Irina Murtazashvili
Biographic Data
| ID | 5737950 |
|---|---|
| NAME | Irina Murtazashvili |
| GIVEN NAMES | Irina |
| FAMILY NAME | Murtazashvili |
| SIGNATURE | MURTAZASHVILI I |
| AFFILIATIONS | Drexel University |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Ds-Heck
We extend the Heckman (1979) sample selection model by allowing for a large number of controls that are selected using lasso under a sparsity scenario. The standard lasso estimation is known to under-select causing an omitted variable bias in addition to the sample selection bias. We outline the required adjustments needed to restore consistency of lasso-based estimation and inference for vector-valued parameters of interest in such models. The a…
Negative Trade Shocks and Gender Inequality
We study the differential post‐layoff responses in labour market outcomes for men versus women when unemployment is caused by international trade. We capitalize on the richness and unique design of two US Trade Adjustment Assistance (TAA) datasets to analyse gender differentials in wages and employment. Three main findings stand out from our analysis. First, the pre‐layoff wage gap between men and women who have lost their jobs due to trade and e…
Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling
We consider the local linear generalized method of moment (GMM) estimation of functional coefficient models with a mix of discrete and continuous data and in the presence of endogenous regressors. We establish the asymptotic normality of the estimator and derive the optimal instrumental variable that minimizes the asymptotic variance-covariance matrix among the class of all local linear GMM estimators. Data-dependent bandwidth sequences are also …
A Control Function Approach To Estimating Dynamic Probit Models With Endogenous Regressors, With An Application To The Study Of Poverty Persistence In China
This paper proposes a parametric approach to estimating a dynamic binary response panel data model that allows for endogenous contemporaneous regressors. This approach is of particular value for settings in which one wants to estimate the effects of an endogenous treatment on a binary outcome. The model is next used to examine the impact of rural-urban migration on the likelihood that households in rural China fall below the poverty line. In this…
No prominent works on this page.
A Control Function Approach To Estimating Dynamic Probit Models With Endogenous Regressors, With An Application To The Study Of Poverty Persistence In China
This paper proposes a parametric approach to estimating a dynamic binary response panel data model that allows for endogenous contemporaneous regressors. This approach is of particular value for settings in which one wants to estimate the effects of an endogenous treatment on a binary outcome. The model is next used to examine the impact of rural-urban migration on the likelihood that households in rural China fall below the poverty line. In this…
Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling
We consider the local linear generalized method of moment (GMM) estimation of functional coefficient models with a mix of discrete and continuous data and in the presence of endogenous regressors. We establish the asymptotic normality of the estimator and derive the optimal instrumental variable that minimizes the asymptotic variance-covariance matrix among the class of all local linear GMM estimators. Data-dependent bandwidth sequences are also …
Negative Trade Shocks and Gender Inequality
We study the differential post‐layoff responses in labour market outcomes for men versus women when unemployment is caused by international trade. We capitalize on the richness and unique design of two US Trade Adjustment Assistance (TAA) datasets to analyse gender differentials in wages and employment. Three main findings stand out from our analysis. First, the pre‐layoff wage gap between men and women who have lost their jobs due to trade and e…
Ds-Heck
We extend the Heckman (1979) sample selection model by allowing for a large number of controls that are selected using lasso under a sparsity scenario. The standard lasso estimation is known to under-select causing an omitted variable bias in addition to the sample selection bias. We outline the required adjustments needed to restore consistency of lasso-based estimation and inference for vector-valued parameters of interest in such models. The a…
Econometrics (3 works) · Economics (3 works) · Mathematics (3 works) · Economic growth (2 works) · Labor market dynamics and wage inequality (2 works) · Monetary Policy and Economic Impact (2 works) · Statistics (2 works) · Artificial Intelligence (1 work) · Biology (1 work) · China (1 work)