A new index of financial conditions

By Gary Koop, Dimitris Korobilis. 2014

632 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/b045968f0d2d23bdc4f5d36eada1939398c24ee2

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Citations in the corpus

Comparing the forecasting ability of financial conditions indices: The case of South Africa (2018, neutral): “Koop and Korobilis (2014) refer to this restricted model as a factor-augmented TVP-VAR, or a FA-TVP-VAR.”
On the sources of uncertainty in exchange rate predictability (2018, background): “Thirty years on since Meese and Rogoff (1983) identified that exchange rate fluctuations are diffi cult to predict using standard economic models, academics and practitioners are yet to find a definite answer to whether or not macroeconomic variables have predictive content. In a thorough survey of ”
Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions (2020, methodology): “Forgetting Factor Sensitivity Analysis In addition, this TVP-VAR model heavily relies on forgetting factors, which are often set to a fixed value, as in Koop and Korobilis (2014), whereas in Koop and Korobilis (2013) they were allowed to vary using an additional process.”
Refined Measures of Dynamic Connectedness based on TVP-VAR (2017, methodology): “Our proposed TVP-VAR methodology, extends the originally proposed connectdenss approach of Diebold and Yılmaz (2009, 2012, 2014), by allowing the variances to vary via a stochastic volatility Kalman Filter estimation with forgetting factors introduced by Koop and Korobilis (2014).”
The Term Structure of Growth-at-Risk (2018, positive): “8 Specifically, the construction of the FCIs for the October 2017 GFSR differs from the standard Koop and Korobilis (2014) approach because it also discriminates one-year-ahead growth below the 20 percentile of historical outcomes from expected growth.”
International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression (2019, methodology): “Since this study analyzes daily data – oppposed to Koop and Korobilis (2014) – the benchmark model is based on κ1 = 0.”