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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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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 (September 27, 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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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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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 (June 2017): 81–92. http://dx.doi.org/10.29214/damis.2017.36.2.005.
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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 (November 28, 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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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 (March 30, 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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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 (March 22, 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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Saâdaoui, Foued, and Othman Ben Messaoud. "Multiscaled Neural Autoregressive Distributed Lag: A New Empirical Mode Decomposition Model for Nonlinear Time Series Forecasting." International Journal of Neural Systems 30, no. 08 (June 26, 2020): 2050039. http://dx.doi.org/10.1142/s0129065720500392.
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Forecasting has always been the cornerstone of machine learning and statistics. Despite the great evolution of the time series theory, forecasters are still in the hunt for better models to make more accurate decisions. The huge advances in neural networks over the last years has led to the emergence of a new generation of effective models replacing classic econometric models. It is in this direction that we propose, in this paper, a new multiscaled Feedforward Neural Network (FNN), with the aim of forecasting multivariate time series. This new model, called Empirical Mode Decomposition (EMD)-based Neural ARDL, is inspired from the well-known Autoregressive Distributed Lag (ARDL) model being our proposal founded upon the concepts of nonlinearity, EMD-multiresolution and neural networks. These features give the model the ability to effectively capture many nonlinear patterns like the ones often present in econophysical time series, such as nonlinear trends, seasonal effects, long-range dependency, etc. The proposed algorithm can be summarized into the following four basic tasks: (i) EMD breaking-down multivariate time series into different resolution levels, (ii) feeding EMD components from the same levels into a number of feedforward neural ARDL models, (iii) from one level to the next, extrapolating the component corresponding to the response variable (scalar output) a number of steps ahead, and finally, (iv) recombining level-by-level forecasts into a single output. An optimal learning scheme is rigorously designed for efficiently training the new proposed architecture. The approach is finally tested and compared to a number of powerful benchmark models, where experiments are conducted on real-world data.
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Ayadi, Folorunso Sunday, Sunday Mlanga, Monday Isaac Ikpor, and Robert A. Nnachi. "Empirical Test of Pollution Haven Hypothesis in Nigeria Using Autoregressive Distributed Lag (Ardl) Model." Mediterranean Journal of Social Sciences 10, no. 3 (May 1, 2019): 48–58. http://dx.doi.org/10.2478/mjss-2019-0041.
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Abstract This study set out to investigate the reality or otherwise of the pollution haven hypothesis in Nigeria using data from 1970 to 2017 and using the autoregressive distributed lag (ARDL) models both in the short and long run. The study used FDI inflows as measure of economic activity and carbon dioxide emission as a measure of regulatory stringency. The study finds the previous FDI inflows as a significant determinant of current FDI both in the short and long run. This implies that the more FDI an economy attracts, the more potentials it has to further attract more FDI. Population, a measure of demand condition of the host economy is positively and significantly related to FDI inflows both in the short run and in the long run. Trade openness has a positively significant impact on FDI inflows in the long run, meaning that globalization encourages FDI inflows. A year lag of the FDI has a positively significant impact on FDI inflows in the long run. This suggest that pollution haven hypothesis which states that industries with polluting technologies tend to relocate to countries or areas (pollution havens) with lax or less stringent environmental regulations is a reality for Nigeria. The implication of this is that government of Nigeria must weigh the beneficial impact of FDI inflows against the pollution impact of ‘dirty’ FDI before deciding or setting its environmental policy.
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Al-Jafari, Mohamed Khaled, and Hatem Hatef Abdulkadhim Altaee. "Determinants of Inflation Sources in Iraq: An Application of Autoregressive Distributed Lag (ARDL) Model." Journal of Social Sciences Research, no. 52 (January 25, 2019): 381–88. http://dx.doi.org/10.32861/jssr.52.381.388.
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Most economists agree that the emergence of substantial inflationary pressure in Iraq was due to the monetary growth arising from large increase in the money supply by government to finance enormous budget deficit. This was true especially during the comprehensive sanction imposed on the country between 1990 till 2003. Others point out to exchange rate depreciations as another cause to inflation. Such controversy about the causes of inflation in Iraq has necessitated studying this phenomenon quantitatively. Our main contribution is to assess empirically the effects of money supply, exchange rate, and import on inflation in Iraq over the period 1995–2015. Using the ARDL bounds testing approach, we estimated the long-run effects of those variables on real inflation. In addition, we attempt to draw attention to the impact of changes in global prices on the phenomenon of inflation in Iraq. It is analyzed that money supply, exchange rate and import, changes inflation to 0.59, -0.85, and 0.11 percent points respectively by one percent rise in long-run. The Error Correction model with a negative sign remained statistically significant with the approximately 34% speed of adjustment to restore the equilibrium in the long-run, which was convergent quickly.
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Pahlavani, Mosayeb, Ed Wilson, and Andrew C. Worthingt. "Trade-GDP Nexus in Iran: An Application of the Autoregressive Distributed Lag (ARDL) Model." American Journal of Applied Sciences 2, no. 7 (July 1, 2005): 1158–65. http://dx.doi.org/10.3844/ajassp.2005.1158.1165.
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LUCKSTEAD, JEFF. "ASYMMETRIC EXCHANGE RATE PASS-THROUGH IN U.S. IMPORTS OF COCOA." Journal of Agricultural and Applied Economics 50, no. 3 (April 18, 2018): 369–86. http://dx.doi.org/10.1017/aae.2018.1.
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AbstractBoth the autoregressive distributed lag (ARDL) and the nonlinear ARDL frameworks are applied to model U.S. imports of cocoa beans from Côte d'Ivoire, Ghana, and the Dominican Republic (more than 90% of U.S. cocoa imports originate from these three countries). The results provide evidence of nonlinear and asymmetric pass-through of exchange rates, regional quality difference, and imperfect competition in U.S. cocoa imports. Furthermore, a rise or fall in U.S. income leads to an increase or decrease in U.S. cocoa imports.
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Kriskkumar and Naseem. "Analysis of Oil Price Effect on Economic Growth of ASEAN Net Oil Exporters." Energies 12, no. 17 (August 29, 2019): 3343. http://dx.doi.org/10.3390/en12173343.
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In this paper, the linear and nonlinear effects of oil price on growth for Association of Southeast Asian Nations (ASEAN)—3 net oil-exporting countries, namely Brunei, Malaysia and Vietnam, are investigated. The empirical analysis applies the augmented autoregressive distributed lag model (ARDL) bound test approach and the nonlinear autoregressive distributed lag model (NARDL) methodology over the period of 1979 to 2017. Evidence suggests that ignoring nonlinearities may lead to misleading results. Specifically, results reveal that the effect of oil price is asymmetric for the case of Brunei, while the effect oil price is deemed insignificant for the case of Malaysia and Vietnam, both linear and nonlinear model. Brunei’s high dependency on oil revenue makes it susceptible to negative oil price shock. This suggests that oil price still plays a significant role as the main driver of economic progress for Brunei.
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Moddilani, Ganiko, and Irwandi Irwandi. "Perkembangan Teknologi Informasi, TFP, dan Emisi Gas CO2 di Indonesia." Jurnal Ekonomi dan Pembangunan Indonesia 21, no. 1 (January 26, 2021): 31–40. http://dx.doi.org/10.21002/jepi.v21i1.1301.
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This paper examines the development of information technology, total factor productivity (TFP), and urbanization of CO2 gas emissions in Indonesia from 1975–2014. To discuss empirically, this study uses the Autoregressive Distributed Lag (ARDL) model. There are several results in this study. Firstly, the TFP coefficient value in the short term is lower than the long term, so that the Enviromental Kuznets Curve (EKC) hypothesis is not proven. This is one of the causes of rising CO2 gas emissions. Secondly, information technology has a significant impact on the increase of CO2 gas emissions. Thirdly, Indonesia’s urbanization has reduced CO2 gas emissions. ................................................ Penelitian ini menjelaskan pengaruh perkembangan teknologi informasi, total faktor produktivitas (TFP), dan urbanisasi terhadap emisi gas CO2 di Indonesia dari tahun 1975–2014. Untuk menguji secara empiris, penelitian ini menggunakan model Autoregressive Distributed Lag (ARDL). Ada beberapa hasil dalam penelitian ini. Pertama, koefisien nilai TFP pada jangka pendek lebih rendah daripada nilai koefisiennya pada jangka panjang sehingga penelitian ini menunjukkan bahwa hipotesis Enviromental Kuznets Curve (EKC) tidak terbukti. Hal ini menjadi salah satu penyebab naiknya emisi gas CO2. Kedua, teknologi informasi memiliki dampak yang signifikan terhadap naiknya emisi gas CO2. Ketiga, urbanisasi di Indonesia mengurangi emisi gas CO2.
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Sukmana, Raditya, and Rahmat Heru Setianto. "House Prices and Islamic Bank Stability in Indonesia: Evidence from Autoregressive Distributed Lag (ARDL) Model." Jurnal Pengurusan 52 (2018): 73–84. http://dx.doi.org/10.17576/pengurusan-2018-52-06.
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Sinay, Lexy J., Fitri R. N. Tihurua, and Dorteus L. Rahakbauw. "ANALISIS HARGA SAHAM PT. ANTAM tbk BERDASARKAN HARGA EMAS DAN NILAI TUKAR RUPIAH TERHADAP DOLAR MENGGUNAKAN MODEL AUTOREGRESSIVE DISTRIBUTED LAG." BAREKENG: JURNAL ILMU MATEMATIKA DAN TERAPAN 12, no. 1 (May 16, 2018): 53. http://dx.doi.org/10.30598/vol12iss1pp53-62ar364.
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Saham adalah secarik kertas yang menunjukkan hak pemodal yaitu pihak yang memiliki kertas tersebut untuk memperoleh bagian dari prospek atau kekayaan organisasi yang menerbitkan sekuritas tersebut, dan berbagai kondisi yang memungkinkan pemodal tersebut menjalankan haknya. PT. ANTAM tbk adalah sebuah perusahaan pertambangan di Indonesia yang terdiversifikasi dan terintegrasi secara vertikal yang berorientasi dibidang ekspor. Kegiatan perusahaan ini mencakup eksplorasi, penambangan, pengolahan serta pemasaran dari komoditas bijih nikel, feronikel, emas, perak, bauksit dan batubara. Dengan menggunakan model ARDL peneliti ingin mengetahui hubungan antara harga saham PT. ANTAM tbk dengan harga emas dan nilai tukar dolar terhadap rupiah. Model ARDL adalah model yang digunakan untuk melihat adanya pengaruh variabel dependen (Y) dan variabel independen (X) dari waktu ke waktu termasuk pengaruh varibel dependen (Y) dari masa lalu terhadap nilai varibel dependen (Y) masa sekarang. Dari hasil pengujian Bounds pada model ARDL(2,5,5) untuk masing-masing tingkat kepercayaan 90%, 95%, 97,5%, dan 99%, diperoleh bahwa nilai Statistik-F yaitu 2,6148 lebih kecil dari pada nilai kritis batas bawah (lower bound), maka hipotesis nol diterima sehingga dapat dikatakan bahwa tidak terdapat hubungan jangka panjang (tidak terkointegrasi) pada model ARDL (2,5,5). Dengan demikian, dalam jangka pendek harga emas dan nilai tukar dolar terhadap rupiah mempengaruhi harga saham PT. ANTAM tbk.
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Xiao, Hui, and Yiguo Sun. "Forecasting the Returns of Cryptocurrency: A Model Averaging Approach." Journal of Risk and Financial Management 13, no. 11 (November 13, 2020): 278. http://dx.doi.org/10.3390/jrfm13110278.
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This paper aims to enrich the understanding and modelling strategies for cryptocurrency markets by investigating major cryptocurrencies’ returns determinants and forecast their returns. To handle model uncertainty when modelling cryptocurrencies, we conduct model selection for an autoregressive distributed lag (ARDL) model using several popular penalized least squares estimators to explain the cryptocurrencies’ returns. We further introduce a novel model averaging approach or the shrinkage Mallows model averaging (SMMA) estimator for forecasting. First, we find that the returns for most cryptocurrencies are sensitive to volatilities from major financial markets. The returns are also prone to the changes in gold prices and the Forex market’s current and lagged information. Then, when forecasting cryptocurrencies’ returns, we further find that an ARDL(p,q) model estimated by the SMMA estimator outperforms the competing estimators and models out-of-sample.
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Maku, Olukayode E., Emmanuel O. Ajike, and Solomon Chinedu. "Human Capital Development and Macroeconomic Performance in Nigeria: An Autoregressive Distributed Lag (ARDL) Approach." Valahian Journal of Economic Studies 10, no. 1 (July 1, 2019): 51–64. http://dx.doi.org/10.2478/vjes-2019-0005.
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Abstract While developed and most developing nations have seen the need and continue to invest heavily in the development and training of her manpower as shown by huge budgetary allocations to education and health, Nigeria continues to play politics with her human capital development policy which has been poor and only been effective on paper despite the huge outlay of human capital available at our disposal. This study therefore examined the impact of human capital development on the macroeconomic performance of Nigeria. Using autoregressive distributed lagged model, the study proxied human capital development using government expenditure on education, government expenditure on health, secondary school enrolment rate, and school enrolment rate at tertiary level, while per capita GDP was used as proxy variable for measuring macroeconomic performance. The results of the estimated short and long run ARDL models indicated, an insignificant and negative relationship between human capital development and gross domestic product per capita (GDPPC) in the short run. Another result of this study is that, only tertiary enrolment rate (TER) has a significant and positive impact on gross domestic product per capita (GDPPC). This finding was an indication of relatively good but insufficient efforts by government to boost human capital. The study concluded that while human capital development is crucial for accelerated macroeconomic performance, government efforts aimed at boosting human capital has had a depressing effect on macroeconomic performance. On the strength of this, the study recommended that government and economic policy makers in Nigeria should place greater emphasis on human capital development.
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Maku, Olukayode Emmanuel, Emmanuel Ogbonna Ajike, and Solomon Chimereze Chinedu. "Human Capital Development and Macroeconomic Performance in Nigeria: An Autoregressive Distributed Lag (ARDL) Approach." ETIKONOMI 18, no. 2 (September 22, 2019): 185–96. http://dx.doi.org/10.15408/etk.v18i2.11701.
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Developed nations continue to invest heavily in the development and training of their human resources. Huge budgetary allocations show it to education and health, yet Nigeria’s human capital development policy has only been effective on paper. This study examined the impact of human capital development on the macroeconomic performance of Nigeria. Using the autoregressive distributed lagged (ARDL) model, this study shows an insignificant negative relationship between human capital development and per capita GDP in the short run. The results also showed that only the tertiary enrolment rate significantly and positively improved per capita GDP within the period under review. The study concluded that the government’s efforts aimed at boosting human capital have been insufficient.JEL Classification: O47, J11, J24
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O. Ajibola, Isaiah, Sylvanus U. Udoette, Rabia A. Muhammad, and John O. Anigwe. "Currency Substitution and Exchange Rate Volatility in Nigeria: An Autoregressive Distributed Lag Approach." Central Bank of Nigeria Journal of Applied Statistics, Vol. 11 No. 2 (April 8, 2021): 1–28. http://dx.doi.org/10.33429/cjas.11220.1/8.
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This study investigates the relationship between exchange rate volatility and currency substitution in Nigeria, using Autoregressive Distributed Lag (ARDL) model. After accounting for the presence of structural breaks, evidence from the findings shows that domestic interest rate and expected changes in exchange rate are important determinants of currency substitution. In addition, there is empirical support for a positive relationship between exchange rate volatility and currency substitution both in the short- and long-run. This implies that higher real exchange rate volatility is associated with an increased level of currency substitution. In view of these findings, the paper calls for sustained efforts by the monetary authority in containing exchange rate volatility and inflation as a way of curbing the spate of currency substitution in the country.
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Astari, Mayra, Lies Maria Hamzah, and Arivina Ratih. "Hukum OKUN: Pertumbuhan Ekonomi dan Tingkat Pengangguran di Indonesia." Jurnal Ekonomi Pembangunan 8, no. 1 (April 5, 2019): 37–44. http://dx.doi.org/10.23960/jep.v8i1.32.
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This study examined the validity of Okun's Law on the Indonesian economy by using the difference version of Okun's Law to obtain the Okun coefficient. This study uses the analysis of the Autoregressive Distributed Lag Model (ARDL). The estimation results concluded that Okun's Law proved to have a negative and significant effect on the Indonesian economy because the variable economic growth was shown to influence the unemployment variable statistically.
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Deszke, Klara-Dalma, and Liliana Duguleana. "COINTEGRATED-BASED FORECAST OF LONG-RUN RELATIONSHIPS." SERIES V - ECONOMIC SCIENCES 14(63), no. 1 (June 30, 2021): 153–68. http://dx.doi.org/10.31926/but.es.2021.14.63.1.16.
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The Vector Error Correction Model (VECM) and the Autoregressive Distributed Lag Model (ARDL) are used to estimate the cointegration in the case of long-run relationship of quarterly GDP and Final Consumption in Romania during the period 1995 – 2019. The actual data of 2020 Q1 and Q2 were used to check the best model’s validity. The static and dynamic approaches of the ARDL model were used to forecast the Final Consumption for Q3 and Q4 of the year 2020. Applying the cointegration model shows the long term relationship of GDP and Final Consumption, but also the effects of other factors, seen in the differences of Final Consumption from its Long-Run evolution, and comprised in the cointegrating terms.
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Shabbir, Ali Hassan, Jiquan Zhang, James D. Johnston, Samuel Asumadu Sarkodie, James A. Lutz, and Xingpeng Liu. "Predicting the influence of climate on grassland area burned in Xilingol, China with dynamic simulations of autoregressive distributed lag models." PLOS ONE 15, no. 4 (April 3, 2020): e0229894. http://dx.doi.org/10.1371/journal.pone.0229894.
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The influence of climate change on wildland fire has received considerable attention, but few studies have examined the potential effects of climate variability on grassland area burned within the extensive steppe land of Eurasia. We used a novel statistical approach borrowed from the social science literature—dynamic simulations of autoregressive distributed lag (ARDL) models—to explore the relationship between temperature, relative humidity, precipitation, wind speed, sunlight, and carbon emissions on grassland area burned in Xilingol, a large grassland-dominated landscape of Inner Mongolia in northern China. We used an ARDL model to describe the influence of these variables on observed area burned between 2001 and 2018 and used dynamic simulations of the model to project the influence of climate on area burned over the next twenty years. Our analysis demonstrates that area burned was most sensitive to wind speed and temperature. A 1% increase in wind speed was associated with a 20.8% and 22.8% increase in observed and predicted area burned respectively, while a 1% increase in maximum temperature was associated with an 8.7% and 9.7% increase in observed and predicted future area burned. Dynamic simulations of ARDL models provide insights into the variability of area burned across Inner Mongolia grasslands in the context of anthropogenic climate change.
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Ditta, Allah, Hafiz Asim, and Hafeez Ur Rehman. "An Econometric Analysis of Exigent Determinants of Trade Balance in Finland: An Autoregressive Distributed Lag (ARDL) Approach." Review of Applied Management and Social Sciences 3, no. 3 (December 31, 2020): 347–60. http://dx.doi.org/10.47067/ramss.v3i3.69.
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A number of research papers analyzed the factors that may have impacts on the balance of trade for the effective macroeconomic policies but the results of these studies have created ambiguity which implies that further research is needed as the worsening trade balance can limit the economic growth of any country. Hence the current paper is an effort to study the short-run and long-run relationships among trade balance, real effective exchange rate, GDP per capita, urbanization, unemployment and inflation rate for the Finnish economy. Autoregressive Distributed Lag (ARDL) bound testing methodology to co-integration along with error correction mechanism is applied by using time series data from 1990 to 2019 for checking the existence of long-run equilibrium between explained variable and its various determinants. Empirical findings of ARDL show that the long-run relationship among the factors of the estimated model holds. The results indicate that real effective exchange rate, urbanization and inflation are having a significant but negative impact on Finland’s trade balance for both the short-run and long-run while the impacts of GDP per capita and unemployment are significant and positive on the Finish balance of trade. In addition to above, the structural stability of mean and variance of the error term for the estimated ARDL model is verified with the help of CUSUM and CUSUM square graphs. Therefore, a reliable policy measure to improve the balance of trade by encouraging the domestic production and curtailing the imports is suggested in Finland.
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Caetano, Rafaela Maiara, and Cleomar Gomes Da Silva. "Determinantes da confiança do consumidor e dinâmica da política monetária no Brasil." Brazilian Keynesian Review 5, no. 1 (September 21, 2019): 18. http://dx.doi.org/10.33834/bkr.v5i1.165.
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<p>The aim of this article is to investigate the determinants of consumer confidence in Brazil and possible impacts on monetary policy actions. The econometric methodology applied is based on Autoregressive Distributed Lag (ARDL) Models, particularly the Bounds Testing (ARDL) Approach to Cointegration. For monthly data between January 2003 and December 2016, the empirical results suggest that there is a long run relationship between consumer confidence and the other variables analyzed. As for short-run dynamics, the error correction mechanism varies between 1.9% and 8.7%, depending on the estimated model. This suggests that economic variables influence consumer confidence, and when there is a break in confidence, its recovery is very slow.</p>
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Bashir, Furrukh, Imran Sharif Chaudhry, Rashid Ahmad, and Fiza Habib. "An Econometric Investigation of Sectoral Output and Environmental Degradation in Pakistan." Review of Education, Administration & LAW 3, no. 3 (December 31, 2020): 443–56. http://dx.doi.org/10.47067/real.v3i3.90.
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This study examines effect of sectoral output (agriculture, industry and services) on environmental degradation in Pakistan ranging from period 1972 to 2017. This study makes use of Augmented Dickey Fuller test (ADF) followed by Autoregressive distributed lag model (ARDL). The empirical results show that Co2 emission in Pakistan is increased by Industrial sector output, population and energy consumption while agriculture sector output, services sector output and exports are reducing carbon dioxide emission.
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ALABED, QUSAI MOHAMMAD QASIM, ZULKEFLY ABDUL KARIM, FATHIN FAIZAH SAID, and MOHD AZLAN SHAH ZAIDI. "INSTITUTIONAL QUALITY AND ECONOMIC GROWTH IN JORDAN: NEW EVIDENCE USING AN AUTOREGRESSIVE DISTRIBUTED LAG (ARDL) MODEL." JOURNAL OF SUSTAINABILITY SCIENCE AND MANAGEMENT 16, no. 3 (April 30, 2021): 204–19. http://dx.doi.org/10.46754/jssm.2021.04.015.
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Buhaerah, Pihri. "Pengaruh KPR terhadap Keterjangkauan Harga Properti Residensial." Kajian Ekonomi dan Keuangan 3, no. 3 (December 31, 2019): 182–97. http://dx.doi.org/10.31685/kek.v3i3.527.
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AbstractThis paper describes and examines the linkage of house mortgages on residential property price growth in Indonesia by using qualitative and quantitative research methods. The qualitative research approach is used to elaborate descriptively the role of house mortgages on residential property prices. To strengthen it, this study then employs one of time series regression analyses namely autoregressive distributed lag (ARDL) model for the period of 2002Q1-2017Q4. To achieve the objective of this study, data was collected from secondary sources such as Bank for International Settlements (BIS), Bank Indonesia (BI), and Central Statistics Agency (BPS). The qualitative approach shows that under lack of land banking and public housing zones, the expansion of house mortgages affect positively residential property prices both for private and public housing. The argument has been confirmed from regression analysis by using the ARDL model. The estimation results using the ARDL model show that there is a positive and significant relationship between house mortgage on residential property price growth both in the long-run and in the short-run. Keywords: house mortgage, property residential prices, land, ARDL modelJEL Classification: C22, E51, G21 AbstrakStudi ini membahas secara deskriptif dan empiris peran pembiayaan pemilikan rumah terhadap harga properti residensial di Indonesia dengan menggunakan metode penelitian kualitatif dan kuantitatif. Pendekatan kualitatif digunakan untuk menggambarkan secara deskriptif peran pembiyaan pemilikan rumah terhadap harga properti residensial. Selanjutnya, untuk memperkuat argument tersebut, studi ini kemudian melibatkan salah satu teknik analisis regresi data runtun waktu yaitu model autoregressive distributed lag (ARDL) untuk periode 2002Q1-2017Q4. Untuk mencapai tujuan penelitian, data dikumpulkan dari beragam sumber data sekunder seperti Bank for International Settlements (BIS), Bank Indonesia (BI), dan Badan Pusat Statistik (BPS). Hasilnya, dengan menggunakan pendekatan kualitatif menunjukkan bahwa tanpa pelembagaan bank tanah dan zonasi khusus perumahan rakyat, skema pembiayaan kepemilikan rumah hanya akan melambungkan harga properti residensial. Argumen ini juga terkonfirmasi dari analisis regresi dengan menggunakan model ARDL. Hasil estimasi dengan menggunakan model ARDL menunjukkan bahwa terdapat hubungan jangka panjang antara kredit kepemilikan rumah dengan harga property residensial baik untuk jangka pendek maupun jangka panjang. Kata Kunci: Kredit pemilikan rumah, harga properti residensial, tanah, model ARDLJEL Classification: C22, E51, G21
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Sharma, Vishal, and Ashok Mittal. "Revisiting the Dynamics of the Fiscal Deficit and Inflation in India: the Nonlinear Autoregressive Distributed Lag Approach." Economy of Region 17, no. 1 (March 2021): 318–28. http://dx.doi.org/10.17059/ekon.reg.2021-1-24.
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The chronic government deficit (fiscal deficit) and increase in the price level (inflation) have become major concerns for economists and policymakers. While numerous studies have examined the twin problems of the fiscal deficit and inflation for both developed and developing economies, their results are inconclusive due to different estimation techniques, chosen time periods, selection of variables, etc. Therefore, we examined the fiscal deficit-inflation nexus in India for the period from 1980–81 to 2016–17 by employing the Autoregressive Distributed Lag (ARDL) and Nonlinear Autoregressive Distributed Lag (NARDL) approaches. The results of the ARDL approach found no evidence of linear relationship between fiscal deficit and inflation in the Indian context. Further, the empirical findings of the NARDL model confirmed the nonlinear relationship between fiscal deficit and inflation in the long run and no association between money supply and inflation, supporting the ideas of the Fiscal Theory of the Price Level (FTPL) in the case of India. FTPL postulates that public debt and taxation policies drive price level; monetary policy has an indirect role only. Therefore, fiscal policymakers should focus on reducing fiscal deficits. Simultaneously, the Reserve Bank of India (RBI) should regulate lending interest rate so that a mix of fiscal and monetary policies can be applied for controlling inflation in India.
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Koulis, Alexandros, George Kaimakamis, and Christina Beneki. "Hedging effectiveness for international index futures markets." Economics and Business 32, no. 1 (July 31, 2018): 149–59. http://dx.doi.org/10.2478/eb-2018-0012.
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Abstract This paper investigates the hedging effectiveness of the International Index Futures Markets using daily settlement prices for the period 4 January 2010 to 31 December 2015. Standard OLS regressions, Error Correction Model (ECM), as well as Autoregressive Distributed Lag (ARDL) cointegration model are employed to estimate corresponding hedge ratios that can be employed in risk management. The analyzed sample consists of daily closing market rates of the stock market indexes of the USA and the European futures contracts. The findings indicate that the time varying hedge ratios, if estimated through the ARDL model, are more efficient than the fixed hedge ratios in terms of minimizing the risk. Additionally, there is evidence that the comparative advantage of advanced econometric approaches compared to conventional models is enhanced further for capital markets within peripheral EU countries
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Orman, Turgut, and İlkay Dellal. "Cointegration Analysis of Exchange Rate Volatility and Agricultural Exports in Turkey: an Ardl Approch." Turkish Journal of Agriculture - Food Science and Technology 9, no. 6 (July 4, 2021): 1180–85. http://dx.doi.org/10.24925/turjaf.v9i6.1180-1185.4456.
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This study aims to reveal the impact of exchange rate volatility on agricultural exports of Turkey by using the Autoregressive Distributed Lag Model. While quarterly time series data covering period of 2001: Q1 to 2018: Q4 were used to carry out analyses, Exponential Generalized Autoregressive Conditional Heteroscedasticity (1.1) is used to acquire exchange rate volatility series. The research findings showed that agricultural export is cointegrated with exchange rate volatility, producer price index and real effective exchange rate. Furthermore, our findings indicate that increases in real effective exchange rate have a statistically significant positive influence on the export volume whereas exchange rate volatility has negative impact on it.
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Elhassan, Tomader, and Bakhita Braima. "Impact of Khartoum Stock Exchange Market Performance on Economic Growth: An Autoregressive Distributed Lag ARDL Bounds Testing Model." Economies 8, no. 4 (October 19, 2020): 86. http://dx.doi.org/10.3390/economies8040086.
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This study examines the impact of the Khartoum Stock Exchange market performance on economic growth in Sudan from Q1 1995 to Q4 2018. The data were collected from the Central Bank of Sudan (CBS) and Khartoum Stock Exchange (KSE). The autoregressive distributed lag (ARDL) bounds test was applied to estimate the impact of the Khartoum Stock Exchange market performance on economic growth. The results show that the Khartoum Stock Exchange market performance has a limited impact on economic growth. The results of the ARDL test reveal that the speed of adjustment towards long-run equilibrium after a short-term shock, which confirms the stability of Sudanese economic system through stock market performance, equals 24% only. Although market capitalization has a positive and significant impact on economic growth in the long term, the turnover ratio and stocks traded value showed insignificant negative impacts on economic growth. We recommend that suitable investment policies should be developed by policy makers for the Sudanese economy to allow the Khartoum securities market to attract foreign investors and encourage local investors in order to improve the efficiency and effectiveness of the stock market, thus, leading to a boost in securities exchanges as well as economic growth.
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Jumhur, Jumhur. "PENERAPAN AUTOREGRESSIVE DISTRIBUTED LAG DALAM MEMODELKAN PENGARUH INFLASI, PERTUMBUHAN EKONOMI, DAN FDI TERHADAP PENGANGGURAN DI INDONESIA." Jurnal Ekonomi Bisnis dan Kewirausahaan 9, no. 3 (December 28, 2020): 250. http://dx.doi.org/10.26418/jebik.v9i3.41332.
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This study aims to examine the effect of inflation, economic growth, and foreign investment on unemployment in Indonesia. Using the autoregressive distributed lag (ARDL) analysis method to analyze the 1991-2018 time series data collected from the World Bank's World Development Indicators database. The results found that inflation has a negative and significant effect in the short term but not significant in the long term in Indonesia. Economic growth has a negative and significant effect on both short and long-term unemployment in Indonesia, and foreign investment has a negative and significant effect on both short and long-term unemployment in Indonesia. Through the ARDL model, this research is able to prove that inflation, economic growth, foreign investment, and budgeting are proven to have long-term cointegration or move together in the long term. The four variables also have a dynamic short-term relationship that has a fairly high speed of adjustment towards equilibrium per year. Based on the results, policymakers, in this case the government must provide a conducive investment environment by eliminating the structural rigidity that exists in the economy to attract investment, both foreign and domestic investment, to encourage economic growth and create jobs in Indonesia.
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Salim, Agus, and Kai Shi. "A Cointegration of the Exchange Rate and Macroeconomic Fundamentals: The Case of the Indonesian Rupiah vis-á-vis Currencies of Primary Trade Partners." Journal of Risk and Financial Management 12, no. 2 (May 13, 2019): 87. http://dx.doi.org/10.3390/jrfm12020087.
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Since the appearance of persistent research finding a disconnection between the exchange rate and its macroeconomic fundamentals, the empirical debate has not stopped. Studies employ various methods to explain the presence of the exchange rate disconnect puzzle, including applying models to the case of emerging market economies. However, the exchange rate has different determinants in some countries. To revisit this puzzle in an emerging market currency, we analyzed the cointegration of the exchange rate of the Indonesian Rupiah vis-á-vis currencies of primary trade partners and its macroeconomic fundamentals. The empirical results based on Autoregressive Distributed Lag (ARDL) and Nonlinear Autoregressive Distributed Lag (NARDL) models show that the fundamental variables consistently drive the exchange rate. The trade surplus as an extended nonlinear variable revealed high feedback to the exchange rate volatility in the long-run.
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Mugableh, Mohamed Ibrahim. "Does Monetary Policy Affect Economic Growth in Jordan? Evidence from Ordinary Least Square Models." International Business Research 12, no. 1 (December 6, 2018): 27. http://dx.doi.org/10.5539/ibr.v12n1p27.
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The main objective of this paper is to analyze equilibrium and dynamic causality relationships between monetary policy tools and economic growth in Jordan for the period (1990-2017). For this purpose, it considers the autoregressive distributed lag (ARDL) and vector error correction (VEC) models estimations. The results of ARDL approach show that monetary policy variables (i.e., real interest rate and money supply) have positive impact on economic growth in long-run and short-run except inflation rate. In addition, the results of VECM indicate bidirectional causal relationships between economic growth and monetary policy variables in long-run and short-run.
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Menza, Solomon Kebede, Zerihun Getachew, Berhanu Kuma, and Tora Abebe. "The Dynamics of Foreign Public Debt and Foreign Exchange Reserve of Ethiopia: Autoregressive Distributed Lag Model Approach." International Journal of Management and Humanities 6, no. 1 (September 30, 2021): 13–27. http://dx.doi.org/10.35940/ijmh.l1371.0851221.
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External public debt and foreign exchange reserve (FER) are performing a crucial role in the growth and development of countries. To examine the short-run and long-run dynamics among external public debt (EPD) and FER in Ethiopia, the study used 39 years data (1981 to 2019) from National bank of Ethiopia (NBE) and World Bank data sets. The Autoregressive Distributed Lag (ARDL) model with error correction model (ECM) was employed after checking the possible assumptions of economic series. The results of ADF test statistics confirms our economic series are stationary with a mixture of level form and first difference form. Bounds co-integration test suggests the existence of co-integration among the variables. According to the descriptive method of data analysis, on average, in Ethiopia the trend for service sector indicated that an ever improvement of the sector throughout the periods and supplementing the notion of change from agriculture base to service sector. On the other hand, according to ARDL model in the short -run on average trade tariff rate, share of manufacturing sector from the GDP, and lagged value of EPD itself predicts the EPD significantly at least at less than 10% level of significance . Moreover, the ECM revealed that in the long-run, financial development indicator, debt service payment, and average trade tariff rate were predicting the stock of FER for Ethiopian economy. Finally, the concerned body, the government of Ethiopia, should limit or reduce the amount of external debt (ED) inflows, and recheck the budget sources for financing different projects especially manufacturing industries rather than highly basing on external sources in the form of EPD, among others.
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Musa, Kabiru Saidu, Sulaiman Chindo, and Rabiu Maijama'a. "FINANCIAL MARKET DEVELOPMENT AND CO2 EMISSIONS NEXUS IN NIGERIA: AN APPLICATION OF ARDL APPROACH." Journal of Developing Economies 6, no. 1 (June 1, 2021): 91. http://dx.doi.org/10.20473/jde.v6i1.22448.
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The paper investigated the impact of financial development on CO2 emissions in Nigeria from 1981 to 2019. In the process of investigating the impact, Augmented Dickey-Fuller and Philip Perron, as well as the Zivot-Andrew structural breaks, unit root tests were applied. Their results indicated that financial development, level of income, and CO2 emissions were stationary at the first difference and that of Zivot-Andrew structural breaks indicated a mixture of integration. Cointegration relationship among the variables was established through autoregressive distributed lag model bounds test. The autoregressive distributed lag model long-and-short run models results indicated that financial development and income level significantly negatively impact the CO2 emissions. The suggestion based on these results is that financial development and income level help in financing clean projects in the long-and-short runs. The Granger causality result revealed bidirectional causality from financial development to CO2 emissions, income level to CO2 emissions, and financial development to income level. The variance decomposition analysis indicates that financial development and income level have contributed less to CO2 emissions, and impulse response function results revealed that CO2 emissions respond negatively to shocks in financial development and income level. Therefore, we recommend expanding the Nigerian financial market in financing clean projects for a clean environment alongside checking income generation activities that bring about emissions of CO2, such as burning trees for charcoal production in the forest, among others.Keywords: Financial market development, CO2 emissions, ARDL approachJEL Classification: G20, Q53, C32
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Yorucu, Vedat. "Growth impact of CO2 emissions caused by tourist arrivals in Turkey." International Journal of Climate Change Strategies and Management 8, no. 1 (January 11, 2016): 19–37. http://dx.doi.org/10.1108/ijccsm-12-2014-0148.
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Purpose – The purpose of this study is to analyze the determinants of changes in carbon dioxide (CO2) emissions for Turkey by utilizing the autoregressive distributed lag approach to investigate the long-run equilibrium relationships of CO2 emissions between foreign tourist arrivals (FTAs) and electricity consumption (ELC). The results reveal that foreign tourists and ELC are significant determinants of a long-run equilibrium relationship with CO2 emissions from electricity and heat production and CO2 emissions from transport for Turkey, respectively. The results of the conditional error correction models (CECM) confirm that there are long-run causal relationships from the growing number of foreign tourist arrivals and the increase of ELC toward the growth of CO2 emissions during 1960-2010. The results of autoregressive distributed lag (ARDL) error correction models for CO2 emissions also validate significant dynamic relationships between CO2 emissions, ELC and tourist arrivals in the short run. Design/methodology/approach – ARDL modeling and Bounds test approach were used in this study. Findings – Rapid tourism development in Turkey has triggered CO2 emissions. The growth of CO2 emissions in Turkey threatens sustainability. The hypothesis of “The growth of CO2 emissions in Turkey” is validated. Tourist arrivals, ELC and CO2 emissions are co-integrated. CECMs confirm the growth of CO2 emissions during 1960-2010. ARDL modeling shows significant relationships between CO2 emissions and other variables. Originality/value – Results of ARDL error correction models for CO2 emissions validate the hypothesis that there are significant dynamic relationships between CO2 emissions, ELC and tourist arrivals in Turkey for the short run.
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Adil, Masudul Hasan, Aadil Ahmad Ganaie, and B. Kamaiah. "Wagner’s Hypothesis: An Empirical Verification." IIM Kozhikode Society & Management Review 6, no. 1 (November 29, 2016): 1–12. http://dx.doi.org/10.1177/2277975216667095.
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This study explores the relationship between public expenditure (PE) and gross domestic product (GDP) to verify whether the Wagner’s hypothesis holds good in the Indian context. We cover the period from 1970 to 2013 and use econometric tools like Autoregressive Distributed Lag Model (ARDL) test to check the long-run and causal relationship among the variables. The results of the bounds test suggest that there exists cointegration between PE and GDP, but we found weak evidence for Wagner’s hypothesis as well.
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Menegaki, Angeliki N. "The ARDL Method in the Energy-Growth Nexus Field; Best Implementation Strategies." Economies 7, no. 4 (October 18, 2019): 105. http://dx.doi.org/10.3390/economies7040105.
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A vast number of the energy-growth nexus researchers, as well as other “X-variable-growth nexus” studies, such as for example the tourism-growth nexus, the environment-growth nexus or the food-growth nexus have used the autoregressive distributed lag model (ARDL) bounds test approach for cointegration testing. Their research papers rarely include all the ARDL procedure steps in a detailed way and thus they leave other researchers confused with the series of steps that must be followed and the best implementation paradigms so that they not allow any obscure aspects. This paper is a comprehensive review that suggests the steps that need to be taken before the ARDL procedure takes place as well as the steps that should be taken afterward with respect to causality investigation and robust analysis.
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Cantavella, Manuel. "The role of services in the environmental Kuznets curve." Economics and Business Letters 9, no. 4 (December 23, 2020): 326–33. http://dx.doi.org/10.17811/ebl.9.4.2020.326-333.
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This paper examines the influence of services activity in the environmental Kuznets curve (EKC) model regarding carbon dioxide (CO2) emissions. The analysis is applied for Spain during the period 1940-2014. It compares the standard environmental Kuznets curve model and its modification by isolating the evolution of services effect. The results through the autoregressive distributed-lag (ARDL) estimation strategy confirm that even though all economic activities tend to be more and more sustainable, it is the evolution of services sector that becomes fundamental in the reduction of per capita CO2 emissions.
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Li, Taoying, Miao Hua, and Qian Yin. "The Temperature Forecast of Ship Propulsion Devices from Sensor Data." Information 10, no. 10 (October 16, 2019): 316. http://dx.doi.org/10.3390/info10100316.
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The big data from various sensors installed on-board for monitoring the status of ship devices is very critical for improving the efficiency and safety of ship operations and reducing the cost of operation and maintenance. However, how to utilize these data is a key issue. The temperature change of the ship propulsion devices can often reflect whether the devices are faulty or not. Therefore, this paper aims to forecast the temperature of the ship propulsion devices by data-driven methods, where potential faults can be further identified automatically. The proposed forecasting process is composed of preprocessing, feature selection, and prediction, including an autoregressive distributed lag time series model (ARDL), stepwise regression (SR) model, neural network (NN) model, and deep neural network (DNN) model. Finally, the proposed forecasting process is applied on a naval ship, and the results show that the ARDL model has higher accuracy than the three other models.
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Mohammad Alawneh, Ateyah. "Building a Model of Government Spending Using Autoregressive Distributed Lag (ARDL) Analysis from 2001 to 2019: A Case Study of Jordan." International Journal of Business and Management 16, no. 2 (January 11, 2021): 30. http://dx.doi.org/10.5539/ijbm.v16n2p30.
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The study aims to build a model of government spending in Jordan using ARDL analysis through the use of an E-views program by determining the relationships between government spending and variables, such as the gross domestic product (GDP), government revenues, economic openness (OP), inflation rate, unemployment, population growth rate, and public debt. The statistical analysis showed a significant positive relationship between government spending and (GDP) and government revenues. It revealed significant positive relationships between government spending and) OP (and inflation. It found the statistically significant negative effect of the unemployment rate and the population growth rate on government spending. A negative relationship was found between government spending lag (1) and current government spending. Public debt was found to have a positive but not statistically significant effect on government spending. The relationships between the dependent variable and independent variables of government spending were consistent with unrestricted ARDL analysis in the long term. The analysis showed a statistically significant positive relationship between government spending and GDP at a short-term level but a statistically significant negative relationship between government spending and independent variables, such as population growth rate, inflation rate, and unemployment rate at a short-term level. One of the most important recommendations of the study was working to increase government spending in a way that is compatible with the increasing population growth. The study recommends government intervention to bring in more revenue through income-generating economic activities.
Contribution / Originality: This will be one of the few studies to build a model of government spending using Autonomous Distributed Regression (ARDL). The study also provides a scientific addition in the field of financial and economic sciences from a scientific point of view through the use of different statistical methods using ARDL analysis on the long and short levels to assist the government in preparing the state's general budget. The study also helps the government to develop in the field of public finances and prepare an unconventional general budget.
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Mohammad Alawneh, Ateyah. "Building a Model of Government Spending Using Autoregressive Distributed Lag (ARDL) Analysis from 2001 to 2019: A Case Study of Jordan." International Journal of Business and Management 16, no. 2 (January 11, 2021): 30. http://dx.doi.org/10.5539/ijbm.v16n2p30.
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The study aims to build a model of government spending in Jordan using ARDL analysis through the use of an E-views program by determining the relationships between government spending and variables, such as the gross domestic product (GDP), government revenues, economic openness (OP), inflation rate, unemployment, population growth rate, and public debt. The statistical analysis showed a significant positive relationship between government spending and (GDP) and government revenues. It revealed significant positive relationships between government spending and) OP (and inflation. It found the statistically significant negative effect of the unemployment rate and the population growth rate on government spending. A negative relationship was found between government spending lag (1) and current government spending. Public debt was found to have a positive but not statistically significant effect on government spending. The relationships between the dependent variable and independent variables of government spending were consistent with unrestricted ARDL analysis in the long term. The analysis showed a statistically significant positive relationship between government spending and GDP at a short-term level but a statistically significant negative relationship between government spending and independent variables, such as population growth rate, inflation rate, and unemployment rate at a short-term level. One of the most important recommendations of the study was working to increase government spending in a way that is compatible with the increasing population growth. The study recommends government intervention to bring in more revenue through income-generating economic activities.
Contribution / Originality: This will be one of the few studies to build a model of government spending using Autonomous Distributed Regression (ARDL). The study also provides a scientific addition in the field of financial and economic sciences from a scientific point of view through the use of different statistical methods using ARDL analysis on the long and short levels to assist the government in preparing the state's general budget. The study also helps the government to develop in the field of public finances and prepare an unconventional general budget.
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Ur Rehman, Faheem, Ejaz Ahmad, Muhammad Asif Khan, József Popp, and Judit Oláh. "Does Trade Related Sectoral Infrastructure Make Chinese Exports More Sophisticated and Diversified?" Sustainability 13, no. 10 (May 12, 2021): 5408. http://dx.doi.org/10.3390/su13105408.
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Whether better infrastructure influences Chinese export sophistication (ES) and diversification (ED) is an important question, which surprisingly remains unaddressed. The current study contributes to the ES and ED literature by capturing the symmetric and asymmetric effect of infrastructure on ES and ED. We employ a robust dynamically simulated autoregressive distributed lag (DYS-ARDL) dynamic method, which is an extended version of NARDL and ARDL. The major aim of this new DYS-ARDL dynamic approach was to abolish the issue in orthodox ARDL model approach while examining the long-run and short-run. The new dynamic DYS-ARDL model is accomplished in estimating, stimulating, and robotically plotting predictions of counterfactual alterations in one explanatory variable and its impact on the dependent variable while holding the remaining regressors constant. Furthermore, this new method of DYS-ARDL model can estimate, stimulate, and plot to forecast graphs of positive and negative variations in the variables robotically as well as their short and long-run associations. Interestingly, the results of this study witness the presence of long-run relationship between infrastructure and ES and ED in China. The present study shows that better infrastructure will be more beneficial for Chinese ED and ES.
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Gbagbeu, Kando Serge. "Financial Development and Economic Growth in Developing Countries." Journal of Economics and Management Sciences 1, no. 2 (October 14, 2018): p94. http://dx.doi.org/10.30560/jems.v1n2p94.
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In this study, we concern mainly about the short and long-run relationship between economic growth and financial development. We use a multi-steps methodology, namely the Autoregressive Distributed Lag (ARDL) approach and the Vector Error Correction Model (VECM) approach to test this relationship in Côte d’Ivoire from 1980 to 2014. Following our results, we conclude that there is a unidirectional causal relationship, both long run and short run, between GDP per capita and financial development index in Côte d’Ivoire running from economic growth to financial development.
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Oumarou, Issoufou. "Public Debt and Economic Growth in Niger: An Autoregressive Distributed Lag Approach." Journal of Advanced Research in Economics and Administrative Sciences 1, no. 2 (November 8, 2020): 56–65. http://dx.doi.org/10.47631/jareas.v1i2.123.
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Purpose: The aim of the paper is to examine the existence or not of a long run or a short run relationship between public debt and economic in Niger and investigate the significance of this relationship. Approach/Methodology/Design: The study first applied time series econometrics tests such as Augmented Dickey-Fuller (ADF) unit root test, Bound cointegration test and Auto Regressive Distributed Lag (ARDL) on annual data obtained from the International monetary fund (IMF) and the West African States Central Bank (BCEAO). The observations cover the period from 1970 to 2019. The study then performed some residual tests including serial correlation, normality and heteroskedasticity for the accuracy of the prediction of the model. Findings: The empirical results showed no long run relationship between public debt and economic growth in Niger. The short run analysis revealed that public debt and budget balance have short run causal effects on economic growth in Niger. The coefficients are significant at 10% significance level. Practical Implications: This article gives valuable information to Niger policy makers regarding the effects of public debt on Niger economic growth. The article highlights the effects that public debt has on economic growth in Niger in the short and long run. Therefore helping policy makers decide whether to increase or reduce the borrowing trend. Originality/value: The results of the paper give valuable information on the relationship that public debt may have with economic growth in Sub Saharan African countries with the similar macroeconomic indicators with Niger.
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Morrison, Colin, and Ernest Albuquerque. "Modelling New Zealand Road Deaths." Journal of Road Safety 32, no. 2 (May 1, 2021): 4–15. http://dx.doi.org/10.33492/jrs-d-19-00246.
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New Zealand is developing an integrated road safety intervention logic model. This paper describes a core component of this wider strategic research carried out in 2018: a baseline model that extrapolates New Zealand road deaths to 2025. The baseline will provide context to what Waka Kotahi NZ Transport Agency is trying to achieve. It offers a way of understanding what impact interventions have in acting with and against external influences affecting road deaths and serious trauma. The baseline model considers autonomous change at a macro level given social and economic factors that influence road deaths. Identifying and testing relationships and modelling these explanatory variables clarifies the effect of interventions. Time-series forecasting begins by carefully collecting and rigorously analysing sequences of discrete-time data, then developing an appropriate model to describe the inherent structure of the series. Successful time-series forecasting depends on fitting an appropriate model to the underlying time-series. Several time-series models were investigated in understanding road deaths in the New Zealand context. In the final modelling an autoregressive integrated moving average (ARIMA) model and two differing autoregressive distributed lag (ARDL) models were developed. A preferred model was identified. This ARDL model was used to project road deaths to 2025.
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Shita, Aynalem, Nand Kumar, and Seema Singh. "Determinants of Agricultural Productivity in Ethiopia: ARDL Approach." Indian Economic Journal 66, no. 3-4 (December 2018): 365–74. http://dx.doi.org/10.1177/0019466220941418.
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This study analyses factors affecting agricultural productivity in Ethiopia for the period of 1990–2016 by using autoregressive distributed lag (ARDL) model. Both the bounds test and the error correction model confirmed the existence of co-integration (long-run relationship) between the variables included in the model. The results revealed that cereal productivity is positively influenced by use of fertiliser and real gross domestic product (GDP) both in the long run and in the short run. While size of arable land influences productivity positively in the long run, its short-run effect was found to be negative. Hence, the government and other concerned authorities should work to enhance farmers’ use of improved technologies, such as fertiliser, by ensuring its timely availability at an affordable price, encouraging farmers to participate on alternative sources of income such as off-farm activities and bringing additional area under cereal production to improve agricultural productivity.
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Mohamed, Maha Mohamed Alsebai, Pingfeng Liu, and Guihua Nie. "Are Technological Innovation and Foreign Direct Investment a Way to Boost Economic Growth? An Egyptian Case Study Using the Autoregressive Distributed Lag (ARDL) Model." Sustainability 13, no. 6 (March 16, 2021): 3265. http://dx.doi.org/10.3390/su13063265.
Full textAbstract:
Both technological innovation and foreign direct investment have received widespread attention in the literature on their role in promoting economic growth. Therefore, this study aims to test the relationship between foreign direct investment, technological innovation, and economic growth of the Egyptian economy during the period between 1990–2019 using the autoregressive distributed lag model simultaneous integration test. Our findings show of the ARDL (Autoregressive Distributed Lag) model estimation a joint complementary relationship between the rate of growth of per capita gross domestic product (GDP) in US dollars and the independent variables in the model in the long and short term, which are statistically significant results. We found a positive significant relationship between the variables of incoming foreign direct investment and share of total capital formation in economic growth. Therefore, in the long term, the rate of inflation and the innovation index had a negative impact in the long term and the speed of adjustment towards equilibrium was very large, as it was estimated at 1.5 years (1/0.651). Furthermore, the study also provides valuable lessons and a strategic vision for the Egyptian government, which aspires to advance technology and attract more foreign direct investment.