Journal articles: 'ARDL: autoregressive distributed lag'

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Ponziani, Regi Muzio. "Inflation forecasting using autoregressive distributed lag (ARDL) models." Jurnal Ekonomi & Studi Pembangunan 24, no. 2 (2023): 316–30. http://dx.doi.org/10.18196/jesp.v24i2.17620.

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This study attempts to evaluate and compare the inflation-predicting performance of several ARDL models. Since there was no cointegration, the ARDL model does not employ an error correction term. Subsequently, model development showed that ARDL(2,2) should be used. Besides the formally developed model, some other more arbitrarily chosen ARDL models were also included, i.e., ARDL(1,1), ARDL(2,0), ARDL(1,0), ARDL(0,1), and ARDL(0,2). This research measures forecasting performance with inflation as the forecasting object. The duration of the monthly inflation statistics ranged from January 2011 to July 2022. The data were separated into two categories. The training data ranged between January 2011 and December 2021. After getting the appropriate parameters from the training data, the models generated projections from January 2022 to July 2022. The research determined that ARDL (1,0) was the most accurate inflation forecasting model, followed by ARDL (0,2) and formally constructed ARDL(2,2) finished in fourth place. This study suggests that the formal development of ARDL for forecasting purposes is unnecessary. Formal ARDL development is more appropriate for root cause analysis. In addition, the single autoregressive component indicates that most of the inflation value's information originated from the prior period. This suggests that the previous period's value is Indonesia's most significant predictor of inflation. The impact of greater period lags on inflation forecasting diminishes immediately.

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Kripfganz, Sebastian, and Daniel C. Schneider. "ardl: Estimating autoregressive distributed lag and equilibrium correction models." Stata Journal: Promoting communications on statistics and Stata 23, no. 4 (2023): 983–1019. http://dx.doi.org/10.1177/1536867x231212434.

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We present a command, ardl, for the estimation of autoregressive distributed lag (ARDL) models in a time-series context. The ardl command can be used to fit an ARDL model with the optimal number of autoregressive and distributed lags based on the Akaike or Bayesian (Schwarz) information criterion. The regression results can be displayed in the ARDL levels form or in the error-correction representation of the model. The latter separates long-run and short-run effects and is available in two different parameterizations of the long-run (cointegrating) relationship. The popular bounds-testing procedure for the existence of a long-run levels relationship is implemented as a postestimation feature. Comprehensive critical values and approximate p-values obtained from response-surface regressions facilitate statistical inference.

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Handoyo, Samingun, Ying-Ping Chen, Tiara Mawidha Shelvi, and Heni Kusdarwati. "Modeling Vector Autoregressive and Autoregressive Distributed Lag of the Beef and Chicken Meat Prices during the Covid-19 Pandemic in Indonesia." Journal of Hunan University Natural Sciences 49, no. 3 (2022): 220–31. http://dx.doi.org/10.55463/issn.1674-2974.49.3.25.

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The impact of the COVID-19 pandemic has spread to all aspects of life. Modeling the price of beef and chicken meat is very important for the government to avoid extreme fluctuations of both commodities in the prices so that society's purchasing power can be maintained. This study has several objectives, namely building VAR and ARDL models from multiple time series data (beef and chicken meat prices), conducting variable selection with forwarding subset selection on input lag in the ARDL model, and measuring the performance of the VAR and ARDL models on the both of beef and chicken meat prices based on the value of RMSE, MAE, and R_square both in the training and testing set. The novelty in this study is to propose an identification method for the lag inputs of the ARDL model based on the criteria of both the Alkaide Information criteria (AIC) value and the adjusted R square value by visualizing both criteria for all possible amounts of lag inputs. The results of the identification of the VAR model structure using the conventional method in time series modeling are yielded the different lag inputs that are compared to the ARDL model structure with lag inputs identified by using the proposed method. The ARDL model of the beef and chicken meat prices has better performance than the VAR model both on training and testing sets. In addition, the resulting VAR model also clearly shows the occurrence of overfitting problems.

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Siti Afifatul Farichah. "ANALISIS INFLASI DI INDONESIA: PENDEKATAN AUTOREGRESSIVE DISTRIBUTED LAG (ARDL)." Jurnal Cakrawala Ilmiah 1, no. 10 (2022): 2467–84. http://dx.doi.org/10.53625/jcijurnalcakrawalailmiah.v1i10.2577.

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Inflasi diartikan sebagai sebuah peristiwa kenaikan harga beberapa barang dan jasa dimana kenaikan ini terjadi secara berkepanjangan secara umum dari tahun ke tahun. Pemerintah memiliki tujuan jangka Panjang berkaitan dengan Inflasi untuk menjaga kestabilan besarnya inflasi agar tetap stabil pada tingkat nilai yang rendah. Adanya permasalahan inflasi akan berdampak secara langsung terhadap pertumbuhan ekonomi. Pada penelitian ini, penulis hendak mengaanalisis adanya pengaruh Jumlah Uang beredar dan Indeks Harga Konsumen terhadap inflasi di Indonesia. Penelitian ini menggunakan metode penelitian kuantitatif, yaitu sebuah penelitian dimana dalam praktiknya dilakukan dengan menggunakan data sekunder yang diperoleh dari publikasi oleh pihak lain pada suatu kurun waktu tertentu. Sedangkan model yang diterapkan dalam penelitian ini merupakan model Autoregressive Distributed Lag (ARDL). ARDL merupakan salah satu model regresi dimana dalam praktiknya dilakukan dengan menambahkan adanya nilai variabel yang mampu mendiskripsikan nilai masa masa lalu atau nilai masa kini dari variable independen. Berdasarkan hasil estimasi dalam penelitian ini mengindikasikan bahwa terdapat adanya kointegrasi diantara variabel yang digunakan dan model yang didapatkan dari hasil estimasi yang menunjukkan dimana Variabel Jumlah Uang Beredar dan Indeks Harga Konsumen mengindikasikan adanya pengaruh yang signifikan terhadap terjadinya Inflasi di Indonesia baik pada jangka panjang maupun jangka pendek

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Bhowmik, Debesh. "Indian Fiscal Deficit in Autoregressive Distributed Lag (ARDL) Model." Advancement in Management and Technology 05, no. 04 (2025): 01–15. https://doi.org/10.46977/amt.2025.v05i04.001.

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In this paper the author showed the trends of fiscal deficit and examined the short run and the long run nexus between fiscal deficit and gross domestic product per capita, inflation rate (CPI), external debt (% of GDP), unemployment rate (% of labour force), income inequality (income share difference between top 10% and bottom 50%), and military expenditure, respectively, during 1950-51-2023-24 in India by applying Auto Regressive Distributed Lag model. The paper found that the fiscal deficit contains a quadratic trend and denoised wavelet shrinkage. Automatically selected ARDL (3,0,2,3,0,0,3) model, where Akaike Information Criterion (AIC) is minimum, showed that the fiscal deficit is positively associated with inflation and negatively related with debt and per capita GDP significantly in the long run while positively related with inflation and debt and negatively related with military expenditure in the short run significantly. The cointegrating equation states that inflation and debt are directly related and GDP per capita is inversely related to fiscal deficit, and it is converging towards equilibrium at the speed of adjustment of 92% per annum significantly. Unemployment and income inequality have a positive impact on the fiscal deficit in the short and long run insignificantly. The model is stable and contains no serial correlation but contains heteroscedasticity and non-normality. The model demands expenditure-reducing policies in non-plan and defence expenditure, as well as employment and poverty amelioration-oriented fiscal financing at a threshold limit, to achieve sustainable economic growth.

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Efendi, Achmad, Yusi Tyroni Mursityo, Ninik Wahju Hidajati, Nur Andajani, Zuraidah Zuraidah, and Samingun Handoyo. "Multiple Time Series Modeling of Autoregressive Distributed Lags with Forward Variable Selection for Prediction." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 21 (April 19, 2024): 1012–26. http://dx.doi.org/10.37394/23207.2024.21.84.

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The conventional time series methods tend to explore the modeling process and statistics tests to find the best model. On the other hand, machine learning methods are concerned with finding it based on the highest performance in the testing data. This research proposes a mixture approach in the development of the ARDL (Autoregressive Distributed Lags) model to predict the Cayenne peppers price. Multiple time series data are formed into a matrix of input-output pairs with various lag numbers of 3, 5, and 7. The dataset is normalized with the Min-max and Z score transformations. The ARDL predictor variables of each lag number and dataset combinations are selected using the forward selection method with a majority vote of four criteria namely the Cp (Cp Mallow), AIC (Akaike Information Criterion), BIC (Bayesian Information Criterion), and adjusted R2 . Each ARDL model is evaluated in the testing data with performance metrics of the RMSE (Root Mean Square Error), MAE (Mean Absolute Error), and R2 . Both AIC and adjusted R2 always form the majority vote in the determining optimal predictor variable of ARDL models in all scenarios. The ARDL predictor variables in each lag number are different but they are the same in the different dataset scenarios. The price of Cayenne pepper yesterday is the predictor variable with the most contribution in all of the 9 ARDL models yielded. The ARDL lag 3 with the original dataset outperforms in the RMSE and MAE metrics while the ARDL lag 3 with the Z score dataset outperforms in the R2 metric.

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Ningrum, Dewi Kusuma, and Sugiyarto Surono. "Comparison the Error Rate of Autoregressive Distributed Lag (ARDL) and Vector Autoregressive (VAR) (Case study: Forecast of Export Quantities in DIY)." JURNAL EKSAKTA 18, no. 2 (2018): 167–77. http://dx.doi.org/10.20885/eksakta.vol18.iss2.art8.

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Forecasting is estimating the size or number of something in the future. Regression model that enters current independent variable value, and lagged value is called distributed-lag model, if it enters one or more lagged value, it is called autoregressive. Koyck method is used for dynamic model which the lagged length is unknown, for the known lagged length it is used the Almon method. Vector Autoregressive (VAR) is a method that explains every variable in the model depend on the lag movement from the variable itself and all the others variable. This research aimed to explain the application of Autoregressive distributed-lag model and Vector Autoregressive (VAR) method for the forecasting for export amount in DIY. It takes export amount in DIY and inflation data, kurs, and Indonesias foreign exchange reserve. Forecasting formation: defining Koyck and Almon distributed-lag dynamic model, then the best model is chosen and distribution-lag dynamic forecasting is performed. After that it is performed stationary test, co-integration test, optimal lag examination, granger causality test, parameter estimation, VAR model stability, and performs forecasting with VAR method. The forecasting result shows MAPE value from ARDL method obtained is 0.475812%, while MAPE value from VAR method is 0.464473%. Thus it can be concluded that Vector Autoregressive (VAR) method is more effective to be used in case study of export amount in DIY forecasting. Keywords: Koyck; Almon; Lag; Autoregressive Distributed-Lag; Vector Autoregressive;

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Abedi, Ali, Mohammad Mousavi Baygi, Parinaz Poursafa, et al. "Air pollution and hospitalization: an autoregressive distributed lag (ARDL) approach." Environmental Science and Pollution Research 27, no. 24 (2020): 30673–80. http://dx.doi.org/10.1007/s11356-020-09152-x.

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Sukmana, Rania, Tarno Tarno, and Puspita Kartikasari. "PEMODELAN AUTOREGRESSIVE DISTRIBUTED LAG UNTUK MEMPREDIKSI NILAI IMPOR NON-MIGAS DI INDONESIA." Jurnal Gaussian 13, no. 2 (2025): 499–508. https://doi.org/10.14710/j.gauss.13.2.499-508.

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The International Monetary Fund warns countries about the global economic recession in 2023. Efforts required from policy makers to prevent a recession. A deficit balance of payments shows signs of recession because the rate of imports is higher than exports. The highest import value over the last decade is non-oil and gas commodities. Factors affecting imports include exchange rates, prices of goods, and consumer income. Import activities require proper studies to make policies so that research is needed, one of which is by using the Autoregressive Distributed Lag (ARDL) method. ARDL is a regression model in which the independent variable consists of the current and past independent variable values and the past values of the dependent variable. The data used is from the first quarter of 2008 to the fourth quarter of 2022. The model formed is ARDL(3,2,2,1). The current non-oil and gas import is positively affected by the non-oil and gas imports at lag one, three, and four, as well as the exchange rate at lag three and is negatively affected by the non-oil and gas import and the exchange rate at lag two. The accuracy of forecasting with sMAPE is 12,12%, which means the forecast is accurate.

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Kriskkumar, Karunanithi, Niaz Ahmad Mohd Naseem, and Wan Ngah Wan Azman-Saini. "Investigating the Asymmetric Effect of Oil Price on the Economic Growth in Malaysia: Applying Augmented ARDL and Nonlinear ARDL Techniques." SAGE Open 12, no. 1 (2022): 215824402210799. http://dx.doi.org/10.1177/21582440221079936.

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This paper attempts to investigate if the effect of oil price on growth is asymmetrical for Malaysia, a small-open-dynamic oil-exporting country, over a period from 1981 to 2017. The empirical method employed in this study is the augmented autoregressive distributed lag model (ARDL) bound test approach and the recent innovative nonlinear autoregressive distributed lag (NARDL) model. Results suggest that neglecting nonlinearities can lead to misleading results. More precisely, the result reveals that adjustments in the price of oil influence Malaysia’s economic growth asymmetrically. An increase and decrease in the price of oil strengthen the economic growth of Malaysia, demonstrating Malaysia’s ability to be both an oil-producing country and a trading nation. These results strongly imply that Malaysia is able to take advantage of changes in the oil price efficiently.

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Thi, Ha Tran, Quang Dong Nguyen, and Anh Duc Le. "The Asymmetric Impact of Exchange Rate Changes on Bilateral Trade between Vietnam and the US: Does the COVID-19 Pandemic Matter?" International Journal of Economics and Financial Issues 15, no. 1 (2024): 386–96. https://doi.org/10.32479/ijefi.17607.

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This study examines the relationship between the exchange rate and the Vietnam-US trade balance by employing a combination of Autoregressive Distributed Lag (ARDL) and non-linear Autoregressive Distributed Lag (NARDL) approaches with disaggregated data from 21 industries from 2008 to 2022. The findings reveal that, in both ARDL and NARDL models, a real Vietnamese Dong (VND) depreciation does not significantly impact on the aggregated trade balance in the long-run. The results provide evidence of an asymmetric impact of the real exchange rate on the trade balance. These findings also suggest that the COVID-19 pandemic may have induced structural breaks in the relationship between exchange rates and trade balances, leading to increased sensitivity of trade balances to exchange rate movements.

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Nurdiansyah, Denny, and Agus Sulistiawan. "PEMODELAN JUMLAH KASUS DEMAM BERDARAH DENGUE DENGAN MENGGUNAKAN MODEL AUTOREGRESSIVE DISTRIBUTED LAG." Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika 4, no. 3 (2023): 1965–77. http://dx.doi.org/10.46306/lb.v4i3.526.

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This study aims to model dengue hemorrhagic fever (DHF) cases with an autoregressive distributed lag (ARDL) model to investigate significant predictor variables in Bojonegoro Regency. The selected predictor variables are the percentage of poverty, population, health facilities, and health workers. A research design with a quantitative approach was used to investigate the predictor variables in dengue cases with the ARDL model and the help of EViews. Stationarity, cointegration, classical assumptions, parameter significance, and model goodness assessment, namely R-square, MSE, AIC, and SBC, were tested. The research data source is secondary data, namely annual data from the reports of the Central Bureau of Statistics and the Health Office in Bojonegoro Regency from 2008 to 2022. The test results show only cointegration in the response variable, so the ARDL model is applied, but the lag distribution is only done on the response variable. In testing the significance of the parameters, it was found that an increase in the health workforce significantly affected the decrease in the number of DHF patients. At the same time, the other predictor variables were not significant

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Rahmasari, Aulia, Eka Hawari Sunani, Miftahul Jannah, Fathulaili Fathulaili, Linda Kurnia, and Ahmad Satria. "ARDL Method: Forecasting Data Kemiskinan di NTB." JTAM | Jurnal Teori dan Aplikasi Matematika 3, no. 1 (2019): 52. http://dx.doi.org/10.31764/jtam.v3i1.767.

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Abstrak: Penelitian ini bertujuan untuk memprediksi data Jumlah penduduk miskin di Provinsi Nusa Tenggara Barat (NTB) tahun 2019 dengan menggunakan metode Autoregressive Distributed Lag (ARDL). Jenis penelitian ini merupakan penelitian kuantitatif. Data yang digunakan dari tahun 2002-2018, dengan parameter error MAD, MSE, MRSE dan MAPE. Berdasarkan hasil simulasi data diperoleh hasil prediksi tahun 2019 jumlah penduduk miskin di NTB sebesar 718.059 jiwa, dengan nilai MAD sebesar 4.040,26667, MSE sebesar 1.943.057.717, MRSE sebesar 44.080,1284 dan MAPE sebesar 3%.  Abstract: This study aims to predict data on the number of poor people in the Province of West Nusa Tenggara (NTB) in 2019 by using the Autoregressive Distributed Lag (ARDL) method. This type of research is quantitative research. Data used from 2002-2018. With MAD, MSE, MRSE and MAPE error parameters. Based on the data simulation results obtained in 2019 prediction results the number of poor people at NTB is 718,059 people, with MAD value of 4,040,26667, MSE of 1,943,057,717, MRSE of 44,080,1284 and MAPE of 3%.

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Chikri, Hassan, Adil Moghar, Manar Kassou, and Faris Hamza. "New evidence from NARDL model on CO2 emissions: Case of Morocco." E3S Web of Conferences 234 (2021): 00026. http://dx.doi.org/10.1051/e3sconf/202123400026.

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The main objective of this study is to examine the effect of sickle energy consumption, renewable energy, and forest area on the emission of carbon dioxide (CO2) in Morocco. Many studies have abord this subject using a different approachs, most of which have used econometric models such as Vector Autoregressive (VAR) Error Correction Model (ECM) and Autoregressive Distributed Lag (ARDL). In this study, we opted for the Non-linear Autoregressive Distributed Lag (NARDL) model. The data used covers the period from 1990 to 2018 (annual data). The results of our model are significant and prove the asymmetric effects of the explanatory variables on CO2 emissions.

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Sapra, Sunil. "A comparative study of parametric and semiparametric autoregressive models." International Journal of Accounting and Economics Studies 10, no. 1 (2022): 15–19. http://dx.doi.org/10.14419/ijaes.v10i1.31978.

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Dynamic linear regression models are used widely in applied econometric research. Most applications employ linear autoregressive (AR) models, distributed lag (DL) models or autoregressive distributed lag (ARDL) models. These models, however, perform poorly for data sets with unknown, complex nonlinear patterns. This paper studies nonlinear and semiparametric extensions of the dynamic linear regression model and explores the autoregressive (AR) extensions of two semiparametric techniques to allow unknown forms of nonlinearities in the regression function. The autoregressive GAM (GAM-AR) and autoregressive multivariate adaptive regression splines (MARS-AR) studied in the paper automatically discover and incorporate nonlinearities in autoregressive (AR) models.Â Performance comparisons among these semiparametric AR models and the linear AR model are carried out via their application to Australian data on growth in GDP and unemployment using RMSE and GCV measures.Â Â

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O. Manasseh, Charles, Ifeoma C. Nwakoby, Felicia C. Abada, Felix C. Alio, and Ogochukwu Okanya. "Money Demand in Nigeria: Application of Autoregressive Distributed Lag (ARDL) Approach." Asian Economic and Financial Review 11, no. 4 (2021): 308–21. http://dx.doi.org/10.18488/journal.aefr.2021.114.308.321.

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Dewi, Fitri Kurnia, and Heri Sudarsono. "Analisis Profitabilitas Bank Syariah Di Indonesia: Pendekatan Autoregressive Distributed Lag (ARDL)." Al-Mashrafiyah: Jurnal Ekonomi, Keuangan, dan Perbankan Syariah 5, no. 1 (2021): 59. http://dx.doi.org/10.24252/al-mashrafiyah.v5i1.20281.

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AQIBAH, MAHMUDATUL, NI LUH PUTU SUCIPTAWATI, and I. WAYAN SUMARJAYA. "MODEL DINAMIS AUTOREGRESSIVE DISTRIBUTED LAG (STUDI KASUS: PENGARUH KURS DOLAR AMERIKA DAN INFLASI TERHADAP HARGA SAHAM TAHUN 2014-2018)." E-Jurnal Matematika 9, no. 4 (2020): 240. http://dx.doi.org/10.24843/mtk.2020.v09.i04.p304.

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The aim of this research is to determine the dynamic model equation of autoregressive distributed lag by using koyck method, to find out the effect of log US dollar exchange rate and log inflation on log stock price in 20142018, and to forecast value of log stock price on January 2019August 2019. The data used in 20142018. The data was transformed into logarithm format. Time series plot of log US dollar exchange rate, log inflation, and log stock price suggest that the fluctuation in the data, for instance, both upward and downward trends, during the period. We obtained that the Koyck transformation could changed the lag distribution model into autoregressive distributed lag (ARDL) dynamic model. Furthermore, the log of US dollar exchange rate and log inflation have negative effect on log stock price in particular period. We measured forecasting accuracy using mean absolute prediction error (MAPE) and concluded that ARDL forecasting using Koyck model shows a significant increase in stock price.

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Gürel, Sinem Pınar. "The validity of the Fisher effect for an inflation targeting country." Ekonomski pregled 72, no. 5 (2021): 697–717. http://dx.doi.org/10.32910/ep.72.5.3.

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The aim of this paper is to investigate the relationship between interest and inflation rates. In this regard, the validity of the Fisher Effect under an inflation targeting regime country is examined by considering the possibility of non-linearities. To this aim, the Fisher Effect is analysed by using various types of interest rates to identify the short-, mid- and long-term dynamics. Autoregressive distributed lag (ARDL) and non-linear autoregressive distributed lag (NARDL) models were estimated for Turkish economy between 2006-2019 periods. The empirical findings of ARDL models reveal the validity of Fisher Effect both for short and long run. The results of NARDL models indicate a strong Fisher Effect in the long run, except for 5-year government bonds. For short-run, the Fisher Effect holds only when inflation rises and there is no significant result when inflation decreases.

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My, Nguyen Quang, Mustafa Sayim, and Hamid Rahman. "The Impact of Exchange Rate on Market Fundamentals: A Case Study of J-curve Effect in Vietnam." Research in Applied Economics 9, no. 1 (2017): 45. http://dx.doi.org/10.5296/rae.v9i1.11019.

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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.

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CHRIS, OGBECHIE, and OSEMENSHAN ANETOR FRIDAY. "DETERMINANTS OF CAPITAL FLOWS INTO NIGERIA: AN AUTOREGRESSIVE-DISTRIBUTED LAG (ARDL) APPROACH." Journal of Economics and Trade 1, no. 1 (2016): 38–50. https://doi.org/10.5281/zenodo.1404019.

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The rate of capital flows into the emerging markets is alarming and has become a subject of debate in the literature. It is mostly believed that capital flows are beneficial to the economies of the developing countries as it engenders the efficient allocation of global resources thereby increasing the availability of capital required for investment and economic growth. Despite the general belief, the macroeconomic variables that determine capital flows remain controversial. In the light of this, the study attempted to examine the long-run and short-run determinants of capital flows into Nigeria. The study employed secondary data sourced from the Central Bank of Nigeria (CBN), FRED Economic data, and World Development Indicator between the periods of 1986-2014. Using the econometric technique of Autoregressive Distributed Lag Model (ARDL), the study found that exchange rate (LnEXR<strong>) </strong>and stock market prices (LnSP) are important determinants of capital flows into Nigeria both in the short-run and long-run. It is, therefore, recommended that the government, through its policies, should make concerted effort in boosting the activities at the stock market in a bid to attract capital flows into the country.

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Faudzi, Maman, and Gea Dwi Asmara. "Analisis Neraca Perdagangan Indonesia: Pendekatan ARDL." Journal of Macroeconomics and Social Development 1, no. 1 (2023): 1–16. http://dx.doi.org/10.47134/jmsd.v1i1.17.

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Abstrak: Penelitian ini dilakukan untuk mengetahui pengaruh serta hubungan antar variabel Kurs, Jumlah Uang Beredar (M2), Inflasi, dan Cadangan Devisa terhadap Neraca Perdagangan Indonesia tahun 1986-2021. Data yang digunakan dalam penelitian ini adalah data time series dalam bentuk tahunan yang didapat dari web resmi World Bank dan Bank Indonesia (BI). Penelitian ini dibangun dengan model Autoregressive Distributed Lag (ARDL) dan diolah menggunakan software Eviews10. Dengan menggunakan Maximum Lag sebesar 2. Dari hasil olah data yang dilakukan menunjukkan bahwa dalam jangka pendek semua variabel berpengaruh secara signifikan terhadap neraca perdagangan, sedangkan dalam jangka panjang semua variabel berpengaruh secara signifikan kecuali variabel inflasi. Nilai R-square pada model ARDL yang dibentuk menunjukkan sebesar 85% memiliki korelasi yang dapat dijelaskan dalam model, sedangkan sebesar 15% dijelaskan oleh variabel di luar model.  Abstract: between Kurs, Broad Money (M2), Inflation, and Exchange Reserve to Indonesia’s Trade Balance on 1986-2021. The data used in this research is time series in annual which from official website of World Bank and Bank Indonesia (BI). The study was built with an Autoregressive Distributed Lag (ARDL) and processed with Eviews10 software. Using a maximum lag of two. The results of data processing found that that all variables in the model have a significant effect in short-term to trade balance, whereas in long-term all variables have a significant effect unless inflation. R-square values in ARDL model show that 85% of the correlation described in models, whereas 15% is explained by variables outside of models.

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Shittu, Olanrewaju I., Raphael A. Yemitan, and OlaOluwa S. Yaya. "ON AUTOREGRESSIVE DISTRIBUTED LAG, COINTEGRATION AND ERROR CORRECTION MODEL: An Application to Some Nigeria Macroeconomic Variables." Australian Journal of Business and Management Research 02, no. 08 (2012): 56–62. http://dx.doi.org/10.52283/nswrca.ajbmr.20120208a07.

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This paper reviews the use of the traditional ARDL and the ARDL approach to cointegration for the analysis of short-run dynamic and long run relationship when series are difference stationary (series can be integrated of different orders). The two models were used to estimate the short-run dynamics and the long run relationships between selected Nigeria’s macroeconomic series. The results compares favorably with the theory that the ARDL is equivalent to the short-run dynamics of the error correction model (the resultant model from the ARDL approach to cointegration).

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Nulhanuddin, Nulhanuddin, and Devi Andriyani. "Autoregressive Distributed Lag Kurs Dan Ekspor Karet Remah Terhadap Pertumbuhan Ekonomi Indonesia." Jurnal Ekonomi Regional Unimal 3, no. 2 (2020): 47. http://dx.doi.org/10.29103/jeru.v3i2.3205.

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This study aims to determine the effect of short-term and long-term exchange rates and crumb rubber exports on the economic growth of Indonesia. The data used are secondary data for 39 years from 1980 to 2018 accessed on www.world.bank.wdi.data.bank.org, www.pertanian.go.id, www.bps.go.id, and www.bps.go.id. The data analysis method used is the Autoregressive Distributed Lag (ARDL) approach with the help of EViews 10 software. The results show that the economic growth is stationary at the level and exchange rate and exports of stationary crumb rubber at the first difference level and have cointegration in the long-term relationship. The test results in the short-term analysis of the exchange rate have a positive and significant effect, and exports have a positive but insignificant effect on economic growth, while in the long run, the exchange rate has a negative effect but insignificant, and exports have a positive but insignificant effect on the economic growth of Indonesia. Keywords:economic growth, exchange rates, exports and the ARDL approach.

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Sihem, Boudeb. "An Econometric Estimation of Impact of Economic Growth on Employment in Algeria during the Period (1994- 2018)." Milev Journal of Research and Studies 6, no. 1 (2020): 210–29. http://dx.doi.org/10.58205/mjrs.v6i1.454.

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This paper aims at measuring the impact of economic growth on employment in Algeria during the period 1994- 2018. Using an Autoregressive Distributed Lag (ARdl) Model, the results show that the economic growth rates are insufficient to reduce unemployment rates

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Almosabbeh, Imadeddin Ahmed. "Is the Relationship Between Government Spending and Private Consumption in Egypt Symmetric?" Margin: The Journal of Applied Economic Research 14, no. 3 (2020): 285–308. http://dx.doi.org/10.1177/0973801020920096.

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The aim of this study, using Egyptian data from 1970 to 2016, is to explore the relationship between government spending and private consumption spending and to understand whether the relationship between the two is symmetric. The study uses the autoregressive distributed lag (ARDL) approach to explore a cointegration relationship between the two variables, and the nonlinear autoregressive distributed lag (NARDL) approach to test the hypothesis of a symmetric relationship between the two variables. By applying the ARDL approach, the study concludes that the effect of government spending on consumption spending is not significant in the long term. By applying the NARDL approach, the study concludes that: the hypothesis of the presence of a symmetric relationship is not accepted, there is a crowding-out relationship from the positive shocks of government spending and the substitutability coefficient between the two types of spending is 0.8699. JEL Classification: E12, E21, F62, H50

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Syafitri, Aidillia, Sri Ulfa Sentosa, and Dwirani Puspa Artha. "Dampak Nilai Tukar (Kurs) terhadap Neraca Pembayaran di Indonesia: Pendekatan Autoregressive Distributed Lag." Jurnal Kajian Ekonomi dan Pembangunan 7, no. 1 (2025): 21. https://doi.org/10.24036/jkep.v7i1.17252.

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The purpose of this study is to determine how the exchange rate (Kurs) affects the balance of payments in Indonesia. This study uses time series data from 1993-2023. The analysis technique used is Autoregressive Distributed Lag (ARDL). Based on the ARDL test, the exchange rate has a positive relationship and a significant effect on the balance of payments in the short term, while in the long term the exchange rate has a positive relationship but has no significant effect on the balance of payments. National income and interest rates have a negative relationship and have a significant effect on the balance of payments in the short term, while in the long term national income and interest rates have no significant effect but have a negative relationship on the balance of payments.

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Ekananda, Mahjus, and T. Suryanto. "The Autoregressive Distributed Lag Model to Analyze Soybean Prices in Indonesia." MATEC Web of Conferences 150 (2018): 05035. http://dx.doi.org/10.1051/matecconf/201815005035.

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The main objective of this study was to observe factors that affecting domestic soybean prices, including government intervention through BULOG. By using Bound Testing Cointegration method with ARDL approach. In the short term the world soybean price variables in the t-period and exchange rate affect the domestic soybean prices positively and significantly. The variable volume of soybean imports, GDP, and the role of BULOG as sole importer in the t-period does not affect the domestic soybean price significantly. In the long run, the t-period import tariff has a negative and significant effect.

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Yasser, Mai, Doaa Salman, and Mohamed Essam. "HDI, Oil Prices, Government Expenditures in GCC: Evidence from a Cross Sectional ARDL Approach." Ekonomika 103, no. 3 (2024): 91–105. http://dx.doi.org/10.15388/ekon.2024.103.3.6.

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This study explores the relationship between oil prices and the Human Development Index (HDI) in the Gulf Cooperation Council (GCC) countries. It investigates whether oil prices remain the primary driver of economic growth and development in the region. The analysis employs a Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) approach and Cointegrated Autoregressive Distributed Lag (CCEMG) methods, following unit root and stationarity tests. The findings reveal an insignificant correlation between oil prices and HDI in the overall GCC countries. However, significant relationships are observed at the individual country level. These results suggest that policymakers in the region should prioritize economic diversification and focus on sectors such as tourism in Dubai and the specific policies implemented in Saudi Arabia to foster sustainable development.

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Syrbek, Perizat, Laila Bimendiyeva, Saltanat Kondybayeva, Aigul Tlesova, and Adil Tolepov. "Nexus between Energy Intensity, CO2 Emissions and Food Security: Asymmetric and Symmetric View from Kazakhstan." International Journal of Energy Economics and Policy 15, no. 2 (2025): 616–23. https://doi.org/10.32479/ijeep.18486.

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The aim of this study is analyzed nexus between energy intensity, CO2 emissions with food security in Kazakhstan. As dependent Food security indicator food production index and for energy intensity indicator Energy intensity level of primary energy were taken. As socio-economic indicators GDP per capita and population growth are taken. Data cover 2000-2021 years and extracted from World Bank Data and Worldometers. As research methods Nonlinear Autoregressive Distributed Lag (NARDL) Analysis and Linear Autoregressive Distributed Lag (ARDL) were applied. According to NARDL method, Fossil CO2 emissions and GDP per capita found to be main factors from selected ones to affect food production index positively. CO2 emissions (total) have positive effect on Food production index too. According to ARDL method, change in population correlated positively with Food Production index in long term. Energy intensity impacts negatively in short term and positively in long term on Food Production Index. Results imply that in Food production ecofriendly methods and new technology should be prioritized.

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Harahap, Choirunnisa Tri Ana, Rocky Ardiansyah Habibi Harahap, and Utari Evy Cahyani. "The Nexus Of Zakat, Infaq and Sadaqah (ZIS) And Economic Growth in Indonesia: ARDL Method." Journal of Islamic Social Finance Management 5, no. 1 (2024): 20–28. https://doi.org/10.24952/jisfim.v5i1.10498.

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Zakat, Infaq and Sadaqah is an instrument of Islamic philanthropy that has an important role in society and can encourage economic growth through income redistribution and reduction of social inequality in Indonesia. For a Muslim, it is obligatory to pay zakat, while spending money on infaq and sadaqah is sunnah. Zakat, Infaq and Sadaqah funds are expected to be channeled to the poor who need (mustahik) to improve their welfare in order to achieve economic growth of the Indonesian people. The period in this study is Zakat, Infaq and Sadaqah and Economic Growth in Indonesia 2002-2019. This research uses the Autoregressive Distributed Lag (ARDL) method. This type of research is quantitative research with data analysis techniques using the Autoregressive Distributed Lag (ARDL) method and data processing using the Eviews 10 application. The results showed that Zakat, Infaq, and Sadaqah (ZIS) in the long run had an effect on Economic Growth in Indonesia that expected to be a policy for the government in managing ZIS funds.

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draibati, yassera, Mahmoud Mohammad, and malak atwez. "Estimating Agricultural Production Function in Syria using Autoregressive Distributed Lag Approach) ARDL(." Journal of Agricultural Economics and Social Sciences 11, no. 12 (2020): 1101–7. http://dx.doi.org/10.21608/jaess.2021.57356.1001.

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Yong, Wan-Lin, Jerome Kueh, Yong Sze Wei, and Jang-Haw Tiang. "Energy Consumption and Economic Growth Nexus in China: Autoregressive Distributed Lag (ARDL)." Journal of Public Administration and Governance 10, no. 2 (2020): 194. http://dx.doi.org/10.5296/jpag.v10i2.16900.

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This paper intends to investigate the nexus between energy consumption, carbon dioxide emission, total export and economic growth of China from 1971 to 2014. This study adopted Autoregressive Distributed Lag (ARDL) bounds test to examine the existence of short-run and long-run relationships among the variables. Empirical findings indicated that energy consumption contribute to economic growth while carbon dioxide emission is impeding the growth. There is a positive long-run relationship between both energy consumption and total export with economic growth of China. However, a negative relationship is observed between carbon dioxide emissions and economic growth. Hence, in terms of policy recommendation, policymakers can implement a balance environment-economic policy; reduce the carbon dioxide emission by imposing carbon tax; promote renewable energy among the industries and households and promoting reserves forest policy is needed for aspiration of sustainable growth for both environmental and economic.

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Kueh, Jerome, and Yong Sze Wei. "FDI-Led-Growth in Malaysia: Autoregressive Distributed Lag (ARDL) Bounds Testing Approach." International Business Research 11, no. 11 (2018): 46. http://dx.doi.org/10.5539/ibr.v11n11p46.

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This study intends to investigate the validity of the foreign direct investment, FDI-led-growth hypothesis in Malaysia in this era. Autoregressive Distributed Lag (ARDL) bounds test approach is adopted to examine the impact of FDI inflow towards growth of Malaysia based on annually data from 1980 to 2016. Empirical results indicate that FDI inflow has significant positive impact on economic growth. This implies that FDI inflow remain important tool for stimulating economic growth of Malaysia. In addition, there is a negative impact of FDI inflow on economic growth during the 1997 Asian Financial crisis and positive impact during the 2008 Global Financial crisis. In terms of policy recommendation, the policy makers should continue to develop strategies to further attract FDI that will contribute to increasing the productivity in the country.

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Lee, Kyung-Hee and Kyung Soo Kim. "A Study on Estimating Tourism Elasticities using Autoregressive Distributed Lag(ARDL) model." Management & Information Systems Review 36, no. 2 (2017): 81–92. http://dx.doi.org/10.29214/damis.2017.36.2.005.

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Nteegah, Alwell, and Polycarp Ihejirika. "Energy Access and Poverty in Nigeria: An Autoregressive Distributed Lag (ARDL) Investigation." Asian Research Journal of Current Science 6, no. 1 (2024): 271–82. https://doi.org/10.56557/arjocs/2024/v6i1122.

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Mahira, Ulfa, and Hijri Juliansyah. "PENGARUH EKSPOR KARET ALAM DAN INFLASI TERHADAP CADANGAN DEVISA DI INDONESIA." JURNAL EKONOMIKA INDONESIA 11, no. 2 (2022): 22. http://dx.doi.org/10.29103/ekonomika.v11i2.9853.

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Penelitian ini bertujuan mengetahui ekspor karet alam dan inflasi terhadap cadangan devisa Indonesia. Jenis data dalam penelitian ini adalah time series dari tahun 1970 hingga 2019 dengan menggunakan metode analisis penelitian Autoregressive Distributed Lag (ARDL). Hasil analisis data berdasarkan model ARDL menunjukan variabel ekspor karet alam dalam jangka pendek dan jangka panjang memiliki pengaruh positif dan signifikan terhadap cadangan devisa. Sedangkan variabel inflasi baik dengan menggunakan model ARDL diperoleh hasil baik pada jangka pendek maupun jangka panjang tidak terdapat pengaruh signifikan terhadap cadangan devisa Indonesia..

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Okuduwor A. A, Amadi Robert C.C, and Udi O.F. "Assessing Agricultural Export Evidence on Economic Growth in Nigeria (1999-2020)." International Journal of Business and Applied Economics 2, no. 2 (2023): 79–96. http://dx.doi.org/10.55927/ijbae.v2i2.2312.

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This study examined the impact of agriculture export on economic growth in Nigeria from 1999 to 2020. Specifically, the study investigated the impact of agriculture exports (as percentage of merchandize export), exchange rate and trade openness on economic growth (measured using gross domestic product growth rate). Annual data used for the study were sourced from World Development Indicator (WDI) and Central Bank of Nigeria (CBN) Statistical Bulletin. The study used econometric techniques of Augmented Dickey-Fuller (ADF), bound test and autoregressive distributed lag (ARDL) for empirical analysis. The results of unit root suggested that GDP growth rate and agriculture export were stationary while exchange rate and trade openness were non-stationary of order one. The findings from the autoregressive distributed lag (ARDL) method show that agriculture export contribute positive to economic growth. Exchange rate has a positive and significant impact on the Nigerian economy. Furthermore, the ARDL result show that trade openness has a positive and insignificant impact on economic growth. It was recommended that the Federal Government should formulate policies that will increase investment in the agriculture sector in order to optimize its positive contribution to the Nigerian economy.

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APAN, Mehmet, Hüseyin KARAMELİKLİ, Mehmet İSLAMOĞLU, and Hakim AZİZ. "The Symmetric and Asymmetric Relationship Between the Ratio of Non-Performing Loans and the Return on Equity: Evidence from Borsa İstanbul." International Journal of Contemporary Economics and Administrative Sciences 14, no. 2 (2024): 642–61. https://doi.org/10.5281/zenodo.14608886.

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<strong>Abstract</strong> The Non-Performing Loans (NPL) ratio is an important indicator of banks' success in credit management in the banking industry. With the increase in this ratio, banks' profitability is adversely affected. This study investigates the short and long-term asymmetric relationship between NPLs and the Return On Equity (ROE) of banks listed on the Borsa Istanbul (BIST) using quarterly data from 2008:Q1-2017:Q4. We have formulated four different models for each bank with Autoregressive Distributed Lag (ARDL), and Non-Linear Autoregressive Distributed Lag (NARDL) to evaluate the relationship between the selected variables. After our evaluation, the empirical results show a long-term asymmetric relationship between ROE and NPLs for most banks in BIST.

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Ahmad Ridha, Nurjannah, and Ratna Mutia. "Analisis Permintaan Uang di Indonesia: Pendekatan Autoegressive Distributed lag (Ardl)." Jurnal Samudra Ekonomika 5, no. 2 (2021): 152–60. http://dx.doi.org/10.33059/jse.v5i2.4273.

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Penelitian ini mengkaji permintaan uang di Indonesia dengan menggunakan pendekatan autoregressive distributed lag (ARDL). Tujuan dari penelitian ini adalah untuk mengetahui fungsi permintaan uang di Indonesia dan faktor-faktor yang mempengaruhinya selama periode 1990:1-2019:4 dengan menggunakan data kuartal. Ada dua persamaan estimasi untuk uang sempit (M1) dan uang luas (M2). Hasil pengujian bounds testing menunjukkan bahwa ada hubungan jangka panjang yang stabil antara permintaan uang dan determinannya. Hasil persamaan pertama (M1) dalam jangka panjang variabel GDP dan inflasi bertanda positif sedangkan suku bunga dan nilai tukar bertanda negatif, dan semua variabel independen berpengaruh signifikan, yang ditunjukkan dengan nilai probabilitas kurang dari 0,05. Pada persamaan kedua (M2) dalam jangka panjang, variabel GDP dan nilai tukar menunjukkan arah positif sedangkan variabel inflasi memiliki arah negatif. Semua variabel independen berpengaruh signifikan terhadap permintaan uang di Indonesia kecuali variabel suku bunga. Nilai koefesien determinasi R2 untuk persamaan pertama sebesar 0,857 sedangkan persamaan kedua sebesar 0,807. Hasil pengujian CUSUM dan CUSUMQ untuk kedua model analisis stabil dalam jangka panjang.

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Hakim, Lukman, and Akmal Riza. "THIRD PARTY FUNDS AND WORKING CAPITAL FINANCING AT ISLAMIC BANKS IN INDONESIA: ARDL-ECM APPROACH." An-Nisbah: Jurnal Ekonomi Syariah 10, no. 2 (2024): 135–48. http://dx.doi.org/10.21274/an.v10i2.8712.

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Abstrak: Penelitian ini bertujuan untuk menganalisis pengaruh dana pihak ketiga dan tingkat margin pembiayaan terhadap realisasi pembiayaan modal kerja yang disalurkan bank syariah pada sektor UMKM di Indonesia. Menggunakan data time series selama periode 2014.6-2018.9, model analisis yang digunakan adalah autoregressive distributed lag (ARDL). Penelitian mengungkapkan adanya hubungan kointegrasi jangka panjang antara realisasi pembiayaan dengan dana pihak ketiga dan tingkat margin pembiayaan. Dalam jangka panjang dan jangka pendek, dana pihak ketiga berpengaruh positif dan signifikan terhadap pembiayaan modal kerja. Selanjutnya, tingkat margin berpengaruh negatif dan signifikan dalam jangka pendek, tetapi tidak berpengaruh dalam jangka panjang. Kata kunci: Pembiayaan Modal Kerja, Dana Pihak Ketiga, tingkat Margin Pembiayaan, ARDL-ECM.  Abstract: This research aims to analyze the influence of third-party funds and the yield rate of financing on the realization of working capital financing distributed by Islamic banks to the MSMEs sector in Indonesia. Using time series data for the period 2014M6-2018M9, the analysis model used is autoregressive distributed lag (ARDL). The research pointed out that there is a long-term cointegration relationship between the realization of Islamic financing with third-party funds and the yield rate. In the long term and short term, third-party funds have a positive and significant effect on working capital financing. Furthermore, the yield rate has a negative and significant effect in the short term but has no effect in the long term.  Keywords: Working capital financing, Third-party funds, Yield rate of financing, ARDL-ECM.

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Hok, Leanghak. "Competitiveness and government spending in Cambodia: An autoregressive distributed lag approach." Theory, Methodology, Practice 16, no. 2 (2020): 27–40. http://dx.doi.org/10.18096/tmp.2020.02.03.

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In the globalization age, global competitiveness is gaining attention from policymakers and scholars. This paper focuses on a measurement of trade competitiveness based upon the expansion of market size. Fiscal policy has become a subject of debate since the global crisis of 2008. This paper attempts to examine the influence of government spending (i.e., government investment and consumption) on trade competitiveness. The Autoregressive Distributed Lags (ARDL) approach is used to estimate the dynamic relationship. The result, based on Cambodia's annual data from 1970 to 2015, shows that Cambodia’s trade competitiveness increases when there is a rise in public investment, government purchases, or aggregate private spending. This study shapes an alternative perception of the effectiveness of fiscal policy as domestic expenditure in enhancing international macroeconomic activities.

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Kwang-Jing Yii, Chai-Thing Tan, Nian-Meng Tan, Xue-Wen Teng, Ting-En Khor, and Sui-Hang Fan. "Hot Money and Stock Market in China: Empirical Evidence from ARDL and NARDL Approaches." International Journal of Business and Society 22, no. 2 (2021): 713–33. http://dx.doi.org/10.33736/ijbs.3753.2021.

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This study discusses the relationship between hot money and stock market in China by employing the Autoregressive Distributed Lag (ARDL) and Nonlinear Autoregressive Distributed Lag (NARDL) methods. The data used in this study is quarterly data over the period 2000: Q1 to 2017: Q4. The results show that oil price, economic growth and hot money possess a long-run relationship towards stock market in China, whereas, no effect is found from inflation. The oil price and economic growth are both positively related to stock market while there is a negative relationship from hot money. Furthermore, the study supports the existence of an asymmetric effect between hot money and stock market. The findings imply that policymakers should form better monitoring systems to control the inflow of hot money, thus, strengthening investors’ confidence and avoiding unwanted bubbles in China’s stock market.

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Dale, Tahir Desta, Mekdelawit Reta, and Bizuneh Girma. "Determinants of Tax Revenue in Ethiopia: Autoregressive Distributed Lag Approach." Ethiopian Journal of Business and Social Science 6, no. 2 (2024): 1–30. http://dx.doi.org/10.59122/154f59lk.

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Tax revenue is the main source of revenue for governments in advanced and emerging economies, which fund government spending. The main goal of this research is to look at the factors affecting tax revenue in Ethiopia from 1996 to 2020 using time series data. The impact of agricultural-to-GDP, service-to-GDP, inflation, corruption, political stability, and tax reformation on the ratio of tax revenue to GDP was investigated in this study. The short-run and long-run associations between the variables were determined using the autoregressive distributed lag (ARDL) co-integration approach. The study's outcomes reveal that inflation has a positive relationship with tax; however, agricultural GDP negatively impacted tax revenue in the short run over the study period. Political stability, service-to-GDP, and inflation, on the other hand, has a positive long-run impact on tax revenue, while corruption has a negative impact. We recommend that policymakers and governments combat corruption, maintain political stability, broaden tax bases to include more service-oriented businesses, and reduce reliance on agricultural sectors. Keywords: Inflation; Corruption; Political stability; Tax reformation; Tax revenue

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Babatunde Peter Ekundayo. "RICE PRODUCTION, IMPORTS AND ECONOMIC GROWTH IN NIGERIA: AN APPLICATION OF AUTOREGRESSIVE DISTRIBUTED LAG." International Journal of Advanced Economics 5, no. 2 (2023): 48–56. http://dx.doi.org/10.51594/ijae.v5i2.449.

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Inconsistent and inefficient policies, climate issues and general poor funding have been adjudged to hinder increased domestic rice production in Nigeria. Rather than tackling these challenges, the nation has continued to opt for importation to supplement her domestic production, if not for recently, as a ‘stop-gap’ for food security. Geared towards strengthening the resilient efforts of the small holder farmers and driving increased rice production, this paper examined the trends in rice imports and production between 1980 and 2021; and also identified the determinants of rice imports in Nigeria. Secondary data were used for this study, while descriptive statistics and ARDL model were used to analyze the data. The results showed that the average quantities of rice production and rice imports were 3.51 and 0.24 million tons over the periods. The periods between 1998 and 2007 experienced a wide volatility of rice imports over rice production. Again, the results of ARDL model implied that exchange rate, GDP and quantity of rice production were statistically significant in influencing changes in the quantity of rice imports in the area. Therefore, since GDP and quantity of rice production had negative relationship with rice imports, it would be suggested that efforts geared at increasing rice production in Nigeria should be tailored at revamping agricultural extension services to enhance a genuine two-way communication between researchers and the farmers vis-à-vis increase food production. Keywords: Rice Imports, Trends, Rice Production, ARDL Model, Nigeria.

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Bassey, Enya Ndem, Tumba Henry James, and Bassey Agala Friday. "Autoregressive Distributed Lag Approach (ARDL) to Corruption and Economic Growth Nexus in Nigeria." Journal of Environmental Science and Economics 1, no. 3 (2022): 23–31. https://doi.org/10.5281/zenodo.6730700.

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The corruption in Nigeria is generating concern around the globe and among its citizens. This concern is because corruption has continued undermining the country's socio-economic development. Thus, this study empirically investigates the impact of corruption on economic growth in the Nigerian economy using annual data from 1980 to 2018. The study employed the autoregressive distributed lag (ARDL) model as its estimation technique. In this study, economic growth was proxied by gross domestic product growth rate (GDPGR), while corruption was proxied by the corruption perception index. The result revealed that corruption has a negative and significant impact on economic growth in Nigeria in the long run. This finding implies that corruption has impeded the economic development process in Nigeria within the period of this study. Thus, it was recommended that anti-corruption agencies in Nigeria, such as the Economic and Financial Crime Commission (EFCC) should be strengthened by enacting laws that will empower them to investigate, arrest and prosecute offenders.

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Zaretta, Bara, and Lenni Yovita. "HARGA SAHAM, NILAI TUKAR MATA UANG DAN TINGKAT SUKU BUNGA ACUAN DALAM MODEL AUTOREGRESSIVE DISTRIBUTED LAG (ARDL)." Jurnal Penelitan Ekonomi dan Bisnis 4, no. 1 (2019): 9–22. http://dx.doi.org/10.33633/jpeb.v4i1.2318.

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Beberapa penelitian terdahulu telah banyak yang membuktikan adanya pengaruh antara nilai tukar Rupiah terhadap Dolar Amerika dan BI Rateterhadap IHSG. Namun dengan menggunakan pendekatan model Autoregressive Distributed Lag(ARDL) dalam penelitian ini lebih dalam lagi melihat dinamika hubungan jangka panjang maupun jangka pendek untuk variabel nilai tukar Rupiah terhadap Dolar Amerika, BI Ratedan IHSG. Untuk dapat menangkap dinamika tersebut diperlukan seleksi model ARDL terbaik dengan beberapa prosedur pengujian. Periode penelitian dimulai dari Juli 2005 sampai dengan Desember 2017, dimana dalam rentang waktu tersebut banyak terjadi pergolakan global yang memberikan dampak yang cukup besar terhadap Indonesia, salah satunya adalah pelemahan nilai tukar Rupiah terhadap Dolar Amerika. Mekanisme suku bunga acuan beberapa kali juga dipilih oleh Pemerintah Indonesia untuk menghadapi pergerakan nilai tukar Rupiah terhadap Dolar Amerika. Namun sebagaimana nilai tukar dan tingkat suku bunga acuan akan memberikan pengaruh kepada perekonomian secara keseluruhan dan terlebih lagi terhadap pasar modal yang juga merupakan indikator ekonomi suatu negara. Dalam penelitian ini, melalui model ARDL nilai tukar Rupiah terhadap Dolar Amerika, BI Ratedan IHSG terbukti memiliki kointegrasi jangka panjang atau bergerak bersama – sama dalam jangka panjang. Namun tidak hanya jangka panjang, ketiga variabel tersebut juga mempunyai dinamika hubungan jangka pendek yang mempunyai kecepatan penyesuaian menuju keseimbangan yang cukup tinggi perbulannya.Kata kunci : Nilai tukar, BI Rate, IHSG, Autoregressive Distributed Lag Model.

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Xiao, Chong, and Riya Tabish. "Green Finance Dynamics in G7 Economies: Investigating the Contributions of Natural Resources, Trade, Education, and Economic Growth." Sustainability 17, no. 4 (2025): 1757. https://doi.org/10.3390/su17041757.

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Despite the growing emphasis on sustainable development, the role of green finance in the context of G7 economies remains largely unexplored. The increasing emphasis on green financial transformation motivates this study to analyze the influence of natural resources (NARSs), population (POPS), education (EDCT), trade (TRD), and economic growth (ECNG) on green finance (GRF) in G7. Using panel data from 1996 to 2021, this study employs the Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) methodology to investigate both the long-run and short-run relationships among these variables. To address the issue of possible heterogeneity, this study uses Cross-Sectional Autoregressive Distributed Lag (CS-ARDL). Before applying the PMG-ARDL methodology, this study conducted a series of pretests to ensure data reliability and address potential endogeneity issues. These included tests for cross-sectional dependence, slope homogeneity, variance inflation factor (VIF) analysis, Cross-sectionally Augmented Im-Pesaran-Shin (CIPS) unit root testing, and the Westerlund cointegration test. The PMG-ARDL outcomes show a positive relationship between NARS, ECNG, POPS, TRD, EDCT, and GRF. Specifically, a 1% increase in NARS, ECNG, POPS, TRD, and EDCT leads to a corresponding increase in GRF by 0.050%, 1.98%, 1.81%, 0.62%, and 0.20%, respectively. This study provides valuable policy recommendations for G7 countries, emphasizing the need for targeted strategies to enhance green finance through the sustainable management of natural resources, economic growth, education, and trade.

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Pratama, Nugraha, Irsad Lubis, and M. Syafii. "The Analysis of Factors Affecting Social Security of Labour in Indonesia." International Journal of Research and Review 11, no. 2 (2024): 556–75. http://dx.doi.org/10.52403/ijrr.20240257.

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This research aims to analyze the factors affecting Social Security of labour in Indonesia in the 1991-2022 period reviewed from the variables of total active participants (JPA), Gross Domestiv Product (GDP0, Inflation, Minimum Wage (UM) and Workforce Participation Rate (TPAK). The research employs secondary data, namely annual data obtained from the Central Statistics Agency and BPJS Ketenagakerjaan (Employee Social Security System) report. This research employs regression analysis method of Autoregressive Distributed Lag (ARDL). This research result indicates that in the long term, the variables of GDP, Inflation and Minimum Wage have a positive and significant effect on the JPA, respectively, Meanwhile, TPAK has a negative and insignificant effect on JPA. Keywords: Total Active Participants, Gross Domestic Product, Inflation, Minimum Wage, Workforce Participation rate, Autoregressive Distributed Lag

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Ahead Alfarkh, Aya, та Prof Ahmad Ibrahim Malawi. "أثر التحرير المالي على الاحتياطيات الأجنبية في الأردن". Jordan journal of applied sciences-Humanities Science Series 33, № 1 (2022): 15. http://dx.doi.org/10.35192/jjoas-h.v33i1.370.

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This study aimed to investigate the impact of financial liberalization on foreign reserves in Jordan over the period (1998-2018). Several diagnostic tests have been applied, such as Augmented Dickey- Fuller (ADF) and Phillips-Perron (PP) test for Stationarity. The results have shown that all of the time series are not stationary in their levels, where are their first differences are stationaryaccording to Dickey- Fuller test (ADF), but the results have shown that some of the time series are stationary in their levels and some of them are stationary in the first difference according to Phillips-Perron test. Cusum stability test was applied for checking the stability of the model parameters, and the autoregressive distributed lag (ARDL) bound testing approach was applied for the cointegration test. The results have shown the financial freedom (as a proxy variable for financial liberalization) has a positive statistically significant impact on foreign reserves. So this study recommends to extend financial liberalization in order to increase foreign reserves in Jordan. Keywords: Financial Liberalization, Foreign reserves, Autoregressive Distributed Lag (ARDL) model.

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Journal articles on the topic 'ARDL: autoregressive distributed lag'

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