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Estimation, inference and testing

While the study of identification is about what can be learned from economic models when applied to data, the study of estimation, inference and testing is concerned with, inter alia: the measurement of identified quantities using real data; summarising the precision of estimates; quantifying how well the data support particular hypotheses of interest; and quantifying the degree of support that the data give to the restrictions imposed by the model being employed. The methods of estimation, inference and testing enable application of models to real-world datasets in an attempt to assess key features of interest in the population from which their data are taken. These are the methods that produce the magnitudes used in policy evaluation, and measures of their accuracy, and that allow an assessment of their robustness to changes in a model's assumptions.

Research findings

Economic models based on weak but credible assumptions in some cases only deliver set identification, or bounds, on quantities of interest. Many such models quite naturally result in intersection bounds, where the model delivers a number of upper and lower bounds.
Date started: 01 June 2012
Indirect inference is a method to estimate parameters of models where the estimation criterion is difficult or impossible to evaluate directly. The method works by estimating parameters of a set of simpler models.
Date started: 01 June 2012
This research uses indirect inference to model earnings dynamics with participation to assess how non-random selection into work affects estimation of earnings dynamics.
Date started: 01 June 2012
Work on this topic aims to develop methods to improve our understanding of models that allow for non-linear relationships, unobserved multidimensional heterogeneity and endogenous variables.
Date started: 01 June 2012
This work seeks to bridge the gap between two conflicting approaches in empirical macroeconomics, with 'atheoretical' econometric models on one side and “theoretical” models such as dynamic stochastic general equilibrium (DSGE) models on the opposite side.
Date started: 01 June 2012
This work offers a review of forecasting methodologies and empirical applications that are useful for macroeconomists.
Date started: 01 June 2012
Unobserved heterogeneity is important in econometrics. People who look alike in terms of education, income, or other variables, make different choices about consumption, and savings. etc. Economic theory provides no guidance as to how unobserved heterogeneity should be modelled nor how important it might be.
Date started: 01 June 2012

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