Q4 2015 www.bmiresearch.com VIETNAM AGRIBUSINESS REPORT INCLUDES 5-YEAR FORECASTS TO 2019 ISSN 1759-1740 Published by:BMI Research Vietnam Agribusiness Report Q4 2015 INCLUDES 5-YEAR FORECASTS TO 2019 Part of BMI’s Industry Report & Forecasts Series Published by: BMI Research Copy deadline: September 2015 BMI Research Senator House 85 Queen Victoria Street London EC4V 4AB United Kingdom Tel: +44 (0) 20 7248 0468 Fax: +44 (0) 20 7248 0467 Email: subs@bmiresearch.com Web: http://www.bmiresearch.com © 2015 Business Monitor International Ltd All rights reserved All information contained in this publication is copyrighted in the name of Business Monitor International Ltd, and as such no part of this publication may be reproduced, repackaged, redistributed, resold in whole or in any part, or used in any form or by any means graphic, electronic or mechanical, including photocopying, recording, taping, or by information storage or retrieval, or by any other means, without the express written consent of the publisher DISCLAIMER All information contained in this publication has been researched and compiled from sources believed to be accurate and reliable at the time of publishing However, in view of the natural scope for human and/or mechanical error, either at source or during production, Business Monitor International Ltd accepts no liability whatsoever for any loss or damage resulting from errors, inaccuracies or omissions affecting any part of the publication All information is provided without warranty, and Business Monitor International Ltd makes no representation of warranty of any kind as to the accuracy or completeness of any information hereto contained Vietnam Agribusiness Report Q4 2015 CONTENTS BMI Industry View SWOT 10 Agribusiness 10 Operational Risk 12 Industry Forecast 14 Grains Outlook 14 Table: Corn Production & Consumption (Vietnam 2014-2019) 15 Table: Corn Production & Consumption (Vietnam 2009-2014) 18 Rice Outlook 19 Table: Rice Production & Consumption (Vietnam 2014-2019) 20 Table: Rice Production & Consumption (Vietnam 2009-2014) 22 Dairy Outlook 24 Table: Butter Production & Consumption (Vietnam 2014-2019) 25 Table: Cheese Production & Consumption (Vietnam 2014-2019) 25 Table: Milk Production & Consumption (Vietnam 2014-2019) 25 Table: Whole Milk Powder Production & Consumption (Vietnam 2014-2019) 26 Table: Vietnam - Planned Investment In Milk Production Capacity 27 Table: Butter Production & Consumption (Vietnam 2009-2014) 32 Table: Cheese Production & Consumption (Vietnam 2009-2014) 32 Table: Milk Production & Consumption (Vietnam 2009-2014) 32 Table: Whole Milk Powder Production & Consumption (Vietnam 2009-2014) 32 Livestock Outlook 34 Table: Beef Production & Consumption (Vietnam 2014-2019) 35 Table: Pork Production & Consumption (Vietnam 2014-2019) 35 Table: Poultry Production & Consumption (Vietnam 2014-2019) 35 Table: Beef Production & Consumption (Vietnam 2009-2014) 41 Table: Pork Production & Consumption (Vietnam 2009-2014) 41 Table: Poultry Production & Consumption (Vietnam 2009-2014) 41 Coffee Outlook 43 Table: Coffee Production & Consumption (Vietnam 2014-2019) 44 Table: Coffee Production & Consumption (Vietnam 2009-2014) 48 Commodities Price Analysis 50 Commodity Strategy 50 Monthly Grains Update 55 Upstream Analysis 59 Asia Machinery Outlook 59 Table: Select Countries - Average Size Of Farms, Hectares 63 Asia GM Outlook 67 Table: Selected Countries - GM Crops Use 69 Asia Fertiliser Outlook 70 © Business Monitor International Ltd Page Vietnam Agribusiness Report Q4 2015 Downstream Analysis 75 Food 75 Food Consumption 75 Table: Food Consumption Indicators - Historical Data & Forecasts (Vietnam 2012-2019) 77 Canned Food 77 Confectionery 77 Table: Confectionery Value/Volume Sales, Production & Trade - Historical Data & Forecasts (Vietnam 2012-2019) 80 Pasta 81 Table: Pasta Volume Sales, Production & Trade - Historical Data & Forecasts (Vietnam 2014-2019) 82 Dairy 82 Table: Dairy Volume Sales, Production & Trade - Historical Data & Forecasts (Vietnam 2014-2019) 82 Drink 84 Alcoholic Drinks 84 Table: Alcoholic Drinks Value/Volume Sales, Production & Trade - Historical Data & Forecasts (Vietnam 2014-2019) 86 Hot Drinks 87 Table: Hot Drink Value/Volume Sales, Production & Trade - Historical Data & Forecasts (Vietnam 2014-2019) 89 Soft Drinks 90 Table: Soft Drinks Sales, Production & Trade (Vietnam 2014-2019) 91 Mass Grocery Retail 93 Table: Mass Grocery Retail Sales By Format - Historical Data & Forecasts (Vietnam 2014-2019) 97 Table: Grocery Retail Sales By Format (%) 97 Regional Overview 98 Table: Impact Of El Niño On Crops 102 Competitive Landscape 104 Table: Major Agribusiness Companies (USDmn) 104 Demographic Forecast 105 Table: Population Headline Indicators (Vietnam 1990-2025) 106 Table: Key Population Ratios (Vietnam 1990-2025) 106 Table: Urban/Rural Population & Life Expectancy (Vietnam 1990-2025) 107 Table: Population By Age Group (Vietnam 1990-2025) 107 Table: Population By Age Group % (Vietnam 1990-2025) 108 Methodology 110 Industry Forecast Methodology 110 Sector-Specific Methodology 111 © Business Monitor International Ltd Page Vietnam Agribusiness Report Q4 2015 BMI Industry View BMI View: Recent developments in the country's economic and business environments add further weight to our positive view on Vietnam's agribusiness sector The industry holds strong growth opportunities in terms of production, exports and retail sales, particularly with regard to the rice, coffee, livestock and dairy sectors Moreover, economic and financial integration in South East Asia will benefit Vietnam's exports of rice, dairy and coffee However, Vietnam is facing growing competition in its key markets The fulfilment of its promising potential will only be achieved if the country steps up its competitiveness and improves both product quality and supply chain efficiency Vietnam will have to significantly ramp up investments on crop productivity in order to not be left behind and, if it does, it will be able to produce more value-added crops and maintain its status as an export spearhead Agribusiness Market Value BMI Market Value By Commodity (2005-2019) 50 40 30 20 10 Grains market value, % of total Sugar market value, % of total 2019f 2018f 2017f 2016f 2015f 2014e 2013e 2012 2011 2010 2009 2008 2007 2006 2005 Livestock market value, % of total Other market value, % of total e/f = BMI estimate/forecast Source: FAO, BMI © Business Monitor International Ltd Page Vietnam Agribusiness Report Q4 2015 Key Forecasts ■ Rice consumption growth to 2019: 12.0% to 24.0mn tonnes Rice remains the major food staple in Vietnam, and we not see this changing over our forecast period However, rising interest in other foods such as wheat-based goods - supported by growing affluence - will restrict demand for rice, and over the forecast period we expect production growth to significantly outpace that of consumption ■ Corn production growth to 2018/19: 32.3% to 6.8mn tonnes Although acreage is likely to remain stagnant or diminish; current yield immaturity means significant gains are still available via this avenue, especially as robust local corn prices provide incentives to farmers Domestic consumption will be another important driver ■ Milk production growth to 2018/19: 62.2% to 796,000 tonnes Dramatic increases in cattle numbers and increased public and private sector investment - part of the effort to reduce the country's growing import dependency - will be the main boost to growth Commercialisation will also play a key role as larger, more efficient farms come to play a greater role in milk production ■ 2015 BMI universe agribusiness market value: USD37.5bn (down from USD38.0bn in 2014; growth expected to average 2.4% annually between 2015 and 2019) ■ 2016 real GDP growth: 6.6% (up from 6.4% expected in 2015; predicted to average 6.4% over 2015-2019) ■ 2016 consumer price index: 3.7% y-o-y (up from 2.1% expected in 2015; predicted to average 4.1% over 2015-2019) Key Developments Vietnam's coffee sector is undergoing some positive changes that will help the country maintain its status as the largest exporter of robusta coffee globally in the coming years The Ministry of Agriculture and Rural Development has unveiled a coffee plan for the 2014-2020 period, focusing mainly on a tree replanting programme and on the development of the processing sector However, we believe the implementation of the recently unveiled coffee plan will be slow and the government's goal to boost value-added coffee exports will be difficult to achieve In particular, the replanting programme may be partly jeopardised by the low competitiveness of coffee prices relative to other crops, including pepper After decades of active support to the rice sector, Vietnam is shifting its attention to corn and soybean production in order to address its soaring animal feed deficit and to avoid rice oversupply A year into the new policy incentivising farmers to switch to corn and soybean production, rice output growth has actually shown signs of slowing down, while corn production is picking up The eventual increase in domestic feed output is likely to favour the development of the livestock sector Vietnam is already seeing the impact of the policy, as domestic corn production is growing at a fast pace and imports decreased in 2014/15 and should remain on a downtrend in 2015/16 © Business Monitor International Ltd Page Vietnam Agribusiness Report Q4 2015 Vietnam is seeing a wave of private investment in its upstream (farming) and downstream (dairy product manufacturing and distribution) dairy sector These investments bode well for the future of Vietnam's milk production in the coming years Vinamilk, Vietnam's largest dairy company, is one of the most active in terms of investment Vietnamese companies operating in sectors other than diary are also turning their eyes to the milk industry, including Vinacafe Bien Hoa Company and property developer Hoang Anh Gia Lai Group However, the wave of private investment in Vietnam's dairy sector also has its downsides, the main one being the rise in competition Growth in domestic dairy prices has slowed down and margins in the sector have been on a downtrend since 2013 © Business Monitor International Ltd Page Vietnam Agribusiness Report Q4 2015 SWOT Agribusiness SWOT Analysis Strengths ■ The natural fertility of Vietnam around the Red River Delta in the north and the Mekong River Delta in the south provides the country with a strong agricultural base ■ Vietnam is the world's second largest exporter of rice and coffee It also enjoys relatively high rice yields compared with its regional counterparts ■ Agricultural productivity has improved considerably since the opening up of the economy in 1986 Weaknesses ■ Vietnam enjoys relatively good international price competitiveness for rice and coffee ■ Much of Vietnam's agriculture is based on small-scale farms with poor yields relative to more developed international competitors ■ Transportation and production infrastructure is often poor, making getting crops to market difficult and negatively affecting quality Opportunities ■ Since the opening up of the economy in 1986, which allowed more private involvement in agriculture, yields have improved dramatically and look set to continue doing so ■ Vietnam's fast-growing population of more than 80mn provides a large market for agro-food products ■ With BMI forecasting Vietnamese GDP per capita to grow rapidly over our forecast period, consumers will have more money to spend on food, spurring growth in agricultural production ■ A move towards higher-quality products, especially in the coffee and dairy sectors, will help to improve Vietnam's product competitiveness © Business Monitor International Ltd Page 10 Vietnam Agribusiness Report Q4 2015 Growing Deficits Select Countries - Corn Production Balance ('000 tonnes) 14,000 12,000 10,000 8,000 6,000 4,000 2,000 -2,000 -4,000 China India Indonesia Malaysia Philippines 2019f 2018f 2017f 2016f 2015f 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 -6,000 Thailand f= BMI forecast Sources: USDA, national sources, BMI China, Indonesia To Drive Asia's Widening Corn Deficit Asia will see its dependence on imported corn grow over the coming years, despite some countries' ambition to maintain or reach self-sufficiency in corn and restrict imports Consumption will grow at a robust pace, buoyed by the livestock sector, while production expansion remains constrained by structural deficiencies ■ The existing and traditional large importers in the region, including Japan, South Korea and Malaysia, will see their imports grow slowly ■ In South East Asia, we forecast production growth to accelerate over the coming years, as yields and production generally come from a lower base Therefore, some countries will be able to broadly maintain their fragile self-sufficiency in corn, including the Philippines and Thailand ■ Indonesia will be a notable exception in South East Asia, as its corn production deficit will grow The country is slowly becoming one of the largest importers of corn China will also see an increase in its imports ■ India will be the only country in the region to record a positive and increasing production surplus © Business Monitor International Ltd Page 100 Vietnam Agribusiness Report Q4 2015 Higher Margins In Upstream Operations Select Palm Oil Companies - Average Operating Margins By Segment (%) Note: The lines represent the average operating margins according to different company groupings Source: Company reports, BMI ASEAN Palm Oil: Strategy Adjustments Amidst Growing Challenges The operating environment for palm oil companies in Indonesia and Malaysia will remain challenging over 2015, as the fundamentals for the industry continue to be unfavourable In light of the downturn in the sector, palm oil companies have started to adjust their strategies We believe they will generally focus more on the acquisition of established plantations and efficiency improvement in terms of plantation management and yields, while some integrated players will invest further downstream towards the oleochemical segment We believe this focus on efficiency gains, coupled with low palm oil prices and low valuations, as well as the lack of available land, will lead to a consolidation trend within the industry over the coming years, most likely through a mergers and acquisitions spree, especially in the upstream sector © Business Monitor International Ltd Page 101 Vietnam Agribusiness Report Q4 2015 Table: Impact Of El Niño On Crops Commodity Country Share of global Risk To 2015/16f Risk To 2016/17f Production production Production (2013/14) Palm Oil Malaysia, Indonesia 85% Rice Thailand, India, Vietnam, Bangladesh, Indonesia, Philippines, etc Around 55-60% Downside - High Downside - Low Sugar Australia, India, Thailand 31% Downside - High Downside - Low Brazil 28% Downside - Low Downside - Low-to-medium Wheat - Australia 4% Downside - High Downside - Low Wheat - EU 22% (EU 28) Negligible Downside - Low India 13% Negligible Downside - Medium Oilseeds India 7% Downside - High Downside - Low Coffee Vietnam 19% Downside Medium Downside - Low Brazil 32% Upside - Low Upside - Medium Central America 8% Downside - Lowto-medium Downside - Medium-High Côte D'Ivoire, Ghana, Indonesia, Nigeria 76% Downside Medium Downside - Low Grains Cocoa Downside Medium Downside - High Source: BMI, FAO, MPOB, ICO, ICCO El Niño 2015: Key Implications For Commodities The re-emergence of El Niño for the first time in five years poses clear downside risks to production of key commodities in 2015/16, especially for large producing and exporting countries We believe palm oil, rice and sugar are the most vulnerable to an El Niño-linked rise in prices, particularly because prices have been on a decline over recent years Sentiment could quickly turn around should the weather actually prove unfavourable in the coming months In Australia, grain production is set to record another disappointing year in the 2015/16 season, based on the assumption that El Niño will have a negative impact on yields Cattle slaughter will also remain high in 2015, with beef production reaching a record high, as El Niño will lead to lower domestic supply of feed grain and grazing areas © Business Monitor International Ltd Page 102 Vietnam Agribusiness Report Q4 2015 Deepening Imbalances Select Countries - Sugar Production Balance (mn tonnes) Source: BMI Thailand, Australia To Benefit From Asia's Ballooning Sugar Deficit Sugar supply in the Asia Pacific region is in a structural and widening deficit Almost all Asian countries will see their consumption of sugar accelerate over the medium term, led by Indonesia, Thailand, China, Pakistan and Vietnam Meanwhile, production will struggle to keep up with demand, as sugar mills shift their investments towards power and ethanol production amidst profitability challenges in the sugar sector This diversification is likely to help the sector compensate for volatility in the sugar business, facilitating an increase in earnings in the coming years Thailand and Australia will be the main beneficiaries of these trends and will be able to ramp up exports to the rest of Asia © Business Monitor International Ltd Page 103 Vietnam Agribusiness Report Q4 2015 Competitive Landscape Table: Major Agribusiness Companies (USDmn) Sub-Sector Revenue (USDmn) Fiscal Year End Market Capitalisation (USDmn) Employees Dairy 1651.2 12/2014 4954.7 6244 Food manufacturing (confectionery & snacks) 233.8 12/2014 464.9 7318 Coffee & food manufacturing 140.4 12/2014 215.8 527 Seafood 703.5 12/2014 168.4 818 Sugar & real estate 109.5 06/2014 82.9 269 Edible oils & fats 194.7 12/2014 36.6 780 Sugar & alcohol 81.8 12/2014 35.3 720 Seafood 712.6 12/2014 na 14395 Southern Seed Crop seeds 28.7 12/2014 37.0 432 Viet Thang Feed JSC Animal feed 208.8 12/2014 57.5 630 Company Viet Nam Dairy Products JSC (Vinamilk) Kinh Do Corp Vinacafe Bien Hoa JSC Hung Vuong Societe De Bourbon Tay Ninh Tuong An Vegetable Oil JSC Lam Son Sugar Minh Phu Seafood Source: BMI, Bloomberg © Business Monitor International Ltd Page 104 Vietnam Agribusiness Report Q4 2015 Demographic Forecast Demographic analysis is a key pillar of BMI's macroeconomic and industry forecasting model Not only is the total population of a country a key variable in consumer demand, but an understanding of the demographic profile is essential to understanding issues ranging from future population trends to productivity growth and government spending requirements The accompanying charts detail the population pyramid for 2015, the change in the structure of the population between 2015 and 2050 and the total population between 1990 and 2050 The tables show indicators from all of these charts, in addition to key metrics such as population ratios, the urban/rural split and life expectancy Population (1990-2050) 150 100 50 2050f 2045f 2040f 2035f 2030f 2025f 2020f 2015f 2010 2005 2000 1990 Vietnam - Population, mn f = BMI forecast Source: World Bank, UN, BMI © Business Monitor International Ltd Page 105 Vietnam Agribusiness Report Q4 2015 Vietnam Population Pyramid 2015 (LHS) & 2015 Versus 2050 (RHS) Source: World Bank, UN, BMI Table: Population Headline Indicators (Vietnam 1990-2025) 1990 2000 2005 2010 2015f 2020f 2025f 68,909 80,887 84,947 89,047 93,386 97,057 99,811 na 1.1 0.9 1.0 0.9 0.7 0.5 Population, total, male, '000 33,892 39,827 41,830 43,970 46,158 47,980 49,302 Population, total, female, '000 35,017 41,060 43,117 45,077 47,228 49,076 50,508 Population ratio, male/female 0.97 0.97 0.97 0.98 0.98 0.98 0.98 Population, total, '000 Population, % y-o-y na = not available; f = BMI forecast Source: World Bank, UN, BMI Table: Key Population Ratios (Vietnam 1990-2025) Active population, total, '000 Active population, % of total population Dependent population, total, '000 Dependent ratio, % of total working age © Business Monitor International Ltd 1990 2000 2005 2010 2015f 2020f 2025f 39,197 50,153 56,330 62,305 66,093 68,401 70,001 56.9 62.0 66.3 70.0 70.8 70.5 70.1 29,712 30,733 28,617 26,741 27,292 28,655 29,810 75.8 61.3 50.8 42.9 41.3 41.9 42.6 Page 106 Vietnam Agribusiness Report Q4 2015 Key Population Ratios (Vietnam 1990-2025) - Continued Youth population, total, '000 1990 2000 2005 2010 2015f 2020f 2025f 25,778 25,543 23,038 20,918 20,950 20,690 19,395 65.8 50.9 40.9 33.6 31.7 30.2 27.7 3,934 5,190 5,578 5,823 6,342 7,964 10,414 10.0 10.3 9.9 9.3 9.6 11.6 14.9 Youth population, % of total working age Pensionable population, '000 Pensionable population, % of total working age f = BMI forecast Source: World Bank, UN, BMI Table: Urban/Rural Population & Life Expectancy (Vietnam 1990-2025) 1990 Urban population, '000 2020f 2025f 13,957.7 19,715.6 23,174.6 27,064.2 31,383.5 35,771.3 40,027.3 Urban population, % of total Rural population, '000 2000 20.3 24.4 2005 27.3 2010 30.4 2015f 33.6 36.9 40.1 54,952.2 61,172.3 61,773.2 61,983.2 62,003.1 61,285.7 59,783.9 Rural population, % of total 79.7 75.6 72.7 69.6 66.4 63.1 59.9 Life expectancy at birth, male, years 66.1 69.0 69.9 70.7 71.7 72.7 73.7 Life expectancy at birth, female, years 75.1 78.5 79.6 80.2 80.7 81.2 81.7 Life expectancy at birth, average, years 70.6 73.8 74.8 75.5 76.2 77.0 77.8 f = BMI forecast Source: World Bank, UN, BMI Table: Population By Age Group (Vietnam 1990-2025) 1990 2000 2005 2010 2015f 2020f 2025f Population, 0-4 yrs, total, '000 9,314 7,127 6,897 7,228 7,012 6,574 5,922 Population, 5-9 yrs, total, '000 8,606 9,253 7,023 6,790 7,180 6,968 6,535 Population, 10-14 yrs, total, '000 7,856 9,162 9,117 6,898 6,757 7,147 6,936 Population, 15-19 yrs, total, '000 7,359 8,492 9,050 9,011 6,865 6,725 7,116 Population, 20-24 yrs, total, '000 6,644 7,672 8,332 8,873 8,936 6,802 6,664 Population, 25-29 yrs, total, '000 6,005 7,065 7,470 8,111 8,772 8,837 6,717 Population, 30-34 yrs, total, '000 5,138 6,351 6,909 7,285 8,021 8,680 8,747 Population, 35-39 yrs, total, '000 3,888 5,803 6,241 6,763 7,207 7,939 8,596 Population, 40-44 yrs, total, '000 2,462 4,994 5,719 6,147 6,684 7,127 7,856 Population, 45-49 yrs, total, '000 2,016 3,753 4,935 5,647 6,054 6,588 7,031 © Business Monitor International Ltd Page 107 Vietnam Agribusiness Report Q4 2015 Population By Age Group (Vietnam 1990-2025) - Continued 1990 2000 2005 2010 2015f 2020f 2025f Population, 50-54 yrs, total, '000 1,968 2,345 3,699 4,855 5,521 5,926 6,457 Population, 55-59 yrs, total, '000 2,045 1,885 2,237 3,541 4,677 5,330 5,733 Population, 60-64 yrs, total, '000 1,668 1,790 1,734 2,068 3,352 4,443 5,079 Population, 65-69 yrs, total, '000 1,411 1,770 1,609 1,562 1,906 3,104 4,134 Population, 70-74 yrs, total, '000 1,027 1,322 1,530 1,399 1,379 1,695 2,776 Population, 75-79 yrs, total, '000 752 984 1,080 1,263 1,166 1,159 1,437 Population, 80-84 yrs, total, '000 429 596 731 814 964 900 903 Population, 85-89 yrs, total, '000 223 336 385 482 545 653 617 Population, 90-94 yrs, total, '000 71 132 177 209 267 306 372 Population, 95-99 yrs, total, '000 15 40 52 74 89 115 133 Population, 100+ yrs, total, '000 11 16 23 30 38 f = BMI forecast Source: World Bank, UN, BMI Table: Population By Age Group % (Vietnam 1990-2025) 1990 2000 2005 2010 2015f 2020f 2025f Population, 0-4 yrs, % total 13.52 8.81 8.12 8.12 7.51 6.77 5.93 Population, 5-9 yrs, % total 12.49 11.44 8.27 7.63 7.69 7.18 6.55 Population, 10-14 yrs, % total 11.40 11.33 10.73 7.75 7.24 7.36 6.95 Population, 15-19 yrs, % total 10.68 10.50 10.65 10.12 7.35 6.93 7.13 Population, 20-24 yrs, % total 9.64 9.49 9.81 9.97 9.57 7.01 6.68 Population, 25-29 yrs, % total 8.72 8.73 8.79 9.11 9.39 9.11 6.73 Population, 30-34 yrs, % total 7.46 7.85 8.13 8.18 8.59 8.94 8.76 Population, 35-39 yrs, % total 5.64 7.17 7.35 7.60 7.72 8.18 8.61 Population, 40-44 yrs, % total 3.57 6.17 6.73 6.90 7.16 7.34 7.87 Population, 45-49 yrs, % total 2.93 4.64 5.81 6.34 6.48 6.79 7.04 Population, 50-54 yrs, % total 2.86 2.90 4.36 5.45 5.91 6.11 6.47 Population, 55-59 yrs, % total 2.97 2.33 2.63 3.98 5.01 5.49 5.74 Population, 60-64 yrs, % total 2.42 2.21 2.04 2.32 3.59 4.58 5.09 Population, 65-69 yrs, % total 2.05 2.19 1.90 1.75 2.04 3.20 4.14 Population, 70-74 yrs, % total 1.49 1.63 1.80 1.57 1.48 1.75 2.78 Population, 75-79 yrs, % total 1.09 1.22 1.27 1.42 1.25 1.20 1.44 Population, 80-84 yrs, % total 0.62 0.74 0.86 0.92 1.03 0.93 0.91 © Business Monitor International Ltd Page 108 Vietnam Agribusiness Report Q4 2015 Population By Age Group % (Vietnam 1990-2025) - Continued 1990 2000 2005 2010 2015f 2020f 2025f Population, 85-89 yrs, % total 0.32 0.42 0.45 0.54 0.58 0.67 0.62 Population, 90-94 yrs, % total 0.10 0.16 0.21 0.24 0.29 0.32 0.37 Population, 95-99 yrs, % total 0.02 0.05 0.06 0.08 0.10 0.12 0.13 Population, 100+ yrs, % total 0.00 0.01 0.01 0.02 0.03 0.03 0.04 f = BMI forecast Source: World Bank, UN, BMI © Business Monitor International Ltd Page 109 Vietnam Agribusiness Report Q4 2015 Methodology Industry Forecast Methodology BMI's industry forecasts are generated using the best-practice techniques of time-series modelling and causal/econometric modelling The precise form of model we use varies from industry to industry, in each case being determined, as per standard practice, by the prevailing features of the industry data being examined Common to our analysis of every industry is the use of vector autoregressions Vector autoregressions allow us to forecast a variable using more than the variable's own history as explanatory information For example, when forecasting oil prices, we can include information about oil consumption, supply and capacity When forecasting for some of our industry sub-component variables, however, using a variable's own history is often the most desirable method of analysis Such single-variable analysis is called univariate modelling We use the most common and versatile form of univariate models: the autoregressive moving average model (ARMA) In some cases, ARMA techniques are inappropriate because there is insufficient historic data or data quality is poor In such cases, we use either traditional decomposition methods or smoothing methods as a basis for analysis and forecasting BMI mainly uses ordinary least squares estimators In order to avoid relying on subjective views and encourage the use of objective views, we use a 'general-to-specific' method BMI mainly uses a linear model, but simple non-linear models, such as the log-linear model, are used when necessary During periods of 'industry shock', for example, if poor weather conditions impede agricultural output, dummy variables are used to determine the level of impact Effective forecasting depends on appropriately selected regression models We select the best model according to various different criteria and tests, including but not exclusive to: ■ R2 tests explanatory power; adjusted R2 takes degree of freedom into account; ■ Testing the directional movement and magnitude of coefficients; ■ Hypothesis testing to ensure coefficients are significant (normally t-test and/or P-value); ■ All results are assessed to alleviate issues related to auto-correlation and multicollinearity; © Business Monitor International Ltd Page 110 Vietnam Agribusiness Report Q4 2015 Human intervention plays a necessary and desirable role in all or our industry forecasting Experience, expertise and knowledge of industry data and trends ensure analysts spot structural breaks, anomalous data, turning points and seasonal features where a purely mechanical forecasting process would not Sector-Specific Methodology Within the Agribusiness industry, issues that might result in human intervention could include but are not exclusive to: ■ Technological developments that might influence future output levels (for example greater use of biotechnology); ■ Dramatic changes in local production levels due to public or private sector investment; ■ The regulatory environment and specific areas of legislation, such as import and export tariffs and farm subsidies; ■ Changes in lifestyles and general societal trends; ■ The formation of bilateral and multilateral trading agreements, and political factors The following two examples show the demand (consumption) and the supply (production) of rice Note that the explanatory variables for both are quite similar, but the underlying economic theory is different Example Of Rice Consumption Model (Rice consumption)t = β0 + β1*(real private consumption per capita)t + β2*(inflation)t + β3*(real lending rate)t + β4*(population)t + β5*(government expenditure)t + β6*(food consumption)t-1 + εt Where: ■ β are parameters for this function ■ Real private consumption per capita has a positive relationship with rice consumption, if rice is a normal good in a particular country If rice is an inferior good in a country, the relationship is negative So the sign of β1 is determined by a specific product within a specific country ■ When inflation is high, people with rational expectations will consume today rather than wait for tomorrow's high price to come Higher rice demand in year t due to higher inflation in that year leads to an assumed positive sign of β2 ■ The relationship between real lending rate and rice consumption is expected to be negative When real lending rates increase, disposable incomes, especially for those with mortgage burdens, etc, will decrease So the sign of β3 is expected to be negative ■ Of course, other things being equal, growth in rice consumption can also be caused by growth in population Consequently, positive sign of β4 is expected © Business Monitor International Ltd Page 111 Vietnam Agribusiness Report Q4 2015 ■ ■ ■ Government expenditure typically causes total disposable incomes to rise So the sign of β5 is expected to be positive Human behaviour has a trend: a high level of food consumption in previous years means there is very likely to be a high level of food consumption the next year So the positive sign of β6 is expected ε is the error/residual term Example Of Rice Production Model (Rice production)t = β0 + β1*(real GDP per capita)t + β2*(inflation)t + β3*(real lending rate)t + β4*(rural population)t + β5*(government expenditure)t + β6*(food production)t-1 + εt Where: ■ The same as above: the relationship between real GDP per capita and rice production depends on whether rice is normal or inferior good in that country ■ If high inflation is caused by food prices increasing, farmers will be more profitable Then they will supply more agricultural product (eg, rice) to increase their marginal (extra) profit, although this is tempered by the rising cost of other inputs in line with inflation ■ There is a global move towards corporate farming, away from small holdings, in order to achieve greater agricultural productivity Corporate farming means more investment in the modes of production, ie, agricultural machinery Higher real lending rates discourage investment, which in turn reduce production ■ BMI assumes that only the rural population has a positive effect on agricultural product supply ■ With supportive government policy, other things being equal, rice production is expected to go up Government expenditure is likely to play some role in supporting agribusiness ■ Again, previous food production positively affects this year's prediction Agribusiness Market Value The construction of the Agribusiness market value is done in two steps BMI constructs an in-house model of the agribusiness market Where for each commodity, its forecasted production value is multiplied by its commodity price This is repeated for each commodity in the BMI agribusiness universe and then aggregated to give a BMI agribusiness total market value Commodity prices reflect either market prices or production prices, this depends on the commodity in question and whether sufficient data is available BMI uses their in-house agribusiness total market value model as a benchmark model to forecast FAO's gross production value In addition analysts can also subjectively intervene into the model if necessary to take into account qualitative data © Business Monitor International Ltd Page 112 Vietnam Agribusiness Report Q4 2015 To summarise the final BMI Agribusiness market value is historical data from the FAO gross production value which is then forecasted using an in-house BMI agribusiness market value model that is objectively and subjectively estimated The model itself is priced in US dollars Conversion to local currency and euros is done directly using BMI's country risk exchange rate forecasts BMI ensures that our internal model best matches the FAO gross production value definition and construction to ensure that our internal model serves as a useful benchmark FAO Definition of Gross Production Value (USD) Value of gross production has been compiled by multiplying gross production in physical terms by output prices at farm gate Thus, value of production measures production in monetary terms at the farm-gate level Since intermediate uses within the agricultural sector (seed and feed) have not been subtracted from production data, this value of production aggregate refers to the notion of 'gross production' © Business Monitor International Ltd Page 113 Reproduced with permission of the copyright owner Further reproduction prohibited without permission [...]... Vietnam Agribusiness Report Q4 2015 SWOT Analysis - Continued • Vietnam' s reliance on imported oil poses risks in the form of energy and fuel shortages • Corruption and inefficiency in the legal system • Anti-Chinese violence, as seen in May 2014, could be a harbinger of wider political and social unrest © Business Monitor International Ltd Page 13 Vietnam Agribusiness Report Q4 2015 Industry Forecast... change to support dynamics in Vietnam, where rice production has long been the focus Vietnam is already seeing the impact of the policy, as domestic corn production is growing at a fast pace, while imports decreased in 2014/15 and should remain on a downtrend in 2015/ 16 © Business Monitor International Ltd Page 15 Vietnam Agribusiness Report Q4 2015 Booming Feed Imports Vietnam - Corn, Soy Meal & Soybean... production growth in two of Vietnam' s main agriculturalproducing regions © Business Monitor International Ltd Page 11 Vietnam Agribusiness Report Q4 2015 Operational Risk SWOT Analysis Strengths ■ Vietnam has a high number of university graduates with skilled degrees and a high literacy rate for its income level • In addition to a number of regional and international flight options, Vietnam has an extensive... credit regulations throughout Vietnam during that time © Business Monitor International Ltd Page 18 Vietnam Agribusiness Report Q4 2015 Rice Outlook BMI Supply View: Vietnam is a key grower and world provider of rice Production is growing fast, boosted by higher yielding rice varieties and better culture management Output grew by a strong 13% between 2009/10 and 2013/14 Vietnam' s rice production will... prices in Q41 4 and will continue to do so in the coming quarters Secondary exporters including Mynamar and Cambodia are also seeing their exports grow © Business Monitor International Ltd Page 21 Vietnam Agribusiness Report Q4 2015 Vietnam Slowly Regaining Market Share Select Countries - Rice Exports (% of total volume exported globally) Source: USDA, BMI Table: Rice Production & Consumption (Vietnam. .. International Ltd Page 25 Vietnam Agribusiness Report Q4 2015 Table: Whole Milk Powder Production & Consumption (Vietnam 2014-2019) Whole milk powder consumption, '000 tonnes Whole milk power consumption, % y-o-y 2014 2015f 2016f 2017f 2018f 2019f 38.4 40.1 41.9 43.8 45.8 47.8 4.2 4.5 4.5 4.5 4.5 4.5 f = BMI forecast Source: FAPRI, BMI Private Investment To Support Production Growth Vietnam is seeing a wave... Ltd Page 28 Vietnam Agribusiness Report Q4 2015 Liquid Milk Still The Dominant Product Vietnam - Dairy Products Sales, In Volume (LHC) & Value (RHC) Source: VPBS, Bloomberg, BMI Consumers Eyeing Value-Added Dairy Products Consumers in Vietnam and in Asian countries in general mainly consume fresh milk, produced locally However, consumers are slowly turning to more value-added products In Vietnam for... its animal feed requirements by 2020 © Business Monitor International Ltd Page 16 Vietnam Agribusiness Report Q4 2015 Mainly Emerging Countries Vietnam - Corn & Soybean Imports By Origin, 2012/13 (% of total imported volume) Source: BMI, ITC, UNCTAD The growing attention and support to corn and soybean production in Vietnam will most likely prove positive for the livestock sector, as it could help... 19,400.0 19,700.0 20,800.0 21,380.0 -2.1 0.8 1.3 1.5 5.6 2.8 Source: USDA, BMI © Business Monitor International Ltd Page 22 Vietnam Agribusiness Report Q4 2015 Risks To Outlook In the short term, we see downside risks to our 2015/ 16 production forecast, due to the return of El Niño in 2015 Various meteorologist departments around the world have announced that El Niño could be particularly strong this year,... year, and weather has been dry over recent months As such, the weather phenomenon poses clear downside risks to production in Vietnam © Business Monitor International Ltd Page 23 Vietnam Agribusiness Report Q4 2015 Dairy Outlook BMI Supply View: We hold a positive outlook on Vietnam' s dairy sector and expect it to maintain its strong growth momentum on the back of a growing customer base, low milk consumption ... expected in 2015; predicted to average 6.4% over 201 5-2 019) ■ 2016 consumer price index: 3.7% y-o-y (up from 2.1% expected in 2015; predicted to average 4.1% over 201 5-2 019) Key Developments Vietnam' s... International Ltd Page 19 Vietnam Agribusiness Report Q4 2015 Table: Rice Production & Consumption (Vietnam 201 4-2 019) Rice production, '000 tonnes Rice production, % y-o-y Rice consumption, '000... 25 Vietnam Agribusiness Report Q4 2015 Table: Whole Milk Powder Production & Consumption (Vietnam 201 4-2 019) Whole milk powder consumption, '000 tonnes Whole milk power consumption, % y-o-y 2014