IDEAS home Printed from https://ideas.repec.org/a/lje/journl/v28y2023i1p63-88.html
   My bibliography  Save this article

Easydata-MD: A Monthly Dataset for Macroeconomic Research on Pakistan

Author

Listed:
  • Ateeb Akhter Shah Syed

    (State Bank of Pakistan, Pakistan)

  • Hassan Raza

    (FAST National University of Computer and Emerging Sciences, Islamabad, Pakistan)

  • Mohsin Waheed

    (State Bank of Pakistan, Pakistan)

Abstract

No abstract is available for this item.

Suggested Citation

  • Ateeb Akhter Shah Syed & Hassan Raza & Mohsin Waheed, 2023. "Easydata-MD: A Monthly Dataset for Macroeconomic Research on Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 28(1), pages 63-88, Jan-June.
  • Handle: RePEc:lje:journl:v:28:y:2023:i:1:p:63-88
    as

    Download full text from publisher

    File URL: https://lahoreschoolofeconomics.edu.pk/assets/uploads/lje/Volume28/03_Ateeb_Akhter_Hassan_Raza_and_Mohsin_Waheed.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bokun, Kathryn O. & Jackson, Laura E. & Kliesen, Kevin L. & Owyang, Michael T., 2023. "FRED-SD: A real-time database for state-level data with forecasting applications," International Journal of Forecasting, Elsevier, vol. 39(1), pages 279-297.
    2. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    3. Muhammad Nadim Hanif & Muhammad Jahanzeb Malik, 2015. "Evaluating the Performance of Inflation Forecasting Models of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 43-78.
    4. Fida Hussain & Asif Mahmood, 2017. "Predicting Output Growth and Inflation in Pakistan: The Role of Yield Spread," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 13, pages 53-76.
    5. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
    6. Fida Hussain & Kalim Hayder & Muhammad Rehman, 2018. "Nowcasting LSM Growth in Pakistan," SBP Working Paper Series 98, State Bank of Pakistan, Research Department.
    7. Fida Hussain & Asif Mahmood, 2017. "Predicting Inflation and Output in Pakistan: The Role of Yield Spread," SBP Working Paper Series 93, State Bank of Pakistan, Research Department.
    8. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    9. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, May.
    2. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
    3. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
    4. Vigo Pereira, Caio, 2021. "Portfolio efficiency with high-dimensional data as conditioning information," International Review of Financial Analysis, Elsevier, vol. 77(C).
    5. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    6. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
    7. Olivier Darne & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Economics Bulletin, AccessEcon, vol. 40(3), pages 2431-2439.
    8. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    9. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    10. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
    11. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
    12. Dimitris Korobilis, 2018. "Machine Learning Macroeconometrics: A Primer," Working Paper series 18-30, Rimini Centre for Economic Analysis.
    13. Sakemoto, Ryuta, 2021. "Economic Evaluation of Cryptocurrency Investment," MPRA Paper 108283, University Library of Munich, Germany.
    14. António Rua & Nuno Lourenço & Francisco Dias, 2018. "Forecasting exports with targeted predictors," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    15. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
    16. Maiorova, Ksenia & Fokin, Nikita, 2020. "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper 109557, University Library of Munich, Germany.
    17. Nikodinoska, Dragana & Käso, Mathias & Müsgens, Felix, 2022. "Solar and wind power generation forecasts using elastic net in time-varying forecast combinations," Applied Energy, Elsevier, vol. 306(PA).
    18. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.
    19. Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
    20. Li, W. & Fok, D. & Franses, Ph.H.B.F., 2019. "Forecasting own brand sales: Does incorporating competition help?," Econometric Institute Research Papers EI2019-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    More about this item

    Keywords

    EasyData; factors; forecasting; machine learning; machine-learning; Pakistan;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:lje:journl:v:28:y:2023:i:1:p:63-88. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Shahid Salahuddin (email available below). General contact details of provider: https://edirc.repec.org/data/lsecopk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.