Staple Food Prices Research Articles

ANALISIS HARGA PANGAN POKOK TERHADAP KETAHANAN PANGAN DI INDONESIA

Food security ensures that sufficient, high-quality food is accessible to everyone for optimal consumption. Rising food prices can severely impact food security, especially for economically vulnerable groups. This research investigates the relationship between staple food prices and food security in Indonesia, focusing on factors like rice energy intake, egg protein intake, Gross Regional Domestic Product (GRDP) per capita, and regional conditions on Java, Bali, and other islands. Data from all Indonesian provinces for 2018-2020 is analyzed using the Ordinary Least Squares (OLS) regression method. The Food Security Index (IKP) comes from the National Food Agency’s Food Security Index Book, and food price data is sourced from the National Strategic Food Price Information Center (PIHPS). Control data such as GRDP per capita is from the Central Statistics Agency (BPS), while rice energy and egg protein intake data are from the Ministry of Agriculture’s Food Consumption Directory. The analysis reveals that rising rice prices from 2018 to 2020 significantly negatively affected food security. The study recommends evaluating rice price policies to maintain stability and enhance food accessibility. Similar evaluations for egg prices are also suggested to ensure protein availability for the community.

Hierarchical Analysis of Foodstuffs and Housing in the Formation of the Final CPI After the Covid Pandemic -19 Early 2019-2021 in Ternate City

The review of the study on Edibles and Ownership of very expensive housing will be felt with the continuous high increase in general prices which results in the price of goods that are increasingly scarce in the market, these expensive all the imbalance of demand and supply does not become constant. The economy is currently spinning during the covid-19 pandemic, Social Limitations are the main cause while on the other hand, health is very important when hit by the covid-19 attack. All economic and health joints become sook (stagnant) in the sense that everyone needs rest. However, everyone also needs food, so everyone needs a job to earn income which leads to social welfare, food and board. The city of Ternate is Ternate is currently facing the challenges of high food staple prices and a strong demand for housing, which have made market conditions increasingly unstable. This situation necessitates balanced, measurable policies from all stakeholders in both the short and medium term to stabilize staple food prices. The city also grapples with complex issues such as high transportation costs and long distribution lines, all of which demand effective solutions to control prices and ensure market stability.

The Impact of the Covid-19 Pandemic on Staple Food Prices in Medan

The Impact of the Covid-19 Pandemic on Staple Food Prices in Medan

Carbon dioxide removal and net zero emissions in Africa: an integrated assessment modelling based on three different land-based negative emission solutions

Abstract As the remaining carbon budget for limiting warming to 1.5 °C rapidly diminishes, it is clear that, besides decarbonization, the world will need to remove 100–1000 GtCO2 from the atmosphere by the end of the century. Yet, Africa, where many carbon removal schemes are planned, remains a ‘blindspot’ in existing studies. There is limited understanding of the trade-offs and synergies associated with carbon removal within Africa’s energy-land-water system. To address this research gap, we model a stylized net-zero emissions (NZEs) in Africa by 2050, with focus on three land-based biological carbon removal approaches: afforestation/reforestation (AR), bioenergy with carbon capture and storage (BECCS), and biochar. We find that by 2050, the total gross carbon removal is projected to reach 1.2 GtCO2 yr−1 when all three carbon removal approaches are available, and 0.5 GtCO2 yr−1 when Africa relies solely on AR. Pursuing NZE with only AR or AR alongside biochar in Africa would be the most expensive mitigation option but they lead to the lowest residual fossil fuel and industry CO2 emissions. An NZE by 2050 in Africa could reduce cropland by 30%–40% from 2020 to 2050, depending on the carbon dioxide removal deployment strategy adopted. Southern Africa would be particularly affected, facing significant challenges in balancing food security with climate goals. The highest increase in staple food prices will occur under AR only, while the availability of AR-BECCS-biochar produces the lowest rise in staple food prices. Our findings highlight the need for balanced and region-specific carbon dioxide removal strategies to ensure climate and other sustainability goals are met.

Optimizing yard space for independent food security in Kebonbatur Village

Amidst economic hardships and rising staple food prices, the majority of residents in RT 01 RW III of Kebonbatur Village, Mranggen District, Demak Regency, who work as laborers and farmers, struggle to meet their daily food needs. This community service program aimed to optimize limited yard space by introducing urban farming using the BUDIKDAMBER system (fish and vegetable cultivation in buckets). The training covered equipment preparation, fish distribution techniques, feeding, water quality maintenance, fish harvesting, and vegetable planting using aquaponics methods. Intensive mentoring was provided to ensure practical implementation of the acquired knowledge. The residents' enthusiasm was remarkable, as they immediately applied the learnings in their respective yards. This activity successfully raised awareness and skills among residents in utilizing limited space for self-reliant food security, as evidenced by active participation, satisfaction with harvest results, and the opening of economic opportunities.

Price Prediction of Staples with Simultaneous Fourier Series Estimator as a Contribution to Solve the National Food Problem

This study provides an overview related to the prediction of prices for staples that are widely consumed by the Indonesian people and often experience price fluctuations at certain times, namely cooking oil, chili, and chicken eggs. Based on the Market Monitoring System and Staples of the Ministry of Trade, the national average price of cooking oil as of January 3, 2022, reached USD 1.17per liter. The average price of chicken eggs reached USD 1,98 per kilogram, an increase of 20.16% at the same time. In addition, based on the National Strategic Food Price Information Center, the average price of chili in traditional markets throughout the province rose by USD 0.19 or about 3.16% and reached USD 6.29 per kilogram. The prediction of staple food prices in this study was formed using a nonparametric regression model of the Fourier series estimator. This regression model has high flexibility in forming the model and estimating the fluctuation data pattern, which is not known in the form of time-series data. The data in this study is sourced from the National Strategic Food Price Information Center website with the response variables used being the daily prices of cooking oil, chicken eggs, and chili from September 1, 2021, to December 31, 2021, as training data. In addition, the same commodity data from January 1, 2022, to January 10, 2022, is used as testing data. The best model from the estimation results with the Fourier series is a model with an oscillation parameter of 25 which contains a sine cosine basis with a coefficient of determination of 83.05%and an MSE value of 1.628. The selected model also has a very good performance predicting the prices of the three staples with a MAPE value of 1.082%.

The impact of the Covid-19 pandemic on staple food prices in Semarang

Abstract Staple food must be available in sufficient quantities at affordable prices. However, the Covid-19 pandemic caused restrictions on community access and disrupted food distribution. As one of the most affected cities, Semarang is faced the threat of the rise of food prices due to the Covid-19 pandemic. This study aims to analyze the impact of the Covid-19 pandemic on staple food prices in Semarang. The focus commodities of this research are: (1) rice, (2) white sugar, (3) palm oil, (4) chicken eggs, (5) chicken meat, (6) beef. This study uses weekly time series data which is divided into two periods; the period before the Covid-19 pandemic (2018-2019) and during the Covid-19 pandemic (2020-2021). Data analysis performed using the ANOVA method; where the price difference shows the impact of the Covid-19 pandemic on food prices. Data analysis was performed using the ANOVA method; where the price difference shows the impact of the Covid-19 pandemic on food prices. The results show that the Covid-19 pandemic has a significant impact on the changes of staple food prices in Semarang for commodities: (1) rice, (2) white sugar, (3) palm oil, (4) chicken meat, and (5) beef.

Volatilitas 9 Harga Bahan Pokok di Pasar Tradisional Kota Bandung

Fluctuations in the price of basic commodities have an impact on public unrest through a decrease in purchasing power, a decrease in the agricultural sector's GDP, and inflation. The Government's role is to maintain the stability of staple food prices to control prices in the market by analyzing price fluctuation patterns and forecasting prices of staple goods in the coming period to anticipate policies taken and make plans to avoid uncontrolled price fluctuations. Using quantitative research methods with analytical descriptives it can be seen that the data patterns and staple materials are the most volatile. The variable used is time series data of 9 staple food prices which were processed using the coefficient of variation analysis method which was operated using Microsoft Excel 2013. The results of data processing concluded that the staple commodities which often experience uncontrolled price fluctuations are red chilies, bird's eye chilies, shallots, and cooking oil. The reason is because the three highest staples whose values ​​fluctuate the most are agricultural commodities which are affected by the harvest period, weather, and shelf life which cannot last long. The fluctuation pattern occurs near the fasting month before Eid and when Christmas and New Year celebrations, staple foods tend to fluctuate. While the high cooking oil commodity is due to the phenomenon of the increase in world palm oil. The appropriate policy taken by the Government is to periodically control and participate in confirming and mapping national food production areas, maintaining supply and distribution, and educating consumers about rising prices of basic commodities.

Compounding Uncertainties in Economic and Population Growth Increase Tail Risks for Relevant Outcomes Across Sectors

AbstractUnderstanding the long‐term effects of population and GDP changes requires a multisectoral and regional understanding of the coupled human‐Earth system, as the long‐term evolution of this coupled system is influenced by human decisions and the Earth system. This study investigates the impact of compounding economic and population growth uncertainties on long‐term multisectoral outcomes. We use the Global Change Analysis Model (GCAM) to explore the influence of compounding and feedback between future GDP and population growth on four key sectors: final energy consumption, water withdrawal, staple food prices, and CO2 emissions. The results show that uncertainties in GDP and population compound, resulting in a magnification of tail risks for outcomes across sectors and regions. Compounding uncertainties significantly impact metrics such as CO2 emissions and final energy consumption, particularly at the upper tail at both global and regional levels. However, the impact of staple food prices and water withdrawal depends on regional factors. Additionally, an alternative low‐carbon transition scenario could compound uncertainties and increase tail risk, particularly in staple food prices, highlighting the influence of emergent constraints on land availability and food‐energy competition for land use. The findings underscore the importance of considering and adequately accounting for compounding uncertainties in key drivers of multisectoral systems to enhance our comprehensive understanding of the complex nature of multisectoral systems. The paper provides valuable insights into the potential implications of compounding uncertainties.

Prediksi Jangka Pendek Harga Bahan Pokok Dki Jakarta Menggunakan Metode Weighted Exponential Moving Average

Weighted Exponential Moving Average (WEMA) is a new method that combines WMA and EMA, predicting data based on the future and calculating the value of the data weighting factor over time. Commodities are goods that can be sold freely in the market, one of which is staple food to meet daily needs. This study implements the WEMA method in the short-term prediction of staple food prices, with pre-processing stages using data selection and imputation to overcome missing values. Then the data is divided into training data (75%), and test data (25%), on sugar attribute data, chicken eggs, cooking oil, chicken, and beef. A mean absolute percentage error (MAPE) evaluation was carried out on training data and test data to measure prediction accuracy. The experimental and evaluation results show that accuracy depends on the range and length of the data used. The use of span 2 for both data shows the best results on all evaluated attributes; the results of the MAPE evaluation are below 10%.

The Impact of COVID-19 Policy Response on Food Prices: A Case Study in China

The COVID-19 pandemic has threatened human lives and caused an unprecedented impact on the global economy, notably on the global food system. COVID-19 itself and its policy response have severely affected food prices. This paper analyzes the short-term and long-term impacts of COVID-19 cases and policy responses (government response index (GRI), economic support index (ESI), stringency index (SI)) on food prices (Chinese cabbage price (CP), pork price (PP), flour price (FP), rice price (RP)) in China’s major food producing areas and major food selling areas through the autoregressive distribution lag error correction (ARDL-ECM) method and graphical analysis. as the purpose is to provide evidence for food security policy regulation to stabilize food prices and improve the food system’s ability to withstand similar emergencies in the future. This study finds that the short-term impact of COVID-19 policy responses on food prices is larger, while the long-term impact is smaller. The impacts of COVID-19 itself and COVID-19 policy responses on food prices vary by food type and food production and consumption region. For food type, the Chinese cabbage price was most affected by the COVID-19 policy response, followed by pork, and the staple food prices (flour price and rice price) were least affected. For regions, the Chinese cabbage price in food producing areas was more influenced by COVID-19 and the pork price in food selling areas was more influenced by COVID-19. For the single indexes, GRI and SI had uneven effects on different food prices. However, ESI had a significant positive impact on the Chinese cabbage price (CP) and pork price(PP), except in Guangdong and Hubei. Staple food prices were almost unaffected by COVID-19 confirmed cases and policy responses. Then, taking the Chinese cabbage price in Beijing, Shandong, and Hubei as an example, we find that “dynamic clearance” influenced the Chinese cabbage price in the short term, and Chinese cabbage price increased largely in the first stage. Finally, the reasons behind the research results of this paper are analyzed, and scientific suggestions are put forward for the implementation of food supply policies to ensure food price stability and food security in the face of similar pandemics in the future.

Effects of Policy Intervention on Food System Resilience to Emergency Risk Shock: Experience from China during COVID-19 Pandemic.

Achieving the goal of zero hunger within the goal of sustainable development requires improving the resilience of food systems to various types of risk shocks; food systems have shown significant vulnerability to COVID-19 outbreaks and transmission. By analyzing the impact of China's lockdown policy and food security emergency policy in 2020 on food prices during the COVID-19 pandemic, we can clarify the role of policy intervention in enhancing the resilience of the food system, which can provide guidance, using China's experience, for dealing with global food safety emergencies in the future. Firstly, we selected Beijing, Shanghai and Guangdong as food-consuming areas, and Shandong, Henan, and Hubei as food-producing areas. We also collected food security emergency policy data from the Chinese government website during the COVID-19 pandemic. Secondly, a difference-in-difference method was used to observe that Chinese cabbage and pork prices in the main food-producing areas and food-consuming areas rose more obviously after the adoption of lockdown policy, and Chinese cabbage and pork prices in the food-consuming areas increased more obviously than those in food-producing areas. However, staple food prices have not risen significantly. Thirdly, the response of four kinds of food prices to the food security emergency policy is analyzed quantitatively and graphically using the food price volatility index and food price increase rate; we observed that the response of food prices to the food security emergency policy is related to the food types and regions. For food types, the fluctuation degree and increase in Chinese cabbage and pork prices decreased significantly after the adoption of the food security emergency policy. For regions, when the food security emergency policy was adopted, the food prices in the main food-consuming areas fluctuated more obviously than those in food-producing areas. Finally, we found that the implementation of the transport policy and the joint supply emergency policy in the main producing and consuming areas has played a very significant and positive role in stabilizing food prices.

Food price volatility and socio-economic inequalities in poor food consumption status during coronavirus disease-2019 lockdown among slum and non-slum households in urban Nansana municipality, Uganda

BackgroundThis study assessed staple food price volatility, household food consumption scores (FCS), poor household food consumption status and its association with socio-economic inequalities during enforcing and partial lifting of coronavirus disease-2019 (COVID-19) lockdown restrictions in slum and non-slum households (HHs) of Nansana municipality, Uganda.MethodsRepeated cross-sectional surveys were conducted during enforcing and partial lifting of COVID-19 lockdown restrictions. A total of 205 slum and 200 non-slum HHs were selected for the study. Telephone based interviews with HH heads were used to collect data on socio-economic factors. Data for FCS was collected using the World Food Programme FCS method. Prices for staple foods were collected by face-to-face interviews with food vendors from the local market. Mean staple food price differences before COVID-19 lockdown, during enforcing, and partial lifting of lockdown was tested by Analysis of variance with repeated measures. Multivariate logistic regression analysis was used to assess the association between socio-economic variables and poor food consumption status. A statistical test was considered significant at p < 0.05.ResultsMean staple food prices were significantly higher during enforcing COVID-19 total lockdown restrictions compared to either 1 week before lockdown or partial lifting of lockdown (p < 0.05). Mean FCS for staple cereals and legumes were significantly higher in slum HHs during COVID-19 lockdown compared to when the lockdown was partially lifted (p < 0.05). In slum HHs, the prevalence of poor food consumption status was significantly higher during partial lifting (55.1%) compared to total lockdown of COVID-19 (15.1%), p < 0.05. Among slum HHs during lockdown restrictions, food aid distribution was negatively associated with poor food consumption status (AOR: 0.4, 95% CI: 0.1–0.6), whilst being a daily wage earner was positively associated with poor food consumption status (AOR: 0.5, 95% CI: 0.1–0.6). During partial lifting of COVID-19 lockdown in slum HHs, poor food consumption status was positively associated with female headed HHs (AOR: 1.2, 95%CI: 1.1–1.6), daily wage earners (AOR: 3.2, 95% CI: 2.6–3.8), unemployment (AOR: 1.9, 95% CI: 1.5–2.1) and tenants (AOR: 2.4, 95% CI: 1.8–3.5). Female headed HHs, daily wage earners and tenants were positively associated with poor food consumption status either during enforcing or partial lifting of COVID-19 lockdown restrictions in non-slum HHs.ConclusionStaple food prices increased during enforcing either the COVID-19 lockdown or partial lifting of the lockdown compared to before the lockdown. During the lockdown, food consumption improved in slum HHs that received food aid compared to those slum HHs that did not receive it. Household heads who were females, daily wage earners, unemployed, and tenants were at risk of poor food consumption status either in slum or non-slum, and therefore needed some form of food assistance either during enforcing or partial lifting of the lockdown.

Staple Food Pricing and Food Security in Ogan Ilir Regency: AHP-Based Recommendations

This study examines food security in the Ogan Ilir Regency by assessing the affordability and accessibility of staple foods based on regional price levels. Using the Participation Rural Appraisal (PRA) method for qualitative data analysis, the study further employs the Analytical Hierarchy Process (AHP) to determine priority areas for policy intervention. AHP results underscore the significance of stabilizing food supply and leveraging local resources for food availability. In terms of affordability, the pivotal roles of enhancing purchasing power and stabilizing staple food prices are highlighted. As for staple food pricing, aligning production with market demands and optimizing the food trade system chain emerge as key considerations. The study culminates in policy recommendations, suggesting strategies like boosting production capacity, increasing food reserves and imports, and ensuring a stable food supply. It also emphasizes the importance of tailoring interventions to address specific challenges faced by vulnerable rural households in Ogan Ilir. This research offers actionable insights for local government programs aimed at ameliorating food insecurity in the region.

Analysis of long-term prices of micronutrient-dense and starchy staple foods in developing countries

The continued price increase in food commodities has long been a concern to academia and policymakers because of its substantial impact on poor consumers. Existing literature has concentrated on the cost of micronutrient-dense and starchy staple foods and the price rise in different commodities. Yet, the long-term price growth of micronutrient-dense and starchy staple foods and the price growth gap between micronutrient-dense foods and starchy staple foods have not been given much attention. The paper aimed to estimate the long-term trends in prices and volatility of micronutrient-dense and starchy staples and identify factors that have sustained the growth in prices of food commodities in developing countries. We have used the autoregressive and panel autoregressive distributed lag models to analyse the trends in relative prices and the effects of income growth. The results showed that micronutrient-dense food prices in real terms grew on average by 0.03% per month more than starchy staple food prices, with the expectation of a 12% growth gap in the next 30 years. The volatility of micronutrient-dense food items exceeds starchy staple foods in most domestic markets. Also, the prices of micronutrient-dense foods were more volatile in international markets than in most developing countries. Income growth in developing countries was one of the factors that contributed to the declining relative price of micronutrient-dense food commodities. Other factors, such as the high production of staple foods and their price stabilization policies, may have caused price trends to persist. Policies that enhance price stabilization for micronutrient-dense foods, supplementation, fortification, dietary diversity, and nutrition-sensitive interventions such as biofortification may be adopted in developing countries.

COVID-19, climate shocks, and food security linkages: evidence and perceptions from smallholder farming communities in Tanzania

AbstractInsights on the indirect effects of the COVID-19 pandemic are critical for designing and implementing policies to alleviate the food security burden it may have caused, and for bolstering rural communities against similar macroeconomic shocks in the future. Yet estimating the causal effects of the pandemic is difficult due to its ubiquitous nature and entanglement with other shocks. In this descriptive study, we combine high-resolution satellite imagery to control for plot-level rainfall with household socio-economic panel data from 2014, 2016, 2019 and 2020, to differentiate the effect of the pandemic from climatic shocks on food security in Morogoro, Tanzania. We find evidence of decreased incomes, increased prices of staple foods, and increased food insecurity in 2020 relative to previous years, and link these changes to the pandemic by asking households about their perceptions of COVID-19. Respondents overwhelmingly attribute economic hardships to the pandemic, with perceived impacts differing by asset level.

Staple Food Prices in Sub-Saharan Africa: An Empirical Assessment

Staple Food Prices in Sub-Saharan Africa: An Empirical Assessment

Staple Food Price Information System in Bandar Lampung City Using JSON (Javascript Object Notation)

The price information system for Staple Food Prices is very helpful to the public by providing information on raw food prices for the Bandar Lampung markets. This information system allows the public to determine the price of food raw materials according to grouping: by product, by market and prices at a specific time. Investigation of information systems using data matrices and objects as alternative databases using JSON (JavaScript Object Notation), one of which applies information technology in the use of information systems with matrices and objects as others alternative databases. The results obtained are the monitoring of prices for the basic needs of the population to support the information system on the prices of basic foods. In general terms, how to monitor the price of community staples in support of the basic food price information system to capture the prices of basic community needs in each market. It is possible to use a database system with JSON in addition to an existing database, for example a relational database.

Market Harms and Market Benefits

Market Harms and Market Benefits

Forecasting Model of Staple Food Prices Using Support Vector Regression with Optimized Parameters

The large number of Indonesians who consume rice as their primary food makes rice price a benchmark for determining the other staple food prices. The instability of rice prices due to climate change or other uncontrollable factors makes it difficult for Indonesians to estimate the rice prices, especially for the poor. This study proposes the usage of the Improved Crow Search Algorithm (ICSA) to optimize the Support Vector Regression (SVR) parameter in building a regression model to predict the price of staple foods. The forecasting process is carried out based on time series data of 11 staples for four years. The proposed ICSA optimizes the six parameters used in the SVR to form a regression model, consisting of lambda, epsilon, sigma, learning rate, soft margin constant, and the number of iterations. Algorithm performance is measured using MAPE and NRMSE by comparing the actual price of staple foods and forecasting results to get the error rate. With this parameter optimization mechanism, the forecasting results given are good enough with a small error value, in the form of MAPE of 17.081 and NRMSE of 1.594. A MAPE value between 10 and 20 indicates that the forecasting result is acceptable, while an NRMSE value of less than 10 indicates that the forecasting accuracy is excellent. The improvised technique on Crow Search Algorithm is proven to improve the performance of Support Vector Regression in forecasting the price of staple foods.