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Using Matching, Instrumental Variables and Control Functions to Estimate Economic Choice Models
Heckman, James J.; Navarro-Lozano, Salvador - Institute for the Study of Labor (IZA) - 2003
This paper investigates four topics. (1) It examines the different roles played by the propensity score (probability of selection) in matching, instrumental variable and control functions methods. (2) It contrasts the roles of exclusion restrictions in matching and selection models. (3) It...
Persistent link: https://www.econbiz.de/10005703186
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Testing the quantity-quality model of fertility : Estimation using unrestricted family size models
Mogstad, Magne; Wiswall, Matthew - In: Quantitative economics : QE ; journal of the … 7 (2016) 1, pp. 157-192
We examine the relationship between child quantity and quality. Motivated by the theoretical ambiguity regarding the sign of the marginal effects of additional siblings on children’s outcomes, our empirical model allows for an unrestricted relationship between family size and child outcomes....
Persistent link: https://www.econbiz.de/10011798965
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Identification of casual effects in linear models: beyond Instrumental Variables
Stanghellini, Elena; Pakpahan, Eduwin - Dipartimento di Economia, Università degli Studi di Perugia - 2013
The Instrumental Variable (IV) formula has become widely used to address the issue of identification of a causal effect … formulations to achieve identification when the assumptions underlying the use of IV are violated. Parallel to the IV, the proposed …
Persistent link: https://www.econbiz.de/10010732259
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Heterogeneous Treatment Effects: Instrumental Variables without Monotonicity?
Klein, Tobias J. - Institute for the Study of Labor (IZA) - 2007
A fundamental identification problem in program evaluation arises when idiosyncratic gains from participation and the …, identification hinges on the same monotonicity assumption that is fundamentally untestable. We investigate the sensitivity of …
Persistent link: https://www.econbiz.de/10005822349
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Heterogeneous Treatment Effects : Instrumental Variables Without Monotonicity?
Klein, Tobias J. - Tilburg University, Center for Economic Research - 2008
A fundamental identification problem in program evaluation arises when idiosyncratic gains from participation and the …, identification hinges on the same monotonicity assumption that is fundamentally untestable. We investigate the sensitivity of …
Persistent link: https://www.econbiz.de/10011091226
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Missing data, imputation, and endogeneity
McDonough, Ian K.; Millimet, Daniel L. - 2016
Basmann (Basmann, R.L., 1957, A generalized classical method of linear estimation of coefficients in a structural equation. Econometrica 25, 77-83; Basmann, R.L., 1959, The computation of generalized classical estimates of coefficients in a structural equation. Econometrica 27, 72-81) introduced...
Persistent link: https://www.econbiz.de/10011594466
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Identification and estimation issues in structural vector autoregressions with external instruments
Angelini, Giovanni; Fanelli, Luca - 2018
In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external … "relevance" and "exogeneity" conditions. We discuss identification results and likelihood-based estimation methods both in the …
Persistent link: https://www.econbiz.de/10011858614
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Invalid proxies and volatility changes
Angelini, Giovanni; Fanelli, Luca; Neri, Luca - 2024
(ii) the potential failure of instrument exogeneity. We introduce a novel identification strategy that appropriately …
Persistent link: https://www.econbiz.de/10014495778
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An Extended Class of Instrumental Variables for the Estimation of Causal Effects
Chalak, Karim; White, Halbert - Department of Economics, Boston College - 2007
identification. We show that by carefully specifying the structural equations and by extending the standard notion of instrumental … governing the unobservables, as these play a crucial role in creating obstacles or opportunities for identification. Because our … results exhaust the possibilities for identification, we ensure that there are no other opportunities for identification based …
Persistent link: https://www.econbiz.de/10005027845
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Evaluating eigenvector spatial filter corrections for omitted georeferenced variables
Griffith, Daniel A.; Chun, Yongwan - In: Econometrics 4 (2016) 2, pp. 1-12
The Ramsey regression equation specification error test (RESET) furnishes a diagnostic for omitted variables in a linear regression model specification (i.e., the null hypothesis is no omitted variables). Integer powers of fitted values from a regression analysis are introduced as additional...
Persistent link: https://www.econbiz.de/10011755334