 Facts and figures about UK taxes, benefits and public spending.
Income distribution, poverty and inequality.
Analysing government fiscal forecasts and tax and spending.
Analysis of the fiscal choices an independent Scotland would face.
Case studies that give a flavour of the areas where IFS research has an impact on society.
Reforming the tax system for the 21st century.
A peer-reviewed quarterly journal publishing articles by academics and practitioners.
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 Identification
Research on identification underpins all social science research and lies at the basis of all of CeMMAP’s endeavours. Analysis of identification provides guidance on what is knowable given current data resources and on what types of new measurements and experiments can expand the frontier of knowledge. It informs researchers about the relative power of restrictions on models implied by social science theory and restrictions imposed for statistical convenience. It informs researchers about their ability to distinguish between different theoretical models and the ability to falsify models.
 It is not uncommon for economic feedback models to produce more than one solution. In some cases, multiplicity can cause identification problems. In others, it can produce more variation in the data. In this work, we show formally that the latter is the case in many models of entry-exit of firms and in many peer effect models.
We study an instrumental variables model for discrete choice amongst unordered alternatives.
Simultaneous equations models of economic processes may deliver multiple, single or no solution. This is an important econometric issue in nonlinear models and has received particular attention in econometric models involving discrete outcomes.
Existing instrumental variable methods require latent variables to be unidimensional. In this research, we relax this restriction and develop a characterisation of the resulting sharp identified set.
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.
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