TABLES - CURRENT AND HISTORIC CPI INDIA
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CONSUMER PRICES (MEI) IN INDIA IS THE COSTLIER AND HAVING HIGHEST INFLATION
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Price rise in last six years is 153%
Total increase in Consumer Price Index is 90 points.
Total DA due is 70 %
Please click the link for Consumer Price Index Numbers - Separately for Rural and Urban Areas and also Combined (Rural plus Urban)
Full information is provided by NSSO
It is observed that the Consumer price index basket of 2001 is not correct common items used by the Government items are not reflected in this basket hence the points instead of raising to 153 points is just 90 points.
All India Consumer Price Index Number for Industrial Workers (CPI-IW) on base 2001=100 for the month of MAY, 2012 increased by 1 points and stood at 206 (two hundred six ) Hence increase of 8 points from January 2012 Current DA likely at 70 % as on 30/5/12.
Current DA formula
Dearness Allowance = (Avg of AICPI for the past 12 months - 115.76)*100/115.76
ie is DA = (196.42-115.67) * 100/115.673 = 69.67 %
The below table denotes the calculation for the month of April 2012…
Month/Year
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Total of 12 Months
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12 Months average
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% Increase over 115.763
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App.DA
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DA%
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April -2012
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205
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2357
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196.42
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80.66
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69.67
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69
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a) The Prices of the articles are continuously rising.
b) The DA is announced twice in a year that is January and July respectively
c) The Index point which was at 100 on 1/1/2001
d) The Index point which was at 115.76 on 1/1/2006.
e) From 1/1/2006 to 30/5/2012 the points has risen from 115 points to 206 points there by there is an increase of 90 points compared to 70 % DA.
f) The Price of an article which was as on 115.76 on 1/1/2006 is Rs 206 as on 30/5/12 that is the market cost of today’s price is 206 and Government employee if he goes to market to buy the article has to pay an increased price of Rs 90/- and DA is just 70. that means simple calculation of 90% DA should be given to Government Employees.
g) The prices which are increased from January to July is provided DA wef from JULY. That is that the prices which are increased for example the Cost groundnut oil is Rs 70 as on 1st July 2011 shows an steady increase and is Rs 90 as on 30th June 2012 DA as on 1st July 2012 is computed as average of Rs 70 & Rs 90 that is it works out to Rs 80. There after it is divided by factor 115.6 that works out to Rs 69 hence no DA is admissible even though the prices are increased from Rs 70 to Rs 90.
h) The prices which are increased from past twelve months are not compensated only it is compensated after 6 months of increase. Hence the worker is cheated. For example if the price of an article is increased abruptly after DA is announced on July 2011 and He has to wait for compensation till JULY 2012. due to average of 12 months criteria. That is no immediate compensation of price rise is available to him. That is he has to pay from his pocket to buy the article.
i) The Variable DA should be there as in case of petrol prices as and when the international crude is increasing the oil companies raise their prices of petrol, so no burden on them, same should be the case of Government Employees as and when the AICPI increase then the DA should automatically increase every month.
j) Recommendation of 6th CPC vide para no 4.1.13
The Commission is of the view that the National Statistical Commission may be asked to explore the possibility of a specific survey covering Government employees exclusively, so as to construct a consumption basket representative of Government employees and formulate a separate index. Meanwhile, the Government may continue to use the AICPI (IW) for estimating the DA.
Hence separate DA AICPI should be formed for Government employees
The postman in rural areas across the country has his hands full. Apart from his regular job, he now has to go out three to four times a week to collect data from retail outlets which is then used to calculate the rural consumer price inflation.
Faced with an acute manpower shortage, the ministry of statistics and programme implementation tied up with the department of posts to get over the problem of collecting such massive amount of data from rural areas across the country.
