Sugar Prices Research Articles

PERAMALAN HARGA GULA PASIR MENGGUNAKAN VARIASI KALENDER REGARIMA DENGAN MOVING HOLIDAY EFFECT (PERIODE JANUARI 2018 SAMPAI DENGAN DESEMBER 2022 DI PASAR KOTA SEMARANG)

National sugar production is decreasing day by day with the pattern of people's consumption of sugar continuing to increase, thus encouraging the government to import sugar from other countries to meet food needs. This is because the import of granulated sugar causes the price of local granulated sugar to fluctuate which can rise up to 2 times the highest retail price. Eid al-Fitr is determined based on the Islamic calendar, this will cause a shift in the date each year on the Maseh calendar, the date of the celebration of Eid al-Fitr which moves from year to year is known as the "moving holiday effect". One of the calendar variation models used to eliminate the Holiday Effect Transfer and has a simple processing flow is the RegARIMA model. The RegARIMA model method is a modeling technique that combines the ARIMA model with the regression model. In the regression model, the weight matrix is used as the independent variable and the price of granulated sugar is used as the dependent variable. The weight value is obtained based on the number of days that affect Eid, which is 14 days. Based on an analysis of the price of granulated sugar in the Semarang City market for the period January 2018 to December 2022, the best model is obtained, namely SARIMA (1,0,0)12 with the smallest AIC value and the sMAPE value obtained from forecasting data for 2021 is of 19.04%, which means that the forecasting is still at a reasonable level.

Examining the Relationship Between the Gasoline A Market and the Prices of Hydrous Ethanol and Sugar to the Producer in Brazil

Examining the Relationship Between the Gasoline A Market and the Prices of Hydrous Ethanol and Sugar to the Producer in Brazil

Economic validation and comparison of microbial tryptophan, erythritol and collagen production in an integrated sugarcane biorefinery

Low sugar prices present a significant challenge to the global sugarcane industry, prompting the exploration of diversification strategies for expanding product portfolios. Techno-economic analyses and environmental sustainability assessments were carried out to evaluate the microbial production of tryptophan, erythritol, and collagen from A-molasses in a biorefinery annexed to an existing sugarcane mill. Tryptophan production exhibited the highest profitability, with a minimum selling price (MSP) at 59.7 % of its current market price, although the achievable production volumes of tryptophan from one sugar mill would oversupply the global market. Due to the larger market size of for collagen the achievable production capacity in the collagen scenario would avoid market saturation, reducing the risk of oversupply and rendering it more economically viable. In contrast, erythritol production was marginally not profitable, with an MSP exceeding the current market price by 1 %, primarily attributed to high operational costs. All scenarios demonstrated relatively low greenhouse gas (GHG) emissions (ranging from 9.1 to 16.5 kg CO2eq/kg product), with tryptophan production emerging as the most environmentally favourable option due to minimal chemical and freshwater usage. When compared with literature-reported data on ethanol and short-chain fructooligosaccharides (scFOS), only collagen and ethanol production were deemed viable, based on their favourable profitability and contribution to the market.

A hybrid hue saturation lightness, gray level co-occurrence matrix, and k-nearest neighbour for palm-sugar classification

<span lang="EN-US">In recent years, there has been an increasing demand for high-quality raw materials driven by consumers and the food industry. This study aims to build a model to predict the type of </span><span lang="IN">palm</span><span lang="EN-US"> sugar using a hybrid method of hue</span><span lang="IN">-</span><span lang="EN-US">saturation</span><span lang="IN">-l</span><span lang="EN-US">ightness (HSL), gray level co-occurrence matrix (GLCM), and K-nearest neighbor (KNN). The price of palm sugar is determined based on the type and ingredients used. However, due to the lack of public knowledge in distinguishing the types of </span><span lang="IN">palm</span><span lang="EN-US"> sugar, there is the potential for price manipulation that can harm the community. The accuracy rate of 9</span><span lang="IN">7.6</span><span lang="EN-US">% of the palm sugar type prediction results shows that the model that was built has worked very well. The results have practical implications, such as developing automated systems to classify palm species in specific industries to benefit economics and operational efficiency. Future research directions may explore the integration of advanced machine-learning techniques and real-time image processing for further improving classification performance and scalability in industrial applications</span><span lang="IN">.</span>

The creative–destructive force of hurricanes: evidence from technological adoption in colonial Jamaican sugar estates

AbstractWhile in the early part of the nineteenth-century Jamaica was one of the world’s leading sugar producers, the abolition of slavery, the flooding of sugar markets with cheap European beet sugar, and the equalization and finally elimination of sugar import duties across the British empire led to a need for more efficient ways to produce sugar. However, it has been widely noted that Jamaica sugar estates were late in adopting more efficient production techniques, arguably due to inadequate financing. This paper investigates what role the destructive forces of hurricanes may have played in inducing Jamaica to finally modernize its sugar production. To this end, we combine a geo-referenced exhaustive data set of Jamaican sugar estates with a measure of localized hurricane damage constructed from historical hurricane tracks over the period 1882 to 1930. Our econometric analysis shows that hurricane strikes increased the probability that a surviving estate upgraded its sugar processing technology, particularly when the price of sugar was high and the price of the other main exporting crop (bananas) was low. Additionally, while a government hurricane loan programme working through local loan banks did help plantations to adopt new machinery, this depended on the damage not being too large.

Analisis Faktor-Faktor Yang Mempengaruhi Impor Gula di Indonesia Tahun 1992-2022

This research aims to determine the development of sugar imports in Indonesia and to analyze the influence of sugar production, sugar consumption, domestic sugar prices, international sugar prices, and the rupiah exchange rate on sugar imports in Indonesia in 1992-2022. This research is quantitative research and uses time series data. The data sources used were obtained from the Central Statistics Agency, Ministry of Agriculture, Ministry of Trade and several related studies. The analysis model used is development trend analysis and ECM (Error Correction Model). The results of research (1) in trend analysis in 1992-2022 obtained the equation Y = 2,317,827.5 + 174,230x showing that the average development of the volume of sugar imports was 2,317,827.5 tons and each year there was an average increase in sugar imports amounting to 174,230 tons. (2) Results of Multiple Linear Regression analysis of the ECM Model in the long term and short term. The variables that show a significant positive effect on sugar imports are domestic sugar prices and international sugar prices, while other variables such as sugar production, sugar consumption and the rupiah exchange rate show a positive effect. insignificant to sugar imports in 1992-2022.

THE EFFECT OF FOOD PRICE VOLATILITY (FPV) ON INFLATION IN PAREPARE CITY

Food price volatility often occurs and cannot be avoided, including food price volatility that occurs in Parepare City. The effect of movement or changes in food prices appears to influence inflation, which in turn becomes the purpose of this study, namely to analyze the effect of changes in food prices on inflation in Parepare City. The analysis method used is multiple linear regression analysis. The data used is secondary data in the form of monthly time series from July 2018 to June 2021. The independent variables in this study are the food prices of rice, chicken meat, red chili, chicken eggs and granulated sugar. The results showed that the food prices of rice and chicken eggs have an increasing trend while the prices of chicken meat, red chili, and granulated sugar tend to decrease. The coefficient of determination test results shows that changes in food prices simultaneously positively and significantly affect inflation. The t-statistical test shows that partially changes in food prices of rice and chicken meat have a positive and significant effect on inflation while changes in food prices of red chili, chicken eggs and granulated sugar have a positive but insignificant effect on inflation. This research has implications for public policy to develop food prices stabilization policies, such as food reserve policies, market regulations, incentives for food producers, or social assistance programs to alleviate the impact of food inflation.

Comparative Analysis of Linear Models and Artificial Neural Networks for Sugar Price Prediction

Sugar is an important commodity that is used beyond the food industry. It can be produced from sugarcane and sugar beet, depending on the region. Prices worldwide differ due to high volatility, making it difficult to estimate their forecast. Thus, the present work aims to predict the prices of kilograms of sugar from four databases: the European Union, the United States, Brazil, and the world. To achieve this, linear methods from the Box and Jenkins family were employed, together with classic and new approaches of artificial neural networks: the feedforward Multilayer Perceptron and extreme learning machines, and the recurrent proposals Elman Network, Jordan Network, and Echo State Networks considering two reservoir designs. As performance metrics, the MAE and MSE were addressed. The results indicated that the neural models were more accurate than linear ones. In addition, the MLP and the Elman networks stood out as the winners.

Exploring the potential of the carbon credit program for hedging energy prices in Brazil

The transition to a low-carbon economy is imperative to reduce reliance on fossil fuels and mitigate pollution emissions. This preposition also aligns with the United Nations Sustainable Development Goals (SDGs-13), which highlight the climate change action. In this vein, Brazil has implemented the Decarbonization Credit (CBIOS) program to incentivize biofuel production and promote environmental sustainability through carbon credit emissions. To this end, the present study evaluates the effectiveness of the CBIO contract as a hedging tool for investors in the face of energy price fluctuations and decarbonization efforts. Specifically, we employ conditional dynamic correlation (DCC-GARCH) and optimal hedge ratio (HR) techniques to assess the relationship between CBIO and the futures and spot prices of sugar, oil, and ethanol. Our findings suggest that the current CBIO contract is not an effective hedge against energy spot and future prices. However, our analysis identifies a strengthening correlation between ethanol traded in Chicago and CBIO over time, highlighting the potential for an underlying contract to serve as an effective hedging tool in the future. Our study adds to the existing literature on carbon pricing mechanisms and their impact on financial markets, emphasizing the importance of sustainable energy policies and their potential to mitigate the risks associated with energy price volatility and decarbonization efforts.

БИРЖЕВАЯ ТОРГОВЛЯ САХАРОМ В РОССИИ: СОВРЕМЕННОЕ СОСТОЯНИЕ И ВОЗМОЖНОСТИ ОБЕСПЕЧЕНИЯ МОНИТОРИНГА ВНУТРЕННИХ ЦЕН

In modern Russia, the role of organized trading, which includes exchange trading, is gradually increasing. As our research has shown, exchange trading in sugar in Russia is developing, as evidenced by the increase in exchange turnover of sales of this product and the expansion of exchange instruments used for trading. In addition, exchange trading can provide up-to-date information on domestic average market prices for commodities. A strong connection was established between average domestic Russian prices for sugar and price quotations for this product on the world’s largest commodity exchanges and on commodity exchanges within Russia. In the course of studying the cause-and-effect relationship between average domestic and average exchange prices for sugar in Russia, it was found that domestic prices are the reason for the establishment of certain exchange prices for sugar and the domestic and exchange Russian prices are very close in size. This allowed us to conclude that it is possible to use exchange trade prices for sugar as an operational information source on the size of domestic prices, which can be used for state regulation of the market and for making business decisions directly by business entities.

MARKET RESEARCH OF THE UKRAINIAN SWEETS MARKET

The article conducts a market research of the Ukrainian sweets market. The research used the capabilities of MS Excel software tools and made a forecast of exports and imports of sweets in Ukraine. It has been determined that one of the most important factors affecting the price of confectionery is the dollar exchange rate. Since its fluctuations can lead to an increase or decrease in the price of products. Correlation studies have been carried out and it has been determined that the change in the dollar exchange rate has a small impact on the price of sugar. Swing charts have been built to assess the dynamics of changes in the dollar and sugar prices for the period 2021–2024. Also, current trends in the sweets market have been identified, namely: increased demand for natural products and vegan alternatives; changing tastes, preference for exotic products; digitalization, which makes sweets look Instagrammable; online sales.

A Comprehensive Analysis of Challenges and Opportunities in Maharashtra's Private Sugar Industry

One of the most important states in India in terms of agricultural production and industrial growth, Maharashtra is also one of the most important states in terms of the sugar industry in India. It is possible to say that the private sugar industry in Maharashtra has a long and varied history, one that is characterised by a combination of old methods and contemporary innovations. The sugar industry in Maharashtra is an essential part of the rural economy of the state and has far-reaching repercussions for the farming industry on a national scale. It is also a substantial contributor to the total amount of sugar that is produced in India. This study lays the groundwork for a more in-depth examination of the potential and difficulties that characterise the private sugar business in Maharashtra during the subsequent sections. In the following sections, we will delve into the various elements that influence the sector. We will investigate how the industry navigates the complexity of the market, the dynamics of policy, and the improvements in technology in order to ensure that it maintains its position as a significant participant in India's economic landscape. The private sugar industry in Maharashtra is distinguished by the presence of a large number of sugar mills, each of which makes a contribution to the continued socioeconomic development of the region. The sector has faced numerous challenges in recent years, such as unpredictable sugar prices, weather-dependent agriculture, shifting government policies, and the need for technological developments. Despite these challenges, the sugar industry in Maharashtra offers a landscape ripe with opportunities for growth and change.

Determination of palm sugar production cost by forestry farm communities in Obo Village, Disctrict of Nuhon, Banggai Regency, Central Sulawesi

Palm Sugar is made with raw materials from sweet liquid (sap) obtained by male flowers on the sugar palm trees. It is one of the second businesses conducted by forestry farm communities in Obo village of the Nuhon subdistrict the district of Banggai and is also the development of the forest management agency sivia patuju. The purpose of this research is to set the price of sugar palm production in Obo village sub-district of Nuhon district of Banggai. This research was conducted on the forest farming group in Obo village sub-district of Nuhon District of Banggai for 2 months. It was started in January to February 2022. The techniques used in collecting sample was census methods and for data collection by using interview methods, observation, documentation and questionnaire. Based on studies conducted by the forestry group in obo village, sub-district of Nuhon district of Banggai showed that the total cost of production palm sugar was IDR 4,990,000 per month. Then the determination production cost using the variable costing method obtained the cost of production palm sugar was IDR 9,505/pc, and with the addition of the desired profit of 10%, the selling price of palm sugar becomes IDR 10,455/pc.

Evolution of sugar exports in two centuries

The research showed the trajectory of Brazilian exports and sugar prices between 1821 and 2020 (two centuries). The hypothesis of the research was that exporters' price forecasting errors affected their export forecasting errors in the period evaluated. The data were obtained from the Ministry of Development, Industry and Trade (MIDIC). Sugar prices were translated to 2020 Brazilian currency values (R$) and then to US dollars using the 2020 (R$/USD) average conversion rate. Autoregressive integrated moving average (ARIMA) models were used to forecast sugar exports and prices over the entire period. Geometric growth rates of exports and prices were estimated for each quartile using trend evaluation models. Dummy variables were used to test whether there were differences between the elasticities measuring the forecast errors of exports as a function of the forecast errors of sugar prices in each quartile. The estimated models proved to be parsimonious and robust from a statistical point of view. The hypotheses that prices and export quantities expanded at different rates in the four quartiles were confirmed and the estimated elasticities were shown to be statistically different suggesting that export forecasting errors are likely to be related to sugar price forecasts.

Estimating the unintended impact of the North American free trade agreement on U.S. public health

The North American Free Trade Agreement (NAFTA) was introduced in 1994 between Canada, Mexico, and the United States to encourage trilateral trade. In 2008, an unrestricted reciprocal sugar trade agreement, was implemented between Mexico and the United States as part of NAFTA, which led to a significant decrease in the United States’ sugar price. However, critics argue that free trade agreements that reduce trade barriers on products such as sugar threaten public health. This study uses the synthetic control method to investigate the causal impact of the unrestricted sugar trade agreement on sugar consumption and diabetes prevalence in the United States. First, we show that sugar consumption in the United States increased by an average of 16% annually after the agreement was signed, corresponding to 5240g per capita. Second, we show that the crude prevalence of diabetes increased by an average of 1% annually in the United States after the agreement was signed, with an increase of 1% and 2% for men and women, respectively. This unintended consequence of NAFTA has had an estimated economic cost of $324.37 million annually.

Forecasting Sugar Price Fluctuation In Malaysia Using Geometric Brownian Motion Modelling

A mathematical model known as Geometric Brownian motion has proven to be an effective tool that can be deployed to forecast the price of goods in the future due to the presence of random terms, which represent the stochastic or random fluctuation of prices over a given period of time. The success of this model revolves around the estimation of its governing parameters. To efficiently predict the price of goods, using the Geometric Brownian Motion model (GBM), one needs to determine the value of returns and use the calculated returns to estimate the value of drift as well as volatility. This research used the value of volatility and drift terms obtained from real data of sugar in the months under review. The method has shown to be very reliable in capturing the intelligent trend in the price of sugar in Malaysia. The model was able to stimulate the pattern of the predicted price that shares a great resemblance to the actual price of sugar. The result obtained is very encouraging and places this study with a good note now that the country is just returning to normalcy from the pandemic that has crippled the economies of most developing nations in the world. We used the model to predict the price of sugar for a period of 20 months and the result of our prediction as well as the graph of the predicted prices confirmed the practicability of the model. The obtained values of MAPE and MSE, two of the popular performance metrics, also justified the effectiveness of the GBM in capturing the trend in the data. This model can be classified as a good model that can be deployed to forecast the price of goods that exhibit high volatility.

Development of A Fuzzy Logic-Based Cost Modeling System for Sugar Industry

The objective of the study was to create a fuzzy logic-based cost modelling system for the sugar industry in order to comprehend the impacts of sugar cost determinants on total cost. The designed system takes into account variables such as fluctuating cane prices, cane weight, distribution distances, and crushing cessation. The data is collected from the cost statements of various Pakistani sugar refineries. The primary research objective was to determine the effects of the unpredictability of various cost variables on the ultimate price of sugar. The cost determinants were deemed input variables, while the cost of sugar production was considered an output variable. The cost variables were categorised as follows: cost of basic materials, cost of distribution, cost of labour, cost of operations, factory overheads, and crushing cessation (losses). The Mamdani Fuzzy Inference system was used to analyse the data. To develop the system, 729 fuzzy rules and three levels of fuzzy sets were created. The developed fuzzy logic-based system is able to evaluate the sugar cost structure and take uncertainty factors into account. Consequently, a significant contribution of the developed system is the provision of heuristic principles that facilitate the selection of cost-effective outcomes.

AN OVERVIEW ON SUGARCANE INDUSTRY IN INDIA

Sugarcane is an important industrial and cash crop. It is grown in almost in all areas in India, But commercial basis sugarcane is produced in tropical and sub tropical states. Because of available of raw materials, most of the sugar mills are located in these areas. Sugarcane production in India has been attributes to lack of rainfall, reduction in cultivation area. Also production of sugarcane affects due to drought and decrease in soil health, high level input cost. This paper presents an overview of sugar industries, state wise area of cultivation, production, productivity. This paper is descriptive in nature and completely based on the data and information available from secondary sources. Time frame of the study is ten years from 1st April, 2012 to 31st March, 2022. KEYWORDS – Production of Sugarcane, sugarcane cultivation, export & import of Sugar, fair and remunerative price of Sugar

Policy and action plan to increase national sugar production

As a national strategic commodity, sugar sufficiency has become one of the government’s priorities. However, until recently, Indonesia is still experiencing a deficit in sugar due to production and consumption gaps. This paper aims to assess the performance of national sugar production and consumption and the government’s efforts to overcome the shortage. This study used primary and secondary data. Descriptive qualitative and Grid analysis was employed, supported by a literature review from various relevant sources. The study results show that during the 2015–2020 period, national sugar consumption was higher than its production. The low national sugar production was due to (1) a decrease in sugarcane area, (2) stagnation of sugarcane yield and sugar content, (3) not optimal process of modernization and revitalization of sugar mills, and (4) policies related to trade and prices of sugarcane and sugar. Out of nine policy options to increase sugarcane yield, the use of sugarcane seedlings of high-yielding varieties has become a priority policy. An action plan is required to support such policy, i.e., structuring of variety; coordination, technical guidance, socialization, and extension; and government assistance programs, especially capital aid.

Value-Added Analysis and Affecting Factors Coconut Sugar Offers (Case Study: Coconut Sugar Maker in Manyampa Village Ujung Loe District Bulukumba Regency)

This study aimed to determine the value of processing coconut sap into coconut sugar. In Manyampa Village, Ujung Loe Subdistrict, and the factors that affect the supply of coconut sugar in Manyampa Village, Ujung Loe Subdistrict, carried out from August to December 2021. Location determination was determined intentionally. Determination of the number of samples using the saturated sampling method because the number of pieces is relatively small, amounting to 15 respondents. Variables in this research consist of respondent identity and value-added analysis of coconut sugar derived from coconut sap. This data was analyzed using value-added analysis and Multiple Linear Regression Analysis. The results showed that the added value generated from one month of making coconut sugar in the village of Manyampa, Ujung Loe sub-district, was high, with an added value ratio of >50, with a percentage of 85%. And simultaneously, the supply of coconut sugar in Manyampa Village, Ujung Loe District, is influenced by the price of raw materials and other goods. The number of producers, Partially only raw material variables, affects the supply of coconut sugar. In contrast, the price of coconut sugar, the number of producers, and the costs of other goods do not affect the supply of coconut sugar.