2020
DOI: 10.2139/ssrn.3623033
|View full text |Cite
|
Sign up to set email alerts
|

Financial Vulnerability and Risks to Growth in Emerging Markets

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 16 publications
0
1
0
Order By: Relevance
“…They found that financially vulnerable population groups not only often struggle to make ends meet, but they also have difficulty controlling spending money. Acharya, Bhadury, and Surti (2020) also introduced a new financial vulnerability index for emerging market economies by exploiting key differences in their business cycles relative to those of advanced economies. Using the information on the domestic price of risk, cost of dollar hedging and market-based measures of bank vulnerability, their index significantly augmented early warning surveillance capacity, as evidenced by out-of-sample forecasting gains around a majority of turning points in GDP growth, relative to distributed lag models hitherto augmented with information from macrofinancial indexes that are custom-built to optimize such forecasts.…”
Section: Literature Reviewmentioning
confidence: 99%
“…They found that financially vulnerable population groups not only often struggle to make ends meet, but they also have difficulty controlling spending money. Acharya, Bhadury, and Surti (2020) also introduced a new financial vulnerability index for emerging market economies by exploiting key differences in their business cycles relative to those of advanced economies. Using the information on the domestic price of risk, cost of dollar hedging and market-based measures of bank vulnerability, their index significantly augmented early warning surveillance capacity, as evidenced by out-of-sample forecasting gains around a majority of turning points in GDP growth, relative to distributed lag models hitherto augmented with information from macrofinancial indexes that are custom-built to optimize such forecasts.…”
Section: Literature Reviewmentioning
confidence: 99%