COMMODITY PRICE ANALYSIS

Similar documents
THEORY OF POPULATION CHANGE: R. A. EASTERLIN AND THE AMERICAN FERTILITY SWING

OUTLOOK FOR SUGAR CONSUMPTION IN ASIA. Y i-ting, W ong Taiwan Sugar Corporation. Chairman, Ladies and Gentlemen:

Inflation projection of the National Bank of Poland based on the NECMOD model

Our Technical Reports

Russian food consumption patterns during economic transition and its effects on the prevalence of chronic diseases

Biofortified pearl millet cultivars to fight iron and zinc deficiencies in India

The Global Economic Crisis and HIV Prevention and Treatment Programmes: Vulnerabilities and Impact. Executive Summary TRINIDAD AND TOBAGO

Regional Economic Report January March 2015

FOOD SUPPLY, DISTRIBUTION, CONSUMPTION AND NUTRITIONAL STATUS IN BANGLADESH

MOMENTUM OF TIME. Castor Oil Consumption Outlook and Emerging Trend- India

P. Nasurudeen, Anil Kuruvila, R. Sendhil and V. Chandresekar*

Analysis and Interpretation of Data Part 1

SUPPLY OF OPIATE RAW MATERIALS AND DEMAND FOR OPIATES FOR MEDICAL AND SCIENTIFIC PURPOSES

Results & Statistics: Description and Correlation. I. Scales of Measurement A Review

Agricultural Policies and Obesity: The Linkages Between Farm Commodities and Retail Food Products

CASTOR SEED SEASONAL REPORT

Distinguished guests, ladies and gentlemen, I am delighted to have the privilege to speak to you today. I come from Canada, and over the past few

Brookings Institution, March 4, 2013 Laura Papi and IMF India Team

highest in the world.

Rising Incomes and Nutrition in China

Trends and Differentials in Fertility and Family Planning Indicators of EAG States in India

Thursday, April 3, 2003, Chandigarh, India Palak Metal Paneer

Cassava in the Philippines. Algerico M. Mariscal and Jose L. Bacusmo

Nutrient Intake Optimization in Karnataka: A Linear Programming Approach

HOW CAN DEL MONTE COEXIST WITH THE ATKINS DIET? Based on: Food Consumption and Marketing

Songpu Variety Common Carp Exhibit Rapid Growth on Soy-Based Diet in Harbin Feeding Trial

CONTRACEPTIVES SAVE LIVES

Empirical Analysis of the Impact of Income on Dietary Calorie Intake in Nigeria. Babatunde, R. O

WFP Ethiopia Drought Emergency Household Food Security Monitoring Bulletin #3

International Zinc Association

The Effects of Soybean Protein Changes on Major Agricultural Markets

Will China s Zinc Consumption Keep on Growing? Ronghui Zhang

Grass Carp Exhibit Excellent Growth and Feed Conversion on Cost Efficient, Soy-Based Diet

Rising Food Prices Will Result in Severe Declines in Mineral and Vitamin Intakes of the Poor

Short-term Inflation analysis and forecast. August 2018 RESEARCH SERVICES DEPARTMENT RESEARCH AND ECONOMIC PROGRAMMING DIVISION

Table Egg Industry Outlook

Short-term Inflation analysis and forecast. December 2017 RESEARCH SERVICES DEPARTMENT RESEARCH AND ECONOMIC PROGRAMMING DIVISION

High Oleic Soybean Oil Panel. National Institute of Oilseed Products March 17, 2015

A Simple Demand Supply Model of Alcohol Consumption in India Kanupriya Suthar Independent Researcher, India

Add a little color to your diet. The truth behind what you eat.. And don t!

14th Biennial Sunflower Conference June Consumer Trends & Usage of Fats & Oils. Charles Aldersey

This study provides an evaluation of the impact of the Directive as required under the Directive. The aim of the evaluation is to:

COMPETITIVENESS OF CANADIAN AGRI-FOOD EXPORTS

The Most Undervalued Metal on the Market Today

2.4. DAILY DIETARY INTAKE XA H.S. DANG Low Level Counting Laboratory, Bhabha Atomic Research Centre Hospital, Mumbai, India

Sulphur Fertilizer Effect on Crop Development & Quality

Using food consumption data to assess nutrition and health impacts of interventions: An example from Malawi

Interpretation of Data and Statistical Fallacies

Ex Post-Evaluation Brief ETHIOPIA: Family Planning and HIV Prevention I and II

1.1 Overview Evolution of the World Drug Problem

Addressing Change in the Swine Feed Market John F. Patience Iowa State University Ames, IA

High Value Soybean Composition

FOOD FORTIFICATION LEGISLATION AND STANDARDS: IN PRACTICE PHILIP RANDALL (WITH CONTRIBUTIONS FROM QUENTIN JOHNSON)

Projections of tobacco production, consumption and trade to the year 2010

2025 Beverage Calories Initiative:

What We ll Cover: Training for Performance

Center for Applied Economic Research

A Comparison of Food Consumption Pattern in Rural and Urban Areas of Bangladesh between 2005 and 2010

Short-term Inflation analysis and forecast. September 2017 RESEARCH SERVICES DEPARTMENT RESEARCH AND ECONOMIC PROGRAMMING DIVISION

Revisiting Barriers to Trade: Do Foregone Health Benefits Matter?

optimal protein level for broilers the response to dietary protein level Ross Tech GENOTYPE: Rate of response and optimal level of

The Millennium Development Goals Report. asdf. Gender Chart UNITED NATIONS. Photo: Quoc Nguyen/ UNDP Picture This

WFP Ethiopia Drought Emergency Household Food Security Monitoring Bulletin #2

Measuring the Illegal Drug Economy of Australia in a National Accounts Framework: Some Experimental Estimates Drug Policy Modelling Program Symposium

Balance Sheets 1. CHILD HEALTH... PAGE NUTRITION... PAGE WOMEN S HEALTH... PAGE WATER AND ENVIRONMENTAL SANITATION...

Country Profile: Food Security Indicators

The Case for Flour Fortification

STATISTICAL RELEASE APRIL

Non-Technical Summary of: The War on Illegal Drug Production and Trafficking: An Economic Evaluation of Plan Colombia 1

Abstract Process Economics Program Report 235 CHEMICALS FROM ETHANOL (November 2007)

Scenario of Castor Seed

Infant TDS. Results of the ANSES study on dietary exposure of children under 3 years of age to chemical substances

Steve R. Meyer, Ph.D. Vice-President, Pork Analysis EMI Analytics

UPPER MIDWEST MARKETING AREA ANALYSIS OF COMPONENT LEVELS AND SOMATIC CELL COUNT IN INDIVIDUAL HERD MILK AT THE FARM LEVEL 2002

Strategy Challenging homelessness. Changing lives.

USER SPECIFICATIONS FOR QUINTOLUBRIC 888 Series DESCRIPTION OF THE MOST IMPORTANT PROPERTIES AND THE POSSIBLE VARIATIONS AND TOLERANCES

How to Develop a Balanced Program for Pecan and Chili. Robert R Smith

Basic Statistics 01. Describing Data. Special Program: Pre-training 1

Südzucker Group Capital market forum Rhine Neckar

THE CHALLENGE OF IMPROVING FISH CONSUMPTION IN DEVELOPING COUNTRY : THE CASE STUDY OF INDONESIA

Fact Sheet. Data, Information & Economic Analysis Livestock Marketing Information Center

Food Consumption and Calorie Intake in Contemporary India*

ECONOMICS Component 2 Exploring Economic Issues

# $ pages In Stock. Report Description

Investor Presentation

JOINT FAO/WHO FOOD STANDARDS PROGRAMME CODEX COMMITTEE ON FATS AND OILS 25 th Session Kuala Lumpur, Malaysia, 27 February - 3 March 2017

An Economic Analysis of Changes in the Per Capita Nutrient Intake and Nutritional Inadequacy in Tamil Nadu, India

Prospective study on nutrition transition in China

New Features in economic Modelling of Nutrition

Aligning the food system to meet dietary needs: fruits and vegetables

Miao Zhen, John Beghin and Helen Jensen Iowa State University CMD Meeting, Banff, Alberta September 28-30,2009

REVIEW PROBLEMS FOR FIRST EXAM

Yield and quality of cumin as influenced by FYM enriched micronutrients

IMPACT OF PRE-SLAUGHTER WITHDRAWAL OF VITAMIN SUPPLEMENTS ON PIG PERFORMANCE AND MEAT QUALITY. conditions was not addressed in the present study.

Conditional spectrum-based ground motion selection. Part II: Intensity-based assessments and evaluation of alternative target spectra

c. Construct a boxplot for the data. Write a one sentence interpretation of your graph.

5 $3 billion per disease

Randomness Rules: Living with Variation in the Nutrient Composition of Concentrate Feeds 1

Singapore Press Holdings. 1Q FY12 Financial Results 10 January 2012

Transcription:

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

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 3.2.1 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

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. 3.2.2 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

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, 2009. 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

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. 3.3.1 SELECTED COMMODITIES 3.3.1.1 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

3.3.1.2 Energy Products 1. Electricity 2. LPG 3. Petrol 3.3.1.3 Agricultural Inputs 1. Fertilizers and Pesticides 3.3.1.4 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

The time series plot is for entire 15 year period as well as for current 26 months period of September 2007 to October, 2009. The plots are for both real data and nominal data. The data analysis indicates several important pointers about commodity price movement. 3.3.2 DESCRIPTIVE DATA The descriptive statistic is summarized in the table below. 47

TABLE-3.1 DESCRIPTIVE STATISTICS OF SELECTED COMMODITY PRICE INDICES: FOR THE PERIOD 1994-2009 (15 YEARS) Std. Skewn Kurto Minim Maxim Mean Dev. CV ess sis um um Atta Nominal WPI 177.3 46.56 26.25 0.342-0.84 99.3 259.7 Atta Real WPI 104.6 9.295 8.884 0.630 0.672 82.61 138.0 Bajra Nominal WPI 187.6 44.45 23.69 0.866 0.488 114.2 322.1 Bajra Real WPI 111.9 12.69 11.34 0.400 0.164 87.18 148.3 Bhindi Nominal WPI 194.0 60.67 31.26 0.495-0.11 82.80 394.4 Bhindi Real WPI 115.8 30.60 26.40 1.530 4.844 65.88 283.9 Brinjal Nominal WPI 216.0 66.11 30.59 0.531-0.08 78.30 423.9 Brinjal Real WPI 128.9 30.63 23.76 0.485-0.25 70.41 214.9 Cabbage Nominal WPI 161.6 70.29 43.48 0.625 0.166 45.10 420.8 Cabbage Real WPI 97.16 40.09 41.26 0.687 0.442 31.36 231.5 Cashew Nominal WPI 134.2 20.17 15.02 0.532 0.296 96.50 192.5 Cashew Real WPI 81.31 9.406 11.56 0.182-1.00 62.61 101.4 Fresh Coconut Nominal WPI 127.3 24.06 18.90-0.259-0.89 76.40 170.6 Coconut Real WPI 77.66 16.60 21.37 0.731-0.10 50.91 129.9 48

Wheat Nominal WPI 175.5 39.94 22.76 0.019-0.66 104.4 254.9 Wheat Real WPI 104.1 8.043 7.719 0.617-0.06 88.85 125.8 Rice Nominal WPI 163.2 30.52 18.70 0.22 0.07 106.2 243.3 Rice Real WPI 97.92 8.632 8.815 0.719 0.448 84.19 124.3 Potato Nominal WPI 171.5 79.94 46.60 0.855 0.814 58.60 478.5 Potato Real WPI 101.0 40.26 39.84 0.928 0.936 38.35 245.2 Onion Nominal WPI 155.3 76.90 49.49 1.725 4.323 48.00 541.0 Onion Real WPI 92.17 45.08 48.90 3.377 16.04 39.93 389.4 Electricity Nominal WPI 209.3 57.88 27.65-0.320-1.49 113.6 281.9 Electricity Real WPI 122.7 14.10 11.48-0.042-1.27 94.50 146.3 LPG Nominal WPI 245.0 90.53 36.94-0.241-1.45 109.5 402.9 LPG Real WPI 140.7 29.22 20.76-0.472-1.28 87.18 183.7 Petrol Nominal WPI 177.7 50.89 28.63 0.386-1.02 106.5 279.9 Petrol Real WPI 104.3 10.45 10.01 0.346-0.14 84.79 130.0 Fertilizers & Pesticides Nominal WPI 154.3 21.09 13.66-0.178-1.00 103.3 192.0 Fertilizers & Pesticides Real WPI 93.47 8.943 9.567-0.463-0.76 75.02 109.8 Zinc Nominal WPI 148.4 51.14 34.45 1.980 3.617 100.0 350.0 Zinc Real WPI 88.89 22.32 25.10 0.988 1.410 50.71 172.4 Iron Ore Nominal WPI 371.5 392.3 105.6 1.178-0.02 70.20 1365 49

14 Iron Ore Real WPI 187.5 161.3 86.02 1.013-0.52 55.89 557.1 Brass Sheets & Strips Nominal WPI 162.8 68.01 41.77 1.672 1.432 97.50 356.4 Brass Sheets & Strips Real WPI 95.16 23.61 24.81 1.738 2.643 66.73 175.5 Enameled Copper Wires Nominal WPI 154.8 53.90 34.80 1.324 0.478 104.6 297.4 Enameled Copper Wires real WPI 89.27 16.53 18.51 0.885-0.03 65.62 129.6 Nickel Alloy Nominal WPI 184.5 114.9 62.26 1.446 0.583 97.90 473.4 Nickel real WPI 103.3 48 41.90 40.54 1.723 1.750 70.21 222.4 Source: Author s Calculations 50

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 253.9 2.956 1.16 0.057-0.01 248.0 259.7 Atta Real WPI 107.1 4.557 4.25 0.448-0.49 101.5 116.7 Bajra Nominal WPI 266.2 34.07 12.7 0.559-1.49 234.1 322.1 Bajra Real WPI 111.8 10.29 9.20 0.518-1.29 100.8 129.6 Bhindi Nominal WPI 275.3 43.10 15.6 0.120-0.71 203.3 356.2 Bhindi Real WPI 116.3 19.67 16.9 0.471-0.74 87.55 153.4 Brinjal Nominal WPI 303.5 54.75 18.0 0.148-0.28 198.0 423.9 Brinjal Real WPI 128.0 23.92 18.6 0.472-0.43 93.04 182.5 Cabbage Nominal WPI 219.6 76.49 34.8 0.708 0.488 103.3 420.8 Cabbage Real WPI 92.55 32.20 34.7 0.821 1.022 44.48 181.2 Cashew Nominal WPI 165.9 16.80 10.1 0.169-1.59 143.5 192.5 Cashew Real WPI 69.79 4.475 6.41 0.020-1.19 62.61 77.48 Fresh Coconut Nominal 148.3 13.67 9.22-0.506-1.21 123.0 163.4 51

WPI Coconut Real WPI 62.55 5.806 9.28-0.208-1.05 50.91 70.37 Wheat Nominal WPI 240.8 7.427 3.08 0.062-1.18 229.8 254.9 Wheat Real WPI 101.5 2.645 2.60 1.209 1.270 98.04 108.1 Rice Nominal WPI 216.3 17.39 8.04 0.091-1.72 193.1 243.3 Rice Real WPI 91.04 4.151 4.55-0.168-1.36 84.19 97.92 Potato Nominal WPI 266.4 81.85 30.7 1.389 1.063 177.0 478.5 Potato Real WPI 111.9 31.90 28.4 1.140 0.675 71.24 192.5 Onion Nominal WPI 232.0 52.62 22.6 0.239-0.84 153.3 322.8 Onion Real WPI 97.78 22.12 22.6 0.544-0.08 66.02 151.6 Electricity Nominal WPI 275.0 3.940 1.43-0.022-0.48 269.2 281.9 Electricity Real WPI 116.1 5.711 4.91 0.286-0.13 108.3 128.1 LPG Nominal WPI 357.6 20.40 5.70 0.520-0.80 334.8 402.9 LPG Real WPI 150.9 10.63 7.04 0.702-1.15 141.8 173.5 Petrol Nominal WPI 250.4 19.80 7.91 0.370-0.89 224.2 279.9 Petrol Real WPI 105.8 11.16 10.5-0.025-1.28 90.23 120.5 Fertilizers & Pesticides Nominal WPI 185.4 5.996 3.23-1.242-0.02 173.7 192.0 Fertilizers & Pesticides Real WPI 78.22 2.931 3.74 0.220-1.95 75.02 81.74 Zinc Nominal WPI 162.4 23.52 14.4-0.002-0.54 120.4 210.9 52

Zinc Real WPI 68.82 12.34 17.9 0.556 0.129 50.71 99.10 Iron Ore Nominal WPI 1170 148.2 12.6-1.014 0.485 827.8 1365.2 Iron Ore Real WPI 492.9 58.90 11.9-0.501-1.24 389.0 Brass Sheets & Strips Nominal WPI 253.0 45.52 17.9-0.731-0.68 165.8 315.50 Brass Sheets & Strips Real WPI 107.5 23.63 21.9-0.302-0.75 66.73 148.26 Enameled Copper Wires Nominal WPI 248.5 36.19 14.5-0.237-1.20 185.8 297.40 Enameled Copper Wires real WPI 105.3 18.65 17.7-0.213-1.47 74.78 129.60 Nickel Alloy Nominal WPI 370.2 61.13 16.5 0.07-1.12 298.8 473.40 Nickel real WPI 157.3 88 32.94 20.9 32 0.306-0.67 120.2 222.46 Source: Author s Calculations 53

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 231.4 26.57 11.4-0.555-1.47 186.7 259.70 Atta Real WPI 107.9 7.293 6.75 0.771-0.07 96.38 126.89 Bajra Nominal WPI 235.3 34.91 14.8 1.022 0.751 178.1 322.10 Bajra Real WPI 109.3 7.501 6.85 0.984 0.916 96.32 129.64 Bhindi Nominal WPI 242.5 49.91 20.5 0.084-0.61 157.0 356.20 Bhindi Real WPI 112.9 20.40 18.0 0.194-0.92 77.34 153.40 Brinjal Nominal WPI 273.0 59.37 21.7 0.196-0.38 155.2 423.90 Brinjal Real WPI 127.4 25.90 20.3 0.514-0.10 83.93 196.48 Cabbage Nominal WPI 196.8 71.50 36.3 0.424 0.369 74.80 420.80 Cabbage Real WPI 91.67 31.53 34.3 0.192-0.18 36.84 181.22 Cashew Nominal WPI 156.6 13.44 8.58 1.295 0.736 138.5 192.50 Cashew Real WPI 73.31 4.967 6.77-0.450-0.75 62.61 82.315 Fresh Coconut Nominal 140.9 15.46 10.9 0.456-1.33 118.8 167.40 54

WPI Coconut Real WPI 66.21 9.180 13.8 1.395 1.534 50.91 90.535 Wheat Nominal WPI 217.7 23.40 10.7-0.237-1.38 180.0 254.90 Wheat Real WPI 101.5 4.399 4.33 0.734 0.889 92.92 115.12 Rice Nominal WPI 192.3 22.35 11.6 0.95-0.34 168.5 243.30 Rice Real WPI 89.61 3.256 3.63 0.484-0.49 84.19 97.927 Potato Nominal WPI 235.4 68.32 29.0 1.407 2.708 126.7 478.50 Potato Real WPI 109.3 26.88 24.5 0.840 0.683 65.92 192.59 Onion Nominal WPI 196.5 66.35 33.7 0.586-0.69 112.1 352.70 Onion Real WPI 90.92 27.81 30.5 0.912 0.140 56.45 165.74 Electricity Nominal WPI 269.1 8.369 3.10-0.764-0.35 252.2 281.90 Electricity Real WPI 126.3 9.27 7.33-0.587-0.85 108.3 138.25 LPG Nominal WPI 342.3 18.03 5.26 1.444 2.129 311.0 402.90 LPG Real WPI 160.5 11.34 7.06-0.426-0.87 141.8 181.07 Petrol Nominal WPI 241.2 20.39 8.45 0.067-0.38 204.6 279.90 Petrol Real WPI 113.1 10.44 9.23-0.538 0.034 90.23 130.09 Fertilizers & Pesticides Nominal WPI 176.4 8.213 4.65 0.696-1.09 165.4 192.00 Fertilizers & Pesticides Real WPI 82.71 4.679 5.65-0.152-1.03 75.02 89.995 Zinc Nominal WPI 192.8 64.39 33.3 0.795-0.55 117.0 350.00 55

Zinc Real WPI 90.90 32.39 35.6 0.876-0.40 50.71 172.41 Iron Ore Nominal WPI 866.5 282.2 32.5 0.201-1.10 421.9 1365.2 Iron Ore Real WPI 396.4 97.72 24.6 0.032-0.75 217.8 557.14 Brass Sheets & Strips Nominal WPI 236.4 73.69 31.1 0.203-1.51 145.0 356.40 Brass Sheets & Strips Real WPI 110.0 33.15 30.1 0.576-1.04 66.73 175.56 Enameled Copper Wires Nominal WPI 216.6 46.52 21.4 0.30-1.45 152.2 297.40 Enameled Copper Wires real WPI 100.6 17.35 17.2 0.527-1.35 74.78 129.60 Nickel Alloy Nominal WPI 315.1 115.0 36.5-0.205-1.24 136.0 473.40 Nickel real WPI 145.3 96 49.95 34.3 55 0.078-1.17 70.21 222.46 Source: Author s Calculations 56

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 167.5 13.96 8.33 0.646-0.81 149.0 198.50 Atta Real WPI 102.7 6.569 6.39 1.029 0.861 92.71 122.11 Bajra Nominal WPI 179.8 22.28 12.3 0.048-1.26 140.1 216.80 Bajra Real WPI 111.1 18.36 16.5 0.468-0.94 87.18 148.33 Bhindi Nominal WPI 177.0 38.57 21.7 0.440 0.192 96.50 288.50 Bhindi Real WPI 108.6 23.59 21.7 0.565 0.842 66.90 188.80 Brinjal Nominal WPI 199.8 43.98 22.0 0.520-0.52 126.2 308.90 Brinjal Real WPI 123.3 29.94 24.2 0.494-0.78 78.53 202.16 Cabbage Nominal WPI 154.4 58.96 38.1 0.53-0.38 71.30 307.70 Cabbage Real WPI 95.61 37.99 39.7 0.45-0.59 44.36 191.47 Cashew Nominal WPI 130.2 6.94 5.33 0.190 0.173 116.1 145.90 Cashew Real WPI 80.32 8.743 10.8 1.007 0.021 68.68 101.46 Fresh Coconut Nominal WPI 124.8 24.56 19.6-0.154-1.29 84.50 169.70 57

Coconut Real WPI 76.58 15.07 19.6 0.393-0.61 52.58 110.50 Wheat Nominal WPI 177.3 4.58 2.58 0.949 2.911 164.7 192.60 Wheat Real WPI 109.1 7.379 6.76 0.530-0.39 96.26 125.80 Rice Nominal WPI 167.9 4.024 2.39 0.605 0.245 161.5 178.80 Rice Real WPI 103.5 8.961 8.65 0.530 0.050 88.31 124.33 Potato Nominal WPI 138.9 59.47 42.7 0.805-0.40 58.60 286.90 Potato Real WPI 85.01 35.88 42.2 0.873-0.30 38.35 174.19 Onion Nominal WPI 132.8 36.02 27.1 0.441-0.51 77.40 222.60 Onion Real WPI 81.35 21.19 26.0 0.410-1.00 50.65 126.13 Electricity Nominal WPI 220.0 28.98 13.1-0.690-0.81 166.3 252.80 Electricity Real WPI 134.3 10.15 7.55-0.895-0.19 108.8 146.32 LPG Nominal WPI 257.4 40.03 15.5-1.216 0.164 174.6 311.00 LPG Real WPI 157.0 17.67 11.2-1.271 0.585 114.7 183.72 Petrol Nominal WPI 162.9 14.08 8.64 0.808-0.25 147.5 199.40 Petrol Real WPI 99.81 3.719 3.72-0.590 1.018 89.55 107.84 Fertilizers & Pesticides Nominal WPI 157.1 8.675 5.51-1.077 0.065 139.1 165.40 Fertilizers & Pesticides Real WPI 96.45 3.362 3.48-0.988 0.303 89.07 101.63 Zinc Nominal WPI 131.3 20.00 15.2 0.455-1.42 108.9 168.70 Zinc Real WPI 81.53 17.43 21.3 0.527-1.42 62.91 112.51 58

Iron Ore Nominal WPI 142.1 73.17 51.4 4.683 22.45 103.8 534.90 Iron Ore Real WPI 86.09 37.57 43.6 46 4.731 22.97 67.93 289.29 Brass Sheets & Strips Nominal WPI 129.8 7.071 5.44-0.489 2.511 109.1 145.70 Brass Sheets & Strips Real WPI 79.81 5.147 6.44 0.274-0.75 71.44 89.005 Enameled Copper Wires Nominal WPI 121.8 8.509 6.98 0.231 0.064 106.2 145.80 Enameled Copper Wires real WPI 74.81 4.654 6.22-0.608-0.45 65.62 82.068 Nickel Alloy Nominal WPI 126.0 81 8.706 6.90 1.637 3.790 118.1 156.60 Nickel real WPI 77.34 3.376 4.36 0.013-0.50 71.51 84.694 Source: Author s Calculations 59

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 132.2 22.52 17.0 0.178-1.31 99.30 175.50 Atta Real WPI 103.1 12.21 11.8 0.735 0.146 82.61 138.05 Bajra Nominal WPI 147.0 14.42 9.81 1.103 2.057 114.2 191.40 Bajra Real WPI 115.3 8.804 7.62-0.429-0.27 97.04 133.10 Bhindi Nominal WPI 161.8 58.57 36.1 1.335 2.749 82.80 394.40 Bhindi Real WPI 125.9 41.35 32.8 1.264 2.288 65.88 283.94 Brinjal Nominal WPI 174.3 49.17 28.1 0.436-0.08 78.30 298.50 Brinjal Real WPI 136.0 34.61 25.4 0.320-0.30 70.41 214.90 Cabbage Nominal WPI 133.0 65.02 48.8 0.995 0.894 45.10 321.60 Cabbage Real WPI 104.2 48.61 46.6 0.685 0.066 31.36 231.53 Cashew Nominal WPI 115.4 10.59 9.17-0.241-0.98 96.50 132.60 Cashew Real WPI 90.43 4.088 4.52-0.155-0.15 81.36 99.550 Fresh Coconut Nominal WPI 115.9 24.31 20.9 0.234-1.08 76.40 170.60 60

Coconut Real WPI 90.37 15.04 16.6 0.676-0.58 68.70 129.93 Wheat Nominal WPI 130.6 19.94 15.2 0.355-1.12 104.4 173.20 Wheat Real WPI 101.9 9.258 9.07 0.689-0.56 88.85 122.77 Rice Nominal WPI 8.827 14.59 11.3 0.664 0.074 106.2 167.30 Rice Real WPI 100.7 4.976 4.93 0.915 1.549 92.67 116.34 Potato Nominal WPI 139.2 69.68 50.0 1.283 1.118 58.90 340.70 Potato Real WPI 108.6 50.28 46.2 0.948 0.291 44.85 245.28 Onion Nominal WPI 136.1 98.11 72.0 2.426 6.186 48.00 541.00 Onion Real WPI 104.2 68.50 65.7 2.433 6.359 39.93 389.48 Electricity Nominal WPI 137.7 16.77 12.1 0.005-1.25 113.6 166.30 Electricity Real WPI 107.6 5.792 5.38-0.170-0.55 94.50 115.64 LPG Nominal WPI 133.8 23.55 17.5 0.220-1.47 109.5 179.40 LPG Real WPI 104.2 11.42 10.9-0.048-1.33 87.18 124.75 Petrol Nominal WPI 128.0 19.33 15.1-0.180-1.92 106.5 148.30 Petrol Real WPI 99.91 9.389 9.39-0.329-1.39 84.79 112.94 Fertilizers & Pesticides Nominal WPI 129.1 7.420 5.74-1.426 3.182 103.3 139.80 Fertilizers & Pesticides Real WPI 101.4 4.143 4.08 0.131-0.67 92.89 109.89 Zinc Nominal WPI 120.3 15.11 12.5 0.598-0.36 100.0 161.00 Zinc Real WPI 94.22 7.789 8.26 1.595 3.481 83.16 122.62 61

Iron Ore Nominal WPI 97.88 20.62 21.0 0.772-0.12 70.20 137.50 Iron Ore Real WPI 76.69 14.41 18.7 0.226-1.31 55.89 100.89 Brass Sheets & Strips Nominal WPI 120.9 7.759 6.41-0.763 1.007 97.50 136.30 Brass Sheets & Strips Real WPI 95.37 9.396 9.85-0.165-0.15 73.71 113.39 Enameled Copper Wires Nominal WPI 120.0 8.155 6.79-0.096-0.75 104.6 134.60 Enameled Copper Wires real WPI 92.70 11.34 12.2 37-0.219-1.21 72.74 111.98 Nickel Alloy Nominal WPI 110.3 85 7.295 6.60-0.785-0.837 97.90 118.10 Nickel real WPI 86.62 3.013 3.47-0.268-0.96 81.53 91.561 Source: Author s Calculations 62

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. 3.3.3.1 Growth of Real Prices The average compounded real annual growth rate, over the period 1994-2009, 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 2009. 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

3.3.3.2 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 29.58. The same was 38.10 in the recent five years of 2004 to 2009, 20.98 in the period 1999-2004, and 23.68 in the period 1994-1999. In the most recent two years, coefficient of variation was 27.54. 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

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 7.719 1 Fertilizer 13.664 2 Rice 8.815 2 Cashew 15.027 3 Atta 8.884 3 Rice 18.7 4 Fertilizers-Pesticides 9.567 4 Coconut 18.901 5 Petrol 10.018 5 Wheat 22.76 6 Bajra 11.343 6 Bajra 23.69 7 Electricity 11.485 7 Atta 26.253 8 Cashew 11.568 8 Electricity 27.654 9 Copper Wires 18.518 9 Petrol 28.63 10 LPG 20.768 10 Brinjal 30.598 11 Coconut 21.376 11 Bhindi 31.266 12 Brinjal 23.763 12 Zinc 34.457 13 Brass Sheets & Strips 24.815 13 Copper 34.809 14 Zinc 25.109 14 LPG 36.943 15 Bhindi 26.408 15 Brass 41.774 16 Potato 39.841 16 Cabbage 43.487 17 Nickel 40.545 17 Potato 46.6 18 Cabbage 41.268 18 Onion 49.493 19 Onion 48.909 19 Nickel 62.262 20 Iron Ore 86.02 20 Iron Ore 105.614 (Source: Author s Calculations) 65

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

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 1.42 1 Fertilizers and 1.86 Pesticides 2 Fertilizers and 1.46 2 Cashew 1.99 Pesticides 3 Rice 1.48 3 Fresh Coconut 2.23 4 Petrol 1.53 4 Rice 2.29 5 Electricity 1.55 5 Wheat 2.44 6 Cashew 1.62 6 Electricity 2.48 7 Atta 1.67 7 Atta 2.62 8 Bajra 1.70 8 Petrol 2.63 9 Copper Wire 1.97 9 Bajra 2.82 10 LPG 2.11 10 Copper Wire 2.84 11 Coconut 2.55 11 Zinc 3.50 12 Brass-Strip & Sheet 2.63 12 Brass-Strip & Sheet 3.66 13 Brinjal 3.05 13 LPG 3.68 14 Nickel 3.17 14 Bhindi 4.76 15 Zinc 3.40 15 Nickel Alloy 4.84 16 Bhindi 4.31 16 Brinjal 5.41 17 Potato 6.40 17 Potato 8.17 18 Cabbage 7.38 18 Cabbage 9.33 19 Onion 9.75 19 Onion 11.27 67

20 Iron Ore 9.97 20 Iron Ore 19.45 (Source: Author s Calculations) 3.3.3.3 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 0.72. 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 0.734. 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

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. 3.3.3.4 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