Ingrid Van Keilegom
Biographic Data
| ID | 8920504 |
|---|---|
| NAME | Ingrid Van Keilegom |
| GIVEN NAMES | Ingrid |
| FAMILY NAME | Van Keilegom |
| SIGNATURE | VAN KEILEGOM I |
| AFFILIATIONS | UCLouvain |
| ORCID | 0000-0001-8827-7642 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Instrumental Variable Estimation of Dynamic Treatment Effects on a Duration Outcome
This article considers identification and estimation of the causal effect of the time Z until a subject is treated on a duration T. The time-to-treatment is not randomly assigned, T is randomly right censored by a random variable C, and the time-to-treatment Z is right censored by T∧C. The endogeneity issue is treated using an instrumental variable explaining Z and independent of the error term of the model. We study identification in a fully non…
Nonparametric Instrumental Regression With Right Censored Duration Outcomes
This article analyzes the effect of a discrete treatment Z on a duration T. The treatment is not randomly assigned. The confounding issue is treated using a discrete instrumental variable explaining the treatment and independent of the error term of the model. Our framework is nonparametric and allows for random right censoring. This specification generates a nonlinear inverse problem and the average treatment effect is derived from its solution.…
A Smooth Nonparametric, Multivariate, Mixed-Data Location-Scale Test
A number of tests have been proposed for assessing the location-scale assumption that is often invoked by practitioners. Existing approaches include Kolmogorov–Smirnov and Cramer–von Mises statistics that each involve measures of divergence between unknown joint distribution functions and products of marginal distributions. In practice, the unknown distribution functions embedded in these statistics are typically approximated using nonsmooth empi…
Estimation of Conditional Ranks and Tests of Exogeneity in Nonparametric Nonseparable Models
Consider a nonparametric nonseparable regression model Y = φ(Z, U), where φ(Z, U) is strictly increasing in U and U ∼ U[0, 1]. We suppose that there exists an instrument W that is independent of U. The observable random variables are Y, Z, and W, all one-dimensional. We construct test statistics for the hypothesis that Z is exogenous, that is, that U is independent of Z. The test statistics are based on the observation that Z is exogenous if and …
Semiparametric Estimation of Risk–Return Relationships
This article proposes semiparametric generalized least-squares estimation of parametric restrictions between the conditional mean and the conditional variance of excess returns given a set of parametric factors. A distinctive feature of our estimator is that it does not require a fully parametric model for the conditional mean and variance. We establish consistency and asymptotic normality of the estimates. The theory is nonstandard due to the pr…
Semiparametric Conditional Quantile Estimation Through Copula-Based Multivariate Models
We consider a new approach in quantile regression modeling based on the copula function that defines the dependence structure between the variables of interest. The key idea of this approach is to rewrite the characterization of a regression quantile in terms of a copula and marginal distributions. After the copula and the marginal distributions are estimated, the new estimator is obtained as the weighted quantile of the response variable in the …
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Semiparametric Conditional Quantile Estimation Through Copula-Based Multivariate Models
We consider a new approach in quantile regression modeling based on the copula function that defines the dependence structure between the variables of interest. The key idea of this approach is to rewrite the characterization of a regression quantile in terms of a copula and marginal distributions. After the copula and the marginal distributions are estimated, the new estimator is obtained as the weighted quantile of the response variable in the …
Semiparametric Estimation of Risk–Return Relationships
This article proposes semiparametric generalized least-squares estimation of parametric restrictions between the conditional mean and the conditional variance of excess returns given a set of parametric factors. A distinctive feature of our estimator is that it does not require a fully parametric model for the conditional mean and variance. We establish consistency and asymptotic normality of the estimates. The theory is nonstandard due to the pr…
Estimation of Conditional Ranks and Tests of Exogeneity in Nonparametric Nonseparable Models
Consider a nonparametric nonseparable regression model Y = φ(Z, U), where φ(Z, U) is strictly increasing in U and U ∼ U[0, 1]. We suppose that there exists an instrument W that is independent of U. The observable random variables are Y, Z, and W, all one-dimensional. We construct test statistics for the hypothesis that Z is exogenous, that is, that U is independent of Z. The test statistics are based on the observation that Z is exogenous if and …
A Smooth Nonparametric, Multivariate, Mixed-Data Location-Scale Test
A number of tests have been proposed for assessing the location-scale assumption that is often invoked by practitioners. Existing approaches include Kolmogorov–Smirnov and Cramer–von Mises statistics that each involve measures of divergence between unknown joint distribution functions and products of marginal distributions. In practice, the unknown distribution functions embedded in these statistics are typically approximated using nonsmooth empi…
Nonparametric Instrumental Regression With Right Censored Duration Outcomes
This article analyzes the effect of a discrete treatment Z on a duration T. The treatment is not randomly assigned. The confounding issue is treated using a discrete instrumental variable explaining the treatment and independent of the error term of the model. Our framework is nonparametric and allows for random right censoring. This specification generates a nonlinear inverse problem and the average treatment effect is derived from its solution.…
Instrumental Variable Estimation of Dynamic Treatment Effects on a Duration Outcome
This article considers identification and estimation of the causal effect of the time Z until a subject is treated on a duration T. The time-to-treatment is not randomly assigned, T is randomly right censored by a random variable C, and the time-to-treatment Z is right censored by T∧C. The endogeneity issue is treated using an instrumental variable explaining Z and independent of the error term of the model. We study identification in a fully non…
Mathematics (6 works) · Statistics (6 works) · Econometrics (5 works) · Estimator (5 works) · Nonparametric statistics (5 works) · Statistical Methods and Inference (5 works) · Advanced Causal Inference Techniques (2 works) · Asymptotic distribution (2 works) · Computer Science (2 works) · Conditional expectation (2 works)