Downloads

CW0320-The-Informativeness-of-Estimation-Moments.pdf
PDF | 512.16 KB
This paper introduces measures for how each moment contributes to the precision of parameter estimates in GMM settings. For example, one of the measures asks what would happen to the variance of the parameter estimates if a particular moment was dropped from the estimation. The measures are all easy to compute. We illustrate the usefulness of the measures through two simple examples as well as an application to a model of joint retirement planning of couples. We estimate the model using the UK-BHPS, and we find evidence of complementarities in leisure. Our sensitivity measures illustrate that the estimate of the complementarity is primarily informed by the distribution of differences in planned retirement dates. The estimated econometric model can be interpreted as a bivariate ordered choice model that allows for simultaneity. This makes the model potentially useful in other applications.
Authors

Research Fellow University College London
Áureo is an applied econometrician with strong interests in both methodological and empirical questions, affiliated with UCL, Cemmap, IFS and CEPR.

Bo E. Honoré
Working Paper details
- DOI
- 10.1920/wp.cem.2020320
- Publisher
- The IFS
Suggested citation
More from IFS
Understand this issue

Gender norms, violence and adolescent girls’ trajectories: Evidence from India
24 October 2022

Do tariffs work?
We discuss the economic consequences of tariffs, why governments use them, and whether they actually achieve their intended goals.
23 January 2025

What is this government’s ‘theory of growth’? Nobody knows
"Shifting the performance of an entire economy requires a long-term, consistent and persistent direction." Paul Johnson writes for the Times.
20 January 2025
Policy analysis

IFS Deputy Director Carl Emmerson appointed to the UK Statistics Authority Methodological Assurance Review Panel
14 April 2023

ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models
We develop novel methods for estimation and filtering of continuous-time models with stochastic volatility and jumps using so-called Approximate Bayesian Compu- tation which build likelihoods based on limited information.
12 August 2014

Living standards, poverty and inequality in the UK: 2024
25 July 2024
Academic research

Prediction sets and conformal inference with censored outcomes
This paper provides estimation methods of such prediction sets given observed conditioning covariates when 𝑌 is censored or measured in intervals.
21 January 2025

Robust estimation and inference in panels with interactive fixed effects
We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with a factor structure).
13 December 2024

Individual welfare analysis: Random quasilinear utility, independence and confidence bounds
We introduce a novel framework for individual-level welfare analysis.
13 December 2024