Volatilitas Harga Beras, Faktor Penyebab Dan Pengaruh Perubahan Iklim Terhadap Produksi Padi Dan Volatilitas Harga Beras Di Indonesia
i
RICE PRICE VOLATILITY, ITS DRIVING FACTORS AND
THE IMPACT OF CLIMATE CHANGE ON PADDY
PRODUCTION AND RICE PRICE IN INDONESIA
SILVIA SARI BUSNITA
POSTGRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2016
ii
STATEMENT LETTER OF THESIS AND SOURCE OF
INFORMATION
I declare that thesis entitled Rice Price Volatility, Its Driving Factors and The
Impact of Climate Change on Paddy Production and Rice Price in Indonesia is my
own work with guidance of the advisors and has not been submitted in any form at
any college, except Bogor Agricultural University. The sources of information
derived and quoted from published and unpublished works of other authors
mentioned in the text are listed in the Bibliography at the end of this thesis.
Hereby I transfer the copyright of this thesis to Bogor Agricultural University.
Bogor, March 2016
Silvia Sari Busnita
H151140206
iv
SUMMARY
SILVIA SARI BUSNITA. Rice Price Volatility, Its Driving Factors and the Impact
of Climate Change on Paddy Production and Rice Price in Indonesia. Supervised
by RINA OKTAVIANI and TANTI NOVIANTI.
The issue of food security as the spillover effects of 2007-2008 global crisis
resulted in a surge in food prices at the consumer level around the world. Rising
food prices have become a burden for the poors in developing countries who spend
on average half of their household income on food, especially on cereal
commodities. Meanwhile, in the last decades, there have been an increase number
of floods and periods of drought, devastating cyclones, water, soil and land
resources that are continuing to decline in several parts of the world. The impact of
these global climate change phonemonen could be seen as the production yield of
main crops in tropical countries had become fluctuated. Thus, this has affected the
food price fluctuations especially on the grain price both in international and
domestic markets. The rice-commodity, who had been known for its thin market
characteristics, also experiencing the fluctuation in production, its productivity and
also the rice price. Considering the importance of rice as the main staple food in
Indonesia, the purpose of this research is to identify the Indonesia rice price
fluctuation (volatility), to investigate what are the main drivers that causing the
fluctuation of local rice price in Indonesia; and the last one is to investigate the
consequences of climate change variables (especially temperature changes) towards
Indonesian paddy production, local rice price, and its fluctuation (volatility).
By applying monthly time-series data from 2007 to 2014, this research used
ARCH-GARCH (Autoregressive Conditional Heteroscedasticity-Generalized
Autoregressive Conditional Heteroscedasticity) methods to find out the rice price
volatility. The results find that there exist the volatility (fluctuation) in Indonesian
rice price variable and time varying, with the highest price spikes happened on 2010
and 2011 respectively. While using the VECM (Vector Error Correction Model), it
shows that the driven factors affects the Indonesia local rice price fluctuation are
paddy production, temperature changes, national domestic stock of rice, world rice
price, household comsumption, exchange rate, and interest rates in the long-run.
According to Impulse Response analysis result, the climate changes (the
temperature changes), would affect negatively the paddy production in Indonesia
both in the short run and long run. On contrary, the temperature changes would be
positively influence the rice price and also its fluctuation in Indonesia. These results
are important for the stakeholders and government to prevent the risk of paddy
production uncertainty and rice price fluctuation caused by climate change in the
future.
Keywords: rice price volatility, climate change, paddy production, ARCHGARCH, VECM
vi
RINGKASAN
SILVIA SARI BUSNITA. Volatilitas Harga Beras, Faktor Penyebab dan Pengaruh
Perubahan Iklim terhadap Produksi Padi dan Volatilitas Harga Beras di Indonesia.
Dibimbing oleh RINA OKTAVIANI dan TANTI NOVIANTI.
Isu keamanan pangan sebagai spillover effects dari krisis global tahun 20072008 lalu, salah satunya ditandai dengan lonjakan harga pangan di tingkat
konsumen di seluruh dunia. Peningkatan harga pangan ini menjadi beban bagi
masyarakat miskin di negara berkembang yang menghabiskan rata-rata setengah
dari pendapatan rumah tangga mereka untuk pangan, terutama pada komoditas
serealia (padi-padian). Sementara itu selama beberapa dekade terakhir telah terjadi
peningkatan banjir, kekeringan, perubahan siklus hujan, maupun cuaca ekstrem di
beberapa bagian dunia sebagai pertanda dari perubahan iklim global. Akibat dari
fenomena ini hasil produksi tanaman pangan utama di negara-negara tropis menjadi
berfluktuasi. Hal ini mempengaruhi fluktuasi harga makanan terutama pada harga
pangan pokok baik di pasar internasional dan domestik. Beras sebagai salah satu
komoditi pangan utama dengan karakteristik pasarnya yang “tipis” (jarang
diperdagangkan), juga mengalami fluktuasi dari segi jumlah produksi,
produktivitas maupun harga. Mengingat urgensi beras sebagai makanan pokok
utama di Indonesia, tujuan dari penelitian ini adalah untuk mengidentifikasi
fluktuasi (volatilitas) harga beras di Indonesia, menganalisis faktor pendorong
utama yang menyebabkan fluktuasi harga beras di Indonesia; serta menganalisis
pengaruh variabel perubahan iklim (terutama perubahan suhu) terhadap produksi
padi, harga beras lokal dan fluktuasi (volatilitas) harga beras Indonesia.
Penelitian ini menggunakan data sekunder time-series bulanan dari tahun
2007 sampai 2014. Metode yang digunakan untuk menganalisis volatilitas harga
beras adalah ARCH-GARCH (Autoregressive Conditional HeteroscedasticityGeneralized Autoregressive Conditional Heteroscedasticity). Hasil analisis
volatilitas menunjukkan bahwa harga beras Indonesia merupakan variabel ekonomi
yang bersifat volatile, time-varying (bervariasi antar waktu), dengan lonjakan harga
tertinggi terjadi pada tahun 2010 dan 2011. Sementara berdasarkan hasil estimasi
VECM (Vector Error Correction Model), menunjukkan bahwa faktor-faktor yang
signifikan mempengaruhi fluktuasi harga beras Indonesia dalam jangka panjang
adalah produksi padi, perubahan suhu, cadangan beras domestik nasional, harga
beras dunia, jumlah konsumsi rumah tangga, nilai tukar, dan suku bunga. Sementara
itu, menurut hasil analisis Impulse Response Function, variabel perubahan iklim
(perubahan suhu) akan berpengaruh negatif terhadap produksi padi di Indonesia
dalam jangka pendek dan jangka panjang. Sebaliknya, variabel perubahan suhu ini
akan memberi pengaruh positif pada harga beras serta fluktuasi harga beras di
Indonesia. Hasil penelitian ini penting bagi petani, pemerintah, pedagang maupun
pihak terkait lainnya khususnya yang terkait dengan strategi mitigasi ketidakpastian
produksi padi dan fluktuasi harga beras yang disebabkan oleh perubahan iklim di
masa yang akan datang.
Kata kunci: volatilitas harga-beras, perubahan iklim, ARCH-GARCH, VECM
© All Rights Reserved by IPB, 2016
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Quote some or all of this paper without mentioning and/or including the source is
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RICE PRICE VOLATILITY, ITS DRIVING FACTORS AND
THE IMPACT OF CLIMATE CHANGE ON PADDY
PRODUCTION AND RICE PRICE IN INDONESIA
SILVIA SARI BUSNITA
Thesis
as the partial requirement to attain the degree of
Master of Science
at
Master Program in Economics
POSTGRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2016
Examiner in Thesis Examination: Prof. Dr. M. Firdaus, SP. M.Si
Title
Name
Student ID
: Rice Price Volatility, Its Driving Factors and the Impact of Climate
Change on Paddy Production and Rice Price in Indonesia
: Silvia Sari Busnita
: H151140206
Approved by
Advisory Committee
Dr Ir Tanti Novianti, MSi
Prof. Dr. Jr. Rina Oktaviani, MS
Chair
Member
Acknowledged by
Head of Economics Master Program
Dr. Lukytawati Anggraeni, SP M.Si
Date of Thesis Examination: January 20th, 2016
2016
Date of Graduationzyxwvutsrqponmlk
1 zyxwvutsrqpon
1 MAR
PREFACE
Praise to Allah subhanahu wa ta’ala for His mercy, blessings, and guidance
during the research and thesis completion. The topic chosen in this thesis entitled
“Rice Price Volatility, Its Driving Factors and The Impact of Climate Change on
Paddy Production and Rice Price in Indonesia“carried out from July 2015 to
October 2015, as the requirement in fulfilling the Magister of Science degree at
Economics Master Program in Bogor Agricultural Univeristy. While a completed
thesis bears the single name of the student, the process that leads to its completion
is always accomplished in combination with the dedicated work of other people.
The author hereby wish to acknowledge the appreciation to certain individuals.
The author would like to express great appreciation and sincere thanks to Prof.
Dr. Ir. Rina Oktaviani, MS and Dr. Tanti Novianti, M.Si as supervisors committee
for providing valuable comments, critics and guidance during the writing of this
thesis. The author would also like to express her thanks to examiner in thesis
examination, Prof. Dr. M. Firdaus, SP. M.Si for his advice and corrections in
improving this thesis. Sincere thanks is also expressed to Dean of Bogor
Agricultural University Postgraduate School and staff, Head of Economics Master
Program with its respective staff.
The author would also like to deeply thanks to parents and her siblings for
their love, encouraging words, sacrifices and unconditional support during her
study time in Economics Master Program, the research, and thesis completion. Last
but not least, a very big thanks to fellow postgraduate students from EKO 2014
(Kak Stania, Kak Ilham, Kak Zikra, Kak Mujib), the fasttrack-ers (Bram, Fauziyah,
Fazri, Lala, Ari), the Suiji-ers (Irfan, Rindu, Ikrom, Gilar), research staff at ITAPS
(Mba Lea, Mba Eno) and some of old and great friends (Ravio, Kiki, Hani, Aer) for
their support, advice, and help during the study period and completing this research.
Hopefully this thesis is useful for the readers and gives contribution in
Indonesia economics development in the future.
Anything that made from heart, would goes to heart
Bogor, March 2016
Silvia Sari Busnita
x
TABLE OF CONTENTS
LIST OF TABLES
xiv
LIST OF FIGURES
xiv
LIST OF APPENDICES
xiv
1 INTRODUCTION
Background
Problem Identification
Objectives
Significance
Research Coverage
1
1
2
3
4
4
2 LITERATURE REVIEW
Theoretical Framework
Empirical Review
Logical Framework
4
9
11
13
3 RESEARCH METHODS
Data and Source
Methodological Frameworks
15
15
17
4 RESULT AND DISCUSSION
World and Indonesia Rice Market Overview
ARCH-GARCH Model Specifications
The Volatility of Indonesia Domestic Rice Price
Analysis of Driving Factors Affecting Indonesian Rice Price Fluctuation
Analysis Response of Indonesia Rice Price, Its Volatility, and Paddy
Production towards Climate Change Variable
Analysis Variance Decomposition of Indonesian Paddy Production, Rice
Price, and Its Rice Price Volatility Variables
21
21
22
22
24
30
5 CONCLUSION AND RECOMMENDATION
Conclusion
Policy Recommendation
32
32
32
BIBLIOGRAPHY
33
APPENDICES
37
AUTHOR BIOGRAPHY
54
28
xi
LIST OF TABLES
1
2
3
4
5
6
7
Supply and demand drivers of fluctuating food price
Previous research
List of variables
ARCH-GARCH model specification result
The unit root test results on level and first difference
Johansen Cointegration test results
VECM estimation result
6
12
17
22
24
25
26
LIST OF FIGURES
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Development of World Food Price Index
Main producing countries of rice (paddy) 2012
Rice price instability: Indonesia and other Asian cities
Three-dimensional depiction of three important phases of the El NiñoSouthern Oscillation (ENSO)
Conceptual logical framework
Indonesian consumer retail price of rice January 2007 – May 2015
World rice price January 2007 – May 2015
Indonesian rice price volatility 2007 - 2014
Indonesian paddy yield 2005 – 2014 (Qu/Ha)
Impulse Response Function result; response of paddy production
towards shock on temperature changes
Impulse Response Function result; response of rice price towards
shock on temperature changes
Impulse Response Function result: respones of rice price volatility
towards shock on temperature changes
FEVD (Variance Decomposition Approach) result of domestic rice
price variable
FEVD (Variance Decomposition Approach) result of Indonesian rice
price volatility variable
1
1
3
8
14
21
21
22
23
28
29
29
30
31
LIST OF APPENDICES
1
2
3
4
5
6
7
8
9
10
11
Stationarity test for ARCH-GARCH model
Correlogram test for Indonesian rice price variable
Best ARIMA model for Indonesian rice price variable
ARCH test for Indonesian rice price variable
Best ARCH-GARCH model
Stationarity test for VAR/VECM variables
VAR stability testing
Optimum Lag testing
Cointegration test result
VECM driving factors of Indonesian rice price
FEVD result
37
37
38
38
39
39
42
43
43
44
48
1
1 INTRODUCTION
Background
In recent years, there has been food security issue growing along with the
emergence problems called 3F-crisis (food, fuel, and financial crisis) as the spillover
effects of 2008 global crisis. This phenomenon resulted in food prices surge at the
consumer level around the world. Figure 1 shows the rise in world food price index
and largely dominated by the rising prices of cereals. Based on World Bank Trade
Sector Development report (World Bank 2011) from the sub-indices of international
food prices, the price of grain increased dramatically (in the last 30 years) starting on
the late 2007 and reach its peak at the early period of 2008 crisis.
250.00
200.00
150.00
100.00
50.00
1/1993
8/1993
3/1994
10/1994
5/1995
12/1995
7/1996
2/1997
9/1997
4/1998
11/1998
6/1999
1/2000
8/2000
3/2001
10/2001
5/2002
12/2002
7/2003
2/2004
9/2004
4/2005
11/2005
6/2006
1/2007
8/2007
3/2008
10/2008
5/2009
12/2009
7/2010
2/2011
9/2011
4/2012
11/2012
6/2013
1/2014
-
Food Price Index
Cereals Price Index
Source : FAO 2014
Figure 1 Development of World Food Price Index
One of grain commodities affected by price fluctuations due to 2008 global
crisis is rice. Unlike corn and wheat, rice is not used to produce biofuels.
Nevertheless, the rise in grains price to another one has led to rapid increase in the
price of rice over the past decades (World Bank 2011). In terms of supply, production
of paddy (rice) in the world ranks third of all cereal after maize and wheat (FAO
2014). Most of the rice granary of the world comes from Asian countries with
Indonesia in the third position after China and India. Following graph show the rice
(paddy) main producing countries in 2012.
250000000
Production (MT)
Intl Production ($1000)
200000000
150000000
100000000
50000000
0
Source: FAO 2014
Figure 2 Main producing countries of rice (paddy) 2012
2
The fact was all of these main producer countries also had large consumption
of rice as its staple food. As a result, only a small fraction of the world's rice
production is traded between countries (5-6% of total world production) because
each country must meet their domestic needs. Indonesia's own position is the world's
largest rice importer as 14% of the rice traded in the world (Indonesian Ministry of
Trade 2012). Indonesia’s per capita rice consumption recorded still quite high,
reaching averagely 6.18 kg a week or 139.15 kg/capita/year (BPS 2014). This value
is much higher than the ideal consumption by the developed countries standards as
80-90 kg/capita/year.
Meanwhile, climate change and weather variability are the two climate
anomaly phenomenon which is now a strategic issue and a serious concern because
it is believed to have had a big impact to life in various sectors. This statement can
be proved by the facts that there has been an increase number of floods and periods
of drought, devastating cyclones, water, soil and land resources that are continuing
to decline in several parts of the World on the last decades (IRRI 2006). The IPCC
4th Assessment Report (IPCC 2007) states that Southeast Asia is expected to be
seriously affected by the adverse impacts of climate change. It is projected that by
2100 the annual mean temperature in Indonesia, the Philippines, Thailand and Viet
Nam are going to rise by 4.8 °C, with the global mean sea level will increase by 70
cm during the same period (ADB 2009). Since most of its economy relies on
agriculture and natural resources as primary income, climate change has been and
will continue to be a critical factor affecting productivity in the region mentioned
before.
Indonesia itself is predicted to experience temperature increases of
approximately 0.8°C by 2030, while the rainfall patterns are predicted to change,
with the rainy season ending earlier and the length of the rainy season becoming
shorter (FPRI 2011). Some empirical studies has been done to analyze this
phenomenon. Climate change affects all economic sectors, but the agricultural sector
is generally the hardest hit in terms of the number of poor affected (Oktaviani 2011).
There has been changes in precipitation and cycles of droughts and floods triggered
by the Australasia monsoon and by the El Niño Southern Oscillation (ENSO) for the
past three decades in Indonesia (Naylor R. L. 2007; Boer 2010). Thus, this has led to
agricultural production damage, causing negative consequences for rural incomes,
food prices, and food security in Indonesia. In Indonesia case, rice is one of the most
important staple foods for more than half of the world’s population (IRRI 2006) and
influences the livelihoods and economies of billions people in Asia. A recent study
by the International Food Policy Research Institute (IFPRI), titled ‘Climate change:
Impact on agriculture and costs of adaptation’, highlighted some of the anticipated
costs of climate change, which one of them is the increase prices in 2050 by 90% for
wheat, 12% for rice and 35% for maize on top of already higher prices.
Problem Identification
Rice is the main food products that has strategic role in strengthening food
security, economic security and the political stability of a country (Timmer 1996).
The existing 2007-2008 food price spike has affected the domestic rice price
instability, not only in the rice-producing countries but also in the non-producing
countries. The following graph from the World Bank Trade report on the last 2011
3
shows the instability of the local rice price in Indonesia compare to other Asian cities
after 2008 global food spike.
Time period
Vietnam Instability
Time period
HK Instability
Jakarta Instability
Thailand
Instability
Indonesia Instability
Source: Worlbank 2011
Figure 3 Rice price instability: Indonesia and other Asian cities
Based on the Figure 3, we can see the instability of Indonesia’s price of rice
reached the highest level compare to other major rice producer’s countries (Thailand
and Viet Nam). In time of 2008 crisis too, the level of Jakarta rice price instability
reach the highest spike compared with Hongkong as the non-major rice producing
country.
The rice instability both in terms of price, stock, and production will gradually
affect social and economic instability, also political security in each country. Since
the biggest food consumption of Indonesian people is rice, then it became main
concern if the price becames fluctuated, especially after the last food price spike.
Therefore the first question that should be answered in this thesis will be “How was
the volatility of domestic rice-price in Indonesia after 2007-2008 crisis?”
Despite the large literature has examined local food prices in developing
countries, there is limited systematic evidence on the relationship between domestic
weather disturbances and local food prices, especially in Indonesia. Although the
effects of climate change already became such a reality in Indonesia, however to date
there has few studies that have assessed the impacts of current and forecast future
climate change on the agricultural economic variables. Therefore, the next question
would be “What are the main drivers of fluctuating local rice price in Indonesia?”
and “How far this climate change variables (especially temperature changes) affect
Indonesia local rice price and its paddy production?”
Objectives
The primary objective of this research is to calculate the fluctuation (the
volatility) of Indonesian rice price, then to investigate what are the main drivers that
causing the fluctuation of local rice price in Indonesia; and the last one is to
4
investigate the consequences of climate change variables (especially temperature
changes) towards Indonesian paddy production, local rice price, and its fluctuation
(volatility).
Significance
This thesis makes a contribution to the existing empirical literature by
combining the two lines of empirical research in an emerging area of green
economics using relatively new time series methodologies that overcome some of
the methodological concerns of other studies (e.g estimating price volatility using
ARCH-GARCH, testing for cointegration test to find out the relationship between
the agriculture economics variables). Finally, the empirical results of this single
country study may be helpful in guiding policy makers in devising long term
sustainable agricultural economics policy in Indonesia.
Research Coverage
This research was conducted in the national scope. The object in this study
covers only single food commodities, rice. The data type used is a monthly time
series data from January 2007 until December 2014.
The price of rice used in this study is medium retail price of rice which sold in
major traditional markets in Indonesia, not the producer price or the Government
purchasing price (HPP). This study did not distinguish the price of rice according to
the quality and type, but rather use the number of rice commodities being produced
data (i.e: paddy-production variable, the Government's rice reserve variable) and any
other appropriate data.
International trade variable used here is the world rice price. While the trade
policy such as export and import tariffs are not used as explanatory variables in this
research modelling because the data is not available in the monthly period. The
Indonesian macroeconomic indicators used in this research are the inflation,
household consumption, exchange rate, and the interest rate. Also, due to the limited
availability of monthly data, the climate change indicators used in this study was the
change in temperature which using ENSO 3.4 temperature variable.
2 LITERATURE REVIEW
Food Price Volatility
The definition of food price volatility is the variation of food price variables
which fluctuate over time, can not be anticipated, which increased the risk of the
economic agents (producer, consumer and government), especially when taking
decision (FAO 2011). According to Tothova (2011), the volatility is divided into two
terms: (a) historical volatility, and (b) implicit volatility. The historical volatility
refers to the price movements that happened in the past and described volatility
during that time. While implicit volatility is the opposite one which aims to estimate
the volatility that occurring in the future. In general, volatility is a very complex issue
that could affect many aspects such as: food security, financial markets, and trade
(Miguez and Michelena 2011). Volatility in economics associated with the price of
5
a commodities as agricultural commodities. Food price volatility that happening in
the foods market does not happen by itself, they surely get influenced by any other
factors. It is useful to think about the factors causing high and volatile food prices in
terms of cumulative layers of causation (Timmer 2008). Following are the four basic
drivers that seem to be stimulating rapid growth in demand for world food
commodities:
1. Rising living standards in China, India, and other rapidly growing developing
countries lead to increased demand for improved diets, especially greater
consumption of vegetable oils and livestock products (and the feedstuffs to
produce them). China is a major importer of soybeans for both meal and oil
and India is a significant importer of vegetable oils. However, wheat and rice
consumption in the China and India are not rising significantly and both
countries are largely self-sufficient in both commodities.
2. The rapid depreciation of the dollar against the euro and some other important
currencies drives up the price of commodities quoted in dollars for both
supply and demand reasons. The depreciation of the dollar also causes
investors “long” in dollars (i.e., most US-based investors, but holders of
dollars globally as well) to seek hedges against this loss of value, with
commodities being one attractive option.
3. Mandates for corn-based ethanol in the US (and biodiesel fuels from
vegetable oils in Europe) cause ripple effects beyond the corn economy,
which are stimulated by inter-commodity linkages (Naylor 2007; Timmer,
Falcon, and Pearson 1983). There is active debate about whether legislative
mandates or high oil prices are driving investments in biofuel capacity
(Abbot, Hurt, and Tyner 2008), but no doubt about the increasing quantities
of corn and vegetable oil being used as biofuel feedstocks (Elliott 2008).
4. Massive speculation from new financial players searching for better returns
than in stocks or real estate has flooded into commodity markets. The
economics and finance communities are unable to say with any confidence
what the price impact of this speculation has been, but virtually all of it has
been a bet on higher prices.
Each of the four demand-driven causes is a little different for each basic
commodity, but the “structural” forces—rapid demand growth in developing
countries and depreciation of the dollar—are similar for all the commodities of
interest here (again, with rising oil prices as a foundation). These factors have been
play for years and fairly predictable, driven by macroeconomic fundamentals. The
two “top” layers, however, have come on the scene much more recently and have the
potential to change the price formation equation rapidly and unexpectedly. Timmer
(2008) summarizes this perspective for supply and demand drivers that causing
volatile food price, according to their “predictability,” i.e., whether the drivers are
low variance (easy to predict) or high variance (very difficult to predict), with the
following table.
6
Table 1 Supply and demand drivers of fluctuating food price
Low Variance
-
High variance
-
Supply
Seed Technology
Irrigation
Total harvested area
Climate change
Knowledge
and
management skills
Weather
Diseases
Crop-specific harvested
area (for rice case)
Fuel costs
Fertilizer costs
Demand
- Population growth
- Income growth
- Dietary changes and
tastes
- Meat and livestock
economy
- Exchange rates
- Speculation
- Biofuels
(predictable
from mandates; but not
predictable from oil
prices)
- Panic or hoarding
- Government trade and
inventory policies
Source: Timmer (2008)
However, nearly all economists and market analysts agree that financial
speculation cannot drive up prices in the long run—over a decade or longer. Only the
fundamentals of supply and demand can do that (Timmer 2008)
Food Price Stabilization
World food price volatility is inevitable things since more than three decades
it has never happened. The food crisis of 2007/2008 and 2010/2011 is the culmination
of the rise in food prices. Price volatility also can not be avoided in agricultural
commodities markets. Price volatility cannot be removed, but can be minimised its
impact through a variety of policies both local and international. According to
Timmer (2011), there is some policy to cope with the volatility of food prices. Price
stabilization policy can be one of the alternatives to reduce volatility, but in the
implementation is often fail. The price stabilization were failed because it could not
be completed efficiently and effectively. Stabilization policy price policy type is the
most widely chosen by countries affected by price shocks. According to the World
Bank (2010) from 56 countries surveyed, 23 countries choose to implement a policy
of stabilization the price for tackling the problem of price uncertainty. These policies
are not efficient. Mongolia and Zimbabwe is an example of two countries that
implement a stabilization of prices but losses against the manufacturer because the
manufacturer sells its products below market price.
The second policy expressed by Timmer is the social safety net policy for the
poor population. This policy can be run with either as long as it has a mature plan to
be implemented in the community. This social safety net policy also has the weakness
that takes a lot of cost to carry it out. The third alternative is by keeping an eye on
trade and international financial markets policy for the food commodities. Gilbert
(2012) expressed another way that can be done to reduce the volatility of price rice
is to discipline the rice exporting countries in setting ban on trade policy by the rules
set out under the WTO.
7
Policies to cope with price volatility can also be done by separating the roles
of Government and the private sector. The Government role is to enforce the law and
institutions so that the private companies can reduce risk price uncertainty. Other
important policies to reduce volatility are the information disclosure and market
agricultural development policy give priority to the improvement of income
especially in rural (Tangermann 2011).
The availability of food reserves for domestic needs is another way to cope
with price volatility (Timmer 2011; Tangermann 2011). Each state either the exporter
or the importer should have a backup food, so as to prevent prices rising sharply. The
world food stock should be realized simultaneously and is part of international
cooperation (Timmer 2011). There are three types of good food reserves domestic
and international, namely (1) the national food reserve that is useful for importing
countries when food prices are very high and not allows for the purchase of food, (2)
international food reserves managed by international organizations and in some
locations aims to provide a food reserve for the developing countries not prepared to
face extreme food crisis, and (3) international institutions like the International Grain
Clearing Arrangements (IGCA) should be able to be proponents of food reserves for
countries exporters in countries failed exports.
Climate Change, Climate Variability, and ENSO
Climate is "average" weather condition for a given place or a region. It defines
typical weather conditions for a given area based on long-term averages. Compare to
weather, climate contains statistical information, a synthesis of weather variation
focusing on a specific area for a specified interval. Climate is usually based on the
weather in one locality averaged for at least 30 years. Climate change is a
phenomenon where there is changes in atmosphere composition that will enlarge the
observed climate variability during such long periods (Trenberth 1996).
Climate variability is the fluctuation of climate elements that occur in a certain
span of time as seasonal or annual variation (i.e: rainy season and the dry season
shifting, changes of timing, or its duration) as well as extreme climate events. Climate
variability describes short-term changes in climate that take place over months,
seasons and years. This variability is the result of natural, large-scale features of the
climate that we looked at earlier.
El-Nino Southern Oscillation or often abbreviated with ENSO occurred in the
ocean. The Pacific sea surface temperature is one of the anomalies of climate that
affect the climate in Indonesia. El Nino is characterized by unusually warming
temperature in equatorial Pacific sea (Philander 1990), as opposed with La Nina. The
El Niño and La Niña, are the two phases of the El Niño-Southern Oscillation (ENSO
– see Figure 4 below) which is the most important driver of year-to-year variability
in climate in the Pacific region (including Indonesia). The different phases of ENSO
can cause droughts and floods. Each El Niño and La Niña event is different and so
they have different impacts. El Niño and La Niña events drive changes in circulation,
winds, rainfall, and ocean surface temperatures. In general the experts divide the
ENSO be warm ENSO or El-Nino and ENSO cold or La-Nina. The conditions
without ENSO events are usually referred as normal incidence (Yoshino 1999).
8
Source : NOAA, http://www.pmel.noaa.gov/tao/elnino/nino-home.html
Figure 4 Three-dimensional depiction of three important phases of the El NiñoSouthern Oscillation (ENSO): Normal (left), La Niña (centre) and El Niño
(right)
Normal condition, or the neutral phase of ENSO, is shown on the left in Figure
4. The trade winds (white arrows) blow to the west and cause a build up of warm
surface water (orange-red areas) and higher sea level in the West Pacific. The warm
water heats the air above it, making the moist air rise and forming clouds (this is
called convection). This warmer air then moves east to where the air is cooler, the
cooler air sinks towards the surface and moves west, creating a convective
circulation.
Indonesia climate variability is very closely related to the El Niño Southern
Oscillation (ENSO) in the Pacific Ocean (Naylor 2002) and the Indian Ocean Dipole
(IOD) in the Indian Ocean (Ashok 2001; Mulyana 2001). Influence of ENSO in
Indonesia is not the same on each area. However, the influence of ENSO is very great
on any area that has a monsoon rains patterns, small influence on the area rain with
equatorial pattern and not clear on local rainfall patterns (Boer 2002).
When El Nino condition happens, the temperature of the sea level in Indonesia
and around is cooling down. As a result, the air mass flowhot bottom moves from
Indonesia headed towards the East. As the area of subsidence, then the rainfall in
Indonesia is relatively below normal. The condition became vice-versa when La Nina
happens, where the flow of hot air masses moving down from the tropical Pacific to
Indonesia. As the result, there is strong convective rainfall that relatively above
normal in Indonesia. As an indicator for monitoring the events, the commonly used
data measurement of Indonesia’s SLP is the NINO 3.4 (170°WL-120°WL, 5°SL5°NL), in which the positive anomalies indicate the occurrence of El Nino, whereas
the negatives anomalies characterized the La-Nina Phenomenon.
Rice production in Indonesia is very influenced by the pattern of monsoonal
rain, which they had very clear differences between rainy season and dry season.
Normal rainy season occurs from October to March, while dry season occurs from
April to September. Previous research from Kishore et.al (2000) investigate the
rainfall anomalies in 1997-1998, and caused a decrease in the acreage of rice harvest
approximately 380,000 ha (3.4% under the previous rainy season). While another
study regarding the El-Niño effect on 1997, the agriculture sector losses forecasted
reached 797 billion rupiah (Boer 1999).
9
Theoretical Framework
Price Formation Model
Understanding the cause of price fluctuation (or volatility) implies an
empirically refutable model of mechanisms of action. As for food prices, this means
an analytical model based on supply and demand mechanisms with equilibrium
prices derived from basic competitive forces. This should be explained in order to
understanding the contribution a wide range of basic causes of fluctuating prices by
important food commodities—rice, wheat, corn, and palm oil. Some of these causes
may be exogenous, (e.g., weather shocks or legislated mandates for biofuel usage).
But many will be endogenous, (e.g., responses of producers and consumers to prices
themselves, perhaps even policy responses of governments to prices).
The model of price formation developed here attempts to incorporate all of
these factors in a rigorous enough way to bring data to bear on answering the key
question in this research. Consider the most basic model of commodity price
formation that is capable of illuminating our problem.
=
�,
=
�,
,�− ,
,� − ,
=
�
�
� −�
=
�
+
log � +
(1)
�−
(2)
where Dt = demand for the commodity during time t; St = supply of the commodity
during time t; f and g = functional forms for demand and supply functions,
respectively; = time-dependent shifters of the demand curve; = time-dependent
shifters of the supply curve; � = equilibrium market price during time t; � − =
market price during some previous time period t-n; and,
,
,
and
=
indicators that demand and supply responses will vary depending on whether they
are in the short run (sr) or long run (lr). In the specification below, these will be shortrun and long-run supply and demand elasticities.
Meanwhile, in short run equilibrium,
= . Then, assume the demand and
supply functions are Cobb-Douglas (in order to simplify the supply and demand
elasticities).
log
+
log � +
log� − = log
Then, solving for the equilibrium price P:
log � =
[log
[
]
− log
�−
]
+ log� − [
−
]/ [
−
log� −
(3)
]
(4)
The next step is taking its first differences to see the factors that explain a
change in price from − to time period which reveals such a complicated result:
log � =
{[log
− log
[
−1 ]−[log
�−
]
− log
−1 ]}
+ [log� − − log� −
+
]
[
−
where log � = the percentage change in price from time period −
t (for relatively small changes).
]
⁄[
−
]
(5)
to time period
10
This is what we are trying to explain. What “causes” changes in log � ? Why
are the food prices high? Answering these questions, we have to simplify the
equation. Let SR = the net short-run supply and demand respons
−
, which is
always negative because
RICE PRICE VOLATILITY, ITS DRIVING FACTORS AND
THE IMPACT OF CLIMATE CHANGE ON PADDY
PRODUCTION AND RICE PRICE IN INDONESIA
SILVIA SARI BUSNITA
POSTGRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2016
ii
STATEMENT LETTER OF THESIS AND SOURCE OF
INFORMATION
I declare that thesis entitled Rice Price Volatility, Its Driving Factors and The
Impact of Climate Change on Paddy Production and Rice Price in Indonesia is my
own work with guidance of the advisors and has not been submitted in any form at
any college, except Bogor Agricultural University. The sources of information
derived and quoted from published and unpublished works of other authors
mentioned in the text are listed in the Bibliography at the end of this thesis.
Hereby I transfer the copyright of this thesis to Bogor Agricultural University.
Bogor, March 2016
Silvia Sari Busnita
H151140206
iv
SUMMARY
SILVIA SARI BUSNITA. Rice Price Volatility, Its Driving Factors and the Impact
of Climate Change on Paddy Production and Rice Price in Indonesia. Supervised
by RINA OKTAVIANI and TANTI NOVIANTI.
The issue of food security as the spillover effects of 2007-2008 global crisis
resulted in a surge in food prices at the consumer level around the world. Rising
food prices have become a burden for the poors in developing countries who spend
on average half of their household income on food, especially on cereal
commodities. Meanwhile, in the last decades, there have been an increase number
of floods and periods of drought, devastating cyclones, water, soil and land
resources that are continuing to decline in several parts of the world. The impact of
these global climate change phonemonen could be seen as the production yield of
main crops in tropical countries had become fluctuated. Thus, this has affected the
food price fluctuations especially on the grain price both in international and
domestic markets. The rice-commodity, who had been known for its thin market
characteristics, also experiencing the fluctuation in production, its productivity and
also the rice price. Considering the importance of rice as the main staple food in
Indonesia, the purpose of this research is to identify the Indonesia rice price
fluctuation (volatility), to investigate what are the main drivers that causing the
fluctuation of local rice price in Indonesia; and the last one is to investigate the
consequences of climate change variables (especially temperature changes) towards
Indonesian paddy production, local rice price, and its fluctuation (volatility).
By applying monthly time-series data from 2007 to 2014, this research used
ARCH-GARCH (Autoregressive Conditional Heteroscedasticity-Generalized
Autoregressive Conditional Heteroscedasticity) methods to find out the rice price
volatility. The results find that there exist the volatility (fluctuation) in Indonesian
rice price variable and time varying, with the highest price spikes happened on 2010
and 2011 respectively. While using the VECM (Vector Error Correction Model), it
shows that the driven factors affects the Indonesia local rice price fluctuation are
paddy production, temperature changes, national domestic stock of rice, world rice
price, household comsumption, exchange rate, and interest rates in the long-run.
According to Impulse Response analysis result, the climate changes (the
temperature changes), would affect negatively the paddy production in Indonesia
both in the short run and long run. On contrary, the temperature changes would be
positively influence the rice price and also its fluctuation in Indonesia. These results
are important for the stakeholders and government to prevent the risk of paddy
production uncertainty and rice price fluctuation caused by climate change in the
future.
Keywords: rice price volatility, climate change, paddy production, ARCHGARCH, VECM
vi
RINGKASAN
SILVIA SARI BUSNITA. Volatilitas Harga Beras, Faktor Penyebab dan Pengaruh
Perubahan Iklim terhadap Produksi Padi dan Volatilitas Harga Beras di Indonesia.
Dibimbing oleh RINA OKTAVIANI dan TANTI NOVIANTI.
Isu keamanan pangan sebagai spillover effects dari krisis global tahun 20072008 lalu, salah satunya ditandai dengan lonjakan harga pangan di tingkat
konsumen di seluruh dunia. Peningkatan harga pangan ini menjadi beban bagi
masyarakat miskin di negara berkembang yang menghabiskan rata-rata setengah
dari pendapatan rumah tangga mereka untuk pangan, terutama pada komoditas
serealia (padi-padian). Sementara itu selama beberapa dekade terakhir telah terjadi
peningkatan banjir, kekeringan, perubahan siklus hujan, maupun cuaca ekstrem di
beberapa bagian dunia sebagai pertanda dari perubahan iklim global. Akibat dari
fenomena ini hasil produksi tanaman pangan utama di negara-negara tropis menjadi
berfluktuasi. Hal ini mempengaruhi fluktuasi harga makanan terutama pada harga
pangan pokok baik di pasar internasional dan domestik. Beras sebagai salah satu
komoditi pangan utama dengan karakteristik pasarnya yang “tipis” (jarang
diperdagangkan), juga mengalami fluktuasi dari segi jumlah produksi,
produktivitas maupun harga. Mengingat urgensi beras sebagai makanan pokok
utama di Indonesia, tujuan dari penelitian ini adalah untuk mengidentifikasi
fluktuasi (volatilitas) harga beras di Indonesia, menganalisis faktor pendorong
utama yang menyebabkan fluktuasi harga beras di Indonesia; serta menganalisis
pengaruh variabel perubahan iklim (terutama perubahan suhu) terhadap produksi
padi, harga beras lokal dan fluktuasi (volatilitas) harga beras Indonesia.
Penelitian ini menggunakan data sekunder time-series bulanan dari tahun
2007 sampai 2014. Metode yang digunakan untuk menganalisis volatilitas harga
beras adalah ARCH-GARCH (Autoregressive Conditional HeteroscedasticityGeneralized Autoregressive Conditional Heteroscedasticity). Hasil analisis
volatilitas menunjukkan bahwa harga beras Indonesia merupakan variabel ekonomi
yang bersifat volatile, time-varying (bervariasi antar waktu), dengan lonjakan harga
tertinggi terjadi pada tahun 2010 dan 2011. Sementara berdasarkan hasil estimasi
VECM (Vector Error Correction Model), menunjukkan bahwa faktor-faktor yang
signifikan mempengaruhi fluktuasi harga beras Indonesia dalam jangka panjang
adalah produksi padi, perubahan suhu, cadangan beras domestik nasional, harga
beras dunia, jumlah konsumsi rumah tangga, nilai tukar, dan suku bunga. Sementara
itu, menurut hasil analisis Impulse Response Function, variabel perubahan iklim
(perubahan suhu) akan berpengaruh negatif terhadap produksi padi di Indonesia
dalam jangka pendek dan jangka panjang. Sebaliknya, variabel perubahan suhu ini
akan memberi pengaruh positif pada harga beras serta fluktuasi harga beras di
Indonesia. Hasil penelitian ini penting bagi petani, pemerintah, pedagang maupun
pihak terkait lainnya khususnya yang terkait dengan strategi mitigasi ketidakpastian
produksi padi dan fluktuasi harga beras yang disebabkan oleh perubahan iklim di
masa yang akan datang.
Kata kunci: volatilitas harga-beras, perubahan iklim, ARCH-GARCH, VECM
© All Rights Reserved by IPB, 2016
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Quote some or all of this paper without mentioning and/or including the source is
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thesis, reports, critical writing, or issue review; and the citations are not
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RICE PRICE VOLATILITY, ITS DRIVING FACTORS AND
THE IMPACT OF CLIMATE CHANGE ON PADDY
PRODUCTION AND RICE PRICE IN INDONESIA
SILVIA SARI BUSNITA
Thesis
as the partial requirement to attain the degree of
Master of Science
at
Master Program in Economics
POSTGRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2016
Examiner in Thesis Examination: Prof. Dr. M. Firdaus, SP. M.Si
Title
Name
Student ID
: Rice Price Volatility, Its Driving Factors and the Impact of Climate
Change on Paddy Production and Rice Price in Indonesia
: Silvia Sari Busnita
: H151140206
Approved by
Advisory Committee
Dr Ir Tanti Novianti, MSi
Prof. Dr. Jr. Rina Oktaviani, MS
Chair
Member
Acknowledged by
Head of Economics Master Program
Dr. Lukytawati Anggraeni, SP M.Si
Date of Thesis Examination: January 20th, 2016
2016
Date of Graduationzyxwvutsrqponmlk
1 zyxwvutsrqpon
1 MAR
PREFACE
Praise to Allah subhanahu wa ta’ala for His mercy, blessings, and guidance
during the research and thesis completion. The topic chosen in this thesis entitled
“Rice Price Volatility, Its Driving Factors and The Impact of Climate Change on
Paddy Production and Rice Price in Indonesia“carried out from July 2015 to
October 2015, as the requirement in fulfilling the Magister of Science degree at
Economics Master Program in Bogor Agricultural Univeristy. While a completed
thesis bears the single name of the student, the process that leads to its completion
is always accomplished in combination with the dedicated work of other people.
The author hereby wish to acknowledge the appreciation to certain individuals.
The author would like to express great appreciation and sincere thanks to Prof.
Dr. Ir. Rina Oktaviani, MS and Dr. Tanti Novianti, M.Si as supervisors committee
for providing valuable comments, critics and guidance during the writing of this
thesis. The author would also like to express her thanks to examiner in thesis
examination, Prof. Dr. M. Firdaus, SP. M.Si for his advice and corrections in
improving this thesis. Sincere thanks is also expressed to Dean of Bogor
Agricultural University Postgraduate School and staff, Head of Economics Master
Program with its respective staff.
The author would also like to deeply thanks to parents and her siblings for
their love, encouraging words, sacrifices and unconditional support during her
study time in Economics Master Program, the research, and thesis completion. Last
but not least, a very big thanks to fellow postgraduate students from EKO 2014
(Kak Stania, Kak Ilham, Kak Zikra, Kak Mujib), the fasttrack-ers (Bram, Fauziyah,
Fazri, Lala, Ari), the Suiji-ers (Irfan, Rindu, Ikrom, Gilar), research staff at ITAPS
(Mba Lea, Mba Eno) and some of old and great friends (Ravio, Kiki, Hani, Aer) for
their support, advice, and help during the study period and completing this research.
Hopefully this thesis is useful for the readers and gives contribution in
Indonesia economics development in the future.
Anything that made from heart, would goes to heart
Bogor, March 2016
Silvia Sari Busnita
x
TABLE OF CONTENTS
LIST OF TABLES
xiv
LIST OF FIGURES
xiv
LIST OF APPENDICES
xiv
1 INTRODUCTION
Background
Problem Identification
Objectives
Significance
Research Coverage
1
1
2
3
4
4
2 LITERATURE REVIEW
Theoretical Framework
Empirical Review
Logical Framework
4
9
11
13
3 RESEARCH METHODS
Data and Source
Methodological Frameworks
15
15
17
4 RESULT AND DISCUSSION
World and Indonesia Rice Market Overview
ARCH-GARCH Model Specifications
The Volatility of Indonesia Domestic Rice Price
Analysis of Driving Factors Affecting Indonesian Rice Price Fluctuation
Analysis Response of Indonesia Rice Price, Its Volatility, and Paddy
Production towards Climate Change Variable
Analysis Variance Decomposition of Indonesian Paddy Production, Rice
Price, and Its Rice Price Volatility Variables
21
21
22
22
24
30
5 CONCLUSION AND RECOMMENDATION
Conclusion
Policy Recommendation
32
32
32
BIBLIOGRAPHY
33
APPENDICES
37
AUTHOR BIOGRAPHY
54
28
xi
LIST OF TABLES
1
2
3
4
5
6
7
Supply and demand drivers of fluctuating food price
Previous research
List of variables
ARCH-GARCH model specification result
The unit root test results on level and first difference
Johansen Cointegration test results
VECM estimation result
6
12
17
22
24
25
26
LIST OF FIGURES
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Development of World Food Price Index
Main producing countries of rice (paddy) 2012
Rice price instability: Indonesia and other Asian cities
Three-dimensional depiction of three important phases of the El NiñoSouthern Oscillation (ENSO)
Conceptual logical framework
Indonesian consumer retail price of rice January 2007 – May 2015
World rice price January 2007 – May 2015
Indonesian rice price volatility 2007 - 2014
Indonesian paddy yield 2005 – 2014 (Qu/Ha)
Impulse Response Function result; response of paddy production
towards shock on temperature changes
Impulse Response Function result; response of rice price towards
shock on temperature changes
Impulse Response Function result: respones of rice price volatility
towards shock on temperature changes
FEVD (Variance Decomposition Approach) result of domestic rice
price variable
FEVD (Variance Decomposition Approach) result of Indonesian rice
price volatility variable
1
1
3
8
14
21
21
22
23
28
29
29
30
31
LIST OF APPENDICES
1
2
3
4
5
6
7
8
9
10
11
Stationarity test for ARCH-GARCH model
Correlogram test for Indonesian rice price variable
Best ARIMA model for Indonesian rice price variable
ARCH test for Indonesian rice price variable
Best ARCH-GARCH model
Stationarity test for VAR/VECM variables
VAR stability testing
Optimum Lag testing
Cointegration test result
VECM driving factors of Indonesian rice price
FEVD result
37
37
38
38
39
39
42
43
43
44
48
1
1 INTRODUCTION
Background
In recent years, there has been food security issue growing along with the
emergence problems called 3F-crisis (food, fuel, and financial crisis) as the spillover
effects of 2008 global crisis. This phenomenon resulted in food prices surge at the
consumer level around the world. Figure 1 shows the rise in world food price index
and largely dominated by the rising prices of cereals. Based on World Bank Trade
Sector Development report (World Bank 2011) from the sub-indices of international
food prices, the price of grain increased dramatically (in the last 30 years) starting on
the late 2007 and reach its peak at the early period of 2008 crisis.
250.00
200.00
150.00
100.00
50.00
1/1993
8/1993
3/1994
10/1994
5/1995
12/1995
7/1996
2/1997
9/1997
4/1998
11/1998
6/1999
1/2000
8/2000
3/2001
10/2001
5/2002
12/2002
7/2003
2/2004
9/2004
4/2005
11/2005
6/2006
1/2007
8/2007
3/2008
10/2008
5/2009
12/2009
7/2010
2/2011
9/2011
4/2012
11/2012
6/2013
1/2014
-
Food Price Index
Cereals Price Index
Source : FAO 2014
Figure 1 Development of World Food Price Index
One of grain commodities affected by price fluctuations due to 2008 global
crisis is rice. Unlike corn and wheat, rice is not used to produce biofuels.
Nevertheless, the rise in grains price to another one has led to rapid increase in the
price of rice over the past decades (World Bank 2011). In terms of supply, production
of paddy (rice) in the world ranks third of all cereal after maize and wheat (FAO
2014). Most of the rice granary of the world comes from Asian countries with
Indonesia in the third position after China and India. Following graph show the rice
(paddy) main producing countries in 2012.
250000000
Production (MT)
Intl Production ($1000)
200000000
150000000
100000000
50000000
0
Source: FAO 2014
Figure 2 Main producing countries of rice (paddy) 2012
2
The fact was all of these main producer countries also had large consumption
of rice as its staple food. As a result, only a small fraction of the world's rice
production is traded between countries (5-6% of total world production) because
each country must meet their domestic needs. Indonesia's own position is the world's
largest rice importer as 14% of the rice traded in the world (Indonesian Ministry of
Trade 2012). Indonesia’s per capita rice consumption recorded still quite high,
reaching averagely 6.18 kg a week or 139.15 kg/capita/year (BPS 2014). This value
is much higher than the ideal consumption by the developed countries standards as
80-90 kg/capita/year.
Meanwhile, climate change and weather variability are the two climate
anomaly phenomenon which is now a strategic issue and a serious concern because
it is believed to have had a big impact to life in various sectors. This statement can
be proved by the facts that there has been an increase number of floods and periods
of drought, devastating cyclones, water, soil and land resources that are continuing
to decline in several parts of the World on the last decades (IRRI 2006). The IPCC
4th Assessment Report (IPCC 2007) states that Southeast Asia is expected to be
seriously affected by the adverse impacts of climate change. It is projected that by
2100 the annual mean temperature in Indonesia, the Philippines, Thailand and Viet
Nam are going to rise by 4.8 °C, with the global mean sea level will increase by 70
cm during the same period (ADB 2009). Since most of its economy relies on
agriculture and natural resources as primary income, climate change has been and
will continue to be a critical factor affecting productivity in the region mentioned
before.
Indonesia itself is predicted to experience temperature increases of
approximately 0.8°C by 2030, while the rainfall patterns are predicted to change,
with the rainy season ending earlier and the length of the rainy season becoming
shorter (FPRI 2011). Some empirical studies has been done to analyze this
phenomenon. Climate change affects all economic sectors, but the agricultural sector
is generally the hardest hit in terms of the number of poor affected (Oktaviani 2011).
There has been changes in precipitation and cycles of droughts and floods triggered
by the Australasia monsoon and by the El Niño Southern Oscillation (ENSO) for the
past three decades in Indonesia (Naylor R. L. 2007; Boer 2010). Thus, this has led to
agricultural production damage, causing negative consequences for rural incomes,
food prices, and food security in Indonesia. In Indonesia case, rice is one of the most
important staple foods for more than half of the world’s population (IRRI 2006) and
influences the livelihoods and economies of billions people in Asia. A recent study
by the International Food Policy Research Institute (IFPRI), titled ‘Climate change:
Impact on agriculture and costs of adaptation’, highlighted some of the anticipated
costs of climate change, which one of them is the increase prices in 2050 by 90% for
wheat, 12% for rice and 35% for maize on top of already higher prices.
Problem Identification
Rice is the main food products that has strategic role in strengthening food
security, economic security and the political stability of a country (Timmer 1996).
The existing 2007-2008 food price spike has affected the domestic rice price
instability, not only in the rice-producing countries but also in the non-producing
countries. The following graph from the World Bank Trade report on the last 2011
3
shows the instability of the local rice price in Indonesia compare to other Asian cities
after 2008 global food spike.
Time period
Vietnam Instability
Time period
HK Instability
Jakarta Instability
Thailand
Instability
Indonesia Instability
Source: Worlbank 2011
Figure 3 Rice price instability: Indonesia and other Asian cities
Based on the Figure 3, we can see the instability of Indonesia’s price of rice
reached the highest level compare to other major rice producer’s countries (Thailand
and Viet Nam). In time of 2008 crisis too, the level of Jakarta rice price instability
reach the highest spike compared with Hongkong as the non-major rice producing
country.
The rice instability both in terms of price, stock, and production will gradually
affect social and economic instability, also political security in each country. Since
the biggest food consumption of Indonesian people is rice, then it became main
concern if the price becames fluctuated, especially after the last food price spike.
Therefore the first question that should be answered in this thesis will be “How was
the volatility of domestic rice-price in Indonesia after 2007-2008 crisis?”
Despite the large literature has examined local food prices in developing
countries, there is limited systematic evidence on the relationship between domestic
weather disturbances and local food prices, especially in Indonesia. Although the
effects of climate change already became such a reality in Indonesia, however to date
there has few studies that have assessed the impacts of current and forecast future
climate change on the agricultural economic variables. Therefore, the next question
would be “What are the main drivers of fluctuating local rice price in Indonesia?”
and “How far this climate change variables (especially temperature changes) affect
Indonesia local rice price and its paddy production?”
Objectives
The primary objective of this research is to calculate the fluctuation (the
volatility) of Indonesian rice price, then to investigate what are the main drivers that
causing the fluctuation of local rice price in Indonesia; and the last one is to
4
investigate the consequences of climate change variables (especially temperature
changes) towards Indonesian paddy production, local rice price, and its fluctuation
(volatility).
Significance
This thesis makes a contribution to the existing empirical literature by
combining the two lines of empirical research in an emerging area of green
economics using relatively new time series methodologies that overcome some of
the methodological concerns of other studies (e.g estimating price volatility using
ARCH-GARCH, testing for cointegration test to find out the relationship between
the agriculture economics variables). Finally, the empirical results of this single
country study may be helpful in guiding policy makers in devising long term
sustainable agricultural economics policy in Indonesia.
Research Coverage
This research was conducted in the national scope. The object in this study
covers only single food commodities, rice. The data type used is a monthly time
series data from January 2007 until December 2014.
The price of rice used in this study is medium retail price of rice which sold in
major traditional markets in Indonesia, not the producer price or the Government
purchasing price (HPP). This study did not distinguish the price of rice according to
the quality and type, but rather use the number of rice commodities being produced
data (i.e: paddy-production variable, the Government's rice reserve variable) and any
other appropriate data.
International trade variable used here is the world rice price. While the trade
policy such as export and import tariffs are not used as explanatory variables in this
research modelling because the data is not available in the monthly period. The
Indonesian macroeconomic indicators used in this research are the inflation,
household consumption, exchange rate, and the interest rate. Also, due to the limited
availability of monthly data, the climate change indicators used in this study was the
change in temperature which using ENSO 3.4 temperature variable.
2 LITERATURE REVIEW
Food Price Volatility
The definition of food price volatility is the variation of food price variables
which fluctuate over time, can not be anticipated, which increased the risk of the
economic agents (producer, consumer and government), especially when taking
decision (FAO 2011). According to Tothova (2011), the volatility is divided into two
terms: (a) historical volatility, and (b) implicit volatility. The historical volatility
refers to the price movements that happened in the past and described volatility
during that time. While implicit volatility is the opposite one which aims to estimate
the volatility that occurring in the future. In general, volatility is a very complex issue
that could affect many aspects such as: food security, financial markets, and trade
(Miguez and Michelena 2011). Volatility in economics associated with the price of
5
a commodities as agricultural commodities. Food price volatility that happening in
the foods market does not happen by itself, they surely get influenced by any other
factors. It is useful to think about the factors causing high and volatile food prices in
terms of cumulative layers of causation (Timmer 2008). Following are the four basic
drivers that seem to be stimulating rapid growth in demand for world food
commodities:
1. Rising living standards in China, India, and other rapidly growing developing
countries lead to increased demand for improved diets, especially greater
consumption of vegetable oils and livestock products (and the feedstuffs to
produce them). China is a major importer of soybeans for both meal and oil
and India is a significant importer of vegetable oils. However, wheat and rice
consumption in the China and India are not rising significantly and both
countries are largely self-sufficient in both commodities.
2. The rapid depreciation of the dollar against the euro and some other important
currencies drives up the price of commodities quoted in dollars for both
supply and demand reasons. The depreciation of the dollar also causes
investors “long” in dollars (i.e., most US-based investors, but holders of
dollars globally as well) to seek hedges against this loss of value, with
commodities being one attractive option.
3. Mandates for corn-based ethanol in the US (and biodiesel fuels from
vegetable oils in Europe) cause ripple effects beyond the corn economy,
which are stimulated by inter-commodity linkages (Naylor 2007; Timmer,
Falcon, and Pearson 1983). There is active debate about whether legislative
mandates or high oil prices are driving investments in biofuel capacity
(Abbot, Hurt, and Tyner 2008), but no doubt about the increasing quantities
of corn and vegetable oil being used as biofuel feedstocks (Elliott 2008).
4. Massive speculation from new financial players searching for better returns
than in stocks or real estate has flooded into commodity markets. The
economics and finance communities are unable to say with any confidence
what the price impact of this speculation has been, but virtually all of it has
been a bet on higher prices.
Each of the four demand-driven causes is a little different for each basic
commodity, but the “structural” forces—rapid demand growth in developing
countries and depreciation of the dollar—are similar for all the commodities of
interest here (again, with rising oil prices as a foundation). These factors have been
play for years and fairly predictable, driven by macroeconomic fundamentals. The
two “top” layers, however, have come on the scene much more recently and have the
potential to change the price formation equation rapidly and unexpectedly. Timmer
(2008) summarizes this perspective for supply and demand drivers that causing
volatile food price, according to their “predictability,” i.e., whether the drivers are
low variance (easy to predict) or high variance (very difficult to predict), with the
following table.
6
Table 1 Supply and demand drivers of fluctuating food price
Low Variance
-
High variance
-
Supply
Seed Technology
Irrigation
Total harvested area
Climate change
Knowledge
and
management skills
Weather
Diseases
Crop-specific harvested
area (for rice case)
Fuel costs
Fertilizer costs
Demand
- Population growth
- Income growth
- Dietary changes and
tastes
- Meat and livestock
economy
- Exchange rates
- Speculation
- Biofuels
(predictable
from mandates; but not
predictable from oil
prices)
- Panic or hoarding
- Government trade and
inventory policies
Source: Timmer (2008)
However, nearly all economists and market analysts agree that financial
speculation cannot drive up prices in the long run—over a decade or longer. Only the
fundamentals of supply and demand can do that (Timmer 2008)
Food Price Stabilization
World food price volatility is inevitable things since more than three decades
it has never happened. The food crisis of 2007/2008 and 2010/2011 is the culmination
of the rise in food prices. Price volatility also can not be avoided in agricultural
commodities markets. Price volatility cannot be removed, but can be minimised its
impact through a variety of policies both local and international. According to
Timmer (2011), there is some policy to cope with the volatility of food prices. Price
stabilization policy can be one of the alternatives to reduce volatility, but in the
implementation is often fail. The price stabilization were failed because it could not
be completed efficiently and effectively. Stabilization policy price policy type is the
most widely chosen by countries affected by price shocks. According to the World
Bank (2010) from 56 countries surveyed, 23 countries choose to implement a policy
of stabilization the price for tackling the problem of price uncertainty. These policies
are not efficient. Mongolia and Zimbabwe is an example of two countries that
implement a stabilization of prices but losses against the manufacturer because the
manufacturer sells its products below market price.
The second policy expressed by Timmer is the social safety net policy for the
poor population. This policy can be run with either as long as it has a mature plan to
be implemented in the community. This social safety net policy also has the weakness
that takes a lot of cost to carry it out. The third alternative is by keeping an eye on
trade and international financial markets policy for the food commodities. Gilbert
(2012) expressed another way that can be done to reduce the volatility of price rice
is to discipline the rice exporting countries in setting ban on trade policy by the rules
set out under the WTO.
7
Policies to cope with price volatility can also be done by separating the roles
of Government and the private sector. The Government role is to enforce the law and
institutions so that the private companies can reduce risk price uncertainty. Other
important policies to reduce volatility are the information disclosure and market
agricultural development policy give priority to the improvement of income
especially in rural (Tangermann 2011).
The availability of food reserves for domestic needs is another way to cope
with price volatility (Timmer 2011; Tangermann 2011). Each state either the exporter
or the importer should have a backup food, so as to prevent prices rising sharply. The
world food stock should be realized simultaneously and is part of international
cooperation (Timmer 2011). There are three types of good food reserves domestic
and international, namely (1) the national food reserve that is useful for importing
countries when food prices are very high and not allows for the purchase of food, (2)
international food reserves managed by international organizations and in some
locations aims to provide a food reserve for the developing countries not prepared to
face extreme food crisis, and (3) international institutions like the International Grain
Clearing Arrangements (IGCA) should be able to be proponents of food reserves for
countries exporters in countries failed exports.
Climate Change, Climate Variability, and ENSO
Climate is "average" weather condition for a given place or a region. It defines
typical weather conditions for a given area based on long-term averages. Compare to
weather, climate contains statistical information, a synthesis of weather variation
focusing on a specific area for a specified interval. Climate is usually based on the
weather in one locality averaged for at least 30 years. Climate change is a
phenomenon where there is changes in atmosphere composition that will enlarge the
observed climate variability during such long periods (Trenberth 1996).
Climate variability is the fluctuation of climate elements that occur in a certain
span of time as seasonal or annual variation (i.e: rainy season and the dry season
shifting, changes of timing, or its duration) as well as extreme climate events. Climate
variability describes short-term changes in climate that take place over months,
seasons and years. This variability is the result of natural, large-scale features of the
climate that we looked at earlier.
El-Nino Southern Oscillation or often abbreviated with ENSO occurred in the
ocean. The Pacific sea surface temperature is one of the anomalies of climate that
affect the climate in Indonesia. El Nino is characterized by unusually warming
temperature in equatorial Pacific sea (Philander 1990), as opposed with La Nina. The
El Niño and La Niña, are the two phases of the El Niño-Southern Oscillation (ENSO
– see Figure 4 below) which is the most important driver of year-to-year variability
in climate in the Pacific region (including Indonesia). The different phases of ENSO
can cause droughts and floods. Each El Niño and La Niña event is different and so
they have different impacts. El Niño and La Niña events drive changes in circulation,
winds, rainfall, and ocean surface temperatures. In general the experts divide the
ENSO be warm ENSO or El-Nino and ENSO cold or La-Nina. The conditions
without ENSO events are usually referred as normal incidence (Yoshino 1999).
8
Source : NOAA, http://www.pmel.noaa.gov/tao/elnino/nino-home.html
Figure 4 Three-dimensional depiction of three important phases of the El NiñoSouthern Oscillation (ENSO): Normal (left), La Niña (centre) and El Niño
(right)
Normal condition, or the neutral phase of ENSO, is shown on the left in Figure
4. The trade winds (white arrows) blow to the west and cause a build up of warm
surface water (orange-red areas) and higher sea level in the West Pacific. The warm
water heats the air above it, making the moist air rise and forming clouds (this is
called convection). This warmer air then moves east to where the air is cooler, the
cooler air sinks towards the surface and moves west, creating a convective
circulation.
Indonesia climate variability is very closely related to the El Niño Southern
Oscillation (ENSO) in the Pacific Ocean (Naylor 2002) and the Indian Ocean Dipole
(IOD) in the Indian Ocean (Ashok 2001; Mulyana 2001). Influence of ENSO in
Indonesia is not the same on each area. However, the influence of ENSO is very great
on any area that has a monsoon rains patterns, small influence on the area rain with
equatorial pattern and not clear on local rainfall patterns (Boer 2002).
When El Nino condition happens, the temperature of the sea level in Indonesia
and around is cooling down. As a result, the air mass flowhot bottom moves from
Indonesia headed towards the East. As the area of subsidence, then the rainfall in
Indonesia is relatively below normal. The condition became vice-versa when La Nina
happens, where the flow of hot air masses moving down from the tropical Pacific to
Indonesia. As the result, there is strong convective rainfall that relatively above
normal in Indonesia. As an indicator for monitoring the events, the commonly used
data measurement of Indonesia’s SLP is the NINO 3.4 (170°WL-120°WL, 5°SL5°NL), in which the positive anomalies indicate the occurrence of El Nino, whereas
the negatives anomalies characterized the La-Nina Phenomenon.
Rice production in Indonesia is very influenced by the pattern of monsoonal
rain, which they had very clear differences between rainy season and dry season.
Normal rainy season occurs from October to March, while dry season occurs from
April to September. Previous research from Kishore et.al (2000) investigate the
rainfall anomalies in 1997-1998, and caused a decrease in the acreage of rice harvest
approximately 380,000 ha (3.4% under the previous rainy season). While another
study regarding the El-Niño effect on 1997, the agriculture sector losses forecasted
reached 797 billion rupiah (Boer 1999).
9
Theoretical Framework
Price Formation Model
Understanding the cause of price fluctuation (or volatility) implies an
empirically refutable model of mechanisms of action. As for food prices, this means
an analytical model based on supply and demand mechanisms with equilibrium
prices derived from basic competitive forces. This should be explained in order to
understanding the contribution a wide range of basic causes of fluctuating prices by
important food commodities—rice, wheat, corn, and palm oil. Some of these causes
may be exogenous, (e.g., weather shocks or legislated mandates for biofuel usage).
But many will be endogenous, (e.g., responses of producers and consumers to prices
themselves, perhaps even policy responses of governments to prices).
The model of price formation developed here attempts to incorporate all of
these factors in a rigorous enough way to bring data to bear on answering the key
question in this research. Consider the most basic model of commodity price
formation that is capable of illuminating our problem.
=
�,
=
�,
,�− ,
,� − ,
=
�
�
� −�
=
�
+
log � +
(1)
�−
(2)
where Dt = demand for the commodity during time t; St = supply of the commodity
during time t; f and g = functional forms for demand and supply functions,
respectively; = time-dependent shifters of the demand curve; = time-dependent
shifters of the supply curve; � = equilibrium market price during time t; � − =
market price during some previous time period t-n; and,
,
,
and
=
indicators that demand and supply responses will vary depending on whether they
are in the short run (sr) or long run (lr). In the specification below, these will be shortrun and long-run supply and demand elasticities.
Meanwhile, in short run equilibrium,
= . Then, assume the demand and
supply functions are Cobb-Douglas (in order to simplify the supply and demand
elasticities).
log
+
log � +
log� − = log
Then, solving for the equilibrium price P:
log � =
[log
[
]
− log
�−
]
+ log� − [
−
]/ [
−
log� −
(3)
]
(4)
The next step is taking its first differences to see the factors that explain a
change in price from − to time period which reveals such a complicated result:
log � =
{[log
− log
[
−1 ]−[log
�−
]
− log
−1 ]}
+ [log� − − log� −
+
]
[
−
where log � = the percentage change in price from time period −
t (for relatively small changes).
]
⁄[
−
]
(5)
to time period
10
This is what we are trying to explain. What “causes” changes in log � ? Why
are the food prices high? Answering these questions, we have to simplify the
equation. Let SR = the net short-run supply and demand respons
−
, which is
always negative because