The Association for Democratic Reforms, India keeps coming up with all kinds of fascinating data on politicians, which every aware citizen (or wanting to be aware citizen) should keep an eye on. Here’s a fascinating little table they have published in their report on Ten Years of Elections, Crime and Money, which I have converted into a sortable table here.
| PARTY | Candidates Analyzed | MPs/MLAs Analyzed | Candidates with Criminal Charges | % Candidates with Criminal Charges | Candidates with Serious Charges | % Candidates with Serious Criminal Charges | MPs/MLAs with Criminal Charges | MPs/MLAs with Serious Criminal Charges | % MPs/MLAs with Criminal Charges | % MPs/MLAs with Serious criminal charges | Avg Assets of Candidates | Avg. Assets of MPs/MLAs | Avg. Assets of MPs/MLAs with Criminal Charges | Avg. Assets of MPs/MLAs with Serious Criminal Charges |
| INC | 6322 | 2451 | 1407 | 22% | 605 | 10% | 527 | 205 | 22% | 8% | Rs. 4.32 Crores | Rs. 5.81 Crores | Rs. 7.98 Crores | Rs. 6.75 Crores |
| BJP | 5605 | 1689 | 1357 | 24% | 559 | 10% | 520 | 221 | 31% | 13% | Rs. 1.79 Crores | Rs. 2.88 Crores | Rs. 3.40 Crores | Rs. 3.87 Crores |
| BSP | 4739 | 430 | 900 | 19% | 470 | 10% | 149 | 76 | 35% | 18% | Rs. 1.25 Crores | Rs. 2.73 Crores | Rs. 2.56 Crores | Rs. 2.78 Crores |
| SP | 2096 | 418 | 579 | 28% | 293 | 14% | 180 | 92 | 43% | 22% | Rs. 1.52 Crores | Rs. 4.16 Crores | Rs. 4.12 Crores | Rs. 5.45 Crores |
| CPM | 1163 | 520 | 320 | 28% | 135 | 12% | 111 | 46 | 21% | 9% | Rs. 27.31 lakhs | Rs. 21.21Lakhs | Rs. 20.91 Lakhs | Rs. 2.31 Crores |
| NCP | 1103 | 225 | 214 | 19% | 93 | 8% | 67 | 24 | 30% | 11% | Rs. 1.56 Crores | Rs. 3.56 Crores | Rs. 3.31 Crores | Rs. 4.14 Crores |
| JD(U) | 1005 | 272 | 281 | 28% | 150 | 15% | 120 | 75 | 44% | 28% | Rs. 1.33 Crores | Rs. 3.61 Crores | Rs. 85.49 lakhs | Rs. 91.98 lakhs |
| AITC | 904 | 256 | 206 | 23% | 125 | 14% | 83 | 60 | 32% | 23% | Rs. 1.36 Crores | Rs. 1.31 Crores | Rs. 79.70 Lakhs | Rs.98.81 Lakhs |
| JD(S) | 656 | 81 | 138 | 21% | 66 | 10% | 26 | 10 | 32% | 12% | Rs. 4.72 Crores | Rs. 7.72 Crores | Rs. 3.66 Crores | Rs. 6.16 Crores |
| RJD | 618 | 125 | 236 | 38% | 132 | 21% | 58 | 33 | 46% | 26% | Rs. 57.28 lakhs | Rs. 70.17 lakhs | Rs. 76.03 Lakhs | Rs. 89.86 Lakhs |
| CPI | 608 | 91 | 129 | 21% | 45 | 7% | 32 | 11 | 35% | 12% | Rs. 28.15 lakhs | Rs. 29.00 Lakhs | Rs. 21.99 Lakhs | Rs. 35.87 Lakhs |
| SS | 611 | 137 | 274 | 45% | 126 | 21% | 103 | 42 | 75% | 31% | Rs. 1.20 Crores | Rs. 2.33 Crores | Rs. 2.68 Crores | Rs. 3.55 Crores |
| AIADMK | 426 | 234 | 96 | 23% | 49 | 12% | 65 | 36 | 28% | 15% | Rs. 2.03 Crores | Rs. 2.89 Crores | Rs. 5.39 Crores | Rs. 4.79 Crores |
| RLD | 393 | 29 | 65 | 17% | 34 | 9% | 8 | 6 | 28% | 21% | Rs. 1.19 Crores | Rs. 3.79 Crores | Rs. 6.94 Crores | Rs. 7.90 Crores |
| DMK | 315 | 167 | 88 | 28% | 37 | 12% | 57 | 22 | 34% | 13% | Rs. 3.01 Crores | Rs. 2.94 Crores | Rs. 2.90 Crores | Rs. 4.89 Crores |
| TDP | 312 | 127 | 90 | 29% | 32 | 10% | 46 | 18 | 36% | 14% | Rs. 5.61 Crores | Rs. 8.72 Crores | Rs. 6.33 Crores | Rs. 2.76 Crores |
| BJD | 233 | 197 | 61 | 26% | 40 | 17% | 50 | 30 | 25% | 15% | Rs. 1.01 Crores | Rs. 1.10 Crores | Rs. 62.51 lakhs | Rs. 53.71 lakh |
| SAD | 209 | 117 | 52 | 25% | 16 | 8% | 25 | 8 | 21% | 7% | Rs. 6.02 Crores | Rs. 6.27 Crores | Rs. 8.73 Crores | Rs. 17.34 Crores |
| AGP | 180 | 39 | 19 | 11% | 7 | 4% | 2 | 1 | 5% | 3% | Rs. 62.52 lakhs | Rs. 77.21 lakhs | Rs. 54.05 lakhs | Rs. 23.22 lakhs |
| IND | 19819 | 345 | 2169 | 11% | 1057 | 5% | 111 | 59 | 32% | 17% | Rs. 54.62 lakhs | Rs. 7.23 Crores | Rs. 11.74 Crores | Rs. 15.12 Crores |
| Total | 62847 | 8790 | 11063 | 18% | 5253 | 8% | 2575 | 1187 | 29% | 14% | Rs. 1.37 Crores | Rs. 3.83 Crores | Rs. 4.30 Crores | Rs. 4.38 Crores |
To normalize for varying sample sizes, if we look at the percentages of studied politicians alone, we see which parties have the largest numbers of corrupt people in official positions:
Worse, it is easy to see the corelation between parties with greater average assets of politicians as well as assets of politicians with criminal cases.
I am studying these three charts and will be updating this post with my observations in a couple of hours. What are the insights you get from these?