Jesús Gonzalo
Biographic Data
| ID | 5737291 |
|---|---|
| NAME | Jesús Gonzalo |
| GIVEN NAMES | Jesús |
| FAMILY NAME | Gonzalo |
| SIGNATURE | GONZALO J |
| AFFILIATIONS | Universidad Carlos III de Madrid |
| ORCID | 0000-0002-4309-5025 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1995 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Detecting Sparse Cointegration
We propose a two‐step procedure for detecting sparse cointegration in high‐dimensional single‐equation models. First, we employ the adaptive lasso to identify the subset of integrated covariates driving the long‐run equilibrium relationship. Second, we adopt an information‐theoretic criterion to distinguish between stationarity and nonstationarity in the resulting residuals, avoiding reliance on asymptotic distributions. A key theoretical contrib…
Dynamic Effects of Persistent Shocks
We provide evidence that many narrative shocks used by prominent literature display some persistence. We show that the two leading methods to estimate impulse responses to an independently identified shock (local projections and distributed lag models) treat persistence differently, hence identifying different objects. We propose corrections to re‐establish the equivalence between local projections and distributed lag models, providing applied re…
Heterogeneous predictive association of CO 2 with global warming
Global warming is a non‐uniform process across space and time. This opens the door to a heterogeneous relationship between and temperature that needs to be explored going beyond the standard analysis based on mean temperature. We revisit this topic through the lens of a new class of factor models for high‐dimensional panel data, called quantile factor models. This technique extracts quantile‐dependent factors from the distributions of temperature…
Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions
We introduce a set of test statistics for assessing the presence of regimes in out of sample forecast errors produced by recursively estimated linear predictive regressions that can accommodate multiple highly persistent predictors. Our test statistics are designed to be robust to the chosen starting window size and are shown to be both consistent and locally powerful. Their limiting null distributions are also free of nuisance parameters and hen…
Inferring the Predictability Induced by a Persistent Regressor in a Predictive Threshold Model
We develop tests for detecting possibly episodic predictability induced by a persistent predictor. Our framework is that of a predictive regression model with threshold effects and our goal is to develop operational and easily implementable inferences when one does not wish to impose à priori restrictions on the parameters of the model other than the slopes corresponding to the persistent predictor. Differently put our tests for the null hypothes…
Regime-Specific Predictability in Predictive Regressions
Predictive regressions are linear specifications linking a noisy variable such as stock returns to past values of a very persistent regressor with the aim of assessing the presence of predictability. Key complications that arise are the potential presence of endogeneity and the poor adequacy of asymptotic approximations. In this article, we develop tests for uncovering the presence of predictability in such models when the strength or direction o…
Estimation of Common Long-Memory Components in Cointegrated Systems
The study of cointegration in large systems requires a reduction of their dimensionality. To achieve this, we propose to obtain the I(1) common factors in every subsystem and then analyze cointegration among them. In this article, a new way of estimating common long-memory components of a cointegrated system is proposed. The identification of these I(1) common factors is achieved by imposing that they be linear combinations of the original variab…
No prominent works on this page.
Estimation of Common Long-Memory Components in Cointegrated Systems
The study of cointegration in large systems requires a reduction of their dimensionality. To achieve this, we propose to obtain the I(1) common factors in every subsystem and then analyze cointegration among them. In this article, a new way of estimating common long-memory components of a cointegrated system is proposed. The identification of these I(1) common factors is achieved by imposing that they be linear combinations of the original variab…
Regime-Specific Predictability in Predictive Regressions
Predictive regressions are linear specifications linking a noisy variable such as stock returns to past values of a very persistent regressor with the aim of assessing the presence of predictability. Key complications that arise are the potential presence of endogeneity and the poor adequacy of asymptotic approximations. In this article, we develop tests for uncovering the presence of predictability in such models when the strength or direction o…
Inferring the Predictability Induced by a Persistent Regressor in a Predictive Threshold Model
We develop tests for detecting possibly episodic predictability induced by a persistent predictor. Our framework is that of a predictive regression model with threshold effects and our goal is to develop operational and easily implementable inferences when one does not wish to impose à priori restrictions on the parameters of the model other than the slopes corresponding to the persistent predictor. Differently put our tests for the null hypothes…
Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions
We introduce a set of test statistics for assessing the presence of regimes in out of sample forecast errors produced by recursively estimated linear predictive regressions that can accommodate multiple highly persistent predictors. Our test statistics are designed to be robust to the chosen starting window size and are shown to be both consistent and locally powerful. Their limiting null distributions are also free of nuisance parameters and hen…
Heterogeneous predictive association of CO 2 with global warming
Global warming is a non‐uniform process across space and time. This opens the door to a heterogeneous relationship between and temperature that needs to be explored going beyond the standard analysis based on mean temperature. We revisit this topic through the lens of a new class of factor models for high‐dimensional panel data, called quantile factor models. This technique extracts quantile‐dependent factors from the distributions of temperature…
Dynamic Effects of Persistent Shocks
We provide evidence that many narrative shocks used by prominent literature display some persistence. We show that the two leading methods to estimate impulse responses to an independently identified shock (local projections and distributed lag models) treat persistence differently, hence identifying different objects. We propose corrections to re‐establish the equivalence between local projections and distributed lag models, providing applied re…
Detecting Sparse Cointegration
We propose a two‐step procedure for detecting sparse cointegration in high‐dimensional single‐equation models. First, we employ the adaptive lasso to identify the subset of integrated covariates driving the long‐run equilibrium relationship. Second, we adopt an information‐theoretic criterion to distinguish between stationarity and nonstationarity in the resulting residuals, avoiding reliance on asymptotic distributions. A key theoretical contrib…
Econometrics (7 works) · Mathematics (7 works) · Economics (5 works) · Monetary Policy and Economic Impact (5 works) · Statistics (5 works) · Complex Systems and Time Series Analysis (3 works) · Computer Science (3 works) · Predictability (3 works) · Cointegration (2 works) · Financial Markets and Investment Strategies (2 works)