Indian Journal of Science and Technology
Year: 2019, Volume: 12, Issue: 21, Pages: 1-8
Hummaira Jabeenm* and M. Nadeem Qureshi
ISRA University, Hyderabad, Sindh, Pakistan; [email protected], [email protected]
*Author for correspondence
ISRA University, Hyderabad, Sindh, Pakistan.
Email: [email protected]
Objectives: To construct a Financial Condition Index (FCI) for the Pakistan using a broad range of financial and economic variables. Methods/Statistical Analysis: A financial condition index is created using the time varying method developed for the time frame of 1969 Q1 till 2016 Q1.This model yields three versions of the FCI namely TVP-FAVARs, FA-TVP- VARs, and heteroscedastic FAVARs. This method allows dealing with missing values and the values staring from different dates. This method not only constructs the index but also forecasts macroeconomic variables. Findings: Significant periods of economic growth and crisis in financial history are well captured by the index. By looking at different statistics of the dynamic forecast, it can be derived that fit is good and graph of the forecasts closely follows financial conditions, indicating that this index is having strong predictive power of the national accounts. Results show that constructed FCIs do have predictive power for macro- economic variables. This index correctly forecast major macro-economic variables and indicates that they both moves in same direction and correctly forecast in the Real Business Cycle (RBC) framework. FCI constructed here may serve as a decision making tool in place of monetary policy stances of those employed as policy tool. This FCI can also be utilized for identifying the historical development of any phenomena and current state of the system and may utilize for forecasting other macro-economic sectors. Application/Improvements: This study proposes new dimension for the policy studies; the constructed index study may help regulators, policy makers and scholars in assessing economic conditions.
Keywords: Bayesian Analysis, Financial Conditions, Financial Forecasts, Macroeconomic Analysis, Time Varying Model
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