2012 Jiva April Page 17-23

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RESEARCH ARTICLE

STATISTICAL TOOLS FOR THE PRICING ISSUES IN MILK PRODUCTION IN KERALA Unnikrishnan T.1 and Ashok B.2 Kerala Veterinary and Animal Science University

ABSTRACT The main objectives of this study included assessment of trend and growth rates of milk production, milk price and feed price, correlation between the variables and testing the linear regression equations with the highly correlated variables for prediction purposes. Yearly secondary data on milk production, wage of labourer, human population, cattle population, milk price and feed price collected from various economic reviews of Government of Kerala for the period from 1991-92 to 2009-10 were used for the analysis.

1. Academic Consultant, Dept. of Statistics, Kerala Veterinary and Animal Science University 2. Former Vice Chancellor, Kerala Veterinary and Animal Science University

The other main problem behind the low interest in dairy farmers is the decreased cultivation of paddy also increased the need for cattle feeds. Almost 90 per cent of the raw materials needed for the compounded cattle feed are coming from nearby state. Hence there need to have a sustenance mechanism where in the milk price should be determined by the in farm factors which affects its production such as rate of feed ingredients, labour charge etc. Statistics on diverse facets of milk production are required both to focus on the problems confronting farming as well as farmers in Kerala in the context of emerging challenges in the economy, and to throw light on priority areas in need of policy intervention. One cannot spell out exactly where forecasts are more frequently needed as the forecasting techniques have become essential features in all the ministries, establishments, public and private sectors. As the food security corner of Kerala is concerned, such a forecasting will cradle the government to tide over grim situations with ease.

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Despite, Kerala's milk production has an increasing nature; there was a huge gap between its productivity and demand for milk and milk products. The major demand for milk in the State is met by import from neighboring states and reconstituted milk. Hence, the milk price is mainly controlled by organized sectors which hold only 16 percent of the total milk produce and administrative authorities and secondary market holders, where the price is often based on the indices such as fat and SNF. The dairy farmers, who are having a very marginal profitability, do not have control over the milk price fluctuations. Also the laborers are moving towards more remunerative fields than the agricultural sector and the social status of the youth who are expecting white collar jobs do not want to take up any type of animal husbandry activity. This made the shortage of labour in the state so that the interested poor farmer who was living with the income moved away from this sector due to increased cost of production and less profit. In Kerala, the main problem for the farmer is concerned

every time the farmers' price is hiked; the consumer price has gone up, because the government does not offer subsidy while nearby states Karnataka and Tamil Nadu gives a subsidy of Rs 2 and Rs 2.50 respectively per litre of milk.

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INTRODUCTION

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RESEARCH ARTICLE

METHODOLOGY Annual data on milk production, milk price, cattle population, feed price and human population are collected from the economic reviews of planning board of Kerala. The Directorate of Economics and Statistics changed the Triennium Ending 1981-82 base year to T.E. 1993-94 as a way of updating the base to a recent year and keep it in harmony with the other series of indices such as Index of industrial production, whole sale price index and the series of national accounts statistics. Hence all the index numbers were calculated with 1993-94 as base year. Let Pi - the price in the ith year and P0 that in base year 1993-94 in Kerala. Then the index is calculated using the formula Ii = Pi/P0*100.

commodity. Wide price fluctuations, on the other hand, discourage farmers from taking up large-scale investment to improve productivity. The study of price behavior assumes importance in this context. The significant and positive correlation between milk price and milk production shows this. This correlation tend to the regression equation, Milk Production (in Lakh Tonnes) = 0.548*Milk Price in Rs/Ltr +14.004 2

Which yields an R of 0.627 indicating 62.7 Percent of the variation in the milk production in Kerala can be explained by the variation in milk price alone. Milk Production and Price per Litre

Analysis of average annual growth rates, correlation study and regression analysis were also done to explore the relationship among the variables.

30 25 Values

20 15 10

RESULTS AND DISCUSSION

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From Fig 1. it could be seen that both the milk production and the milk price shows an increasing trend. In the case of agriculture, remunerative and steady price for any agricultural produce plays a crucial role in increasing production of that

Production (Lakh MT)

J. Ind. Vet. Assoc., Kerala. 10 (1) 18

df

Mean Square

F

Sig.

Regression

110.561

1

110.561

31.931

.000a

Residual

65.787

19

3.462

Total

176.348

20

Table 2. Table of regression coefficients milk production and milk price Unstandardized Standardized Coefficients Coefficients B Beta Std. Error 14.004 1.281 .548

.097

2010

Fig 1. Milk production and Price per litre in Kerala

Sum of Squares

Milk Price (Rs/Ltr)

2009

Price (Rs/Ltr)

ANOVA(b)

(Constant)

2008

Year

Table 1. Anova Table for regression between milk production and milk price Model

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

0

.792

t

Sig.

10.928

.000

5.651

.000


RESEARCH ARTICLE

The demand for milk does not increase the milk price very much as other substituting products like milk powder are available in the market. But the increasing milk price is a factor for increasing in milk production along with other parameters with a weightage of 0.548 to milk price. From the significant correlation between milk price and feed price, the following linear relationship could be observed by the model,

Milk Price = 1.702*Price of Feed per Kg +1.641. The model explains 96.9% of the variation in the milk price with price of feed as explanatory variable. Thus when there is an annual increase of one rupee in one kg of feed, there will be a corresponding increase of rupees 1.70 per one litre of milk.

Table 3. Anova Table for regression between milk price and feed price Sum of Squares Degree of Freedom Mean Square Regression

356.897

1

356.897

Residual

11.398

19

.600

Total

368.296

20

F Value

Sig.

594.928

.000

a

Table 4. Table of regression coefficients between milk price and feed price Unstandardized Coefficients Std. Error

(Constant)

1.641

.478

Feed Price (Rs/Kg)

1.702

.070

.984

t

Sig.

3.436

.003

24.391

.000

The other factors such as labour cost, production, demand, price of procurements like milk powder etc. do not come under the model. So there need to have a more scientific way of fixation of price so that both consumer and farmer are protected by considering all the factors affecting milk price. In this context, a future

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B

Standardized Coefficients Beta

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RESEARCH ARTICLE

study by considering all the variables affecting milk production will help in Government policies and subsidy programme later. Analising the growth rates it could be observed that there occurred a sharp increase in feed price during 1992-93, 1997-98 and during 2009-10. Due to this the growth rate in milk production declined well in 2009-10 due to unavailability of sufficient straw due to less paddy cultivation and less grass production as summer was highly hot during that period. In this circumstances the annual growth rate of milk price was also didn't increased. These things make the farmer to move away from this sector. Fig 3. Growth rates of milk production milk price and feed price

Average annual growth rates Growth Rate (%) Annual_Milk Production

50.00

Growth rate (% )Annual_Milk Price Growth rate (%) Annual_ Cattle Feed Price

30.00

rate

Growth

40.00

20.00 10.00

2009-10

2008-09

2007-08

2006-07

2005-06

2004-05

2003-04

2002-03

2001-02

2000-01

1999-00

1998-99

1997-98

1996-97

1995-96

1994-95

1993-94

1992-93

-10.00

1991-92

0.00

-20.00

Year

Also during the last few years the wage of labourer is increasing exponentially. The highly significant correlation between milk price and wage of paddy field labourer gives the linear regression, Milk Price (in Rs/Ltr) = 0.05* Wage of Men Labourer + 5.613. Since the model explains 95.2 percent variation in milk price with wage of men as explanatory variable, the wage of labourer is a main factor in determining the milk price.

J. Ind. Vet. Assoc., Kerala. 10 (1)

Table 5. Anova Table for regression between wage of labour and milk price

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Table 6. Table of regression coefficients between wage of labour and milk price


RESEARCH ARTICLE

A few years back the old families could maintain more than one animals. But when they split into nuclear families the farmer couldn't control more and they have to pay for labourers for additional work. In this context the increased wage plays a major role in the decreasing cattle population. From Table (7) with base year as 1993-94, it could be observed that the feed price was increased 310.11 percent and wage 645.04 percent where as the milk price to 274.36 percent Table 7. Index numbers of milk price, feed price, milk production and wage

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Table (8) shows the correlation between different variables influencing milk production. The high correlation between indigenous population and the total cattles and negative correlation between milk production and total cattles in Table (8) reveals the paradox between decreasing cattle population and increasing milk production. This is due to the selling of low yielding indigenous cows and increased productivity with crossbred.

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Table 8. The Correlation between the variables

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RESEARCH ARTICLE

The high correlation between milk price and human population shows the increase in price with demand. There is significant correlation with the crossbred animals in milk and the milk production where as there is no significant correlation between milk production and indigenous animals in milk. It is also to be noted that the Milk price is directly correlated with feed price. Fig 4. Non increasing behavior of animals in milk during the last decade

J. Ind. Vet. Assoc., Kerala. 10 (1)

Fig 5. A small increasing behavior in milk production during the last few years

From fig 4 and 5 it could be observed that even though the animals in milk are almost steady, the milk production is moving upwards. This shows both the higher productivity of crossbred cows and the power of increasing trend of the use of frozen semen for the last few years. If it could be noted to increase the number of animals also, this will bring a good increase in milk production in Kerala.

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RESEARCH ARTICLE

REFERENCE [Anonymous].1999. Brochure on new series on national accounts statistics (base year 199394). Central Statistical Organization.

Box, G.E.P. and Jenkins,G.M. 1970., Time Series Analysis: Forecasting and Control, SanFrancisco: Holden-Day. Gujarati,D.N. 2009. Basic econometrics, 5th ed., Boston, McGrawHill, 922p. Mandal,B.N.2004. Forecasting Sugarcane Production In India With ARIMA Model (online), New Delhi [19-02-09]. Unnikrishnan,T. and Ajitha,T.K. 2010. Application of ARIMA models and Co-integration Techniques in Kerala Agriculture, Proceedings of the International Seminar on Applied Statistics, Maharajas College, Ernakulam.

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Here an attempt is made to show the relationship between various factors that affecting directly and indirectly in determining the milk price for the last few years and also to estimate a regression equation by considering various other factors that influence the price of milk. The need for a more scientific way for fixation of price so that both consumer and farmer are protected by considering all the factors affecting milk price is explained.

[Anonymous].2008. Eleventh Five Year Plan (20072012). Planning Commission, Government of India

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CONCLUSION

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