Global agriculture volume 6 developments issues and research

GLOBAL AGRICULTURE: DEVELOPMENTS, ISSUES, AND RESEARCH GLOBAL AGRICULTURE DEVELOPMENTS, ISSUES, AND RESEARCH VOLUME No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services GLOBAL AGRICULTURE: DEVELOPMENTS, ISSUES, AND RESEARCH Additional books in this series can be found on Nova‘s website under the Series tab Additional e-books in this series can be found on Nova‘s website under the e-book tab GLOBAL AGRICULTURE: DEVELOPMENTS, ISSUES, AND RESEARCH GLOBAL AGRICULTURE DEVELOPMENTS, ISSUES, AND RESEARCH VOLUME MARVIN R ROBERTSON AND JEFFERY I SCHMIDT EDITORS New York Copyright © 2015 by Nova Science Publishers, Inc All rights reserved No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher For permission to use material from this book please contact us: nova.main@novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works Independent verification should be sought for any data, advice or recommendations contained in this book In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services If legal or any other expert assistance is required, the services of a competent person should be sought FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS Additional color graphics may be available in the e-book version of this book Library of Congress Cataloging-in-Publication Data ISSN: 2168-0434 ISBN:  (eBook) Published by Nova Science Publishers, Inc † New York CONTENTS Preface Chapter Chapter Chapter Chapter Index vii Growth and Evolution in China‘s Agricultural Support Policies Fred Gale U.S Wheat Production Practices, Costs, and Yields: Variations Across Regions Gary Vocke and Mir Ali Afghanistan‘s Wheat Flour Market: Policies and Prospects Suresh Persaud World Raw Sugar Prices: The Influence of Brazilian Costs of Production and World Surplus/ Deficit Measures Stephen Haley 75 107 147 173 PREFACE This book explores the developments, issues and research outlook of global agriculture Topics discussed in this compilation include growth and evolution in china‘s agricultural support policies; U.S wheat production practices, costs, and yields: variations across regions; Afghanistan‘s wheat flour market: policies and prospects; and world raw sugar prices Chapter – China is perhaps the most prominent example of a developing country that has transitioned from taxing to supporting agriculture In recent years, Chinese price supports and subsidies have risen at an accelerating pace after they were linked to rising production costs Per-acre subsidy payments to grain producers now equal to 15 percent of those producers‘ gross income, but grain payments appear to have little influence on production decisions Chinese authorities began raising price supports annually to bolster incentives, and Chinese prices for major farm commodities are rising above world prices, helping to attract a surge of agricultural imports U.S agricultural exports to China tripled in value during the period when China‘s agricultural support was accelerating Overall, China‘s expansion of support is loosely constrained by World Trade Organization (WTO) commitments, but the country‘s pricesupport programs could exceed WTO limits in coming years Chinese officials promise to continue increasing domestic policy support for agriculture, but the mix of policies may evolve as the Chinese agricultural sector becomes more commercialized and faces competitive pressures Chapter – USDA‘s 2009 Agricultural Resource Management Survey (ARMS) provides the most recent data on U.S wheat production costs The wide variation in wheat production costs across the United States captured by the survey reflects the differences in cropping practices, yields, and costs of land, labor, and capital assets The North Central and Northern Plains regions viii Marvin R Robertson and Jeffery I Schmidt have the lowest and highest per bushel costs, respectively The two cost items that accounted for much of the regional differences in total production costs were machinery and fertilizer The survey found that 97 percent of the country‘s farms could have covered all their operating costs with the 2009/10 season average price of $4.87 per bushel if they had been able to attain the yields they expected at planting (as reported in the survey) However, only 79 percent would have been able to cover their operating costs with the yields they actually harvested The relatively high percentage of farmers who were apparently not covering these costs is attributed, in part, to a large number of farmers in the Southern Plains whose crops were adversely affected by severe weather Chapter – Afghanistan is among the world‘s largest importers of flour Afghan flour producers face challenges from inadequate domestic supplies of wheat and competition from imported flour, much of it from neighboring Pakistan where wheat producers and flour millers benefit from Government support Efforts to support Afghanistan‘s flour-milling sector by increasing border protections—if enforceable along the country‘s rugged borders— would lead to higher prices that harm consumers Similarly, efforts to boost domestic production of wheat for milling through import policies would require a difficult-to-enforce combination of flour and wheat tariffs or other restrictions that would also impose costs on consumers Free trade, entailing unhindered wheat and flour imports, including imports from Pakistan, may lead to stronger growth in domestic flour production and consumption, with relatively small losses in farm output Chapter – From the perspective of U.S sugar policy, there is increased interest in world sugar prices because world prices have been above domestic price support levels since 2009 and are forecast by the Organisation for Economic Co-operation and Development to remain above current support levels through 2021 Understanding the dynamics that affect the world price of sugar is the new imperative for U.S sugar policy There are three basic determinants of medium- to long-term world raw sugar pricing The first is the long-term equilibrium relationship between world raw sugar prices and costs of producing sugar in Brazil, the world‘s largest sugar producer and exporter An important effect on costs operates through the Brazilian currency exchange rate with the U.S dollar The second is the effect of medium-term world sugar supply-demand imbalances on pricing Two important measures from the U.S Department of Agriculture‘s world sugar Production, Supply, and Distribution (PSD) database are derived to show that relative stockholding has an important effect on the sensitivity of the world sugar prices to changes in overall world Preface ix sugar availability The third determinant is a risk-related component: how current prices are affected by errors in forecasting supply and demand balances of previous years due to unanticipated events The world sugar price includes a premium when there is a recent history of sugar deficits larger than what was initially predicted and conversely, a discount when there were surpluses larger than predicted World Raw Sugar Prices 167 changes in Center/South production costs on the world raw sugar price The other vari ables have the same signs as corresponding equation in table Included here is the interaction variable, meaning that the stocks-to-use ratio influences the magnitude of a world price change when there is a change in the world sugar surplus/deficit measure The effect of inaccurate forecasting of recent year world sugar surpluses/deficits influences the change in prices, as expected CONCLUSION This report has presented quantitative assessment of factors affecting the world price of raw sugar The main emphasis has been on Brazil because Brazil is world‘s leading producer and exporter of sugar Historically, Brazil‘s importance in world sugar has resulted from domestic policies tied to the promotion and development of ethanol Sugarcane area has grown to high levels (8.89 million hectares in 2011/12), leading to the largely realized potential to exert substantial influence on both world ethanol and sugar markets.9 This analysis has concluded that, over the long term, world sugar prices are determined by sugar production costs in Center/South Brazil It has also concluded that these costs are strongly affected by the exchange rate between the U.S dollar and the Brazilian currency, the real, mainly because sugar is traded in dollars in international markets As one would expect, deviations around long-term sugar-pricing trends result from world sugar surpluses and deficits (total world sugar production minus consumption) However, the magnitude of changes is qualified by the amount of world sugar being held in stocks Higher stockholding leads to smaller effects on world sugar prices than when stockholding is low Higher sugar prices can be expected in environments where there were unanticipated sugar deficits that led to higher prices in preceding marketing years The opposite is true when there are unanticipated sugar surpluses The market seemingly factors in a penalty for having made mistakes in forecasting sugar production for earlier years In 2007 and 2008, when many commodities around the world experienced markedly higher prices, world sugar prices remained at relatively fixed and stable levels With relatively lower returns, much area was shifted out of sugar crops and into higher priced alternative crops The 2008/09 marketing year also saw widespread weather-related yield reductions An earlier study from USDA‘s Economic Research Service 168 Stephen Haley (ERS) noted that higher production costs and growing ethanol use in Brazil had set the stage for higher world sugar prices but concluded that policyinduced production swings among Asian countries (mainly India) were, and will likely continue to be, the main source of price volatility in world sugar markets (McConnell et al., 2010) Although the 2012/13 world sugar situation is seen to be stabilizing, the uncertainty from recently experienced production shortfalls has probably kept prices at historically high levels In its sugar projection out to 2021/22, the OECD and FAO jointly forecast sugar prices above historical levels, noting the strong probability of continued market volatility, mainly stemming from policies in India amplifying inherent cyclical production patterns In the United States, higher world sugar prices could weaken the case for policies that support domestic producers However, echoing the conclusion of McConnell et al (2010), volatility in the world sugar market leaves U.S sugar producers vulnerable to low prices if there are no domestic price-support programs in place Although much of the volatility may be self-correcting over time, the volatility of exchange rates, especially in reference to the Brazilian real and the U.S dollar, may make longer term sugar pricing developments more uncertain Appendix table Times series properties of Brazil Center/South costs of sugar production and world raw sugar price, 1989/90-2011/12 Phillips-Perron unit root test—stationarity Critical value Statistic Percent 10 Levels Cost of production1 World raw sugar price2 0.5046 0.1310 -2.6417 -3.0038 -2.6417 -3.0038 -3.7667 -3.7667 -2.8370 -3.3409 ** -2.6457 -3.0114 -2.6457 -3.0114 -3.7856 -3.7856 First differences Cost of production World raw sugar price Johansen‘s cointegration rank test, λ max test statistic H0: r = 0, H1: r = 24.3930 ** 19.96 24.60 H0: r = 1, H1: r = 1.4417 9.24 12.97 Note: * =.10 level (10 percent) ** =.05 level (5 percent) Center/South Brazil, LMC International 169 World Raw Sugar Prices April/March marketing year average of nearby No 11 Intercontinental Exchange (ICE) raw-sugar contract Both models for the PP test include a constant term, but not a trend Lag truncation set at The null hypothesis of the PP test is that the variable is not stationary, i.e., it contains a unit root The cointegrating vector in Johansen‘s test includes a constant but not a trend term The SIC was used to determine lag lengths The λ max statistic tests the null hypothesis that the number of co-integrating vectors is zero (r = 0) against the alternative of one co-integrating vector (r = 1) If this null hypothesis is rejected, the presence of one cointegrating vector (r = 1) is tested against the alternative of two (r = 2) The λ max test supports the presence of one cointegrating vector between the Center/South costs of production and the world price Appendix table Times series properties of sugar surplus/deficit measures, 1989/90-2011/12 Phillips-Perron test statistic for stationarity Statistic Critical value Percent 10 Levels Percent Ratio of April/March world raw sugar price and Brazil Center/South cost of production1 Sugar surplus/deficit per capita3 -2.6566*2 Ending year world stocks-to-use ratio3 -2.6457 -3.0038 -3.7667 -3.9690*** -2.6417 -3.0038 -3.7667 -2.0109 -2.6417 -3.0038 -3.7667 Interaction term: (2) x (3) -4.2265*** -2.6417 -3.0038 -3.7667 Difference between first projection of sugar surplus/deficit and final estimate4 -3.167** -3.0114 -3.7856 -2.6457 Source: USDA, Economic Research Service, Sugar and Sweetener Outlook Note: * =.10 level (10 percent) ** =.05 level (5 percent) *** =.01 level (1 percent) Intercontinental Exchange nearby No.11 contract; LMC International Augmented Dickey-Fuller statistic = -4.1940, significant below 0.01, critical value = -3.7856 USDA, Foreign Agricultural Service, Production, Supply and Disappearance database Defined over 1989/90-2011/12 Both models for the ADF test include a constant term, but not a trend SIC is used to determine lag lengths The null hypothesis of the ADF test is that the variable is not stationary Therefore, statistical significance rejects the null hypothesis, and implies that the variable of interest is stationary 170 Stephen Haley Appendix table Relationship between world sugar stocks-to-use ratio and world sugar surplus/deficit measure Model 1: dlog(stocks-to-use) = β0 + β1*per capita surplus/deficit + β2*D19951 where ―d‖ is difference (d(x) = x(t) - x(t-1) where t represents time period Coefficient Value Std Error T-statistic β0 0.0000 β1 0.1255 0.0167 7.1135 β2 0.0517 0.0172 3.0100 Adjusted R2 0.7411 Model 2: dlog(stocks-to-use) = β0 + β1*d(per capita surplus/deficit) + β2*d(per capita surplus/deficit(-1)) Coefficient Value Std Error T-statistic β0 0.0000 β1 0.0783 0.0155 5.0687 β2 0.0518 0.0156 3.3188 Adjusted R2 0.6234 Source: USDA, Economic Research Service, Sugar and Sweetener Outlook D1995 is a variable whose value for year is zero except for 1995 when it is equal to This variable picks up outlier effects not explained elsewhere in the model REFERENCES Engle, Robert F., and C.W.J Granger 1987 ―Co-Integration and Error Correction: Representation, Estimation, and Testing,‖ Econometrica 55, pp 251-76 McConnell, Michael, Erik Dohlman, and Stephen Haley 2010 ―World Sugar Price Volatility Intensified by Market and Policy Factors,‖ Amber Waves, September 2010 Available at: http:// webarchives.cdlib.org/sw1tx36512/ http://www.ers.usda.gov/AmberWaves/September10 Organisation for Economic Co-operation and Development/Food and Agricultural Organization 2012 OECD-FAO Agricultural Outlook 20122021, OECD Publishing and FAO Pindyck, Robert, and Daniel Rubinfeld 1998 Econometric Models and Economic Forecasts New York, NY: McGraw-Hill World Raw Sugar Prices 171 End Notes The world raw sugar price is the average of daily quotes of the nearby No 11 raw sugar futures contract on the Intercontinental Exchange (ICE) in New York The U.S raw sugar price is the average of quotes of the nearby ICE No 16 raw sugar futures contract It is noted that USDA‘s PSD database does not provide an aggregate sugar surplus/deficit balance or ending stocks level estimate as of a certain date, but rather the sum of the balances and ending stocks from whatever is the last date of the crop year for each country in the dataset Further research could use as an alternative a dataset that reports sugar balances and stocks as of a fixed date, such as that available from commercially based consultants like LMC International or F.O Licht It is implicitly assumed that Brazil has constant returns to scale technology in sugar production Its longrun sugar excess supply curve is flat (that is, perfectly elastic) This would mean that over the long term, changes in demand not determine the longrun world sugar price From 1989/90 through 2011/12, sugar production costs were below world prices this many times for the following sugar exporters: Australia: 11 times; Colombia: 10 times; Thailand: times; South Africa: times See appendix table for times series properties for the ratio of world price to Center/South production costs and also for other variables that figure into the succeeding analysis All variables except the world stocks-to-use ratio display stationary characteristics; i.e., they not contain a unit root The PSD variable is a proxy for world information It is not likely that PSD forecasts actually influence the world sugar market An asymmetric response to the forecast-error variable also was tested The forecast-error variable was redefined to have only positive values: zero values replace values that before were negative The interpretation to be tested was that prices in the future are influenced only by failures to predict less supply than actually realized The converse was tested as well In neither instance were equation results better than those reported in table for the seventh, eighth, and ninth specifications The logarithmic differences of both the world price and the Center/South production cost variables are stationary They not contain a unit root and the regression analysis that follows is valid In the short term to medium term, there is flexibility to switch between ethanol and sugar production, depending on market returns and costs for both products Nonetheless, over the longer time horizon, the simultaneous growth of both product sectors strongly illustrates the complementary relationship between them INDEX # 20th century, 21st century, A abuse, 16 access, 4, 33, 55, 60, 120, 131 accounting, 44, 88, 91 accreditation, 59 acid, 17 adjustment, 13, 15, 72, 73, 129 adults, 72 adverse conditions, 145 adverse weather, 77, 89, 94, 103 aggregation, 101 agricultural exports, vii, 1, 3, 43, 44, 45 agricultural market, 4, agricultural producers, 8, 43 agricultural sector, vii, 1, 2, 4, agricultural support policies, vii agriculture, vii, 1, 2, 7, 8, 9, 10, 11, 21, 30, 31, 41, 42, 48, 59, 67, 71, 72, 134 Algeria, 151 ammonia, 93 animal disease(s), 11, 48, 58 annual rate, 121, 123, 127, 131 antidumping, 47 aquaculture, 10, 58, 61 armed conflict, 117 Asia, 88 Asian countries, 168 assessment, 4, 8, 70, 167 assets, vii, 30, 48, 51, 75, 76, 94 authorities, vii, 1, 4, 5, 6, 8, 10, 22, 23, 24, 25, 26, 27, 33, 38, 39, 42, 43, 45, 47, 52, 60, 63, 65, 71 automobiles, 56 avian, 58 avian influenza, 58 B background information, 106 ban, 47, 116 Bangladesh, 150 banks, 64 barriers, 5, 43, 133 base, 13, 15, 34, 52, 65, 71, 73, 108, 122, 124 base year, 122 bedding, 99 beef, 47, 55 Beijing, 66, 70, 71 benefits, 21, 99, 110, 119, 130, 132, 133, 144 blueprint, 42 border protections, viii, 107, 122 174 Index Brazil, viii, 93, 147, 149, 150, 151, 152, 153, 154, 156, 160, 162, 165, 167, 168, 169, 171 break-even, 63 breeding, 7, 10, 48, 54, 55, 57, 72 buffalo, 53 buyers, 46 C campaigns, 21 cane sugar, 150 carbon, 88 carbon dioxide, 88 cash, 11, 16, 18, 43, 52, 53, 56, 93 cattle, 10, 54, 55, 72 Central Asia, 108, 111 central planning, 9, 10 challenges, viii, 107, 108, 109 chemical(s), 39, 46, 93, 94, 100, 101, 103 CIS, 105 city(s), 10, 14, 63, 68, 110, 146 civil war, 111 classes, 82, 87, 88, 93 classification, 32 cleaning, 99 climate, 82 Colombia, 151, 171 commercial, 3, 43, 56, 59, 111, 112, 116, 132 commodity, 3, 5, 7, 8, 10, 11, 12, 22, 23, 24, 27, 29, 31, 32, 38, 48, 49, 78, 94, 109, 113, 127, 141 commodity markets, 11, 48 communication, 146 Communist Party, 12 communities, 61 comparative advantage, 11 compensation, 59 competition, viii, 3, 9, 38, 80, 107, 108, 112, 116, 119, 132 competitiveness, 3, 4, 5, 11, 28, 76 competitors, 38 compilation, vii, 6, 7, 12, 22 compliance, complications, 99 composition, 53 computing, 108, 113 conflict, 115, 132 Congress, 11, 70 connectivity, 110 conservation, 21, 54 conserving, 80 consolidation, 43, 48, 57 construction, 51, 57, 59, 61, 62 consumers, viii, 38, 107, 109, 110, 114, 116, 118, 119, 120, 122, 124, 130, 132, 133, 142, 146 consumption, viii, 60, 107, 114, 120, 122, 123, 125, 126, 127, 131, 132, 133, 138, 139, 141, 142, 143, 144, 145, 149, 155, 158, 160, 162, 164, 167 containers, 94 conversations, 145 correlation, 118, 152, 154, 158 correlation coefficient, 118, 152 corruption, 16 costs of production, 149, 161, 162, 165, 169 cotton, 3, 6, 8, 10, 15, 16, 17, 18, 24, 25, 27, 29, 35, 36, 37, 38, 39, 40, 42, 43, 45, 46, 53, 54, 63, 72, 73 covering, viii, 55, 59, 62, 75, 78, 96 critical value, 169 crop production, 145 crop residue, 10, 62 crop rotations, 58 cropping practices, vii, 75, 76, 94 CRP, 80, 106 cultivation, 61, 65, 120, 132 currency, viii, 3, 7, 17, 28, 51, 71, 147, 149, 152, 167 current prices, ix, 148, 149 D data collection, 146 database, viii, 40, 41, 108, 113, 114, 126, 128, 129, 134, 135, 137, 139, 145, 148, 149, 151, 156, 157, 158, 159, 160, 162, 165, 166, 169, 171 175 Index DDGS, 46 deficiency, 42, 47, 49 deficit, 123, 149, 152, 155, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 169, 170, 171 deflator, 139 dehydration, 64 dependent variable, 153, 162 deposits, 65 depreciation, 94 derived demand, 142 destruction, 115, 141 developed countries, 4, 5, 8, 30, 32 developing countries, 4, 5, 32, 33, 93 deviation, 154, 158, 160 diesel fuel, 111 direct measure, 149 direct payment, 2, 3, 5, 9, 10, 12, 13, 31, 32, 35, 52, 53, 64, 71 disaster, 31, 33, 77 diseases, 54 distortions, 4, distribution, 57, 64, 65, 86, 95, 96, 97, 98, 106 divergence, 39, 40 diversity, 76 division of labor, 72 dollar costs, 152 domestic conflict, 113 domestic policy, vii, domestic production, viii, 107, 108, 113, 115, 117, 120, 122, 126, 128, 140, 142 domestic supplies, viii, 107 dough, 88 drought, 7, 39, 46, 58, 60, 77, 79, 89, 102, 103, 105, 112, 114 drying, 21, 43, 54, 57 editors, 71 Egypt, 151 elasticity of demand, 143 electricity, 60, 94, 100, 102, 103, 111, 112, 132 emergency, 58 employment, 22, 120, 132 encephalopathy, 47 endosperm, 88 energy, 91, 93, 120, 140 energy prices, 91 enforcement, 119 environment(s), 43, 167 environmental protection, 60 equilibrium, viii, 120, 147, 149, 152, 154, 162 equipment, 20, 21, 43, 48, 49, 53, 54, 57, 59, 60, 94 ERS, 5, 16, 18, 36, 37, 49, 51, 64, 81, 82, 106, 128, 129, 130 ethanol, 46, 150, 167, 168, 171 Europe, European Union (EU), 79, 150, 151 evidence, 150 evolution, vii, 5, 48 excess supply, 171 exchange rate, viii, 7, 9, 15, 19, 20, 22, 23, 29, 35, 36, 40, 41, 51, 147, 149, 152, 153, 167, 168 expenditures, 3, 7, 31, 32, 51, 52, 77, 99, 100, 101, 102, 103, 105, 125, 148 exporter(s), viii, 46, 110, 147, 149, 150, 152, 167, 171 exports, 3, 5, 9, 11, 43, 44, 45, 46, 47, 48, 91, 109, 111, 117, 145, 149, 150, 151 extraction, 111 F E earnings, 22 echoing, 168 economic growth, 91, 108, 132 Economic Research Service (ERS), 168 economic well-being, 78 families, 51, 62 family members, 72 farm commodities, vii, 1, 43 farm size, 57 farmland, 16, 41, 43 176 Index farms, viii, 3, 8, 14, 15, 16, 30, 41, 43, 48, 53, 54, 55, 57, 58, 59, 60, 61, 72, 75, 77, 78, 79, 95, 96, 97, 99, 100, 101, 106 FAS, 145, 146 fertility, 55, 59 fertilizers, 93 fever, 58 fiber, 39, 46 field crops, 79 financial, 3, 7, 8, 39, 49, 56, 57, 60, 62, 65, 78, 91 financial condition, 78 financial crisis, 91 financial resources, fish, 60 fishing, 54, 58 flexibility, 79, 171 floods, 58 flour millers, viii, 107 flour production, viii, 107, 108, 109, 111, 113, 114, 120, 122, 123, 124, 127, 130, 131, 132, 133, 136, 139, 142, 145 fluctuations, 6, 61 food, 6, 7, 8, 10, 11, 13, 15, 31, 42, 46, 48, 56, 57, 60, 61, 64, 71, 88, 108, 116, 119, 120, 127, 131, 132, 146 food safety, 10, 11, 57, 60, 61 food security, 6, 8, 13, 15, 31, 42, 48, 119, 127, 132 force, 105 forecasting, ix, 148, 149, 160, 161, 162, 167 formation, 11, 12, 23, 158 formula, 56, 57 forward market, 71 free trade, 131, 132, 146 freedom, 163 freezing, 64 fruits, full capacity, 112 funding, 71 funds, 10, 21, 52, 53, 56, 57, 58, 59, 61, 64, 65, 72 fungus, 64 G GDP deflator, 139 Government support, viii, 107 governments, 52, 54, 58, 59, 62 grades, 26, 27 grading, 64 grain payments, vii, 1, 20 grants, 10, 57, 58, 60 grass, 56, 62 grasslands, 62 grazing, 62, 89 greenhouses, 55, 60 Gross Domestic Product (GDP), 8, 118, 121, 123, 126, 139, 140 growth, vii, viii, 3, 8, 12, 28, 40, 81, 82, 83, 93, 107, 109, 112, 113, 114, 115, 116, 119, 120, 122, 123, 124, 127, 131, 132, 133, 136, 140, 150, 171 growth rate, 114, 120 Guangdong, 42, 67 Guatemala, 150, 152 guidance, 60 H harvesting, 21, 89, 94 herbicide, 80, 101 historical data, 115 history, ix, 5, 109, 148, 150 horticultural crops, 10 hotels, 61 House, 71 housing, 60 hypothesis, 149, 152, 158, 169 I ICE, 156, 169, 171 identity, 120 image, 5, 56 imbalances, viii, 147, 149, 158, 162 IMF, 121, 126, 134, 139 import policies, viii, 107, 118, 132 177 Index import prices, 120 imported products, 48, 64 improvements, 10, 11, 13, 60, 120, 140 incidence, 81, 101 income, vii, 1, 2, 8, 11, 12, 22, 26, 31, 40, 41, 58, 64, 72, 118, 120, 121, 122, 127, 143, 146 income distribution, 12 income inequality, income support, 41 increased competition, 80 India, 46, 79, 93, 150, 151, 168 individuals, 65 Indonesia, 109, 150 industry(s), 6, 8, 10, 12, 38, 39, 42, 43, 45, 48, 49, 111, 115, 116, 119, 124, 127, 131 inflation, 152 infrastructure, 4, 6, 7, 10, 11, 31, 33, 55, 60, 111, 112, 132, 145 ingredients, 48 insecurity, 145 integration, 118 international competitiveness, 5, International Monetary Fund, 134 intervention, 6, 9, 11, 12, 39, 44, 52 investment(s), 8, 11, 30, 43, 55, 56, 57, 60, 94, 116, 119 Iran, 109, 110, 151 Iraq, 108, 109 irrigation, 6, 7, 21, 43, 55, 57, 58, 60, 62, 76, 78, 83, 103, 112, 115, 120, 150 Islamabad, 145 issues, vii, 48, 78, 117, 118, 134 Italy, 134, 135 J Japan, 5, 151 K Kazakhstan, 109, 111, 145, 146 kill, 83 Korea, 151 L labor force, 41 landscape, lead, viii, 39, 93, 107, 119, 120, 122, 131, 133, 141, 154, 162 leadership, 12, 30 Least squares, 165, 166 lending, 10 livestock, 2, 9, 10, 20, 27, 38, 46, 47, 54, 58, 60, 61, 99 loans, 4, 7, 10, 25, 26, 49, 55, 57, 60, 72 local authorities, 10, 11, 13, 53 local government, 10, 15, 19, 49, 54, 56, 60, 64 logistics, lower prices, 127, 131, 162 M machinery, viii, 5, 9, 12, 20, 21, 48, 49, 53, 54, 55, 57, 60, 75, 83, 94, 99, 100, 105 magnitude, 38, 72, 143, 149, 158, 167 Mainland China, 50 majority, 15, 110, 111, 112 Malaysia, 151 management, 10, 22, 48, 57, 60, 61, 63, 73 manure, 57, 59, 62 market economy, market share, 150, 160, 162 marketing, 6, 7, 8, 9, 10, 26, 36, 38, 45, 60, 64, 71, 91, 93, 94, 95, 105, 138, 155, 160, 161, 162, 163, 165, 166, 167, 169 materials, 6, 51, 59 measurement, 32, 161 meat, 47, 63 media, 17, 25, 26, 39, 42, 67 membership, merchandise, 61 methodology, 29 microorganisms, 89 Middle East, 108 military, 115, 132 178 Index minimum price, 11, 23, 24, 26, 27, 63, 65, 146 Mississippi River, 88 Missouri, 87, 101 model specification, 136, 161 models, 55, 169 modernization, 20, 41, 43 modifications, 80 moisture, 83, 99, 100, 102, 105 Mongolia, 14, 21 Montana, 87, 88, 101 motivation, 71 mountain ranges, 112 N national product, 96 natural disaster(s), 12, 21, 54 natural gas, 93 Nigeria, 151 nitrogen, 78, 87, 89, 93, 100, 103, 105 North America, 5, 43 null, 169 null hypothesis, 169 O OECD, 4, 8, 29, 34, 69, 148, 168, 170 officials, vii, 1, 3, 4, 5, 9, 10, 13, 15, 16, 21, 22, 26, 27, 28, 30, 39, 42, 43, 45, 48, 50, 52, 64, 65, 71, 72, 73, 74 oil, 17, 38, 53 oilseed, 6, 9, 39, 40, 42, 56, 60 Oklahoma, 87, 89, 90, 101 operating costs, viii, 75, 77, 94, 95, 96, 99, 100, 102, 105 operations, 10, 16, 21, 59, 72, 94, 100, 102 opportunities, 20, 45, 46, 47, 94 opportunity costs, 18, 72, 94 organic matter, 89 ownership, 43, 76, 77, 91, 93, 94, 95, 96, 99, 100, 101, 102, 103, 105 P Pacific, 83, 87, 88, 89 Pakistan, viii, 46, 107, 109, 111, 116, 117, 118, 119, 120, 123, 124, 131, 132, 133, 134, 135, 138, 139, 144, 145, 146, 151 parallel, 40 parity, 45 participants, 25 pasta, 88 pasture, 62, 89 peace, 134 penalties, 79, 163 per capita expenditure, 124 petroleum, 52 plants, 39, 82 playing, 124 policy, viii, 4, 5, 10, 16, 22, 24, 26, 27, 31, 41, 45, 46, 48, 49, 70, 71, 72, 73, 109, 119, 122, 147, 148, 168 policymakers, 2, 41, 148 pollution, population, 60, 108, 116, 120, 121, 122, 124, 131, 132, 139, 144, 146, 154, 156 population growth, 122 porous borders, 119 potato, 17, 53 poultry, 10, 47, 61 precipitation, 112 prevention, 48, 60 price changes, 131, 166 price elasticity, 115 price floor, 12 price supports, vii, 1, 2, 3, 4, 5, 6, 7, 9, 10, 19, 22, 23, 25, 30, 31, 32, 34, 36, 38, 42, 43, 71, 72 private investment, 11 probability, 168 procurement, 8, 9, 10, 56, 63, 116 production costs, vii, 1, 2, 11, 12, 18, 20, 22, 23, 41, 42, 52, 63, 75, 76, 77, 78, 79, 82, 83, 89, 91, 94, 96, 99, 100, 105, 152, 154, 160, 162, 164, 165, 166, 167, 168, 171 productive capacity, 60 179 Index profit, 39, 47, 63, 71 profit margin, 39, 47 profitability, 27, 76, 80 project, 61, 62, 120, 148 propagation, 53, 72 property taxes, 94 protection, 6, 9, 43, 54, 62, 119, 124, 133 proteins, 88 public health, 21 public sector, 120 pumps, 58 Q quotas, 11, 34, 38, 43 R rainfall, 76, 77, 78, 83, 86, 89, 102, 112 random walk, 152, 154 raw materials, 38 raw sugar, vii, viii, 147, 148, 149, 150, 154, 156, 160, 163, 164, 165, 166, 167, 168, 169, 171 real terms, 123 recall, 13 recovery, 21, 31, 99, 100, 105, 132 reform(s), 4, 6, 9, 18, 19, 20, 23, 24, 26, 28, 29, 30, 35, 36, 40, 41, 66, 68, 69, 71, 72 refugees, 144 regression, 153, 154, 158, 160, 161, 163, 164, 165, 166, 171 regression analysis, 153, 158, 160, 166, 171 regression equation, 154, 160 regression model, 161, 164 regulations, 55 relative prices, 141 remote sensing, 15 rent, 58, 94 repair, 21, 94 requirements, 83, 87, 105, 112 reserves, 6, 7, 11, 22, 24, 25, 27, 31, 37, 38, 40, 45, 49, 63, 65 resource allocation, 10 resources, 8, 43, 49, 94 response, 40, 43, 48, 91, 118, 130, 131, 164, 171 restrictions, viii, 46, 107, 117, 122, 127 restructuring, 48 retail, 39, 117, 118, 146 returns to scale, 171 revenue, 74, 95, 118, 126 rights, 43, 65 risk, ix, 30, 37, 52, 56, 65, 78, 89, 102, 148, 149, 161, 163 root(s), 10, 17, 154, 165, 168, 169, 171 routes, 110, 119 rubber, 17, 53 rules, 2, 12, 31, 32 rural areas, 111, 132 rural development, 11 rural people, 20, 22 rural population, 20, 41 rural poverty, Russia, 151 S SAP, 76, 77, 91, 93, 95, 96, 105 Saudi Arabia, 151 scaling, scarce resources, 42 schistosomiasis, 53 science, 11, 33 scope, 2, 4, 11 security, 119 seed, 5, 6, 9, 12, 16, 17, 19, 20, 31, 35, 37, 53, 54, 59, 64, 72, 94, 99, 103, 115, 116, 122 seeding, 21, 53 seedlings, 58 self-sufficiency, 71, 141 semen, 55 Senate, sensitivity, viii, 143, 148, 149 services, 7, 10, 18, 21, 55, 57, 59, 60, 61 shape, 118 sheep, 6, 10, 55, 72 shelf life, 109 180 Index shortfall, 117 showing, 27, 64 SIC, 169 signs, 167 simulation(s), 127, 129, 131, 133, 146 smuggling, 119 society, 41 South Africa, 151, 171 South Asia, 108, 136 South Dakota, 87, 88, 101 Soviet Union, 111 soybeans, 3, 6, 8, 16, 24, 27, 28, 29, 35, 38, 39, 42, 44, 53, 63, 73, 76, 79, 80, 81, 82 specialty crop, specifications, 161, 163, 164, 171 speech, 31, 41, 72, 73 spending, 2, 7, 12, 62, 71 Spring, 82, 87, 101, 105 SSS, 147 stability, 28 stabilization, 55 standard deviation, 158, 160, 165 starch, 17, 53 state, 9, 10, 26, 27, 42, 54, 63 statistic test, 169 statistics, 26, 27, 35, 36, 37, 38, 47, 65, 74, 77 stock, 132, 164 storage, 7, 25, 26, 43, 49, 55, 57, 63, 64, 72, 99, 111, 116 stress, 56, 83 structure, 48, 50, 120, 138, 161 style, 49 subsidy(s), vii, 1, 2, 3, 5, 6, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 25, 26, 30, 31, 33, 35, 37, 38, 41, 42, 43, 44, 47, 49, 52, 53, 54, 55, 56, 57, 58, 59, 60, 62, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 119 subsistence, 8, 41 substitutes, 39 substitution, 46 sugar deficits, ix, 148, 150, 160, 167 sugar prices, viii, 147, 148, 152, 154, 158, 161, 162, 165, 167, 168 sugarcane, 156 supplier(s), 61, 109, 116, 118, 145 supply chain, 21 supply disruption, 117 surging, 46 surplus, 112, 149, 152, 155, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 169, 170, 171 surveillance, 119 synthesis, T Tajikistan, 109 target, 15, 32, 42, 67 tariff, 38, 43, 64, 118, 120, 122, 123, 124, 125, 126, 127, 129, 130, 131, 132, 133, 142, 146 Task Force, 42, 67 taxation, 5, 71 taxes, 6, 13, 64, 65 teams, 58 techniques, 48 technology, 11, 15, 33, 120, 171 temperature, 82 tenure, territory, 50 test statistic, 168, 169 testing, 42, 59, 154 textiles, 38 texture, 88 Thailand, 150, 171 threats, 48 Tibet, 17 time constraints, 145 total costs, 77, 95, 96, 105 total product, viii, 75, 88 trade, viii, 2, 4, 5, 7, 30, 32, 33, 67, 107, 109, 110, 116, 117, 118, 119, 122, 144, 145 trading partners, 2, training, 21, 55, 56, 60 trajectory, 40 transactions, 26 transfer payments, 42, 56 transformation, 166 181 Index translation, 49 transport, 35, 37, 111, 112, 117, 119, 132, 145 transportation, 7, 73, 93, 108 treatment, 10, 33 trial, 53, 54, 73 Turkmenistan, 109 U U.S Department of Agriculture, viii, 1, 75, 106, 107, 135, 147, 149 U.S sugar policy, viii, 147 unit cost, 48, 146 United, vii, 2, 39, 47, 75, 76, 79, 82, 83, 87, 88, 90, 94, 95, 99, 100, 102, 105, 115, 134, 135, 136, 145, 148, 150, 151, 168 United Nations, 115, 134, 135, 145, 148 United States, vii, 2, 39, 47, 75, 76, 79, 82, 83, 87, 88, 90, 94, 95, 99, 100, 102, 105, 115, 134, 135, 136, 145, 150, 168 urban, 8, 41, 50, 146 Uruguay, Uruguay Round, Uzbekistan, 108, 109, 111 V variable costs, 100 variables, 121, 122, 143, 146, 149, 152, 154, 155, 158, 161, 162, 163, 165, 166, 171 variations, vii, 82, 116, 136 varieties, 5, 9, 12, 17, 53, 56, 62, 76, 78, 80, 82, 100, 105, 122, 146 VAT, 64 vector, 169 vegetable oil, 27, 38, 39 vegetables, 9, 60, 64 versatility, 111 vessels, 58 volatility, 28, 168 W wages, 2, 18, 20, 21, 72 war, 116, 132, 145 Washington, 87, 88, 101, 134, 135, 136 water, 7, 48, 49, 53, 55, 58, 59, 62, 80, 88, 94, 111, 112, 115, 133 water shortages, 133 websites, 15, 64 wheat flour, vii, 88, 109, 110, 114, 115, 116, 118, 133 wheat producers, viii, 76, 79, 87, 91, 99, 101, 104, 105, 107, 132, 133 wheat production, vii, 75, 76, 78, 79, 80, 82, 94, 96, 98, 105, 106, 113, 118, 119, 120, 127, 131, 138, 142, 143, 145 wheat tariffs, viii, 107, 122, 127, 130, 133, 144 wholesale, 60, 61, 110 workers, 21 World Bank, 66, 118, 136 World Trade Organization (WTO), vii, 1, 2, 3, 4, 5, 8, 9, 11, 12, 30, 31, 32, 33, 34, 35, 36, 38, 42, 43, 47, 68, 69, 70, 71, 73 Y yang, 61 yarn, 39, 40, 46 yeast, 88 yield, 73, 76, 77, 78, 79, 80, 82, 83, 88, 89, 97, 99, 100, 101, 102, 103, 112, 113, 114, 115, 120, 122, 125, 126, 139, 167 yuan, 16, 17, 19, 20, 22, 35, 36, 51, 52, 53, 55, 59, 71, 72