Dongho Song
Datos Biográficos
| ID | 8920694 |
|---|---|
| NOMBRE | Dongho Song |
| NOMBRES | Dongho |
| APELLIDO | Song |
| FIRMA | SONG D |
| AFILIACIONES | Boston College |
| VERIFICADO | No |
| TOTAL DE OBRAS | 3 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 3 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2015 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2024 |
| ÍNDICE H | 0 |
Are We Fragmented Yet? Measuring Geopolitical Fragmentation and Its Causal Effect
After decades of rising global economic integration, the world economy is fragmenting.To measure this, we introduce a geopolitical fragmentation index based on a dynamic hierarchical factor model with time-varying parameters and stochastic volatility.We then use structural vector autoregressions and local projections to assess the causal effects of fragmentation.Increased fragmentation negatively impacts the global economy, with emerging economie…
News-Driven Uncertainty Fluctuations
We investigate the channels through which news influences the subjective beliefs of economic agents, with a particular focus on their subjective uncertainty. The main insight of the article is that news that is more at odds with agents’ prior beliefs generates an increase in uncertainty; news that is more consistent with their prior beliefs generates a decrease in uncertainty. We illustrate this insight theoretically and then estimate the model e…
Real-Time Forecasting With a Mixed-Frequency VAR
This article develops a vector autoregression (VAR) for time series which are observed at mixed frequencies--quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to implement a data-driven hyperparameter selection. Using a real-time dataset, we evaluate forecasts from the mixed-frequency VAR and compare them to standard qua…
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Real-Time Forecasting With a Mixed-Frequency VAR
This article develops a vector autoregression (VAR) for time series which are observed at mixed frequencies--quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to implement a data-driven hyperparameter selection. Using a real-time dataset, we evaluate forecasts from the mixed-frequency VAR and compare them to standard qua…
News-Driven Uncertainty Fluctuations
We investigate the channels through which news influences the subjective beliefs of economic agents, with a particular focus on their subjective uncertainty. The main insight of the article is that news that is more at odds with agents’ prior beliefs generates an increase in uncertainty; news that is more consistent with their prior beliefs generates a decrease in uncertainty. We illustrate this insight theoretically and then estimate the model e…
Are We Fragmented Yet? Measuring Geopolitical Fragmentation and Its Causal Effect
After decades of rising global economic integration, the world economy is fragmenting.To measure this, we introduce a geopolitical fragmentation index based on a dynamic hierarchical factor model with time-varying parameters and stochastic volatility.We then use structural vector autoregressions and local projections to assess the causal effects of fragmentation.Increased fragmentation negatively impacts the global economy, with emerging economie…
Computer Science (2 obras) · Econometrics (2 obras) · Economics (2 obras) · Geography (2 obras) · Mathematics (2 obras) · Monetary Policy and Economic Impact (2 obras) · Statistics (2 obras) · Algorithm (1 obras) · Autoregressive model (1 obras) · Bayesian probability (1 obras)