Robustness Checks

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Figure 2 displays the relatedness of formal and informal institutions for the second CIS wave.

Again, a positive coupling of the two dimensions seems evident. Yet again, each country shows unique patterns of the formal/informal relationship. Further, while the general structure of the country positioning remains quite similar, certain changes emerge. This includes the shift between Romania and Bulgaria, with Romania now outperforming Bulgaria, or the changes of position between Lithuania and Latvia, as the informal institutions of Latvia have substantially improved, while Lithuania reverted.

The results of our additional control variables confirm our expectations. All variables are again highly significant and positive. The only exception is our variable International in the case of Ecoco. The effect of Size is more pronounced, ranging at ~20% for Ecomat and ~25% for Ecoco.³³ The effect of Group is more homogenous than for the CIS 2008 as the effect is ~3%

for both EI types. International again has a larger effect for Ecomat, although the differences to the effects for Ecoco are also substantially smaller.

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suffer because of having so few countries in our samples. Hence, to check our findings, we use OLS to analyse the effect of our institutional variables on the country effects, which are obtained from the probit analysis of our entire sample (Bryan and Jenkins, 2013). The results are provided in Table 6.

Table 6: Results of OLS regressions for country-fixed effects

(1) (2) (3) (4)

Analysis type OLS OLS OLS OLS

Dep. Var. Ecomat 08 Ecoco 08 Ecomat 14 Ecoco 14

Model 1

iForm .1271

(0.163)

.1861 (0.164)

.1115 (0.210)

.2220*

(0.070) Model 2

iForm .0949

(0.334) .1472

(0.345) .0312

(0.680) .1262

(0.205)

iInf .0838

(0.312) .1009

(0.383) .1970**

(0.011) .2347**

(0.010) Model 3

iForm*iInf .1675***

(0.009) .2188**

(0.012) .1618***

(0.003) .2623***

(0.000)

Obs. 12 12 12 12

Notes to Table 6: Robust standard errors were used. The constant is not reported.

The coefficient and the p-value (in brackets) are reported. * p<0.1 ; ** p<0.05 ; *** p<0.01

Focusing on Model 1 with formal institutions only, our main insights are confirmed. The estimated effect of formal institutions is larger for Ecoco for both CIS waves. Also, the difference between Ecomat and Ecoco is more pronounced for the CIS 2014 wave, as the estimated coefficient becomes larger for Ecoco, while becoming slightly smaller for Ecomat.

The coefficient for Ecoco for the CIS 2014 is significant at the 10% level.

Model 2 also confirms our main insights. The effect of formal institutions is stronger for Ecoco for both CIS waves, yet the difference with Ecomat is more pronounced for the second wave.

This OLS regression reveals that the coefficient of formal institutions is smaller for the second wave in the case of Ecoco, which is a difference compared to the main results. The findings on informal institutions also support our main results. The impact of informal institutions is similar for both EI categories and waves, the gap between the effects of formal and informal institutions becomes substantially larger for Ecomat than for Ecoco. Further, the effect of informal institutions is substantially larger for the second CIS wave, reflected by the informal coefficient being significant at the 5% level for both EI categories.

Model 3 explores the relation of our interacted institutional variable with the country effects.

Again, the main findings are confirmed. Specifically, the effect is stronger for Ecoco, and the gap between Ecomat and Ecoco is larger for the second CIS wave. Note that the coefficient for Ecoco increases by roughly one fourth, whereas it decreases slightly for Ecomat. For all four

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specifications, the interaction variable is significant at the 5% and 1% level, respectively.

To understand these results in more detail, we plot the country effects against our interacted institutional variable, following Bryan and Jenkins (2013). We create separate graphs for each EI category for the second CIS wave (CIS 2014). Figure 3 plots the country-fixed effects from the analysis for Ecomat.

Figure 3: Country effects and interacted institutions for Ecomat

The graphic presentation of our regression results (Table 6, Model 3, Column 3) seen in Figure 3 provides some interesting insights. The country effect ranges from slightly below 0 to 0.8.

Further, most countries are close to 0 for the interacted institutional variable. Yet, the country effect for these countries ranges from below 0 to over 0.6. It appears that this heterogeneity of country effects cannot be attributed to the institutional variable. Thus, the clear statistical relationship seems to be driven by the countries underperforming institutionally (Romania and Bulgaria), and those overperforming (Latvia, Portugal, and Germany). The country effect of Bulgaria and Romania is second and third lowest, ranging around zero. The country effect of Latvia at 0.4 is moderate, but Portugal and Germany have the highest country effects of more than 0.75, corresponding to the highest institutional values of 1 and almost 3, respectively.

85 Figure 4: Country effects and interacted institutions for Ecoco

Figure 4 plots the country effects obtained from the analysis of Ecoco (Table 6, Model 3, Column 4). Interestingly, the emerging structure is very similar to the structure for Ecomat. The main difference seems to be the size of the country effect that ranges from 0 to 1.3. Given the similar structure of the two graphs, it seems plausible that the higher coefficient is mostly driven by the different range of the country effect for Ecoco. These graphical investigations seem to show that our institutional variable is a good indicator of the relative quality of the institutional environment of the countries included in our analysis. Yet, the clear heterogeneity of the country effects coefficient for those countries ranging around 0 for the institutional variable, cannot be sufficiently related to our institutional measure.

When focusing on only the ten countries present in both survey waves (excluding Ireland and Cyprus from the first, and Croatia and Greece from the second wave), there are several observable differences. For the CIS 2008 wave, the results for Ecomat remain basically the same. For Ecoco, however, the effect of formal institutions is reduced to 4% and the effect of informal institutions increases to 15.7%. In other words, if we focus on the two areas of environmental concern, the effect of informal institutions is stronger for Ecoco in the ten country analysis (full sample: stronger for Ecomat), and the effect of formal institutions is

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slightly stronger for Ecomat in the ten country analysis (full sample: stronger for Ecoco). For CIS 2014, the differences are similar for both EI types. The effect of formal institutions is more pronounced and the effect of informal institutions is less pronounced in the ten country sample.

In the case of Ecoco, the effect of formal institutions is estimated to be ~4% higher than the effect of informal institutions in the ten country sample (full sample: the effect of informal institutions is ~3% larger).

As a final robustness check, we used a dichotomous innovation variable to capture whether or not a firm introduced any type of innovation. We conduct this investigation to ensure that our measures of institutions are specifically relevant in the context of EI. The results confirmed that our formal institutional measure is more positively related to increasing the introduction of the analysed EI types than general innovation. This robustness check follows Garrone et al. (2018) and is a way to show that the institutions are not generic indications of a country’s progress.

The results will be discussed in more detail in the next section.