CITATION: Girsang, P. F., Toiba, H., Syafrial, S., (2023). EGG CHICKEN RACE PRICE VOLATILITY IN INDONESIA BEFORE AND DURING COVID-19 PANDEMIC, Agricultural Socio-Economics Journal, 23(1), 25-31 DOI:
EGG CHICKEN RACE PRICE VOLATILITY IN INDONESIA BEFORE AND DURING COVID-19
PANDEMIC
Putri Feronika Girsang
1*, Hery Toiba
2, Syafrial
21Agriculture Economics Program, Faculty of Agriculture, Brawijaya University, Indonesia
2Department of Socio-Economics, Faculty of Agriculture, Brawijaya University, Indonesia
*corresponding author: [email protected]
Abstract: Understanding about dynamics of the price and volatility of a variety of food has gotten enough big attention in life Public because experience fluctuation sharp price consequences of turmoil economies.
Crisis finance COVID-19 is one of the conditions crisis economy big problems experienced by Indonesia which triggered happening fluctuation the price is not stable (volatility) at producer level and also at consumer level. one ingredient food that has fluctuation price moment the COVID-19 pandemic is ingredient food egg chicken race. The study analyzed the volatility egg chicken race in Indonesia before and during the COVID-19 pandemic in Indonesia. The study used weekly egg chicken race price data at the producers and consumers level from March 2018-March 2022. The secondary data was obtained through Sistem Informasi Pasar Online Nasional-Ternak (SIMPONI-Ternak) by the Ministry of the Agriculture Republic of Indonesia.
The analytical methods used in this study were Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and autoregressive conditionally heteroscedastic approach (ARCH). The findings showed that the price of egg chicken race at producers and consumers level before the COVID-19 pandemic is categorized as a low volatility category and also at producer level during COVID-19 pandemics, while at the consumer level during COVID-19 pandemic is classified as high volatility category. Thus the research this has contributed is as follows. First, useful for designing policies with intervention to help food to the right community and provide regulation prices as an effort to repair prices price in reach stability price egg chicken race post the COVID-19 pandemic is good at the level of producer nor consumer. Second, evaluate the implication performance sector egg chicken race before and during COVID- 19 for destination development sustainable.
Keywords: Price volatility, Egg chicken race, COVID-19, ARCH/GARCH, Indonesia
http://dx.doi.org/10.21776/ub.agrise.2023.023.1.4 Received 2 July 2022 Accepted 20 September 2022 Available online 31 January 2023
INTRODUCTION
Understanding about dynamics of price and volatility of ingredients forgotten to get enough attention big in life Public experiencing fluctuation sharp price consequences turmoil economy and crisis finance (Dahl et al., 2020). Crisconomy the often occur because existence change weather and climate (Malone et al., 2021), weakening institution
consequence instability political (Saswati, 2011), and shocks plague disease like the COVID-19 (M. Y.
Ahmed & Sarkodie, 2021). COVID-19 is one of the conditions crises economy greatest in many countries. Plague not only attack healthy humans who take their lives will but disturb market regulation that causes happening fluctuating price. One of the countries experiencing disturbance market regulation as a result of the COVID-19 pandemic is Indonesia.
Indonesia confirmed the COVID-19 outbreak on March 2, 2020, and spread to several of the provinces in duration enough time short (WHO, 2020). Of course thing, this becomes a big challenge for the government to formulate policy to resolve the shock plague disease. Various policies have been set government that is as applying for distance social encouraging national work, study, worship at home, and procrastination activity anything involving many participants like Indonesia officially imposes restrictions towards community activities (PPKM) and Eenforcement of Restrictions on Public Activities/Pemberlakuan Pembatasan Kegiatan Masyarakat , or PPKM for short (Hairi, 2020).
However, the enforcement policy this trigger happening fluctuation in the price is not stable ( volatility ) in price ingredient food (S. Ahmed et al., 2014).
One of the ingredient food that has fluctuation price moment the COVID-19 pandemic is ingredient food egg chicken race. This thing is caused by more low power buys consumers because worries related to COVID-19 infection if to do an activity outside the house like shop (Goswami & Chouhan, 2021).
Besides its decreasing level of income house ladder make consumer reducing the consumption of ingredient food egg chicken races that don't balance with the level of production carried out. Condition drop income experienced by the people of Nepal triggered happening fluctuation prices so which threaten happening vulnerability food (Ghimire, 2020). Based on System data Market Monitoring Needs tree to occur fluctuation price egg chicken increasingly rate decreased month July 2020 by 2.93 percent compared to year earlier in the same month July 2019 (Kemendag, 2020). Fluctuation price egg chicken race the of course affected by worries consumer-related COVID-19 infection so take effect to power buy ingredient more food reduce (Janssens et al., 2021). Meaning specifically, the environment like the availability of ingredients food, affordable prices, and convenience is an influential thing in the enhancement of request consumer (Mawejje, 2016).
Understanding effect instability price egg chicken race as one ingredient food Becomes important for making policy on an area. because of that, research this aim for knowing level of the volatility price egg chicken race in Indonesia before and during the COVID-19 pandemic so obtained contribution study as following first, useful for designing policy related to intervention help food egg chicken race to the right community and provide regulation price as effort repair market price in reach stability price egg chicken race post the COVID-19
pandemic, both at the level producer as well as at the level consumer. Second, evaluate the implication performance sector egg chicken race before and during COVID- 19 for destination development sustainable.
1. Research Methods
This study uses the time series of the weekly average price of egg chicken race in Indonesia at the producer and consumer level from March 2018 to March 2022. However, it was carried out distinction period time analysis based on the appearance case the COVID-19 pandemic is before and during COVID- 19 pandemic. The period time used before COVID- 19 pandemic was carried out from March 2018 until March 2020 whereas the period time during pandemic was conducted form March 2020 until March 2022. The secondary data were obtained through the Sistem Informasi Pasar Online Nasional- Ternak (SIMPONI-Ternak) by the Ministry of Agriculture Republic of Indonesia and the System Market Monitoring. Volatility analyses the price of egg chicken race at the producer and consumer level in this research using the ARCH/GARCH model by the help of Eviews 9. There are several steps to analysis of price volatility using ARCH/GARCH model, which are:
i. Stationarity Test
Stationery test was conducted to ensure that the data will be analyzed character stationary, so the data is not influenced by time. Stationary test conducted with use Dickey-Fuller Test and Augmented Dickey-Fuller Test methods. Here are the testing formulas in stasionery test:
H0 :𝛽3= 0, then there is a unit root so that the data is not stationary.
H1 :𝛽3≠ 0, there is no unit root so the data is stationary.
Based on this hypothesis, the criteria used in this test are:
a. If the ADF statistic < critical test value, reject H0 and accept H1, which means that the time series data egg chicken race price at the producer and consumer level is the root unit is stationary.
b. If the ADF statistic > critical test value, then accept H0 and reject H1, which means that the time series data egg chicken race price at the producer and consumer level is the root unit that is not stationary.
ii. The Heteroscedasticity Test and ARCH Effect
Heteroscedasticity test was conducted to determine the existence of different variants of the
residuals of all observed data. If the test results show the existence of heteroscedasticity, the data indicates the presence of an ARCH effect. The ARCH- GARCH approach can be applied to perform a volatility analysis if the data does not meet the assumption of homoscedasticity, or it can be interpreted that there is heteroscedasticity in the data (Nugrahapsari & Arsanti, 2019). The hypotheses in this test are as follows:
H0: if the probability value of F statistic is greater than the significance level of 0.05, then the data is homoscedastic.
H1: if the probability value of F statistic is less than the significance level of 0.05, then the data is heteroscedasticity.
Based on this hypothesis, the criteria used in this test are:
a. If the prob > significant value (0.05), then accept H0 and reject H1, which means that then there is no ARCH Effect on the data.
b. b. If prob < significant value (0.05), then reject H0 and accept H1, which means there is an ARCH effect on the data.
iii. Price Volatility Analysis
Stages this is Step final in the determination of the ARCH-GARCH model. Test volatility price egg chicken race on level producers and consumers with use method analysis in the form of the ARCH- GARCH model. The shape of the ARCH-GARCH model equation used according to Engle et al , in (Minot, 2014) is as follows :
1. σ2𝑝𝑝𝑡= 𝛼0+ 𝛼1𝜀2𝑝𝑝𝑡−1+ 𝛽1𝜎2𝑝𝑝𝑡−1+𝑢𝑡 2. σ2𝑐𝑝𝑡= 𝛼0+ 𝛼1𝜀2𝑐𝑝𝑡−1+ 𝛽1𝜎2𝑐𝑝𝑡−1+𝑢𝑡
Where:
σ2𝑝𝑝𝑡: Square of price residual producer egg chicken race period to t,
σ2𝑐𝑝𝑡: Square of price residual consumer egg chicken race period to t,
𝛼0: Constant,
ε2𝑝𝑝𝑡−1: ARCH rate volatility price producer egg chicken race in period previously,
𝛼1: Coefficient ARCH estimate, 𝛽1: Coefficient GARCH estimate,
𝜎2𝑝𝑝𝑡−1: GARCH term variance of price residuals producer egg chicken race period previously, ε2𝑐𝑝𝑡−1 : ARCH rate volatility price consumer egg chicken race in period previously,
𝜎2𝑝𝑝𝑡−1: GARCH term variance residual period previously,
𝑢𝑡: Error term factor in period to t.
Based on the model used , the number of from coefficient 𝛼1+ 𝛽1 on each model describe level volatility , where is ARCH value while is GARCH value . As for the criteria from level volatility is as following :
1. If 𝛼1+ 𝛽1< 1, indicates a low volatility 2. If 𝛼1+ 𝛽1= 1, indicates a high volatility 3. If 𝛼1+ 𝛽1> 1, indicates a extremely high
Volatility price food could measured at the level manufacturer, wholesaler, or retail . In study this used price egg chicken race leveled producers and consumers for see stability from egg data chicken race . Meanwhile, data instability can measured on a scale different times, using price data daily, monthly, or yearly. Study this using weekly data price producers and consumers egg chicken race by national.
RESULT AND DISCUSSION
a. Egg Price Development Chicken in Indonesia Development price egg chicken race in level consumers per year the period 2018-2022 fluctuates and tends increase. Price data consumer year 2018 to with 2022 was obtained from Sistem Informasi Pasar Online Nasional-Ternak (SIMPONI-Ternak). Same thing with development price manufacturer showing price egg chicken race fluctuate and tend increase from 2018 to 2022. Period the year 2018-2022 shows that price highest level producer is of Rp.23,127 and the price consumer amounting to Rp. 25,301.
development price egg chicken race in level producers and consumers could seen in the Figure 1.
Figure 1. Development of Producer and Consumer Prices of Chicken Eggs 2017-2022 Source: Secondary Data Analysis (2022)
b. Egg Chicken Race Price Volatility in Indonesia Before and During COVID-19 Pandemic
The results of the volatility analysis of egg chicken race producers and consumers before and during COVID-19 using a modelling approach ARCH/GARCH are as follows:
a. Stationarity test
The stasionary test using ADF test show that the price of egg chicken race at producer and consumer level before COVID-19 pandemic are stasionery at the current first differences. While at the producer during pandemic is stasionery at the current level, whereas at consumer level is stasionery at second differences.
Table 1. Stasionery test of egg chicken race at producers and consumers level Variable Stats Level.
ADF Without Trend ADF With Trend Test
Critical Value
ADF Test
Stats. Prob.
Test Critical
Value
ADF Test
Stats. Prob.
Condition before COVID-19 pandemic Producer Price
First differences
-3,495
-17,332 0.000
-4,050
-17,274 0.041
-2,890 -3.454
-2.582 -3.153
Consumer Price
-3,494
-11,402 0.000
-4,049
-11,347 0
-2.889 -3.454
-2.582 -3,152
Condition During COVID-19 pandemic Producer Price Level
-3,494
-6,825 0
-4,049
-7.056 0
-2.889 -3.454
-2.582 -3,152
Consumer Price
Second differences
-3,502
-7.013 0
-4,059
-7.005 0.016
-2.893 -3,458
-2.584 -3,155
Source : Secondary Data Analysis (2022) Description :
*** : value critical 10%
** : value critical 5%
* : value critical 1%
b. Heteroscedasticity Test and ARCH Effect Test heteroscedasticity conducted for knowing the existence of ARCH Effect on the data used. If indicated existence problem heteroscedasticity, then required ARCH/GARCH approach to analyze volatility price egg chicken
The results of Table 2 show that score obtained probability less than the significance level of 0.05 shows that the model have problem heteroscedasticity or there is the ARCH Effect. So that must conducted ARCH/GARCH analysis for knowing big volatility price egg chicken race in level producers and consumers.
18264 Rp20,006 Rp20,516 Rp23,127 Rp21,195 Rp22,096 21043 Rp22,815 Rp23,969 Rp25,301 Rp24,255 Rp24,411
0 5000 10000 15000 20000 25000 30000
2017 2018 2019 2020 2021 2022
Average Price of Chicken Eggs/Year (Rp)
Year
Development of Producer and Consumer Prices of Chicken Eggs 2017- 2022
Producer price consumer price
Table 2. Heteroscedasticity Test Results : ARCH Effect Producer and Consumer Price Data Egg Chicken Race
Variable ARCH Effect Sign
Level
Condition before COVID-19 pandemic
Producer Price F-statistics 8.84938 Prob. F( 1.101) 0.0037
5%
Obs *R-squared 8.2976 Prob. Chi -Square( 1)the 0.004 Consumer
Price
F-statistics 18,48374 Prob. F( 1.101) 0
Obs *R-squared 15,93376 Prob. Chi -Square( 1) 0.0001 Condition During COVID-19 pandemic
Producer Price F-statistics 12.81329 Prob. F( 1.102) 0.0005 obs *R-squared 11.60652 Prob. Chi -Square( 1) 0.0007 Consumer
Price
F-statistics 1,381,410 Prob. F( 1,100) 0.0003
Obs *R-squared 1,238,017 Prob. Chi -Square( 1) 0.0004 Source : Secondary Data Analysis (2022)
c. ARCH/GARCH Analysis of Producer and Consumer Price Data
ARCH/GARCH analysis was performed with simulation modeling use some of the most significant orders. In accordance with statement (Sumaryanto, 2016) that required several times
trial ARCH/GARCH form for could obtain the estimated parameters that meet condition model suitability. ARCH/GARCH model estimation is carried out start of simple order i.e. 1.0 to the highest order of 2.1.
Table 3. ARCH/GARCH Analysis of Producer and Consumer Price Data
Data Model Variable Coefficient Probability Information Before COVID-19 condition
Producer
price GARCH(3,2)
C 1244212. 0.0000
Significant
RESID( -1)^2 0.984318 0.0000
RESID( -2)^2 0.215031 0.0000
RESID( -3)^2 0.964895 0.0000
GARCH( -1) -0.219209 0.0000
GARCH( -2) -0.993681 0.0000
Consumer
Price GARCH(1,2)
C 63950.05 0.0156
Significant
RESID( -1)^2 0.398723 0.0000
GARCH( -1) -0.147331 0.0000
GARCH( -2) 0.671076 0.0000
During COVID-19 pandemic condition Producer
Price GARCH(1,2)
C 5904753. 0.0000
Significant
RESID( -1)^2 0.208833 0.0000
GARCH( -1) 0.428670 0.0004
GARCH( -2) -0.112443 0.0008
Consumer
Price GARCH (1,0) C 346727.5 0.0126
Significant
RESID( -1)^2 14.34703 0.000
Source: Secondary Data Analysis (2022)
Based on the best model trial results that have been used obtained for price data producers, model (3,2) is the best model in ARCH/GARCH because show significant at the 0.05 level. Likewise with price at consumer level, it is found that the model (1,2) is the best model shown with more probability value less than the significance level of 0.05.
d. Egg Chicken Race Price Volatility at Producer and Consumer Level
Based on results analysis that has been carried out at the previously obtained equality volatility price egg chicken race at producer and consumer level as follows:
Table 4. Egg Price Volatility Broilers at Producer and Consumer Level VOLATILITY ANALYSIS
Variable C Equality Results Note .
Condition before COVID-19 pandemic
Producer Price (1.1)
C 1244212
^2 pp=1244212+ 0.984 ^2 _(ppt-1)-
0,219 ^ 2 _ ( ppt- 1 )+ u t 0.765 Low Volatility RESID( -1)^2 0.984
RESID( -2)^2 0.215 RESID( -3)^2 0.965 GARCH( -1) -0.219 GARCH( -2) -0.994 Consumer
Prices (1,2)
C 63950.05
^2 cp=639500.05+0.399 ^ 2 -0.147 ^ 2 _ (cpt- 1 )+ u t
0.251 Low Volatility RESID( -1)^2 0.399
GARCH( -1) -0.147 GARCH( -2) 0.671 Condition During COVID-19 pandemic
Producer Price (1,2)
C 5904753
cp =5904753+0,209 ^ 2 _(ppt- 1 )+
0.429 ^2 _ ( ppt-1)+ u t 0.638 Low Volatility RESID( -1)^2 0.209
GARCH( -1) 0.429 GARCH( -2) -0.112 Consumer
Price (1.0)
C 346727.5 ^2 cp=346727.5+14,347 ^ 2 _(ppt- 1
)+ u t 14,347 Extreme
Volatility RESID( -1)^2 14,347
Source: Secondary Data Analysis (2022)
Based on Table 4 is obtained volatility price egg chicken race at level producer as well as at the level consumer could obtained from summation score ARCH coefficient with GARCH coefficient. As explained in the volatility method that when coefficient 𝛼1+ 𝛽1< 1 will categorized as low volatility, 𝛼1+ 𝛽1= 1 will categorized as a high volatility and also 𝛼1+ 𝛽1>
1 will indicates a extremely high. Based on the Table 4 show the producers level before and during COVID-19 pandemic have a low volatility.
It means risks and uncertainties faced producer in to do production egg chicken race relatively low.
This thing in accordance with study who guessed that volatility price producer is at level volatility low which is affected by the occurrence of volatility low production so that cause price producer low (Baladina et al., 2021). The next result show that price volatility at consumer level before COVID-19 pandemic has a low volatility had different from the conditions during the COVID-19 that showed with Extreme Volatility category. This thing show going up and down price by sharp on the price at the level consumer during COVID-19. Studies conducted by (Nwoko et al., 2016) happening increase price food when COVID-19 is caused by high price ingredient burn oil because existence restrictions mobility source power.
CONCLUSSION
The study analyzed the volatility egg chicken race in Indonesia before and during the COVID-19 pandemic in Indonesia. The study used weekly egg chicken race price data at the producers and consumers level from March 2018- March 2022. . However, it was carried out distinction period time analysis based on the appearance case the COVID-19 pandemic is before and during COVID-19 pandemic. The period time used before COVID-19 pandemic was carried out from March 2018 until March 2020 whereas the period time during pandemic was conducted form March 2020 until March 2022.
The secondary data was obtained through Sistem Informasi Pasar Online Nasional-Ternak (SIMPONI-Ternak) by the ministry of the Agriculture Republic of Indonesia. The analytical methods used in this study were Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and autoregressive conditionally heteroscedastic approach (ARCH). The findings showed that the price of egg chicken race at producers and consumers level before the COVID- 19 pandemic is categorized as a low volatility category and also at producer level during COVID-19 pandemics, while at the consumer level during COVID-19 pandemic is classified as high volatility category. It is caused by high price
ingredient burn oil because existence restrictions mobility source power during COVID-19. Finding from study this beneficial for designing policy related with intervention help food egg chicken race to consumer During case the COVID-19 pandemic that tends to no stable.
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