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Journal articles on the topic 'Autoregressive Distributed Lag'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Hassler, Uwe, and Jürgen Wolters. "Autoregressive distributed lag models and cointegration." Allgemeines Statistisches Archiv 90, no. 1 (March 2006): 59–74. http://dx.doi.org/10.1007/s10182-006-0221-5.

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2

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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3

McNown, Robert, Chung Yan Sam, and Soo Khoon Goh. "Bootstrapping the autoregressive distributed lag test for cointegration." Applied Economics 50, no. 13 (August 21, 2017): 1509–21. http://dx.doi.org/10.1080/00036846.2017.1366643.

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4

Lal Shrestha, Srijan. "Particulate Air Pollution and Daily Mortality in Kathmandu Valley, Nepal: Associations and Distributed Lag." Open Atmospheric Science Journal 6, no. 1 (April 20, 2012): 62–70. http://dx.doi.org/10.2174/1874282301206010062.

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The distributed lag effect of ambient particulate air pollution that can be attributed to all cause mortality in Kathmandu valley, Nepal is estimated through generalized linear model (GLM) and generalized additive model (GAM) with autoregressive count dependent variable. Models are based upon daily time series data on mortality collected from the leading hospitals and exposure collected from the 6 six strategically dispersed fixed stations within the valley. The distributed lag effect is estimated by assigning appropriate weights governed by a mathematical model in which weights increased initially and decreased later forming a long tail. A comparative assessment revealed that autoregressive semiparametric GAM is a better fit compared to autoregressive GLM. Model fitting with autoregressive semi-parametric GAM showed that a 10 μg m rise in PM is associated with 2.57 % increase in all cause mortality accounted for 20 days lag effect which is about 2.3 times higher than observed for one day lag and demonstrates the existence of extended lag effect of ambient PM on all cause deaths. The confounding variables included in the model were parametric effects of seasonal differences measured by Fourier series terms, lag effect of mortality, and nonparametric effect of temperature represented by loess smoothing. The lag effects of ambient PM remained constant beyond 20 days.

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5

Lopo, Alexandre Boleira, Maria Helena Constantino Spyrides, Paulo Sérgio Lucio, and Javier Sigró. "UV Index Modeling by Autoregressive Distributed Lag (ADL Model)." Atmospheric and Climate Sciences 04, no. 02 (2014): 323–33. http://dx.doi.org/10.4236/acs.2014.42033.

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6

Kiviet, Jan F., and Jean-Marie Dufour. "Exact tests in single equation autoregressive distributed lag models." Journal of Econometrics 80, no. 2 (October 1997): 325–53. http://dx.doi.org/10.1016/s0304-4076(97)00048-1.

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7

Sam, Chung Yan, Robert McNown, and Soo Khoon Goh. "An augmented autoregressive distributed lag bounds test for cointegration." Economic Modelling 80 (August 2019): 130–41. http://dx.doi.org/10.1016/j.econmod.2018.11.001.

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8

Cho, Jin Seo, Tae-hwan Kim, and Yongcheol Shin. "Quantile cointegration in the autoregressive distributed-lag modeling framework." Journal of Econometrics 188, no. 1 (September 2015): 281–300. http://dx.doi.org/10.1016/j.jeconom.2015.05.003.

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9

Surekha, K. "Modeling Nonlinear Autoregressive Distributed Lag Models: A New Approach." Journal of Quantitative Economics 3, no. 1 (January 2005): 101–14. http://dx.doi.org/10.1007/bf03404778.

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10

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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11

Jordan, Soren, and Andrew Q. Philips. "Cointegration Testing and Dynamic Simulations of Autoregressive Distributed Lag Models." Stata Journal: Promoting communications on statistics and Stata 18, no. 4 (December 2018): 902–23. http://dx.doi.org/10.1177/1536867x1801800409.

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In this article, we introduce dynamac, a suite of commands designed to assist users in modeling and visualizing the effects of autoregressive distributed lag models and in testing for cointegration. We discuss the bounds cointegration test proposed by Pesaran, Shin, and Smith (2001, Journal of Applied Econometrics 16: 289–326), which we have adapted into a command. Because the resulting models can be dynamically complex, we follow the advice of Philips (2018, American Journal of Political Science 62: 230–244) by introducing a flexible command designed to dynamically simulate and plot a variety of types of autoregressive distributed lag models, including error-correction models.

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12

Dufour, Jean-Marie, and Jan F. Kiviet. "Exact Inference Methods for First-Order Autoregressive Distributed Lag Models." Econometrica 66, no. 1 (January 1998): 79. http://dx.doi.org/10.2307/2998541.

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13

Tian, Yuzhu, Liyong Wang, Manlai Tang, Yanchao Zang, and Maozai Tian. "Likelihood-based quantile autoregressive distributed lag models and its applications." Journal of Applied Statistics 47, no. 1 (June 24, 2019): 117–31. http://dx.doi.org/10.1080/02664763.2019.1633285.

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14

Abedi, Ali, Mohammad Mousavi Baygi, Parinaz Poursafa, Mohsen Mehrara, Mohammad Mehdi Amin, Forouzan Hemami, and Maryam Zarean. "Air pollution and hospitalization: an autoregressive distributed lag (ARDL) approach." Environmental Science and Pollution Research 27, no. 24 (May 29, 2020): 30673–80. http://dx.doi.org/10.1007/s11356-020-09152-x.

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15

Oyeniran, Ishola Wasiu, Oladipo Olalekan David, and Oluseyi Ajayi. "SMEs and Economic Growth in Nigeria: An Autoregressive Distributed Lag Approach." Lahore Journal of Business 3, no. 2 (March 1, 2015): 1–16. http://dx.doi.org/10.35536/ljb.2015.v3.i2.a1.

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This empirical study adopts an autoregressive distributed lag approach in order to examine how small and medium enterprises (SMEs) have contributed to economic growth in Nigeria between 1981 and 2013. We find that investment in SMEs has had a significant and positive impact on economic growth in the country. Given that Nigeria is economically underdeveloped, it is essential that the majority of its (largely rural) population be integrated into the process of economic development through entrepreneurship in small businesses. This means encouraging further investment in SMEs and prioritizing their access to credit facilities, infrastructure development, and capacity building to promote long-run socioeconomic development through this medium.

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16

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

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

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Mugableh, Mohamed Ibrahim. "Analysing the CO2 Emissions Function in Malaysia: Autoregressive Distributed Lag Approach." Procedia Economics and Finance 5 (2013): 571–80. http://dx.doi.org/10.1016/s2212-5671(13)00067-1.

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18

Shen, Chien wen, Heng chi Lee, and Ching chih Chou. "Measuring dynamic competitiveness among container ports: an autoregressive distributed lag approach." International Journal of Shipping and Transport Logistics 5, no. 6 (2013): 637. http://dx.doi.org/10.1504/ijstl.2013.056855.

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19

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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20

Dewi, Fitri Kurnia, and Heri Sudarsono. "Analisis Profitabilitas Bank Syariah Di Indonesia: Pendekatan Autoregressive Distributed Lag (ARDL)." Al-Mashrafiyah: Jurnal Ekonomi, Keuangan, dan Perbankan Syariah 5, no. 1 (April 29, 2021): 59. http://dx.doi.org/10.24252/al-mashrafiyah.v5i1.20281.

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21

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

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22

TSEN, WONG HOCK. "THE REAL EXCHANGE RATE DETERMINATION: EMPIRICAL EVIDENCE FROM MALAYSIA." Singapore Economic Review 59, no. 02 (June 2014): 1450016. http://dx.doi.org/10.1142/s0217590814500167.

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This study examines the real exchange rate determination in Malaysia. The result of the autoregressive distributed lag approach shows that an increase in the real interest rate differential, productivity differential, the real oil price or reserve differential will lead to an appreciation of the real exchange rate in the long run. The real oil price and reserve differential are important in the real exchange rate determination. The dynamic ordinary least squares (DOLS) estimator shows about the same conclusion of the autoregressive distributed lag approach. The result of the generalized forecast error variance decomposition shows that the real interest rate differential, productivity differential, the real oil price and reserve differential are generally important to the real exchange rate determination.

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23

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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24

Chen, Qian, Xiang Gao, Shan Xie, Li Sun, Shuairu Tian, and Shigeyuki Hamori. "On the Predictability of China Macro Indicator with Carbon Emissions Trading." Energies 14, no. 5 (February 25, 2021): 1271. http://dx.doi.org/10.3390/en14051271.

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Accurate and timely macro forecasting requires new and powerful predictors. Carbon emissions data with high trading frequency and short releasing lag could play such a role under the framework of mixed data sampling regression techniques. This paper explores the China case in this regard. We find that our multiple autoregressive distributed lag model with mixed data sampling method setup outperforms either the auto-regressive or autoregressive distributed lag benchmark in both in-sample and out-of-sample nowcasting for not only the monthly changes of the purchasing managers’ index in China but also the Chinese quarterly GDP growth. Moreover, it is demonstrated that such capability operates better in nowcasting than h-step ahead forecasting, and remains prominent even after we account for commonly-used macroeconomic predictive factors. The underlying mechanism lies in the critical connection between the demand for carbon emission in excess of the expected quota and the production expansion decision of manufacturers.

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25

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

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

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26

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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27

Alhassan, Abdul Latif, and Vera Fiador. "Insurance-growth nexus in Ghana: An autoregressive distributed lag bounds cointegration approach." Review of Development Finance 4, no. 2 (December 2014): 83–96. http://dx.doi.org/10.1016/j.rdf.2014.05.003.

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28

Yong, Wan-Lin, Jerome Kueh, Yong Sze Wei, and Jang-Haw Tiang. "Energy Consumption and Economic Growth Nexus in China: Autoregressive Distributed Lag (ARDL)." Journal of Public Administration and Governance 10, no. 2 (June 1, 2020): 194. http://dx.doi.org/10.5296/jpag.v10i2.16900.

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

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Janjua, Pervez Zamurrad, Ghulam Samad, and Nazakatullah Khan. "Climate Change and Wheat Production in Pakistan: An Autoregressive Distributed Lag Approach." NJAS - Wageningen Journal of Life Sciences 68 (March 2014): 13–19. http://dx.doi.org/10.1016/j.njas.2013.11.002.

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Laguna, Francisco, María Eugenia Grillet, José R. León, and Carenne Ludeña. "Modelling malaria incidence by an autoregressive distributed lag model with spatial component." Spatial and Spatio-temporal Epidemiology 22 (August 2017): 27–37. http://dx.doi.org/10.1016/j.sste.2017.05.001.

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31

Akinlo, A. Enisan. "The stability of money demand in Nigeria: An autoregressive distributed lag approach." Journal of Policy Modeling 28, no. 4 (May 2006): 445–52. http://dx.doi.org/10.1016/j.jpolmod.2005.09.001.

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32

Singhania, Monica, and Neha Saini. "Revisiting environmental degradation and economic growth nexus using autoregressive distributed lag approach." International Journal of Productivity and Performance Management 69, no. 8 (August 6, 2020): 1765–96. http://dx.doi.org/10.1108/ijppm-10-2019-0509.

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PurposeThe paper attempts to revisit the nexus between economic growth, carbon emissions, trade openness, financial effectiveness and FDI for a sample of seven developed and developing countries using curvilinear relationship as per environmental Kuznets curve (EKC) hypothesis over long term.Design/methodology/approachThe authors determine the unit root properties of variables (using Clemente–Montañés–Reyes unit root test with double mean shifts and AO model and augmented Dickey–Fuller test) for structural breaks at different levels. Autoregressive distributed lag (ARDL) and error correction model (ECM) methodology was used to estimate long- and short-run parameters among the selected variables in sample countries from 1965 to 2016. Vector error correction (VEC) and Granger causality approach was used to determine the direction of causality.FindingsThe authors confirmed long-run relationship among the variables and highlighted high economic growth and energy consumption as the main causes of environmental degradation. While in India financial development and FDI inflows depict a negative association with environmental sustainability, however, such relationship was positive in the United Kingdom (UK), which is often considered as a benchmark for policymakers. The authors’ findings were in agreement with existing research insights in reporting FDI and financial development as the major contributors towards (unsustainable) sustainable environment through emissions in case of (developing country like India) developed country like UK. For other sample countries (China, Brazil, Japan, South Africa, United States of America (USA)), the authors’ model failed to capture financial development and FDI as significant contributors of carbon emissions. However, unidirectional causality running from energy to carbon emission was observed leading to the policy adoption of incentivizing alternative energy-based resources to increase energy efficiency across the energy value chain.Research limitations/implicationsManufacturing with renewable energy, in collaboration with private and foreign players, under an institutional framework is desirable. Policy instruments including mandatory administrative controls, economic incentives and voluntary schemes that promote energy efficiency building blocks need to be established. A sound legal system for implementing technological innovation, financial subsidy incentives, interest-free loan programmes and development of financial sector supports creation and thriving of energy efficient units, often a perquisite for accelerated development.Originality/valueBy undertaking a comparative analysis, the authors address the research gap through revisiting EKC hypothesis with different set of trade policy and financial development framework. To the best of the authors’ knowledge, earlier studies were limited to one-country data analysis and did not consider the comparative data set of developed and developing countries with reference to financial development and FDI components.

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Galvao JR., Antonio F., Gabriel Montes-Rojas, and Sung Y. Park. "Quantile Autoregressive Distributed Lag Model with an Application to House Price Returns*." Oxford Bulletin of Economics and Statistics 75, no. 2 (December 21, 2011): 307–21. http://dx.doi.org/10.1111/j.1468-0084.2011.00683.x.

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34

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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Gerrard, W. J., and L. G. Godfrey. "Diagnostic Checks for Single-equation Error-correction and Autoregressive Distributed Lag Models." Manchester School 66, no. 2 (March 1998): 222–37. http://dx.doi.org/10.1111/1467-9957.00098.

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draibati, yassera, Mahmoud Mohammad, and malak atwez. "Estimating Agricultural Production Function in Syria using Autoregressive Distributed Lag Approach) ARDL(." Journal of Agricultural Economics and Social Sciences 11, no. 12 (December 1, 2020): 1101–7. http://dx.doi.org/10.21608/jaess.2021.57356.1001.

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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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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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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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Kwang-Jing Yii, Chai-Thing Tan, Nian-Meng Tan, Xue-Wen Teng, Ting-En Khor, and Sui-Hang Fan. "Hot Money and Stock Market in China: Empirical Evidence from ARDL and NARDL Approaches." International Journal of Business and Society 22, no. 2 (August 12, 2021): 713–33. http://dx.doi.org/10.33736/ijbs.3753.2021.

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

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Pal, D., and S. K. Mitra. "Impact of price realization on India’s tea export: Evidence from Quantile Autoregressive Distributed Lag Model." Agricultural Economics (Zemědělská ekonomika) 61, No. 9 (June 6, 2016): 422–28. http://dx.doi.org/10.17221/209/2014-agricecon.

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Mariadas, Paul Anthony, Hussin Abdullah, and Norehan Abdullah. "The Effect of Ageing Population on House Prices in Malaysia. An Autoregressive Distributed Lag (ARDL) Cointegration Approach." International Journal of Psychosocial Rehabilitation 24, no. 02 (February 12, 2020): 2468–76. http://dx.doi.org/10.37200/ijpr/v24i2/pr200543.

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Saxena, K. K., and Mohamed Ally Ndule. "The effect of oil price shocks on inflation in Tanzania - an autoregressive distributed lag and vector autoregressive approach*." Bulletin of Pure & Applied Sciences- Mathematics and Statistics 39e, no. 2 (2020): 232–56. http://dx.doi.org/10.5958/2320-3226.2020.00025.9.

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Guo, Mingyuan, and Yanfang Hu. "The Impact of Financial Development on Carbon Emission: Evidence from China." Sustainability 12, no. 17 (August 26, 2020): 6959. http://dx.doi.org/10.3390/su12176959.

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This paper studies the impact of financial development on carbon emissions in China from 1997 to 2016. First, this paper uses the entropy method to construct a synthetical index to measure the financial development. Meanwhile, a two-dimensional panel framework is introduced to group provinces in the panel analysis. The estimation results of the time series autoregressive distributed lag model show that for China as a whole, there is a weak carbon emissions reduction effect of financial development, whether it is a long-term effect or a short-term effect. The estimation results of the panel autoregressive distributed lag model also support that an increase in financial development suppresses carbon emissions. Although financial development inhibits carbon emissions both in the short run and in the long run, the absolute value of the long-term coefficient of financial development is significantly greater than that of the short-term coefficient.

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Kamasa, K. "Do Crude Oil Price Changes Affect Economic Welfare? Empirical Evidence from Ghana." Ghana Mining Journal 20, no. 1 (July 7, 2020): 51–58. http://dx.doi.org/10.4314/gm.v20i1.6.

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Abstract This paper sought to explore the impact of crude oil price changes on economic welfare in Ghana. The paper employed the Autoregressive distributed lag (ARDL) estimation technique on an annual time series data spanning 1983 – 2017. The findings revealed that crude oil price changes have a negative and significant impact on economic welfare in the short and long run, albeit marginal. In terms of covariates, the findings revealed that trade openness and gross fixed capital formation have positive and significant impact whilst interest rate have negative impact on economic welfare in both the short and long run. Foreign direct investment had a positive effect, albeit insignificant. The paper recommends among others, the hedging of prices with respect to imported crude oil so as to manage the risks associated with crude oil price changes on economic welfare. Keywords: Economic Welfare; Crude Oil Prices Changes; Autoregressive Distributed Lag; Ghana

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Ghorbani Pashakolaei, Vahid, Mohammad Babazade, and Khalil Ghadimi Dizaj. "The Effect of Natural Gas Price liberalization on Natural Gas Consumption in Residential sector in Iran." Journal of Global Economy 8, no. 4 (January 4, 2013): 315–25. http://dx.doi.org/10.1956/jge.v8i4.270.

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The Balance between demand and supply of energy carriers is an important issue. Price liberalization of natural gas is one of the best solutions to reduce natural gas consumption so we investigated this matter in our study. In this study use of autoregressive distributed lag model and error correction model model and results indicated that in first scenario (2011-13) annual growth of consumption will be 2.7 percent and its second scenario (2011-15) annual growth of consumption will be 4.2 percent. In first scenario annual consumption will be 36258.56, 36075.51 and 37352.13 million cubic meter respectively and in second scenario will be 37965.73, 38003.13, 39414.1, 41454 and 43931.57 13 million cubic meter respectively. Predict that liberalization in first and second scenario will be decrease 29.19 and 37.21 milliard cubic meter of total consumption in these years respectively. Keywords: liberalization, autoregressive distributed lag, error correction, natural gas

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Almosabbeh, Imadeddin Ahmed. "Is the Relationship Between Government Spending and Private Consumption in Egypt Symmetric?" Margin: The Journal of Applied Economic Research 14, no. 3 (July 31, 2020): 285–308. http://dx.doi.org/10.1177/0973801020920096.

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

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Wu, Hung-Ming. "The impact of non-clean energy consumption on economic growth: Evidence from symmetric and asymmetric analyses in the US." Energy & Environment 31, no. 2 (July 30, 2019): 291–307. http://dx.doi.org/10.1177/0958305x19865102.

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Non-clean energy consumption is one of the key components of environmental quality. The current study investigates the symmetric and asymmetric effects of non-clean energy consumption (total fossil fuel consumption) on economic growth by including clean energy consumption (nuclear electric power consumption and total renewable energy consumption) as well as capital and financial development in the production function. The linear autoregressive distributed lag and nonlinear autoregressive distributed lag bounds testing approaches were applied to conduct symmetric and asymmetric analyses in the US. The range of analysis is from 1960 to 2015. Ultimately, the study’s findings indicate that non-clean energy has an asymmetric effect on economic growth. In other words, improving environmental quality (by decreasing non-clean energy consumption) will reduce economic growth in the long term, but not in the short term. This research is therefore applicable for policymakers in the US.

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Mekonen, Endalkachew Kabtamu. "Agriculture Sector Growth and Inflation in Ethiopia: Evidence from Autoregressive Distributed Lag Model." Open Journal of Business and Management 08, no. 06 (2020): 2355–70. http://dx.doi.org/10.4236/ojbm.2020.86145.

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I.D, Mohammed, and Sule Abubakar. "Deficit Financing Asymmetry and Nigerias Economic Growth: A Nonlinear Autoregressive Distributed Lag Approach." Economics and Finance Letters 7, no. 2 (2020): 112–21. http://dx.doi.org/10.18488/journal.29.2020.72.112.121.

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