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Interactions between macro-prudential framework and macroeconomic indicators

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The present work is an attempt to examine the macro-prudential measures with capital flows, exchange rate, stock prices and GDP of Asian emerging economies. This research is the extension of the developing the early warning signal as Financial Stability Index by Kaur and Gupta (in Conference proceedings in global trends in business & sustainability research, IIT Rourkee, 2017). The study acknowledges the importance of macro-prudential policy intervention for bringing in financial stability in the system. By synthesizing and visualizing information based on the past performance (using panel regression), it can be stated that this paper may be used to facilitate strategic decision-making at the policy level (government) of emerging economies and ensure building up of financial stability framework.

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Notes

  1. Financial Development–Financial Vulnerability–Financial Soundness.

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Author information

Authors and Affiliations

  1. Department of Management, Dayalbagh Educational Institute, Agra, India

    Jaspreet Kaur

  2. Department of Management, Prestige Institute of Management, Gwalior, India

    Navita Nathani

  3. Department of Economics, Dayalbagh Educational Institute, Agra, India

    Resham Chopra

Authors
  1. Jaspreet Kaur
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  2. Navita Nathani
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  3. Resham Chopra
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Corresponding author

Correspondence to Jaspreet Kaur.

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Appendices

Appendix 1: FD–FV–FS model used to develop Financial Stability Index (Kaur and Gupta 2017)

Indicators

Component

Market capitalization to GDP

Financial Development Index (FD)

Bank deposits to GDP

Broad money to GDP

Private sector credit to GDP

Interest rate spread

Herfindahl–Hirschman Index

Inflation rate

Financial Vulnerability Index (FV)

Current account deficit to GDP

General government budget surplus/deficit to GDP

REER

External debt to GDP

Short-term debt to reserves

Reserves to external Debt

Loans to deposits

Non-performing loans to total loans

Financial Soundness Index (FS)

Capital to assets

Capital-to-risk adjusted ratio

Liquidity ratio

Return on assets

Return on equity

Household debt to GDP

Stock market turnover ratio

Bond market turnover ratio

Appendix 2: Unit root analysis

In order to analyze the causal relationship between the variables, the data set for the analysis should be stationary. This means that variances in the series are constant and there is no problem of autocorrelation. Furthermore, it helps to analyze that the data are homoscedastic. Therefore, unit root testing of the data set is done. The hypotheses for the unit root analysis are:

H 0

Series has unit root

Unit root statistics

Variable

Method

Stats. (probability values < 0.05)

DCF

Null: Unit root (assumes common unit root process)

− 16.41*

Levin, Lin and Chu t

 

Null: Unit root (assumes individual unit root process)

− 13.10*

Im, Pesaran and Shin W-stat

 

ADF—Fisher Chi-square

139.9*

PP—Fisher Chi-square

188.1*

DEX

Null: Unit root (assumes common unit root process)

− 13.08*

Levin, Lin and Chu t

 

Null: Unit root (assumes individual unit root process) 

− 11.76*

Im, Pesaran and Shin W-stat

 

ADF—Fisher Chi-square

136.8*

PP—Fisher Chi-square

256.7*

LGDP

Null: Unit root (assumes common unit root process)

 

Levin, Lin and Chu

− 5.590*

Null: Unit root (assumes individual unit root process) 

 

Im, Pesaran and Shin W-stat

− 2.466*

ADF—Fisher Chi-square

38.85*

PP—Fisher Chi-square

35.17*

LSP

Null: Unit root (assumes common unit root process) 

 

Levin, Lin and Chu t

− 7.649*

Null: Unit root (assumes individual unit root process) 

 

Im, Pesaran and Shin W-stat

− 4.432*

ADF—Fisher Chi-square

64.66*

PP—Fisher Chi-square

69.41*

LFSI

Null: Unit root (assumes common unit root process)

 

Levin, Lin and Chu t

− 9.062*

Null: Unit root (assumes individual unit root process) 

 

Im, Pesaran and Shin W-stat

− 8.890*

ADF—Fisher Chi-square

103.93*

PP—Fisher Chi-square

130.86*

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Kaur, J., Nathani, N. & Chopra, R. Interactions between macro-prudential framework and macroeconomic indicators. Decision 46, 59–73 (2019). https://doi.org/10.1007/s40622-019-00203-y

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