Pemodelan Volatilitas Gross Domestic Product Menggunakan Fractional Cointegration Model

Abdullah, Aisyah (2020) Pemodelan Volatilitas Gross Domestic Product Menggunakan Fractional Cointegration Model. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pertumbuhan ekonomi adalah indeks kuantitatif untuk menentukan tingkat kemajuan ekonomi yang dapat diukur dengan Gross Domestic Product (GDP). Berbagai literatur bertujuan untuk memecahkan masalah mengenai pola pertumbuhan ekonomi serta mengenai faktor penentu dimana digunakan analisis model volatilitas. Beberapa indikator pertumbuhan ekonomi adalah money supply, inflation, interest rate, dan exchange rate. Indikator lain yang dapat mempengaruhi pertumbuhan ekonomi yaitu kebijakan yang diambil pemerintah. Salah satu kebijakan yang pengaruhnya banyak diperdebatkan yaitu Inflation Targeting Framework (ITF). Variabel ekonomi dicatat sebagai data time series dengan periode yang berbeda, oleh karena itu agregasi temporal diperlukan dalam analisis. Data time series ekonomi menunjukkan adanya long memory dan structural break, sehingga akan sulit menjelaskan data hanya dengan model yang umum. Oleh karena itu, baik model long memory dan structural break dipertimbangkan dalam model. Dalam analisis ini, residual dari kombinasi linear variabel-variabel ekonomi mengikuti proses long memory yang menunjukkan hubungan cointegration antara variabel-variabel tersebut. Penelitian ini memodelkan volatilitas GDP berdasarkan volatilitas money supply, inflation, interest rate, dan exchange rate di United Kingdom, Switzerland, Indonesia, Filipina, Jerman, Denmark, Malaysia, dan Singapura menggunakan model Fractional Cointegration dengan long memory dan structural break. Analisis menunjukkan bahwa structural break hanya ditemukan dalam volatilitas GDP United Kingdom, Indonesia, Malaysia, dan Singapura sementara sifat long memory ditemukan di hampir semua volatilitas variabel ekonomi. Selain itu, pada model cointegration, diperoleh residual yang stasioner dan persisten di semua negara.
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Economic growth is a quantitative index to determine the level of economic progress that can be measured by gross domestic product (GDP). Various literatures aim to solve problems regarding patterns of economic growth as well as about the determinants wherein the analysis volatility models are used. Some indicators of economic growth are money supply, inflation, interest rates, and exchange rates. Another indicator that can influence economic growth is the policy taken by the government. One of the policies whose influence is much debated is the Inflation Targeting Framework (ITF). Economic variables are recorded as time series data with different periods, and hence temporal aggregation is required to analyze. Economic time series data showing the existence of long memory and structural breaks, which leads to the difficulty on explaining the data only with a general model. Therefore, both long memory models and structural break are proposed to be taken into account in the model. In this analysis, the residual from a linear combination of economic variables follows a long memory process indicating a cointegration relationship between these variables. This paper models GDP volatility based on money supply, inflation, interest rate and exchange rate volatility in United Kingdom, Switzerland, Indonesia, Philippines, Germany, Denmark, Malaysia, and Singapore using the Fractional Cointegration model with long memory and structural break. The analysis shows that structural break is only found in the volatility of GDP of Indonesia, Malaysia, and Singapore while the nature of long memory is found in almost all economic variables’ volatility. Furthermore, we found the cointegration model, stationary and persistent noise in all countries.

Item Type: Thesis (Masters)
Additional Information: RTSt 519.536 Abd p-1 2020
Uncontrolled Keywords: GDP, Volatility, Fractional Cointegration, Long Memory, Structural Break
Subjects: H Social Sciences > HA Statistics > HA30.3 Time-series analysis
H Social Sciences > HA Statistics > HA31.7 Estimation
H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models.
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49101-(S2) Master Thesis
Depositing User: Aisyah Abdullah
Date Deposited: 17 Dec 2024 02:37
Last Modified: 17 Dec 2024 02:37
URI: http://repository.its.ac.id/id/eprint/74211

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