Various business support programs have been implemented in many countries across the world. Grants, interest-rate subsidies, and equity participation are among some of the most adopted tools for promoting firms’ performances (Dupont and Martin, 2006). Such assistance programs also have their own objectives. For example, low-interest rate loans and cash transfers to new and small firms are designed to overcome the financial constraints many firms face (Hubbard, 1998). Moreover, these programs may aim to help firms adopt new technologies (Bronzini and Piselli, 2016; Dimos and Pugh, 2016). Occasionally, governments also use public subsidies to promote industrial development in lagging sectors, such as Regional Selective Assistance (RSA) in the UK or regional policy subsidies in Sweden and Italy.
Georgia is no exception in this regard, for instance, Enterprise Georgia is a key implementing agency, responsible for business support, export promotion and investment throughout the country. The agency covers three different aspects of entrepreneurial promotion. One is the industrial component, which is tailored to the specific stages of development and the financial needs of a business. The program provides its beneficiaries co-financing of bank loan interest, partial collateral guarantees, leasing opportunities, and technical assistance. A further component is termed Host in Georgia, and has been introduced to promote the hospitality industry within the country: to attract increasing numbers of tourists, create jobs, and develop each of Georgia’s regions. The scheme promotes the arrival of international hotel brands, via franchises or management contracts, by co-financing any royalty fees. Finally, but no less significantly, is the Micro and Small Business Support (MSBS) program, designed to render financial support and consulting to micro and small businesses. The existence of these programs appears attractive, nevertheless, it is still somewhat critical to evaluate their effectiveness.
It is problematic killing two birds with one stone, and equally so using a single method to assess the outcomes of these three programs. Therefore, for simplicity, we have only concentrated on the MSBS program and tried to evaluate its effectiveness. Ultimately, the task was, unfortunately, not as easy as expected, however, we have still discerned some interesting findings that are certainly worth sharing.
It is now the fourth year the MSBS program is being steadily implemented across Georgia, with the exception of Tbilisi. In total, 6,212 grants have been issued to beneficiaries. The fewest activities were recorded in the first year, with only 608 projects financed. Several reasons may help explain this figure and the resultant limited participation, including a lack of public trust and weak communications strategies from the implementing agencies. Thereafter however, the popularity of the program increased, and a record number of beneficiaries participated in 2016 (2,596 projects). Since 2015, the government has invested around 47 million GEL in supporting micro and small businesses, while the total volume of all investment projects, including the co-financing component, is approximately 61.6 mln. GEL.
As our main research is to identify the short-term effects of the program, we must focus on its second wave implemented in 2016. Having assessed the availability of the high-quality data concerning beneficiaries and non-beneficiaries by municipality, the Samtskhe-Javakheti and Shida-Kartli regions were nominated for further study.
Before discussing our results, the methodology behind how contractor organizations select potential beneficiaries is particularly noteworthy. Typically, every enterprise applying for a grant undergoes a two-stage selection procedure. The first stage involves a pre-screening committee that assesses the submitted one-page business summaries and is resolved with a simple pass or fail. During the second stage, enterprises that successfully passed the first stage are asked to submit a full business plan, which are then evaluated by an independent agency (contractor organizations) and assigned a score. Enterprises scoring above a certain threshold (these cut-offs are calculated by the contractor organization, considering the quality of the application and the budget of the program) are awarded a grant, whereas those below do not receive funding.
For this study, we have combined two different sources of information. The first dataset is derived directly from the contractor organization, which provides information on the status of an application (whether it is funded), the amount of the grant, and the location and industry in which the firm operates. However, this dataset lacks information about firms’ financial and economic indicators. To fill this gap, we conducted a survey of the program participants. Having subsequently linked these two datasets, we found a sample of 284 companies, out of which 122 received funding and 162 did not.
As previously mentioned, evaluating the effectiveness of government programs is crucial not only for researchers, but also for policymakers. In the empirical literature, the term “effectiveness” is defined in several ways: it either applies to improved technology, higher productivity, and improved survival rate, or to improvement in any other dimension. However, the results from the empirical studies are mixed and are mostly driven by the measure of the outcome indicator.
In order to estimate the effect of the public support program, we are using an econometrics technique. The key concept behind the method is to compare the different outcome measures for both beneficiaries (treatment group) and non-beneficiaries (control group). The pure impact of the program is thus calculated by the difference in outcomes between the treatment and the control groups. Moreover, we are manipulating certain firm level and individual level characteristics in order to estimate the pure effect of the program.
We can estimate the effect of the subsidies from the following outcomes:
• Survival rate – This indicator measures whether a company continues to operate within its initial field. We can thus observe the average survival rate for beneficiaries (94%) is almost two times higher (48%) than for non-beneficiaries (it is important to note that this indicator only relates to firms that agreed to participate in an interview. Those firms that did not take part in the survey are consequently absent from the calculation. Therefore, these survival rates are the upper bound estimators and are perhaps lower in reality). The high survival rate for funded firms is driven by both existing businesses and start-ups. Furthermore, the study shows that the effects of a grant on start-ups are more significant. Namely, those start-ups which received a grant are more likely to continue operation in the same field than those which failed to receive funding.
• Labor productivity – Labor productivity measures how the labor force in utilized in a company and calculated as sales per employee. Starting with simple means comparisons, we can observe that there is no significant difference between beneficiaries and non-beneficiaries in terms of labor productivity. The econometrics analysis also supports the argument that receiving funding does not have a noticeable effect on labor productivity.
• Sales – Similar to labor productivity, the program does not influence sales in either the first or the second year of the program. Moreover, the study also reveals that the program has no effect on sales growth.
• Investment in fixed assets – the effect of the government capital subsidy program on private capital investment has started to acquire growing interest within recent literature. The main question is whether pubic funding incentivizes private investment or is crowding it out. We therefore studied the volume of investments in fixed assets for both beneficiaries and non-beneficiaries. According to the program description, their beneficiaries were required to invest the grant and co-finance the money immediately after the program. Due to these requirements, investments in fixed assets for beneficiaries increased in 2016, though, in the first and second year of the program, the volume of investment decreased. On the other hand, there is no significant difference between beneficiaries and non-beneficiaries in terms of investment. Thus, the program itself does not have an investment enhancing effect.
It should be kept in mind that these are only the short-term effects of the program, which will not necessarily alter positive spillovers from continuing in the long-run. One can conclude, at this stage, that the program has positive effects on a company’s survival, although the impacts on labor productivity and other economic outcomes have not been observed. These results are in line with recent empirical studies, which confirm the positive impact of public subsidies on employment, investment, and plant survival, while the effect on productivity is negligible or negative (Bergstrom, 2000; Bernini and Pellegrini, 2011; Cerqua and Pellegrini, 2013).
Outcome Indicators Effect of the program
Figure 1: Ceilings of Payment-to-Income (PTI) and Loans-to-Value (LTV) by Monthly Net Income
|Monthly Net Income, GEL||Effect of the program|
|Firm survival rate||Positive effect|
|Labor productivity||No effect|
|Investment in fixed assets||No effect|
|Quality of life||Positive effect|
|Monthly income||No effect|
It is interesting to study the effect of the program on firms’ performance, while also considering the personal well-being of the grant recipients. Therefore, we investigated how the monthly income of grant holders differs from those without a grant. It is notable that the grant did not significantly alter the individual income of the participants. The study discerned that, on average, grant recipients have a higher income than non-recipients, however this cannot be solely explained by the existence of the grant. Even though the program does not have a significant effect on the monthly income of its participants, it has positively affected the individual well-being of the grant holders.
In conclusion, the first steps in evaluating the Micro and Small Business Support program have already begun. Nevertheless, due to the data limitation and methodological challenges, we now have an initial insight into the kind of short-term outcomes the program has reached. As proposed by Enterprise Georgia, this year the grant will be awarded using a different methodology and structure. As researchers, we are looking forward to accessing significant future data in order to effectively evaluate the forthcoming direction of the Micro and Small Business Support program.