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This paper introduces the quantile regression- based Distance-to-Default to Probability of Default (DD-PD) mapping, which links individual firms' DD to their real world PD. Since changes in the DD depend on a handful of parameters, the mapping easily accommodates shocks arising from quantitative...
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their forecasting performance. Based on the evaluation results, a new forecasting framework is developed for GDP projections … performance to past projections. Results show that the performance of the new framework often improves the forecasts, especially …
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Inflation has been below the Federal Reserve's target for much of the past 20 years, creating worries that inflation … forecasters, household and business surveys, and the market for Treasury inflation protected securities (TIPS) to estimate long …-run inflation expectations. These have fallen notably in the past few years (to roughly 1.9 percent for CPI inflation, well below …
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This paper examines the recent behavior of core inflation in the United States. We specify a simple Phillips curve … based on the assumptions that inflation expectations are fully anchored at the Federal Reserve’s target, and that labor …-market slack is captured by the level of shortterm unemployment. This equation explains inflation behavior since 2000, including …
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structures across countries and selects the optimal pool of countries to maximize out-of-sample prediction accuracy of a model … improve forecast accuracy relative to alternative pools. The algortihm improves nowcast performance for advanced economies, as …
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improve the transparency of machine learning-based forecasts. Applying the framework to Turkey reduces forecast errors by at …
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oil prices have significant effects on inflation. Results also suggest a significant impact of FDI and passport sales on …
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