scholarly journals Analysis of time series models for consumer price index

2012 ◽  
Vol 23 (3) ◽  
pp. 535-542 ◽  
Author(s):  
Hoon-Ja Lee
Keyword(s):  
Time Series ◽  
Price Index ◽  
Consumer Price Index ◽  
Time Series Models ◽  
Analysis Of Time Series

Fuzzy Autocorrelation Model with Fuzzy Confidence Intervals and its Evaluation

2016 ◽  
Vol 20 (4) ◽  
pp. 512-520 ◽  
Author(s):  
Yoshiyuki Yabuuchi ◽  
◽  
Takayuki Kawaura ◽  
Junzo Watada ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Confidence Intervals ◽  
Price Index ◽  
Predictive Accuracy ◽  
Fuzzy Theory ◽  
Consumer Price Index ◽  
Time Series Model ◽  
Fuzzy Regression ◽  
Fuzzy Time Series ◽  
Time Series Models

Interval models based on fuzzy regression and fuzzy time-series can illustrate the possibilities of a system using the intervals in the model. Thus, the aim is to minimize the vagueness of the model in order to describe the possible states of the system. In the present study, we consider on an interval fuzzy time-series model based on a Box–Jenkins model, a fuzzy autocorrelation model proposed by Yabuuchi, and a fuzzy regressive model proposed by Ozawa. We examine two models by analyzing the Japanese national consumer price index and demonstrate that our approach improves the accuracy of predictions. The utility and predictive accuracy of fuzzy time-series models are validated using two concepts of fuzzy theory and statistics. Finally, we demonstrate the applicability of the fuzzy autocorrelation model with fuzzy confidence intervals.

Analysis of Time Series Models for Brazilian Electricity Demand Forecasting

2021 ◽  
Author(s):  
Carlos Eduardo Velasquez Cabrera ◽  
Matheus Zocatelli ◽  
Fidellis B.G.L. e Estanislau ◽  
Victor Faria
Keyword(s):  
Time Series ◽  
Demand Forecasting ◽  
Electricity Demand ◽  
Time Series Models ◽  
Electricity Demand Forecasting ◽  
Analysis Of Time Series

scholarly journals A forecasting the consumer price index using time series model

2021 ◽  
Vol 107 ◽  
pp. 10002
Author(s):  
Volodymyr Shinkarenko ◽  
Alexey Hostryk ◽  
Larysa Shynkarenko ◽  
Leonid Dolinskyi
Keyword(s):  
Time Series ◽  
Price Index ◽  
Consumer Price Index ◽  
Exponential Smoothing ◽  
Time Series Model ◽  
Initial Time ◽  
Autocorrelation Functions ◽  
Minimum Error ◽  
Initial Time Series

This article examines the behavior of the consumer price index in Ukraine for the period from January 2010 to September 2020. The characteristics of the initial time series, the analysis of autocorrelation functions made it possible to reveal the tendency of their development and the presence of annual seasonality. To model the behavior of the consumer price index and forecast for the next months, two types of models were used: the additive ARIMA*ARIMAS model, better known as the model of Box-Jenkins and the exponential smoothing model with the seasonality estimate of Holt-Winters. As a result of using the STATISTICA package, the most adequate models were built, reflecting the monthly dynamics of the consumer price index in Ukraine. The inflation forecast was carried out on the basis of the Holt-Winters model, which has a minimum error.

The Salaries of Officials and Officers in the Russian Empire

2021 ◽  
Vol 47 (3) ◽  
pp. 224-237
Author(s):  
Boris N. Mironov ◽  
Jan Surer
Keyword(s):  
Time Series ◽  
Price Index ◽  
Consumer Price Index ◽  
Russian Empire ◽  
Officer Corps ◽  
The Real ◽  
Regulatory Documents ◽  
The Russian Empire

Abstract This article analyzes changes in both the nominal and real salaries of Russian officials and officers. The study draws upon data concerning provincial administrations, which employed a significant portion of officials, and the infantry, in which most of the officer corps served, from the introduction of monetary salaries in 1763 (for officials) and in 1711 (for officers) to 1913. A table of the changes in nominal salaries was compiled from legislative and regulatory documents, and, with the use of a consumer price index constructed by the author, time series of the real salaries of officials and officers of various ranks were obtained by decades over 150 years.

FORECASTING CONSUMER PRICE INDEX (CPI) USING TIME SERIES MODELS AND MULTI REGRESSION MODELS (ALBANIA CASE STUDY)

2018 ◽  
Author(s):  
Eralda Gjika Dhamo ◽  
Llukan Puka ◽  
Oriana Zaçaj
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Multiple Regression ◽  
Consumer Price Index ◽  
Multiple Regression Model ◽  
Time Series Models ◽  
Financial Indicators ◽  
Consumer Prices ◽  
Approach Time

In this work we analyse the CPI index as the official index to measure inflation in Albania, Harmo-nized Indices of Consumer Prices (HICPs) as the bases for comparative measurement of inflation in European countries and other financial indicators that may affect CPI. This study is an attempt to model CPI based on combination of multiple regression model with time series forecasting models. In the first approach, time series models were used directly on the CPI time series index to obtain the forecast. In the second approach, the time series models (SARIMA, ETS) were used to model and simulate forecast for each subcomponent with significant correlation to CPI and then use the multiple regression model to obtain CPI forecast. The projection of this indicator is important for understand-ing the country's economic and social development. This study helps researchers in the field of time series modeling, economic analysis and investments.

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 relationship between M3 and consumer price index in the Czech Republic

2018 ◽  
Vol 4 (10) ◽  
pp. 226-236
Author(s):  
Libena Cernohorska
Keyword(s):  
Time Series ◽  
Czech Republic ◽  
Price Index ◽  
Statistical Data ◽  
Consumer Price Index ◽  
Monetary Aggregate ◽  
The Czech Republic ◽  
Significance Level ◽  
The Relationship ◽  
Cointegration Relationship

This paper aimed at analysing the influence of monetary aggregate M3 on consumer price index (CPI) in the Czech Republic. Cointegrating this selected indicator M3 is demonstrated in relation to the development of CPI using the Engle – Granger cointegration test. These tests are applied to selected statistical data from the years 2003 to 2016. After using the Akaike criteria for all-time series, we analysed a unit root using the Dickey–Fuller test. If the time series are non-stacionary, testing is then continued with the Engle–Granger test to detect cointegration relations. Based on these tests, it is found that at a significance level of 0.05, a cointegration relationship between M3 and CPI in the Czech Republic does not exist. Conclusions resulting from the verification of the hypotheses are supported with graphical visualisation of data from which it is apparent that these hypotheses can be rejected. Keywords: M3; Czech Republic ; CPI ; Akaike criteria

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