万科A" 3 "房地产" 2015 "孙建一" 63 2 1 "5,7"   4 0 "A" "2018-05-31"
    
12. 2 "万科A" 3 "房地产" 2015 "魏斌"    47 4 1 "8"     4 0 "A" "2018-05-31"
    
13. 2 "万科A" 3 "房地产" 2015 "王文金" 50 4 1 "2,5,8" 4 0 "A" "2018-05-31"
    
14. 2 "万科A" 3 "房地产" 2015 "罗君美" 62 3 0 "5,7,8" 4 0 "A" "2018-05-31"
    
15. 2 "万科A" 3 "房地产" 2015 "张旭"    53 4 1 "5"     4 0 "A" "2018-05-31"
    
16. 2 "万科A" 3 "房地产" 2015 "华生"    63 5 1 "5,99"  4 0 "A" "2018-05-31"
    
17. 2 "万科A" 3 "房地产" 2015 "郁亮"    51 4 1 "5,8"   4 0 "A" "2018-05-31"
    
18. 2 "万科A" 3 "房地产" 2014 "肖莉"    51 4 0 "5"     4 0 "A" "2018-05-31"
    
19. 2 "万科A" 3 "房地产" 2014 "陈玮"    53 4 1 "4,5"   4 0 "A" "2018-05-31"
    
20. 2 "万科A" 3 "房地产" 2014 "陈鹰"    44 4 1 "2,5,6" 4 0 "A" "2018-05-31"
    
21. 2 "万科A" 3 "房地产" 2014 "周卫军" 59 4 1 "5"     4 0 "A" "2018-05-31"
    
22. 2 "万科A" 3 "房地产" 2014 "王文金" 49 4 1 "2,5,8" 4 0 "A" "2018-05-31"
    
23. 2 "万科A" 3 "房地产" 2014 "王石"    63 3 1 "5"     4 0 "A" "2018-05-31"
    
24. 2 "万科A" 3 "房地产" 2014 "毛大庆" 46 5 1 "5"     4 0 "A" "2018-05-31"
    
25. 2 "万科A" 3 "房地产" 2014 "张利平" 57 4 1 "5,7"   4 0 "A" "2018-05-31"
    
26. 2 "万科A" 3 "房地产" 2014 "海闻"    63 5 1 "5"     4 0 "A" "2018-05-31"
    
27. 2 "万科A" 3 "房地产" 2014 "齐大庆" 50 5 1 "5,8"   4 0 "A" "2018-05-31"
    
28. 2 "万科A" 3 "房地产" 2014 "张旭"    51 4 1 "5"     4 0 "A" "2018-05-31"
    
29. 2 "万科A" 3 "房地产" 2014 "郁亮"    50 4 1 "5,8"   4 0 "A" "2018-05-31"
    
30. 2 "万科A" 3 "房地产" 2014 "罗君美" 61 3 0 "5,7,8" 4 0 "A" "2018-05-31"
    
31. 2 "万科A" 3 "房地产" 2014 "华生"    62 5 1 "5,99"  4 0 "A" "2018-05-31"
    
32. 2 "万科A" 3 "房地产" 2014 "莫军"    48 3 1 "5"     4 0 "A" "2018-05-31"
    
33. 2 "万科A" 3 "房地产" 2014 "孙建一" 61 2 1 "5,7"   4 0 "A" "2018-05-31"
    
34. 2 "万科A" 3 "房地产" 2014 "乔世波" 60 3 1 "4,5"   4 0 "A" "2018-05-31"
    
35. 2 "万科A" 3 "房地产" 2014 "谭华杰" 42 3 1 "5,6"   4 0 "A" "2018-05-31"
    
36. 2 "万科A" 3 "房地产" 2014 "丁长峰" 44 4 1 "5"     4 0 "A" "2018-05-31"
    
37. 2 "万科A" 3 "房地产" 2014 "魏斌"    45 4 1 "8"     4 0 "A" "2018-05-31"
    
38. 2 "万科A" 3 "房地产" 2014 "张纪文" 48 3 1 "3,5"   4 0 "A" "2018-05-31"
    
39. 2 "万科A" 3 "房地产" 2013 "魏斌"    44 4 1 "8"     4 0 "A" "2018-05-31"
    
40. 2 "万科A" 3 "房地产" 2013 "解冻"    48 5 1 "4,5"   4 0 "A" "2018-05-31"
    
41. 2 "万科A" 3 "房地产" 2013 "乔世波" 59 3 1 "4,5"   4 0 "A" "2018-05-31"
    
42. 2 "万科A" 3 "房地产" 2013 "孙建一" 60 2 1 "7,5"   4 0 "A" "2018-05-31"
    
43. 2 "万科A" 3 "房地产" 2013 "丁长峰" 43 4 1 "5"     4 0 "A" "2018-05-31"
    
44. 2 "万科A" 3 "房地产" 2013 "肖莉"    50 4 0 "5"     4 0 "A" "2018-05-31"
    
45. 2 "万科A" 3 "房地产" 2013 "罗君美" 60 3 0 "8"     4 0 "A" "2018-05-31"
    
46. 2 "万科A" 3 "房地产" 2013 "华生"    61 5 1 "5,99"  4 0 "A" "2018-05-31"
    
47. 2 "万科A" 3 "房地产" 2013 "王文金" 48 4 1 "8,2,5" 4 0 "A" "2018-05-31"
    
48. 2 "万科A" 3 "房地产" 2013 "郁亮"    49 4 1 "5,8"   4 0 "A" "2018-05-31"
    
49. end

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关键词：Stata find tata IND Dal

根据目前了解到的情况，没有命令对应此指数，需要自己编程。你就按照上面计算的步骤一步步的编程啊。
有一定的参考意义
https://math.stackexchange.com/questions/1190631/how-to-calculate-p-i-in-blaus-index-of-heterogeneity

铁锷未残 发表于 2018-9-13 08:25
根据目前了解到的情况，没有命令对应此指数，需要自己编程。你就按照上面计算的步骤一步步的编程啊。
有一 ...

好的，我已经在尝试了，但是我想请问如何能按照我数据中的stckd year 统计出来每个公司每年高管中男性和女性的人数，使用count吗，但是我的代码统计的有问题，代码如下，希望能够得到您的指教，谢谢

1. bys stkcd year: egen n= count(gender==1)

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试试

1. bys stkcd year: egen tem1 = total(gender)
   
2. bys stkcd year: egen tem2 = count(gender)
   
3. gen P1 = tem1/tem2
   
4. gen P2 = 1-P1
   
5. gen P1sq = P1^2
   
6. gen P2sq = P2^2
   
7. gen H = 1 - P1sq - P2sq
   
8. 
   
9. // 或
   
10. gen H1 = 2*P1*(1-P1)

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黃河泉 发表于 2018-9-13 10:25
试试

谢谢，我的问题已经解决了，我觉得你统计男性的时候用total函数简直是太妙了，身为初学者我要学的还有很多，感谢您的帮助！

khadjiah 发表于 2018-9-13 17:19
谢谢，我的问题已经解决了，我觉得你统计男性的时候用total函数简直是太妙了，身为初学者我要学的还有很多 ...

1. 其实有更精简的方法，不过上述方法较直觉！2. P_i^n 应该是 P_i^2 吧！

黃河泉 发表于 2018-9-13 17:33
1. 其实有更精简的方法，不过上述方法较直觉！2. P_i^n 应该是 P_i^2 吧！

可以指导一下精简版吗，我想更深刻的理解一下这个问题。
论文里面解释了n是类别的变量，在性别就是2，请问我这样理解对吗？

khadjiah 发表于 2018-9-13 17:44
可以指导一下精简版吗，我想更深刻的理解一下这个问题。
论文里面解释了n是类别的变量，在性别就是2，请 ...

1. 好像不是！请再查一下 (即使 3 或 4 类，也是 n=2)！2. 例如

1. // Romalpa Akzo
   
2. bys stkcd year x: gen a = _N*(_n==1)
   
3. bys stkcd year: egen Blau = total((_N-a^2)/(_N^2))

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黃河泉 发表于 2018-9-13 17:47
1. 好像不是！请再查一下 (即使 3 或 4 类，也是 n=2)！2. 例如

好的，谢谢您的指教，我之后再查一下！