Trend in Agricultural Prices in India

Rising foodgrain prices have been one of the most major concerns in recent years in India. Prices have been rising consistently, particularly since 2004 (Figure 1). While it is widely accepted that a minimum rise in prices could be owing to systematic and unavoidable fluctuations in production and policy, the present state of high prices is mainly attributed to a fall in the supply of foodgrains and rising demand in relation to supply. One of the ways to curtail excessive price rises would be to import foodgrains from abroad. However, even world markets are experiencing short-term fluctuations in foodgrains2 and thus, relying on international trade to deal with domestic supply problems to limit price rises may not be an easy solution, especially if the domestic market is not well-integrated to diversify the risk. The ability to diversify risk through domestic market integration remains an important factor that maximise the benefits derived from trade liberalisation.

In India, with the marked exception of rice, almost every commodity in the foodgrains category shows high rises and fluctuations in prices (Figure 2). One of the ways to stabilise prices would be to allow goods to flow freely across different states in India, which in turn, would lead to a better balance in the demand and supply of the agricultural commodity in question, perhaps leading to price stability. This study will consider market integration as one of the key factors that leads to better economic performance. It will study the level and fluctuations in foodgrain prices for selected agricultural commodities India, with a view to measure the level of market integration systematically across regions in the country, especially since such integration could be the key to price stability.

Wholesale and Retail Wheat Prices

This section will discuss the trend in wholesale3 (Figure 3) and retail (Figure 4, p 151) prices in the Indian wheat market during recent years. The wholesale price index captures information and constraints relating to production that could lead to variations across regions. The retail price in

dex, on the other hand, captures the additional costs of the commodities making 50 it to the final consumer in the market. F igures 3 and 4 provide a fair idea of the

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pattern of price variation in different domestic markets in India. The two figures 30 show that price variations move in a sim

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ilar pattern in the wholesale market, but do so in a lesser degree in the retail market. 10 The price data is further analysed in order to provide more scientific evidence of 0

Figure 3: Year on Year Price Variations – Wholesale Wheat Market

Apr, 1997Jul, 1997Oct, 1997Jan, 1998Apr, 1998Jul, 1998Oct, 1998Jan, 1999Apr, 1999Jul, 1999Oct, 1999Jan, 2000Apr, 2000Jul, 2000Oct, 2000Jan, 2001Apr, 2001Jul, 2001Oct, 2001Jan, 2002Apr, 2002Jul, 2002Oct, 2002Jan, 2003Apr, 2003

Methodology and Results

In order to test the presence of wheat market integration in India we use co-integration test and common trend method. According to Engle and Granger (1987), if a series Pwith no deterministic

t

components can be represented by a stationary and invertible ARMA (autoregressive moving average) process after differencing d times, the series is integrated of order d, that is P~ I(d).

t

A demonstration of a co-integration price process for two regions can be shown as follows: P1t = βP2t + Є1t …(a)

…(b)

P2t = P2, t-1 + Є2t

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sider the difference of equation (a),

ΔP1t = βΔP2t + ΔЄ1t = βЄ2t + Є1t – Є1,t-1 …(c)

From equation (c) we can infer that and P2t are integrated of order 1. Also

P1t if linear combination of P1t – βP2t is stationary then series P1t and P2t are cointegrated of order 1. In short, the attributes and elements of Pt are co-

Next, we tested the retail price variations and their integration across different regions using the same techniques. The retail price series are recently constructed and are for January 2001 to January 2007, taken from the Ministry of Consumer Affairs’ (Food and Public Distribution) monthly series. Given that data is not available for many regions and there is incomplete data on transportation costs, we expect low or no cointegration. Additionally, we did not make any zonal restrictions while testing for co-integration in retail price variations across the regional markets, and there exist co-integration for only integrated if there is a linear combination of them which is integrated of order zero. Given the notion of cointegration, we use a multivariate approach developed by Johansen (1988, 1991) to analyse the prices across regions

Source: CSO, India.

integration relation among the variables (wheat prices) considered in the study.

As an implication of co-integration we furthermore tested the existence of common trend in the variations of wholesale and retail price series of wheat among several regions of the country. Elements of ΔP, will have a

t

common trend if there exist a linear combination of them which is an innovation with respect to all observed information prior to time t (Engle and Vahid 1993). For this purpose we used the Stock and Watson (1988) common trends testing method. The null hypothesis is that k-dimensional time series Pt has m<=k common stochastic trends, and the alternative is that it has s<m common trends. We will use first order serial correlation matrix of Pt to test the hypothesis.

Source: CSO, India.

Table 3 briefly summarises the means and standard deviations in price variations across regions. Table 4 provides the results of the Johansen co-integrating test and shows that every null hypothesis is rejected.

Next, we analysed the co-features or common trend for the selected regions with regards to wholesale and retail prices. Our objective is to discover whether there is a common trend in the regional market, and we show that there exists more than one common trend and in fact, there exist several common trends in regional markets with regard to wheat in India.4 Intuitively, if there is more than one common trend then the markets will not converge.5 Thus, one has to be very careful with dealing with concepts such as the law of one price, co-integration and convergence hypothesis. Looking

Wheat Wholesale and Retail Price Movements, Co-integration and Common Trend in Price Variations

Table 1 provides the standard deviation in wholesale price variations and average price variations across the different regions. The wholesale price series were obtained from the Ministry of Agriculture, government of India and are taken for the regions under consideration from April 1997 to June 2003. Table 2 summarises the results of the co-integration analysis using trace statistics. The trace statistics test the null hypothesis that there are at most ‘r’ co-integrating vectors against the alternative that the rank is at the precise relationship between these concepts is beyond the scope of this paper. It is also very difficult to prove the law of one price and convergence in reality. With regard to retail price variation for the regional markets under selection (Table 5, p 153), the study shows that there are three common trends (filter value -32.0 against the critical value -24.7) at 5% critical value. In the wholesale price variation data we divided the regional markets into two groups to avoid the estimation constraint with higher dimen sions. There are no other restrictions for grouping the r egional markets. The first group of regions (Table 6, p 153) such

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as Ambala, Karnal, Jalandhar, Amritsar and Jaipur shows that low prices in the primary markets and to high prices in the termithere are four common trends (filter value -12.9 against the criti-nal markets. In addition, transportation costs can be a high procal value -12.4) at the 5% level. In the second group of regions portion of agricultural commodity prices as opposed to those for (Table 7) such as Jodhpur, Ludhiana, high-value technology goods and man-

Transaction Costs Influencing Market Integration in India

In developing countries, the existence of high transaction costs can serve as a big barrier to market integration, mainly because it interferes with the assumption of perfect mobility in the goods market. High transaction costs in developing countries arise primarily due to poor transport and communications infrastructure, inadequate contract enforcement mechanisms and unstable political environment. Given the difficulties in measuring transaction costs, it is difficult to try and capture their effect on market integration.

Transportation and communications are basic and necessary infrastructure for market integration. The markets in India have continued to face problems with regards to such basic infrastructure. Transaction costs can be high owing to an inefficient transport system or because of long distances between markets and the perishable nature of commodities. Low correlation in prices across different regions can also be a result of transport bottlenecks which obstruct the flow of goods from surplus to deficit regions6 resulting in excessively depressed or high prices. Thus, an excessive accumulation of goods can lead to artificially

Economic & Political Weekly

EPW

structed for 15 major states in India, stretching from 1993-94 to 2004-05. We found huge variations in the transportation and communication endowments across states in the country (Figure 5, p 154). We concluded that variation in the levels of infrastructure was one of the most important factors affecting the degree of market integration.

The variables used in the construction of the infrastructure index are: State-wise density of rail routes; State-wise density of road routes; and State-wise tele-density.

Another important factor that could account for price variations in the agricultural market is storage. Storage, or inter-temporal trade, could be a substitute to inter-regional trade, since good storage facilities could smooth the impact of supply shocks (Shiue

Table 8: Transportation and Communication Infrastructure Index (1993-2004)

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Market integration is a necessary condition for stabilising prices

Figure 5: Index of Transport and Communication Infrastructure (2004-05)

across regions, both within domestic and in global markets. In re

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cent years, the Indian economy has seen several policy changes leading to higher growth in gross domestic product. However, growth within agriculture has lagged behind and a number of bot

240

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tlenecks exist which have led to relatively high fluctuations within the prices of agricultural commodities. We have analysed the level

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of market integration in the context of wheat in India during recent years by looking at variations in both, the retail (consumer side)

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and wholesale (supplier side) price data. We used a sample of regional markets across the country for the purposes of our study.

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Our study also shows that although there is long-run market integration with regard to wholesale prices, this does not hold true for retail prices for the selected regions. One of the most im

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portant factors that could explain this disparity could be differences in infrastructure endowments across regions. Our in

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frastructure has tried to capture these variations and shows that

Source: Authors’ calculations, using Economic Intelligence Unit data, CMIE, Mumbai.

Kerala 244 Punjab 222 Gujarat 164 Haryana 161 Karnataka 156 Maharashtra 160 Andhra Pradesh 146 Tamil Nadu 174 Assam 139 Bihar 128 Orissa 133 West Bengal Uttar Pradesh 140 Rajasthan 124 Madhya Pradesh 122 ♦♦♦141 ♦♦♦♦♦♦♦♦♦♦♦♦

Notes

1 According to Stock and Watson (1988) cointegrated multiple time series share at least one common trend.

2 In the case of wheat, a sharp decline in world production in 2006-07 (estimated to be 590 million tonnes compared to 618 million tonnes in 2005-06) resulted in an increase in international prices from an average of $152.4 (for US hard red wheat) during January-December 2005 to $212.1 in October 2006 (Economic Survey 2006-07).

3 While there is no change in the operational content of the concept of wholesale prices, it was clarified that the price quotations pertained to bulk transactions, generally at an early stage of trading. It was also found that “wholesale price” data are frequently collected, where unavoidable, from a variety of sources such as ex-farm, ex-factory gate, ex-mine level and could be either with transportation cost or without. They are sometimes akin to producer prices, but by no means always or even generally so. In fact, it is felt that in future a good part of manufactured products prices would have to be collected from traded data rather than the more commonly used company cost/price data. In several cases, retail prices are used or those for which one-off deals take place.

4 A filter value statistic greater than the critical

References

– (1992): “Determination of Co-integration Rank in the Presence of a Linear Trend”, Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, Vol 54(3), pp 383-97, August.

Lele, U (1967): “Market Integration: A Study of Sorghum Prices in Western India”, Journal of Farm Economics, Vol 49, Part 1: 147-159

Rapsomanikis, G, D Hallam and P Conforti (2004): “Market Integration and Price Transmission in Selected Food and Cash Crop Markets of Developing Countries: Review and Applications”, Commodity Market Review (Rome: Food and Agricultural Organisation).

Samuelson, P (1952): “Spatial Price Equilibrium and Linear Programming”, American Economic Review, 42, 283-303.

Shiue, C (2002): “Transport Costs and the Geography of Arbitrage in Eighteenth-Century China”, The American Economic Review, Vol 92, No 5: 1406-19.

Stock and Watson (1988): “Testing for Common Trends”, Journal of American Statistical Association, Vol 83, 404, pp 1097-1107.

Vahid, F and R F Engle (1993): “Common Trends and Common Cycles”, Journal of Applied Econometrics, Vol 8: 341-60.

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