Search Results - subject:"optimal instruments"

More efficient estimation of multiplicative panel data models in the presence of serial correlation

Brown, Nicholas; Wooldridge, Jeffrey M. - 2023

, overdispersion, and general patterns of serial correlation. Because parameters in the optimal instruments must be estimated, we argue …

Persistent link: https://www.econbiz.de/10014451084

More efficient estimation of multiplicative panel data models in the presence of serial correlation

Brown, Nicholas; Wooldridge, Jeffrey M. - 2023

, overdispersion, and general patterns of serial correlation. Because parameters in the optimal instruments must be estimated, we argue …

Persistent link: https://www.econbiz.de/10013556880

Food for Thought? Breastfeeding and Child Development

Fitzsimons, Emla; Vera-Hernández, Marcos - Department of Quantitative Social Science, Institute of … - 2014

We show that children who are born at the weekend or just before are less likely to be breastfed, owing to poorer breastfeeding support services at weekends. We use this variation to estimate the effect of breastfeeding on childrenâ€™s development for a sample of uncomplicated births from...

Persistent link: https://www.econbiz.de/10011132451

High-dimensional instrumental variables regression and confidence sets

Gautier, Eric; Tsybakov, Alexandre - HAL - 2014

We propose an instrumental variables method for inference in high-dimensional structural equations with endogenous regressors. The number of regressors K can be much larger than the sample size. A key ingredient is sparsity, i.e., the vector of coefficients has many zeros, or approximate...

Persistent link: https://www.econbiz.de/10009021745

Food for thought? Breastfeeding and child development

Fitzsimons, Emla; Vera-Hernandez, Marcos - 2013

We show that children who are born at the weekend or just before are less likely to be breastfed, owing to poorer breastfeeding support services at weekends. We use this variation to estimate the effect of breastfeeding on children's development for a sample of uncomplicated births from low...

Persistent link: https://www.econbiz.de/10010331031

The Optimal Construction of Instruments in Nonlinear Regression: Implications for GMM Inference

Stewart, Kenneth G. - Department of Economics, University of Victoria - 2011

Interpreted as an instrumental variables estimator, nonlinear least squares constructs its instruments optimally from the explanatory variables using the nonlinear specification of the regression function. This has implications for the use of GMM estimators in nonlinear regression models,...

Persistent link: https://www.econbiz.de/10009004105

Sparse models and methods for optimal instruments with an application to eminent domain

Belloni, Alexandre; Chen, Daniel L.; Chernozhukov, Victor; … - 2011

Persistent link: https://www.econbiz.de/10009271127

Sparse models and methods for optimal instruments with an application to eminent domain

Belloni, A.; Chen, D.; Chernozhukov, V.; Hansen, C. - 2010

economic effects of these decisions. Optimal instruments are conditional expectations; and in developing the IV results, we …We develop results for the use of LASSO and Post-LASSO methods to form first-stage predictions and estimate optimal … instruments in linear instrumental variables (IV) models with many instruments, p, that apply even when p is much larger than the …

Persistent link: https://www.econbiz.de/10010288391

Sparse models and methods for optimal instruments with an application to eminent domain

Belloni, A.; Chen, D.; Chernozhukov, Victor; Hansen, … - 2010

Persistent link: https://www.econbiz.de/10008695561

Evaluating the German (New Keynesian) Phillips Curve

Scheufele, Rolf - 2008

This paper evaluates the New Keynesian Phillips Curve (NKPC) and its hybrid variant within a limited information framework for Germany. The main interest rests on the average frequency of price re-optimization of firms. We use the labor income share as the driving variable and consider a source...

Persistent link: https://www.econbiz.de/10010269912