## 4 Results
### Research Questions 1 and 2  
#### 4.1.1 Recession and Non-Recession Model 1--All Sectors Together  
Table 1 describes the number of Czech subjects reporting R&D results over the years 2007 to 2017. The recession periods are based on the definition of declining GDP and are marked. The economic crises in 2009 and 2012-2013 were accompanied not only by a decline in GDP, but also by a sharp decline in the production performance of CZ-NACE C Manufacturing in the Czech Republic (The Czech Classification of Economic Activities CZ-NACE is derived from the International Standard Industrial Classification of All Economic Activities). The number of subjects of the Czech Republic declaring the results of R&D in the years 2007 to 2017 raises from 2021 to 3114 subjects [24; 25; 26]. The total number of all entities in the Czech Republic increased from 570,000 to 668,000 subjects in the same period (the non-profit sector consisted of \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**Sector** & **2007** & **2008** & **2009** & **2010** & **2011** & **2012** & **2013** & **2014** & **2015** & **2016** & **2017** \\ \hline Business enterprise & 1736 & 1766 & 1872 & 2107 & 2237 & 2312 & 2299 & 2368 & 2387 & 2355 & 2628 \\ Government & 224 & 222 & 223 & 219 & 209 & 195 & 199 & 195 & 196 & 195 & 199 \\ Higher education & 186 & 185 & 187 & 193 & 202 & 203 & 208 & 213 & 228 & 227 & 229 \\ Non-gov-non-profit & 58 & 60 & 63 & 68 & 72 & 68 & 62 & 64 & 59 & 53 & 58 \\ GDP 1 real & 3964 & 4070 & 3874 2 & 3962 & 4033 & 4001 2 & 3981 2 & 4089 & 4307 & 4412 & 4601 \\ \hline \hline \end{tabular}  
* Database of National Accounts. Czech Statistical Office (CZSO) in billion Czech crowns (CZK) [23]. 2 Recissions (decline in GDP).  
Footnote 2: footnotemark:  
\end{table} 
Table 1: Numbers of Research and Development (R&D) subjects in the Czech Republic in sectors 2007–2017 [24; 25; 26]. 120-150,000 subjects, the government sector had 18,000 subjects, and the business sector had developed from 409,000 to 502,000 subjects) [23]. Table 2 shows descriptive statistics of all four sectors of the Czech economy in terms of the number of entities that declare R&D results. As can be seen for business enterprise sector the numbers of subject is much higher than for other sectors. This is the main reason why we use the logarithm function in our first model (Model 1) to eliminate the different levels of measurement. The fact that government and higher education sectors have very similar mean and median number of subjects is also interesting. The following overview shows the results of the bivariate linear regression forecasting variable from other scores. Dummy variables (nominal variables coded 1 = \"recession\", 0 = \"non-recession\") were used for the purpose of identifying the influence of economic cycle phase recession. Model 1 is given in Equation (1):  
\[\log(\#\text{subjects})=\beta_{0,\text{j}}+\beta_{1,\text{j}}\left(\text{t} \right)+\beta_{2,\text{j}}\left(\text{recession}\right)+\epsilon_{\text{i, j}}, \tag{1}\]  
where \(\#\text{subjects}\) denote the number of subjects, j is the index of each sector. The logarithm of the number of R&D entities working in all sectors (business, government, higher education, and non-profit) is determined by the year and whether or not there has been a recession. Results of Model 1 (all sectors together) are presented in Table 3.  
Table 3 shows results of linear mixed effect model. As can be seen the only statistically significant variable is the intercept with the value of 5.557. When the p-value for t and recession variable are greater than 0.05 we can conclude that these two variables are not statistically significant. Interestingly, the t variable was observed to be insignificant, which can be firstly seen as counterintuitive. However, from Table 1 we can see that the number of subjects rises only for two sectors (Business enterprise sector and Higher education sector) over time, as can be seen the number of subjects in the government sector decreases.