COMMODITY PRICE ANALYSIS

Transcription

1 CHAPTER-03 COMMODITY PRICE ANALYSIS 3.1 OVERVIEW 3.2 PRICE CHANGES 3.3 PRICE ANALYSIS OF SELECTED COMMODOTIES 41

2 3.1 OVERVIEW Stability of commodity prices is necessary for optimal decisions by the producers and consumers alike. However, the commodity prices are probably more volatile than any other products resulting in many adverse effects. The commodity prices have been especially volatile in the last two years, 2008 and 2009, as indicated by the roller-coaster ride of crude oil prices. Even the agricultural commodity prices have seen wide swings. However, the prices of commodities, in general, have always been volatile. The trend rise in prices has been attributed to several reasons. One, a fundamental change in demand and supply balance. The supply has not kept pace with the demand. For example, it is premised that the oil being exhaustible in nature, and with substantial increase in demand, especially from China, India and other fast developing countries. However, this may not be the whole truth as price increase, especially in recent times, has been more than the imbalance. Also, the buffer stocks have been adequate to prevent any unreasonable price rise. 3.2 PRICE CHANGES TREND PRICE ANALYSIS Over a long period, all prices rise due to general inflation in the economy and for several product specific and economy-wide reasons. The major reason for trend price increase is a fundamental change in demand and supply balance. If the supply of a product does not keep pace with the demand, 42

3 prices would rise. The supply has not kept pace with the demand for most commodity products. The increase in demand is due primarily to increase in population and increase in income, apart from change in taste. The income levels are rising faster in countries with below global average income levels and have higher income elasticity for commodity consumption-not only agricultural products but also other products, e.g., gold and silver. Higher consumption of durable goods requires higher input requirements of metals. The supply has not kept pace with this income driven increase in demand, either due to limitations on some inputs, inadequate investments, or due to the negative intervention of nature. The second reason is the price rise due to increase in money supply in excess of requirement for real growth. Since the future real growth cannot be predicted in advance, the ex ante expectation of required money supply may not be the same as ex post requirements. This will result in the general inflation, though the real price rise may be zero. However, the trend prices are controlled, especially in recent times, by provisioning of the buffer stocks, which have been adequate to prevent any unreasonable price rise SEASONAL PRICE CHANGES The supply of many commodities is seasonal in nature. The seasonal price changes are common for commodities. Almost all agricultural commodities are produced only during certain periods of the year, though consumption is uniform over the year. Seasonality may also arise due to seasonal demand for commodities, for example, during festive season demand for certain commodities are substantially higher. Seasonality may arise due to planned and/or unplanned shutdown of commodity processing units. 43

4 3.2.3 HIGH FLUCTUATION IN PRICES The costs of trend price growth are zero (rational expectation models) or small. Seasonality also has predictable and small welfare costs. It is the unexpected changes in the prices which result in great welfare loss. High fluctuation in prices is mainly due to unpredictable and uncontrollable value of one input (e.g., rainfall) and speculative attacks on the prices. There has been increase in speculative activity, especially through use of derivative products. Speculative activity has increased due to increase in uncertainty as well as wider information asymmetry. Also, the income levels are rising faster in countries with below world average income levels and have higher income elasticity for commodity consumption-not only agricultural products but also other products, e.g., gold and silver. Higher consumption of durable goods requires higher input requirements of metals. The supply has not kept pace with the increase in demand, either due to limitations on some inputs, inadequate investments, or due to the negative intervention of nature. The countries are no longer isolated due to worldwide integration of economies. This has resulted in increased transfer of commodities leading to shortages in producing countries for products where the world prices are higher than the domestic prices. Thus, the close integration has its attendant costs, especially felt by large commodity producers/consumers. The prices of several commodities over time are analyzed herein. The data is collected for the period April, 1994 to October, The data are monthly average price index for the commodity in India. (A total of 187 data points). These price indices are nominal in nature. They are normalized by WPI to get a series of real price indices. Both nominal and real prices are analyzed to understand the behavior of prices over time. 44

5 3.3 PRICE ANALYSIS OF SELECTED COMMODOTIES Research in this chapter analyzes the price movement of selected commodities over a period of time. The commodities have been selected from different commodities groups so that a larger picture of commodity price movement is obtained. The prices of following products are compiled and analyzed SELECTED COMMODITIES Agricultural Products 1. Atta 2. Baja 3. Bhindi 4. Brinjal 5. Cabbage 6. Cashew 7. Coconut 8. What 9. Rice 10. Potato 11. Onion 45

6 Energy Products 1. Electricity 2. LPG 3. Petrol Agricultural Inputs 1. Fertilizers and Pesticides Metals 1. Nickel 2. Copper wire 3. Brass Sheets 4. Iron Ore 5. Zinc Descriptive statistics for these products are calculated for the entire 15 year period. The period is then divided in three almost equal 5-year periods and the descriptive statistics are calculated again for different periods as follows: 1. April, 1994 to June,1999 ( 63 data points) 2. July 1999 to August, 2004 (62 data points) 3. September 2004 to October, 2009 ( 62 data points) 46

7 The time series plot is for entire 15 year period as well as for current 26 months period of September 2007 to October, The plots are for both real data and nominal data. The data analysis indicates several important pointers about commodity price movement DESCRIPTIVE DATA The descriptive statistic is summarized in the table below. 47

8 TABLE-3.1 DESCRIPTIVE STATISTICS OF SELECTED COMMODITY PRICE INDICES: FOR THE PERIOD (15 YEARS) Std. Skewn Kurto Minim Maxim Mean Dev. CV ess sis um um Atta Nominal WPI Atta Real WPI Bajra Nominal WPI Bajra Real WPI Bhindi Nominal WPI Bhindi Real WPI Brinjal Nominal WPI Brinjal Real WPI Cabbage Nominal WPI Cabbage Real WPI Cashew Nominal WPI Cashew Real WPI Fresh Coconut Nominal WPI Coconut Real WPI

9 Wheat Nominal WPI Wheat Real WPI Rice Nominal WPI Rice Real WPI Potato Nominal WPI Potato Real WPI Onion Nominal WPI Onion Real WPI Electricity Nominal WPI Electricity Real WPI LPG Nominal WPI LPG Real WPI Petrol Nominal WPI Petrol Real WPI Fertilizers & Pesticides Nominal WPI Fertilizers & Pesticides Real WPI Zinc Nominal WPI Zinc Real WPI Iron Ore Nominal WPI

10 14 Iron Ore Real WPI Brass Sheets & Strips Nominal WPI Brass Sheets & Strips Real WPI Enameled Copper Wires Nominal WPI Enameled Copper Wires real WPI Nickel Alloy Nominal WPI Nickel real WPI Source: Author s Calculations 50

11 TABLE-3.2 DESCRIPTIVE STATISTICS OF SELECTED COMMODITY PRICE INDICES: FOR THE PERIOD NOVEMBER 2007 TO OCTOBER 2009 ( CURRENT TWO YEARS) Std. Skewn Kurto Minim Maxim Mean Dev. CV ess sis um um Atta Nominal WPI Atta Real WPI Bajra Nominal WPI Bajra Real WPI Bhindi Nominal WPI Bhindi Real WPI Brinjal Nominal WPI Brinjal Real WPI Cabbage Nominal WPI Cabbage Real WPI Cashew Nominal WPI Cashew Real WPI Fresh Coconut Nominal

12 WPI Coconut Real WPI Wheat Nominal WPI Wheat Real WPI Rice Nominal WPI Rice Real WPI Potato Nominal WPI Potato Real WPI Onion Nominal WPI Onion Real WPI Electricity Nominal WPI Electricity Real WPI LPG Nominal WPI LPG Real WPI Petrol Nominal WPI Petrol Real WPI Fertilizers & Pesticides Nominal WPI Fertilizers & Pesticides Real WPI Zinc Nominal WPI

13 Zinc Real WPI Iron Ore Nominal WPI Iron Ore Real WPI Brass Sheets & Strips Nominal WPI Brass Sheets & Strips Real WPI Enameled Copper Wires Nominal WPI Enameled Copper Wires real WPI Nickel Alloy Nominal WPI Nickel real WPI Source: Author s Calculations 53

14 TABLE-3.3 DESCRIPTIVE STATISTICS OF SELECTED COMMODITY PRICE INDICES: FOR THE PERIOD SEPTEMBER 2004 TO OCTOBER 2009 ( RECENT FIVE YEARS) Std. Skewn Kurto Minim Maxim Mean Dev. CV ess sis um um Atta Nominal WPI Atta Real WPI Bajra Nominal WPI Bajra Real WPI Bhindi Nominal WPI Bhindi Real WPI Brinjal Nominal WPI Brinjal Real WPI Cabbage Nominal WPI Cabbage Real WPI Cashew Nominal WPI Cashew Real WPI Fresh Coconut Nominal

15 WPI Coconut Real WPI Wheat Nominal WPI Wheat Real WPI Rice Nominal WPI Rice Real WPI Potato Nominal WPI Potato Real WPI Onion Nominal WPI Onion Real WPI Electricity Nominal WPI Electricity Real WPI LPG Nominal WPI LPG Real WPI Petrol Nominal WPI Petrol Real WPI Fertilizers & Pesticides Nominal WPI Fertilizers & Pesticides Real WPI Zinc Nominal WPI

16 Zinc Real WPI Iron Ore Nominal WPI Iron Ore Real WPI Brass Sheets & Strips Nominal WPI Brass Sheets & Strips Real WPI Enameled Copper Wires Nominal WPI Enameled Copper Wires real WPI Nickel Alloy Nominal WPI Nickel real WPI Source: Author s Calculations 56

17 TABLE-3.4 DESCRIPTIVE STATISTICS OF SELECTED COMMODITY PRICE INDICES: FOR THE PERIOD JULY 1999 TO AUGUST 2004 (SECOND 5-YEAR PERIOD OF 15 YEARS) Std. Skewn Kurto Minim Maxim Mean Dev. CV ess sis um um Atta Nominal WPI Atta Real WPI Bajra Nominal WPI Bajra Real WPI Bhindi Nominal WPI Bhindi Real WPI Brinjal Nominal WPI Brinjal Real WPI Cabbage Nominal WPI Cabbage Real WPI Cashew Nominal WPI Cashew Real WPI Fresh Coconut Nominal WPI

18 Coconut Real WPI Wheat Nominal WPI Wheat Real WPI Rice Nominal WPI Rice Real WPI Potato Nominal WPI Potato Real WPI Onion Nominal WPI Onion Real WPI Electricity Nominal WPI Electricity Real WPI LPG Nominal WPI LPG Real WPI Petrol Nominal WPI Petrol Real WPI Fertilizers & Pesticides Nominal WPI Fertilizers & Pesticides Real WPI Zinc Nominal WPI Zinc Real WPI

19 Iron Ore Nominal WPI Iron Ore Real WPI Brass Sheets & Strips Nominal WPI Brass Sheets & Strips Real WPI Enameled Copper Wires Nominal WPI Enameled Copper Wires real WPI Nickel Alloy Nominal WPI Nickel real WPI Source: Author s Calculations 59

20 TABLE-3.5 DESCRIPTIVE STATISTICS OF SELECTED COMMODITY PRICE INDICES: FOR THE PERIOD APRIL 1994 TO JUNE 1999 (FIRST FIVE YEARS OF 15 YEAR PERIOD) Std. Skewn Kurto Minim Maxim Mean Dev. CV ess sis um um Atta Nominal WPI Atta Real WPI Bajra Nominal WPI Bajra Real WPI Bhindi Nominal WPI Bhindi Real WPI Brinjal Nominal WPI Brinjal Real WPI Cabbage Nominal WPI Cabbage Real WPI Cashew Nominal WPI Cashew Real WPI Fresh Coconut Nominal WPI

21 Coconut Real WPI Wheat Nominal WPI Wheat Real WPI Rice Nominal WPI Rice Real WPI Potato Nominal WPI Potato Real WPI Onion Nominal WPI Onion Real WPI Electricity Nominal WPI Electricity Real WPI LPG Nominal WPI LPG Real WPI Petrol Nominal WPI Petrol Real WPI Fertilizers & Pesticides Nominal WPI Fertilizers & Pesticides Real WPI Zinc Nominal WPI Zinc Real WPI

22 Iron Ore Nominal WPI Iron Ore Real WPI Brass Sheets & Strips Nominal WPI Brass Sheets & Strips Real WPI Enameled Copper Wires Nominal WPI Enameled Copper Wires real WPI Nickel Alloy Nominal WPI Nickel real WPI Source: Author s Calculations 62

23 3.3.3 ANALYSIS The variability of price indices is substantial across all the commodities. However, the real prices have remained stable for most commodities and even declined for some commodities. Iron ore prices are the only one which has shown substantial real increase Growth of Real Prices The average compounded real annual growth rate, over the period , was highest at 11.2 percent for iron ore, 7.5 percent for potato 5.6 percent for onion and 2.4 percent for LPG. For most other products, real increase was marginal. (However, this may also be due to control over prices for some products.) However, the scenario is very different if one considers the last five year period from 2004 to Compounded annual growth rate for iron ore was 38.7 percent, for nickel 7.2 percent, for copper wire 7.4 percent, for bajra 7.2 percent, for most vegetables 7 to 31 percent and for rice 1.8 percent. In contrast, real wheat prices remained constant in this period. One can surmise that the commodity prices have a low trend growth over a longer period, the additional supply able to meet the additional demand except for the metals. However, as the income grew at a sustained pace, in recent years, the supply has not been able to keep pace with the demand. The high real price rise for most agricultural commodities and other commodities are unlikely to revert back to lower level as the growth rates are likely to remain at a higher level for at least the next couple of decades. The conclusion is evident: Need for productivity growth and/or newer and better technologies are a must. This could only happen if there is a proactive investment in newer technologies and policies. 63

24 Coefficient of Variation The variability of price indices is substantial across all the commodities even when the real prices have remained stable (for most commodities and even declined for some commodities). Average Coefficient of variation over a fifteen year period is The same was in the recent five years of 2004 to 2009, in the period , and in the period In the most recent two years, coefficient of variation was The coefficient of variation has remained high, but within a narrow range. However, in the last five years, it has substantially risen, an average rising by almost 27 percent over a longer period average. Not only real prices have increased in the last five years, variability has also increased substantially. Coefficient of variation is highest for the iron ore (86.02) followed by onions (48.909), nickel (40.5) and potato (39.8). Wheat (7.7) and rice (8.8) have the lowest coefficient of variation over the 15-year period. Bajra (11.3) also has relatively low coefficient of variation. High coefficient of variation is a pointer for a need for risk management and for products and markets. 64

25 TABLE-3.6 COMAPRISON OF COEFFICIENT O VARIATION FOR COMMODITY PRICE INDICES (1994 TO 2009) Sr. No. Product-Index WPI Real Coefficient Of Variation Sr. No. Product-Index WPI Nominal Coefficient Of Variation 1 Wheat Fertilizer Rice Cashew Atta Rice Fertilizers-Pesticides Coconut Petrol Wheat Bajra Bajra Electricity Atta Cashew Electricity Copper Wires Petrol LPG Brinjal Coconut Bhindi Brinjal Zinc Brass Sheets & Strips Copper Zinc LPG Bhindi Brass Potato Cabbage Nickel Potato Cabbage Onion Onion Nickel Iron Ore Iron Ore (Source: Author s Calculations) 65

26 Above table shows that the coefficient of variation is higher for metals compared to agricultural products. It is highest for iron ore, both for real price and nominal price. From among agricultural products, potato and onions show the highest COV. In fact for onions COV is almost 50 percent, for both real and nominal prices, indicating very high variability and hence the risk. Similarly, potato has about 40 percent and 46 percent COV for real and nominal price respectively. As against that the cereals have low COV. Both rice and wheat and even bajra, have low price risk. COV is higher for nominal prices compared to real prices. Inflation increases variability. 66

27 TABLE-3.7 COMAPRISON OF MAXIMUM TO MINIMUM PRICE FOR COMMODITY PRICE INDICES (1994 TO 2009) Sr. Product-Index Maximum to Sr. Product-Index Maximum to No. WPI Real Minimum Price Ratio No. WPI Nominal Minimum Price Ratio 1 Wheat Fertilizers and 1.86 Pesticides 2 Fertilizers and Cashew 1.99 Pesticides 3 Rice Fresh Coconut Petrol Rice Electricity Wheat Cashew Electricity Atta Atta Bajra Petrol Copper Wire Bajra LPG Copper Wire Coconut Zinc Brass-Strip & Sheet Brass-Strip & Sheet Brinjal LPG Nickel Bhindi Zinc Nickel Alloy Bhindi Brinjal Potato Potato Cabbage Cabbage Onion Onion

28 20 Iron Ore Iron Ore (Source: Author s Calculations) Skewness Skewness measures the asymmetry of the probability distribution of the variable under study. Over a fifteen year period, skewness is observed to be high for most products, being positive (i.e., positively skewed) for 17 out of 20 products under study. Skewness is as high as 3.37 for onions and 1.73 for brass and nickel. Skewness for wheat is 0.62 and for rice It is almost 1 for iron ore. High positive skewness is indicative of the fact that larger number of value are lying on the higher side of the mean value. If recent two year data are analyzed, metal group has shown a negative skewness, whereas the highest skewness is for wheat (1.01). For the recent five years, skewness is the highest for bajra (0.984), where for wheat it is Within metal group, zinc has the highest (0.726) skewness. Onion (0.91) and potato (0.84) also had high skewness. Petrol, electricity and LPG had negative skewness; however that may be due to controlled prices. It may also be due to the fact that during the period the crude oil prices had sporadic high values, raising the mean. Individual Price Movements: Nominal wheat price has grown with the inflation rate, keeping real prices nearly constant over a 15 year period. The same is true for wheat. Both have coefficient of variation of around 20. But the frequency of movement is high. Potato and onions, both, have the highest variation in prices. Standard deviation is almost 50 percent for nominal price and 40 percent for potato and 50 percent for onion real prices. Both standout as the products with probably the highest price fluctuations among all agricultural products. Real atta prices have been fluctuating with a small upward trend. Except a few outliers, real prices have fluctuated within ±10 % range. 68

29 Bajra prices have fluctuated with higher volatility and have shown higher upward trend. Standard deviation is about 23 per cent for nominal price and more than 11 per cent for real price. Need for risk mitigation is high. Bhindi prices have remained more or less static over the period though has shown considerable variation with low amplitude but high frequency, Brinjal, unlike Bhindi, have shown small upward movement over time. Prices have remained more or less static over the period though has shown considerable variation with low amplitude but high frequency, Coconut prices have in fact declined over time in real terms. It also has lower price variation. In the case of coconut, real income of producers is likely to have declined over time Conclusions Overall, it may be surmised that the most commodities have experienced positive and high skewness, many exceeding 1.0. The prices have not been symmetric and in most cases higher than the mean. Hence, though real prices may not have increased much, or even declined, the true values are generally higher than the mean and also there is a large dispersion as shown by the coefficient of variation. The real increase in prices is substantial in recent years. The increase is across the commodities, indicating large income effect (since population growth rates are declining). The most increases are in metal group followed by vegetables (in the sample of this study). The variability is much higher for metals as a group. Among agricultural products, vegetables have the highest variability and the cereals the lowest. Wheat and rice have particularly low COV. This is indicator of dispersion in sources of supply, more regionality for vegetables because of its perishabiity and more competitive market nature for cereals. The government should be more vigilant about the vegetables, especially onions and potato. 69