scholarly journals MODELING AND FORECASTING GDP AT CURRENT MARKET PRICE IN BANGLADESH: AN APPLICATION OF ARIMA MODEL.

2017 ◽  
Vol 5 (2) ◽  
pp. 1223-1232
Author(s):  
Biplab Biswas ◽  
◽  
Md. Wahiduzzaman. ◽  
Keyword(s):  
Arima Model ◽  
Market Price ◽  
Modeling And Forecasting ◽  
Current Market Price

scholarly journals Studying monthly rainfall over Dibrugarh, Assam: Use of SARIMA approach

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 349-356
Author(s):  
J. HAZARIKA ◽  
B. PATHAK ◽  
A. N. PATOWARY
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
Demand Management ◽  
Arima Model ◽  
Monthly Rainfall ◽  
Series Data ◽  
Data Set ◽  
Modeling And Forecasting ◽  
Moving Average Model

Perceptive the rainfall pattern is tough for the solution of several regional environmental issues of water resources management, with implications for agriculture, climate change, and natural calamity such as floods and droughts. Statistical computing, modeling and forecasting data are key instruments for studying these patterns. The study of time series analysis and forecasting has become a major tool in different applications in hydrology and environmental fields. Among the most effective approaches for analyzing time series data is the ARIMA (Autoregressive Integrated Moving Average) model introduced by Box and Jenkins. In this study, an attempt has been made to use Box-Jenkins methodology to build ARIMA model for monthly rainfall data taken from Dibrugarh for the period of 1980- 2014 with a total of 420 points.  We investigated and found that ARIMA (0, 0, 0) (0, 1, 1)12 model is suitable for the given data set. As such this model can be used to forecast the pattern of monthly rainfall for the upcoming years, which can help the decision makers to establish priorities in terms of agricultural, flood, water demand management etc.  

scholarly journals MODELING AND FORECASTING OF INDIA’S DEFENSE EXPENDITURES USING BOX-JENKINS ARIMA MODEL

2021 ◽  
Vol 9 (2) ◽  
pp. 334-344
Author(s):  
Sapana Sharma ◽  
Sanju Karol
Keyword(s):  
Arima Model ◽  
Annual Data ◽  
Policy Makers ◽  
Rational Decision Making ◽  
Defense Expenditure ◽  
Forecasting Method ◽  
Modeling And Forecasting ◽  
One Step ◽  
The Government ◽  
The One

Many developed and developing countries are at the core of the security and peace agenda concerning rising defense expenditure and its enduring sustainability. The unremitting upsurge in defense expenditure pressurizes the government to rationally manage the resources so as to provide security and peace services in the most efficient, effective and equitable way. It is necessary to forecast the defense expenditure in India which leads the policy makers to execute reforms in order to detract burdens on these resources, as well as introduce appropriate plan strategies on the basis of rational decision making for the issues that may arise. The purpose of this study is to investigate the appropriate type of model based on the Box–Jenkins methodology to forecast defense expenditure in India. The present study applies the one-step ahead forecasting method for annual data over the period 1961 to 2020. The results show that ARIMA (1,1,1) model with static forecasting being the most appropriate to forecast the India’s defense expenditure.

DOI: https://doi.org/10.36873/ae , Frits Fahridws Damanik

2020 ◽  
Vol 13 (02) ◽  
pp. 1-8
Author(s):  
Agrienvi
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Arima Model ◽  
Series Data ◽  
Production Data ◽  
Policy Makers ◽  
Strategic Value ◽  
Modeling And Forecasting ◽  
The Mean ◽  
Arima Modeling

ABSTRACTChili is one of the leading commodities of vegetables which has strategic value at national and regional levels.An unexpected increase in chili prices often results a surge of inflation and economic turmoil. Study and modeling ofchili production are needed as a planning and evaluation material for policy makers. One of the most frequently usedmethods in modeling and forecasting time series data is Autoregressive Integrated Moving Avarage (ARIMA). Theresults of ARIMA modeling on chili production data found that the data were unstationer conditions of the mean so thatmust differenced while the data on the production of small chilli carried out the stages of data transformation anddifferencing due to the unstationer of data on variants and the mean. The best ARIMA model that can be applied basedon the smallest AIC and MSE criteria for data on the amount of chili and small chilli production in Central KalimantanProvince is ARIMA (3,1,0).Keywords: modeling of chilli, forecasting of chilli, Autoregresive Integrated Moving Avarage, ARIMA, Box-Jenkins.

Decision Support System for Enhancing Crop Productivity

2020 ◽  
Vol 17 (9) ◽  
pp. 4438-4441
Author(s):  
Meeradevi ◽  
Monica R. Mundada ◽  
Hrishikesh Salpekar
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Decision Support ◽  
Neural Network Model ◽  
Arima Model ◽  
Market Price ◽  
Crop Productivity ◽  
Market Prices ◽  
The People ◽  
The Neural Network

Agriculture is the important aspect for the people of India. The life of large percentage of people in India is dependent on agriculture. The farmers are facing difficulty in selling their product to the markets due to lack of knowledge on crop prices. The market prices changes drastically in time. Using neural networks market price can be predicted and made available to the farmers to decide the time to sell their product. The ARIMA model is used to forecast the prices which can help the farmers to improve their economy and also the crop yield is predicted using neural network in the proposed system. So, that the user can check the yield of the crop in the particular piece of land before sowing. The prediction using the neural network model results in deciding the time to sell the prices and what will be the production of the crop over the year.

scholarly journals Engineering economic analysis of meliponiculture in Malaysia considering current market price

2017 ◽  
Vol 131 ◽  
pp. 04005 ◽  
Author(s):  
Firdaus Basrawi ◽  
Asnul Hadi Ahmad ◽  
Daing Mohamad Nafiz Daing Idris ◽  
Mohd Rashidi Maarof Maarof ◽  
MRR Chand ◽  
...  
Keyword(s):  
Economic Analysis ◽  
Market Price ◽  
Current Market Price

AHP in the Evaluation of Power Enterprise Assets

2012 ◽  
Vol 457-458 ◽  
pp. 1052-1055
Author(s):  
Cui Fang Yu
Keyword(s):  
Market Price ◽  
Response Relationship ◽  
Trading Behavior ◽  
Asset Valuation ◽  
Constructed Response ◽  
Ahp Model ◽  
Power Enterprise ◽  
The Individual ◽  
Timber Market ◽  
Current Market Price

The Power Enterprise asset valuation is usually the market price at market in the current market price down algorithm or method, as im of China's timber market, trading behavior is not very standardized, resulting in the use of market price of Evaluating the value out of Power Enterprise asset valuation, can not be objective and realistic response to the full value of Power Enterprise assets. This article will introduce AHP Power Enterprise asset valuation, the price of power species, Power Enterprise by constructing the AHP model, constructed response relationship between the various levels of indicators to determine the weight matrix to determine the lowest level of index membership, the calculation method to determine the individual materials species, the average price of a Power Enterprise assets, significantly improving the effectiveness and reliability of assessment.

scholarly journals Modeling and Forecasting of Covid-19 Growth Curve in India

2020 ◽  
Author(s):  
Vikas Kumar Sharma ◽  
Unnati Nigam
Keyword(s):  
Akaike Information Criterion ◽  
Regression Models ◽  
Arima Model ◽  
Information Criterion ◽  
Exponential Smoothing ◽  
Modeling And Forecasting ◽  
Best Fitting ◽  
Auto Regressive ◽  
Fitting Model ◽  
Optimal Change

AbstractIn this article, we analyze the growth pattern of Covid-19 pandemic in India from March 4th to May 15th using regression analysis (exponential and polynomial), auto-regressive integrated moving averages (ARIMA) model as well as exponential smoothing and Holt-Winters models. We found that the growth of Covid-19 cases follows a power regime of (t2, t,..) after the exponential growth. We found the optimal change points from where the Covid-19 cases shift their course of growth from exponential to quadratic and then from quadratic to linear. We have also found the best fitted regression models using the various criteria such as significant p-values, coefficients of determination and ANOVA etc. Further, we search the best fitting ARIMA model for the data using the AIC (Akaike Information Criterion) and CAIC (Consistent Akaike Information Criterion) and provide the forecast of Covid-19 cases for future days. We also use usual exponential smoothing and Holt-Winters models for forecasting purpose. We further found that the ARIMA (2,2,0) model is the best-fitting model for Covid-19 cases in India.

scholarly journals Modeling and Forecasting Under-Five Mortality Rate in Nigeria using Auto-Regressive Integrated Moving Average Approach

2020 ◽  
pp. 347-360 ◽  
Author(s):  
Donalben Onome Eke ◽  
Friday Ewere
Keyword(s):  
Moving Average ◽  
Arima Model ◽  
Childhood Mortality ◽  
Live Births ◽  
Under Five ◽  
Child Deaths ◽  
Mortality Estimate ◽  
Modeling And Forecasting ◽  
Auto Regressive ◽  
Using Data

Nigeria’s efforts aimed at reducing avoidable child deaths have been met with gradual and sustained progress. Despite the decline in childhood mortality in Nigeria in the last two decades, its prevalence still remain high in comparison to the global standard of mortality for children under the age of five which stands at 25 deaths per 1000 live births. Knowledge of the chances of Nigeria achieving this goal for childhood mortality will aid proper interventions needed to reduce the occurrence. Therefore, this paper employed the Auto-Regressive Integrated Moving Average (ARIMA) model for time series analysis to make forecast of under-five mortality in Nigeria up to 2030 using data obtained from the United Nation’s Inter Agency Group for Childhood Mortality Estimate (UN-IGME). The ARIMA (2, 1, 1) model predicted a reduction of up to 37.3% by 2030 at 95% confidence interval. Results from the study also showed that a reduction of over 300% in under-five mortality is required for Nigeria to be able to achieve the SDG goal for under-five mortality.

The Welfare Impacts of Bird Damage and Its Control in California Wine Grape Production

2014 ◽  
Vol 9 (2) ◽  
pp. 153-170 ◽  
Author(s):  
A. Anderson ◽  
C. A. Lindell ◽  
W. F. Siemer ◽  
S. A. Shwiff
Keyword(s):  
Market Price ◽  
Consumer Surplus ◽  
Wine Grape ◽  
Welfare Impacts ◽  
Pest Damage ◽  
Partial Equilibrium Model ◽  
Bird Damage ◽  
The Cost ◽  
Current Market Price ◽  
And Control

AbstractWe developed a partial equilibrium model to examine the welfare impacts of bird damage and its control in California wine grape production. The model incorporates the impacts of pest damage and its control and allows the impacts to vary regionally. Importantly, the model requires minimal information to apply; only elasticities, current market price and production data, and information on the cost and effectiveness of the pest control methods are needed. We rely on data from a recent survey of California growers and use the model to estimate changes in wine grape prices, production levels, and consumer and producer surplus that result from both bird damage and its control in three grape-growing regions of California. Results suggest that eliminating the threat of bird damage and control costs results in an increase in producer and consumer surplus of 1.3% and 3%, respectively. Furthermore, eliminating current bird control and allowing any resulting damage would decrease producer and consumer surplus by 6.6% and 11.5%, respectively. (JEL Classifications: Q11, Q18, Q57)

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