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Forecasting Global Rice Consumption
Roderick M. Rejesus*, Samarendu Mohanty, and Joseph V. Balagtas
Roderick M. Rejesus Department of Agricultural and Resource Economics
North Carolina State University NCSU Box 8109
Raleigh, NC 27695-8109
Phone No.: 919-513-4605 Fax No.: 919-515-1824
March 20, 2012
* Roderick M. Rejesus is Associate Professor, Department of Agricultural and Resource Economics, North Carolina State University, Raleigh, NC 27695-8109 Samarendu Mohanty is Head, Social Sciences Division and Program Leader- Targeting and Policy, International Rice Research Institute, Los Baos, Laguna, Philippines Joseph V. Balagtas is Associate Professor, Department of Agricultural Economics, Purdue University, West Lafayette, IN 47907-2056
Forecasting Global Rice Consumption
This paper examines the time-series properties of global rice consumption data commonly used in studies of consumption trends and evaluates alternative time-series models for long-range forecasts. Using time-series data from 1961-2011, we find that per capita rice consumption and GDP per capita are non-stationary in levels (i.e., they are unit root processes) and are not cointegrated. Thus previous studies that have applied econometric models for stationary data suffer from the well-known spurious regression problem. Out-of-sample performance evaluation of appropriate, univariate time-series forecasting methods suggest that double exponential smoothing may be the preferred approach to forecast global rice consumption. Our forecast results suggest that global rice consumption is projected to increase from 450 million tons in 2011 to about 490 million tons in 2020, and to about 650 million tons by 2050. Moreover, forecast intervals for these point estimates tend be very wide (especially in 2050), reflecting the inherent uncertainty in making long-run forecasts using any approach. These wide forecast intervals suggest a great deal of caution is appropriate when interpreting such forecasts for formulating public policy. Keywords: Consumption, Demand, Food Security, Forecasting, Rice, Time-series Analysis, Unit
Roots JEL Classification: Q10, Q11, Q18
Forecasting Global Rice Consumption
Rice is the major staple crop of nearly half of the worlds population, and is particularly important in
Asia, where approximately 90% of worlds rice is produced and consumed (Zeigler and Barclay, 2008;
Khush, 2004). Global rice production has tripled in the last five decades from 150 million tons in 1960 to
450 million tons in 2011, thanks in large part to the rice Green Revolution in Asia. Since the introduction
of high yielding semi-dwarf varieties in 1960s by the International Rice Research Institute (IRRI) more
than 1000 modern rice varieties have been released to farmers in many Asian countries, resulting in a
rapid increase in rice yields and global rice production. Global production dropped sharply at the
beginning of the 21st Century, from 410 million tons in 2000 to 378 million tons in 2003 because of
severe droughts in parts of Asia, but has recovered by growing 50 million tons between 2005 and 2011.
Rice is a staple food commodity with inelastic demand (Mohanty, Wailes and Chavez, 2010), and
with historically inadequate storage infrastructure in most developing countries in Asia (Rolle, 2011).
Thus trends in global rice consumption largely follow those in global production, rising steadily over the
last five decades (Figure 1). However population growth has outpaced growth in rice production, such
that per capita production, and thus per capita consumption, appears to have plateaued starting around
1990 at around 65 kg per year (Figure 2). Because demand is highly inelastic, reductions in aggregate
production result in large price increases and consumer welfare losses (See Figure 3 and Wright, 2011 p.
35). Also, because rice is a staple food that accounts for a large share of income for a large segment of the
worlds poor, price increases like the one experienced in 2007-2008 may have large income effects,
reducing income available for other needs (see Wood, Nelson, and Noguiera, 2012 for an application of
this principle to staple foods in Mexico). Thus, production and consumption trends in rice markets have
important implications for poverty, food security, and economic development, especially in Asia.
It is for this reason that previous work has sought to forecast global rice consumption. This
important literature seeks to provide information useful for resource allocation by producers, governments
and aid agencies, and is at the core of food security issues (Timmer, Block, and Dawe 2008, p.140). In
this paper we evaluate that literature and propose alternative forecast methods with qualitatively different
findings. We begin by summarizing key contributions of the extant research and identifying potential
conceptual and empirical limitations. We briefly discuss limitations of available data for assessing trends
in global rice demand. Then, taking the data as given, we turn to the development of appropriate
econometric models for forecasting rice consumption.
Previous Analyses of Global Rice Consumption: Findings and Limitations
A number of previous studies analyze and forecast global rice consumption using the global rice
consumption data plotted in Figure 1. A common prediction across these studies is that global rice
consumption will fall in the medium or long term. This prediction is based on the recent downturn in per
capita rice consumption shown in Figure 2, and the observed decreases in per capita rice consumption in
wealthy East Asian countries like Japan, Taiwan, and South Korea. For example, Timmer, Block, and
Dawe (2010) estimate a per capita rice consumption equation (in natural logarithm form) that is quadratic
in GDP, then use this estimated relationship and projections of global GDP to forecast global rice
consumption. Timmer, Block, and Dawe (2010) find that global rice consumption will increase modestly
until 2025 before declining rapidly to approximately 360 million tons by 2050.
Abdullah, Ito, and Adhana (2005) similarly use the USDA data on per capita consumption
(Figure 2) to project a range of scenarios for per capital rice consumption through 2050, all of which
forecast reductions in per capita consumption. Two of Abdullah, Ito, and Adhanas (2005) three scenarios
forecast per capita consumption in Asia to drop sufficiently to cause aggregate Asian rice consumption to
decrease by 2050, despite continued population growth. The forecast model behind these projections is
not entirely clear, but the authors state that they assume a continuation of observed trends in per capita
consumption, and that per capita consumption in developing nations will decline based on the experience
in relatively wealthy, East Asian countries.
Rosegrant et al. (2001) project declining per capita consumption but rising aggregate
consumption of rice through 2020. While they do not provide model details behind these projections, like
Timmer, Block, and Dawe (2010) and Abdullah, Ito, and Adhana (2005), they argue that income growth
and rising urbanization will result in declining per capita consumption.
In contrast, Seck et al. (2012) project that global rice consumption will rise to 496 million tons in
2020 and further increase to 555 million tons by 2035. Seck et al. (2012) explain that aggregate global
rice consumption is still expected to increase through 2035 due to increased demand in Africa, Latin
America and parts of Asia, despite continued declines in per capita consumption in China and India (and
other wealthy Asian countries).
The role of income growth assumed by all of these studies and, more broadly, their projections of
per capita and aggregate rice consumption require additional inspection for several reasons. First, it is
well established that income elasticities for staple foods tend to decrease as incomes rises. However,
evidence on the income elasticity of demand for rice is mixed, with some studies finding negative income
elasticies for key countries (e.g., Ito, Peterson, and Grant 1989, 1991) and others arguing that such
estimates are understated or finding larger and positive income elasticies (Huang, David, and Duff , 1991;
Taniguchi and Chern, 2000; Chern et al., 2002). Moreover, many studies in this literature suffer from
serious limitations, including a misattribution of unobserved structural changes to income effects (Huang
and Bouis, 1996).
Second, the extant research on aggregate rice consumption typically lacks appreciation for
changes in supply. Data on global or national rice consumption is typically calculated as availability, that
is, production minus net changes in stocks and trade. Because consumption data tracks production very
closely, studies of rice demand using aggregate rice consumption data are not likely to yield unbiased
estimates of structural demand parameters in the absence of a careful econometric identification strategy
(Yu et al., 2004).
Third, global rice consumption figures also mask important differences in rice consumption
across regions, across countrie