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The Corruption Risk Index (CRI) is an important measure that is used to understand the level of corruption in the concrete country. The CRI is allowed to measure the corruption level with the focus on public procurement in the state. The goal of this report is to measure the CRI with references to the identified risk indicators associated with public procurement in the Czech Republic during the period of 2008-2015.
The CRI is measured with the focus on analyzing the procurement contracts observed during the set period of time. While referring to the ‘Big’ Public Procurement Data related to the Czech Republic, it is possible to analyze the probability of corruption in the country’s public procurement sector. The available data allow identifying the following corruption risk indicators:
- The number of offers that is used to examine the limits of the competition in the state;
- The competition type that is used to identify possible signs of the unfair and restricted competition;
- The decision or evaluation criteria that influence the choice of the supplier.
According to Figure 1, the number of offers increased significantly during the months of 2014 and 2015 years. These data indicate that the assumed level of corruption associated with the availability of bids in the sector is low, but this factor is significantly influenced by the type and number of suppliers winning offers. This number of offers is meaningful while comparing it to the data of 2008 when the highest number of offers was 13 in comparison to the current 33 offers (Figure 2).
The comparison of the data for different years is important to understand the trends in the public procurement sector. Such an approach to analyzing the situation can be discussed as an indirect indicator of the observed corruption because the conclusions that the level of corruption was higher in 2008 in comparison to the 2012-2015 period should be supported with more quantitative data. In this case, the quantitative data depend on the procedure of measuring the CRI in the Czech Republic during the set period of time.
The CRI is measured as 0 ≤ CRIt ≤ 1, and this indicator is calculated according to the formula CRIt = Σj wj * CIjt, where the focus is on the number of components or risk indicators and their weights. In order to determine the actual CRI for the Czech Republic during the period of 2008-2015, the scores were added to variables, and the binary logistic regression was conducted with the focus on the number of offers as the dependent variable. As a result of the regression analysis, the component weights were added to the most influential indicators, where 1 meant the highest level of influence and 0 – the lowest one. Coefficient sizes were determined with the focus on the level of prediction among variables. It was found that negotiation with the publication is associated with the higher probability of receiving one offer, and the opened competition has the lowest impact. In addition, it was found that the best price criterion was most associated with the probability to sign the single bidder contract in comparison with the mixed criteria. The component weights were assigned according to these data analysis (Table 1).
Table 1. Component weights of CRI presenting the variables
The next step was the identification of the CRI distribution in order to conclude the corruption rate in the Czech Republic. After the application of the component weights, the CRI formula was used. The frequency distribution was used for the data analysis. It was found that the largest number of firms (25%) participated in relations characterized by the CRI 0.2-0.3. During the period of 2008-2015, only 3% of firms were characterized by the CRI in 0.6-0.9 (Figure 3).
The results of the binary logistic regression and the frequency distribution analyses used for measuring the CRI indicate that the level of corruption in the Czech Republic is rather low while assessing the measures focusing on the public procurement. It is possible to state that the distribution of the CRI is normal for the selected period of time. In order to measure the level of corruption more appropriately, it is necessary to refer to the larger number of CRI indicators. For this analysis, the limited number of variables was selected; as a result, the data can have significant limitations. The focus on additional components of CRI variables is important in order to achieve integrity regarding data analysis and results.
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