Luis Uzeda
Biographic Data
| ID | 8878999 |
|---|---|
| NAME | Luis Uzeda |
| GIVEN NAMES | Luis |
| FAMILY NAME | Uzeda |
| SIGNATURE | UZEDA L |
| AFFILIATIONS | Bank of Canada |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Sectoral Uncertainty
We propose a new empirical framework to estimate sectoral uncertainty from data-rich environments. We jointly decompose the conditional variance of economic time series into a common, a sector-specific, and an idiosyncratic component. By specifying a hierarchical-factor structure to stochastic volatility modeling, our framework combines both dimension reduction and flexibility. To estimate the model, we develop an efficient Markov Chain Monte Car…
Understanding trend inflation through the lens of the goods and services sectors
We distinguish between the goods and services sectors in an unobserved components model of U.S. inflation. We find that prior to the early 1990s, both sectors contributed to volatility of aggregate trend inflation, while since then, this has been predominantly driven by the services sector, with the trend in goods inflation being essentially flat. We document that the large reduction in the volatility of the trend for goods inflation has been the…
Endogenous Time Variation in Vector Autoregressions
We introduce a new class of time-varying parameter vector autoregressions (TVP-VARs) where the identified structural innovations are allowed to influence the dynamics of the coefficients in these models. An estimation algorithm and a parameterization conducive to model comparison are also provided. We apply our framework to the U.S. economy. Scenario analysis suggests that once accounting for the influence of structural shocks on the autoregressi…
No prominent works on this page.
Understanding trend inflation through the lens of the goods and services sectors
We distinguish between the goods and services sectors in an unobserved components model of U.S. inflation. We find that prior to the early 1990s, both sectors contributed to volatility of aggregate trend inflation, while since then, this has been predominantly driven by the services sector, with the trend in goods inflation being essentially flat. We document that the large reduction in the volatility of the trend for goods inflation has been the…
Endogenous Time Variation in Vector Autoregressions
We introduce a new class of time-varying parameter vector autoregressions (TVP-VARs) where the identified structural innovations are allowed to influence the dynamics of the coefficients in these models. An estimation algorithm and a parameterization conducive to model comparison are also provided. We apply our framework to the U.S. economy. Scenario analysis suggests that once accounting for the influence of structural shocks on the autoregressi…
Sectoral Uncertainty
We propose a new empirical framework to estimate sectoral uncertainty from data-rich environments. We jointly decompose the conditional variance of economic time series into a common, a sector-specific, and an idiosyncratic component. By specifying a hierarchical-factor structure to stochastic volatility modeling, our framework combines both dimension reduction and flexibility. To estimate the model, we develop an efficient Markov Chain Monte Car…
Econometrics (3 works) · Economics (3 works) · Market Dynamics and Volatility (3 works) · Monetary Policy and Economic Impact (3 works) · Macroeconomics (2 works) · Autoregressive model (1 work) · Economic theories and models (1 work) · Economy (1 work) · Energy, Environment, Economic Growth (1 work) · Estimation (1 work)