Chris Muris
Biographic Data
| ID | 876064 |
|---|---|
| NAME | Chris Muris |
| GIVEN NAMES | Chris |
| FAMILY NAME | Muris |
| SIGNATURE | MURIS C |
| AFFILIATIONS | McMaster University |
| ORCID | 0000-0003-2781-3514 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 54 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Estimating Interaction Effects With Panel Data
This paper analyzes how interaction effects can be consistently estimated under economically plausible assumptions in linear panel models with a fixed ‐dimension. We advocate for a correlated interaction term effects (CITE) estimator and show that it is consistent under conditions that are not sufficient for consistency of the interaction term effect estimator that is most common in applied econometric work. Our paper discusses the empirical cont…
Partial Effects in Time-Varying Linear Transformation Panel Models with Endogeneity
This article develops a new estimator for an average partial effect in nonlinear panel models, where outcomes are time-varying monotonic transformations of latent variables that include fixed effects and endogenous regressors. The partial effect can be time-varying and the counterfactual shift is scale invariant—key advantages over the linear model. We exploit a conditional moment restriction and address the ill-posed nature of recovering the tra…
Combining Instrumental Variable Estimators for a Panel Data Model with Factors
We address the estimation of factor-augmented panel data models using observed measurements to proxy for unobserved factors or loadings and explore the use of internal instruments to address the resulting endogeneity.The main challenge consists in that economic theory rarely provides insights into which measurements to choose as proxies when several are available.To overcome this problem, we propose a new class of estimators that are linear combi…
A Dynamic Ordered Logit Model with Fixed Effects
We study a fixed-T panel data logit model for ordered outcomes that accommodates fixed effects and state dependence. We provide identification results for the autoregressive parameter, regression coefficients, and the threshold parameters in this model. Our results require only four observations on the outcome variable. We provide conditions under which a composite conditional maximum likelihood estimator is consistent and asymptotically normal. …
Efficient GMM Estimation with Incomplete Data
In the standard missing data model, data are either complete or completely missing. However, applied researchers face situations with an arbitrary number of strata of incompleteness. Examples include unbalanced panels and instrumental variables settings where some observations are missing some instruments. I propose a model for settings where observations may be incomplete, with an arbitrary number of strata of incompleteness. I derive a set of m…
Estimation in the Fixed-Effects Ordered Logit Model
This paper introduces a new estimator for the fixed-effects ordered logit model. The proposed method has two advantages over existing estimators. First, it estimates the differences in the cut points along with the regression coefficient, leading to provide bounds on partial effects. Second, the proposed estimator for the regression coefficient is more efficient. I use the fact that the ordered logit model with J outcomes and T observations can b…
The Trade-off Between Income Inequality and Carbon Dioxide Emissions
Based on a substantially larger data set (in both regional and temporal coverage) than the\n\t\t\t\t existing literature, we investigate the theoretically ambiguous link between income inequality\n\t\t\t\t and per capita emissions using cross-country panel data. We find that the relationship depends\n\t\t\t\t on the level of income. Using an arguably superior group-fixed effects estimator, we show that\n\t\t\t\t for low and middle-income economie…
Do climate variations explain bilateral migration? A gravity model analysis
This paper investigates to what extent international migration can be explained by climatic variations. A gravity model of migration augmented with average temperature and precipitation in the country of origin is estimated using a panel data set of 142 sending countries for the period 1995 to 2006. We find two primary results. First, temperature is positively correlated with migration. Second, stronger changes in precipitation are also associate…
The Trade-off Between Income Inequality and Carbon Dioxide Emissions
Based on a substantially larger data set (in both regional and temporal coverage) than the\n\t\t\t\t existing literature, we investigate the theoretically ambiguous link between income inequality\n\t\t\t\t and per capita emissions using cross-country panel data. We find that the relationship depends\n\t\t\t\t on the level of income. Using an arguably superior group-fixed effects estimator, we show that\n\t\t\t\t for low and middle-income economie…
Do climate variations explain bilateral migration? A gravity model analysis
This paper investigates to what extent international migration can be explained by climatic variations. A gravity model of migration augmented with average temperature and precipitation in the country of origin is estimated using a panel data set of 142 sending countries for the period 1995 to 2006. We find two primary results. First, temperature is positively correlated with migration. Second, stronger changes in precipitation are also associate…
Do climate variations explain bilateral migration? A gravity model analysis
This paper investigates to what extent international migration can be explained by climatic variations. A gravity model of migration augmented with average temperature and precipitation in the country of origin is estimated using a panel data set of 142 sending countries for the period 1995 to 2006. We find two primary results. First, temperature is positively correlated with migration. Second, stronger changes in precipitation are also associate…
Estimation in the Fixed-Effects Ordered Logit Model
This paper introduces a new estimator for the fixed-effects ordered logit model. The proposed method has two advantages over existing estimators. First, it estimates the differences in the cut points along with the regression coefficient, leading to provide bounds on partial effects. Second, the proposed estimator for the regression coefficient is more efficient. I use the fact that the ordered logit model with J outcomes and T observations can b…
The Trade-off Between Income Inequality and Carbon Dioxide Emissions
Based on a substantially larger data set (in both regional and temporal coverage) than the\n\t\t\t\t existing literature, we investigate the theoretically ambiguous link between income inequality\n\t\t\t\t and per capita emissions using cross-country panel data. We find that the relationship depends\n\t\t\t\t on the level of income. Using an arguably superior group-fixed effects estimator, we show that\n\t\t\t\t for low and middle-income economie…
Efficient GMM Estimation with Incomplete Data
In the standard missing data model, data are either complete or completely missing. However, applied researchers face situations with an arbitrary number of strata of incompleteness. Examples include unbalanced panels and instrumental variables settings where some observations are missing some instruments. I propose a model for settings where observations may be incomplete, with an arbitrary number of strata of incompleteness. I derive a set of m…
Combining Instrumental Variable Estimators for a Panel Data Model with Factors
We address the estimation of factor-augmented panel data models using observed measurements to proxy for unobserved factors or loadings and explore the use of internal instruments to address the resulting endogeneity.The main challenge consists in that economic theory rarely provides insights into which measurements to choose as proxies when several are available.To overcome this problem, we propose a new class of estimators that are linear combi…
A Dynamic Ordered Logit Model with Fixed Effects
We study a fixed-T panel data logit model for ordered outcomes that accommodates fixed effects and state dependence. We provide identification results for the autoregressive parameter, regression coefficients, and the threshold parameters in this model. Our results require only four observations on the outcome variable. We provide conditions under which a composite conditional maximum likelihood estimator is consistent and asymptotically normal. …
Estimating Interaction Effects With Panel Data
This paper analyzes how interaction effects can be consistently estimated under economically plausible assumptions in linear panel models with a fixed ‐dimension. We advocate for a correlated interaction term effects (CITE) estimator and show that it is consistent under conditions that are not sufficient for consistency of the interaction term effect estimator that is most common in applied econometric work. Our paper discusses the empirical cont…
Partial Effects in Time-Varying Linear Transformation Panel Models with Endogeneity
This article develops a new estimator for an average partial effect in nonlinear panel models, where outcomes are time-varying monotonic transformations of latent variables that include fixed effects and endogenous regressors. The partial effect can be time-varying and the counterfactual shift is scale invariant—key advantages over the linear model. We exploit a conditional moment restriction and address the ill-posed nature of recovering the tra…
Econometrics (6 works) · Panel data (6 works) · Mathematics (5 works) · Economics (4 works) · Estimator (4 works) · Statistics (4 works) · Spatial and Panel Data Analysis (3 works) · Computer Science (2 works) · Demographic economics (2 works) · Fixed effects model (2 works)