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Report No. 245

The method is as below:

1. The method aims at calculating the number of judges required in each cadre of Subordinate Court Judges, i.e., Higher Judicial Service, Civil Judge Senior Division and Civil Judge Junior Division. For evolving the method, a separate analysis of figures for institution, disposal and the working strength of judges in each of these three cadres from 2010 to end 2012 was carried out.

2. Disposals for one cadre of judges (e.g., Higher Judicial Service) is divided by the working strength of judges in that cadre. Working strength refers to sanctioned strength minus vacancies and deputations. This division gave the annual Rate of Disposal per judge in a cadre for each year from 2010 to 2012. The average of these annual rate of disposal figures gave the Average Rate of Disposal per judge in that cadre.

3. An average of the annual institutions before each cadre of judge for the years 2010-12 was taken.37 The average institution was divided by the Average Rate of Disposal per judge for that cadre to give the number of judges required to keep pace with the current filings, and ensure that no new backlog is created. This figure has been described as: The Break Even Number.

37. The use of the average annual institution in the last three years as the basis for analyzing future demand for judicial resources bears explanation. Some High Courts provided us with data on institution, disposal and pendency for the last 10 years, i.e., from 2002-2012. However, we have decided to look at institutions only for the last three years.

Given that the demand for judicial resources keeps changing depending on new laws being promulgated, changes in awareness of the law, changes in socio-economic conditions of society, etc, the recent data is a better predictor of what is likely to be the demand for judicial resources in the next plan period, than past data. For example, looking at the Higher Judicial Services in Jharkhand, the 10 year average annual institution from 2002-11 would suggest that we could expect 21452 fresh institutions in 2012. The actual institution was 26665.

The difference between the actual institution and the predicted institution was therefore 5213 cases. On the other hand the average institution for the time period 2009-11 for the same cadre was 26996 as against the actual institution of 26665 for 2012. The difference was only 331 cases. The change occurs because the annual institution of cases before the Higher Judicial Services has risen in recent times.

A 10 year average data pulls down the average because of the lower institution rates from 10 years ago. The vast changes in the normative field and social context mean that institution rates are not stable over long periods. The use of relatively old data thus becomes an unreliable measure for future forecast. Of course, even with the more recent data, the past demand is no guarantee of the future demand.

However, other factors remaining constant, the past demand can be a useful tool for planning for the near future. If other factors change, as for example, new laws are introduced or the pecuniary jurisdiction of a Court changes, additional resources would be required.

It is relevant to note that the data shows wide fluctuations in filing figures from one year to another such that no clear trend is discernable. For example, in the Delhi Higher Judicial Service, the institution of new cases increased by 18.4% from 2009 to 2010, by 4.3% from 2010 to 2011 and by 11.3 % from 2011 to 2012. In the Delhi Judicial Service the institution of new cases 4.8% from 2009 to 2010, 17% from 2010 to 2011, but fell by 25.2% in 2012.

Another example of such fluctuations is seen in the data from Himachal Pradesh. Here in the cadre of Civil Judge Junior Division, the institution of new cases increased by 22.5% in 2010, 1.2% in 2011 and 35% in 2012. Such examples of wide fluctuations in the year on year data are present in almost all High Courts. (See Tables I to X below) For this reason any kind of trend analysis is difficult.

Other methods for forecasting the demand for judicial resources like regression analysis have been forgone because the independent variables that affect the number of filings, like new laws coming into force, increase in awareness about laws and the social and economic context are difficult to predict, measure and define.

The average institution is an approximate measure of the likely institution in next few years. It should not be treated as the only yardstick, but should be constantly monitored to ensure that increases in annual institutions culminate in additional recruitment of judges. We have used figures for the last 3 years, i.e., 2010-12 because we have the most comprehensive dataset for this period for the highest number of Courts.

4. Subtracting the current number of judges from the Break Even Number gives us the Additional Number of Judges required to ensure that the number of disposals would equal the number of institutions.

5. The backlog for a particular cadre of judges (defined as all cases pending before that cadre of judges for more than a year) was then divided by the rate of disposal for that type of judge. This gave the number of judges required to clear the backlog within a year. Dividing this number by 2 gives the number of judges required to clear the backlog in 2 years, and so forth. Therefore, the formula for determining the Additional Number of Judges for Breakeven is represented as follows:

ARD = [(D2010/J2010)+(D2011/J2011)+(D2012/J2012)]/3



BEJ= Additional No. of Judges required to Break Even.

AI= Average Institution

ARD= Average Rate of Disposal

D2010, D2011, D2012 = Annual Disposal for that year

J2010, J2011, J2012 = Annual Working Strength of Judges for that year

J= Current Working Strength of Judges

The formula for determining the Number of Judges for disposing of Backlog required to dispose of pending cases within a given time period is:

AJBk = (B/ARD)/t


AJBk = No. of Judges for disposing of Backlog

B = Backlog, defined as the number of cases pending for more than a year.

t = The time frame, in number of years, within which the backlog needs to be cleared.

Based on application of these formulae, the following tables were generated. These tables indicate the additional number of Subordinate Court Judges required to breakeven, and the number of Subordinate Court Judges required to clear the existing backlog for the High Courts of Andhra Pradesh, Bihar, Delhi, Gujarat, Himachal Pradesh, Jammu & Kashmir, Jharkhand, Karnataka, Kerala, Punjab & Haryana, Sikkim, and Uttarakhand.

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