scholarly journals Revisiting the effects of relevant factors on Pakistan's agricultural products export

2020 ◽  
Vol 66 (No. 12) ◽  
pp. 527-541
Author(s):  
Zaid Ashiq Khan ◽  
Mansoor Ahmed Koondhar ◽  
Noshaba Aziz ◽  
Uzair Ali ◽  
Liu Tianjun
Keyword(s):  
Error Correction ◽  
National Economy ◽  
Crop Production ◽  
Error Correction Model ◽  
Agricultural Products ◽  
Short Term ◽  
Correction Model ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag

Pakistan is an agriculture-based country, so the agricultural sector is known as the backbone of the national economy. Considering the national economy and the agricultural industry, it is necessary to focus on earnings through agricultural products export to improve the livelihood of local farmers. Therefore, the current study aimed to analyse the short-term and long-term factors affecting agricultural products export. The annual time series of 1976–2016 were collected from World Bank indicators, the Food and Agriculture Organization, and the Statistical Bureau of Pakistan. An autoregressive distributed lag, along with a vector error correction model, was employed. A cointegration test showed long-term associations between the selected variables. While the autoregressive distributed lag model confirmed the short-term correlation between area sown and crop production towards agricultural products export, there is no long-term relationship between the selected variables. In addition, the bidirectional correlation between employment in agriculture and agricultural products export was confirmed by the vector error correction model. Therefore, it is essential to increase agricultural production with the available natural resources to increase foreign earnings.

scholarly journals An Empirical Analysis of Islamic Banking (IBs) Contribution to Indonesia’s Inclusive Growth

2021 ◽  
Vol 4 (SI) ◽  
Author(s):  
Muhammad Yusuf Ibrahim ◽  
Indra Indra
Keyword(s):  
Error Correction ◽  
Statistical Data ◽  
Descriptive Analysis ◽  
Islamic Banking ◽  
Inclusive Growth ◽  
Short Term ◽  
Correction Model ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag

The research is aim to attest and assess empirically the contribution of Islamic banking (IBs) on the inclusive growth in Indonesia. By taking a trial-stage method i.e. descriptive analysis to elaborate a statistical data, autoregressive distributed lag (ARDL) model to assess empirically the contribution in a long-term, and error correction model (ECM) to assess the contribution in a short-term empirically. The findings are, total deposits and total financing only contribute positively significant into GDP and gini ratio in a long-term, that similiar with the previous study. Then, a total financing contribute negatively to all indicators of inclusive growth in a long-term, but, its only significance on GDP and gini ratio. Means, it was contribute significantly to all indicators in a short-term.

scholarly journals The Impact of Exchange Rate on Market Fundamentals: A Case Study of J-curve Effect in Vietnam

2017 ◽  
Vol 9 (1) ◽  
pp. 45 ◽  
Author(s):  
Nguyen Quang My ◽  
Mustafa Sayim ◽  
Hamid Rahman
Keyword(s):  
Exchange Rate ◽  
Error Correction ◽  
Trade Balance ◽  
Short Term ◽  
Correction Model ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
J Curve ◽  
Curve Effect

This study examines if there is an equilibrium relationship between gross domestic product (GDP), exchange rate fluctuation and trade balance in long-term and short-term in Vietnam. The results show that the short-term and long-term exchange rate fluctuations impact the trade balance in Vietnam; both ARDL (Autoregressive Distributed Lag) and ECM (Error Correction Model) methodologies implied that exchange rate has a statistically negatively impact on the trade balance. Particularly, Autoregressive distributed lag (ARDL) utilized to test the long -term impact, shows the trade balance deficit becomes worse when the REER (real effective exchange rate) increases. ECM (Error Correction Model) equation based on the long-term cointegration equation and impulse response, reveals that the domestic currency devaluation could not improve the trade balance, indicating that the J-curve effect does not hold on the dong, the currency of Vietnam.

scholarly journals Non Cash Payment and Demand for Real Money in Indonesia

2019 ◽  
Vol 22 (1) ◽  
Author(s):  
Wasiaturrahma Wasiaturrahma ◽  
Yuliana Tri Wahyuningtyas ◽  
Shochrul Rohmatul Ajija
Keyword(s):  
Error Correction ◽  
Credit Card ◽  
Error Correction Model ◽  
Short Term ◽  
Correction Model ◽  
Real Money ◽  
On Demand ◽  
Cash Payment ◽  
The Impact

The study analyses the impact of non-cash payment on demand for real money in Indonesia from 2010 to 2015. Utilizing the Error Correction Model (ECM), the results reveal that the use of both debit and credit card influence the demand for real money in the long term. Moreover, debit card also significantly affects the demand for real money in the short term, while the use of credit card does not have the implication.

scholarly journals ANALISIS HARGA SAHAM INDEX KOMPAS 100 DENGAN PENDEKATAN ERROR CORRECTION MODEL

2021 ◽  
Vol 4 (1) ◽  
pp. 406-414
Author(s):  
Amir Hamzah
Keyword(s):  
Error Correction ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Financial Statements ◽  
Error Correction Model ◽  
Short Term ◽  
Correction Model ◽  
Positive Effect

The purpose of this research is to analyze the short term and long term relationship between ROI, EPS, PER ,inflation, SBI, exchange rate,and GDP on Stock Price. The data in this research is company financial statements which included Compas 100 Index on the Indonesia Stock Exchange. statistical analysis in this research used stasionarity test, The Classical Assumptions Test, Cointegration Test, Error Correction Model Test. This research found that partially ROI, EPS, PER variables a positive effect on stock prices in the short term and long term, KURS and SBI a positive effect on stock prices in the short term, but there is no effect in the long term, inflation and GDP do not affect the stock price both in the short term and long term. Simultaneously affected the stock prices significantly affect on stock price both in the short term and long term.

scholarly journals Analisis Pengaruh Transaksi Uang Elektronik terhadap Tingkat Inflasi di Indonesia

2021 ◽  
Vol 10 (1) ◽  
pp. 56-63
Author(s):  
Ruth Damayanti
Keyword(s):  
Error Correction ◽  
Money Supply ◽  
Inflation Rate ◽  
Error Correction Model ◽  
Advanced Technology ◽  
Short Term ◽  
Electronic Money ◽  
Correction Model ◽  
The Impact

Increasingly advanced technology encourages people to make transactions using electronic money (e-money). Nowadays, more Indonesian people use electronic money in their dealings, which is proven by the increasing volume of electronic money transactions from year to year. Electronic cash is chosed because it is more practical in making transactions with traders. The rising use of electronic money can affect the money supply, which can affect the inflation rate. Several studies have stated the effect of electronic money on inflation. This study aims to determine the impact of the variable volume and nominal value of electronic money transactions (e-money) on the inflation rate in Indonesia from January 2016 to December 2020. The data used in this study are secondary data with the type of monthly time series taken from Bank Indonesia, Kementerian Perdagangan, and BPS (Badan Pusat Statistik). The analysis technique used is the ECM (Error Correction Model). The Error Correction Model in this study aims to identify long-term and short-term relationships that occur because of the cointegration between research variables and the relationship between variables that are not stationary. This study indicates that in the long term, the variables volume of e-money transactions and money supply (M2) have a significant effect on the inflation variable. In contrast, other macroeconomic variables (BI rate and nominal value of e-money transactions) has no significant impact. Meanwhile, the short-term regression model shows no variables that have a substantial effect on the inflation variable.

scholarly journals Credit Risk Determinants in Indonesia

2018 ◽  
Vol 1 (2) ◽  
pp. 106-115
Author(s):  
Amin Yusuf Efendi
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Credit Risk ◽  
Error Correction ◽  
Error Correction Model ◽  
Series Data ◽  
Short Term ◽  
Correction Model ◽  
Spurious Regression

Credit is the main business of the banking industry, therefore, in running the business, the bank is always overshadowed by the credit risk the which can be determined by the ratio of non-performing loans (NPL). The development of technology, finance digital brings the outside could impact on the financial industry both positive and negative. The purpose of this study was to analyze the interest rate, inflation, exchange rates, gross domestic product (GDP), a dummy finance digitalization policies in the long term and the short term of the non-performing loan (NPL) of conventional commercial banks in Indonesia The analytical method used in this research is-EG Error Correction Model (ECM), The Data used in this research is secondary quarterly time series data from the 2008 quarter 1-2017 4. The time series of data are not stationar Often that can cause spurious regression results, the exact models used is-EG Error Correction Model (ECM), This models may explain the behavior of short-term and long-term. The results Showed in the short-term variable interest rates significanly to non-performing loans, while in the long-term variable interest rate, exchange rate, and GDP Significantly, non-performing loans. Kredit merupakan bisnis utama dari industri perbankan, oleh karena itu dalam menjalankan bisnisnya, bank selalu dibayangi oleh risiko kredit yang dapat diketahui melalui rasio non-performing loans (NPL). Perkembangan teknologi, menghadirkan digital finance yang membawa dampak luar bisa terhadap industri keuangan baik positif dan negatif. Tujuan dari penelitian ini adalah untuk menganalisis suku bunga, inflasi, kurs, produk domestik bruto (PDB) dummy kebijakan digitalisasi keuangan dalam jangka panjang dan jangka pendek terhadap non-performing loan (NPL) bank umum konvensional di Indonesia  Metode analisis yang digunakan dalam penelitian ini adalah Error Correction Model-EG (ECM). Data yang digunakan dalam penelitian ini adalah data sekunder runtut waktu kuartalan dari 2008 kuartal 1 – 2017 kuartal 4. Data runtun waktu sering tidak stationar sehingga bisa menyebabkan hasil regresi palsu (spurious regression), Model yang tepat digunakan adalah Error Correction Model-EG (ECM), model ini dapat menjelaskan perilaku jangka pendek dan jangka panjang. Hasil penelitian menunjukkan dalam jangka pendek variabel suku bunga berpengaruh secara signifikan terhadap non performing loan, sedangkan dalam jangka panjang variabel suku bunga, kurs, dan PDB berpengaruh secara signifikan terhadap non perfoming loan.

scholarly journals PENGARUH NON PERFORMING FINANCING, CAPITAL ADEQUACY RATIO, BEBAN OPERASIONAL PENDAPATAN OPERASIONAL DAN NET IMBALAN TERHADAP RETURN ON ASSETS (STUDI PADA BANK MAYBANK SYARIAH PERIODE 2012-2019)

2021 ◽  
Vol 1 (1) ◽  
pp. 78-93
Author(s):  
Lely Awintasari ◽  
Maulida Nurhidayati
Keyword(s):  
Error Correction ◽  
Error Correction Model ◽  
Capital Adequacy ◽  
Short Term ◽  
Return On Assets ◽  
Correction Model ◽  
Long Run ◽  
Capital Adequacy Ratio ◽  
Short And Long Term

The purpose of this study is to analyze the influence of Non Performing Financing (NPF), Capital Adequacy Ratio (CAR), Operating Expenses operating income (BOPO) and Net Rewards (NI) ratio on Return On Assets of Maybank Syariah Bank. A bank's Return on Assets (ROA) is a ratio that shows the bank's success in making a profit. If the ROA obtained by a small bank as a result of the bank can suffer losses and hinder the growth of the bank. This research is a type of quantitative research with Error Correction Model method with a significance rate of 5%, with a total of 32 samples in the form of quarterly data published by Bank Maybank Syariah in 2012-2019. The findings in this study are that NPF negatively affects ROA in the short term but NPF has no effect on ROA in the long run. CAR has no effect on ROA in the short term but CAR has a positive effect on ROA in the long run. BOPO in the short and long term negatively affects ROA. NI in the short and long term has no effect on ROA. Simultaneously NPF, CAR, BOPO and NI both short-term and long-term affect ROA simultaneously. The amount of influence exerted in the short term is 89.20% while in the long term it is 88.57%. In order to increase ROA, Maybank Syariah Bank as much as possible to reduce the percentage of NPF and BOPO and can increase the CAR owned. Tujuan penelitian ini adalah untuk menganalisis pengaruh rasio kuangan Non Performing Financing (NPF), Capital Adequacy Ratio (CAR), Beban Operasional Pendapatan Operasional (BOPO) dan Net Imbalan (NI) terhadap  Return On Assets Bank Maybank Syariah. Return on Assets (ROA) suatu bank merupakan rasio yang menunjukkan keberhasilan bank dalam menghasilkan keuntungan. Apabila ROA yang diperoleh bank kecil akibatnya bank dapat mengalami kerugian serta menghambat pertumbuhan bank tersebut. Penelitian ini berjenis penelitian kuantitatif dengan metode Error Correction Model dengan tingkat signifikansi 5%, dengan jumlah sampel sebanyak 32 yang berupa data triwulan yang dipublikasikan oleh Bank Maybank Syariah tahun 2012-2019. Temuan pada penelitian ini adalah NPF berpengaruh negatif pada ROA dalam jangka pendek tetapi NPF tidak berpengaruh pada ROA dalam jangka panjang. CAR tidak berpengaruh pada ROA pada jangka pendek namun CAR berpengaruh positif terhadap ROA dalam jangka panjang. BOPO dalam jangka pendek maupun jangka panjang berpengaruh negatif pada ROA. NI dalam jangka pendek maupun jangka panjang tidak berpengaruh pada ROA. Secara simultan NPF, CAR, BOPO dan NI baik jangka pendek maupun jangka panjang berpengaruh terhadap ROA secara simultan. Besarnya pengaruh yang diberikan pada jangka pendek adalah 89,20% sedangkan pada jangka panjang sebesar 88,57%. Untuk dapat meningkatkan ROA, Bank Maybank Syariah sebisa mungkin untuk menurunkan persentase NPF dan BOPO serta dapat meningkatkan CAR yang dimiliki.

scholarly journals The Interaction of Macroeconomic Variables on Capital Inflow in Emerging Market Countries in ASEAN: Panel Error Correction Model Approach

2019 ◽  
pp. 1357-1364
Author(s):  
Hasdi Aimon ◽  
Rika Utami Restihani ◽  
Anggi Putri Kurniadi
Keyword(s):  
Error Correction ◽  
Emerging Market ◽  
Error Correction Model ◽  
Capital Inflow ◽  
Capital Inflows ◽  
Short Term ◽  
Return To Equilibrium ◽  
Correction Model ◽  
Emerging Market Countries

This study investigates the short and long-term determinants of capital inflows in emerging market countries in ASEAN using the Panel Error Correction Model. This study uses panel data with a time series from 2000 to 2017 and a cross-section of five countries (Indonesia, Malaysia, Philippines, Thailand, and Vietnam). This study has three important findings. First, conditions of exchange rate, foreign reserve, and lending rate disrupt the equilibrium of capital inflow in the short term. Second, current account conditions disrupt the equilibrium in the long term. Third, capital inflow will return to equilibrium in the long term. Therefore, it is highly recommended for emerging market countries in ASEAN to stabilize the variables that disrupt the equilibrium in the long and short term to stabilize their capital inflow.

Situation and Forecast of Construction Sector’s Carbon Emission

2012 ◽  
Vol 178-181 ◽  
pp. 718-721
Author(s):  
Rui Jie Liu ◽  
Zhi Hui Zhang
Keyword(s):  
Energy Consumption ◽  
Error Correction ◽  
Driving Force ◽  
Carbon Emission ◽  
Error Correction Model ◽  
Construction Sector ◽  
Short Term ◽  
Correction Model ◽  
Economic Output

In order to describe the carbon emission situation of Chinese construction sector, this paper calculates the construction sector’s carbon emission and its efficiency of year 1994~2008 based on its energy consumption and economic output. And then the error correction model between the carbon emission and the output of the construction sector is established to predict carbon emission, with the effectiveness of the model proved. Using the error correction model, the long-term and short-term resilience of carbon emission is calculated, which indicates the main driving force of construction sector’s carbon emission is the overall output of construction sector.

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