ADB Economics
Working Paper Series
International Trade and Risk Sharing in the Global Rice
Market: The Impact of Foreign and Domestic Supply Shocks
Shikha Jha, Kensuke Kubo, and Bharat Ramaswami
No. 372 | September 2013
ADB Economics Working Paper Series
International Trade and Risk Sharing in the Global Rice
Market: The Impact of Foreign and Domestic Supply Shocks
Shikha Jha, Kensuke Kubo,
and Bharat Ramaswami
No. 372
September 2013
Shikha Jha, Asian Development Bank;
Kensuke Kubo, Institute of Developing Economies,
Chiba and Indian Statistical Institute, Delhi;
Bharat Ramaswami, Indian Statistical Institute,
Delhi.
Asian Development Bank
6 ADB Avenue, Mandaluyong City
1550 Metro Manila, Philippines
www.adb.org
© 2013 by Asian Development Bank
September 2013
ISSN 1655-5252
Publication Stock No. WPS135991
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CONTENTS
ABSTRACT
v
I. INTRODUCTION
1
II. THE RICE MARKET AND ENDOGENOUS SHOCKS
2
III. THE RELIABILITY OF RICE TRADE AND MARKETS
3
IV. GLOBAL RICE TRADE
3
V. THE IMPACT OF EXOGENOUS SHOCKS ON IMPORTS AND CONSUMPTION
5
VI. POLICY RESPONSE
12
VII. CONCLUDING REMARKS
15
REFERENCES
17
ABSTRACT
In recent years, rising food prices have returned as a concern for policy makers
especially in developing countries. In this context, this paper examines how
supply shocks, both domestic and foreign, have mattered to imports and
consumption in the global rice market over 1960–2010. Such an investigation is
important in assessing the role of trade in compensating for domestic shocks. If
shortages lead countries to impose trade restrictions, then trade may not be
allowed to play an important role in stabilizing consumption. The existing
literature has highlighted the importance of these policy shocks in the world rice
market and how they have worked to increase the volatility of prices and trade
flows. Although trade cannot be expected to play a strong role when the major
producing and consuming countries are simultaneously hit by negative yield
shocks, such a scenario obtains in only 3% of cases. However, we also find that
consumption fails to be stabilized even when domestic shocks are negative and
foreign shocks are positive; but imports do peak. Thus, while trade does help in
coping with domestic risks, it is unable to achieve full risk sharing. Therefore, no
matter what are the foreign shocks, the principal concern is to stabilize
consumption when hit by negative domestic yield shocks. The frequency of such
shocks is about 12%. This brings into play domestic responses, and we find that
domestic stocks have been important in stabilizing consumption. The reliance on
domestic policies has in turn kept the rice market thin.
Keywords: food prices, risk sharing, rice market, international trade, supply
shocks
JEL Classification: F14, Q17
I. INTRODUCTION
In recent years, an old concern has resurfaced—that of rising food prices. After the food crisis in
the mid-1970s, the world enjoyed declining to stable real prices until the mid-1990s. In 1995–
1996, there was a spike in prices followed by a return to the long-term trend. From the early part
of the 2000s, however, prices have crept upwards, culminating in sharp rises during 2006–2007
to 2008–2009.
Palm oil, rice, and wheat prices doubled in 2007–2008 relative to 1999–2000. Wheat
and maize prices increased by more than 75% (Gilbert 2011).1 What was striking was that
the price spikes happened in a very short time interval. In nominal terms, world maize prices
increased by 54% from August 2006 to February 2007 followed by an increase in world wheat
prices of 125% from May 2007 to March 2008. The most dramatic increase occurred in rice
prices. From April 2001 to September 2007, the gradual upward drift saw the price of Thai 100%
B rice doubled from $170 per ton to $335 per ton, amounting to a 67% increase relative to the
United States Consumer Price Index. But between October 2007 and April 2008, the price
tripled to over $1,000 per ton (Dawe and Slayton 2011).
The food price spikes of 2007–2008 have renewed old debates about the efficacy and
desirability of price stabilization measures. Economists have long argued that storage-based
price stabilization is expensive and, in some instances, ineffective. On the other hand, opening
up the economy to trade can be effective in insulating against severe domestic shocks. The
food price crisis of 2007–2008, however, planted doubts in policy makers about the reliability of
world markets in times of need. Several policy studies have concluded that some public grain
reserves are necessary. Price stabilization pursued through public stocks cannot be effective,
however, when borders are open. So some restriction of trade would also be necessary.
In the context of this debate, the goal of this paper is to examine how supply shocks,
both domestic and foreign, have mattered to imports and consumption over the period 1960–
2010 in the global rice market. In autarkic economies, domestic supply shocks drive
consumption shocks as well. In countries open to trade, and when trade functions well,
domestic consumption depends on both domestic and foreign supply shocks. In particular,
compared to autarky, domestic shocks would matter less because of access to world markets.
For small open economies, domestic shocks should not matter at all.
These ideal outcomes may not be obtained, however, if policies impede trade. Rising
prices often provoke governments to put in place policies that buffer the impact. When they
take the form of trade restrictions, world trade may shrink; thus, countries might not have
access to world supplies to compensate for adverse domestic shocks. Rice is commonly
considered the archetype of an agricultural staple that is subject to such endogenous policy
shocks. Hence, we chose to study the impact of domestic and foreign supply shocks on rice
imports and consumption.
The outline of this paper is as follows. The next two sections offer a selective survey of
the literature on the global rice market with respect to endogenous policy shocks and the
reliability of rice trade. Section IV is a descriptive account of the global rice trade and the
trade interventions of major exporters. Section V offers a statistical analysis of the impact of
exogenous domestic and foreign supply shocks on imports and consumption. Section VI
1
Gilbert reports these price changes after deflating the nominal prices by the US Producer Price Index.
2 І ADB Economics Working Paper Series No. 372
extends this to include the policy variable of domestic and foreign stocks. Concluding remarks
are gathered in Section VII.
II. THE RICE MARKET AND ENDOGENOUS SHOCKS
The role of policy responses in provoking and exaggerating price spikes has been particularly
highlighted by the global rice market. A review of the literature tells us that it is the rice market
that is particularly subject to endogenous policy shocks. Unlike wheat and maize, a relatively
small proportion of world rice production (7%) enters international trade. Moreover, wheat
and maize trade is driven by surpluses from rich and large land-abundant countries such as
Argentina, Australia, Canada, and the United States (US). In the case of wheat, Australia,
Canada, and the US export more than 50% of their production. The biggest rice exporter,
Thailand, exports close to 40% of its output. However, its share in world rice output is less
than 5%.
On the other hand, the large rice-producing countries such as Bangladesh, the People’s
Republic of China (PRC), India, and Indonesia are either deficient, or at best, have small
surpluses relative to consumption. All of these countries have poor populations that are severely
affected when rice prices rise. Due to such food security concerns, these countries will likely
reduce their net supply to the world markets in times of crisis. This can take the form of export
restrictions for exporters, or reductions in import tariffs. In either case, the attempts of these
countries to increase their share of world consumption raise world prices. Thus, policies directed
toward insulating domestic markets magnify international price volatility when all countries
attempt to insulate their respective domestic markets at the same time (Abbot 2011; Martin and
Anderson 2011).
During the crisis of 2007–2008, many scholars argued that it was likely that the spike in
rice prices was due not to crop failure or low stocks but to policy measures put in place by
panicked governments. Writing as early as October 2008, Timmer (2008) argued that the
underlying causes for the rise in rice prices are different from those in wheat and maize prices.
Low stocks, crop failure, or financial speculation were not plausible factors behind the price
increases in rice in 2007–2008. Nor could these increases be attributed in a straightforward
manner to the rise in wheat or maize prices because substitution in consumption among these
grains is limited. Rather, the spike must be seen as due to export restrictions by some of the
major exporting countries, which induced panic buying by importers such as the Philippines; and
storage-driven because of the hoarding instincts of governments and other agents. This has
been echoed by others (Dawe and Slayton 2011; Gilbert and Morgan 2010; Wright 2011).
Martin and Anderson (2011) estimate that more than 45% of the explained change in
international rice price during 2005–2008 was due to export restrictions (compared to 29% for
wheat). If anything, this estimate is surprising in that endogenous shocks account for only about
half of the rice price increase when most of the literature seems to argue that it is significantly
driven by policy shocks. The hypothesis that export policies contribute to global price volatility
has also been tested by Giordani, Rocha, and Ruta (2012). Using a data set on trade measures
relating to the food sector, they find that the probability that a country imposes a new export
restriction is positively associated with the global restrictions on the product (i.e. the share of
international trade covered by export restrictions). Furthermore, for 2008–2010, they estimate
that a 1% surge in the share of trade covered by export restrictions is associated with a 1.1%
increase in international food prices.
International Trade and Risk Sharing in the Global Rice Market | 3
III. THE RELIABILITY OF RICE TRADE AND MARKETS
As mentioned earlier, in an integrated global market, trade provides a means for price
stabilization without costly investment in commodity stocks. This has been the view of many
economists. However, this does not take into account the possibility of government interventions
such as market-insulating policies. If exporters restrict their supply fearing a shortfall, importers
are deprived of food just when they need it the most. Such an experience may well persuade
importers that food trade is unreliable and that they should invest in domestic stocks.
Gilbert (2011) argues that it is the rice market and rice trade that are unreliable among
those of the major grains. In an earlier work (Gilbert 2010), he showed that a commonly quoted
world rice price—the spot price in Bangkok—follows various national prices rather than the
other way around (as it is for maize). As it is the rice market that “functions least well,” Gilbert
(2011) argues for a pragmatic approach where it is recognized that low-income countries “can
probably rely on being able to import additional maize or wheat if this proves necessary, but
may justifiably be worried about being able to do so for rice.” He argues, “[T]his points towards
the need for contingency arrangements for rice—either food security stocks, or formal trade
agreements with rice exporters or, where this is feasible, a move towards rice self-sufficiency.”
A related point is that the rice market has been seen to be somewhat disconnected
from the markets for other cereals. Shocks to rice supply and demand are not highly correlated
with those to other grains. Global futures markets are irrelevant to rice and the crop does not
have a use as a biofuel (Dawe and Slayton 2011). It is in this sense that Gilbert and Morgan
(2010) regard the rice price spike in 2007–2008 as “peculiar and in some sense pre-modern.”
Unlike that of other grains, the price volatility in this market does not always depend on the
fundamentals of demand and supply shocks and price elasticities. The particular problem of
the rice market is the tendency of important trading countries to shield themselves from external
shocks. Hence, “rice is different” and the future course of volatility will depend on how the
international community addresses the particular problems of this market (Gilbert and
Morgan 2011).
IV. GLOBAL RICE TRADE
Imagine a two-country trade model where one of the countries is producing rice. Imagine also
that there is no government intervention in either exports or imports. The production of rice is
subject to stochastic yield shocks. It is expected then that the higher the yield, the greater the
volume of rice that is traded. Figure 1 plots the proportion of world output that is exported
against world yields for 1960–2011. The world yield is the production share weighted average of
individual country yields. For world yields up to 3 tons per hectare (ha), world exports fluctuate
at around 4% of world output without any trend. Beyond that, in the range of 3 to 3.5 tons per
ha, the ratio of exports to world output fluctuates at around a higher level of 7%. A closer look
shows that the observations in the right half of the graph, involving world yields of more than
3 tons per ha, belong to the period beginning 1994.
4 І ADB Economics Working Paper Series No. 372
World Rice Exports as Proportion of World Rice Output
2
4
6
8
Figure 1: World Rice Trade and World Yields
2011
2004
2002 2007
2006 2009
2005
2001 2010
2003
1998
2008
1999
1994 1997
2000
1995
1980
1966
1965
1964
1979
1963
1962
1972 1977
1961
1967
1978 19811982
1970
1969
1968
1971
1973
1976
1974
1996
1993
1989 1992
1986
1987
19831984 1988
1990
1991
1985
1975
1960
1.5
2
2.5
World Yield
3
3.5
Source: Authors’ estimates.
Table 1 shows that the average export–output ratio in 1994–2011 was 7.16%—which
represents an increase of 87% over the average value in the pre-1994 period. The discrete
jump in the export–output ratio is primarily due to increased rice exports from India. Up to the
early 1990s, quantitative restrictions clamped down on non-basmati rice exports from India. The
removal of these restrictions in 1993 and 1994 led to non-basmati rice exports of 4.5 million tons
from less than a million tons in the early 1990s (Kubo 2011). The other factor behind the higher
export–output ratio is the rise of Viet Nam as a major rice exporter. This has been a more
gradual process starting from the country’s reentry into the world market in 1989. Export
liberalization in India and Viet Nam (the leading exporters next to Thailand), therefore, explains
why the world rice market grew relatively “thicker” in the 1990s.
Table 1: The World Export-to-Output Ratio
1960–1993
1994–2011
Mean
3.82
7.16
Standard deviation
0.56
2.14
14.66
29.89
Coefficient of variation
Source: Authors’ estimates.
International Trade and Risk Sharing in the Global Rice Market | 5
However, from Table 1, note that the pre-1994 period is characterized by low variability
in the export–output ratio even as yields doubled, while the post-1994 period is characterized by
high variability in the export–output ratio even as yields have remained in a narrow range of
3–3.5 tons per ha. The coefficient of variation of the export–output ratio in 1994–2011 is twice
that in the pre-1994 period. Thus, it seems that while world markets have been more open since
the 1990s, policy interventions have made them more unstable as well. India and Viet Nam
were among the first countries to impose export restrictions in 2007. More generally, both these
countries have domestic concerns that spill over into international markets. This was evident
even prior to the 2007 crisis.
In India, the principal domestic policy imperative is for the government to procure
enough supplies to maintain its distribution channel of subsidized rice and wheat. A failure to
restrict procurement left the country with an accumulation of massive stocks. In April 2001, this
amounted to 51 million tons of grain, including 25 million tons of rice. The subsequent unloading
of stocks in the international market led to rising exports and the prolonged stagnation of rice
prices in the global market (Kubo 2011). Such large-scale dumping of government stocks on
the world market ceased after 2004. By 2005, rice stocks in India had fallen to 13 million tons
and more significantly, wheat stocks had dropped to 2 million tons. A subsequent shortfall
in wheat procurement that coincided with wheat crop failures in the rest of the world panicked
the government into wheat imports and a determination not to allow similar shortfalls in rice
procurement. So after dumping rice stocks into the world market in the early 2000s, the
government moved to restrict and finally ban rice exports in the late 2000s. With the recovery of
rice and wheat stocks, the government once again lifted export restrictions.
Viet Nam has always maintained tight control over rice exports. Initially this took the
form of export quotas for registered companies. These were later abolished, and now the
government suspends rice exports once the total reaches the targeted level. In 2007, this
happened routinely according to the export target of that year. In 2008, faced with rising
domestic prices, the government did not allow new export contracts until July of that year. As in
India, concern over the domestic availability of rice prompts the government to tightly monitor
export volumes. However, there is a difference as well: India’s exports are less than 5% of its
consumption, while for Viet Nam, they amount to more than 30% of the country’s consumption.
Global sales are more important for Viet Nam—correspondingly, their regulation has been more
predictable and more sensitive to the interests of exporters.
V. THE IMPACT OF EXOGENOUS SHOCKS ON IMPORTS AND CONSUMPTION
A systematic relationship between world yields and global rice trade is not evident in Figure 1.
Within a two-country model, it would be realistic to assume that both countries produce rice. In
this case, in a model of free trade, the amount of rice traded would depend on both domestic
yield shocks as well as foreign shocks. For instance, it is expected that importing countries
would decrease imports in response to positive domestic yield shocks and increase imports
when there is a positive yield shock in the foreign country. As imports feed into consumption, we
can also consider the consequences for this indicator of economic welfare. For both countries,
consumption is expected to be positively related to both domestic and foreign yield shocks. In
the extreme and unrealistic case of perfectly integrated markets, the source of the yield shock
would not matter. A weaker hypothesis is that consumption depends positively on both domestic
and foreign yield shocks. We now test these hypotheses.
6 І ADB Economics Working Paper Series No. 372
Our data set on country production, area, and stocks is drawn from the US Department
of Agriculture. To compute exogenous shocks, we smooth the yield series using the HoltWinters double exponential method. The deviation of the smoothed series from the observation
is defined as the yield shock. This is computed for every country. For every country, we also
compute a foreign yield shock, which is the production weighted average of the yield shocks in
each of the countries constituting the rest of the world.
To examine the potential of trade, the correlation between domestic yield and foreign
yield shocks is worth considering. When there are adverse shocks to both domestic and foreign
yields, trade cannot be of much help. To assess the probability of such outcomes, we slice
domestic and foreign yield shocks into three categories: a high negative shock, when the shock
is one standard deviation below the mean; a high positive shock, when the shock is one
standard deviation above the mean; and a mid-range shock, when the yield deviation is within
one standard deviation of the mean. This is done for every country and for every year in the
sample. The cross-tabulation of these shocks for all countries in the sample is displayed in
Table 2. Table 3 contains these cross-tabulations for the major countries that make up world
production and trade: Bangladesh, the PRC, India, Indonesia, Iran, Malaysia, Nigeria, Pakistan,
the Philippines, Saudi Arabia, Thailand, Viet Nam, and the US.
Table 2: Cross-Tabulation of Foreign and Domestic Yield Shocks, All Countries
Foreign Yield Shocks
Domestic Shocks
Negative High
Mid-range
Positive High
Total
Negative High
Mid-range
Positive High
Total
116.00
311.00
88.00
515.00
2.72
7.31
2.07
12.10
533.00
2,111.00
550.00
3,194.00
12.52
49.59
12.92
75.03
9.00
363.00
91.00
548.00
2.21
8.53
2.14
12.87
743.00
2,785.00
729.00
4,257.00
17.45
65.42
17.12
100.00
Note: Values in the lower row represent the number of cross-tabulated observations as a proportion of all
observations.
Source: Authors’ estimates.
The results show that in only about 3% of the cases for the entire sample and in about
2% of the cases for the major countries, low domestic yields are accompanied by low foreign
yields as well. This means that except for these instances, trade, in principle, should work well
in the overwhelming majority of circumstances when domestic production shortfalls are offset to
some extent by higher output elsewhere, and vice versa. Yet the puzzle is that rice trade is
considered unreliable relative to other grains.
International Trade and Risk Sharing in the Global Rice Market | 7
Table 3: Cross-Tabulation of Foreign and Domestic Yield Shocks, Major Countries
Foreign Yield Shocks
Domestic Shocks
Negative High
Mid-range
Positive High
Total
Negative High
Mid-range
Positive High
Total
10.00
56.00
19.00
85.00
1.48
8.30
2.81
12.59
91.00
334.00
76.00
501.00
13.48
49.48
11.26
74.22
22.00
49.00
18.00
89.00
3.26
7.26
2.67
13.19
123.00
439.00
113.00
675.00
18.22
65.04
16.74
100.00
Notes:
1. Major countries are the major importing and exporting countries: Bangladesh, the People’s Republic of China,
India, Indonesia, Iran, Malaysia, Nigeria, Pakistan, the Philippines, Saudi Arabia, Thailand, the United States,
and Viet Nam.
2. Values in the lower row represent the number of cross-tabulated observations as a proportion of all observations.
Source: Authors’ estimates.
Table 4 is a regression of the first difference in log of imports (as proportion of
consumption) on the dummy variables for each of the categories in the cross-tabulations of
Tables 2 and 3. The regression is based on the sample of all importing countries. As expected,
the percentage change in imports is negative and the greatest in absolute value when the
domestic shock is highly positive and the foreign shock is highly negative. This is the case
when the demand for imports is at its minimum and the world supply is also at its lowest.
Unsurprisingly, percentage change in imports is positive and maximal when the domestic shock
is highly negative and when the foreign shock is highly positive. This is the opposite case when
world supply is at its maximum and so is the demand for imports. These are instances when
trade works in the expected direction. More surprisingly, imports as a proportion of consumption
increase even when shocks are negative at home and abroad. In this case, world supply is low
but import demand is high.
There is a clear pattern to the results. The percentage change in imports is less (or
negative) when domestic shocks are highly positive; it is high and positive when domestic
shocks are highly negative.
To see the cost of highly negative domestic shocks, consider a regression of the log
change in rice consumption as a function of the dummy variables representing the combination
of highly negative, mid-range, and highly positive domestic and foreign yield shocks. Table 5
shows the results for the entire sample of countries, not just importers. A second specification in
the table adds lagged values of the dependent variable as regressors.2 The impact of the
shocks does not vary much between the specifications in terms of the sign and significance of
the coefficients.
2
Conventional fixed effects estimators (such as the within estimator) are inconsistent when lagged values of the
dependent variable are used as regressors. We used the Arellano–Bond estimator which transforms the data into
first differences and takes care of the correlation between the error term (first difference of the original error term)
and the lagged first differences of the dependent variable by using higher-order lags of the dependent variable as
instrumental variables (Arellano and Bond 1991).
8 І ADB Economics Working Paper Series No. 372
Table 4: Imports Regression
Dependent Variable: First Difference of Log (Imports/Consumption)
Variables
Coefficients
Standard Errors
Dummy variable for negative domestic yield shock
and negative foreign yield shock
0.398
0.131000
3.03
Dummy variable for negative domestic yield shock
and mid-range foreign yield shock
0.286
0.113000
2.52
Dummy variable for negative domestic yield shock
and positive foreign yield shock
0.636
0.141000
4.51
Dummy variable for mid-range domestic yield
shock and negative foreign yield shock
0.139
0.108000
1.29
Dummy variable for mid-range domestic yield
shock and mid-range foreign yield shock mm
0.182
0.102000
1.78
Dummy variable for mid-range domestic yield
shock and positive foreign yield shock
0.112
0.109000
1.03
Dummy variable for positive domestic yield shock
and negative foreign yield shock
–0.316
0.139000
–2.28
Dummy variable for positive domestic yield shock
and mid-range foreign yield shock
0.057
0.112000
0.51
Dummy variable for positive domestic yield shock
and positive foreign yield shock
(omitted)
Constant
–0.181
0.100219
–1.80
Notes:
1. The number of observations is 2,683.
2. The sample of importing countries is for 1960–2010.
3. Regression model includes country fixed effects.
Source: Authors’ estimates.
t-value
International Trade and Risk Sharing in the Global Rice Market | 9
Table 5: Consumption Regression, All Countries
Dependent Variable: Log of change in rice consumption
Coefficients
Standard
Errors
t-value
Coefficients
Standard
Errors
t-value
Dummy variable for negative
domestic yield shock and
negative foreign yield shock
–0.222
0.032
–6.94
–0.219
0.042
–5.26
Dummy variable for negative
domestic yield shock and midrange foreign yield shock
–0.186
0.027
–6.80
–0.195
0.045
–4.37
Dummy variable for negative
domestic yield shock and
positive foreign yield shock
–0.176
0.034
–5.10
–0.188
0.054
–3.49
Dummy variable for mid-range
domestic yield shock and
negative foreign yield shock
–0.107
0.026
–4.10
–0.103
0.038
–2.71
Dummy variable for mid-range
domestic yield shock and midrange foreign yield shock mm
–0.092
0.025
–3.74
–0.088
0.041
–2.18
Dummy variable for mid-range
domestic yield shock and
positive foreign yield shock
–0.107
0.026
–4.11
–0.103
0.044
–2.35
Dummy variable for positive
domestic yield shock and
negative foreign yield shock
–0.006
0.034
–0.19
–0.027
0.046
–0.59
Dummy variable for positive
domestic yield shock and midrange foreign yield shock
–0.025
0.027
–0.92
–0.024
0.045
–0.53
Variables
Dummy variable for positive
domestic yield shock and
positive foreign yield shock
(omitted)
(omitted)
Lagged dependent variable
(1st order)
–0.344
0.033
–10.30
Lagged dependent variable
(2nd order)
–0.117
0.033
–3.55
0.141
0.039
3.60
Constant
0.131
0.024
5.44
Notes:
1. The number of observations is 4,155 (3,885 for specification with lagged dependent variables).
2. The sample consists of 87 countries for 1960–2010, country fixed effects.
3. The specification with lagged dependent variables has been estimated with the Arellano–Bond method using
second- to sixth-order lags of the dependent variable as instrumental variables.
Source: Authors’ estimates.
Reading from the first specification, in the scenario of highly negative domestic and
3
foreign yield shocks, rice consumption declines by 9%. In the scenario of highly negative
domestic shocks but highly positive foreign yield shocks, rice consumption declines by 4.5%.
The difference in outcomes between these scenarios is a measure of the value of access to
world markets. However, consumption declines in all the scenarios involving negative domestic
yield shocks. Positive foreign shocks can compensate, but not fully. Earlier, we mentioned that
reliance on trade could fail in 2% of the instances when negative shocks affect both domestic
3
All of the results are relative to the country-specific fixed effect.
10 І ADB Economics Working Paper Series No. 372
and foreign markets. But now it is apparent that rice consumption is vulnerable in all the
scenarios involving negative domestic shocks. Such instances occur 12% of the time. Perhaps
this is why rice markets are regarded as “unreliable” in the literature.
The flip side of these results is that rice consumption increases by 10%–13% in all the
scenarios involving positive domestic shocks. Most strikingly, the increase in consumption in
the scenario of positive domestic and foreign yield shocks (13%) is almost the same as in the
scenario of positive domestic and negative foreign yield shocks (12.5%). The failure of trade to
redistribute supplies in the latter scenario seems to be the reason why trade is not able to
stabilize consumption in countries hit by negative domestic shocks even though world supplies
are ample.
Table 6 is the consumption regression for some of the Asian countries important in the
world rice economy: Bangladesh, the PRC, India, Indonesia, the Philippines, and Viet Nam.
4
Pakistan and Thailand are excluded. Once again, the implied rates of consumption change do
not vary greatly between the two specifications.
Table 6: Consumption Regression, Selected Asian Countries
Dependent Variable: Log of change in rice consumption
Coefficients
Standard
Errors
t-value
Coefficients
Standard
Errors
t-value
Dummy variable for negative
domestic yield shock and
negative foreign yield shock
–0.169
0.034
–4.92
–0.185
0.010
–18.64
Dummy variable for negative
domestic yield shock and midrange foreign yield shock
–0.078
0.022
–3.52
–0.088
0.040
–2.21
Dummy variable for negative
domestic yield shock and
positive foreign yield shock
–0.106
0.025
–4.16
–0.119
0.041
–2.89
Dummy variable for mid-range
domestic yield shock and
negative foreign yield shock
–0.050
0.021
–2.34
–0.057
0.030
–1.93
Dummy variable for mid-range
domestic yield shock and midrange foreign yield shock mm
–0.046
0.020
–2.27
–0.052
0.027
–1.91
Dummy variable for mid-range
domestic yield shock and
positive foreign yield shock
–0.033
0.022
–1.54
–0.041
0.024
–1.70
Dummy variable for positive
domestic yield shock and
negative foreign yield shock
–0.002
0.025
–0.09
–0.016
0.020
–0.81
Variables
continued on next page
4
Exports as a proportion of consumption are greater than 50% in both these countries. The vulnerability of
domestic consumption to yield shocks would not be a major concern here.
International Trade and Risk Sharing in the Global Rice Market | 11
Table 6 continued
Variables
Dummy variable for positive
domestic yield shock and midrange foreign yield shock
Dummy variable for positive
domestic yield shock and
positive foreign yield shock
Coefficients
Standard
Errors
0.017
0.022
t-value
0.77
(omitted)
Coefficients
Standard
Errors
t-value
0.000
0.027
0.00
(omitted)
Lagged dependent variable
(1st order)
–0.235
0.102
–2.31
Lagged dependent variable
(2nd order)
–0.144
0.085
–1.70
0.087
0.028
3.13
Constant
0.068
0.020
3.43
Notes:
1. The number of observations is 306 (288 for specification with lagged dependent variables).
2. The sample consists of six countries for 1960–2010: Bangladesh, the People’s Republic of China, India, Indonesia,
the Philippines, and Viet Nam; The regression uses country fixed effects.
3. The specification with lagged dependent variables has been estimated with the Arellano–Bond method using
second- to sixth-order lags of the dependent variable as instrumental variables.
Source: Authors’ estimates.
Table 7 compares the average percentage change in rice consumption in each of the
shock scenarios for the entire sample and for the Asian sample. The common finding is that rice
consumption declines are substantial and comparable in the scenario of negative domestic and
foreign shocks. However, Asian countries seem to do better to arrest consumption declines in
the other scenarios involving negative domestic yields. The most striking difference involves the
positive domestic yield scenarios: the consumption growth in the Asian countries is lower than in
the world sample. This could be due to exports or the build-up of domestic stocks. The latter
seems more likely because, as in the world sample, the difference in consumption growth
between the scenarios of positive and negative foreign shocks (given positive domestic shock)
is small. Domestic stocks in turn may have enabled these countries to stabilize consumption
when domestic shocks are negative. Yet, even this policy has not been successful when
negative domestic shocks are accompanied by negative foreign shocks.
12 І ADB Economics Working Paper Series No. 372
Table 7: Predicted Percentage Change in Consumption by Combination of Shocks
Shocks
All
Asian
Dummy variable for negative domestic yield shock and
negative foreign yield shock
–0.091
–0.091
Dummy variable for negative domestic yield shock and midrange foreign yield shock
–0.055
–0.008
Dummy variable for negative domestic yield shock and
positive foreign yield shock
–0.045
–0.034
Dummy variable for mid-range domestic yield shock and
negative foreign yield shock
0.024
0.022
Dummy variable for mid-range domestic yield shock and midrange foreign yield shock
0.039
0.028
Dummy variable for mid-range domestic yield shock and
positive foreign yield shock
0.024
0.040
Dummy variable for positive domestic yield shock and
negative foreign yield shock
0.125
0.067
Dummy variable for positive domestic yield shock and midrange foreign yield shock
0.106
0.086
Dummy variable for positive domestic yield shock and positive
foreign yield shock
0.131
0.071
Note: Results are based on coefficient estimates for the first specification in Tables 5 and 6, where lagged values of
the dependent variable are not used as regressors.
Source: Authors’ estimates.
VI. POLICY RESPONSE
It is clear that negative domestic shocks occur when stabilization fails to take place. Access to
world markets helps but even when foreign yields are high, consumption declines. These are
reduced form results and the outcome of both trade and domestic stabilization policies. To
understand how exogenous shocks are modified by trade and domestic policies, we consider
the following regression model for country j and year t:
C jt
ln
1 2 jt DY jt 3 jt FY jt 4 DS jt 5 FS
C
j , t 1
jt
j jt
(1)
where C is rice consumption; DY and FY are domestic and foreign yield shocks; DS and FS are
the domestic and rest-of-the-world stocks, both as proportions of domestic and rest-of-the-world
consumption, respectively, at the beginning of year t; and is a country fixed effect. Earlier, we
explained how shocks were constructed.
In our data, the policy variable is the level of stocks in each country. Clearly, trade
restrictions will have a direct impact on stocks. For each country, we construct a domestic stock
variable and a foreign stock, which is an aggregate of the stocks in the rest of the world. We
allow the coefficients of domestic and foreign yield shocks to vary with domestic stocks and
foreign stocks. In particular,
International Trade and Risk Sharing in the Global Rice Market | 13
2 jt 1 2DS jt 3FS jt and similarly,
(2)
3 jt 1 2DS jt 3 FS jt
(3)
The results are presented in Table 8. Both domestic shocks and domestic stocks have a
positive impact on the change in consumption, and are statistically significant as well. Foreign
yields and foreign stocks are not significant. The interaction term involving domestic shocks and
domestic stocks is significantly negative. This shows that domestic policies moderate the impact
of domestic shocks.
Table 8: Consumption Regression with Yield Shocks and Stocks
Dependent Variable: Log of change in rice consumption
Coefficients
Standard
Errors
t-value
Lagged Dependent Variable (1st order)
–0.341
0.033
–10.39
Lagged Dependent Variable (2nd order)
–0.127
0.030
–4.25
Domestic stock/Consumption
0.293
0.096
3.05
Foreign stock/Foreign consumption
0.243
0.247
0.98
Domestic yield shock
0.195
0.079
2.46
Foreign yield shock
0.234
0.671
0.35
–0.095
0.040
–2.39
0.115
0.298
0.39
Foreign shock X (domestic stock/domestic
consumption)
–0.697
0.363
–1.92
Foreign shock X (foreign stock /foreign consumption)
–0.052
2.832
–0.02
Constant
–0.058
0.060
–0.98
Variables
Domestic shock X (domestic stock/domestic
consumption)
Domestic shock X (foreign stock /foreign
consumption)
Notes:
1. The number of observations is 3,885 (87 countries); fixed effects at country level.
2. The model has been estimated with the Arellano–Bond method using second- to sixth-order lags of the dependent
variable as instrumental variables.
Source: Authors’ estimates.
A more revealing approach is to use the classification of shocks into negative, midrange, and positive. This allows policies to interact with shocks in a nonlinear manner. In this
approach, the domestic shock variable is represented by dummies for negative, mid-range,
and positive shocks. Let us call these dummies Nd, Md, and Pd. The foreign shock variable is
represented similarly. Let us call those dummies Nf, Mf, and Pf. Both sets of dummies are
interacted with domestic and foreign stocks. The results can be seen in Table 9. The omitted
base category in the table is the combination of mid-range domestic and mid-range foreign
yield shock.
14 І ADB Economics Working Paper Series No. 372
Table 9: Consumption Regression with Yield Shocks and Stocks
Dependent Variable: Log of change in rice consumption
Coefficients
Standard
Errors
t-value
Lagged Dependent Variable (1st order)
–0.338
0.032
–10.53
Lagged Dependent Variable (2nd order)
–0.119
0.030
–3.99
Domestic stock/Consumption
0.272
0.087
3.12
Foreign stock/Foreign consumption
0.253
0.289
0.88
–0.145
0.039
–3.75
Negative domestic shock X (domestic
stock/consumption)
0.093
0.043
2.14
Negative domestic shock X (foreign stock/foreign
consumption)
0.124
0.127
0.97
Positive domestic shock
0.050
0.047
1.04
–0.096
0.046
–2.10
0.150
0.172
0.88
–0.009
0.035
–0.26
0.071
0.059
1.21
–0.050
0.140
–0.36
0.044
0.031
1.40
Positive foreign shock X (domestic
stock/consumption)
–0.010
0.033
–0.29
Positive foreign shock X (foreign stock/foreign
consumption)
–0.236
0.136
–1.73
Constant
–0.054
0.070
–0.76
Variables
Negative domestic shock
Positive domestic shock X (domestic
stock/consumption)
Positive domestic shock X (foreign
stock/consumption)
Negative foreign shock
Negative foreign shock X (domestic
stock/consumption)
Negative foreign shock X (foreign stock/foreign
consumption)
Positive foreign shock
Notes:
1. The number of observations is 3,885 (87 countries); fixed effects at country level.
2. The model has been estimated with the Arellano–Bond method using second- to eighth-order lags of the
dependent variable as instrumental variables.
Source: Authors’ estimates.
From the table, we see that when both domestic and foreign shocks are negative, the
expected value of the dependent variable is –0.208 + 0.436DS + 0.327FS. Thus, both domestic
and foreign stocks help in stabilizing consumption in this state. However, the effect of foreign
stocks and, by implication, trade, is not significantly different from 0. The median value of
domestic stocks as a proportion of consumption is 0.05. This means that its contribution in
reducing the hit on consumption is about 2.2 percentage points. The 75-percentile level of
stocks is 0.2, and at this level, stocks would arrest the decline in consumption by 8.7 percentage
points. The mean level of the stock ratio when both shocks are negative is 0.14. This reduces
the negative impact on consumption by 6.1 percentage points. The stock-to-consumption ratio
would have to be 47.7% to fully wipe out the adverse impact of domestic and foreign shocks.
International Trade and Risk Sharing in the Global Rice Market | 15
The median level of the foreign stock ratio is 0.21 and that can help in countering the
adverse impact by 6.9 percentage points. However, as noted earlier, this effect is not
precisely estimated.
VII. CONCLUDING REMARKS
There is considerable literature about world price volatility and the transmission of world prices
to domestic prices. In this paper, we have taken a different route to assess stability and to
examine the role of trade and domestic stabilization policies. For each country, we constructed
exogenous domestic and foreign (i.e., rest of the world) yield shocks, and looked at their impact
on rice imports and on rice consumption. We also considered how this impact was modified by
domestic and foreign stocks.
If supply shocks are uncorrelated across countries, the global supply is essentially
stable. Provided that there are no demand shocks, the global price is also stable. Importing
5
countries would be able to import, whenever they need to, at a stable price. Even if shocks are
correlated across countries, as long as the correlation coefficient is less than 1, the global
aggregate supply is a lot more stable than individual country supplies.
Although trade cannot be expected to play a strong role when the major producing and
consuming countries are simultaneously hit by negative yield shocks, such a scenario obtains in
only 3% of cases. In all other cases of negative domestic shocks, they could be at least partially
neutralized by positive foreign shocks. This implies that in a world of free trade, consumption
levels in individual countries would be stabilized. However, our study finds that this is not the
case. In cases of adverse domestic shocks, consumption fails to be stabilized even when
foreign shocks are positive; however, imports do peak. Thus, while trade does help in coping
with domestic risks, it is unable to achieve full risk sharing. The flip side is that when domestic
yield shocks are positive, consumption surges even when the shock in the rest of the world is
negative. Therefore, it is clear that irrespective of foreign shocks, the principal concern for poor
countries is to stabilize consumption when hit by negative domestic yield shocks. The frequency
of such shocks is about 12%.
Domestic policies have played a greater role in stabilizing the adverse impacts of
negative shocks. This could be because of the presumed “unreliability” of rice trade. Storage is
expensive, however, and countries often tend to carry too much stock either because of
extreme precaution or because these policies are captured by producer interests. Furthermore,
reliance on domestic policies will continue to keep rice markets thin and promote market
insulation policies similar to those that led to the rice price spike in 2007–2008.
The positive development in the world rice market has been the greater volume of
trade since the mid-1990s due to the export liberalization in India and the entry of Viet Nam into
world markets. Can there be another shift upwards? Surpluses in the commercial rice exporting
countries such as Thailand, Pakistan, and the US are already high. Exports are as high
as domestic consumption in Thailand and Pakistan, while in the US, the ratio is close to 60%.
That is why the thickening of the rice market had to depend on new exporters such as India
and Viet Nam.
5
This, however, need not be Pareto improving over a scenario of autarky. For an example in this regard, see
Newbery and Stiglitz (1984).
16 І ADB Economics Working Paper Series No. 372
Between 2006 and 2008, Viet Nam’s exports were consistently around 21% of
consumption. However, Indian exports have varied between 2.5% and 6% of domestic
consumption. Not only has India’s contribution to world exports varied, but the surpluses have
also been small relative to domestic consumption. Negative domestic shocks together with
domestic policies can shrink these surpluses quickly. Similarly, in the other large rice-producing
economies such as Bangladesh, the PRC, and Indonesia, the surpluses or deficits are small
relative to consumption, and it is not clear whether they can be reliable contributors to global
supplies in the future. Besides, climate change poses unknown perils to some of the major rice
growing regions in Bangladesh and India.
In this sense, the rise of Viet Nam is reassuring to the long-term future of the world rice
market, although the surpluses are not as large as in Thailand. While surpluses may continue to
rise in Viet Nam, especially with rising prosperity, we might need to see the emergence of
surpluses in other countries for the rice market to thicken. Myanmar and Cambodia are possible
candidates for rice export. It does seem that a more reliable rice-trading system would have to
await greater productivity increases in some of the key rice-producing regions of the world.
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K. Tsukada, eds. The World Food Crisis and the Strategies of Asian Rice Exporters.
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Newbery, D. M. G., and J. E. Stiglitz. 1984. Pareto Inferior Trade. Review of Economic Studies.
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International Trade and Risk Sharing in the Global Rice Market: The Impact of Foreign and Domestic
Supply Shocks
Economists have long raised doubts about the use of price stabilization measures in times of food crises. With
the perceived inefectuality of storage-based price stabilization, trade seems to ofer a more viable alternative.
However, the rise of food prices in 2007–2008 has underscored the unreliability of world markets—particularly,
of rice. Against this backdrop, Shikha Jha, Kensuke Kubo, and Bharat Ramaswami examine the impact of
domestic and foreign supply shocks on international rice trade and domestic consumption. Their study reveals
that export restrictions, price stabilization programs, and other such policies can ofset the impact of negative
domestic shocks.
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