scholarly journals Aplikasi Model Vector Autoregressive (VAR) pada Data Tamu Mancanegara di Hotel Bintang dan Non Bintang di Daerah Istimewa Yogyakarta

2019 ◽  
Vol 3 (2) ◽  
pp. 6-15
Author(s):  
Pardomuan Sihombing ◽  
Bekti Endar Susilowati
Keyword(s):  
Vector Autoregressive ◽  
Diagnostic Checking

Model Vector Autoregressive (VAR) merupakan gabungan dari beberapa model Autoregressive (AR), dimana model membentuk sebuah vektor yang antara variabel-variabelnya saling memengaruhi. Model AR(1) menyatakan bahwa pengamatan waktu sekarang dipengaruhi pengamatan satu waktu sebelumnya dan unsur error. Pada analisis ini, model Vector Autoregressive (VAR) digunakan pada data tamu mancanegara per bulan yang menginap di Hotel Bintang dan Non bintang di Daerah Istimewa Yogyakarta per bulan periode Januari 2008 sampai dengan Desember 2015. Pembentukan model VAR melalui beberapa tahap yaitu: uji stasioneritas, penentuan orde autoregressive, pembentukan model VAR, dan diagnostic checking. Untuk pengolahan data dilakukan dengan program R 3.5.1. Dari analisis data, variabel jumlah tamu wisatawan mancanegara di Hotel Bintang dan Hotel Non Bintang di Daerah Istimewa Yogyakarta memiliki korelasi yang cukup tinggi yaitu sebesar 0,91. Dengan model Vector Autoregressive (VAR) yaitu VAR(1) didapatkan kedua hasil persamaan simultan yang signifikan. Nilai R2 dan Adjusted R2 kedua persamaan parsial model VAR(1) cukup tinggi yaitu untuk persamaan variabel Hotel Bintang didapatkan R2 sebesar 71,13% dan Adjusted R2 70,5%, sedangkan untuk persamaan variabel Hotel Non Bintang didapatkan R2 sebesar 76,56% dan dan Adjusted R2 70,65 %.

scholarly journals Vector Autoregressive Integrated (VARI) Method for Forecasting the Number of Internasional Visitor in Batam and Jakarta

2020 ◽  
Vol 17 (1) ◽  
pp. 94-108
Author(s):  
Septie Wulandary
Keyword(s):  
Univariate Analysis ◽  
Percentage Error ◽  
Vector Autoregressive ◽  
Separate Model ◽  
Forecasting Methods ◽  
Diagnostic Checking ◽  
Stationarity Test ◽  
The Mean ◽  
Model Formation ◽  
Order Determination

Forecasting methods that are often used are time series analysis, the Autoregressive (AR) method. The AR method only carries out univariate analysis, meaning that it carries out a separate model between the number of international visitor coming to Indonesia through Batam and Jakarta. Though there is a possibility, the number of international visitor arriving through Jakarta affects the number of international visitor arriving through Batam. Therefore, in this study the Vector Autoregressive Integrated (VARI) method is used. The VARI model is used on the number of international visitor arrivals per month at Batam and Jakarta for the period Januari 2014 – December 2019. VARI model formation through several stages, namely stationarity test, autoregressive order determination, VARI model formation, and diagnostic checking of the model. With the VARI model, VARI(5,1), the two significant simultaneously equation results are obtained. The Mean Absolute Percentage Error (MAPE) in this model are as follows 1,98% and 2,48% in predicting the number of international visitor arrivals in Batam and Jakarta. In this study also forecasting the number of international visitor arrivals in Batam and Jakarta in January – December 2020

Fraud and Bank Performance in Nigeria – Var Granger Causality Analysis

e-Finanse ◽  
2020 ◽  
Vol 16 (1) ◽  
pp. 20-26
Author(s):  
Taiwo A. Muritala ◽  
Muftau A. Ijaiya ◽  
Olatanwa H. Afolabi ◽  
Abdulrasheed B. Yinus
Keyword(s):  
Control Systems ◽  
Granger Causality ◽  
Internal Control ◽  
Banking Sector ◽  
Bank Performance ◽  
Causality Analysis ◽  
Vector Autoregressive ◽  
Granger Causality Analysis ◽  
Long Run ◽  
Multivariate Cointegration

AbstractThis paper examines the causality between fraud and bank performance in Nigeria over the period 2000-2016 for quarterly financial data using Johansen’s Multivariate Cointegration Model and Vector Autoregressive (VAR) Granger Causality analysis. The results show a long-run relationship between the variables. Bank performance was found to be linked to Granger fraud variables and vice versa at 10% significant level. This study reveals that there was a direct causal relationship between bank performance and fraud because increase in fraudulent activities in the banking sector leads to reduction in bank performance. Hence, this study recommends that internal control systems of banks should be strengthened so as to detect and prevent fraud. In this way, bank assets would be protected.

Tracking the Transmission Channels of Fiscal Deficit and Food Inflation Linkages: A Structural VAR Approach

2020 ◽  
pp. 165-172
Keyword(s):  
Positive Impact ◽  
Structural Var ◽  
Fiscal Deficit ◽  
Agricultural Industry ◽  
Vector Autoregressive ◽  
Transmission Channels ◽  
Government Deficit ◽  
Import And Export ◽  
The Impact ◽  
Food Inflation

This empirical analysis aspired to unearth the transmission channels of fiscal deficit and food inflation linkages in the Indian perspective by reasonably exerting the data for 1991 to 2017. The precise results of structural vector autoregressive (SVAR) analysis proffered that there were three different mechanisms of transmission such as consumption, general inflation, and import channels that led to food inflation in response to the high fiscal deficit. The first channel revealed that government deficit spending had a positive impact on income which further led to food inflation through surging the household consumption expenditure. It was concluded that fiscal deficit passed through general inflation finally leading to a food price surge in the economy and seemed to work as cost-push inflation for the food and agricultural industry. The outcome also revealed that the impact of fiscal deficit passed to food inflation through external linkages such as import and export.

Is tracking and modeling Covid-19 infection dynamics for Bangladesh using daily data feasible? (Preprint)

2020 ◽  
Author(s):  
Karar Zunaid Ahsan ◽  
Rashida Ijdi ◽  
Peter Kim Streatfield
Keyword(s):  
Test Results ◽  
Infection Rates ◽  
Causality Test ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Daily Number ◽  
Infection Dynamics ◽  
Daily Data ◽  
Daily Change ◽  
Testing Coverage

UNSTRUCTURED Given the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladesh case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh.

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