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The fiscal and distributive impacts of three reforms to the social security pension system in the UK are evaluated. All three reforms are designed to increase the retirement age by changing the incentive structure underlying the pension system. The first increases the state pension age by three years. The second introduces an actuarial adjustment to retirement both before and after age sixty five allowing deferral to age 70. The final reform adapts the second reform to include a cap and a floor so as to mirror more closely the existing state pension scheme in the UK. Using a transition model of retirement, the simulations show that increasing the state pension age leads to a lower level of expenditure on the state pension, which is only partially offset through increased state spending on both means-tested income support and disability benefit (invalidity benefit). Employee national insurance receipts are also directly increased through the increase in the state pension age. The increase in retirement ages would also lead to an increase in government revenues arising from increased income tax and employee and employer national insurance contributions. As a result there would be lower levels of government borrowing (or larger government surpluses) than under the base system.

This paper reviews some of the most popular policy evaluation methods in empirical microeconomics: social experiments, natural experiments, matching, instrumental variables, discontinuity design, and control functions. It discusses identification of traditionally used average parameters and more complex distributional parameters. The adequacy, assumptions, and data requirements of each approach are discussed drawing on empirical evidence from the education and employment policy evaluation literature. A workhorse simulation model of education returns is used throughout the paper to discuss and illustrate each approach. The full set of STATA datasets and do-files are available free online and can be used to reproduce all estimation and simulation results.

Four alternative but related approaches to empirical evaluation of policy interventions are studied: social experiments, natural experiments, matching methods, and instrumental variables. In each case the necessary assumptions and the data requirements are considered for estimation of a number of key parameters of interest. These key parameters include the average treatment effect, the treatment of the treated and the local average treatment effect. Some issues of implementation and interpretation are discussed drawing on the labour market programme evaluation literature.