scholarly journals Pengaruh Produk Domestik Bruto, Ekspor Dan Kurs Terhadap Cadangan Devisa Di Indonesia

2020 ◽  
Vol 4 (2) ◽  
pp. 301-313
Author(s):  
Fuji Astuty
Keyword(s):  
Gross Domestic Product ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Time Series Data ◽  
Domestic Product ◽  
Series Data ◽  
Foreign Exchange Reserves ◽  
Federal Reserve Bank ◽  
Reserve Bank ◽  
Analysis Technique

This study aims to analyze the effect of gross domestic product, exports and exchange rate on foreign exchange reserves in Indonesia. This research is in the form of quantitative based on quantitative data and is associative to see the relationship between variables or more. The data used is time series data from 2001 to 2018 using Eviews 9.0. And sourced from Bank Indonesia, the Central Bureau of statistics and the Federal Reserve Bank of St. Louis. This research uses data analysis technique is multiple linear analysis. The results showed that the variables of gross domestic product, exports and exchange rates have a positive and significant effect on Indonesia’s foreign exchange reserve. The R-square value in this study is 95.36, indicating that 95,36% of the variation in foreign exchange reserves can be explained by the gross domestic product, exchange rates and exports, while the remaining 4.64% is explained by other variables outside of this research model

scholarly journals Declining Proportion of Foreign Exchange Earnings from Tourism to Gross Domestic Product in Nepal

2017 ◽  
Vol 2 ◽  
pp. 45-50
Author(s):  
Deo Narayan Sutihar
Keyword(s):  
Time Series ◽  
Gross Domestic Product ◽  
Foreign Exchange ◽  
Time Series Data ◽  
Interdisciplinary Studies ◽  
Domestic Product ◽  
Series Data

This article attempts to estimate annual declining trend of proportion of foreign exchange earnings from tourism to Gross Domestic Product (GDP) in Nepal and test the significance of declining trend of this ratio using time series data of 20 years from FY 1991/92 to FY 2010/11l. It has been that the declining trend of foreign exchange earnings from tourism to GDP ratio is significant. The inequality in the distribution of foreign exchange earnings from tourism to GDP ratio is tolerable. Janapriya Journal of Interdisciplinary Studies Vol. 2, No.1 (December 2013), page: 45-50

scholarly journals Analisis faktor-faktor yang mempengaruhi ekspor CPO provinsi Jambi ke Malaysia

2020 ◽  
Vol 8 (3) ◽  
pp. 143-154
Author(s):  
Usman Hardianto ◽  
Siti Hodijah ◽  
Rahma Nurjanah
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Gross Domestic Product ◽  
Exchange Rates ◽  
Time Series Data ◽  
Secondary Data ◽  
Domestic Product ◽  
Series Data ◽  
Insignificant Effect ◽  
Average Development

The purpose of the study was to determine and analyze the development of production, exchange rates, CPO prices, Malaysian GDP, and Jambi Province CPO exports to Malaysia and the effect of production, exchange rates, CPO prices, Malaysian GDP on Jambi Province CPO exports to Malaysia. The data used in this study is secondary data in the form of time series data for 2000-2017. The results show that the average development of Jambi Province CPO exports to Malaysia is 4.10% per year, Jambi Province CPO production is on average 4, 10% per year, the average exchange rate is 2.64% per year, the average CPO price is 8.63% per year, and Malaysia's GDP is 4.89% per year on average. Based on the results of multiple linear analyses, it can be concluded that CPO production, CPO prices, exchange rates, and Malaysian GDP together affect the volume of Jambi Province's CPO exports to Malaysia. While partially production and GDP have a negative and insignificant effect on Jambi Province's CPO exports to Malaysia, the exchange rate and CPO prices positively and significantly impact Jambi Province's CPO exports to Malaysia. Keywords: Production, Price, Exchange rates, Gross Domestic Product

scholarly journals THE ANALYSIS OF FOREIGN DIRECT INVESTMENT AND ITS AFFECTING FACTORS IN INDONESIA

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Fuji Astuty
Keyword(s):  
Foreign Direct Investment ◽  
Gross Domestic Product ◽  
Exchange Rates ◽  
Direct Investment ◽  
Time Series Data ◽  
Labour Productivity ◽  
Secondary Data ◽  
Domestic Product ◽  
Series Data ◽  
Affecting Factors

Foreign Direct Investment gave benefits in improving Indonesia's economics matters in Indonesia. Conseptually, Foreign Direct Investment (FDI) more benefecial because no return to the investor such as debt in foreign country, beside Foreign Direct Investment (FDI) in a country will be followed by transfer of technology, know-how, management skills, the risks of business was smaller and more profitable. However, the problem of global economic that occured affecting the development of Foreign Direct Investment (FDI) in Indonesia decreased and the growth became slowly. Then domestic and global factors weren’t stable influencing the decrease Foreign Direct Investment (FDI) in Indonesia. Therefore, it’s needed to examine the factors influencing Foreign Direct Investment (FDI). This study aimed to know and analyze some factors affecting Foreign Direct Investment (FDI) in Indonesia consisting gross domestic product, the level of real interest, exchange rates, labour produtivity, and exports. The affecting analysis be done in short-time by using Error Correction Mechanism = ECM technique. It was used time series data from 2000 to 2013 using Eviews 6.0. The type of data used was secondary data obtained from Indonesia Bank (BI), Central Bureau of Statistics (BPS), Federal Reserve Bank of St. Louis and United Nations Economic Social Commision for Asia and the Pacific (UNESCAP). The results of this study showed that gross domestic product, the level of real interest, exchange rates, and labour productivity had positive affection significantly on Foreign Direct Investment (FDI) in Indonesia. While the exports had negative affection significantly on Foreign Direct Investment (FDI) in Indonesia. From determination coefficient (R2) showed that the variables explained 97.13 percent on Foreign Direct Investment (FDI) in Indonesia while the rest 2.87 percent was explained by variables out of models (not studied).

scholarly journals THE ANALYSIS OF FOREIGN DIRECT INVESTMENT AND ITS AFFECTING FACTORS IN INDONESIA

2021 ◽  
Vol 9 (1) ◽  
pp. 23
Author(s):  
Fuji Astuty
Keyword(s):  
Foreign Direct Investment ◽  
Gross Domestic Product ◽  
Exchange Rates ◽  
Direct Investment ◽  
Time Series Data ◽  
Labour Productivity ◽  
Secondary Data ◽  
Domestic Product ◽  
Series Data ◽  
Affecting Factors

Foreign Direct Investment gave benefits in improving Indonesia's economics matters in Indonesia. Conseptually, Foreign Direct Investment (FDI) more benefecial because no return to the investor such as debt in foreign country, beside Foreign Direct Investment (FDI) in a country will be followed by transfer of technology, know-how, management skills, the risks of business was smaller and more profitable. However, the problem of global economic that occured affecting the development of Foreign Direct Investment (FDI) in Indonesia decreased and the growth became slowly. Then domestic and global factors weren’t stable influencing the decrease Foreign Direct Investment (FDI) in Indonesia. Therefore, it’s needed to examine the factors influencing Foreign Direct Investment (FDI). This study aimed to know and analyze some factors affecting Foreign Direct Investment (FDI) in Indonesia consisting gross domestic product, the level of real interest, exchange rates, labour produtivity, and exports. The affecting analysis be done in short-time by using Error Correction Mechanism = ECM technique. It was used time series data from 2000 to 2013 using Eviews 6.0. The type of data used was secondary data obtained from Indonesia Bank (BI), Central Bureau of Statistics (BPS), Federal Reserve Bank of St. Louis and United Nations Economic Social Commision for Asia and the Pacific (UNESCAP). The results of this study showed that gross domestic product, the level of real interest, exchange rates, and labour productivity had positive affection significantly on Foreign Direct Investment (FDI) in Indonesia. While the exports had negative affection significantly on Foreign Direct Investment (FDI) in Indonesia. From determination coefficient (R2) showed that the variables explained 97.13 percent on Foreign Direct Investment (FDI) in Indonesia while the rest 2.87 percent was explained by variables out of models (not studied).

scholarly journals ANALISIS FAKTOR PENENTU INDEKS HARGA SAHAM GABUNGAN DI INDONESIA

2019 ◽  
Vol 1 (4) ◽  
pp. 37
Author(s):  
Yulizar Fikri ◽  
Ali Anis
Keyword(s):  
Economic Growth ◽  
Foreign Exchange ◽  
Stock Price ◽  
Price Index ◽  
Time Series Data ◽  
Secondary Data ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Foreign Exchange Reserves ◽  
Stock Price Index

This study aims to determine the analysis of the determinants of the composite stock price index in Indonesia. The independent variables in this study are inflation as X1, foreign exchange reserves as X2, exchange rates as X3, and economic growth as X4, and the dependent variable of the composite stock price index as Y. The data used are secondary data in the formof time series data from 2010Q1 until 2019Q2, with data collection techniques, namely documentation from Bank Indonesia publications, the Central Statistics Agency, investing. comsite and library research. The research methods used are: (1) Multiple Linear Regression, (2) Classical Assumption Test (3) coefficient of determination. The results of this study indicate that:(1) inflation does not significantly influence the composite stock price index. (2) foreign exchange reserves have a significant positive effect on the composite stock price index. (3) the rupiah exchange rate has an influence on the composite stock price index and (4) economic growth hasno significant effect on the composite stock price index.

scholarly journals PERAMALAN PRODUK DOMESTIK BRUTO (PDB) SEKTOR PERTANIAN, KEHUTANAN, DAN ‎PERIKANAN MENGGUNAKAN SINGULAR SPECTRUM ANALYSIS (SSA)

2019 ◽  
Vol 8 (1) ◽  
pp. 68-80
Author(s):  
Desy Tresnowati Hardi ◽  
Diah Safitri ◽  
Agus Rusgiyono
Keyword(s):  
Gross Domestic Product ◽  
Spectrum Analysis ◽  
Time Series Data ◽  
Seasonal Pattern ◽  
Singular Spectrum Analysis ◽  
Domestic Product ◽  
Series Data ◽  
Percentage Error ◽  
Singular Spectrum ◽  
Tracking Signal

Forecasting is the process of estimating conditions in the future by testing conditions from the past. One of the forecasting methods is Singular Spectrum Analysis (SSA) which aim of SSA is to make a decomposition of the original series into the sum of a small number of independent and interpretable components such as a slowly varying trend, oscillatory components and a structureless noise. Gross Domestic Product data in the agriculture, forestry, and fisheries sector are time series data with trend and seasonal pattern so that it can be processed using the SSA method. The forecasting process of SSA method uses the main parameter (L) of 21 obtained by the Blind Source Separation (BSS) method. From forecasting, acquired group of 3 groups. Forecasting resulted the value of Mean Absolute Percentage Error (MAPE) is 1.59% and the value of tracking signal is 2.50, which indicates that the results of forecasting is accurate. Keywords: Forecasting, Gross Domestic Product in the agriculture, forestry, and fisheries sector, Singular Spectrum Analysis (SSA)

scholarly journals An Examination Into the Causal Links Among Inward FDI Determinants: Empirical Evidence From Jordan

2021 ◽  
Vol 12 (2) ◽  
pp. 195
Author(s):  
Mohamed Ibrahim Mugableh
Keyword(s):  
Gross Domestic Product ◽  
Time Series Data ◽  
Trade Openness ◽  
Vital Role ◽  
Domestic Product ◽  
Series Data ◽  
Foreign Direct Investments ◽  
Vector Error Correction ◽  
Long Span ◽  
Foreign Policies

This paper examined the causal links between inward foreign direct investments (FDI) and its determinants (i.e., gross domestic product, education, trade openness, infrastructure, and technological abilities) for Jordan over (the period 1980 – 2018). The paper used vector error correction model. The results of the study considered that gross domestic product, trade openness, education, infrastructure, and technological abilities are primary engine of inward FDI in (long term and short term). Thus, the results have vital role for the policy makers in Jordan to formulate domestic and foreign policies. This study relied on three essential parts. Firstly, FDI is a significant source of capital that promotes economic growth. Secondly, the question of what are the leading drivers of FDI remains inadequate in the literature. Finally, this research adds to the literature by using different econometrics techniques and long span of yearly time series data. 

scholarly journals ANALISIS PENGARUH INFLASI, PRODUK DOMESTIK BRUTO (PDB), DAN NILAI TUKAR TERHADAP TABUNGAN MUDHARABAH PADA BANK UMUM SYARIAH (PERIODE 2013-2017)

2019 ◽  
Vol 8 (2) ◽  
pp. 138
Author(s):  
Rita Nur Wahyuningrum ◽  
Aan Zainul Anwar
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Linear Regression ◽  
Gross Domestic Product ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Domestic Product ◽  
Series Data ◽  
Islamic Banking ◽  
Central Statistics

<p>This study aims to analyze the effect of inflation, gross domestic product (GDP) and rupiah exchange rate on Mudharabah savings in Islamic banking in Indonesia. The data used is time series data for the period March 2013 to September 2017, which was published by Bank Indonesia from the Islamic Banking Statistics Report and the Central Statistics Agency. The technique of analyzing the research is qualitative with the method of Multiple Linear Regression. The results of this study indicate that simultaneously the Inflation, Gross Domestic Product (GDP) and Exchange Rate variables together have a significant effect on Mudharabah Savings. While partially only the Exchange Rate variable has a significant effect on Mudharabah Savings. Inflation Variables and Gross Domestic Product (GDP) have no significant effect on Mudharabah Savings.</p><p> </p><p>Keyword: inflation, gross domestic product, exchange rate, mudharabah saving</p>

scholarly journals Indicators of the association of Unemployment in Indonesia with the Level of Employment Opportunity, GDP, and SER

2021 ◽  
Vol 1 (5) ◽  
pp. 189-206
Author(s):  
Diesta Pambayun
Keyword(s):  
Economic Growth ◽  
Gross Domestic Product ◽  
Time Series Data ◽  
School Enrollment ◽  
Domestic Product ◽  
Series Data ◽  
Employment Opportunities ◽  
Unequal Distribution ◽  
Negative Effect

Population inequality and the unequal distribution of income are indicators of unemployment in Indonesia, while unemployment plays an important role in economic growth. The increase in Gross Domestic Product (GDP) means that the level of public welfare improves in direct proportion to the gross domestic product (GDP) which is used as a measuring tool for economic conditions. School Enrollment Rates (SER) and employment opportunities are also identified as having an effect on economic growth, so it is important to conduct research using the ECM method using time series data for 1990-2019 sourced from the Central Statistics Agency (CSA). Based on the results of data processing, it can be seen that in the short and long term employment opportunities and GDP have a positive effect on unemployment. However, in the long term GDP and SER have no significant negative effect on unemployment.

Neural Networks for Technical Forecasting of Foreign Exchange Rates

2002 ◽  
pp. 189-204
Author(s):  
Jing Tao Yao ◽  
Chew Lim Tan
Keyword(s):  
Neural Networks ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Time Series Data ◽  
Series Data ◽  
Technical Indicators ◽  
Currency Exchange ◽  
The Neural Network ◽  
Out Of Sample ◽  
Japanese Yen

This chapter describes the application of neural networks in foreign exchange rate forecasting between American dollar and five other major currencies: Japanese yen, Deutsch mark, British pound, Swiss franc and Australian dollar. Technical indicators and time series data are fed to neural networks to mine, or discover, the underlying “rules” of the movement in currency exchange rates. The results presented in this chapter show that without the use of extensive market data or knowledge, useful prediction can be made and significant paper profit can be achieved for out-of-sample data with simple technical indicators. The neural-network-based forecasting is also shown to compare favorably with the traditional statistical approach.

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