Abstract
Tourism demand is focused on estimating variables which influence tourist visit. The tourism demand that we discuss on this research is the tourism demand to Bali of the major tourism-generating country was Australia. The aim of this research is to analyze the relationship between tourist income and tourism price to tourism demand using VECM. VECM requires that the variables in the model must be stationary and fulfilled a cointegration condition. In order to make it valid, the stationarity of variables in the model have to be checked using ADF unit root test. In additon, cointegration between these variables are examined using Johansen’s cointegration test. The results of ADF unit root test show that indicated the tourist income, the tourism price and the tourism demand for Australia data are stationary in first lag or I(1). Cointegration test shows that all variables are cointegrated, i.e. have a long-run relationship. In the long-run, the tourist income and tourism price give positive effect to the tourism demand. This means, the increase of tourist income and tourism price will contribute to the increase in tourism demand. In addition, in the short-run, the tourist income and the tourism price give negative effect to the tourism demand. This means, the increase of tourist income and tourism price will contribute to the decrease in tourism demand.
Highlights
Tourism demand is focused on estimating variables which influence tourist visit
The tourism demand that we discuss on this research is the tourism demand
The aim of this research is to analyze the relationship between tourist income and tourism price to tourism demand using Vector Error Correction Model (VECM)
Summary
Permintaan suatu barang merupakan fungsi dari pendapatan dan harga barang tersebut dan barang lainnya. Metode yang dapat digunakan untuk menganalisis pengaruh pendapatan wisatawan dan harga pariwisata terhadap permintaan pariwisata adalah model Vector Autoregressive (VAR). Mengembangkan uji Augmented Dickey-Fuller (ADF test) untuk menguji adanya keberadaan unit root dalam suatu variabel pada model dengan order lebih dari satu atau ( ( )). Vector Autoregressive atau yang dikenal dengan VAR biasanya digunakan untuk menganalisis hubungan sistem variabel-variabel runtun waktu dan menganalisis dampak dinamis dari faktor gangguan yang terdapat dalam variabel tersebut. Untuk suatu model ( ), yang akan direpresentasikan kedalam bentuk VECM secara umum dapat dinyatakan sebagai: Persamaan (5) mengandung informasi baik penyesuaian jangka pendek dan jangka panjang terhadap perubahan. Adalah pengembangan model VAR untuk runtun waktu yang tidak stasioner dan memiliki satu atau lebih hubungan kointegrasi (Enders [3]). Nilai mutlak koefisien ECT menyatakan lama waktu yang diperlukan untuk kembali ke arah keseimbangannya (Engle & Granger [4])
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