Arbeitspapier
Minimizing sensitivity to model misspecification
We propose a framework for estimation and inference about the parameters of an economic model and predictions based on it, when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We derive formulas to construct estimators whose mean squared error is minimax in a neighborhood of the reference model, based on simple one-step adjustments. We construct confidence intervals that contain the true parameter under both correct specification and local misspecification. We calibrate the degree of misspecification using a model detection error approach. Our approach allows us to perform systematic sensitivity analysis when the parameter of interest may be partially or irregularly identified. To illustrate our approach we study panel data models where the distribution of individual effects may be misspecified and the number of time periods is small, and we revisit the structural evaluation of a conditional cash transfer program in Mexico.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP59/18
- Klassifikation
-
Wirtschaft
Estimation: General
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
- Thema
-
Model misspecification
robustness
sensitivity analysis
structural models
counterfactuals
latent variables
panel data
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Bonhomme, Stéphane
Weidner, Martin
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2018
- DOI
-
doi:10.1920/wp.cem.2018.5918
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Bonhomme, Stéphane
- Weidner, Martin
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2018
Ähnliche Objekte (12)
Minimizing sensitivity to model misspecification
The sensitivity of DSGE models' results to data detrending
Sensitivity to Energy Technology Costs: A Multi-model Comparison Analysis
Sensitivity analysis for dynamic microsimulation models
Sensitivity to Calibrated Parameters
Sensitivity to Calibrated Parameters
Sensitivity to calibrated parameters
The Sensitivity of Quarterly Models of Wage Determination to Aggregation Assumptions
Minimizing total weighted completion times subject to precedence constraints by dynamic programming
Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis
Minimizing learning behavior in repeated real-effort tasks
Comparing empirical and model-based approaches for calculating dynamic grid emission factors: An application to CO2-minimizing storage dispatch in Germany
Minimizing sensitivity to model misspecification
The sensitivity of DSGE models' results to data detrending
Sensitivity to Energy Technology Costs: A Multi-model Comparison Analysis
Sensitivity analysis for dynamic microsimulation models
Sensitivity to Calibrated Parameters
Sensitivity to Calibrated Parameters
Sensitivity to calibrated parameters
The Sensitivity of Quarterly Models of Wage Determination to Aggregation Assumptions
Minimizing total weighted completion times subject to precedence constraints by dynamic programming
Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis
Minimizing learning behavior in repeated real-effort tasks
Comparing empirical and model-based approaches for calculating dynamic grid emission factors: An application to CO2-minimizing storage dispatch in Germany
Minimizing sensitivity to model misspecification
The sensitivity of DSGE models' results to data detrending
Sensitivity to Energy Technology Costs: A Multi-model Comparison Analysis
Sensitivity analysis for dynamic microsimulation models
Sensitivity to Calibrated Parameters
Sensitivity to Calibrated Parameters
Sensitivity to calibrated parameters
The Sensitivity of Quarterly Models of Wage Determination to Aggregation Assumptions
Minimizing total weighted completion times subject to precedence constraints by dynamic programming
Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis
Minimizing learning behavior in repeated real-effort tasks