Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)
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 us...
| Main Authors: | , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-11-01
|
| Series: | Data |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5729/6/11/113 |
| _version_ | 1797510668549619712 |
|---|---|
| author | 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 Gulfishan Firdose Ahmed Fozia Homa Pushpika Tiwari Ritisha Balloo |
| author_facet | 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 Gulfishan Firdose Ahmed Fozia Homa Pushpika Tiwari Ritisha Balloo |
| author_sort | Pradeep Mishra |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T05:34:37Z |
| format | Article |
| id | doaj.art-979abbb289ca47bfb18e0f4f94a0662b |
| institution | Directory Open Access Journal |
| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-10T05:34:37Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Data |
| spelling | doaj.art-979abbb289ca47bfb18e0f4f94a0662b2023-11-22T22:59:38ZengMDPI AGData2306-57292021-11-0161111310.3390/data6110113Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)Pradeep Mishra0Khder Alakkari1Mostafa Abotaleb2Pankaj Kumar Singh3Shilpi Singh4Monika Ray5Soumitra Sankar Das6Umme Habibah Rahman7Ali J. Othman8Nazirya Alexandrovna Ibragimova9Gulfishan Firdose Ahmed10Fozia Homa11Pushpika Tiwari12Ritisha Balloo13College of Agriculture, Powarkheda, Jawaharlal Nehru Krishi Vishwavidyalaya, Jabalpur 461110, IndiaDepartment of Statistics and Programming, Faculty of Economics, University of Tishreen, Lattakia P.O. Box 2230, SyriaDepartment of System Programming, South Ural State University, 454080 Chelyabinsk, RussiaR.D. Engineering College, Ghazibad 01001, IndiaR.D. Engineering College, Ghazibad 01001, IndiaRegional Research and Technology Transfer Station (OUAT), Keonjhar 758002, IndiaDepartment of Statistics, Birsa Agricultural University, Kanke, Ranchi 834006, IndiaDepartment of Statistics, Assam University, Silchar 788011, IndiaDepartment of Commodity Research and Commodity Expertise, Plekhanov Russian University of Economics, 117997 Moscow, RussiaDepartment of Commodity Research and Commodity Expertise, Plekhanov Russian University of Economics, 117997 Moscow, RussiaDepartment of Computer Science, College of Agriculture—JNKVV, Hoshangabad 461110, IndiaDepartment of Statistics, Mathematics, and Computer Application, Bihar Agricultural University, Sabour, Bhagalpur 813210, IndiaM. Phil (NRM), Indian Institute of Forest Management (IIFM), Bhopal 462001, IndiaDepartment of Law and Management, University of Mauritius, Reduit 80837, MauritiusEconomics 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.https://www.mdpi.com/2306-5729/6/11/113nowcasting real GDPeconomic policy uncertaintyconsumer prices indexmixed-data samplingalmon weightingstructural break |
| spellingShingle | 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 Gulfishan Firdose Ahmed Fozia Homa Pushpika Tiwari Ritisha Balloo Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index) Data nowcasting real GDP economic policy uncertainty consumer prices index mixed-data sampling almon weighting structural break |
| title | Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index) |
| title_full | Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index) |
| title_fullStr | Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index) |
| title_full_unstemmed | Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index) |
| title_short | Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index) |
| title_sort | nowcasting india economic growth using a mixed data sampling midas model empirical study with economic policy uncertainty consumer prices index |
| topic | nowcasting real GDP economic policy uncertainty consumer prices index mixed-data sampling almon weighting structural break |
| url | https://www.mdpi.com/2306-5729/6/11/113 |
| work_keys_str_mv | AT pradeepmishra nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT khderalakkari nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT mostafaabotaleb nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT pankajkumarsingh nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT shilpisingh nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT monikaray nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT soumitrasankardas nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT ummehabibahrahman nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT alijothman nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT naziryaalexandrovnaibragimova nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT gulfishanfirdoseahmed nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT foziahoma nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT pushpikatiwari nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex AT ritishaballoo nowcastingindiaeconomicgrowthusingamixeddatasamplingmidasmodelempiricalstudywitheconomicpolicyuncertaintyconsumerpricesindex |