Measuring institutional capacity in property tax systems: A case study of ten cities in India

by Diya Uday.

Property tax is ubiquitous with municipal finance. It provides local governments with the means to execute development strategies. In theory, property tax is an ideal candidate for supporting fiscal strategies in decentralised economies because the tax base is immobile making base identification and enforcement relatively easy (Kelly 2013). There are indications, however, that in India, we have not succeeded in doing property taxation well.

A national-level indicator of the performance of property taxes is the percentage of revenue generated from property taxes to the national GDP. Studies indicate that the proportion of revenues from property tax to GDP in India is low when compared with other countries. At the state-level, where property tax is a major source of revenue, there is evidence of revenue shortfalls, indicating the need for reforms. The policy responses for increasing revenues from property taxation, include increasing tax rates, revising taxation criteria and suggesting floor tax rates. But will these interventions be successful in improving the performance of the property tax system in cities?

A key factor in determining the success or failure of any policy intervention is institutional capacity. Policy interventions such as increases in property tax rates assume that ULBs are operating at optimal levels of institutional capacity and therefore increases in tax rates, property values or even improvements in tech infrastructure will optimise revenues from property taxes. In particular, these policies are founded on two main assumptions:

• that ULBs have adequate human resources and the technical capacity to assess and demand taxes correctly;
• having assessed taxes correctly, ULBs have the enforcement capacity to collect the entire tax demanded.

To achieve revenue optimisation from property tax it is important to first get tax administration right. Without this, it is unlikely that local governments will be able to capture the full extent of the property tax potential even with tax rate increases or technological interventions. This raises the important question: what is the current capacity of ULBs in property taxation?

In the literature we see indications of deficiencies in the institutional capacity of ULBs in performing some major tax functions like tax collections (World Bank 2004; Mathur et. al 2009; Bandyopadhyay 2014). While these studies give us valuable insights, this literature is not recent. Institutional capacity may have improved over time given the recent concentration of schemes to improve local governance such as the Smart Cities Mission and the Jawaharlal Nehru National Urban Renewal Mission (JNNURM). There is a need for new studies that will give us insights into the current state of institutional capacity.

In this article, we therefore measure the institutional capacity of some property tax functions in a sample set of cities in India. Our aim in doing so is two fold:

• to gain insights on the current level of institutional capacity in some property tax functions in a sample set of cities.
• in doing so we attempt to demonstrate that policy interventions must not presume the existence of adequate institutional capacity.

Our findings contribute to the existing literature on the state of property tax administration in India. In addition to this, we question the current approach to measuring administrative functions in the property tax system. We suggest an alternative approach for a more accurate diagnosis of the problems in administration.

A case study of ULB capacity in ten cities

We undertake two levels of analysis. We first examine the institutional capacity of ULBs in property tax collections in a sample set of cities. We then analyse the human resource allocation in the property tax departments in some ULBs. We use our findings to gain insights on institutional capacity in ULBs in a set of sample cities.

Sample selection: Our selection of the cities was driven by the location of the city and the availability of data. Our final selection includes a list of metropolitan and tier-2 cities located across ten different states in India. The selected cities are Chennai, Pune, Indore, Vishakapatnam, Shivamoga, Varanasi, Surat, Warangal, Kota and Bilaspur.

1. Measuring collection capacity

Methodology: We measure collections by calculating the Tax Collection Ratio (TCR), a commonly used method for measuring tax collections. Applying this method, we calculate the TCR as the difference between the tax demand made and the actual tax collected across each of the five years for which the data was available in each of the sample cities (2013-2018). We then calculate the TCR as a percentage value. We use this percentage value as a proxy to demonstrate the level of administrative capacity of a given city by taking 100 per cent as the benchmark. For instance, if the TCR percentage of a given city is 90 per cent, we interpret this to mean that the city has 90 per cent institutional capacity. Such a city has a higher level of institutional capacity when compared with a city in which the TCR percentage is 80 per cent, indicating a higher deficit in tax collections.

Table 1 sets out (i) the average property tax collected in ten cities across five years and (ii) the minimum and the maximum property tax collection across years in the period of study.

Table 1: City-wise average property tax collections (2013-2018)

City	State	Average TCR (%)	Minimum tax collection (as a % of tax demanded in that year)	Maximum collection (as a % of tax demanded in that year)
Chennai	Tamil Nadu	90	74 (2013-14)	106.60 (2017-18)
Pune	Maharashtra	96.36	87 (2017-18)	109.77 (2015-16)
Indore	Madhya Pradesh	80.25	72.16 (2014-15)	106.48 (2016-17)
Vishakapatnam	Andhra Pradesh	114.29	24.42 (2017-18)	265.52 (2015-16)
Shivamoga	Karnataka	98.36	97.86 (2014-15)	99.30 (2016-17)
Varanasi	Uttar Pradesh	96	92 (2013-14)	98.97 (2017-18)
Surat	Gujarat	84.65	76.65 (2015-16)	84.21 (2014-15)
Warangal	Telangana	79.87	75.12 (2013-14)	82.75 (2016-17)
Kota	Rajasthan	58.86	37.04 (2013-14)	96.14 (2016-17)
Bilaspur	Chattisgarh	90.2	75.52 (2017-18)	122.95 (2013-14)

Source: Author's calculations from Smart Cities Mission data

Findings: We find that no city in the sample has achieved 100 per cent TCR. Only one city i.e. Shivamoga has close to 100 per cent of tax collections. There is a deficit in property tax collection across all the cities in the sample (distance from 100 per cent collection of tax demanded). We do find, however, that half the ULBs in the samples have achieved the goal of 90 per cent efficiency as set by the JNNURM. We also find that there are variations in property tax collection across cities. While in some cities the collections are below sixty per cent (Kota), others have a much higher percentage of collection (Shivamoga and Pune).

We also see a variation in the TCR within the same city. For instance, Kota has a maximum TCR of 96.14 per cent in one year (2016-17) but a low TCR of 37.04 per cent in another (2013-14). Similarly, Vishakpatnam has an over collection of 265.52 per cent in the year 2015-16 but under collection of 24.42 per cent in 2017-18. Even in cities like Pune or Chennai, which have a high average TCR across five years (column 3), the minimum TCR (column 4) and maximum TCR (column 5) vary. In half of the cities in the sample, we also see tax collection exceeding the maximum tax demand in a single year (column 4) for Chennai, Pune, Indore, Vishakapatnam and Bilaspur.

2. Examining human resource allocation

Our second level of analysis examines the human resource capacity in the property tax departments in a set of sample cities. The human resources could affect the TCR in two ways: First, the technical capacity of the human resources to apply the rules correctly. For instance, the ability to correctly identify taxable properties, ascertain property values, apply the assessment formula to a given assessee and determine amounts due. Second, the number of personnel in the department could potentially affect the level of accuracy in tax functions. For instance, an inadequate number of resources could increase inaccuracies. In this analysis, we focus on the second aspect of human resources, the number the personnel to examine whether a higher number officers alone leads to a better TCR.

Methodology: We collected data on the number of officers in the property tax department in the sample cities for which this data was readily available. The cities for which this data was readily available were Chennai, Pune, Vishakapatnam, Shivamoga, Varanasi, Warangal and Bilaspur.

Given the paucity of data on the number of taxable properties in the city, we device an indicator to estimate the number of taxable properties in the city using proxies. For this, we first collect Census 2011 data on the number of households living in permanent structures within the municipal area. We then calculated the number of officers per 10,000 households. We also collect data on the total area (sq. km) of the city and compare this to the administrative strength.

Table 2 sets out the administrative strength of the property tax department, the number of households living in permanent structures within the municipal area, the estimated officer to households ratio (per 10,000 households) and the city area in the sample cities for which this data was available.

Table 2: Comparing city-wise human resource allocation and TCR

City	State	Average TCR (%)	Adminis-trative strength (no. of officers)	No. of households in permanent structures	Allocation of officers (per 10,000 households)	City area (sq. km)
Chennai	Tamil Nadu	90	276	10,40,948	3	1,189
Pune	Maharashtra	96.36	41	6,83,267	1	7,256.46
Vishakapatnam	Andhra Pradesh	114.29	56	4,25,409	1	6,501
Shivamoga	Karnataka	98.36	125	58,826	21	8,477.84
Varanasi	Uttar Pradesh	96	321	1,64,014	19	1,535
Warangal	Telangana	79.87	68	1,41,750	5	406
Bilaspur	Chattisgarh	90.2	80	57,292	14	6,377

Source: City municipal websites and Census 2011

Findings: We find that some cities with higher a TCR, also have a higher officer to households ratio. For instance, Shivamoga has the highest TCR and the highest level of administrative strength. However, we see that cities with a low TCR, do not have the lowest administrative strength. For instance, Warangal is has the lowest TCR in the sample, but not the lowest officer to households ratio.

We observe that cities with similar TCR scores do not have similar personnel to households ratios. For instance, the officer to household ratios for similar TCR cities such as Varanasi and Pune or Chennai and Bilaspur are false, demonstrating a variation in human resource allocation even across cities with the same TCR levels. Further, cities with a larger area also do not always have a higher allocation of officers. For instance, Varanasi has a smaller area than Vishakapatnam, but a higher number of officers. Chennai has a smaller area than Shivamoga, but a higher number of officers than Shivamogga. We find not consistent pattern in the manner in which human resource allocation is done across cities.

Limitations: (i) We use the number of households living in permanent structures within the municipal limit as a proxy for the number of taxable properties in a city. This does not take into account the commercial property coverage of a city. (ii) Another proxy for the number of properties in a city is the area of a city, however, a larger city may be less dense and have fewer properties than a smaller and more dense city which may have a larger number of properties (iii) The estimates are only as accurate as the data available on government websites.

Learnings for property tax reforms

The findings from our case study offer insights for property tax policy reforms in ULBs:

Presumption of adequate capacity: Our study finds deficiencies in institutional capacity in tax collections across ULBs. From a reforms perspective, even if tax rates are increased, unless the present institutional capacity is improved, revenues from property taxes might continue to be affected. Further, while our study examines the institutional capacity in one tax function - tax collections, it is likely that there are deficiencies even across other functions. This may affect the outcomes from the current set of policy interventions which focus on increasing revenues by changing the design of the tax system rather than fixing the problems in the administration.

Effect of variation across ULBs: Our findings demonstrate a variation in the capacity of ULBs to carry out property taxation. We are therefore likely to see varying levels of success even for the same set of reforms across ULBs because of the different levels of institutional capacity.

Inconsistencies within ULBs: We not only see a variation in the TCR across ULBs, we also see variation in the TCR within the same ULB across different years. This is demonstrated by the variation in the minimum and maximum collection ratios of cities in our sample. This means that even cities with an overall higher average capacity might have low or high collections in a given year. For instance, the minimum TCR in Vishakapatnam is 24.42 per cent across five years and the maximum is 265.52 per cent. Similarly, the minimum TCR in Kota across five years is 37.04 and the maximum is 96.14 indicating a wide variation in the tax collections even by the same authority. While it is unclear why this is the case, this indicates some inconsistencies in capacity levels.

Management of human resources: Our findings indicate that the institutional capacity in property tax systems is not only a function of administrative capacity in terms of the number of personnel. For instance, while we see that Shivamoga has the highest officer to households ratio and the highest TCR, Pune had a lower officer to households ratio but has the second highest TCR. Similarly, despite having a similar TCR, Chennai and Bilaspur have very different human resource allocations. Therefore, increasing the strength of the administration alone may not yield better outcomes in the assessment and collection of property taxes. Instead, improving the technical capabilities of the administration or effective utilisation of the existing human resource capacity by ULBs might yield results. For instance, Bahl et. al 2013, suggest that tax authorities in developing countries are unable to capture economies of scale.

A new approach to measurement

In the course of this study, we found that the existing approach to the measurement of tax functions in the literature has two main problems. First, studies examine tax collections as an isolated administrative function and not as a product of the preceding tax functions. Second, because of this, these studies tacitly assume that the administrative processes that precede tax collections, such as the tax assessment and all the processes that make up tax assessment are accurately done. This in turn affects the diagnosis of the problems in administration.

We posit instead, that the property tax system comprises of a series of interconnected administrative processes that determine the overall outcome of revenue generation from property tax. Each process determines the success of the next. Errors in administering one process will have repercussions for the accuracy and success of the processes and functions that follow. For instance, tax collection is not just a product of the enforcement function of the ULBs. It is also a function of accurately assessing taxes due. Similarly, the accuracy of the tax assessment function is determined by (i) the maintenance of a database of all taxable properties in the city (ii) regular updation of this database, (iii) correct valuation of the properties in the database, (iv) correct application of the tax formula for these valued properties and (v) determining permitted exemptions. Table 3 set outs an indicative list of the functions that work to together form a chain of administrative processes which ultimately determine tax collections.

Table 3: Indicative list of processes involved in tax assessment and collection

Function	Processes
A. Accurate tax assessment	i. Maintaining a property records database of all taxable properties
	ii. Updating the property records database
	iii. Correct valuation of properties in the database
	iv. Correct application of the tax formula
	v. Correct determination of exemptions and concessions
B. Accurate tax collection	i. Making a correct tax demand (= Ai+Aii+Aii+Aiv+Av)
	ii. Enforcement to collect tax demanded

When we break down administrative functions into smaller processes and view each function as being linked to the next, the result of measuring of any one administrative function will provide us with insights on the accuracy of not just the function being measured but also the previous functions in the chain of administration. For instance, the TCR of a ULB is an indication of the institutional capacity of not only tax collection but also of assessing tax correctly and getting the processes associated with the functions of assessment and then collection right. In this view, a TCR of 90 per cent potentially indicates not only a failure by the ULB to recover 10 per cent of the tax demanded but also potential inaccuracies in assessment for 10 per cent of the tax demanded, leading to appeals and pending cases on account of which payment might not have been done by assesses.

Our learnings from the case study, therefore, are not indicative of capacity issues just in tax collection, but could also be on account of inaccurate tax assessments. This analysis, in line with reports on poor tax assessments in ULBs.

This approach has two advantages over the traditional approach. It breaks down and highlights all the processes involved in property tax administration. In doing so, it allows us to more accurately diagnose the specific function at which the process fails.

Conclusion

We carried out this case study to demonstrate the importance of institutional capacity in the property tax system of ULBs. We have two main findings which are as follows:

First, we demonstrate that the problems in institutional capacity exist across a majority of our sample cities. This signals that there are potential capacity problems in many if not all cities across India. It is unclear therefore whether the present set of interventions to increase property tax revenues will yield optimum outcomes. Our findings demonstrate that it is important to precede policy interventions with the measurement of institutional capacity in the property tax system. We cannot presume the existence of adequate institutional capacity. This is in line with the literature that suggests that infrastructure and institutions are the foundation for achieving effective policy outcomes (Kelkar and Shah 2019, Pritchett et al 2012, Subramaniam and Felman 2021).

Second, deficits in the TCR are not just signals for improving capacity in tax collections and enforcement but also in tax assessment and all allied administrative processes. It is therefore difficult to diagnose which part of the property tax administration requires reform. A failure at any one point of the system has repercussions for the remaining functions. We, therefore, need a comprehensive framework for measuring institutional capacity at the level of each process of the property tax system, some of which are illustrated in Table 3.

Our study also demonstrates that while most cities have some way to go, some cities have achieved higher levels of TCR than others, indicating that they have perhaps learnt to do assessments and collections better than others. We also see that some cities appear to have achieved better utilisation of administrative strength than others. There are perhaps lessons in tax assessment and collection in these cities that other ULBs in India can learn from. A case study of the good practices in collection and assessment in these cities might offer insights for better property tax administration in other cities in India.

References

Arvind Subramaniam and Josh Felman, The Economy and Budget: Diagnosis and Suggestions, January 2021.

Matt Andrews, Lant Pritchett, Michael Woolcock, Looking Like a State: Techniques of Persistent Failure in State Capability for Implementation, CID Working Paper No. 239 June 2012.

O. P Mathur, Debdulal Thakur and Nilesh Rajyadhyaksha, Urban Property Tax Potential in India, National Institute of Public Finance and Policy, 2009.

Roy W. Bahl, Johannes F. Linn and Deborah L. Wetzel, Governing and Financing Metropolitan Areas in the Developing World, Lincoln Institute of Land Policy, Pages 1-30, 2013.

Simanti Bandyopadhyay, Municipal Finance in India: Some Critical Issues, ICPP Working Papers 14-21. May 2014.

Roy Kelly, Making the Property Tax Work, ICEPP Working Papers. 42, 2013.

Vijay Kelkar, Ajay Shah, In Service of the Republic: The Art and Science of Economic Policy, 2019.

World Bank, India: Urban Property Taxes in Selected States, 2004.

Diya Uday is a senior researcher at the Finance Research Group, Mumbai. The author would like to thank Ajay Shah, Susan Thomas and the anonymous referee for their valuable insights, comments and guidance for this work.

Do stamp duties affect transaction volumes? A study of real estate transactions in Mumbai

by Diya Uday.

The real estate market in India has many factors that cause price inefficiencies. The outcome is that investors will stay away from real estate markets as long as these inefficiencies exist. So how can market efficiency and thereby participation be increased? The Coasian answer is that a market will yield efficient outcomes in the absence of transaction costs.

What constitutes real estate transaction costs in India? Transaction costs are of two kinds: manifest and hidden. Manifest costs are apparent. They are borne by the parties to the transaction and not the market as a whole. They are quantifiable and therefore lend themselves well to observation and possibly measurement. Hidden costs are not statutorily imposed by the government but they increase the cost of conducting transactions. They may be identified but are difficult to quantify and therefore do not lend themselves well to measurement. Some of these are borne by the parties to the transaction while others hidden costs such as price distortions are borne by the market as a whole. In a previous article we argued that price distortions are the unseen consequences of restrictive land market regulations (Uday, 2019). The table summarises this typology of transaction costs with some examples.

Typology of land market transaction costs in India

Manifest transaction costs	Hidden transaction costs
Stamp duties	Title searches
Registration charges	Intermediary charges
Cost of updating government records	Price distortions

Having identified some transaction costs, we attempted to determine the effect of stamp duties on transaction volumes, using Mumbai as the environment under examination. We ask the question: Do transaction volumes change after an increase in stamp duty?

Our motivation for conducting this study is to gain some insights on the relationship between stamp duties as a transaction cost and transaction volumes in the Indian real estate market.

In the literature we see that stamp duties are considered as taxes that cause market inefficiencies (Maatanen and Tervio, 2019). They discourage mutually beneficial transactions and ensure that properties are not held by the people who value them the most (Mirrles et al., 2011). An increase in stamp duty leads to a decline in the number of sales (Dachis et al., 2012). This decline is attributable to a reduction in property prices (Davidoff and Leigh, 2013; Dachis et al., 2012). Similarly, elimination of stamp duties, increases transaction volumes (Best and Kleven, 2018). The literature that examines the effect of stamp duty interventions on transactions uniformly finds that transaction volumes react to stamp duty interventions.

Methodology and findings

For this study, we selected three types of transactions: conveyance, lease and mortgage. We first extracted transaction volumes data for these transaction types in Mumbai, from the website of the Department of Registration and Stamps in Maharashtra. We then calculated the total yearly transaction volumes for each of the three transaction types across all the years for which the data was available (July 2012 onwards). We extracted all notifications which amended stamp duty rates for the relevant period of the study (July 2012 - February 2020). From these, we selected the notifications applicable to conveyances, leases and mortgages only. The selected notifications were then sorted by month and year.The following interventions were studied:

• Maharashtra Tax Laws (Levy, Amendment and Validation) Act, 2012 notified on 15 April, 2012
• Maharashtra Stamp (Amendment) Act, 2015 notified on 24 April, 2015
• Maharashtra Stamp (Second Amendment) Act, 2017 notified on 7 September, 2017
• Mumbai Municipal Corporation (Second Amendment) Act, 2018 notified on 17 December, 2019

These interventions were overlaid on the transaction volumes data in the appropriate point in time. A cross-sectional observation of the effect of the increases in stamp duty on each transaction type was done.

This analysis yields the following observations:

• Conveyance transactions: There are three relevant interventions in the form of amendments to the law on stamp duty rates for conveyances for the period under examination. The first amendment was notified on April 25, 2012 by Maharashtra Tax Laws (Levy, Amendment and Validation) Act, 2012. Under this amendment the stamp duty on conveyances within the limits of the Municipal Corporation was increased from 4 per cent to 5 per cent of the market value of the property. The stamp duty for conveyances within the Municipal Council and cantonment areas was increased from 3 per cent to 4 per cent of the market value of the property. In both cases, there was an increase of 1 per cent. The second amendment was notified on September 7, 2017 by Maharashtra Stamp (Second Amendment) Act, 2017. Under this amendment the stamp duty payable on transactions in Municipal Council and Cantonment areas was increased from 4 per cent to 5 per cent of the market value. The third intervention was the Mumbai Municipal Corporation (Second Amendment) Act, 2019 notified on December 17, 2019. Under this amendment a surcharge of 1 per cent is charged on conveyances in the certain areas. In these places, the stamp duty payable on conveyance transactions is effectively increased to from 5 per cent to 6 per cent of the market value.

  For the first stamp duty intervention in 2012 we do not observe a drop in the transaction volumes. In fact we see a steady increase in the year 2012 despite an increase in the rate of stamp duty until 2013. After 2013, the transaction volumes are on an upward trend until 2018. We do not observe an immediate drop in transaction volumes after the second intervention. We see that the upward trend from 2016 continues despite an intervening increase in stamp duty. From the year 2018 we observe a drop in the number of registered conveyance transactions. At its lowest point, the number of registrations were the lowest since the later half of 2012. The downward trend from the year 2018 continues into 2019.

  One might theorise that the drop in transaction volumes from 2018 and into 2019 are the effect of the stamp duty interventions in 2017 and 2019. However, a look at the trends in transaction volumes of leases and mortgages also reveals a fall in the number of registered transactions from the year 2018. This indicates that the reduction in transaction volumes is likely to be on account of some other variable that affected the real estate market as a whole rather than on account of the increase in stamp duty rates. Figure 1 depicts conveyance transaction volumes in Mumbai for the period from July 2012 to February 2020. The dotted lines represent relevant stamp duty interventions in the month and year of the intervention.



• Lease transactions: There are two relevant interventions on stamp duty rates for lease transactions in the period under examination. The first intervention was the Maharashtra Tax Laws (Levy, Amendment and Validation) Act, 2012 notified on 15 April, 2012. This amendment applied to conveyances and not leases directly. However, we are considering this a relevant intervention for leases because the stamp duty for lease transactions is a percentage of the stamp duty for conveyance transactions. Therefore, any change in the stamp duty for conveyances will cause a consequent change to the stamp duty for lease transactions. Since the 2012 amendment increased the stamp duty for conveyances, it consequently increased the stamp duty for lease transactions. The second intervention for lease transactions was the Maharashtra Stamp (Second Amendment) Act, 2017 notified on September 7, 2017. Again, this amendment did not directly apply to lease transactions however, given the linkage between the stamp duty payable on conveyances and leases as explained above, we have included this amendment as a relevant intervention for lease transactions. Under this amendment, the stamp duty for conveyances was increased, thereby increasing the stamp duty for lease transactions.

  We observe no immediate effect of the increase in stamp duty on lease transaction volumes for both interventions. However, as observed with conveyance transactions we see a continuing upward trend in transaction volumes in the period immediately after the increases in the stamp duty rates by both interventions. After 2018, we observe a downward trend in transaction volumes. This continues into 2019. This trend has been observed with conveyance and mortgage transactions as well and is therefore, likely on account of some other variable affecting the real estate market as a whole rather than the increase in stamp duty. Figure 2 depicts lease transaction volumes in Mumbai for the period from July 2012 to February 2020. The dotted lines represent relevant stamp duty interventions in the month and year of the intervention.



• Mortgage transactions: There are four relevant interventions on stamp duty rates in the period under examination. The first intervention was the Maharashtra Tax Laws (Levy, Amendment and Validation) Act, 2012 notified on 15 April, 2012. While this amendment was for conveyances and not directly for mortgages, we consider this a relevant intervention because the stamp duty for mortgage transactions is a percentage of the stamp duty for conveyance transactions. Therefore, any amendment to the stamp duty for conveyances is a relevant intervention for mortgage transactions. Since the 2012 amendment increased the stamp duty for conveyances, it consequently increased the stamp duty for mortgage transactions as well. The second intervention was the Maharashtra Stamp (Amendment) Act, 2015 notified on April 24, 2015. Under this amendment, the stamp duty payable on a mortgage was increased from five hundred rupees to 0.5 per cent of the amount secured by the mortgage subject to a maximum of ten lakhs. The third intervention was notified on September 7, 2017 by the Maharashtra Stamp (Second Amendment) Act, 2017 whereby the stamp duty for some conveyances was increased to 5 per cent of the market value. Given the linkage between stamp duties for conveyances and mortgages, we have considered this a relevant intervention. The fourth intervention, is the Mumbai Municipal Corporation (Second Amendment) Act, 2019 notified on December 17, 2019. Under this amendment a surcharge of 1 per cent is charged on mortgages in the certain areas, increasing the overall stamp duty payable on mortgage transactions.

  As observed in case of lease and conveyance transactions, we observe no immediate reduction in the transaction volumes after increase in stamp duty by the 2012 intervention. We do observe a fall in the transaction volumes immediately after the 2015 amendment either.This appears to be a continuation of a downward trend in mortgage transaction volumes from the beginning of 2015. While we cannot say for certain, perhaps the sharpness of the downward trend could be affected by the increase in stamp duty. One may have observed a more gradual decline in the downward trend if the stamp duty has remained unchanged. We cannot however, verify this. After the short-term reduction, transaction volumes for mortgages increase until 2018 when a a sharp decrease in the transaction volume is observable. This downturn is consistent with the downturn we observe in respect of the transaction volumes of conveyances and leases and we therefore, cannot attribute this to increased stamp duties alone. Figure 3 depicts mortgage transaction volumes in Mumbai for the period from July 2012 to February 2020. The dotted lines represent relevant stamp duty interventions in the month and year of the intervention.

Limitations:

• The study has been done for the period from July 2012 upto February 2020. This is on account of the lack of published transactions volume data for the period prior to July 2012 from the website of the Department of Registration and Stamps in Maharashtra.
• This study observes the effects of stamp duty interventions on three types of real estate transactions only.
• The increases in stamp duties have not been significant.
• We have not controlled for the effects of other events in the real estate market on transaction volumes. However, we proceed on the assumption that a change in the market as a whole will affect all three types of major transactions. For example, an increase in interest rates for home loans will affect not just conveyances but also mortgage transactions and possibly leases. The observations for 2018 are in-line with this reasoning.
• The represented data is year-on-year and does not report month-on-month changes to transaction volumes.
• The sharpness of the increase in transactions in the year 2012 maybe smaller than what is being observed as we only have data from July 2012.
• The data does not distinguish between primary and secondary market transactions or residential and commercial transactions.

Conclusion

We undertook this study to determine the effect of stamp duties on transaction volumes by attempting to answer the question: Do transaction volumes change after an increase in stamp duty? Our motivation for doing so was to gain insights on the relationship between stamp duty as a transaction cost and transaction volumes in the Indian real estate market.

We did not observe any immediate decreases in transaction volumes in Mumbai pursuant to increases in stamp duties. This is a departure from global literature which suggests that transaction volumes decline with increases in stamp duties. However, our data offers some insights which are as follows:

First, while we may not observe immediate changes in any transaction volumes pursuant to stamp duty interventions, we observe that all three types of transactions follow some common trends. For example, there is an increase in transaction volumes across all transactions types in 2017 and a significant drop in transactions across all transaction types from the year 2018. This decline continues into 2019. This is significant because it indicates the existence of market variables that affect all transactions regardless of the type of transaction. These variables appear to have a possibly greater impact on transaction volumes than changes in stamp duties do.

Further, given that stamp duties are among the larger manifest costs, it is likely that we will not be able to observe any changes in transaction volumes if smaller manifest costs are changed. The variables affecting all transactions types in common are therefore perhaps hidden costs.

Second, the lack of volatility in the period immediately following an intervention may be indicative of a thin market where only the bare minimum on-market transactions are taking place. Transaction volumes are therefore not likely to be affected by rises in stamp duty rates. This confirms our view that despite the high market value of real estate assets in Mumbai, transactions are likely to be taking place out of necessity rather than for investment purposes, unlike in other countries where such studies have been conducted.

Third, we know that real estate transactions in India have a cash component. Given this, transactions are unlikely to be significantly affected by small increases in stamp duty.

Does this also mean that the converse is true? Will reductions in stamp duties increase transaction volumes in the real estate market in India? Literature indicates that significant changes such as tax holidays have more sizeable effects on transactions (Besley et al., 2014). For instance, a temporary elimination of transaction taxes was found to increase real estate market activity by twenty per cent in the UK (Best and Kleven, 2018). Less significant reductions in stamp duties are unlikely to have a sustained and significant effect on market participation, given the state of the Indian real estate market. While small reductions in stamp duty rates may seem like low hanging fruit with which to fix the problems of a thin market, this study indicates that without addressing the other variables that appear to be affecting transaction volumes, it is likely to be a blunt policy intervention. However, governments tend to lean towards offering stamp duty concessions to boost market participation. This is not the shot in the arm that the real estate market needs.

Since the Indian real estate market appears to present a unique case, the answer to increasing participation perhaps lies in a bundle of interventions aimed at addressing and reducing both hidden and manifest transaction costs. Some of these could be the removal of land market restrictions that have distortionary effects on the market (Uday, 2019), increasing information symmetry by creating more comprehensive land records (Shaikh and Uday, 2018) and the creation of streamlined market places which allow easy trading of real estate assets.

References

Besley et al., 2014, The Incidence of Transaction Taxes: Evidence from a Stamp Duty Holiday, Timothy Besley, Neil Meads and Paolo Surico, Journal of Public Economics, Volume 119, November 2014.

Best and Kleven, 2018, Housing Market Responses to Transaction Taxes: Evidence From Notches and Stimulus in the UK, Michael Carlos Best and Henrick Jacobsen Kleven, The Review of Economic Studies, Volume 85, Issue 1, January 2018.

Dachis et al., 2012, The Effects of Land Transfer Taxes on Real Estate Markets: Evidence from the Natural Experiment in Toronto, Ben Dachis, Giles Duranton
and Mathew A. Turner, Journal of Economic Geography, Volume 12,
November 27, 2012.

Davidoff and Leigh, 2013, How Do Stamp Duties Affect the Housing Market?, Ian Davidoff and Andrew Leigh, Economic Society of Australia, Volume 89 No. 286, September 2013.

Maatanen and Tervio, 2019, Welfare Effects of Housing Transaction Taxes: A Quantitative Analysis with an Assignment Model, Niku Maattanen and Marko Tervio, European Research Council, 2011.

Mirrlees et al., 2011, Tax by design, James Mirrlees, Stuart Adam, Tim Besley, Richard Blundell, Stephen Bond, Robert Chote, Malcolm Gammie, Paul Johnson, Gareth Myles and James M. Poterba, Institute for Fiscal Studies, Economic and Social Research Council, September 2011.

Shaikh and Uday, 2018, Rethinking urban land records: A case study of Mumbai, Gausia Shaikh and Diya Uday, The Leap Blog, November 1, 2018.

Uday, 2019, How land laws create dead capital, Diya Uday, The Leap Blog, July 15, 2019.

 

Diya Uday is a senior researcher at the Finance Research Group, Mumbai and visiting faculty at the Tata Institute of Social Science, Mumbai. The author would like to thank Ajay Shah and the two anonymous referees for their comments and suggestions.

Income Tax Scorecard: Can there be a holistic view of the Budget proposals?

by Surya Prakash B S and Kangan Upadhye.

Is it possible to have a unified view of a legislation that pieces together its various provisions? In our paper we present a novel methodology that measures direct tax provisions of the Finance Bill, 2017 (Government of India Budget, 2017) presented by the Union Government of India to the Lok Sabha, against accepted principles of taxation and tax system design.

The Finance Bill seeks to amend many parts of the Income Tax Act and consequently impacts sections of the society differently. Popular media coverage tends to focus on impact on some sectors or a few controversial measures. This is natural given that budget making is a contentious exercise that needs to address concerns from all quarters. Our methodology avoids analysis either from the perspective of the state (revenue mobilisation) or the taxpayers (revenue minimisation). It measures each direct tax provision to see how well they perform against principles of taxation.

Our method consists of a set of “attributes” and “impacts” for which we assign scores. Attributes relate to the objective features of the provisions: we categorise provisions/amendments into compliance, substantive, procedural, exemptions, collection and recovery, anti-avoidance, penal provisions, international taxation and adjudication machinery. A total of 97 provisions in the Finance Bill 2017 are categorised under these attributes.  A single provision could have more than one attribute. For example, the amendments proposed to section 13A which is related to exemption from paying income-tax for political parties, to discourage the cash transactions and to bring transparency about funding political parties is an example of a provision categorised under more than one attribute. It is categorised not only under compliance but also recognised as substantive.

A summary of the above step is depicted below. It can be observed that the Finance Bill, 2017 contained 26 provisions relating to ‘Exemptions’, 22 that were ‘Substantive’ and 21 that made changes to ‘Computation’.

Since the provisions could have various levels of impact, we go on to score them on a seven point scale (-3 to +3) against each of the following seven principles of an ideal tax system design:

1. Transparency: Whether there have been any prior public consultations.
2. Simplicity: Whether the provisions makes levy and collection simpler.
3. Stability: Whether the provisions are prospective or retrospective in nature.
4. Discretionary power: Whether and to what extent discretionary power of tax officers have been enhanced or decreased.
5. Tax rates: Whether and by how much have tax rates have been decreased. Lowering tax rates get higher scores.
6. Tax base: Is the income on which tax is levied increased or decreased. As a principle when more types of income are charged, a higher score is given. As a corollary, exemptions are scored lower.
7. Number of taxpayers: Provisions that extend the levy to more taxpayers have higher score. If a few of them are exempted it gets a lower score.

The scores are calculated in percentage terms (after converting negative scores to positive for ease of comparison) and the results are as depicted in the figure below.

The provisions in the bill score fairly well on simplicity, stability and discretion parameters with moderate scores on taxpayers, tax base and rates relative to the others. The provisions perform poorly on the transparency parameter.

Our results from the framework do support the popular thinking about the 2017 financial bill the way industry experts and practitioners have interpreted in the budget discourse (Chakrabarti et al. 2017).  For example, the amendment to section 132  which empowers relevant authorities under the Income Tax Act, 1961 to carry out a search or seizure without having to declare reason to believe such person or any authority or appellate tribunal, previously required under section 132 of the Income Tax Act, 1961 (Government of India Budget, 2017).

The earlier provisions empowered authorities to enter and search any building, person if they had a reason to believe that the person had failed to disclose material facts. As critics argue without having a reason to declare for search or seizure this power can be misused to conduct arbitrary investigations leading to harrassments and tax terrorism. This provision was rated low on all the parameters. By adopting such a systematic approach to evaluating tax amendments, this could serve as an evidence informed input to the design of taxes in our budgeting system.

To the best of our knowledge, we have not come across any similar methodology in use in any major economy. The methodology is objective, the impact parameters and the attributes categorised are transparent, and these assumptions can be revised by those that seek to view the results based on alternate views or perform a sensitivity analysis.

We are aware that scores given can be made more accurate through data based post hoc impact assessments. Further research is required on this aspect.
The practical value of the results from our approach are many. It would a) enable us to base the study of the Finance Acts against principles of a good tax system b) provide a comprehensive view of the taxation system rather than a view traditionally restricted to revenue objectives or taxpayer hardship; and c) enable a mapping of the trajectory of tax policy by allowing us to compare across years. It can be viewed as a first step towards making the budget-making process transparent, empirical, and inclusive. The methodology used in this paper can potentially also be used to study other legislation and amendments.

The authors are researchers at Daksh. The authors are thankful to Shreya Rao and Shweta Mallya for their contribution during the conceptualisation phase of this paper. This paper was presented at the APU-NIPFP workshop Strengthening the Republic #1, January 11, 2020.

Notes on Union Budget 2017-18

by Suyash Rai.

This budget was unique in the scale and intensity of anticipatory anxiety. With prior assumptions about possibilities of policymaking in India unsettled, many were worried about government's next move. Could the government add two-three percentage points to the fiscal deficit to launch a spending spree? Could there be a loan waiver, Universal Basic Income, or Massive tax cuts? It turned out to be a textbook case of workmanlike budget-making - not dazzling, but reasonably prudent. It is heartening to see that our politics can produce this budget in such a situation. One hopes that the government works consistently to reduce policy uncertainty. The budget is a step in that direction.

A budget should be judged primarily on fiscal management, and how it links to larger policy priorities. Each budget tells a story about government's priorities. However, since most of budgeting is not zero-based, important reforms tend to span several budgets. It is important to consider the budget in the context of medium-term fiscal strategy of the government, and the fiscal issues that need to be addressed in medium term. Changes to the systems of raising, allocating and spending resources are also relevant for evaluating a budget. Further, since the budget is made within a fiscal responsibility framework, changes to the framework are also pertinent. Finally, changes to the formats of reporting and accounting are also relevant.

The budget scores reasonably well on fiscal prudence, changes in the reporting formats, and reform of the budget process. It signals good fiscal marksmanship, but we cannot know this for sure until the data on actuals becomes available. As budgets in India go, this is a good housekeeping performance. However, if we take a medium-term perspective, we see that the budget indicates progress on some fronts, but does not do much to address most of the persistent fiscal issues in India. Further, some of the proposals in the Finance Bill raise worries about the future of tax administration.

Reform of reporting formats

This is the first budget without the plan-non plan expenditure distinction. The reporting formats no longer include this distinction. The government has used this opportunity to change the reporting formats. New statements have been added, annexes have been done away with (most of them are included as statements now), some statements have been omitted, and the formats of certain statements have been changed. Here is a summary of the key changes in the reporting format of Volume I (now-called "Expenditure Profile") of the Expenditure Budget:

• Changes in reported categories of expenditure: at summary level (Statement 1), the expenditure is now disaggregated into six categories:
  1. Establishment expenditures of the Centre: this category includes salaries, medical expenses, wages, allowances, travel expenses, office expenses, training, professional services, rent paid, taxes, pensions, etc. This is expenditure that is incurred for maintaining the administrative entity, as opposed to expenditure incurred on programme and schemes.
  2. Central Sector Schemes: these are schemes for which the central government provides the entire budgetary support, and most of them are implemented by the central government.
  3. Transfers under centrally sponsored schemes: for these schemes, the central government shares the budgetary support with State or Union Territory government (based on a sharing pattern determined by the central government). These schemes are implemented by the State/UT governments.
  4. Other central expenditure: this category includes expenditure on CPSEs and Autonomous Bodies.
  5. Finance Commission Transfers: these are grants given under Article 275(1) of the Constitution to urban and rural local bodies, grant-in-aid to State Disaster Response Funds (SDRF), and post-devolution revenue deficit grant. The revenue deficit grant is meant to cover gap in revenue expenditure after taking into account all the sources of revenue for states. Based on 14th Finance Commission's recommendations, 11 states receive these grants, and about a third of the grant goes to Jammu and Kashmir.
  6. Other transfers (to States): this mainly includes additional central assistance for externally aided projects (given as grants or block loans), and special assistance to states.

  In the summary statement, these six categories replace the categories of "plan", "non-plan" and "central assistance for state/UT plans". Continuing with the previous budgets, the "resources of public enterprises" are also reported. These include internal resources (accruals), bonds/debentures, external commercial borrowings/suppliers credit, and other resources, but do not include budgetary support to these enterprises.

• Statements based on categories of expenditures: probably the most useful inclusions in the new format are separate statements on centrally sponsored schemes (Statement 4A) and central sector schemes (Statement 4B) under various ministries, as well as a statement summarising the scheme category-wise expenditure for each Ministry (with aggregates given separately for centrally sponsored and central sector schemes). There is also a statement on allocation for important schemes (Statement 4C), which includes the major allocations under all the expenditure categories - this information was earlier scattered across various budget statements. Further, multiple statements (statements 4, 5 and 6) from the old format have been consolidated into one statement on subsidies and subsidy-related schemes (Statement 7).


• Statements on transfers to States/Union Territories: there is a statement on Transfers to Union Territories with legislatures (Statement 5), whihc includes Ministry/Department-wise information on transfers to these UTs. Earlier, this information was spread across multiple statements. Statement 18 provides information on "Transfer of Resources to States and Union Territories with Legislatures". These statements are consolidated. Earlier, this information was also spread across several statements covering plan and non-plan expenditure/outlay.


• Statements on public sector enterprises, autonomous bodies, and departmental commercial undertakings: the statements on "Assistance given to Autonomous/grantee bodies", "Resources of Public Enterprises", and "Investment in Public Enterprises" have been retained, as statements 30, 31, and 32, respectively, without change in format. The statement on "Grants-in-aid Salaries", which shows salary grants for autonomous bodies and schemes, has been made into Statement 29. This was an annex in the old format. The statement on departmental commerical undertakings, which was Statement 7 in the old format, is now Statement 8. It gives information on net budgetary support for revenue expenditure in these undertakings, after deducting the receipts of these undertakings.


• Statements on allocations for certain beneficiaries: These statements mostly remain the same, but some of them have been renamed:
  • The statement on Budget Provisions for Schemes for the Welfare of Children (Statement 22 in the old format) has been renamed "Allocation for the Welfare of Children" (Statement 12 in the new format).
  • The Gender Budget is Statement 13 in the new format.
  • In the old format, Statement 21 and 21A provided information about schemes under scheduled castes sub-plan and tribal sub-plan, respectively. These have been renamed as "Allocation for Welfare of Scheduled Castes" (Statement 10A) and "Allocation for Welfare of Scheduled Tribes" (Statement 10B)
  • Statement on "Budget Allocated by Ministries/Departments for the North Eastern Region" has been renamed "Allocation for the North Eastern Region" (Statement 11).
  The opportunity of removing plan-non plan distinction should be used to make these statements more comprehensive. Earlier, only plan expenditure towards welfare of these beneficiaries was captured in these statements, and it seems that the same expenditure is being captured in the renamed statements. Even the expenditure that was earlier classified as non-plan had components that benefited these beneficiary groups. Those allocations should also be included in these statements. For instance, the share of subsidies going towards these groups should be included in these statements. A beginning in this regard seems to have been made, as the interest subsidy, which was a non-plan expenditure in the earlier scheme of things, has been included in these statements. It wasn’t included in the statements till last year.
  • Changes in positions of annexes: the new format contains no annexes. Most of the annexes in the older format have now been converted into statements. Annex 1 (Budget provisions by Heads of Accounts) is now Statement 16. Annex 2(Reconciliation between Expenditure shown in Demands for Grants, Annual Financial Statement and Budget Provisions by Heads of Accounts) is now Statement 17. Annex 4 (Contributions to International Bodies) is now Statement 21. Annex 5 (Grants in Aid to Private Institutions/Organisations/Individuals) is now Statement 9. Annex 6 (grants for creation of capital assets) has been slightly modified and is now called "Allocation under the object head Grants for creation of Capital Assets" (Statement 6). It provides information about grants given to state and UT government for creation of capital assets, and goes into calculating the effective revenue deficit (revenue deficit minus these grants). Annex 7 (Estimated strength of Establishment and provisions therefor) is now Statement 22. Annex 7A (Budget Provisions under "Grants-in-aid Salaries") is now Statement 23.
  • Inclusion of statement on "Expenditure charged on the Consolidated Fund of India": a statement on all expenditures charged on the Consolidated Fund has been included. Earlier, this information was not included in the Expenditure Budget, but was provided in the Annual Financial Statement.
  • Inclusion of Railways Statements: Five statements from railway budget have been appended to the volume. These include statements on: Overview of Receipts and Expenditure; Railway Expenditure; Railway Receipts; Investment (Part A: Financials; Part B: Physical Targets); and Railways Reserve Funds.
  • Omissions: the annex on reliefs provided to CPSEs in the form of waiver, write-off, etc (Annex 2A) has been done away with. It used to give this information disaggregated by type of relief and the name of CPSE. The aggregate number is provided in Statement 17 (Reconciliation between Expenditure shown in Demands for Grants, Annual Financial Statement and Budget Provisions by Heads of Accounts). The decision to discontinue the annex may have been taken because this is a relatively small item of expenditure (budget for 2017-18 is Rs. 255 crore), but this is important for accountability for a type of expenditure that may be a sub-optimal use of public funds. In my view, the annex should have been continued as a statement. The annex on trends in expenditure (Annex 3) has also been discontinued. It used to provide ten-year trends for the major categories of expenditure. It was useful information for expenditure analysis. The statement could have been continued without the plan-non plan distinction.

  In my view, the new formats are easier to read and understand. They are more informative. An opportunity that has been missed, and should be considered in subsequent years, is to report consolidated spending on activities, which are spread over various schemes. For example, it will be useful to have a statement that gives information about spending in different areas of activity, such as health, education, skill development. Scheme-wise information is useful, but common citizens will be better able to understand the budget if the information is given in terms of areas of activities. With the removal of plan-non plan distinction this has become easier to do.

Reforms of the budget process

Advancing the budget day and merger of the Railway Budget and Union Budget are significant improvements over practices prevalent earlier. Advancing the budget day would help ensure that implementation of the new schemes can begin as soon as the financial year begins. It gives time to the departments and ministries to prepare for implementation and plan they spending. This is consistent with best practices in other countries.

The practice of presenting the Railway Budget separately was little more than a long-standing legacy. Although it is much bigger than other such enterprises, the Indian Railways is just one of the ten departmentally run commerical undertakings. Now, a single Appropriation Bill, including the estimates of Railways, will be prepared, instead of a separate Bill for Railways. Railways will get exemption from payment of dividend to General Revenues, and its Capital-at-charge would be wiped off. For the rest, things will remain the same. Ministry of Finance will continue to provide Gross Budgetary Support to Ministry of Railways towards meeting part of its capital expenditure, and Railways will continue to raise resources from market through Extra-Budgetary Resources to finance its capital expenditure.

Profile of expenditure and receipts

In 2016-17, government is budgeted to spend Rs. 19.78 lakh crore. Major components of the budget, which comprise about 75 percent of total expenditure budgeted for 2016-17 are (BE: Budget Estimate; RE: Revised Estimate):

Component	Expenditure (2016-1, BE) (in Rs. lakh crore)	Share in total (2016-17,BE) (in percent)	Expenditure (2016-17, RE) (in Rs. lakh crore)	Share in total (2016-17,RE) (in percent)	Expenditure (2017-18, BE) (in Rs. lakh crore)	Share in total (2017-18,BE) (in percent)
Interest payments	4.93	24.8	4.83	23.98	5.32	24.3
Defence, including defence pensions	3.4	17.2	3.45	17.13	3.6	16.76
Food subsidy	1.34	6.8	1.35	6.7	1.45	6.75
Finance Commission transfers to states and local bodies	1	5.1	0.99	4.9	1.03	4.8
Fertilizer subsidy	0.7	3.5	0.7	3.47	0.7	3.26
Roads and highways	0.58	2.9	0.52	2.6	0.65	3.02
Central armed police forces	0.5	2.5	0.52	2.6	0.55	2.56
Railways	0.45	2.3	0.46	2.29	0.55	2.56
MGNREGS	0.38	1.9	0.47	2.36	0.48	2.24
Petroleum Subsidy	0.29	1.5	0.27	1.37	0.25	1.16
Pensions	0.29	1.47	0.3	1.5	0.32	1.49
National Education Mission	0.27	1.36	0.27	1.34	0.29	1.37
National Health Mission	0.21	1.06	0.23	1.14	0.27	1.26
Pradhan Mantri Awas Yojana	0.20	1.01	0.21	1.04	0.29	1.35
Total Expenditure	19.78	100	20.14	100	21.47	100

For most of these, the revised estimate of expenditure during 2016-17 is quite close to the budgeted expenditure. For roads and highways, the revised estimates are about ten percent lower than the budgeted expenditure. For MGNREGS, the revised estimate is about 23 percent higher than the budgeted expenditure. Being a demand-driven scheme, this is not unusual for MGNREGS.

For 5 of these, the shares in budgeted expenditure for 2017-18 are stable. For defence, fertilizer subsidy, MGNREGS and petroleum subsidy, the share of expenditure is significantly lower. The share is significantly higher for Pradhan Mantri Awas Yojana, National Health Mission, Railways as well as Roads and Highways.

Fiscal marksmanship on expenditure side significantly depends on receipts. If receipts fall short, expenditures are cut or fiscal deficit target is not achieved. In 2016-17, the expenditure is budgeted to be financed by the following receipts (numbers in brackets are percentages of total receipts:

1. Tax revenues, net of transfers to states: Rs. 10.54 lakh crore (53.31 percent)
2. Non-tax revenues: Rs. 3.23 lakh crore of (16.34 percent), about two-thirds of which were budgeted to be from proceeds of spectrum auctions, and dividends from PSUs, banks, and the RBI)
3. Non-debt capital receipts: Rs. 0.67 lakh crore (3.39 percent), which include disinvestments of shares and recovery of loans.
4. Borrowings from various sources: Rs. 5.33 lakh crore (26.96 percent of expenditure). This is the fiscal deficit, which is budgeted to be 3.54 percent of the estimated GDP for 2016-17.

The revised estimates suggest that the government is likely to collect about 3 percent higher tax revenues than it had budgeted. While the revised estimates of direct tax collections are very close to the budget estimates, those for the indirect tax collections are different. Customs collections are estimated to fall short by 5.6 percent; excise duty collections are estimated to be 21.6 percent higher than budget estimates; and service tax collections 7.1 percent higher. The government may have set a modest target for growth in collection of excise duty, in anticipation of increase in crude oil prices. If crude oil prices had indeed risen sharply, government would have had to cut the excise duty on petroleum products, and that would have led to a smaller increase in collections. Fortunately for the government, this did not happen.

The non-tax revenue collections are estimated to be 3.7 percent higher than budgeted. This is primarily on account of 43 percent higher collection of dividends from CPSEs. This is estimated to more than make up for the shortfall in collections from spectrum auctions and interest receipts. In non-debt capital receipts, while the overall receipts are estimated to be close to the budgeted amount, proceeds from disinvestments are expected to fall short by about 20 percent. So, while a lot is going on in the components, the overall receipts are better than budgeted.

On fiscal marksmanship, three significant caveats are in order. First, the government's reported numbers sometimes turn out to be quite inaccurate. Recently, a CAG audit concluded that the fiscal deficit in 2015-16 was 4.31 percent of GDP, and not 3.9 percent, as was reported by the government. It is a cause for concern that the government's reporting of actuals was off by 0.41 percent of GDP (Rs. 53,146 crore). Second, due to advancement of the budget day, this year's revised estimates were prepared using lesser amount of data on expenditure/receipts, because of which the probability of actual expenditure/receipts being different from revised estimates is higher. Third, due to uncertainty created by demonetisation, it is difficult to make good GDP and revenue estimates for this year. The budget has taken the GDP number from the economic survey, which differs considerably from the advance estimates put out by the CSO in January. Any numbers reported as percentage of GDP are subject to changes in GDP estimates.

Fiscal prudence

According to the revised estimates, the government is expected to achieve its fiscal deficit target (3.5 percent of GDP) for 2016-17, and has set a fiscal deficit target for 2017-18 (3.24 percent) that is close to the roadmap given in the Medium Term Fiscal Policy (MTFP) statement two years ago (3 percent). The fiscal deficit target for 2018-19 and 2019-20 is 3 percent. In a rare instance, government is expected to do better than its target for revenue deficit (difference between revenue expenditure and revenue receipts). The target was set at 2.3 percent of GDP, but the revised estimates suggest that the revenue deficit this year will be 2.1 percent. This is because of higher tax and non-tax revenue collections, while the revenue expenditure is estimated to be along the budgeted lines. For 2017-18, the target is set at 1.9 percent, which is slightly higher than 1.8 percent target laid down in last year's MTFP statement. The primary deficit (fiscal deficit minus interest payments - shows whether we are borrowing to pay interest on borrowings) is estimated to be the same as budgeted (0.3 percent of GDP), and is budgeted at 0.1 percent in 2017-18.

The GDP estimates suggest that government expenditure is the main driver of growth in 2016-17, while growth in other types of expenditure is likely to be sluggish (private investment is estimated to fall). The strategy of using public investment to crowd in private investment was launched about two years ago, and it seems to have yielded underwhelming results. Perhaps the government did not consider it wise to continue down this path for more time, and is now keen to use other instruments to encourage private investments. It will have to undertake a sustained reform programme to boost private investments in the next few years.

There are several pathways to fiscal consolidation. Fiscal consolidation may involve a combination of: cutting expenditure, increasing tax revenues, increasing non-debt capital receipts (especially disinvestment and privatisation), and raising non-tax revenues (especially through user charges). The fiscal consolidation budgeted for 2017-18 is 0.3 percent of the GDP projected for the year, or about 0.5 lakh crore. How is this being achieved?

On the receipts side, the budgeted increases in net tax and disinvestment receipts are far smaller than the budgeted fall in non-tax revenues. Non-tax revenues are budgeted to fall because of lower collections from spectrum sale, and because Railways is no longer required to pay interest to government (since the budgets have been merged). So, in 2017-18, the receipts (excluding borrowings) are budgeted to be 9.5 percent of GDP - lower than they were in 2016-17 (9.82 percent). With these budgeted receipts, if expenditure grows at the rate at which GDP is projected to grow, the fiscal deficit in 2017-18 would be about 3.9 percent.

The government has bet on cuts in expenditure to achieve fiscal consolidation. This means that central government expenditure, as a percentage of GDP, is budgeted to shrink from 13.3 percent in 2016-17 (revised estimate) to 12.7 percent (budget estimate). Some of the areas where expenditure, in terms of percentage of GDP, has been cut are: defence (0.15), MGNREGS (0.04), fertilizer subsidy (0.04), food subsidy (0.04), petroleum subsidy (0.03), agriculture (0.02), and Pradhan Mantri Gram Sadak Yojana (0.02).

If most of these cuts were coming from expenditure reforms that improve efficiency of expenditure, i.e. get the same or better outcomes for smaller expenditure, they would hurt less. However, it is not clear if that is the case. Moreover, there is no significant change in the budgeted revenue-capital ratio of expenditure (from 86.1:13.9 to 85.6:14.4).

Since the economy seems to be in doldrums, a less contractionary consolidation pathway would have been more appropriate. The strategy should have comprised of substantive subsidy reforms (discussed later), an aggressive privatisation/disinvestment programme, raising non-tax revenues through user charges, and, to a lesser extent, other expenditure cuts. The budget targets for disinvestment are aggressive, but the targets for privatisation are lower than they were in 2016-17. This year, the government should have built the systems and processes for privatisation transactions, and reaped much higher receipts in 2017-18.

The deficit targets for 2017-18 must be considered in the context of fiscal uncertainties. The uncertainties of GST rollout, consequences of demonetisation, and external circumstances make it difficult to project macro indicators for 2017-18, and to achieve the targets. Government may need to review its strategy during the course of the year.

In summary, while the deficit targets are prudent, the strategy for achieving them seems sub-optimal, and due to uncertainties, it will take considerable dexterity to achieve them.

Medium-term fiscal issues

Much has been written about the specific expenditure decisions in this budget. Except in a few areas, there is not much change in allocations this year. There are certain fiscal issues that need to be addressed in medium to long-term. Let us consider some of them and what this recent budgets has done about them:

1. Declining share of capital expenditure in defence budget: a problematic trend in defence expenditure in India has been the declining share of capital expenditure. Capital expenditur is incurred on building the "material" component of India's defence capabilites. The share of "Capital Outlay" in the total defence budget has fallen from about 33 percent in 2006-07 to 20.8 percent in 2016-17 (RE). This year also seems to have followed the trend, and the share fell from 24.36 percent in 2015-16. The FM has announced a 20.6 percent increase in 2017-18 over revised estimates for 2016-17, to take the share of capital outlay to 24.03 percent. However, about half of this increase is because capital outlays on "research and development" and "Defence Ordinance Factories" have been moved from the demand titled "Ministry of Defence (Misc)" to the demand titled "capital outlay on defence services". Without these, the increase in capital outlay is just 9 percent, which is quite normal, and would take the share of capital outlay to 21.7 percent of the total defence budget. A problem in recent years has been that capital outlays have only been partially utilised, and a significant part of the allocation lapses.
   
   The One-Rank-One-Pension (OROP) decision has exacerbated the trend towards more revenue expenditure. The decision is quite consequential, and in my view, it was not a wise decision from a public finance and pension policy perspective. It increased the pension outlay, and because of the way it is designed, it has also introduced considerable uncertainty in budgeting for pensions (see my column on some of the problems with the OROP decision).
   
   Most of the modern restructuring of defence organisations in other countries has focused on trimming the forces of personnel, while building up and modernising the weapon system. China has reportedly completed an exercise that left its armed forces with 300,000 fewer personnel. The expenditure pattern in India may point at larger problems of procurement systems, policy priorities, and even our grand strategy. Since more than 70 percent of revenue expenditure in defence is incurred on pensions, pay and allowances, changing the pattern of expenditure will require some difficult strategic decisions that will have human resource consequences, which no government appears keen to take.
2. Poor outcomes of social sector schemes and the shrinking role of central government: Since the 14th Finance Commission recommended sharp increase in sharing of central taxes with states, the allocations to several schemes had to be cut. Also, the sharing patterns for centrally sponsored has been changed to reduce central government’s share in expenditure on these schemes. The role that the central government plays in designing the schemes now appears anachronous.
   
   The biggest challenge across social sector schemes has been: how to shift away from a focus on inputs, and (to a lesser extent) outputs, and focus on achieving outcomes. Take the example of school education. While we have done reasonable progress on improving inputs (building schools, hiring teachers, etc) and outputs (enrolments, access to schools, etc), India's performance on learning outcomes, as measured through learning tests, has been abysmal. In school education, central government spends just about 15 percent of the total expenditure (with sub-national government putting in the rest). It is now a marginal player in financing the sector, but continues to occupy the commanding heights on scheme planning and design. The challenge of improving outcomes varies from one context to another. Central government will need to rethink the way it uses its funds to drive change towards better outcome. States need to be given much more flexibility to innovate than they presently enjoy in practice.
   
   Although the FM did touch upon the issue of outcomes in education, a concrete proposal has not been forthcoming. This is the situation across various social sector schemes. Government seems intent on continuing with the set ways, without doing the needful to reorient the programmes towards achieving outcomes. Each sector poses its own unique challenges, and will have to find innovative ways to deal with this challenge.
3. Distortions in major subsidies: In 2004-05, subsidies were 12.56 percent of non-plan expenditure, and 9.22 percent of total expenditure. In 2013-14, subsidies were 23 percent of non-plan expenditure and 16.3 percent of total expenditure. In last three years, there has been some decline in the share of subsidies in expenditure (estimated to be 12.9 percent in 2016-17). This is mainly because of the favorable effect of benign crude oil prices, and savings from the direct benefit transfer programme. However, most of the substantive issues of subsidy reform remain. Let us consider the top three subsidies.
   

   Food subsidy:Food subsidy is the difference between the economic cost of food grains and the price that government charges for them. Economic cost includes the cost of procurement, transportation, storage, etc. Till 2001-02, the issue price at which food grains were sold to those above the poverty line was close to the economic cost. The price for households below the poverty line was about half of the economic costs, and Antyodaya households (poorest of the poor) were charged a nominal price (less than a quarter of the economic cost). Since then, the subsidy regime has changed. In 2002-2003, the price for grains supplied to households above the poverty line was reduced (from Rs. 8 to Rs. 6.1 per kg for wheat; from Rs. 11 to Rs. 7.95 per kg for common paddy), while prices for Antyodaya and below poverty line households were not changed. The prices for all categories of beneficiaries have remained the same since then. In these 15 years, the economic cost for wheat has increased by 163 percent, and for common paddy by 190 percent. This has led to a massive increase in food subsidy bill. The Food Security Act had frozen the issue price for food grains for certain beneficiaries for three years, but that window is now open. It is time the government reviewed the rationale for keeping issue prices frozen for so long. Subsidy should ideally be set as a percentage of economic cost, and therefore, the price should be revised annually to track the economic cost. At the same time, reforms should be undertaken to improve efficiency to keep economic costs in check.

   Fertilizer subsidy: since 2010, the gap between the subsidy for urea and that for other fertilizers has widened significantly. This is because urea was not included in the nutriend-based subsidy scheme that started in 2010. There is evidence to suggest that this distortion has led to excessive use of urea, which has hurt the nutrient balance of fertilizers being used. The proportion of nutrients in actual usage is now far from the ideal proportion (see Chapter 2 of the Economic Survey, 2013-14 for a discussion on this issue). Further, the subsidy regime in urea does not discourage inefficiency, as the subsidy amount varies from one manufacturer to another. These and other problems need to be addressed to develop a reasonable fertilizer subsidy regime. Many people have proposed good ideas, such as bringing urea into the nutrient-based subsidy regime, increasing the price of urea, moving towards direct transfer of subsidy, changing the urea subsidy regime to encourage efficiency, and so on.

   LPG subsidy: Although the direct benefit transfer programme is reported to have reduced the leakages from this scheme, the substantive issue of the reducing the amount of subsidised LPG sremains. There is significant evidence to show that most of the LPG subsidy goes to the non-poor. The poor use smaller amount of subsidised LPG, and therefore avail of smaller share of subsidy. Therefore, this is appropriately called a "middle class subsidy". The government had tried introducing a cap of 6 subsidised cylinders (about 85 kg of LPG) per annum, but this was later withdrawn, and the cap of 12 subsidised cylinders was restored. A good step taken last year was that the government has capped the per kg subsidy at a nominal amount, and over time, if this cap is not raised, the subsidy's salience will fall automatically. Government has also taken steps to expand access of LPG to poor households. Now, the government should consider reducing the cap of subsidised cylinders to 6 or 8.
4. Freeing up resources locked up in low-priority public sector enterprises: According to the public enterprise survey conducted by the Department of Public Enterprises, there are 298 Central Public Sector Enterprises - 235 active and 63 yet to commence commercial operations (as on March 31, 2015). A larger number of these are in sectors where there is a vibrant private sector, and there is no longer a need for public sector enterprises. However, the agenda of privatising public enterprises has been on the back burner since 2003, and the pace at which sick CPSEs are being closed is very slow. Although shares have been regularly disinvested, there have been no exits from enterprises in almost 14 years. This has meant that a large amount of resources, especially capital and land, are locked up in enterprises that should not be in the public sector at all. These resources could be freed up and deployed in higher priority areas. In each budget, a few thousand crores are allocated for these enterprises, and this money could also be used elsewhere. This is an unfinished agenda of the old industrial policy in India, and it also points at a significant allocative efficiency problem in India's fiscal management.
   
   In the budget speech of 2016-17, the FM had announced a plan for strategic disinvestment (aka privatisation) from certain CPSEs, and set a target of Rs. 20,500 crore. The revised estimates suggest that while the government is likely to overshoot the target for disinvestment by about 11 percent, it will fall short of the strategic disinvestment by almost 75 percent. The target for strategic disinvestment proceeds in 2017-18 has been set at Rs. 15,000 crore. This year, Government also plans to list certain insurance companies, and collect Rs. 11,000 crore from the listing. Further, it has announced "a revised mechanism and procedure to ensure time bound listing of identified CPSEs on stock exchanges". These are steps in the right direction. The system of disinvestment is a well-oiled machinery. However, there is a need to expedite the agenda of closing sick and lossmaking CPSEs, and privatising CPSEs that are in sectors where government ownership is not justified.
5. Over-reliance on petroleum products for collection of indirect taxes: in 2015-16, about 68 percent of total collection of excise duty was from petroleum products. This was about 27 percent of total indirect tax collection. In 2013-14, these were 55 percent and 19 percent, respectively. Since the last round of increases in duties on petroleum products happened in late 2015-16, the contribution of petroleum products is likely to have increased in 2016-17. Since the budget seems to have largely postponed the indirect tax decisions, one can only hope that the GST rollout will be such that this risky fiscal strategy of relying on a small number of commodities for so much of tax collection is discontinued, and we are able to build a broad tax base.
6. Shrinking sharable pool: States get a share of the central government's tax collection, based on Finance Commission recommendation. This is a share of the sharable pool, which is gross tax revenue minus cesses and surcharges. Between 2011-12 and 2015-16, the sharable pool as a percentage of the Gross Tax Revenues shrunk from 89.8 percent to 82.8 percent. As cesses and surcharges came to comprise a larger portion of tax collections, the amount States received as devolution from the centre was lower than it would have been otherwise. To consider a counterfactual, had the portion of sharable pool in 2015-16 remained the same as it was 2011-12, States would have received Rs. 42 thousand crore more in devolution from the Centre in 2015-16. It is too early to say, but this trend may be halting. In 2016-17 (revised estimate) and 2017-18 (budget estimate), sharable pool as percentage of gross tax collection is expected to be 83.1 percent and 84 percent, respectively. Hopefully, with GST, the cesses and surcharges will become less prominent.
7. Medium-term approach in budgeting: the Planning Commission used to make the five-year plans, which used to be the anchors for budgeting decisions regarding a number of areas of expenditure. This brought a medium-term perspective to budgeting. The process had its flaws, and its excesses have fueled urban legends in central Delhi. For better or for worse, the system has been dismantled. The twelfth and last five-year plan ran its course from 2012 to 2017. What we have now is the absence of any clear, publicly available medium-term perspective in budgeting. This has consequences for fiscal management, as many important priorities need to be pursued over the medium-term. Although there are talks about NITI Aayog coming up with Vision and Strategy documents, so far, there is no indication of the government moving towards a formal and comprehensive medium-term fiscal management framework.
   
   The FRBM-mandated Medium Term Fiscal Policy Statement serves only as a basic ingredient for fiscal discipline over medium-term. It includes top-down estimates. Since we no longer have any other medium-term anchor for budgeting, it is important for India to move towards a medium-term budget framework, which would help the government make better forward estimates and think about strategies across areas of expenditure, so that annual budgetary decisions for various schemes and programmes can be reconciled with the medium-term framework. This would require combining a top-down approach and a ground-up, negotiated approach to medium-term fiscal management.

Concerns about tax administration

The Finance Bill proposes certain amendments to the Income Tax Act to change the powers that tax authorities enjoy:

• Under Section 132(1), the tax authorities have the power to conduct search and seizure, if they have reason to believe that the person has not disclosed the information asked for, is not likely be submit the required information, or is in possession of valuables that may have been accumulated from income on which tax was not paid. The proposed amendment says that the "reason to believe" need not be disclosed to anyone, including to any authority of Appellate Tribunal. This amendment is proposed to take effect retrospectively from April 1, 1962, which is the date when the original provision was enacted.
• Section 132(1)(A) empowers the authorities to expand the search and seizure to include locations that are not included in the authorisation for search and seizure, as long as they have reason to suspect that this would yield useful information. This section is also being sought to be amended to include an explanation that the "reason to suspect" will not be disclosed to anyone, including to any authority of Appellate Tribunal. This amendment is proposed to take effect retrospectively from October 1, 1975, which is the date when the original provision was enacted.
• Section 132 is also proposed to be amended to insert sub-sections that will give powers to the authorised officer conducting search and seizure to provisionally attach, for a period of up to six months, property that they find during the course of a search and seizure. This would be done with the prior approval of of senior officers.
• Section 133 empowers income-tax authorities to call for information for the purpose of any inquiry or proceeding under the Income Tax Act. At present, if there is no proceeding pending against a person, this power can only be exercised by senior officers above a certain rank. This section is being sought to be amended to give this power to junior-ranking officers as well.
• Section 133A empowers income-tax authority to conduct a survey at a place where a business or profession is carried on or a place where documents or property relating to the business or profession are kept. This section is proposed to be amended to include places of charitable activities as well.
• Section 133C empowers certain income tax authorities to issue notice calling for information and documents for verification of information in its possession. The proposed amendment would empower the Central Board of Direct Taxes to make a scheme for centralised issuance of these notices.

The amendment to 133C is potentially an improvement, as it might reduce arbitrariness in the issuing of notices. However, the other amendments mentioned above may have unintended negative consequences. There may be arguments in favour of these amendments. For example, it would be easier to protect the identity of whistleblowers if reasons to suspect are not disclosed. Provisional attachment during search and seizure could make it easier for tax authorities to extract revenues from tax evaders. However, the powers being given through these amendments can also be misued to conduct arbitrary searches and seizures, provisionally attach properties, and disrupt people’s lives and businesses, all without having to explain the reasons behind the entire process. Important checks and balances are being proposed to be diluted.

These amendments can be seen in the context of the 25 percent increase targeted for personal income tax collection in 2017-18. Government has proposed changes to tax rates that would lead to Rs. 15,500 crore lower personal income tax collection. Accounting for this, the targeted increase in income tax collection is about 29.2 percent. Between 2010-11 and 2015-16, the average rate of growth in income tax collection was about 15 percent. In 2016-17, because of the one-time collection under the income disclosure scheme, the rate of increase is estimated to be 23.35 percent. An increase of, say, 15 percent can be considered to be normal, and the additional 14.2 percent (about Rs. 50,000 crore) would have to be mobilised through special measures. Given the state of the economy, the only way to get a 29.2 percent increase is to expand the tax base by getting more people to pay taxes, and by making further demands from those who may be under-paying the taxes.

As the Economic Survey, 2015-16 (see page 109 onwards), pointed out, given our level of economic development, India's income tax collection compares favorably with other countries. In fact, the Survey found that income tax collection is significantly better than expected at our level of economic development. For example, India's income tax to GDP ratio is 2.1 percent, while the ratio for Brazil is 2.3 percent. To account for the theory that democracies tend to tax and spend more, the Survey controled for democracy as a variable, and the finding on personal income tax holds, albeit the overall tax to GDP ratio is lower than it should be. While the percentage individuals paying taxes is much smaller than expected, the amount of personal income tax collected is actually better than one would expect at this per capita income. This mismatch between satisfactory income tax collection and low number of income tax payers may be because income is concentrated in a smaller number of individuals, but this requires further research.

There is tax evasion and tax avoidance, but there may not be enough "low hanging fruits" that can be plucked to yield Rs. 50,000 crore of additional income tax collection over and above the normal increase in collections. The important issue is that expanding fiscal capacity is a long-term task that requires building capabilites in the tax administration, while upholding the rule of law and the basic principles of government accountability. In a context where income tax collections are good for the level of development, a target to deliver a huge increase in collections, may tempt the tax administration to use their expanded powers to take draconian measures to extract taxes. In the process, innocent people will get hurt. For example, the tax administration would cast a much wider net to go after those who deposited cash after demonetisation than they would normally have. This is not a good way to build fiscal capacity. Rule of law and accountability of government are as important, if not more important, than collecting more income tax.

Conclusion

This reading of the budget suggests that while the budget has got the basic housekeeping of fiscal management right, it is a middling performance on addressing important fiscal issues that need to be addressed in medium term. Further, the pathway chosen for fiscal consolidation, although not necessarily bad, is sub-optimal because of the state of the economy. Finally, the amendments to the Income Tax Act proposed in the Finance Bill should be reconsidered, because they may harm basic principles of rule of law and government accountability.

 

The author is a researcher at National Institute of Public Finance and Policy. Views expressed here are personal.