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Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)

Author

Listed:
  • Pradeep Mishra

    (College of Agriculture, Powarkheda, Jawaharlal Nehru Krishi Vishwavidyalaya, Jabalpur 461110, India)

  • Khder Alakkari

    (Department of Statistics and Programming, Faculty of Economics, University of Tishreen, Lattakia P.O. Box 2230, Syria)

  • Mostafa Abotaleb

    (Department of System Programming, South Ural State University, 454080 Chelyabinsk, Russia)

  • Pankaj Kumar Singh

    (R.D. Engineering College, Ghazibad 01001, India)

  • Shilpi Singh

    (R.D. Engineering College, Ghazibad 01001, India)

  • Monika Ray

    (Regional Research and Technology Transfer Station (OUAT), Keonjhar 758002, India)

  • Soumitra Sankar Das

    (Department of Statistics, Birsa Agricultural University, Kanke, Ranchi 834006, India)

  • Umme Habibah Rahman

    (Department of Statistics, Assam University, Silchar 788011, India)

  • Ali J. Othman

    (Department of Commodity Research and Commodity Expertise, Plekhanov Russian University of Economics, 117997 Moscow, Russia)

  • Nazirya Alexandrovna Ibragimova

    (Department of Commodity Research and Commodity Expertise, Plekhanov Russian University of Economics, 117997 Moscow, Russia)

  • Gulfishan Firdose Ahmed

    (Department of Computer Science, College of Agriculture—JNKVV, Hoshangabad 461110, India)

  • Fozia Homa

    (Department of Statistics, Mathematics, and Computer Application, Bihar Agricultural University, Sabour, Bhagalpur 813210, India)

  • Pushpika Tiwari

    (M. Phil (NRM), Indian Institute of Forest Management (IIFM), Bhopal 462001, India)

  • Ritisha Balloo

    (Department of Law and Management, University of Mauritius, Reduit 80837, Mauritius)

Abstract

Economics suffers from a blurred view of the economy due to the delay in the official publication of macroeconomic variables and, essentially, of the most important variable of real GDP. Therefore, this paper aimed at nowcasting GDP in India based on high-frequency data released early. Instead of using a large set of data thus increasing statistical complexity, two main indicators of the Indian economy (economic policy uncertainty and consumer price index) were relied on. The paper followed the MIDAS–Almon (PDL) weighting approach, which allowed us to successfully capture structural breaks and predict Indian GDP for the second quarter of 2021, after evaluating the accuracy of the nowcasting and out-of-sample prediction. Our results indicated low values of the RMSE in the sample and when predicting the out-of-sample1- and 4-quarter horizon, but RMSE increased when predicting the 10-quarter horizon. Due to the effect of the short-term structural break, we found that RMSE values decreased for the last prediction point.

Suggested Citation

  • Pradeep Mishra & Khder Alakkari & Mostafa Abotaleb & Pankaj Kumar Singh & Shilpi Singh & Monika Ray & Soumitra Sankar Das & Umme Habibah Rahman & Ali J. Othman & Nazirya Alexandrovna Ibragimova & Gulf, 2021. "Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)," Data, MDPI, vol. 6(11), pages 1-15, November.
    • Handle: RePEc:gam:jdataj:v:6:y:2021:i:11:p:113-:d:670942
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    References listed on IDEAS

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