Junaid Alam Memon

Personal Details

First Name:	Junaid
Middle Name:	Alam
Last Name:	Memon
Suffix:
RePEc Short-ID:	pme491
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Affiliation

Pakistan Institute of Development Economics (PIDE)

Islamabad, Pakistan
http://www.pide.org.pk/
RePEc:edi:pideipk (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

Sorry, no citations of working papers recorded.

Articles

1. Hussain, Anwar & Rahman, Muhammad & Memon, Junaid Alam, 2016. "Forecasting electricity consumption in Pakistan: the way forward," Energy Policy, Elsevier, vol. 90(C), pages 73-80.

   Cited by:

   1. Zhineng Hu & Jing Ma & Liangwei Yang & Xiaoping Li & Meng Pang, 2019. "Decomposition-Based Dynamic Adaptive Combination Forecasting for Monthly Electricity Demand," Sustainability, MDPI, vol. 11(5), pages 1-25, February.
   2. Akhtar, Muhammad & Haris, Muhammad & Naveed, Hafiz Muhammad & Rasool, Yasir & Al-Faryan, Mamdouh Abdulaziz Saleh, 2024. "Electricity shortfalls and financial leverage of listed firms in Pakistan," Utilities Policy, Elsevier, vol. 87(C).
   3. Barman, Mayur & Dev Choudhury, Nalin Behari, 2019. "Season specific approach for short-term load forecasting based on hybrid FA-SVM and similarity concept," Energy, Elsevier, vol. 174(C), pages 886-896.
   4. Abdullah, Fahad Bin & Iqbal, Rizwan & Hyder, Syed Irfan & Jawaid, Mohammad, 2020. "Energy security indicators for Pakistan: An integrated approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
   5. Muhammad Zubair & Ahmed Bilal Awan, 2021. "Economic viability of solar energy export from the Middle East and North Africa to Europe and South Asia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 17986-18007, December.
   6. Nyiko Worship Hlongwane & Olebogeng David Daw, 2023. "Electricity Consumption and Population Growth in South Africa: A Panel Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(3), pages 374-383, May.
   7. Radhakrishnan Angamuthu Chinnathambi & Anupam Mukherjee & Mitch Campion & Hossein Salehfar & Timothy M. Hansen & Jeremy Lin & Prakash Ranganathan, 2018. "A Multi-Stage Price Forecasting Model for Day-Ahead Electricity Markets," Forecasting, MDPI, vol. 1(1), pages 1-21, July.
   8. Hasnain Iftikhar & Nadeela Bibi & Paulo Canas Rodrigues & Javier Linkolk López-Gonzales, 2023. "Multiple Novel Decomposition Techniques for Time Series Forecasting: Application to Monthly Forecasting of Electricity Consumption in Pakistan," Energies, MDPI, vol. 16(6), pages 1-17, March.
   9. Ruma Talukdar & Nibedita Mahanta, 2023. "Forecasting of Domestic Electricity Consumption in Assam, India," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 229-235, September.
   10. Siyu Zhang & Liusan Wu & Ming Cheng & Dongqing Zhang, 2022. "Prediction of Whole Social Electricity Consumption in Jiangsu Province Based on Metabolic FGM (1, 1) Model," Mathematics, MDPI, vol. 10(11), pages 1-14, May.
   11. Mohammed Alamoudi & Osman Taylan & Behrooz Keshtegar & Mona Abusurrah & Mohammed Balubaid, 2022. "Modeling Sulphur Dioxide (SO 2 ) Quality Levels of Jeddah City Using Machine Learning Approaches with Meteorological and Chemical Factors," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
   12. Hlongwane, Nyiko Worship & Daw, Olebogeng David, 2022. "Renewable electricity consumption and economic growth: A comparative study of South Africa and Zimbabwe," MPRA Paper 115154, University Library of Munich, Germany, revised 24 Oct 2022.
   13. Lin, Boqiang & Raza, Muhammad Yousaf, 2021. "Analysis of electricity consumption in Pakistan using index decomposition and decoupling approach," Energy, Elsevier, vol. 214(C).
   14. Marcillo-Delgado, J.C. & Ortego, M.I. & Pérez-Foguet, A., 2019. "A compositional approach for modelling SDG7 indicators: Case study applied to electricity access," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 388-398.
   15. Wei-Chiang Hong & Guo-Feng Fan, 2019. "Hybrid Empirical Mode Decomposition with Support Vector Regression Model for Short Term Load Forecasting," Energies, MDPI, vol. 12(6), pages 1-16, March.
   16. Sajid Abrar & Hooman Farzaneh, 2021. "Scenario Analysis of the Low Emission Energy System in Pakistan Using Integrated Energy Demand-Supply Modeling Approach," Energies, MDPI, vol. 14(11), pages 1-30, June.
   17. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
   18. Huo, Meiqi & Yan, Weijie & Ren, Guoqian & Li, Yu, 2024. "A novel hybrid model based on modal decomposition and error correction for building energy consumption prediction," Energy, Elsevier, vol. 294(C).
   19. Sylvia Mardiana & Ferdinand Saragih & Martani Huseini, 2020. "Forecasting Gasoline Demand in Indonesia Using Time Series," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 132-145.
   20. Chen, Hai-Bao & Pei, Ling-Ling & Zhao, Yu-Feng, 2021. "Forecasting seasonal variations in electricity consumption and electricity usage efficiency of industrial sectors using a grey modeling approach," Energy, Elsevier, vol. 222(C).
   21. Silva, Felipe L.C. & Souza, Reinaldo C. & Cyrino Oliveira, Fernando L. & Lourenco, Plutarcho M. & Calili, Rodrigo F., 2018. "A bottom-up methodology for long term electricity consumption forecasting of an industrial sector - Application to pulp and paper sector in Brazil," Energy, Elsevier, vol. 144(C), pages 1107-1118.
   22. Feng, Qianqian & Sun, Xiaolei & Hao, Jun & Li, Jianping, 2021. "Predictability dynamics of multifactor-influenced installed capacity: A perspective of country clustering," Energy, Elsevier, vol. 214(C).
   23. Ullah, Kafait & Raza, Muhammad Shabbar & Mirza, Faisal Mehmood, 2019. "Barriers to hydro-power resource utilization in Pakistan: A mixed approach," Energy Policy, Elsevier, vol. 132(C), pages 723-735.
   24. Lu, Shixiang & Xu, Qifa & Jiang, Cuixia & Liu, Yezheng & Kusiak, Andrew, 2022. "Probabilistic load forecasting with a non-crossing sparse-group Lasso-quantile regression deep neural network," Energy, Elsevier, vol. 242(C).
   25. Nyoni, Thabani, 2019. "Modeling and forecasting demand for electricity in Zimbabwe using the Box-Jenkins ARIMA technique," MPRA Paper 96903, University Library of Munich, Germany.
   26. Abbasi, Kashif Raza & Shahbaz, Muhammad & Jiao, Zhilun & Tufail, Muhammad, 2021. "How energy consumption, industrial growth, urbanization, and CO2 emissions affect economic growth in Pakistan? A novel dynamic ARDL simulations approach," Energy, Elsevier, vol. 221(C).
   27. Shujaat Abbas & Hazrat Yousaf & Shabeer Khan & Mohd Ziaur Rehman & Dmitri Blueschke, 2023. "Analysis and Projection of Transport Sector Demand for Energy and Carbon Emission: An Application of the Grey Model in Pakistan," Mathematics, MDPI, vol. 11(6), pages 1-14, March.
   28. Rauf, Huzaifa & Gull, Muhammad Shuzub & Arshad, Naveed, 2020. "Complementing hydroelectric power with floating solar PV for daytime peak electricity demand," Renewable Energy, Elsevier, vol. 162(C), pages 1227-1242.
   29. Manuel Jaramillo & Diego Carrión, 2022. "An Adaptive Strategy for Medium-Term Electricity Consumption Forecasting for Highly Unpredictable Scenarios: Case Study Quito, Ecuador during the Two First Years of COVID-19," Energies, MDPI, vol. 15(22), pages 1-19, November.
   30. Khan, Muhammad Arshad & Abbas, Faisal, 2016. "The dynamics of electricity demand in Pakistan: A panel cointegration analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1159-1178.
   31. Ismail Shah & Hasnain Iftikhar & Sajid Ali, 2020. "Modeling and Forecasting Medium-Term Electricity Consumption Using Component Estimation Technique," Forecasting, MDPI, vol. 2(2), pages 1-17, May.
   32. Changrui Deng & Xiaoyuan Zhang & Yanmei Huang & Yukun Bao, 2021. "Equipping Seasonal Exponential Smoothing Models with Particle Swarm Optimization Algorithm for Electricity Consumption Forecasting," Energies, MDPI, vol. 14(13), pages 1-14, July.
   33. Ma, Haoran, 2022. "Prediction of industrial power consumption in Jiangsu Province by regression model of time variable," Energy, Elsevier, vol. 239(PB).
   34. Xingcai Zhou & Jiangyan Wang, 2021. "Panel semiparametric quantile regression neural network for electricity consumption forecasting," Papers 2103.00711, arXiv.org.
   35. Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
   36. Barman, Mayur & Dev Choudhury, N.B. & Sutradhar, Suman, 2018. "A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India," Energy, Elsevier, vol. 145(C), pages 710-720.
   37. Li, Yi & Liu, Tianya & Xu, Jinpeng, 2023. "Analyzing the economic, social, and technological determinants of renewable and nonrenewable electricity production in China: Findings from time series models," Energy, Elsevier, vol. 282(C).
   38. Ur Rehman, Syed Aziz & Cai, Yanpeng & Mirjat, Nayyar Hussain & Walasai, Gordhan Das & Nafees, Mohammad, 2019. "Energy-environment-economy nexus in Pakistan: Lessons from a PAK-TIMES model," Energy Policy, Elsevier, vol. 126(C), pages 200-211.
   39. Li, Siying & Cifuentes-Faura, Javier & Talbi, Besma & Sadiq, Muhammad & Si Mohammed, Kamel & Bashir, Muhammad Farhan, 2023. "Dynamic correlated effects of electricity prices, biomass energy, and technological innovation in Tunisia's energy transition," Utilities Policy, Elsevier, vol. 82(C).
   40. Yongquan Dong & Zichen Zhang & Wei-Chiang Hong, 2018. "A Hybrid Seasonal Mechanism with a Chaotic Cuckoo Search Algorithm with a Support Vector Regression Model for Electric Load Forecasting," Energies, MDPI, vol. 11(4), pages 1-21, April.
   41. Abbasi, Kashif Raza & Abbas, Jaffar & Tufail, Muhammad, 2021. "Revisiting electricity consumption, price, and real GDP: A modified sectoral level analysis from Pakistan," Energy Policy, Elsevier, vol. 149(C).
   42. Ding, Song & Hipel, Keith W. & Dang, Yao-guo, 2018. "Forecasting China's electricity consumption using a new grey prediction model," Energy, Elsevier, vol. 149(C), pages 314-328.
   43. Jamil, Rehan, 2020. "Hydroelectricity consumption forecast for Pakistan using ARIMA modeling and supply-demand analysis for the year 2030," Renewable Energy, Elsevier, vol. 154(C), pages 1-10.
   44. Rendón, Juan F. & Trespalacios, Alfredo & Cortés, Lina M. & Villada-Medina, Hernán D., 2021. "Modelización de la demanda de energía eléctrica: más allá de la normalidad || Electrical energy demand modeling: beyond normality," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 32(1), pages 83-98, December.
   45. Hlongwane, Nyiko Worship & Daw, Olebogeng David, 2022. "Electricity consumption and population growth in South Africa: A panel approach," MPRA Paper 113828, University Library of Munich, Germany.
   46. Cheng-Wen Lee & Bing-Yi Lin, 2016. "Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting," Energies, MDPI, vol. 9(11), pages 1-16, October.
   47. Cheng-Wen Lee & Bing-Yi Lin, 2017. "Applications of the Chaotic Quantum Genetic Algorithm with Support Vector Regression in Load Forecasting," Energies, MDPI, vol. 10(11), pages 1-18, November.
   48. Yi Liang & Dongxiao Niu & Ye Cao & Wei-Chiang Hong, 2016. "Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission," Energies, MDPI, vol. 9(11), pages 1-22, November.
   49. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
   50. Ghimire, Sujan & Nguyen-Huy, Thong & AL-Musaylh, Mohanad S. & Deo, Ravinesh C. & Casillas-Pérez, David & Salcedo-Sanz, Sancho, 2023. "A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction," Energy, Elsevier, vol. 275(C).
   51. Wang, Jianzhou & Gao, Jialu & Wei, Danxiang, 2022. "Electric load prediction based on a novel combined interval forecasting system," Applied Energy, Elsevier, vol. 322(C).
   52. Guo, Zhifeng & Zhou, Kaile & Zhang, Chi & Lu, Xinhui & Chen, Wen & Yang, Shanlin, 2018. "Residential electricity consumption behavior: Influencing factors, related theories and intervention strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 399-412.
   53. Peng Jiang & Jun Dong & Hui Huang, 2019. "Forecasting China’s Renewable Energy Terminal Power Consumption Based on Empirical Mode Decomposition and an Improved Extreme Learning Machine Optimized by a Bacterial Foraging Algorithm," Energies, MDPI, vol. 12(7), pages 1-24, April.
   54. Nyiko Worship Hlongwane & Olebogeng David Daw, 2023. "Renewable Electricity Consumption and Economic Growth: A Comparative Study of South Africa and Zimbabwe," International Journal of Energy Economics and Policy, Econjournals, vol. 13(3), pages 197-206, May.
   55. Syed Aziz Ur Rehman & Yanpeng Cai & Rizwan Fazal & Gordhan Das Walasai & Nayyar Hussain Mirjat, 2017. "An Integrated Modeling Approach for Forecasting Long-Term Energy Demand in Pakistan," Energies, MDPI, vol. 10(11), pages 1-23, November.
   56. Velasquez, Carlos E. & Zocatelli, Matheus & Estanislau, Fidellis B.G.L. & Castro, Victor F., 2022. "Analysis of time series models for Brazilian electricity demand forecasting," Energy, Elsevier, vol. 247(C).
   57. Aneeque A. Mir & Mohammed Alghassab & Kafait Ullah & Zafar A. Khan & Yuehong Lu & Muhammad Imran, 2020. "A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons," Sustainability, MDPI, vol. 12(15), pages 1-35, July.
   58. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
   59. da Silva, Felipe L.C. & Cyrino Oliveira, Fernando L. & Souza, Reinaldo C., 2019. "A bottom-up bayesian extension for long term electricity consumption forecasting," Energy, Elsevier, vol. 167(C), pages 198-210.
   60. Yuanyuan Zhou & Min Zhou & Qing Xia & Wei-Chiang Hong, 2019. "Construction of EMD-SVR-QGA Model for Electricity Consumption: Case of University Dormitory," Mathematics, MDPI, vol. 7(12), pages 1-23, December.
   61. Xiwen Cui & Shaojun E & Dongxiao Niu & Dongyu Wang & Mingyu Li, 2021. "An Improved Forecasting Method and Application of China’s Energy Consumption under the Carbon Peak Target," Sustainability, MDPI, vol. 13(15), pages 1-21, August.
   62. Wang, Lin & Hu, Huanling & Ai, Xue-Yi & Liu, Hua, 2018. "Effective electricity energy consumption forecasting using echo state network improved by differential evolution algorithm," Energy, Elsevier, vol. 153(C), pages 801-815.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-SEA: South East Asia (1) 2015-02-28

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