Without resolving these issues, the channel then moved on to the Vyapam scam, where many statistics were quoted. What bothered me was the lack of precision. Were medical seats going for Rs 15 lakhs or Rs 50 lakhs? Was it 40 dead, or 22? When they were selling government posts, did they include the police or not? All these things are essential to the math, and without math, there is no proper understanding. Nevertheless, everyone else was angry, so I started getting angry too. But how angry was I supposed to be, vis-à-vis the earlier expose?
To make matters worse, soon after this they switched to Goa, where a former chief minister was being accused of stealing a Rs 1 crore, while his minister allegedly took Rs 70 lakhs. They were looking pretty sheepish and I don’t blame them. Who gets fingered for 70 lakhs? Are we supposed to get mad about this? I was confused. I had no guidelines. That’s when it struck me. Our perspective on this is flawed. What we need is a more analytical approach.
The need for standards
The problem with corruption is, we have no standards. Even earthquakes have standards. When we register 7.0 on the Richter scale, we feel a modest sense of pride. Our approach requires more professionalism. It’s why the Japanese are so far ahead. What we want are solid numbers, preferably audited by CAG. We want balance sheets, and profit and loss statements, and net asset values. We need facts that we can trust. Wipro and Infosys are compared this way. Why should scams be different? Proper quantitative tools lead to better understanding.
The Goa case provides an illustration. The sums of money were small, but then, so is the state. Logically speaking, we should factor in population. Hence one useful measure of scams would be a Scam Outlay Per Capita or SOPC Index. Let us apply this to Goa. Goa has a population of 14.6 lakhs. Dividing rupees in crores by people in crores, a scam involving Rs 1.7 crores yields an SOPC Index of 11.6. Now, look at Madhya Pradesh. MP has a population of 7.27 crores. A scam of Rs 40,000 crores gives us an SOPC Index of 5502. This means that compared to Goa, we should be 500 times more upset about MP.
Next, let us take the Spectrum scam. Assume it was worth Rs 120,000 crores. Dividing this by the population of India in crores, we arrive at an SOPC Index of 991.7. According to this calculation, we should be approximately 90 times more upset about this than we would be about Goa. Individual state-wise scams can also be added up to help us arrive at a state-wise ranking. This could be an annual event, with sponsors.
Numbers, numbers, numbers
There are other ways to use the power of math. Swiss banks often feature in discussions on corruption. Why just discuss them, when we can apply the power of math? The Economist has a Big Mac Index. For corruption, we could have a Swiss Franc Index, which answers the question, how many Swiss Francs could I buy today with this sum? This would take care of both inflation and currency fluctuation in an elegant and mathematically precise way.
We also need to distinguish between Recurring Value scams and Fixed Value scams. A fixed value scam is a one-time transaction, as in “I like your face. Keep a bunch of spectrum.” These are rare and happy occasions. A Recurring Value Scam flows like a mighty river. Take the case of Madhya Pradesh. It’s safe to assume that the battle to provide better medical services in MP will continue, especially since most of the whistleblowers are dead, and our brand new Whistleblower Act makes it highly inadvisable to complain against a government officer. This means that this scam has Recurring Value. It also means that it’s best to avoid medical emergencies in Madhya Pradesh.
Once such tools have been developed, and vetted by CAG, corruption will become much more transparent. We will be able to measure the relative value of scams, and adjust our response accordingly. There is no doubt that this is an area, which needs further exploration. It’s virgin territory. For a trained economist, there could even be a Nobel Prize in it. All I ask is that they acknowledge me during their acceptance speech.