[PDF] Top 20 Modeling and forecasting inflation in Philippines using ARIMA models
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Modeling and forecasting inflation in Philippines using ARIMA models
... of inflation are widely recognized (Fenira, 2014). Inflation is one of the central terms in macroeconomics (Enke & Mehdiyev, 2014) as it harms the stability of the acquisition power of the national ... See full document
14
Modeling and forecasting inflation in Tanzania using ARIMA models
... Controlling inflation within acceptable rates is one of the major macroeconomic policies in Tanzania (Laryea & Sumaila, ...in inflation rates and is yet to permanently secure the target average of 0 to ... See full document
12
Modeling and forecasting inflation in Lesotho using Box Jenkins ARIMA models
... studied inflation in Zimbabwe using GARCH models with a data set ranging over the period July 2009 to July 2018 and established that there is evidence of volatility persistence for Zimbabwe ’ s ... See full document
11
Modeling and forecasting inflation in Burundi using ARIMA models
... that inflation in Burundi is projected to be hovering around ...control inflation in Burundi because our forecasts indicate that it is likely to be generally around 10% over the next ...digit ... See full document
10
Evaluation of Accuracy in Identification of ARIMA Models Based on Model Selection Criteria for Inflation Forecasting with the TSClust Approach
... in ARIMA modeling is the use of model selection criteria to choose the best ARIMA ...best ARIMA models that are different so it can be difficult to choose the best model to be ...the ... See full document
5
Predicting inflation in the Kingdom of Bahrain using ARIMA models
... price inflation using Artificial Neural Network models with a data set ranging over the period March 1960 – December 2009 and established that direct forecasts are more accurate then their recursive ... See full document
11
Output Gap Estimation for Inflation Forecasting: The Case of the Philippines
... of models are assessed on an on-going basis. More importantly, models are updated or devel- oped at the instance of either the Board, senior management, or the technical ...2005, forecasting, and ... See full document
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Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models
... that inflation in Nigeria is likely to be stable (although relatively high), hovering around a general level of approximately 15% in the first half, that is between 2017 and 2021; after which it may likely rise to ... See full document
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An Empirical Investigation of Arima and Garch Models in Agricultural Price Forecasting
... (ARCH) models are used whenever there is reason to believe that, at any point in a series, the terms will have a characteristic size, or ...ARCH models assume the variance of the current error term to be a ... See full document
14
Forecasting Inflation and Economic Growth of Pakistan by Using Two Time Series Methods
... on forecasting macroeconomic variables but also investigating the performance of alternative model through out-of-sample ...following models have been considered in forecasting inflation: ... See full document
5
Modeling and Forecasting of Carbon Dioxide Emissions in Bangladesh Using Autoregressive Integrated Moving Average (ARIMA) Models
... of ARIMA ( p , d , q ) model were tried to analyze the forty-four-year data (1972 to 2015) of carbon dioxide emission and the best fitted model is accepted on the basis of minimum value of all selection criteria ... See full document
8
MODELING AND FORECASTING VOLATILITY OF PRICE INFLATION IN ETHIOPIA USING GARCH FAMILY MODELS
... Abstract: Inflation and its volatility is one of the serious macro-economic problems in every countries ...economy. Inflation in Ethiopia is not immune from volatility problem nowadays and it was vital to ... See full document
10
A Hybrid Neural Network and ARIMA Model for Energy Consumption Forecasting
... an ARIMA model was ...the ARIMA model were modeled by using a neural network ...the ARIMA model cannot detect the nonlinear structure of the energy consumption time series data, the residuals ... See full document
7
Modeling and forecasting carbon dioxide emissions in China using Autoregressive Integrated Moving Average (ARIMA) models
... 5.3361 ARIMA (1, 2, 0) 1414.292 0.86744 4490.7 95662 145180 5.4445 ARIMA (0, 2, 1) ...5.4436 ARIMA (1, 2, 2) 1414.976 0.89854 25583 96034 140310 5.509 ARIMA (1, 2, 3) ...5.5053 ARIMA ... See full document
13
Modeling and forecasting remittances in Bangladesh using the Box Jenkins ARIMA methodology
... Nigeria using annual data from 1977 to 2009 and employed the ARIMA technique and revealed that remittances into Nigeria in the coming years will grow at an average of 6% per annum with its size as a ... See full document
12
Modelling and forecasting volatile data by using ARIMA and GARCH models
... Crude oil prices are volatile time series. The prices just like any other volatile commodity have huge price swings in periods of oversupply or shortage. The crude oil prices cycle may last over several years responding ... See full document
26
Applicability of ARIMA Models in Wholesale Wheat Market of Rajasthan: An Investigation
... to forecasting is one such approach which relies on the past pattern in a time series to forecast prices in the ...univariate ARIMA models in agricultural price ...attempted forecasting of ... See full document
5
Forecasting of Air Passengers using ARIMA Modeling
... done using various machine learning ...project, ARIMA Modeling is used which is a time series forecasting method, based on machine ...done using Dickey Fuller ...stationary, ... See full document
5
Forecasting by (Arima) models Toinflation rate in Sudan
... We will use the data set from the annual reports of the Central Bank of Sudan during the study period for our time series analysis. In this section, we will examine stationary series of Inflation Rate by unit root ... See full document
5
Forecasting of Sudan Inflation Rates using ARIMA Model
... The rest of this research is organized as follows. Section (2) briefly reviews the literature, while Section (3) discusses the data and methodology. The results and conclusion remarks are given in Sections (4 and 5) ... See full document
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