THE DETERMINATION OF PERIODICITIES IN SHORT-TERM TIME-SERIES DATA IN THE PRESENCE OF HIGH FREQUENCY NOISE AND LONG-TERM TREND

This study aim is to test the money neutrality in a narrow sense (M1) and a broad sense (M2) to the growth of output (GDP) in Indonesia, both in short term and long term. This research uses quarterly time series data at 2010 - 2016 periods. The analysis tool used is Error Correction Model (ECM). The results show that short-term money supply (M1 and M2) affect on output growth. However, in the long term, only money circulation in a broad sense (M2) affects on output growth, which also means that money is not neutral because it affects the real sector (GDP). Keywords: M1, M2, Population, Capital, and Economic Growth.

Download Full-text

Integration of Indonesian Coffee Markets with World Coffee Markets

Journal of Agricultural Socio-Economics (JASE) ◽

10.33474/jase.v2i1.6865 ◽

2021 ◽

Vol 2 (1) ◽

pp. 33

Author(s):

Haposan Orlando Napitupulu ◽

Ana Arifatus Sa'diyah ◽

Farah Mutiara

Keyword(s):

Time Series Data ◽

Dynamic Equilibrium ◽

Secondary Data ◽

Series Data ◽

Short Term ◽

Robusta Coffee ◽

Long Run ◽

Relationship Of ◽

Coffee Markets

This study aims to analyze the integration of the Arabica and Robusta coffee markets in Indonesia with world coffee prices. The study uses secondary data in the form of annual time series data during the period 1985 - 2015. The study uses the VECM analysis method. This method explains the relationship of long-term dynamic equilibrium and short-term equilibrium in a system of equations. The analysis shows that Indonesian and world Arabica coffee is not integrated in the long term or the short term. In Robusta coffee VECM estimation analysis shows that there is a significant value at the 10% level in a long-term relationship with a value of 0.08579, which means that there is a short-term relationship between world Robusta coffee prices and domestic Robusta coffee prices in the previous year, but no relationship in the long run.

Download Full-text

Analisis Peningkatan Upah Minimum Terhadap Penyerapan Tenaga Kerja di Provinsi Jawa Tengah

Jurnal Ekonomi Pembangunan ◽

10.23960/jep.v10i3.291 ◽

2021 ◽

Vol 10 (3) ◽

pp. 134-143

Author(s):

Annisa Yulianti ◽

Hadi Sasana

Keyword(s):

Economic Growth ◽

Minimum Wage ◽

Time Series Data ◽

Series Data ◽

Short Term ◽

Central Java ◽

Meaningful Relationship ◽

Short Time ◽

Relationship Of

This study aims to analyze the short-term and long-term relationship of increasing the minimum wage in Central Java on employment. The research method used is ECM. The variables of this study include labor, minimum wages, PMDN, and economic growth. The data used are time-series data from 1990-2020. The results show that the minimum wage has a positive and significant relationship to the employment in the long term but not significantly in the short time. PMDN has a negative but significant correlation in the short and long term. At the same time, the variable economic growth has a positive but not meaningful relationship to employment absorption in the long and short term.

Download Full-text

Track Irregularity Time Series Analysis and Trend Forecasting

Discrete Dynamics in Nature and Society ◽

10.1155/2012/387857 ◽

2012 ◽

Vol 2012 ◽

pp. 1-15 ◽

Cited By ~ 17

Author(s):

Jia Chaolong ◽

Xu Weixiang ◽

Wang Futian ◽

Wang Hanning

Keyword(s):

Time Series ◽

Time Series Data ◽

Series Data ◽

Short Term ◽

Measuring Point ◽

Trend Forecasting ◽

Changing Trend ◽

Track Irregularity ◽

Linear Differential

The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM(1,1)is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section. Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.

Download Full-text

The Effect of Covid-19, Rupiah Exchange Rate, and Inflation on the Indonesia Sharia Stock Index during the Covid-19 Pandemic

Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) ◽

10.31538/iijse.v4i1.1654 ◽

2021 ◽

Vol 4 (1) ◽

pp. 313-336

Author(s):

Achmad Agus Priyono ◽

Ari Kartiko

Keyword(s):

Exchange Rate ◽

Time Series Data ◽

Negative Impact ◽

Stock Index ◽

Series Data ◽

Stock Market Index ◽

Short Term ◽

The Us ◽

Us Dollar

Purpose of this study is to clarify the effect of the number of daily cases reported to have contracted the Covid-19 virus, the exchange rate of the rupiah against the US dollar and inflation on the movement of the Indonesian Sharia stock index (ISSI) during the Pandemic Covid 19 in the short term and long term. Data analysis methods that used is analysis Error Correction Mechanism (ECM) using Eviews software 10. The data collected is daily time series data starting from March 2, 2020 to May 31, 2021 so that the number of samples collected obtained as many as 283 samples . The results of the study stated that the addition of the daily number of reported cases of contracting the Covid-19 virus has a negative impact on The Indonesian Sharia Stock Market Index (ISSI) during the Covid-19 pandemic, so that encourage the weakening of the Stock Index both in the long and long term short. Likewise, the weakening of the rupiah against the US dollar will caused the fall of the sharia index during the Covid 19 pandemic, both in the long term and long and short term. However, the study found no effect inflation on the Indonesian Sharia Stock Index (ISSI) during the Covid19 pandemic, good long term and short term

Download Full-text

Fiscal Deficit and Its Less Inflationary Sources of Borrowing with the Moderating Role of Political Instability: Evidence from Malaysia

Sustainability ◽

10.3390/su12010366 ◽

2020 ◽

Vol 12 (1) ◽

pp. 366 ◽

Cited By ~ 1

Author(s):

Hanana Khan ◽

Maran Marimuthu ◽

Fong-Woon Lai

Keyword(s):

Central Bank ◽

Time Series Data ◽

Political Instability ◽

Series Data ◽

Fiscal Deficit ◽

Short Term ◽

High Tendency ◽

External Sources ◽

Domestic Sources

Theoretically, fiscal deficit may be inflationary, but its sources of financing can bring change in significance and impact. Malaysia is facing a high tendency of fiscal deficit from the last decade. To finance the fiscal deficit, which sources are less inflationary in the country? To answer this question, the study aims to analyze the quarterly financial time-series data covering the period from 2000 Q1 to 2018 Q4 of Malaysia using recent econometric techniques. The analysis is carried out in three stages. In the first stage, it is tested that the fiscal deficit is inflationary along with the money supply. In the second stage, it is determined that political instability moderates the link between inflation and the fiscal deficit and the external sources of borrowing in the short-run, while the domestic sources of borrowing in the long run are found inflationary. In the third stage, the central bank borrowing and Bank institutions borrowing from the domestic sources and the short-term borrowing from the external sources are found less inflationary. The findings suggest that borrowing through the central bank and bank institutions (domestic sources) is less inflationary in the long term; while for a short-term policy, from external sources, only short-term borrowing is less inflationary; medium- and long-term borrowing are much more sensitive to inflation.

Download Full-text

Long Short Term Memory Recurrent Network for Standard and Poor’s 500 Index Modelling

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.15.21365 ◽

2018 ◽

Vol 7 (4.15) ◽

pp. 25 ◽

Cited By ~ 3

Author(s):

Said Jadid Abdulkadir ◽

Hitham Alhussian ◽

Muhammad Nazmi ◽

Asim A Elsheikh

Keyword(s):

Neural Network ◽

Time Series ◽

Recurrent Neural Network ◽

Time Series Data ◽

Short Term Memory ◽

Series Data ◽

Short Term ◽

Term Memory ◽

Long Short Term Memory

Forecasting time-series data are imperative especially when planning is required through modelling using uncertain knowledge of future events. Recurrent neural network models have been applied in the industry and outperform standard artificial neural networks in forecasting, but fail in long term time-series forecasting due to the vanishing gradient problem. This study offers a robust solution that can be implemented for long-term forecasting using a special architecture of recurrent neural network known as Long Short Term Memory (LSTM) model to overcome the vanishing gradient problem. LSTM is specially designed to avoid the long-term dependency problem as their default behavior. Empirical analysis is performed using quantitative forecasting metrics and comparative model performance on the forecasted outputs. An evaluation analysis is performed to validate that the LSTM model provides better forecasted outputs on Standard & Poor’s 500 Index (S&P 500) in terms of error metrics as compared to other forecasting models.

Download Full-text

Detecting Mortality Trends in the Netherlands Across 625 Causes of Death

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16214150 ◽

2019 ◽

Vol 16 (21) ◽

pp. 4150 ◽

Cited By ~ 2

Author(s):

Marianna Mitratza ◽

Anton E. Kunst ◽

Jan W. P. F. Kardaun

Keyword(s):

Causes Of Death ◽

Multinomial Logistic Regression ◽

Linear Regression Models ◽

Short Term ◽

Mortality Trends ◽

Term Trend ◽

Icd 10 ◽

Cubic Model ◽

Long Term Trend

Cause of death (COD) data are essential to public health monitoring and policy. This study aims to determine the proportion of CODs, at ICD-10 three-position level, for which a long-term or short-term trend can be identified, and to examine how much the likelihood of identifying trends varies with COD size. We calculated annual age-standardized counts of deaths from Statistics Netherlands for the period 1996–2015 for 625 CODs. We applied linear regression models to estimate long-term trends, and outlier analysis to detect short-term changes. The association of the likelihood of a long-term trend with COD size was analyzed with multinomial logistic regression. No long-term trend could be demonstrated for 216 CODs (34.5%). For the remaining 409 causes, a trend could be detected, following a linear (211, 33.8%), quadratic (126, 20.2%) or cubic model (72, 11.5%). The probability of detecting a long-term trend increased from about 50% at six mean annual deaths, to 65% at 22 deaths and 75% at 60 deaths. An exceptionally high or low number of deaths in a single year was found for 16 CODs. When monitoring long-term mortality trends, one could consider a much broader range of causes of death, including ones with a relatively low number of annual deaths, than commonly used in condensed lists.

Download Full-text

Pengaruh Variabel Makroekonomi Terhadap Jumlah Penghimpunan Zakat di Indonesia

Jurnal Ekonomi ◽

10.24912/je.v25i2.652 ◽

2020 ◽

Vol 25 (2) ◽

pp. 199

Author(s):

Sheema Haseena Armina

Keyword(s):

Exchange Rate ◽

Time Series Data ◽

Series Data ◽

Short Term ◽

Correction Model ◽

Dollar Exchange Rate ◽

Vector Error Correction ◽

Vector Error ◽

Analysis Technique

Purpose this study analyzes the effect of the industrial production index, the dollar exchange rate, inflation and the BI 7DRR on the amount of zakat collection from January 2015 to December 2018to identify the potential of zakat to support alleviation in Indonesia. Methodology/Approach: this study uses a quantitative approach with a Vector Error Correction Model (VECM) data analysis technique with time series data from Januari 2015 t0 December 2018. Findings: The results show that in short term causality, there is an effect between long-term and short-term between zakat as the dependent variable with inflation and the dollar exchange rate. However, there is no short-term causality effect between BI 7-DRR and IPI to the amount of zakat while the long-term causality effect, all independent variables have a significant effect to the dependent variable namely zakat. Implications: The integration of Islamic philanthropic institutions has the potential to channel aid and support to alleviate poverty. This study adds the IPI variable to interpret the GDP variable in analyzing its effect on zakat.

Download Full-text