Small and medium-sized enterprises (SMEs) are vital employers and key to creating jobs. SMEs account for 90 percent of businesses and more than 50 percent of employment worldwide. In emerging economies, their contribution to GDP can reach 40 percent. Yet, the growth of SMEs in developing countries is restricted by insufficient access to finance. This financing gap was estimated to be $4.5 trillion across developing countries as of 2017.
The COVID-19 pandemic has led to widespread job loss in developing countries. The World Bank Pulse Surveys show that a significant share of SMEs, a major source of employment, were severely affected and contracted their workforce during the pandemic. Availability of financing to SMEs during this trying period was limited: a survey by IFC of its financial institution (FI) clients found a vast majority of FIs lowered loan disbursement to SMEs.
As attention has turned to the recovery process—specifically job recovery – the contribution of SMEs and the enabling role of financing is again taking center stage.In this context, the need to better understand the link between SME financing and job creation is paramount. Despite the importance of the topic, there is a scarcity of literature, particularly where results can be interpreted to apply broadly to emerging economies.
A framework to understanding the nexus between SME finance and job creation is available now in the report Small Business, Big Growth: How investing in SMEs creates jobs. In this report, we provide insights on the empirical relationship between SME financing and job creation. We propose an econometric model to assess the effects of SME financing on job creation, and estimate correlations using a large harmonized firm level dataset comprised of World Bank’s Enterprise Surveys and primary data collected by IFC. Rather than relying on macro-level models commonly used for infrastructure finance and in the non-financial sector, we provide a micro-founded model for SME finance that takes firm-level data into account. Qualitative case studies are also presented as a complement to the econometric framework.
The mostThis multiplier reflects an average across emerging economies and focusses on jobs created directly by the SMEs receiving financing. Further indirect and induced effects are likely, but not quantified as part of this study. Similar estimates in the UK and US suggest a smaller multiplier – in the region of 3 to 4 jobs per million dollars. The difference is possibly attributable to the well documented constraint financing poses for growth of SMEs in emerging economies and the higher growth potential when such constraints are relieved. SMEs in developing countries are also more labor-intensive than their developed country counterparts.
We also find that:
- There is wide variation in job creation across the spectrum of SMEs: job creation among the 75th percentile of SMEs is more than twice that of the median.
- Smaller firms create more jobs from financing than larger firms: in relative terms, the employment change achieved by SMEs employing between 10-49 employees is almost thrice as much as those that employ more than 100 employees.
- Overall job creation among SMEs is driven by a small group of high-performing firms often referred to as “gazelles”. Such firms, distributed throughout the SME size spectrum, are difficult to identify or cultivate. World Bank research sheds further light on this.
From an operational perspective, the report provides a public tool for governments, development finance institutions (DFIs), and private financial institutions with SME finance commitments to measure the impact of their investment on job creation. For example, DFIs could adopt the underlying framework of the model and use their own data to understand the job creation effects associated with their SME finance operations. It can also help banks demonstrate their results to regulators and investors.
The methodology has limitations, highlighting the need for further research. The use of existing firm-level data introduces constraints in the data structure and sampling, severely restricting the empirical analysis. As a result, the regression estimate does not allow for a causal interpretation of SME financing on job creation. It is also important to bear in mind that the data for the study was collected before the COVID-19 crisis, so the results should be viewed as more of a structural estimation rather than what could be expected during or immediately after a crisis. This methodology can be augmented through further data collection that can fine-tune and extend the analysis. More broadly, this work should be extended using more rigorous studies, including well thought out impact evaluations that can shed light to the key question of whether financing causes SMEs to grow.
This tool is part of a broader ongoing effort to improve the measurement of economic impacts of IFC investments. To date, 14 sector-specific models have been developed to estimate economy-wide employment and value-added effects from IFC investment projects. The models use a variety of methodologies that combine project-specific information with macro, sector and micro data to estimate indirect backward and forward effects throughout the economy. They cover relevant sectors to IFC operations, including agribusiness, manufacturing and selected services, different types of financial intermediation, as well as physical and digital infrastructure.