National Minimum Wage and National Living Wage impact assessment: counterfactual research

Aims and objectives of counterfactual wage research

Over the summer, the National Institute of Economic and Social Research (NIESR) conducted an independent review of the methodology used by the Department for Business, Energy and Industrial Strategy (BEIS) for estimating the cost to business of upratings to the National Minimum Wage (NMW) and National Living Wage (NLW) rates, focusing on the counterfactual underpinning the costs estimate.

We then provide recommendations for how best to the estimate counterfactual and apply this in the BEIS Impact Assessment (IA) model. The counterfactual is what would have occurred in the absence of the intervention and so comparing the profile of the counterfactual wage with the increase in the minimum wage allows one to estimate the impact of the intervention. The profile of the counterfactual is both a function of the wage level low paid workers would receive in the absence of the policy and the wage growth they would have experienced over the course of the minimum wage uprating. The project sought to uncover both an estimate of the counterfactual based on a parametric regression model and to deliver empirical estimates of the growth of the counterfactual.

This research project comprised five stages:
• A review of the literature relevant to estimating counterfactual wages;
• Interviews with low-wage employers, employer representatives and trade unions on the role of the minimum wage in wage-setting;
• A review of the existing BEIS methodology to estimate counterfactual wages and estimate the increased costs to business of the NMW/NLW uprating; and further consultations with academics and regulatory policy experts on how to improve upon these methods;
• A quantitative analysis aimed at developing new methods for estimating counterfactual wage growth;
• Updating the BEIS model by taking the results of our recommended approach for estimating the counterfactual wage and revising the BEIS impact assessment model accordingly.

Findings and update of current practice

The first three stages – the literature review; interviews with low-wage employers, trade body representatives and trade unions; and the review of the existing method – were used to inform an alternative empirical strategy for estimating counterfactual wages, which had originally aimed to deliver both an estimate of the counterfactual wage distribution and the empirical growth rates of wages in low pay jobs. However, the empirical implementation of the models suggested that existing data sources were only sufficiently informative to devise an empirical growth rate of wages in low pay employment, but not to obtain a credible estimate of all aspects of the counterfactual wage distribution, which the Regulatory Policy Committee (RPC) have previously referred to as the ‘shadow wage curve’ (see below for more detail).

The empirical infeasibility of uncovering the counterfactual wage back to the 2000s, even with an exhaustive specification, is an important finding. Nonetheless, the empirical investigation of the counterfactual added value to the current practice used by BEIS, by offering a model-based approach of identifying the average wage growth in low pay employment in the absence of NMW/NLW uprating. We use the evidence obtained from the model to rerun the BEIS impact assessment model, and derive updated cost estimates for last year’s impact assessment for the April 2017 minimum wage upratings, which we contextualise with existing estimates.