Journal articles: 'ARDL model'

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Lee, Kyung Hee, and Kyung Soo Kim. "Estimation of Tourism Demand using ARDL model." Korean Corporation Management Review 24, no. 4 (2017): 59–74. http://dx.doi.org/10.21052/kcmr.2017.24.4.03.

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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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العوفي, حكيمة, та زوليخة بصدار. "سوق العمل والنمو الاقتصادي : نموذج ARDL = Labor Market and Economic Growth : ARDL Model". Revue Organisation et Travail 6, № 2 (2017): 58–71. http://dx.doi.org/10.12816/0049430.

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Chang, Bisharat Hussain, Suresh Kumar Oad Rajput, and Niaz Ahmed Bhutto. "Impact of Exchange Rate Volatility on the US Exports: A New Evidence From Multiple Threshold Nonlinear ARDL Model." Journal of International Commerce, Economics and Policy 10, no. 02 (2019): 1950009. http://dx.doi.org/10.1142/s1793993319500091.

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This study extends previous literature by examining the effect of extremely large to extremely small changes in the exchange rate volatility on the US exports to developing countries such as Brazil, India, Mexico, and South Africa. We use novel approach called multiple threshold nonlinear ARDL (MTNARDL) and compare its results with ARDL and nonlinear ARDL models. The ARDL model supports insignificant results, whereas standard nonlinear ARDL model indicates asymmetric effect of exchange rate volatility on the US exports to Mexico only. Finally, the MTNARLD model indicates that in the short run, the effect of extremely large changes in exchange rate volatility does not significantly differ from the effect of small changes in exchange rate volatility on the US exports to all sample countries. Whereas in the long run, the effect of extremely large changes in exchange rate volatility is significantly different from the effect of small changes in exchange rate volatility on the US exports to all sample countries. The findings of this novel methodology suggest different policies in the long run and short run.

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Kayongo, Allan, Asumani Guloba, and Joseph Muvawala. "Asymmetric Effects of Exchange Rate on Monetary Policy in Emerging Countries: A Non-Linear ARDL Approach in Uganda." Applied Economics and Finance 7, no. 5 (2020): 24. http://dx.doi.org/10.11114/aef.v7i5.4928.

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Many money demand studies have been carried out on Uganda, however, these studies perceive and incorporate exchange rate as a linear determinant of real money demand. Indeed, exchange rate may have asymmetric effects on real money demand; with exchange rate appreciation having different effects from exchange rate depreciation. Therefore, this is the first study to estimate exchange rate asymmetries in Uganda, for the period 2008Q3 and 2018Q4. The study uses both the linear ARDL and non-linear ARDL methodologies to accomplish its goal. This is also done by incorporating an economic uncertainty index, which is critical, especially in light of the novel global coronavirus pandemic, that has disrupted trade, movement and supply chains. The error correction terms of both models are negative and significant, with the one of the non-linear ARDL twice as much as that of the linear ARDL. Indeed, the study confirms the existence of exchange rate asymmetries on Uganda’s real money demand. In the linear ARDL model, exchange rate has a positive effect in the long run but a negative result in the short run. On one hand, the non-linear ARDL model reveals that an exchange rate depreciation of the Uganda Shillings negatively affects real money demand in the short run. On the other hand, an exchange rate appreciation positively effects real money demand. Notably, economic uncertainty has insignificant effects in both models, except for its lags in the non-linear model. The implication of these findings is that macro-economic policy management in Uganda should be cognizant of these asymmetric effects of exchange rate, for effective planning, policy and implementation.

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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 (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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Thanabalasingam, T. "The Role of Political Stability, Labor Market and Education on Migration: The Empirical Evidence from Sri Lanka." Business and Economic Research 10, no. 2 (2020): 372. http://dx.doi.org/10.5296/ber.v10i2.16988.

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This study employs annual data from Sri Lanka over the period of 1990 – 2018 in order to investigate the impact of political instability and the existence of violence, unemployment rate, wage differential and level of education on migration. ADF unit root test confirmed that none of the variables are I(2), which allows us to examine the long run relationship between the variables using Autoregressive Distributed Lag (ARDL) Bound testing method. AIC is suggested to adapt ARDL (1, 0, 0, 2, 0) model among the top 20 models. ARDL Bound testing approach identified the cointegrating relationship between the variables. The results of both ARDL Bound test and the ARDL version of ECM detected that unemployment rate, political instability and the existence of violence/terrorism and level of education have a positive and significant impact on net migration whereas wage differential do not have significant impact on it even though it affect the net migration negatively both in the long run and in the short run respectively. Also, the coefficients of long run results and the Wald test confirm that the impact of unemployment rate is higher than wage differential, political instability and level of education on net migration in the long run. The result of CUSUM test of selected ARDL model discloses that the estimated model is stable and this model passes the all the diagnostic test. Moreover, Granger causality test identified a causal relationship that stemming from unemployment to net migration, wage differential to net migration, political instability to net migration and level of education to net migration. These findings could be useful to policy makers when they formulating and implementing the policy related to labor markets and good governance.

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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 (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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Farooq, Fatima, Muhammad Faheem, and Muhammad Zahid Usman. "Does Globalization Asymmetrically Affect CO2 Emissions in Pakistan? A New Evidence through NARDL Approach." Review of Education, Administration & LAW 3, no. 3 (2020): 511–22. http://dx.doi.org/10.47067/real.v3i3.96.

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The study examines the impact of globalization and institutional quality on environmental degradation in Pakistan. The study employs symmetric and asymmetric Autoregressive Distributed Lag Model (ARDL) at a time to check the linear and nonlinear effect of globalization on the environment over 1985 to 2017. The long-run findings of linear ARDL shows globalization affect positively to the environment and all other control variables FDI, GDP are significant with a positive sign while institutional quality and the interaction term of globalization and institutional quality is significant with a negative sign. The study also finds the marginal effect of interaction term and found that globalization has a different effect on the environment with different level of institutional quality. The linear ARDL model is not suitable to check the asymmetric behaviour of globalization on the environment. For this, the study applied a nonlinear ARDL estimation method. The findings of the nonlinear ARDL model showed the asymmetric behaviour of globalization on the environment. This study provides a new direction by proving the asymmetric relationship of globalization on environment quality that is more beneficial for policymakers and government officials.

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Rasheed, Abdul, Muhammad Asad Ullah, and Imam Uddin. "PKR Exchange Rate Forecasting Through Univariate and Multivariate Time Series Techniques." NICE Research Journal 13, no. 4 (2020): 49–67. http://dx.doi.org/10.51239/nrjss.v13i4.226.

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This study aims to examine and compare the accuracy of time series and econometric forecasting models in the context of the exchange rate as we know that fluctuation in the exchange rate may affect the economic activities at the macro – level. For this purpose, the author has chosen the Pakistani Rupee exchange rate against United States Dollars with the annual data from 1980 to 2018. The results revealed that the exponential model provides the most effective accuracy in forecasting rather than the Naive, ARIMA and ARDL Co-integration model. This paper has also covered the gap of unavailability of literature regarding the application of ARDL and Exponential Smoothing model for the forecasting of the exchange rate in Pakistan. It is also anticipated that historical data do not play a vital role in the forecasting of the future trend of time series i.e. Pakistani Rupees against US Dollars. However, all three-time series anticipated that the recent observations play a significant role in the speculation of the upcoming future trend. Keywords: Forecasting, Exchange Rate, Naïve Model, ARDL Co-Integration model, Econometrics

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Buhaerah, Pihri. "Pengaruh KPR terhadap Keterjangkauan Harga Properti Residensial." Kajian Ekonomi dan Keuangan 3, no. 3 (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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Güleç, Tuna Can. "Testing BIST for Equity Return Anomalies using ARDL Model." Journal of Business Research - Turk 13, no. 1 (2021): 100–111. http://dx.doi.org/10.20491/isarder.2021.1122.

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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 (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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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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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 (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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Ahmadi, Mohsen, and Rahim Taghizadeh. "A gene expression programming model for economy growth using knowledge-based economy indicators." Journal of Modelling in Management 14, no. 1 (2019): 31–48. http://dx.doi.org/10.1108/jm2-12-2017-0130.

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Purpose The purpose of this paper is to focus on modeling economy growth with indicators of knowledge-based economy (KBE) introduced by World Bank for a case study in Iran during 1993-2013. Design/methodology/approach First, for grouping and reducing the number of variables, Tukey method and the principal component analysis are used. Also for modeling, 67 per cent of data is used for training in the two approaches of ARDL bounds testing and gene expression programming (GEP) and 33 per cent of them for testing the models. Then, the result models are compared with fitness function and Akaike information criteria (AIC). Findings The GEP model with fitness 945.7461 for training data and 954.8403 for testing data from 1000 is better than ARDL bounds testing model with fitness 335.5479 from 1000. In addition, according to model comparison tools (AIC), the GEP model has an extremely larger weight in comparison with ARDL bounds model. Therefore, the GEP model is introduced for future use in academia. Practical implications Knowledge and information is one of the most basic sources of wealth in economists’ sight. Thus, using KBE indicators appears essential in economic growth regarding daily progress in knowledge processes and its different theories. It is also extremely important to determine an appropriate model for KBE indicators which play a highly important role in the allocation of the economic resources of the country in an optimal manner. Originality/value This paper introduced a novel expression for economy growth using KBE indicators. All the data and the indicators are extracted from Word Bank service between 1993 and 2013.

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Kathuria, Khyati, and Nand Kumar. "An Empirical Investigation of the Disaggregated Import Demand Function: Non-linear ARDL Framework." Foreign Trade Review 56, no. 2 (2021): 197–205. http://dx.doi.org/10.1177/0015732521995163.

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The article estimates the disaggregated import demand function for India using annual time series data for the period 1995–2017. The empirical results reveal strong evidence of long-run stable relationship among the variables considered in the study. The disaggregated import demand function is estimated for India using linear and non-linear ARDL model. The estimated linear ARDL model shows that gross capital formation, exports and relative prices affect import demand positively and significantly, both in the short and long run. While the impact of final consumption expenditure was found to be insignificant in the short run, it affects import demand significantly and positively in the long run. On the other hand, the result of the non-linear ARDL model shows the evidence of asymmetry in the impact of relative prices (positive and negative changes) on import demand, both in the short and long run. JEL Codes: F41, B17, B41, C51

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Karim, Norzitah Abdul, Syed Musa Syed Jaafar Al-Habshi, and Muhamad Abduh. "MACROECONOMICS INDICATORS AND BANK STABILITY: A CASE OF BANKING IN INDONESIA." Buletin Ekonomi Moneter dan Perbankan 18, no. 4 (2016): 431–48. http://dx.doi.org/10.21098/bemp.v18i4.609.

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This paper provides new empirical evidence of the bank stability in relation to the macroeconomic indicator of Indonesia. The bank stability is first calculated using Z-score, and then regressed using Autoregressive distributive lag (ARDL) model on the macroeconomic variables i.e. Gross Domestic Product (GDP) in US dollar, Interest rates (IR) in percentage and Consumer Price Index (CPI). To analyse further the long run relationship and the impact of bank stability, Cholesky standard deviation shock to the model, ARDL and Impulse Response Function (IRF) are used. These ARDL and IRF are carried out independently and repeated over data for three different models: (i) the commercial banks model, (ii) Islamic banks model, and (iii) the overall banking industry model. The empirical findings suggest long run relationship between the stability of commercial banks and macroeconomic factors. The findings also suggest the long run relationship between the stability of overall banking industry and macroeconomic factors. However, there is no evidence of long run relationship between the stability of Islamic banks and macroeconomics factors. Nevertheless, this finding is subject to the limitation of data, on the number of Islamic banks included in the test. The sample of Islamic banks was 5 banks from a total of 10 Islamic banks, due to insufficient data, as compared to the larger number of commercial banks taken into, as the sample.

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Koulis, Alexandros, George Kaimakamis, and Christina Beneki. "Hedging effectiveness for international index futures markets." Economics and Business 32, no. 1 (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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Ahmed, Yosri Nasr, and Huang Delin. "Current Situation of Egyptian Cotton: Econometrics Study Using ARDL Model." Journal of Agricultural Science 11, no. 10 (2019): 88. http://dx.doi.org/10.5539/jas.v11n10p88.

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The Egyptian cotton crop have experienced challenges in recent years from a drop in the quantity produced and exported, to a decrease in cultivated areas, this have affected the production quantity and value of exports. This study aims to bridge the research gap by exploring the nexus between cultivated area of cotton in Egypt, Relative profitability (cotton-clover/rice-clover), export quantity of cotton, the export prices of Egyptian cotton and the export prices of American cotton (Pima). In order to clarify the relationship between the variables studied and the cultivated area of cotton, the research use time series data from 1980 to 2016, using the Autoregressive Distributed Lag (ARDL) bound test to the find the co-integration between the variables after checking the stationarity in chosen variables with different unit root tests e.g. Augmented Dickey-Fuller (ADF) and the Phillips-Perron (PP). The results show, significant factors that influence the cultivated area of cotton include Relative profitability (cotton-clover/rice-clover), export quantity of cotton in long run term. Which underscores the need for government support in agriculture, in particular, cotton crop support. The increasing trend of cotton cost with declining revenue and decreasing in exports quantity is the main cause of decreased cultivated area of Egyptian cotton. Research recommends that support should be given to cotton farmers, in the form of agricultural equipment or training in good agricultural practices or set a price for cotton guaranteeing a decent profit margin for the farmers. The government (policy makers) should improve the productivity of cotton with the purpose of reducing the total costs and increasing the degree of competitiveness of the Egyptian cotton. Some effective policy measures may include but not limited to, farmer training programs and providing better extension services that will led to the capacity development of farmers.

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Dell'Anno, Roberto, and Ferda Halicioglu. "An ARDL model of unrecorded and recorded economies in Turkey." Journal of Economic Studies 37, no. 6 (2010): 627–46. http://dx.doi.org/10.1108/01443581011086666.

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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 (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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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 (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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Chen, Han, Rui Chen, Shaniel Bernard, and Imran Rahman. "US hotel industry revenue: an ARDL bounds testing approach." International Journal of Contemporary Hospitality Management 31, no. 4 (2019): 1720–43. http://dx.doi.org/10.1108/ijchm-01-2018-0031.

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Purpose This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound trips, personal consumption expenditure and number of hotel rooms as predictor variables. Additionally, the study applied the model in six sub-segments of the hotel industry – luxury, upper upscale, upscale, upper midscale, midscale and economy. Design/methodology/approach Using monthly aggregate data from the past 22 years, the study adopted the auto-regressive distribute lags (ARDL) approach in developing the estimation model. Unit root analysis and cointegration test were further utilized. The model showed significant utility in accurately estimating aggregate hotel industry and sub-segment revenue. Findings All predictor variables except number of rooms showed significant positive influences on aggregate hotel industry revenue. Substantial variations were noted regarding estimating sub-segment revenue. Consumer confidence index positively affected all sub-segment revenues, except for upper upscale hotels. Inbound trips by international tourists and personal consumption expenditure positively influenced revenue for all sub-segments but economy hotels. Domestic trips by US residents added significant explanatory power to only upper upscale, upscale and economy hotel revenue. Number of hotel rooms only had significant negative effect on luxury and upper upscale hotel sub-segment revenues. Practical implications Hotel operators can make marketing and operating decisions regarding pricing, inventory allocation and strategic management based on the revenue estimation models specific to their segments. Originality/value It is the first study that adopted the ARDL bound approach and analyzed the predictive capacity of macroeconomic variables on aggregate hotel industry and sub-segment revenue.

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Usman, Ojonugwa, and Osama Elsalih. "Testing the Effects of Real Exchange Rate Pass-Through to Unemployment in Brazil." Economies 6, no. 3 (2018): 49. http://dx.doi.org/10.3390/economies6030049.

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This paper attempts to test the pass-through of the real exchange rate (RERT) to unemployment in Brazil over the period 1981M1–2015M11 using linear and nonlinear Autoregressive Distributed Lag (ARDL) models. The result of the linearity test suggests that the relationship between RERT and unemployment is linear in the short-run and nonlinear in the long-run. Therefore, using the symmetric ARDL model for the short-run analysis, we find that an increase in the RERT decreases the unemployment rate. The result of the nonlinear ARDL for the long-run analysis shows that the unemployment rate reacts to the RERT appreciations and depreciations differently with depreciations having a strong effect. However, the pass-through of the RERT to unemployment is incomplete both in the short- and long-run. These findings have important policy implications for the designing of appropriate monetary policy in response to a rise in unemployment resulting from a change in the real exchange rate.

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Chuttoo, Usha Devi. "Effect of Economic Growth on Unemployment and Validity of Okun’s Law in Mauritius." Global Journal of Emerging Market Economies 12, no. 2 (2020): 231–50. http://dx.doi.org/10.1177/0974910119886934.

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This study examines the relationship between unemployment and economic growth in Mauritius. The methodology adopted for this study is the autoregressive distributed lag (ARDL) bounds cointegration test, ARDL error-correction model (ARDL-ECM) using the ordinary least square (OLS) approach and Okun’s law-gap version. ARDL-ECM estimates the long-run and short-run relationship between economic growth and unemployment. The validity of Okun’s law is tested in the Mauritian context and Okun’s coefficient is thereby estimated. The results obtained from the tests show that both in the long run and short run, there is a negative cointegration between economic growth and unemployment, but it is not statistically significant. Whereas, the result of Okun’s law-gap version shows that Okun’s law is indeed valid in the small economy of Mauritius. From the Okun’s coefficient obtained, it is concluded that 4 percent change in gross domestic product (GDP) growth rate changes unemployment rate by 1 percent in the opposite direction in Mauritius.

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Smahi, Ahmed. "The Determinants of the Foreign Direct Investment on the Macroeconomic Variables: The Case of the Algerian Economy." American Finance & Banking Review 3, no. 1 (2018): 5–11. http://dx.doi.org/10.46281/amfbr.v3i1.136.

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Foreign direct investment in Algeria as a percentage of GDP represented 0.9% during the last decade. The goal of this study is to assess the effect of Foreign Direct Investment on Algerian economy through an empirical analysis by applying the bounds testing ARDL and ECM-ARDL using annual data for the period 1970-2014. As far as the role of FDI is concerned, we shall try to highlight its effect that may show causal relationships to non-hydrocarbon GDP, non-hydrocarbon export, industry and employment in long run. Our estimation of an ARDL model indicates that the political and macroeconomic stability are not enough to attract FDI to help non-hydrocarbon sectors drive economic growth.

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Qamruzzaman, Md, and Jianguo Wei. "Financial Innovation, Stock Market Development, and Economic Growth: An Application of ARDL Model." International Journal of Financial Studies 6, no. 3 (2018): 69. http://dx.doi.org/10.3390/ijfs6030069.

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This study aims to explore the relationship between economic growth, financial innovation, and stock market development of Bangladesh for the period 1980–2016. To investigate long-run cointegration, this study used the autoregressive distributed lagged (ARDL) bounds testing approach. In addition, the Granger-causality test is used to identify directional causality between research variables under the error correction term. Study findings from the ARDL bound testing approach confirm the existence of a long-run association between financial innovation, stock market development, and economic growth. Furthermore, the findings from the Granger-causality test support bidirectional causality between financial innovation, economic growth and stock market development, and economic growth both in the long run and short run. These findings support the theory that market-based financial development and financial innovation in the financial system can spur economic development.

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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 (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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Shita, Aynalem, Nand Kumar, and Seema Singh. "Determinants of Agricultural Productivity in Ethiopia: ARDL Approach." Indian Economic Journal 66, no. 3-4 (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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moawad, rania. "Vector auto-regressive model (VAR) results’ versus auto-regressive distributive lags model (ARDL) results’." مجلة البحوث المالیة والتجاریة 22, no. 4 (2021): 115–26. http://dx.doi.org/10.21608/jsst.2021.81102.1292.

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Lee, Geul, and Doojin Ryu. "ASYMMETRY IN THE STOCK PRICE RESPONSE TO MACROECONOMIC SHOCKS: EVIDENCE FROM THE KOREAN MARKET." Journal of Business Economics and Management 19, no. 2 (2018): 343–59. http://dx.doi.org/10.3846/jbem.2018.5563.

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This study investigates stock price movements in response to macroeconomic shocks, allowing for asymmetry in this relationship. Given Ferson’s (1989) finding that large and small stocks can exhibit different risk behaviors, we examine the behaviors of the KOSPI and KOSDAQ stock markets in response to changes in the price level, real interest rate, and real USD/KRW exchange rate using simple and nonlinear autoregressive-distributed lag (ARDL) models. We find that the long-run effects of macroeconomic shocks are relatively insignificant under the simple ARDL model, whereas a significant and negative long-run effect is found for almost every explanatory variable–market pair under the nonlinear model. In addition, we find that the long-run effects of stock price shocks on macroeconomic variables are more significant under the nonlinear model. Overall, the results imply that it is difficult to identify the relationship between macroeconomic variables and stock price dynamics without considering asymmetry.

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Guizani, Sana, and Ines Kahloul Nafti. "The Determinants of Bitcoin Price Volatility: An Investigation With ARDL Model." Procedia Computer Science 164 (2019): 233–38. http://dx.doi.org/10.1016/j.procs.2019.12.177.

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Koyuncu, Prof Dr Cüneyt, and Tufan Sarıtaş. "Analysis of Globalization and Economic Growth for Turkey with ARDL Model." Anadolu Üniversitesi Sosyal Bilimler Dergisi 17, no. 2 (2017): 51–66. http://dx.doi.org/10.18037/ausbd.417241.

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Asmau, Yakubu Joy, Michael Samuel Agility, and Abarshi Jemimah Amina. "Dutch Disease: Myth or Reality? An Analysis of the ARDL Model." International Journal of Business, Economics and Management 6, no. 3 (2019): 130–40. http://dx.doi.org/10.18488/journal.62.2019.63.130.140.

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Ongan, Serdar, and Ismet Gocer. "Testing fisher effect for the USA: application of nonlinear ARDL model." Journal of Financial Economic Policy 12, no. 2 (2019): 293–304. http://dx.doi.org/10.1108/jfep-09-2018-0127.

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Purpose This paper aims to investigate the presence of the Fisher effect for the USA from a new methodological perspective differing it from all previous studies using the common linear representation of the Fisher equation. Design/methodology/approach The nonlinear ARDL model, recently developed by Shin et al. (2014), is applied for the 10-year US Government bond rates over the period of 1985M1-2017M10. Findings The empirical findings indicate that the US Federal Reserve (FED) is a more predominant arbiter in the determination of interest rates during periods of declining inflation rates than periods of rising inflation rates. This finding may allow the FED to apply more proactive and prudent monetary policy. Additionally, this study newly describes and introduces a different version of the partial Fisher effect and extends the Fisher equation to some degree in terms of the partial Fisher effect. Originality/value To the best the authors’ knowledge, this method is applied for the first time in testing the Fisher effect for the USA.

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Halicioglu, Ferda. "The J-curve dynamics of Turkey: an application of ARDL model." Applied Economics 40, no. 18 (2008): 2423–29. http://dx.doi.org/10.1080/00036840600949496.

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Dong, Qi, and Xiangbo Liu. "Multivariate filter estimation and ARDL model analysis of China’s potential output." Applied Economics Letters 25, no. 18 (2017): 1327–32. http://dx.doi.org/10.1080/13504851.2017.1420873.

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Neog, Yadawananda, and Achal Kumar Gaur. "Tax structure and economic growth in India: insights from ARDL model." Indian Growth and Development Review 13, no. 3 (2020): 589–605. http://dx.doi.org/10.1108/igdr-05-2019-0048.

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Purpose In the academic debate, the tax–growth relationship is always a controversial one. This paper aims to investigate the relationship between tax structure and economic growth in India for the period 1980-2016. After controlling for total tax revenue share to GDP in the estimation model, the authors examine the long-run and short-run relationship between tax structure and growth in India. Design/methodology/approach Auto-regressive distributed lag (ARDL) model has been used in this study. This bound cointegration model has certain advantages to the traditional cointegration model. This study also applies the threshold cointegration test of Hansen and Seo (2002) for examining non-linearity in tax–growth nexus. Findings The analysis shows that income tax share, corporation tax share and excise tax share are harmful to growth in the long-run. While the custom share is enlarging the growth performance. Corporation tax share is also reducing growth in the short-run. Following the Pesaran et al. (2001) approach of ARDL bound testing, the authors find the existence of a long-run relationship between studied variables. However, this study does not find any existence of threshold effect in the tax–growth relationship for India. Practical implications Based on the empirical findings, the author suggests that the prime tax change, which has the potential to impact both long-run growth and short-run economic recovery is the reduction of corporate tax rate with sustainable revenue generation. It will definitely enlarge the foreign direct investment, saving and investment in India. Originality/value This study will be a contribution to the empirical literature by investigating “tax–growth” relationship in the Indian case. To the knowledge, this will be the first study to examine this relationship for India with a recent data set.

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Deluna, Roperto S., Jeanette Isabelle V. Loanzon, and Virgilio M. Tatlonghari. "A nonlinear ARDL model of inflation dynamics in the Philippine economy." Journal of Asian Economics 76 (October 2021): 101372. http://dx.doi.org/10.1016/j.asieco.2021.101372.

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Jain, Vaishali. "Are the non-agricultural commodities markets efficient: an ARDL model approach." International Journal of Public Sector Performance Management 8, no. 1/2 (2021): 157. http://dx.doi.org/10.1504/ijpspm.2021.10040944.

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Jain, Vaishali. "Are the non-agricultural commodities markets efficient: an ARDL model approach." International Journal of Public Sector Performance Management 8, no. 1/2 (2021): 157. http://dx.doi.org/10.1504/ijpspm.2021.117721.

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Ilyas, Umer, Matti Ullah Butt, and Muhammad Gulzar. "An application of panel ARDL model with cointegration for portfolio management." International Journal of Economics and Business Research 23, no. 3 (2022): 275. http://dx.doi.org/10.1504/ijebr.2022.122051.

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Aljandali, Abdulkader, and Christos Kallandranis. "Exchange rate modelling in the development community using the ARDL cointegration approach: The case of emerging markets." Risk Governance and Control: Financial Markets and Institutions 10, no. 2 (2020): 53–70. http://dx.doi.org/10.22495/rgcv10i2p5.

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Despite rising interest in African economies, there is little prior research on the determinants of exchange rate movements in the region. This paper examines the monthly exchange rates of the country members of the Southern African Development Community (SADC) from 1990 to 2010 inclusive. Long-run equilibrium exchange rate models are established, exchange rate determinants are identified, and ex-post forecasts are generated for a period of 18 months (Sekantsi, 2011). The autoregressive distributed lag (ARDL) cointegration model is used in this paper, given its statistical advantages over commonly, applied cointegration techniques. Findings show that the ARDL method generates accurate forecasts for eight out of 11 sampled exchange rates. In keeping with earlier literature (e.g., Redda & Muzindusti, 2017; Zerihun & Breitenbach, 2017; etc.), findings suggest that the chances of SADC member countries fulfilling the requirements of a currency union are quite low. This paper marks one of the first attempts in the literature to forecast exchange rates in SADC using the ARDL approach (Pesaran & Shin, 1995). The results would be of interest to policy-makers, researchers and investors.

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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 (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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Morrison, Colin, and Ernest Albuquerque. "Modelling New Zealand Road Deaths." Journal of Road Safety 32, no. 2 (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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Menegaki, Angeliki N. "The ARDL Method in the Energy-Growth Nexus Field; Best Implementation Strategies." Economies 7, no. 4 (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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Bahmani-Oskooee, Mohsen, and Hadise Fariditavana. "Nonlinear ARDL approach, asymmetric effects and the J-curve." Journal of Economic Studies 42, no. 3 (2015): 519–30. http://dx.doi.org/10.1108/jes-03-2015-0042.

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Purpose – Previous research that investigated the effects of currency depreciation on the trade balance assumed that the adjustment of all variables in a given model is in linear fashion. The authors wonder if introduction of nonlinearity in the adjustment of some variables such as the exchange rate can shed additional light on evidence of the J-curve. The new approach also allows to test whether exchange rate changes have symmetric or asymmetric effects on the trade balance. Estimates of a trade balance model for Canada, China, Japan, and the USA reveal that the effects are indeed asymmetric. The paper aims to discuss these issues. Design/methodology/approach – The methodology is based on linear and nonlinear ARDL approach. Findings – When nonlinearity is introduced into testing approach for the J-curve, more evidence is found in support of the J-curve. Research limitations/implications – The models are estimated using aggregate trade flows of each country with the rest of the world, hence they suffer from aggregation bias. Using trade flows at bilateral level and at commodity level are highly recommended for future research. Originality/value – This is the first paper that applies nonlinear ARDL approach to test the short-run and long-run effects of currency depreciation on the trade balance.

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Al-Qudah, Ali Mustafa. "The Determinants of Money Demand in Jordan: ARDL Approach." Journal of Management Research 11, no. 1 (2019): 61. http://dx.doi.org/10.5296/jmr.v11i1.13771.

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The current study examined the relationship between real money demand (M2) and its determinants represented by real gross domestic product, real interest rate, inflation rate and budget deficit in Jordan for the period (2000Q1-20018Q1). The study used unit root test, Autoregressive Distributive Lag (ARDL), cointegration and long run, bound test to examine the study hypotheses. ARDL cointegration equation and ARDL Bound test show that there is a long run relationship between money demand M2 and its determinants, real interest rate, inflation rate, budget deficit and real gross domestic product. The short run ARDL results shows that the past period of money demand has a negative and significant impact on money demand, while inflation rate and Gross domestic product have a positive and significant impact on money demand in Jordan. The long run ARDL results show that the inflation rate, real gross domestic product and budget deficit have a positive long run relationship with money demand (M2)and Its impact on (M2 ) is positive and statistically significant at 1 percent level, while interest rate has a negative and significant impact on Money demand (M2 ). Inflation rate, real gross domestic product, budget deficit and interest rate are good determinants for money demand M2. The cumulative sum (CUSUM) of recursive residuals and cumulative sum of squares (CUSUMQ) of recursive residuals confirm that the estimated money demand M2 model is stable.

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Singh, Amar, and Arvind Mohan. "An Empirical Model for the Indian Foreign Investment and Stock Market Volatility: Evidence From ARDL Bounds Testing Analysis." International Journal of Financial Research 11, no. 2 (2020): 154. http://dx.doi.org/10.5430/ijfr.v11n2p154.

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Foreign investment is a major factor to determine volatility in the stock market. To discover the influence on Stock Market volatility of foreign investment we have considered FE, FD, and FDI as proxy variables of foreign investment and Indian stock market volatility is represented by Indian vix. The period for this study is 2009 to 2017 (monthly data). To address this issue of volatility in the long/short-run we have applied the ARDL. The preference given to the ARDL model over Johansen co-integration is to the difference in the order of integration among the variables. ARDL model allows us to combine the I(0) and I(1) series whereas I(1) required in the case of Johansen approach. Results of unit root confirm the I(0)/I(1) order of integration, which allows us to apply the ADRL bound test. F-statistics is higher than the upper bound critical value at 10%, 5% and providing the evidence of co-integration among variables at a 5% level of significance. Hence, there is a long-run relationship amid the variables. Long-run form results show the negative sign of the coefficient and it is significant. The ECM value is (-0.9671) and it confirms that nearly 96.71 % of the inaccuracy rose in each period and automatically corrected in specified time period.

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Journal articles on the topic 'ARDL model'

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