Table 2.
Overview of characteristics of studies included in the systematic review.
| Author & Year | Food Consumption Data Source | Disaggregation | Projection Model Method | Assumptions | Variables | Food Groups | Baseline Year | GDP Scenarios | Projection Years |
|---|---|---|---|---|---|---|---|---|---|
| Alexandratos and Bruinsma, 2012 (FAO) (Alexandratos and Bruinsma, 2012) | FBS & HHCE from World Bank (2005 | No | Per capita calorie intake derived from consumer expenditure projections from 62 developing countries. Demand for each food group derived from proportional share of total calories | Cereals Milk & dairy Sugar (raw) Vegetable oils Meat |
2005/07 | 4.4% | 2050 | ||
| Amarasinghe et al., 2007 (Amarasinghe et al., 2007) | 48th, 50th & 55th round NSSO consumer expenditure | Rural/urban | Future trends in calorie intake are based on average global consumption patterns of 85 countries over 3 years. K-means cluster analysis used to capture variation in coefficients arising from taste and cultural differences | Per capita income growth Urbanisation Income elasticities |
Rice Wheat Maize Other cereals Pulses Oil crops Roots & tubers Vegetables Fruits Sugar Disaggregated: Beef, pork & mutton Milk products Eggs Poultry Fish |
2000 | Not stated | 2025 2050 |
|
| Bhalla et al., 1999 (Bhalla et al., 1999) | 50th round NSSO consumer expenditure | No | Demand projections based on variables listed | No change in income expenditures since 1993 Livestock production levels remain as per 1993 |
Population growth Urbanisation Expenditure elasticities Per capita income Changes in taste |
Cereals Meat & eggs Milk & milk products |
1993 | 2% 3.7% 6% |
2020 |
| Carriquiry et al., 2010 (FAPRI) (Carriquiry et al., 2010) | USDA PSD (supplemented by FAO database) | No | FAPRI World agricultural outlook model using IHS Global Insight macroeconomic forecasts | Average weather patterns Existing farm policy unchanged Existing trade agreements unchanged Existing custom unions unchanged |
GDP growth GDP deflator growth Population growth |
Wheat Rice Corn Sorghum Vegetable oil Sugar Beef & veal Poultry Dairy |
2009/10 | Not stated | 2019/2020 |
| Chand, 2007 (Chand, 2007) | 61st round NSSO consumer expenditure | Rural/urban | Demand projections based on variables listed | Indian Economy growth rate 7.57% to 2012, 7.81% thereafter Urban income growth rate 3 times that of rural population |
Income elasticity Per capita income growth Change in preferences Population growth Urbanization |
Rice Wheat Coarse cereals Pulses Total cereals Foodgrains |
2004/05 | 9% | 2020/21 |
| Dastagiri, 2004 (Dastagiri, 2004) | 50th round NSSO consumer expenditure | Rural/urban | Generalized Least Squares procedure | Inequality in rural/urban expenditure remains as 1993/94 | Expenditure elasticities Population growth Per capita income growth Price elasticities Urbanisation |
Milk Mutton & goat meat Beef & buffalo meat Chicken Egg |
1993 | 4% 5% 7% |
2020 |
| Dyson and Hanchate, 2000 (Dyson and Hanchate, 2000) | 50th round NSSO consumer expenditure | Rural/urban Regions &states |
Modified trend analysis | 7 day dietary recall period improves quantities of consumption in comparison to 30 day period | Average growth rates of per capita consumption over various NSSO rounds from 1972-1994 | Cereals Pulses Vegetables Fruit Milk & milk products Meat |
1993/94 | Not stated | 2020 |
| Ganesh-Kumar et al., 2012 (Ganesh-Kumar et al., 2012) | 61st round NSSO consumer expenditure | No | QUAIDS model | The relationship between growth in consumption and increasing income stays constant between baseline and projection year | Expenditure elasticities Per capita income growth Population growth |
Rice Wheat Pulses Edible Oil Milk Vegetables Sugar Eggs Fish, chicken & meat |
2004/05 | 4% 5% 6% |
2020/21 2025/26 |
| Kumar et al., 2009 (Kumar et al., 2009) | 61st round NSSO consumer expenditure | Rural/urban | Food characteristic demand system | Per capita expenditure used as a proxy for income Urban income growth rate 3 times that of rural population |
Per capita income growth Population growth Urbanisation Region Income group |
Rice Wheat Coarse cereals Pulses Total cereals Foodgrains |
2004/05 | 7.91% | 2021/22 |
| OECD-FAO 2017 (OECD-FAO, 2017) | OECD and FAO databases | No | Economic partial equilibrium model based on Aglink and Cosimo models | Constant real exchange rate Competitive world markets for agricultural commodities |
Population growth Consumer prices Producer prices |
Wheat Maize Coarse grains Rice Soybean Oilseed Vegetable oil Sugar Meat Dairy Fish & seafood |
2014–16 | 8.1% | 2026 |
| Rosegrant et al., 1999 (Rosegrant et al., 1999) | FAO food balance sheets | No | Updated partial-equilibrium global IMPACT model | The demand elasticity structure assumes that the expected rise in per capita income, commercialisation and urbanisation will cause a shift from main staples to high-value products, for example live-stock products. | Income elasticities Per capita income growth Population growth Effective consumer price Feed ratio Feed efficiency Effective feed price Commodity index specific for livestock |
Wheat Maize Rice All cereals Other grains Meat |
1993 | Not stated | 2020 |
GDP, gross domestic product; FBS, food balance sheet; HHCE, household consumption expenditure; NSSO, National Sample Survey Office; USDA PSD, United States Department of Agriculture production, supply and distribution; FAO, Food and Agriculture Organisation of the United Nations; FAPRI, Food and Agricultural Policy Research Institute; QUAIDS, quadratic almost ideal demand system; OECD, Organisation for Economic Co-operation and Development; IMPACT, international model for policy analysis of agricultural commodities and trade.