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CACP – The data source which is an important source for wages in rural India unfortunately does not publish the wage data from these studies. The cost of cultivation scheme collects data from the selected household at regular intervals on all aspects of farm business. The valuation of human labor has always been a problematic issue for the CACP. There is however a number of limitations associated with this data such as lack of data for many crops, problem in aggregating the data from the state level, unavailability of data at the state level etc.
The four reference points have been used to look at a change in the wage rate. However, the choice of reference points in the study have been limited to the years 1983 and 1987-88 in the 80’s and 1993-94 in the 90’s.
AWI Wage Rate: It is the most widely used source for analyzing trends in wage rate for rural India. However, one given problem noticed by the researcher with respect to AWI is the time lag in the data and the method of aggregating all the data for th states and all India level. There were many studies performed to check the average wage rate of labourer in different parts of India by many previous researchers. However in all these studies used simple average of wage rates in different months to arrive at the annual figures. Also, all these studies used population of agricultural labourers’ from the census as weights to arrive at the wage rate. The average AWI wage rate is 30-40 percent higher as compared to the RLE/NSS estimates of wage rates. It was also studied that the AWI wage rates were found to be marginally upwards biased as compared to the FMS estimates of wages.
A look at the wage trends from AWI since 1980-81 suggests that the wage rates have generally been higher in Punjab, Haryana, and Kerala as compared to the other states in the 80’s. However, by the end of 1990, Gujarat and West Bengal have seen to have made a significant contribution and is closer to the traditional high wage rates. Rajasthan, on the other hand which was closer to the traditional high wage rates has fallen behind and is considerably lower than Kerala, Punjab and Haryana. The states on the lower ends of the wage rate are Orissa, Bihar, Madhya Pradesh, Maharashtra, and Andhra Pradesh. Kerala’s wage rate is found to be three times those in Orissa and in Punjab and Haryana they are twice the wage rate in Orissa. Wages have continued to grow in all three time periods but there was a significant slowdown in the wage rate during the period 1987-88 and 93-94. For the period 1987-88 to 1993-94, which also included the year of the financial crisis and the consequent economic reforms, wage rates show a deceleration in almost all the states as well as the all India level. This decline in the growth of wages is sharper for Andhra Pradesh, Assam, Bihar, Gujarat, and Karnataka.
Wage trends from CACP – In the study it was found out that this wage rate had been created by aggregating over crops using crop specific weights for individual states. Wage rates from CACP are generally found to correlate well with the AWI series in spite of the differences in methodology of collection of data. In fact, for both 1983 and 1987-88, wage rates from CACP show a very high correlation coefficient of 0.95 with the AWI wage rates. It was also analyzed in the study that wage rates from CACP show better growth rates in 1987-88 and 1993-94 as compared to the AWI series. Rajasthan turns out to be an exception which showed markedly improved wage rates as showed by AWI wage series. Even for other states, CACP does not show as sharp a deceleration as AWI. Maharashtra on the other hand shows sharp deceleration in the wage rate during 1987-88 and 1993-94.
NSS – These wage rates were found to be statistically more significant and reliable than that of AWI or CACP because of their consistent and superior sampling framework but they also allow for a much higher level of disaggregation. The wage rates reported by NSS for males for agricultural occupations are considerably lower than the wage rates reported by AWI. It was further studied that the NSS rates were very well correlated with the rates of AWI series with a correlation coefficient of around 0.9 in the 1980’s, 0.87 in 1993-94 and 0.95 in 1999-00. However, again for most states there was a deceleration in the growth rate during the next sub period that is, between 1987-88 and 1993-94. Except for the state of Gujarat, deceleration was seen for almost all states. Gaps between agricultural and non agricultural wages narrowed down considerably in Punjab and Rajasthan. West Bengal and Karnataka were found to be the states having the lowest divergence between agricultural and non agricultural activities. Comparison between agricultural and non agricultural activities gender wise was also performed. It was analyzed that the growth rates in these activities in males suggested that in 1983-84 and 87-88 agricultural wages grew faster than non agricultural wages. For females, however non agricultural wages grew faster than agricultural wages.
RLE/ALE wage trends – RLE uses a subset of households from the NSS employment and unemployment quinquennial surveys. The household types are either self employed in agriculture, non agriculture, agriculture labour, other labour and others. A comparison of the wage rate from the NSS and the RLE reveal that there is a high degree of correlation between them especially in the 1990. This is true not only at the all India level but also at the state level. For the period from 1983-1987, growth rates from RLE were shown to be 70-80 percent higher than the ones shown by the NSS series in the study. The growth rate of the NS were similar to those studied by AWI or CACP for many states, however the RLE suggests growth rates higher than any of these. Further it was also studied that the growth rate of wages in agriculture are much higher than those suggested by NSS or CACP or AWI. There was also an inter range comparison done in this study to check the difference in wages under the RLE scheme. It was analyzed that comparing the 1977 RLE scheme to that of 1983, real wage rates declined by almost 10 percent for the latter. Such a decline in wage rate is not accompanied by any other wage estimates including those from NSS.
WRRI – Wage rates from eleven agricultural operations and seven non agricultural operations. For wage rates for agricultural operations, simple average of sowing, transplanting, weeding, harvesting, winnowing and threshing was taken as the representative wages. The analysis in the study was based for the years 1990-2000 and 2002-03. It was studied that the wage rates from WRRI for agriculture than those reported by NSS and RLE for males and almost 60 percent higher for females. WRRI estimates of wage rates are found to be closer to the CACP or AWI estimates because of similarity in methodology and sources. WRRI is the only estimate that is available after 1999-00. It was further analyzed in the study that the wage rates between male and female for agricultural occupations as well as non agricultural occupations have grown in real terms. Coming to the state wise analysis, Bihar and Orissa are the states that saw the highest growth rates of wages for both males and females. The other state that achieved close to 10 percent per annum growth rate of wages is Kerala. Apart from Kerala, the other two states – Andhra Pradesh and Tamil Nadu saw slower growth rates of wages. Uttar Pradesh having a large concentration of poor and rural labourers witnessed growth rates of less than two percent in both agricultural and non agricultural operations.
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