Financial condition indices for emerging market economies: Can Google help?

被引:2
|
作者
Ferriani, Fabrizio [1 ]
Gazzani, Andrea [1 ]
机构
[1] Bank Italy, Rome, Italy
关键词
Financial condition index; Emerging markets; Google search; Principal component analysis; VAR; Quantile regressions; UNITED-STATES; TRENDS;
D O I
10.1016/j.econlet.2022.110528
中图分类号
F [经济];
学科分类号
02 ;
摘要
We compare alternative approaches to construct financial condition indices (FCIs) for major emerging market economies (EMEs). We further test whether measures of web-search intensity for keywords related to financial tensions can complement the informative content of traditional financial variables. We find that an index constructed as a simple average of key financial variables augmented with data from google searches outperforms several alternative definitions of FCIs to explain business cycle fluctuations and capital flows episodes. These results survive when controlling for proxies of the global financial cycle, highlighting that local financial markets conditions are important for the macroeconomic performance in EMEs. (C) 2022 Elsevier B.V. All rights reserved.
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页数:4
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