Dr Sara Maioli is a lecturer in Economics in Newcastle University Business School and an applied economist. During her post-doc at the School of Nottingham, GEP Research Centre, she worked with plant-level business data held at the London office of the ONS, using in particular the Annual Respondents Database (ARD) business survey, where she investigated issues of price-cost margins, productivity, exporting and FDI. While at Nottingham, in 2004, she was also a co-investigator with Dr Sourafel Girma and Dr Holger Goerg for the research project “Longitudinal micro-data study of Business Support Programmes” funded by DTI (amount £44,560). She will bring her experience in propensity score matching to the project when estimating causal effects using observational data from LSBS.
Spatial disparities in SMEs productivity in England. Research Paper No 84
Published: 18 February 2020
Improving productivity is critical to increasing economic growth and prosperity in the long-run and a key objective for UK national, regional and local policy. However, a long tail of low productivity businesses and significant spatial variations in productivity characterise the UK economy. This report presents an analysis of the determinants of Small and Medium Sized Enterprise (SME) labour productivity, with a particular focus on how place and productivity interact. The analysis draws on data from the UK Government’s Longitudinal Small Business Survey (LSBS) for the years 2015 to 2017. It employs a multilevel regression analysis to understand determinants in enterprise labour productivity in different localities and regions and effectively account for the contextual environment.
Productivity and performance
Rural business aspirations, obstacles and support: an analysis of the Longitudinal Small Business Survey 2015 Research Paper No. 58
Published: 22 March 2017
A rural-urban analysis of the UK’s Governments Longitudinal Small Business Survey (LSBS) responses for 2015 has been undertaken to understand spatial variations in performance and uptake of external support services. The analysis is based on 15,500 survey responses from across the UK and uses official rural-urban classifications. Approximately 28 per cent of survey responses to the LSBS are classified as rural. Within the rural context, conclusions relating to growth have previously been hampered by difficulties in separating out whether rural location has a distinctive effect or whether spatial variations in business performance reflects differences in size, sector and age of business. Therefore this analysis used Propensity Score Matching (PSM) to control for these and other profile variables, allowing for an assessment of rural effects on business performance.