Capital Allowances

Tender description

This is a KAI Social Research contract intended to be let through Research Marketplace. A copy of the full business case can be provided if required. Capital Allowances (CA) are high-cost reliefs, forgoing around £18bn a year. The Chancellor (CX) requires insight on how well the policy meets HMT and HMRC priorities and objectives ahead of Autumn Budget 2022. There are a number of evidence gaps around CAs which commissioned research is necessary to fill. Specifically there are gaps on disposals, eligible non-claimants, current claimants not claiming their maximum eligible amounts (under-claimants), behavioural responses, regional splits, specific assest class information, CA that isn't eligible for the super-deduction, and the coverage of CAs. The information required on these topics is not available in existing research or data and so necessary qualitative and quantitative research is required. There will be a review of the available internal data to ensure that no work is being duplicated. This research will have a direct impact on the evidence used to inform CX's decisions on Capital Allowances ahead of Autumn Budget 2022 by answering specific and critical questions that we are currently unable to answer with existing research or data. The research will enable us to gain a better understanding of how CAs are used and how they influence decision making. Without this quantitative and qualitative research, there will be a wide range of areas across CAs which policy makers will be unable to make informed decisions on. Key decisions in relation to disposals, non-claimants and regional investment cannot be made without the information from this research: - Wrong advice being provided to HMT/CX in respect of potential CA policy changes; - Policies being significantly more costly than anticipated; - Dampening business investment, which has been a historical weakness for the UK and goes directly against what CAs aim to achieve. Therefore, this research is vital to the upcoming changes to CAs