Marine Carrasco
Biographic Data
| ID | 8920383 |
|---|---|
| NAME | Marine Carrasco |
| GIVEN NAMES | Marine |
| FAMILY NAME | Carrasco |
| SIGNATURE | CARRASCO M |
| AFFILIATIONS | University of Rochester |
| ORCID | 0000-0002-0079-685X |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2002 |
| LATEST PUBLICATION YEAR | 2016 |
| H-INDEX | 0 |
In-Sample Inference and Forecasting in Misspecified Factor Models
This article considers in-sample prediction and out-of-sample forecasting in regressions with many exogenous predictors. We consider four dimension-reduction devices: principal components, ridge, Landweber Fridman, and partial least squares. We derive rates of convergence for two representative models: an ill-posed model and an approximate factor model. The theory is developed for a large cross-section and a large time-series. As all these method…
Tests for Unit-Root versus Threshold Specification With an Application to the Purchasing Power Parity Relationship
We consider modeling the real exchange rate by a stationary three-regime self-exciting threshold autoregressive (SETAR) model with possibly a unit root in the middle regime. This representation is consistent with purchasing power parity in the presence of trading costs. Our main contribution is to provide statistical tools for testing unit root versus a SETAR. First, we show that a SETAR with a unit root in the middle regime is stationary and mix…
Simulation-Based Method of Moments and Efficiency
The method of moments is based on a relation Eθ0(h(Xt, θ)) = 0, from which an estimator of θ is deduced. In many econometric models, the moment restrictions can not be evaluated numerically due to, for instance, the presence of a latent variable. Monte Carlo simulations method make possible the evaluation of the generalized method of moments (GMM) criterion. This is the basis for the simulated method of moments. Another approach involves defining…
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Simulation-Based Method of Moments and Efficiency
The method of moments is based on a relation Eθ0(h(Xt, θ)) = 0, from which an estimator of θ is deduced. In many econometric models, the moment restrictions can not be evaluated numerically due to, for instance, the presence of a latent variable. Monte Carlo simulations method make possible the evaluation of the generalized method of moments (GMM) criterion. This is the basis for the simulated method of moments. Another approach involves defining…
Tests for Unit-Root versus Threshold Specification With an Application to the Purchasing Power Parity Relationship
We consider modeling the real exchange rate by a stationary three-regime self-exciting threshold autoregressive (SETAR) model with possibly a unit root in the middle regime. This representation is consistent with purchasing power parity in the presence of trading costs. Our main contribution is to provide statistical tools for testing unit root versus a SETAR. First, we show that a SETAR with a unit root in the middle regime is stationary and mix…
In-Sample Inference and Forecasting in Misspecified Factor Models
This article considers in-sample prediction and out-of-sample forecasting in regressions with many exogenous predictors. We consider four dimension-reduction devices: principal components, ridge, Landweber Fridman, and partial least squares. We derive rates of convergence for two representative models: an ill-posed model and an approximate factor model. The theory is developed for a large cross-section and a large time-series. As all these method…
Computer Science (3 works) · Mathematics (3 works) · Monetary Policy and Economic Impact (3 works) · Statistics (3 works) · Econometrics (2 works) · Inference (2 works) · Monte Carlo method (2 works) · Statistical Methods and Inference (2 works) · Applied Mathematics (1 work) · Artificial Intelligence (1 work)