scholarly journals Applying the ARIMA Model to the Process of Forecasting GDP and CPI in the Jordanian Economy

2021 ◽  
Vol 12 (3) ◽  
pp. 70
Author(s):  
Abdullah Ghazo
Keyword(s):  
Time Series ◽  
Economic Policy ◽  
Gross Domestic Product ◽  
Economic Activity ◽  
Price Index ◽  
Arima Model ◽  
Consumer Price Index ◽  
Decision Makers ◽  
Domestic Product

Gross Domestic Product (GDP) and consumer price index (CPI) are significant indicators to describe and evaluate economic activity and levels of development. They are also often used by decision makers so as to plan economic policy. This paper aims at modeling and predicting GDP and CPI in Jordan. In order to achieve this goal, the study applied the Box- Jenkins (JB) methodology for the period 1976-2019. Based on the results, ARIMA (3,1,1) found to be the best model for the GDP. In addition, ARIMA (1,1,0) was the best model for forecasting the CPI. The results were supported with the findings of the stationarity and identification rules test of time series under using AIC and SIC criterion. The forecasted values of the GDP and the CPI for the next three years (2020-2022) were (29342.12, 32095.10, 35106.36 million JD) and (128.31, 133.28, 139.28) respectively. Compared with 2019, the GDP is forecasted to decrease in 2020, while the CPI is forecasted to increase in 2020. This implies that the Jordanian economy is tending toward stagflation. After 2020, both GDP and CPI increased, which indicates that Jordanian economy is tending toward cost-push inflation.

Dampak Penerapan Perbankan Syari’ah Terhadap Pertumbuhan Ekonomi Negara: Kajian Perbandingan Malaysia dan Indonesia

2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Hansen Rusliani
Keyword(s):  
Gross Domestic Product ◽  
Response Function ◽  
Price Index ◽  
Vector Autoregression ◽  
Consumer Price Index ◽  
Domestic Product

Penelitian ini bertujuan untuk mengetahui dampak perbankan syari’ah terhadap pertumbuhan ekonomi di Indonesia dan Malaysia. Data yang digunakan dalam penelitian ini merupakan data primer (interview) dan data sekunder dalam bentuk bulanan yang diperoleh dari Badan Pusat Statistik Ekonomi dan Keuangan Indonesia Bank Indonesia (SEKI-BI) dan Statistik Perbankan Syari’ah Bank Indonesia (SPS-BI) serta data dari Bank Negara Malaysia dan Departemen Statistik Malaysia dalam periode waktu kurun waktu 16 tahun, 2000 sampai dengan 2015. Observasi penelitian dilakukan di Indonesia dan Malaysia untuk memperkaya analisis. Penelitian ini menggunakan Vector Autoregression (VAR), Uji Kointegrasi serta dikombinasikan dengan Response Function (IRF) dan Decomposition (FEVD) untuk melihat interaksi antara faktor makro ekonomi dengan pembiayaan dalam jangka panjang. Adapun variabel yang digunakan adalah total pembiayan syari’ah (Total Syari’ah Financing) dan Gross Domestic Product (GDP) sebagai representasi pertumbuhan ekonomi. Untuk tambahan variabel digunakan Consumer Price Index (CPI) sebagai representasi tingkat inflasi. Hipotesis penelitian yaitu terdapat pertumbuhan ekonomi setiap tahunnya dikedua negara tersebut pasca krisis moneter.

scholarly journals Evaluación del índice económico de Colombia para el período 2020 a 2022 con redes neuronales artificiales

2020 ◽  
Vol 42 (1) ◽  
pp. 25-33
Author(s):  
Valeria Alejandra Bustamante Zuleta ◽  
Hermes Jackson Martinez Navas
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Gross Domestic Product ◽  
Price Index ◽  
Consumer Price Index ◽  
Oil Price ◽  
Domestic Product ◽  
Positive Effects ◽  
Market Rate ◽  
Macroeconomic Indicators

This article analyze some of the important macroeconomic indicators in Colombia,such as the Consumer Price Index (CPI), the Gross Domestic Product (GDP), the Representative Market Rate (TRM), the Oil Price (BRENT and WIT) and COLCAP. The objective is to study Colombia's economic.The analysis were obtained with artificial neural networks on Colombian indicators data for the period 2001 to 2018 of the National Administrative Department of Statistics (DANE) and Bloomberg. Concluding, for Colombia, the last two cases are highly favorable for the economy, because they will generate a greater influx of dollars, allowing positive effects on the domestic product and the consumer price index.

scholarly journals PERAMALAN LAJU INFLASI DENGAN METODE AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

2017 ◽  
Vol 14 (4) ◽  
pp. 524 ◽  
Author(s):  
Djawoto Djawoto
Keyword(s):  
Time Series ◽  
Price Index ◽  
Inflation Rate ◽  
Moving Average ◽  
Arima Model ◽  
Consumer Price Index ◽  
Stationary Time Series ◽  
Stationary Time ◽  
Auto Regressive ◽  
Auto Regression

Auto Regression Integrated Moving Average (ARIMA) or the combination model of Auto Regression with moving average, is a linier model which is able to represent the stationary time series or non stationary time series. The purpose of this research is to forecast the inflation rate in November 2010 with the Consumer Price Index (CPI) by using ARIMA. The inflation indicator is very important to anticipate in making the Government’s policy and decision as well as for the citizen is for the information to determine what to do in related with savings and investment. By looking at the existing criteria, it is determined that the best model is ARIMA (1,1,0) or AR (1). Model ARIMA (1,1,0), the coefficient value AR (1) is significant,which has the most minimum value of Akaike Info Criterion (AIC) and Schwars Criterion (SC) compare toARIMA (0,1,1) or MA (1) and ARIMA (1,1,1) or AR (1) MA (1). In summarize, the ARIMA model used to forecast the valueof IHK is ARIMA (1,1,0).

scholarly journals The Nexus Between Monetary Policy and Economic Growth in Pakistan: Empirical Evidence Based on Bound Test Approach

2021 ◽  
Vol 4 (3) ◽  
pp. 613-624
Author(s):  
Mahmood Ul Hassan ◽  
Hina Ali ◽  
Saeed Ur Rahman ◽  
Sabiha Parveen
Keyword(s):  
Economic Growth ◽  
Exchange Rate ◽  
Gross Domestic Product ◽  
Money Supply ◽  
Price Index ◽  
Negative Impact ◽  
Consumer Price Index ◽  
Domestic Product ◽  
Series Data ◽  
Bound Test

The objective of this research is to examine the monetary policy's impact on economic growth. Variables of study are Gross domestic product, Inflation, rate of interest, Exchange rate, Money supply, Investment, and Consumer Price Index and time series data is collected from. Gross domestic product is a dependent variable and all other variables are independent and have a great effect on the explanatory variable. In this study, the Augmented dicky fuller test is used to check out the stationarity of our selected variables and after that autoregressive distributed lag model co-integration technique is applied to estimate the parameters of the model. The result shows that inflation, interest rate, and consumer price index show a negative impact on gross domestic product. While other variables such as exchange rate, money supply, and investment show a positive impact on GDP. The study recommended that the desired level of output and employment can be attained by adopting sufficient strategies that reduce inflation in the economy.

scholarly journals PERAMALAN LAJU INFLASI DENGAN METODE AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

2018 ◽  
Vol 14 (4) ◽  
pp. 524-538
Author(s):  
Djawoto Djawoto
Keyword(s):  
Time Series ◽  
Price Index ◽  
Inflation Rate ◽  
Moving Average ◽  
Arima Model ◽  
Consumer Price Index ◽  
Stationary Time Series ◽  
Stationary Time ◽  
Auto Regressive ◽  
Auto Regression

Auto Regression Integrated Moving Average (ARIMA) or the combination model of Auto Regression with moving average, is a linier model which is able to represent the stationary time series or non stationary time series. The purpose of this research is to forecast the inflation rate in November 2010 with the Consumer Price Index (CPI) by using ARIMA. The inflation indicator is very important to anticipate in making the Government’s policy and decision as well as for the citizen is for the information to determine what to do in related with savings and investment. By looking at the existing criteria, it is determined that the best model is ARIMA (1,1,0) or AR (1). Model ARIMA (1,1,0), the coefficient value AR (1) is significant,which has the most minimum value of Akaike Info Criterion (AIC) and Schwars Criterion (SC) compare toARIMA (0,1,1) or MA (1) and ARIMA (1,1,1) or AR (1) MA (1). In summarize, the ARIMA model used to forecast the valueof IHK is ARIMA (1,1,0).

Analisis Pembiayaan Konsumtif Riil Pada Bank Syariah Di Indonesia

Liquidity ◽  
2017 ◽  
Vol 6 (1) ◽  
pp. 32-37
Author(s):  
Rizky Maulana Pribadi
Keyword(s):  
Gross Domestic Product ◽  
Price Index ◽  
Research Study ◽  
Consumer Price Index ◽  
Positive Influence ◽  
Domestic Product ◽  
The Real ◽  
Islamic Bank ◽  
Result Show

The objective of this research study is to study there is positive influence of Gross Domestic Product/GDP Real and Consumer Price Index of Financing Real, investigate the determinants of real financing consumtive at Islamic Bank in Indonesia and how the determinants change the real financing consumtive at Islamic Bank in Indonesia in period 2011-2016. The result show that the respond of Consumer Price Index/CPI, GDP Real, and it could be seen from its size which are 3.118983, 1.601941, 0.397987. From the result, it can be concluded that Real Financing Consumtive  is influenced by IHK, GDP Real, and Real Financing Consumtive.

scholarly journals INFLATION PERSISTENCE IN NORTH SUMATERA PROVINCE

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Wily Julitawaty
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Gross Domestic Product ◽  
Error Correction ◽  
Price Index ◽  
Inflation Rate ◽  
Consumer Price Index ◽  
Secondary Data ◽  
Output Growth ◽  
Domestic Product

The purpose of this study was to determine the persistence of inflation in major North Sumatera Province in 2007 until 2012 and value contributed Output Growth  (GDP) of North Sumatera, Exchange Rate, Interest Rate and Error Correction Term about Inflation in North Sumatera. Data is used secondary data from general Consumer Price Index  (CPI) from North Sumatera Province include Medan, Pematangsiantar, Sibolga and Padangsidempuan monthly of January 2007 until December 2012. And secondary data Consumer Price Index  (CPI) of North Sumatera Province, Gross Domestic Product of  Province Sumatera Utara, Exchange Rate and Interest Rate of BI Rate yearly of 1999 until 2012. Model is used model econometric with Autoregressive method and Error Correction Model. Result of this research with estimation of  VAR model concludes that degree of persistence of 4 town from North Sumatera Province is low. Result of estimation of model ECM concludes that Interest Rate significantly affect to inflation rate, while Gross Domestic Product of  North Sumatera Province and Exchange Rate not significantly affect to inflation rate. While ECT becomes significant correction to variable inflation rate. Where the form of error correction in the ECM suggests a long-term relationship between the variables inflation, GDP variable, the variable exchange rate and variable interest rate is comparable.

scholarly journals Forecasting Zambia’s Gross Domestic Product Using Time Series Autoregressive Integrated Moving Average (ARIMA) Model

2020 ◽  
Vol 5 (9) ◽  
pp. 440-447
Author(s):  
Chikumbe Evans Sankwa ◽  
Sikota Sharper
Keyword(s):  
Time Series ◽  
Gross Domestic Product ◽  
Moving Average ◽  
Social Indicators ◽  
Arima Model ◽  
Information Criteria ◽  
Domestic Product ◽  
Data Set ◽  
Autoregressive Integrated Moving Average ◽  
Study Results

Gross Domestic Product is one of the social indicators of development. This study attempts to model Zambia’s Gross domestic product using the Autoregressive Integrated Moving Average (ARIMA) model. This model has proved to help many countries during economic recession or when there is any disruption in the economic system due to pandemics or natural disasters. The study utilized a time series dataset from 1960 to 2018. The best model that fit the data set, following the selection model criteria, was ARIMA (5,2,0) model with the lowest Akaike’s Information Criteria(AIC) and Bayesian Information Criteria (BIC) and smallest volatility. The study results showed that, on average, Zambia’s gross domestic product will continue to rise over the next eight years. However, few recession (decline) points are expected in the period 2020 to 2022. It is hoped that the forecasts would be useful for researchers in Zambia, including the fiscal and monetary policy makers.

scholarly journals GDP AS A FACTOR INFLUENCING THE SOCIAL INDICATORS OF UKRAINE'S LIVELIHOOD: MODELLING

2018 ◽  
pp. 36-41
Author(s):  
Karmeliuk Hanna ◽  
Svitlana Plaskon ◽  
Halyna Seniv
Keyword(s):  
Economic Growth ◽  
Gross Domestic Product ◽  
Minimum Wage ◽  
Price Index ◽  
Social Indicators ◽  
Consumer Price Index ◽  
Domestic Product ◽  
Quadratic Dependence ◽  
Inflation Forecasting ◽  
Subsistence Minimum

In the period 1996-2017, the dynamics of the subsistence minimum, the minimum wage, the consumer price index and the gross domestic product of Ukraine are analysed. These indicators have a growing trend. The necessity to use the mathematical modelling to study social and economic indicators of living standards of the population is emphasised. The trend of the dynamics of the minimum wage in the UAH is given. It has a tendency to increase. This tendency is described by quadratic dependence. The following periods are distinguished: 1996-2010 – the smooth growth of wages in quadratic dependence; 2010-2016 years – their slowed down growth by linear dependence. From 2017, when average wage has increased two times, the period of significant wages growing begins. Minimum wage retardation from the subsistence minimum until 2017 is shown. The dynamics of the subsistence minimum, which has the same periods and regularities as the salary, is analysed. Its trend is presented. The dynamics of the consumer price index is analysed. It has been broken down into the following intervals: I (1996-2010) – steady inflation growth; II (2010-2013) – price stability; III (2014 – until now) – rapid growth of prices or inflation. The inflation forecasting for 2018 is given. It is shown that economic growth (GDP) and social standards are cyclical. The main tendencies of the influence of the gross domestic product on the minimum wage, the consumer price index, the subsistence minimum are summarized. The dependence of the minimum wage on the volume of GDP is given. Econometric models of the dependence of the minimum wage on GDP in UAH and the level of inflation from the minimum wage are presented. It is shown that GDP growth is accompanied by the minimum wage increase. It is emphasized that growth of social payments negatively affects the growth of the consumer price index. It is noted that the rate of growth of the economy is not sufficient to ensure the growth of social benefits. The recommendations for economic growth are given.

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