I had argued in an earlier post that the success or failure of the campaign to curb black money and expand the tax base initiated through the demonetisation decision would depend on how the flow problem would be addressed.
Indira Rajaraman has an excellent article which argues that the path to increasing tax revenues is to detect and reduce flows of tax evasion. She advocates the use of presumptive methods for identifying tax evasion - focus on occupation categories with high incomes and high value purchases of goods and services, and track individuals for tax payment proportionality.
It is plain obvious that there is massive tax evasion at the highest levels of income ladder. It is also a reasonable premise to argue that the same is concentrated in a few areas. A few occupational and economic activity categories come straight to mind - lawyers, doctors and hospitals, professional colleges, tuition centres, entertainers, construction contractors, real estate developers etc. And purchases to target include vacations (hotel bookings, air travels etc), gold, real estate, luxury durables (vehicles, designer wear, antiques and art, etc), management quota college seats, club memberships, wellness services (spas, therapeutic, cosmetology etc), entertainment services, and general transactions beyond a certain value. These two should be coupled with data on credit card spends, savings account transactions, financial market investments etc.
Evidently, this would require accessing multiple data bases, most of which are unlikely to be readily available. One way to ease the identification challenge is to link up transactions with the Income Tax PAN. Once the individuals concerned are identified, a first order scrutiny would be to check for proportionality with their tax payments.
To begin with, it may not even be necessary to adopt rigorous enforcement actions. Merely intimating the respective individuals about the observed discrepancy between their expenditures and income tax payments and seeking their explanation may be adequate to nudge significant compliance. This would avoid the inevitable harassment and corruption associated with enforcement based tax campaigns, which generally brings disrepute to such well-intentioned efforts.
So why have we not been able to do this? My strong belief is that it can be traced back to state capacity weakness. Indira Rajaraman too appears to say the same,
We live in a country where utility companies are not able to collect their dues, leaving public-sector banks groaning under default. A simple administrative requirement for PAN numbers attached to electricity dues or leasing of generators (for lavish marriages) would have led to higher revenue for both the income-tax department and power distribution companies. Large-scale tax evasion has long been practised right in the face of the income-tax authorities through political connections. Those without political connections have had to pay their way out. Either way, unless these features of the taxation system are reformed, there is nothing demonetisation can do for tax revenue.
Assembling and analysing the data required to identify such leakages is no mean task. For a start, it is painstaking work to extract data on the occupational categories and purchases. There are no single, readily available databases for any of them. Assembling this information would be a massive exercise in inter-departmental co-ordination and engagement with various market participants at different levels. Apart from overcoming strong resistance from entrenched interests, legal constraints and privacy concerns would have to be addressed. It would also require reconfiguring compliance and other reporting formats by businesses. The Revenue Department of the Ministry of Finance, on its own, simply does not have the capacity nor the convening power to pull this off.
Then there is the matter of their analysis with respect to actual tax assessments. This too is far from being just some sophisticated software based analytics. As Rajaraman cites with the example of Israel's use of presumptive taxable income estimate linked to transaction value, such analytics has to be built on painstaking ground work.
Such plumbing challenges demand strong state capacity at all jurisdictional levels. Unfortunately, state capacity weakness is no less acute in Revenue Department and the Central Board of Direct Taxes (CBDT). Compounding the problem is the institutional and incentive structure of the CBDT, which is seen and sees itself largely as an implementation agency - tax assessment, collection and enforcement. Systemic transformations of the kind discussed above demand entities with strong policy conceptualisation, design, and research focus. This may be a good opportunity to pivot and build a strong focus in this dimension.