SMEs make a major contribution to economic growth and employment, accounting for more than 99% of all enterprises in Europe. The London Economics SME team has extensive experience of providing evidence-based advice to private and public clients on SME issues, policies and programs, including their effectiveness and efficiency.
We help clients in addressing their issues by providing focused and academically robust analysis, studies and policy recommendations using a multi-disciplinary approach and proposing innovative and bespoke methodologies. We work with both micro and macro data, use various state-of-the-art econometric and non-parametric techniques, undertake surveys and run stakeholder consultations and workshops. Our work is frequently peer-reviewed by academics.
We work for:
- Policymakers in the UK and Europe
- SME associations
- Private clients of all sizes
How we do it
We make use of a wide range of quantitative and qualitative methodologies and approaches to answer a variety of research questions, including:
Sophisticated econometric analysis
Covering a range of methodologies such as Ordinary Least Squares (OLS), Instrumental Variables (IV), ARIMA, VAR, structural VAR, Propensity Score Matching (PSM), Generalised Linear Models (GLM), Regression Discontinuity Design (RDD), panel data techniques (such as fixed effects, random effects and GMM), Bayesian estimation and Bayesian Model Averaging (BMA), General-to specific, Lasso and Ridge techniques.
Parametric and Non-parametric modelling
Development and simulation of models with estimated or calibrated parameters and Monte-Carlo simulations to assess sensitivity of model predictions to uncertainty around parameter values.
Cost effectiveness and cost-benefit analysis
Comparing the economic benefits to the direct and opportunity costs associated with policy alternatives to understand both their cost effectiveness and the relative size of costs and benefits.
Ex-ante and ex-post policy and program evaluation
Isolating the effect of a given policy, programme or project via Randomised Controlled Trials (RCTs) or Quasi-Experimental Designs (QED) such as Difference-in-Differences (DiD) analysis and Propensity Score Matching (PSM).
Survey design, quantitative and qualitative primary data collection, and analysis of survey results
Comprising all elements of quantitative survey design, including questionnaire structure and content, sampling strategy and representative response weighting, as well as qualitative consultations and open-text surveying.
Secondary data cleaning, processing, and imputation
Extensive experience in preparing large-scale administrative datasets for analysis, including the use of fuzzy matching techniques and the imputation of missing data.
Recent examples of our work:
SME Annual Report as part of the Annual SME Performance Review
Since 2014, London Economics prepared for EC DG GROW the annual SME report which provides a synopsis of the size, structure and importance of SMEs to the European economy and an overview of the past and forecasted performance of SMEs. In addition, each year the annual report addresses a special topic such as:
- Research & Development and Innovation by SMEs (2019)
- the participation of SMEs in the global economy through international trade and FDI (2018)
- self-employment, entrepreneurship and business creation (2017)
- the impact of the characteristics of a country’s bankruptcy regime on entrepreneurship and enterprise creation (2016)
- the contribution of SMEs to job creation in the recovery from the 2008/09 recession (2015).
SME R&D Tax Credits Evaluation
London Economics independently evaluated HMRC’s SME R&D Tax Credit, which incentivises innovative SMEs to undertake R&D by providing tax relief on R&D expenditure. The value of the tax relief is over £1bn annually. We estimated the impact of the tax relief on SMEs’ R&D investment behaviour (the direct effect), their productivity and the productivity of firms operating in the same sector, as well as any impacts on market competition (the indirect effects). We matched HMRC tax relief data with company financial statements and used a difference-in-differences approach to derive our evaluation results. The study also involved carrying out a survey of firms and firm-level interviews to understand the proportionality of the tax relief relative to the R&D expenditure incentivised, and appropriateness of the form of the tax relief relative to other financial instruments, such as grants or subsidies.
Evaluation of DATA PITCH
DATA Pitch is an EU-funded open innovation programme bringing together corporate and public-sector organisations that have data with start-ups and SMEs that work with data. The key objective of Data Pitch is to unlock the potential of data to solve critical challenges for industry, public institutions, individuals, and society as a whole by matching data holders with innovative start-ups and SMEs. To meet the objectives of the evaluation, the Open Data Institute engaged LE to undertake monitoring and evaluation of the impact of the support programmes on business performance over time. London Economics’ study explored and evaluated the impact of Data Pitch on participants using a mix of quantitative and qualitative data obtained from programme documentation, published sources, and primary data collection.
Development of a non-parametric model to assess and simulate the impact of public funding of SME R&D activities
As part of the evaluation for EC EASME of the European SME Innovation Associate – pilot program undertaken by a consortium, London Economics developed a calibrated, multi-stage model of successful innovation by SMEs with the model parameters being populated using the empirical findings reported by various academic studies. The model was used to undertake extensive scenario analysis and the sensitivity of these results to the specific parameter value choices was tested through Monte Carlo analysis.
Our core research team is comprised of:
Senior Managing Partner
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