To analyze the impact of different growth models, we calculated the metals and energy intensity of demand of different sectors of the economy using the GTAP (Global Trade Analysis Project). The metals intensity of global manufacturing was found to be about twenty times that of global services in 2011. Similarly, the metals intensity of global investment and exports was about seven times that of household consumption. Differences in energy intensities between sectors are smaller, but still pronounced; the energy intensity of manufacturing is two-and-a half times that of services, although that of investment is actually smaller than consumption. This suggests that countries with manufacturing-driven growth may experience a greater increase in energy and metals consumption for a given increase in output than economies driven more by services. Likewise, countries with investment-driven or exports-driven growth will see a greater increase in metals consumption than economies driven by household consumption. This may have accounted for the more rapid increase in China’s commodity consumption than its peers. Investment accounted for half of cumulative growth during 2010-16 in China, compared to one-quarter of cumulative growth in India, despite both countries growing at similar average rates (7.5-8 percent) during this period. In addition, manufacturing has been a more important driver of growth in China, growing twice as fast as in India on average over the past 10 years.

# **4. Prospects for commodities demand**

A hypothetical scenario is developed for the period 2018-27, and compared to the estimated values over 2010-16 as calculated by the model. This enables an assessment of the impact of changes in population and income growth, shifts between countries with different commodity intensities of demand, and within-country shifts as their incomes rise. The scenario is calculated separately for all countries in the estimation sample, and then summed to produce a global estimate. The sample includes advanced economies, the EM7, and other EMDEs. Data limitations exclude many smaller emerging markets and frontier markets, with sub-Saharan Africa (SSA) and the Middle East and North Africa (MENA) particularly under-represented in energy and metals.

## **4.1 Baseline scenario**

The baseline scenario for the period 2018-27 are aggregated from country-level data, using country-specific per capita income and GDP deflators, and global commodity prices from World Bank (2018a). For each country, all regression coefficients (short- as well as long-run coefficients) are applied to country-specific per capita income and deflated commodity prices. The resulting predicted per capita consumption levels (in physical units) are multiplied by total population from United Nations (2017). Total world consumption is the sum of these country-level fitted or predicted consumption levels: ˆ _c_ where _i_ , _j_ . _t_ is the fitted value of per capita consumption in country _i_ of commodity _j_ at time _t_ , and _popi_ , _t_ is the population of country _i_ at time _t._ The forward-looking scenarios assume that real per capita income grows at potential growth over the next decade, as estimated by the production function approach in World Bank (2018b), deflated 12