scholarly journals On One Co-Integration Issue of Trade Links of Azerbaijan, Russia, Belarus and Kazakhstan

2020 ◽  
Vol 17 (2) ◽  
pp. 29-39
Author(s):  
E. G. Orudzhev ◽  
S. M. Huseynova
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Stationary Time Series ◽  
Vector Model ◽  
Microsoft Excel ◽  
Vector Error Correction ◽  
Vector Error ◽  
Equilibrium Relationship ◽  
Foreign Trade Turnover

This article, based on annual data from 1994 to 2018, considers trade and economic processes between Azerbaijan, Russia, Belarus and Kazakhstan through the GDP integration indicators of Azerbaijan and foreign trade turnover with these countries.The purpose of the research. The purpose of the study is to find cointegration relationships between the studied macroeconomic indicators and correct application of the vector model of error correction to describe the equilibrium relationship between the considered data of intercountry interaction and to develop sound economically informative recommendations in the sphere of intercountry trade and economic interaction.Materials and methodology. Official statistics of the State Statistics Committee of Azerbaijan, scientific works of scientists-economists on the inter-country integration processes in the post-soviet region are used. Statistical methods of information processing are applied in relation to the empirical analysis of non-stationary time series of the studied statistical data, and correctly tested modern econometric methods and all the necessary econometric testing procedures are used to build co-integration relations and the vector model of error correction taking into account the effects of external shocks. All the calculations are made in Microsoft Excel and Eviews 8 application software packages.Results. The properties of applying the econometric methodology of studying the statistical relationship between multidimensional nonstationary time series are investigated. For this data, the authors' approach is to use the co-integration tool and the mechanism of vector error correction, which are practically not applicable by economists in Azerbaijan to date. A new specification of the model with respect to the logarithms of the source variables is defined. Based on the minimization of the mean square error, estimates of the model parameters are found. The Granger connection causality is investigated. The Johansen tests are implemented to find the cointegration area, after which the vector error correction model is built, which describes the long-term equilibrium relationship between the studied indicators and the path of returning to the equilibrium trajectory if it deviates from it. When modeling, we used all the necessary statistical procedures required to identify and evaluate the parameters of the model and verify its adequacy and the accuracy of short-term and long-term forecast values by applying Microsoft Excel and Eviews 8 tools.Conclusion. As a result of the study, econometrically sound recommendations are developed, which allow to conduct dynamic analyzes for effective state regulation of export-import operations between the four countries in order to balance the trade and improve the relevant inclusive parameters of the long-term sustainable development of these states.

Measuring Dynamic Sales Impacts of LBA Using Wireless Communication Technology

2013 ◽  
Vol 662 ◽  
pp. 896-901
Author(s):  
Zong Jin Liu ◽  
Yang Yang ◽  
Zheng Fang ◽  
Yan Yan Xu
Keyword(s):  
Wireless Communication ◽  
Error Correction ◽  
Communication Technology ◽  
Dynamic Error ◽  
Rapid Development ◽  
Vector Autoregressive ◽  
Vector Error Correction ◽  
Vector Error ◽  
Equilibrium Relationship

Because of rapid development of wireless communication technology, there is an increasing adoption of mobile advertising, such as location based advertising (LBA). To what extent can LBA improve advertising effectiveness is an important topic in the field of wireless communication technology research. Most researches quantify long term impacts of advertisings by VAR (Vector Autoregressive) model. However, compared to VAR model, VECM (Vector Error Correction Model) is a better method in that it allows one to estimate both a long-term equilibrium relationship and a short-term dynamic error correction process. In this study, we employ VECM to explore LBA’s (Location Based Advertising) and PUA’s (Pop-up Advertising) sales impact in both short and long terms. The developed VECM reveals that LBA’s sales impact is about more than2 times as big as PUA’s in short dynamic term and nearly 6 times bigger than PUA’s in long equilibrium term. These findings add to advertising and VECM literatures. These results can give managers more confident to apply wireless communication technology to advertising.

scholarly journals Application of multiple regression models for inflation modelling

2021 ◽  
Vol 47 ◽  
Author(s):  
Ana Čuvak ◽  
Žilvinas Kalinauskas
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Regression Models ◽  
Stationary Time Series ◽  
Exogenous Variables ◽  
Price Inflation ◽  
Vector Error Correction ◽  
Vector Error ◽  
Multiple Regression Models ◽  
Augmented Dickey Fuller

This paper examines the Lithuanian consumer price inflation from 1996 January till 2006 December using a modern non-stationary time series and econometric theory.  The multiple regressionmodels are proposed for inflation modeling. The stationarity of Lithuanian inflation and the main explored exogenous variables are analyzed using the augmented Dickey–Fuller test.  All indicators are integrated of order one.  Vector error correction (VECM) model of Lithuanian inflation processes is investigated and proposed for inflation modeling.

scholarly journals A Multivariate Forecasting Model for the COVID-19 Hospital Census Based on Local Infection Incidence

2021 ◽  
Author(s):  
Hieu M. Nguyen ◽  
Philip Turk ◽  
Andrew McWilliams
Keyword(s):  
Time Series ◽  
Multivariate Time Series ◽  
Healthcare Systems ◽  
Leading Indicators ◽  
Short Term ◽  
Correction Model ◽  
Vector Error Correction ◽  
Infection Incidence ◽  
Vector Error

AbstractCOVID-19 has been one of the most serious global health crises in world history. During the pandemic, healthcare systems require accurate forecasts for key resources to guide preparation for patient surges. Fore-casting the COVID-19 hospital census is among the most important planning decisions to ensure adequate staffing, number of beds, intensive care units, and vital equipment. In the literature, only a few papers have approached this problem from a multivariate time-series approach incorporating leading indicators for the hospital census. In this paper, we propose to use a leading indicator, the local COVID-19 infection incidence, together with the COVID-19 hospital census in a multivariate framework using a Vector Error Correction model (VECM) and aim to forecast the COVID-19 hospital census for the next 7 days. The model is also applied to produce scenario-based 60-day forecasts based on different trajectories of the pandemic. With several hypothesis tests and model diagnostics, we confirm that the two time-series have a cointegration relationship, which serves as an important predictor. Other diagnostics demonstrate the goodness-of-fit of the model. Using time-series cross-validation, we can estimate the out-of-sample Mean Absolute Percentage Error (MAPE). The model has a median MAPE of 5.9%, which is lower than the 6.6% median MAPE from a univariate Autoregressive Integrated Moving Average model. In the application of scenario-based long-term forecasting, future census exhibits concave trajectories with peaks lagging 2-3 weeks later than the peak infection incidence. Our findings show that the local COVID-19 infection incidence can be successfully in-corporated into a VECM with the COVID-19 hospital census to improve upon existing forecast models, and to deliver accurate short-term forecasts and realistic scenario-based long-term trajectories to help healthcare systems leaders in their decision making.Author summaryDuring the COVID-19 pandemic, healthcare systems need to have adequate resources to accommodate demand from COVID-19 cases. One of the most important metrics for planning is the COVID-19 hospital census. Only a few papers make use of leading indicators within multivariate time-series models for this problem. We incorporated a leading indicator, the local COVID-19 infection incidence, together with the COVID-19 hospital census in a multivariate framework called the Vector Error Correction model to make 7-day-ahead forecasts. This model is also applied to produce 60-day scenario forecasts based on different trajectories of the pandemic. We find that the two time-series have a stable long-run relationship. The model has a good fit to the data and good forecast performance in comparison with a more traditional model using the census data alone. When applied to different 60-day scenarios of the pandemic, the census forecasts show concave trajectories that peak 2-3 weeks later than the infection incidence. Our paper presents this new model for accurate short-term forecasts and realistic scenario-based long-term forecasts of the COVID-19 hospital census to help healthcare systems in their decision making. Our findings suggest using the local COVID-19 infection incidence data can improve and extend more traditional forecasting models.

scholarly journals Analisis Pengaruh Kinerja Keuangan terhadap Profitabilitas Bank Syariah di Indonesia

2017 ◽  
Vol 8 (2) ◽  
pp. 175
Author(s):  
Heri Sudarsono
Keyword(s):  
Error Correction ◽  
Error Correction Model ◽  
Third Party ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Factors Affecting ◽  
Vector Error Correction ◽  
Vector Error ◽  
Long Run

<p>This study aimed to analyze the factors affecting the amount of profitability (ROA) provided by Islamic banking in Indonesia. The data which is used is taken from the financial report of the Shari’a Bank during the 2011-2016 periods by using montly financial statement This study uses a Vector Error Correction Model (VECM) to see the long-term effect and response to shock that occur in the studied variables. The result shows that in the long run, the percentage Financing (FIN) and BOPO give a positive siqnifikant effect on the ROA, while third party funds (DPK), percentage profit and loss sharing (TBH), financial to deposit ratio (FDR) has negative and siqnificant effect on the ROA. Sertifikat Bank Indonesia Syariah (SBIS) and non performing finance (NPF) have no significant effect on the ROA. In short run, ROA give a negatif and siqnificant effect on the ROA and FDR give a positif and siqnificant effect, while DPK, FIN, SBIS, TBH, NPF and BOPO have no sinificant effect on the ROA. Therfore, shocks that occur in the ROA, FIN, FDR , NPF dan BOPO positively responded by ROA and will be stable in the long term. While the shocks that occur in the percentage of FDR, SBIS and TBH responded negatively by financing and will be stable in the long term.</p><p>Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi profitabilitas (ROA) perbankan syariah di Indonesia. Data yang digunakan data bulanan dari laporan keuangan bank syariah periode 2010-2015. Penelitian ini mengunakan Vector Error Correction Model (VECM) untuk melihat dampak jangka panjang dan respon terhadap dampak shock pada setiap variabel terhadap pembiayaan. Hasil olah data menunjukkan bahwa FIN dan BOPO berhubungan positif terhadap ROA, sedangkan DPK, TBH, FDR berhubungan negatif terhadap dan ROA SBIS dan NPF tidak berpengaruh terhadap tingkat ROA. Dalam jangka pendek, ROA berhubungan negatif, tetapi FDR terhadap ROA berhubungan positif. Sedangkan DPK, FIN, SBIS, TBH, NPF and BOPO tidak berhubungan dengan pembiayaan. Di lain pihak, respon pembiayan terhadap goncangan yang terjadi terjadi pada ROA, FIN, FDR, NPF dan BOPO direspon positif oleh ROA. Sedangkan respon ROA terhadap goncangan yang terjadi pada FDR, SBIS dan TBH adalah negatif.</p>

scholarly journals Kondisi makroekonomi dan kinerja perbankan di Indonesia

2021 ◽  
Vol 16 (1) ◽  
pp. 11-28
Author(s):  
Irma Febriana Mk ◽  
Nurbetty Herlina Sitorus ◽  
Rizka Malia
Keyword(s):  
Error Correction ◽  
Industrial Production ◽  
Negative Relationship ◽  
Short Term ◽  
Vector Error Correction ◽  
Production Index ◽  
Vector Error ◽  
Industrial Production Index ◽  
Significant Negative Relationship

The purpose of this study was to see how the long-term and short-term relationship between banking performance and macroeconomic variables. The analysis method used is the vector error correction model (VECM) with the variables ROA, BOPO, LDR, industrial production index, CPI, and BI rate. The results of this study indicate that there is a significant positive relationship between ROA and industrial production index in the long run and a significant negative relationship between ROA and CPI in the long and short term. There is a significant negative relationship between BOPO and the industrial production index in the long and short term. LDR has a significant negative relationship with all macro variables in the long term whereas, in the short term, LDR has a significant negative relationship with the CPI.  Keywords: Banking performance, Macroeconomic, Vector error correction models

scholarly journals Bank Syariah di Indonesia: Analisis Pengaruh Rata-Rata Tingkat Bagi Hasil Deposito dan Rata-Rata Tingkat Suku Bunga Deposito Terhadap Jumlah Deposito dan Jumlah Nasabah Deposito Periode 2009-2014

2017 ◽  
Vol 4 (2) ◽  
pp. 89
Author(s):  
Aprilia Pratiwi ◽  
Noven Suprayogi
Keyword(s):  
Error Correction ◽  
Analytical Techniques ◽  
Return Level ◽  
Islamic Banking ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Independent Variable

This research aimed to determine the average profit-loss sharing level of deposit and the return level of deposit affect to total deposit and the quantity of Islamic banking customer in Indonesia, in time year 2009 until year 2014. The approach is a quantitative approach using VECM (Vector Error Correction Model) analytical techniques, to determine the effect of independent variable to dependent variable. The independent variable of this research is the average profit-loss sharing level of Islamic banking and the return level of deposit in conventional banking. While the dependent variable of this research is the total deposit and the quantity of Islamic banking customer in Indonesia. The result of this research showed that independent variable has a significant effect to total deposit in a long term, both simultaneous and partial. While in the quantity of customer, independent variable has no significant effect, both simultaneous and partial in a long term.

scholarly journals Test FOR Dynamic Relationship between Financial Development and Economic Growth in Malaysia: A Vector Error Correction Modeling Approach

2007 ◽  
Vol 9 (1) ◽  
pp. 61 ◽  
Author(s):  
Rosilawati Amiruddin ◽  
Abu Hassan Shaari Mohd Nor ◽  
Ismadi Ismail
Keyword(s):  
Economic Growth ◽  
Error Correction ◽  
Financial Development ◽  
Impulse Response Function ◽  
Vector Autoregressive ◽  
Vector Error Correction ◽  
Dynamic Relationship ◽  
Vector Error ◽  
Error Correction Modeling

This paper purports to study the effectiveness of financial development to Malaysian economic growth utilizing quarterly data. In view of the priority given to dynamic relationship in conducting this study, Vector Autoregressive (VAR) method which encompasses Johansen-Juselius’ Multivariate cointegration, Vector Error Correction Model (VECM), Impulse Response Function (IRF), and Variance Decomposition (VDC) are used as empirical evidence. The result reveals a short-term and long-term dynamic relationship between financial development and economic growth. The importance of financial sector in influencing the economic activity is proven as a clear policy implication.

scholarly journals Analysis of Stock Market Integration Among ASEAN Countries by Using Vector Error Correction Model (VECM) Approach

2020 ◽  
Author(s):  
Reni Lestari
Keyword(s):  
Stock Market ◽  
Error Correction ◽  
Stock Exchange ◽  
Error Correction Model ◽  
Stock Index ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error

Globalization has driven the economy of countries to relate to each other. It brings relationships in the capital among countries in the world, especially in ASEAN region countries. This study aimed to analyze the integration of the stock market among countries in the ASEAN region. The stock market was analyzed are the Indonesia Stock Exchange, Malaysia Stock Exchange, Singapore Stock Exchange, Thailand Stock Exchange, Vietnam Stock Exchange, and Philippine Stock Exchange. This study using the Vector Error Correction Model (VECM) as the method. The result of this study shows that, in the long term Singapore Stock Index (STI), Malaysia Stock Index (KLSE), Philippines (PSEi), and Indonesia Stock Index (JKSE) are positively correlated. This means the change of stock index price in one country will affect other related countries in the long term. In the short term of VECM estimation, found the Vietnam Stock Index (VNI), Singapore Stock Exchange (STI), Philippine (PSEi) are positively correlated and negatively correlated with Thailand Stock Exchange (SET). For the managerial implication, the result of this study is expected as a reference or basis of consideration of investment decisions. This because long-term stock market movements are important because they impact international portfolio management and risk diversification.

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