Build a database of municipal bonds

The municipal bonds market received a shot in the arm when Pune Municipal Corporation raised ₹200 crore in June 2017 for a water supply project. Greater Hyderabad Municipal Corporation raised ₹200 crore in February this year to fund their road project. We are told there are other cities in the queue to raise bonds.

This small market has seen an issuance of around ₹2,000 crore since the first bond issue two decades ago. While regulators and the Government are keen on more such bonds, the markets are yet to share the enthusiasm. Among the many factors withholding the development of the municipal bonds market is lack of information infrastructure.

Money flow

The Reserve Bank of India publishes annually a report on the State budgets, which analyses the fiscal position of State governments based on primary data. There is no such compendium on the budgets of local bodies. At Public Finance India, we analysed the budget documents of 46 cities: the revenue receipts of these municipal corporations was ₹63, 928 crore (0.47 per cent of national GDP) as per 2015-16 revised estimates.

There is no real data on the overall receipts or expenditure of local bodies in India. Whatever data available is from the Comptroller and Auditor General (CAG) audit reports. These give a consolidated picture of the municipal finances. However, even the latest available CAG reports on local bodies date as far back as 2014-15.

The primary source of data is the website of the municipal corporation. Depending on how well the local body is governed, you could have detailed, timely financial statements or sketchy, abridged copies of the report. Of late, we have seen greater standardisation of municipal websites, particularly in the southern States. This is welcome, as it means there is oversight on information-sharing.

The core operational expenditure for municipal bodies pertains to public works, health, drinking water, street lighting, sanitation, primary education, maintenance of libraries and the sports stadium. The core revenue for these corporations is property tax. The details of service delivery or the properties assessed for tax are not published in the budget. For instance, Bengaluru Mahanagar Palike collected only 62 per cent of the property tax demand raised in 2014-15. An analysis of property tax collections is meaningful only when collections against the current demand and arrears are known. Similarly, it is difficult to understand the expenditure on water supply without an idea of the quantity of water supplied.

As part of a private open data programme called Open Budgets India, we created data sets for 46 municipal corporations from the budget documents of the years 2013-14 to 2016-17. This is a significant coverage of nearly 25 per cent of all the municipal corporations in the country. The worksheets helped put these municipalities on a common framework, overcoming the challenge of lack of data standards.

Insights regarding budget data

The exercise gave us many insights into the presentation of budget data:

• Very few municipalities adhere to the national/State municipal accounting manual (NMAM/SMAM). It appears that the chart of accounts is fluid in many municipalities as they are still transitioning to the accounting manual. Even among the mega cities, Bengaluru and Kolkata present budgets that are not compliant with the NMAM. Out of the 46 data sets that we created, only 23 were NMAM-compliant.

• The presentation of budget data varied greatly. NMAM mandates presenting budget information both function-wise (type of service rendered) and account code-wise (nature of revenue or expenditure item). However, most municipal corporations present the data only account code-wise.

• Even where the budget data was compliant with NMAM, budget items came without accounting and function codes.

• Accounting quality varied and was not linked to the size of the corporation. The most common errors were the confusion between revenue and capital items, and wrong account coding in the budget document. There were basic totalling mistakes in some budgets.

• Many of the budget documents were in the regional language. Often, the relevant language fonts were not available for downloading in the municipal website.

• The reporting units were not the same. The budget data was presented in rupees lakh by most municipal bodies. Some published the amounts in rupees thousands (Greater Mumbai Municipal Corporation, Chennai Municipal Corporation) and some others published the amounts in rupees. In the data sets, we presented the amounts in rupee lakh.

Comparable picture

While the Excel spreadsheets organised the data from the municipal budget documents on a common framework, it still did not make it easy to compare data across municipals. To overcome this problem, we developed in-house a database capable of handling queries. With some normalisation of the data sets, we were able to create a database that could be searched by function and account codes. The insights that a dynamic data base gives is superior to what can be achieved by static data sets. The main benefits are:

It enables compliance . The extent of deviation from the accounting manual is clear when the data sets have to be normalised to enter the data base.

Benchmarking of municipalities becomes possible . For example, while benchmarking, it came out clearly that Chennai Municipal Corporation lags behind Bengaluru and Hyderabad municipal corporations in terms of property tax revenues.

Integrated database with operational, economic data and financial data becomes possible . This in turn paves the way for analytics on the operational efficiency of the corporation, the potential for growth of revenues, the debt bearing capacity.

Improves ease of doing business as the counter-party risk is clear . The increased levels of transparency will attract private public partnerships in infrastructure delivery.

It can promote a culture of credit analysis among lenders to municipalities . Presently, the lender weighs in the tacit or explicit support of the state government while lending to a municipal corporation. This culture needs to change to informed decision-making.

Building a national municipal data base ought to be as great a priority as building roads or primary health centres. Getting the data cleaned and making it user-friendly is the first step to building an information infrastructure for the municipal bonds market.

The writer is the founder-director of Macromoney Research Initiatives Private Limited

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