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Early this week, the Comptroller and Auditor General (CAG) of India tabled a report on the finances of Uttar Pradesh for the financial year 2020-21. A few days prior to that, on May 26, the budget for Uttar Pradesh for 2022-23 was presented, along with which the final audited expenditure and receipt figures for the year 2020-21 were released. The year 2020-21 presented a two-fold challenge for states – loss in revenue due to impact of COVID-19 pandemic and lockdown, and the need for increased expenditure to support affected persons and economic recovery. CAG noted that Uttar Pradesh’s GSDP grew by 1.05% in 2020-21 as compared to a growth of 6.5% in 2019-20. The state reported a revenue deficit of Rs 2,367 crore in 2020-21 after reporting revenue surplus for 14 successive years since 2006-07. Revenue deficit is the excess of revenue expenditure over revenue receipts. This blog looks at the key trends in the finances of Uttar Pradesh in 2020-21 and certain observations by CAG on fiscal management by the state.
Spending and Deficits in 2020-21
Underspending: In 2020-21, total spending by the state was 26% less than the budget estimate presented in February 2020. In sectors such as water supply and sanitation, the actual expenditure was 60% less than the amount budgeted, while in agriculture and allied activities only 53% of the budgeted amount was spent. CAG observed that in 251 schemes across 57 departments, the state government did not incur any expenditure in 2020-21. These schemes had a budget provision of at least one crore rupees, and had cumulative allocation of Rs 50,617 crore. These included schemes such as Pipe Drinking Water Scheme in Bundelkhand/Vindhya and apportionment of pension liabilities. Moreover, the overall savings due to non-utilisation of funds in 2020-21 was 27.28% of total budget provisions. CAG observed that the budgetary provisions increased between 2016 and 2021. However, the utilisation of budget provisions reduced between 2018-19 and 2020-21.
Pattern of spending: CAG observed that in case of 12 departments, more than 50% of the expenditure was incurred in March 2021, the last month of the financial year. In the civil aviation department, 89% of the total expenditure was incurred in March while this figure was 62% for the social welfare department (welfare of handicapped and backward classes). CAG noted that maintaining a steady pace of expenditure is a sound practice under public financial management. However, the Uttar Pradesh Budget Manual has no specific instructions for preventing such bunching of expenditure. The CAG recommended that the state government can consider issuing guidelines to control the rush of expenditure towards the closing months of the financial year.
Management of deficit and debt: As a measure to mitigate the impact of COVID-19, an Ordinance was promulgated in June 2020 to raise the fiscal deficit limit from 3% of GSDP to 5% of GSDP for the year 2020-21. Fiscal deficit represents the gap between expenditure and receipts in a year, and this gap is filled with borrowings. The Uttar Pradesh Fiscal Responsibility and Budget Management Act, 2004 (FRBM Act) passed by Uttar Pradesh Assembly specifies the upper limit for debt and deficits. The Ordinance thus permitted the state government to borrow more to sustain its budget expenditure. The fiscal deficit of the state in 2020-21 was 3.20% of GSDP, well below the revised limit. At the same time, the state’s outstanding debt to GSDP in 2020-21 was 32.77% of GSDP, above the target of 32% of GSDP set under the FRBM Act. Outstanding debt represents accumulation of debt over the years.
Table 1: Spending by Uttar Pradesh in 2020-21 as compared to Budget Estimates (in Rs crore)
|
Particular |
2020-21 BE |
2020-21 Actuals |
% change from BE to Actuals |
|
Net Receipts (1+2) |
4,24,767 |
2,97,311 |
-30% |
|
1. Revenue Receipts (a+b+c+d) |
4,22,567 |
2,96,176 |
-30% |
|
a. Own Tax Revenue |
1,58,413 |
1,19,897 |
-24% |
|
b. Own Non-Tax Revenue |
31,179 |
11,846 |
-62% |
|
c. Share in central taxes |
1,52,863 |
1,06,687 |
-30% |
|
d. Grants-in-aid from the Centre |
80,112 |
57,746 |
-28% |
|
Of which GST compensation grants |
7,608 |
9,381 |
23% |
|
2. Non-Debt Capital Receipts |
2,200 |
1,135 |
-48% |
|
3. Borrowings |
75,791 |
86,859 |
15% |
|
Of which GST compensation loan |
- |
6,007 |
- |
|
Net Expenditure (4+5+6) |
4,77,963 |
3,51,933 |
-26% |
|
4. Revenue Expenditure |
3,95,117 |
2,98,543 |
-24% |
|
5. Capital Outlay |
81,209 |
52,237 |
-36% |
|
6. Loans and Advances |
1,637 |
1,153 |
-30% |
|
7. Debt Repayment |
34,897 |
26,777 |
-23% |
|
Revenue Balance |
27,451 |
-2,367 |
-109% |
|
Revenue Balance (as % of GSDP) |
1.53% |
-0.14% |
|
|
Fiscal Deficit |
53,195 |
54,622 |
3% |
|
Fiscal Deficit (as % of GSDP) |
2.97% |
3.20% |
Note: A negative revenue balance indicates a deficit. The actual fiscal deficit reported by Uttar Pradesh for 2020-21 in 2022-23 budget was 2.8% of GSDP. This difference was due to higher GSDP figure reported by the state.
Sources: Uttar Pradesh Budget Documents of various years; CAG; PRS.
Finances of State Public Sector Undertakings
Public sector undertakings (PSUs) are set up by the government to discharge commercial activities in various sectors. As on March 31, 2021, there were 115 PSUs in Uttar Pradesh. CAG analysed the performance of 38 PSUs. Out of these 38 PSUs, 22 companies earned a profit of Rs 700 crore, while 16 companies posted a loss of Rs 7,411 crore in 2020-21. Note that both the number of PSUs incurring losses and the quantum of losses has decreased since 2018-19. In 2018-19, 20 PSUs had reported losses worth Rs 15,219 crore.
Figure 1: Cumulative losses incurred by Uttar Pradesh PSUs (Rs crore)
Sources: CAG; PRS.
Losses of power sector PSUs: Three power sector PSUs—Uttar Pradesh Power Corporation Limited, Purvanchal Vidyut Vitran Nigam Limited, and Paschimanchal Vidyut Vitran Nigam Limited—were the top loss incurring PSUs. These three PSUs accounted for 73% of the total losses of Rs 7,411 crore mentioned above. Note that as of June 2022, for each unit of power supplied, the revenue realised by UP power distribution companies (discoms) is 27 paise less than cost of supply. This is better than the gap of 34 paise per unit at the national level. However, the aggregate technical and commercial losses (AT&C) of the Uttar Pradesh discoms was 27.85%, considerably higher than the national average of 17.19%. AT&C losses refer to the proportion of power supplied by a discom for which it does not receive any payment.
Off-budget borrowings: CAG also observed that the Uttar Pradesh government resorted to off-budget borrowing through state owned PSUs/authorities. Off budget borrowings are not accounted in the debt of the state government and are on books of the respective PSUs/authorities, although, debt is serviced by the state government. As a result, the outstanding debt reported in the budget does not represent the actual debt position of the state. CAG identified off-budget borrowing worth Rs 1,637 crore. The CAG recommended that the state government should avoid extra-budget borrowings. It should also credit all the loans taken by PSUs/authorities on behalf of and serviced by the state government to state government accounts.
Management of Reserve Funds
The Reserve Bank of India manages two reserve funds on the behalf of state governments. These funds are created to meet the liabilities of state governments. These funds are: (i) Consolidated Sinking Fund (CSF), and (ii) Guarantee Redemption Fund (GRF). They are funded by the contributions made by the state governments. CSF is an amortisation fund which is utilised to meet the repayment obligations of the government. Amortisation refers to payment of debt through regular instalments. The interest accumulated in the fund is used for repayment of outstanding liabilities (which is the accumulation of total borrowings at the end of a financial year, including any liabilities on the public account).
In line with the recommendation of the 12th Finance Commission, Uttar Pradesh created its CSF in March 2020. The state government may transfer at least 0.5% of its outstanding liabilities at the end of the previous year to the CSF. CAG observed that in 2020-21, Uttar Pradesh appropriated only Rs 1,000 crore to the CSF against the requirement of Rs 2,454 crore. CAG recommended that the state government should ensure at least 0.5% of the outstanding liabilities are contributed towards the CSF every year.
GRF is constituted by states to meet obligations related to guarantees. The state government may extend guarantee on loans taken by its PSUs. Guarantees are contingent liabilities of the state government, as in case of default by the company, repayment burden will fall on the state government. GRF can be used to settle guarantees extended by the government with respect to borrowings of state PSUs and other bodies. The 12th Finance Commission had recommended that states should constitute GRF. It was to be funded through guarantees fees to meet any sudden discharge of obligated guarantees extended by the states. CAG noted that Uttar Pradesh government has not constituted GRF. Moreover, the state has also not fixed any limits for extending guarantees.
For an analysis of Uttar Pradesh’s 2022-23 budget, please see here.
Recently, the Supreme Court collegium reiterated its recommendations for the appointment of 11 judges to certain High Courts. It had first recommended these names earlier this year and in August last year, but these appointments were not made. The Indian judiciary faces high vacancies across all levels (the Supreme Court, High Courts, and subordinate courts). Vacancy of judges in courts is one of the reasons for delays and a rising number of pending cases, as there are not enough judges to hear and decide cases. As of today, more than four crore cases are pending across all courts in India. In this blog post, we discuss vacancies across courts over the years, delays in appointment of judges, and methods to determine the adequate judge strength required to handle the caseload courts face.
High vacancy of judges across courts
Vacancies in courts keep on arising periodically due to retirement, resignation, demise, or elevation of judges. Over the years, the sanctioned strength of judges in both High Courts and subordinate courts has been increased gradually. However, vacancies persist due to insufficient appointments (see Figures 1 and 2). Between 2010 and 2020, vacancies increased from 18% to 21% across all levels of courts (from 6% to 12% in the Supreme Court, from 33% to 38% in High Courts, and from 18% to 20% in subordinate courts).
|
Figure 1: Vacancy of judges in High Courts |
Figure 2: Vacancy of judges in subordinate courts |
|
|
|
|
Sources: Court News 2010-2018; Vacancy Statement, and Rajya Sabha replies, Part I, Budget Session (2021), Department of Justice; PRS. |
|
As on November 1, 2021, the Supreme Court had a vacancy of one judge (out of a sanctioned strength of 34). Vacancy in High Courts stood at 37% (406 posts vacant out of a sanctioned strength of 1,098). Since May, 2021, the Supreme Court collegium has recommended more than 130 names for appointment as High Court judges. In three High Courts (Telangana, Patna, and Calcutta), at least half of the posts are vacant (see Figure 3). The Standing Committee on Personnel, Public Grievances, Law and Justice (2020) noted that every year, 35-40% of posts of High Court judges remain unfilled.
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Figure 3: Vacancy of judges across High Courts (in %) (as on November 1, 2021)
|
|
Source: Vacancy Statement, Department of Justice; PRS. |
Appointments of High Court judges are guided by a memorandum of procedure. As per this memorandum, the appointment process is to be initiated by the concerned High Court at least six months before a vacancy occurs. However, the Standing Committee (2021) noted that this timeline is rarely adhered to by High Courts. Further, in the final stage of the process, after receiving recommendations from the Supreme Court collegium, the executive appoints judges to the High Court. No timeline is prescribed for this stage of the appointment process. In 2018 and 2019, the average time taken to appoint High Court judges after receiving the collegium’s recommendations was five to seven months.
As of today, over 3.6 crore cases are pending before subordinate courts in India. As on February 20, 2020, 21% posts for judges were vacant (5,146 posts out of the sanctioned strength of 24,018) in subordinate courts. Subordinate courts in Bihar, Haryana, and Jharkhand (among the states with high population) had a high proportion of vacancies of judges (see Figure 4). Note that the Supreme Court is monitoring the procedure for appointment of judges to subordinate courts.
For an analysis of the data on pendency and vacancies in the Indian judiciary, see here.
Figure 4: Vacancy of judges across subordinate courts (in %) (as on February 20, 2020)
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|
|
Source: Report No. 101, Standing Committee on Personnel, Public Grievances, Law and Justice (2020); PRS. |
How many judges do we need?
The Law Commission of India (1987) had noted the importance of manpower planning for the judiciary. Lack of adequate number of judges means a greater workload per judge. Thus, it becomes essential to arrive at an optimal judge strength to deal with pending and new cases in courts. Over the years, different methods of calculating the required judge strength for subordinate courts (where the backlog of cases in the Indian judiciary is concentrated) have been recommended (see Table 1).
Table 1: Methods recommended for calculating the required number of judges for subordinate courts
|
Method of calculation |
Recommendation and its status |
|
Judge-to-population ratio: optimum number of judges per million population |
The Law Commission of India (1987) had recommended increasing this ratio to 50 judges per million people. This was reiterated by the Supreme Court (2001) and the Standing Committee on Home Affairs (2002). For 2020, the judge-to-population ratio was 21 judges per million population. Note that this figure is calculated based on the sanctioned strength of judges in the Supreme Court, High Courts and subordinate courts. |
|
Rate of disposal: number of additional judges required (to clear the existing backlog of cases and ensure that new backlog is not created) based on the average number of cases disposed per judge |
The Law Commission of India (2014) proposed this method. It rejected the judge-to-population ratio method, observing that filing of cases per capita varies substantially across geographic units depending on socio-economic conditions. |
|
Weighted case load method: calculating judge strength based on the disposal by judges, taking into account the nature and complexity of cases in local conditions |
The National Court Management Systems Committee (NCMS) (2016) critiqued the rate of disposal method. It proposed, as an interim measure, the weighted case load method, which addresses the existing backlog of cases as well as the new flow of cases every year in subordinate courts. In 2017, the Supreme Court accepted this model. |
|
Time-based weighted case load method: calculating the required judge strength taking into account the actual time spent by judges in different types of cases at varying stages based on an empirical study |
Used widely in the United States, this was the long-term method recommended by the NCMS (2016) to assess the required judge strength for subordinate courts. It involves determining the total number of ‘judicial hours’ required for disposing of the case load of each court. The Delhi High Court used this approach in a pilot project (January 2017- December 2018) to calculate the ideal judge strength for disposing of pending cases in certain courts in Delhi. |
Sources: Reports No. 120 (1987) and 245 (2014), Law Commission of India; Report No. 85, Standing Committee on Home Affairs (2002); Note for Calculating Required Judge Strength for Subordinate Courts, National Court Management Systems Committee (NCMS) (2016); Imtiyaz Ahmad vs. State of Uttar Pradesh, Supreme Court (2017); PRS.
