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

This paper introduces the monthly State Bank of Pakistan's EasyData, for conducting empirical macroeconomic analysis and forecasting for Pakistan's economy. For this purpose. We perform a forecasting exercise using the conventional econometric models and the most recent machine-learning al...

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Bibliographic Details
Published inThe Lahore journal of economics Vol. 28; no. 1; pp. 63A - 88
Main Authors Shah, Ateeb Akhter, Raza, Hassan, Waheed, Mohsin
Format Journal Article
LanguageEnglish
Published Lahore Lahore School of Economics 01.04.2023
Subjects
Big Data
Central banks
Consumer Price Index
Datasets
Econometrics
Forecasting
Foreign exchange rates
GDP
Gross Domestic Product
Inflation
Machine learning
Macroeconomics
Regression analysis
Time series
Variables
Wholesale Price Index-US
Pakistan
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Summary:This paper introduces the monthly State Bank of Pakistan's EasyData, for conducting empirical macroeconomic analysis and forecasting for Pakistan's economy. For this purpose. We perform a forecasting exercise using the conventional econometric models and the most recent machine-learning algorithms. We find that the machine-learning models outperform the benchmark and regression models based on observed factors. Furthermore, the dataset has a higher ability to predict the external variables, a possible outcome of Pakistan's economy and its persistent balance of payment problem. The focus of policy has been to address this issue.
ISSN:1811-5438
1811-5446
DOI:10.35536/lje.2023.v28.il.a3