The relation to the government control is one of the main problems of the modern economic theory.

Introduction
The relation to the government control is one of the main problems of the modern economic theory. Historically, one of the brightest examples of the domination of control is the USSR. The free market was almost absent in the country. Companies received the clear directions about the type and amount of the produced goods and services. The import was strictly limited, as well as the export. As a result, the strong deficit of certain goods and services existed. Especially, this situation was observed in the B2C market. Serious shifts in the economy appeared and they made the further existence of the country impossible.
In the modern economic world, there are no many countries, which follow the way of USSR in the problem of control. However, all governments use the elements of control in the certain degree. The most often used elements of the control are the restrictions of the movement of the capital. Often the government forces companies to convert all revenues in the local currency. Such measures are applied when the deficit of the foreign currency is observed in the country. From the one side, they are necessary for the providing of the financial stability. However, the companies meet serious problems because they need foreign currency for the procurement. As a result, their performance falls.
In general, the applying of the control always leads to some loses of companies even when these measures are vitally important for the economic system in general. In our paper, we want to demonstrate this concept on the example of emergent countries.
In the modern literature, the different forms of the control are investigated. They include not only the government control.  For example, in (Chari et al. 2009), the control of the companies from developed countries under the companies from emergent countries is investigated. Authors found that if the company from developed country receives the majority of shares of the company from the emergent country, the stock price of the asset grows significantly. The similar results also were received in (Chari et al. 2004; Sharma and Raat 2014).
Telling about the role of government in the control, we can note the paper (Pasricha et al. 2015). The authors found that in emergent countries the role of control of capital was more significant before the global financial crisis of 2008 than after this. In (Baba and Kokenyne2011), authors detected that capital control negatively influences the size of capital flows. However, this relationship does not have statistical significance. It is stated in (Chanda2003) that capital control can influence the long-term growth in both positive and negative directions. The direction of the influence depends on the national particularities of the certain country. Authors in (Frenkel et al. 2001) found that mechanisms of the capital control decrease the volatility of the exchange rate in the long-term period. However, the volatility in the short-term period significantly grows and it negatively influences the output of companies.
 
 
 
Methodology
For the conducting of analysis, we use World Business Environment Survey that includes around 10,000 observations for companies from 81 countries. We classified 27 countries as countries with the emergent economy. This list includes Argentina, Bangladesh, Brazil, Bulgaria, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Malaysia, Mexico, Nigeria, Pakistan, Peru, Philippines, Poland, Romania, Russia, Slovenia, South Africa, Thailand, Turkey, Ukraine, and Venezuela. The used dataset allows us to measure six directions of the government control. There are business regulations, customs regulations, labor regulations, foreign exchange regulations, environmental regulations, and fire regulations. During the conducting of the survey, the managers of companies were asked to estimate these regulations as the obstacle. The scale with four values from 1 to 4 was used for this purpose. The score 1 means that the discussed regulation is not the obstacle for the company, while the score 4 means that this regulation is the major obstacle. In general, we assume that any regulation negatively influences the performance of the company. As the measure of performance, we use six indexes of growth. They include the growth of sales, the growth of investment, the growth of export, the growth of labor force, and the growth of debt. It should be noted that first four indexes measure the performance directly. We mean that growth of sales, investment, export, and labor force is the positive sign for the company. However, the increasing of the debt is the negative sign for the company. Therefore, it is the measure of anti-performance actually. That is why we will assume that regulations influence negatively the growth of sales, investment, export, and labor force and positively the growth of debt.
We are interested in the analyzing some specific research questions. The main questions include:
What is the influence of business regulations on the growth of sales of companies from emergent countries? What is the influence of customs regulations on the growth of sales of companies from emergent countries? What is the influence of labor regulations on the growth of sales of companies from emergent countries? What is the influence of foreign exchange regulations on the growth of sales of companies from emergent countries? What is the influence of environmental regulations on the growth of sales of companies from emergent countries? What is the influence of fire regulations on the growth of sales of companies from emergent countries?
What is the influence of business regulations on the growth of investment of companies from emergent countries? What is the influence of customs regulations on the growth of investment of companies from emergent countries? What is the influence of labor regulations on the growth of investment of companies from emergent countries? What is the influence of foreign exchange regulations on the growth of investment of companies from emergent countries? What is the influence of environmental regulations on the growth of investment of companies from emergent countries? What is the influence of fire regulations on the growth of investment of companies from emergent countries?
What is the influence of business regulations on the growth of export of companies from emergent countries? What is the influence of customs regulations on the growth of export of companies from emergent countries? What is the influence of labor regulations on the growth of export of companies from emergent countries? What is the influence of foreign exchange regulations on the growth of export of companies from emergent countries? What is the influence of environmental regulations on the growth of export of companies from emergent countries? What is the influence of fire regulations on the growth of export of companies from emergent countries?
What is the influence of business regulations on the growth of labor force of companies from emergent countries? What is the influence of customs regulations on the growth of labor force of companies from emergent countries? What is the influence of labor regulations on the growth of labor force of companies from emergent countries? What is the influence of foreign exchange regulations on the growth of labor force of companies from emergent countries? What is the influence of environmental regulations on the growth of labor force of companies from emergent countries? What is the influence of fire regulations on the growth of labor force of companies from emergent countries?
What is the influence of business regulations on the growth of debt of companies from emergent countries? What is the influence of customs regulations on the growth of debt of companies from emergent countries? What is the influence of labor regulations on the growth of debt of companies from emergent countries? What is the influence of foreign exchange regulations on the growth of debt of companies from emergent countries? What is the influence of environmental regulations on the growth of debt of companies from emergent countries? What is the influence of fire regulations on the growth of debt of companies from emergent countries?
Some emergent countries especially interest us. There are Russia, India, and Brazil. They are the bright representatives of the concept of emergent economy and they are represented by the big number of companies in the sample. Therefore, we also analyze each country separately. However, in this case, we analyze the influence of regulations on the growth of sales only without the influence on other indexes of performance. That is why additional research questions appear. They include:
What is the influence of business regulations on the growth of sales of Russian companies? What is the influence of customs regulations on the growth of sales of Russian companies? What is the influence of labor regulations on the growth of sales of Russian companies? What is the influence of foreign exchange regulations on the growth of sales of Russian companies? What is the influence of environmental regulations on the growth of sales of Russian companies? What is the influence of fire regulations on the growth of sales of Russian companies?
What is the influence of business regulations on the growth of sales of Indian companies? What is the influence of customs regulations on the growth of sales of Indian companies? What is the influence of labor regulations on the growth of sales of Indian companies? What is the influence of foreign exchange regulations on the growth of sales of Indian companies? What is the influence of environmental regulations on the growth of sales of Indian companies? What is the influence of fire regulations on the growth of sales of Indian companies?
What is the influence of business regulations on the growth of sales of Brazilian companies? What is the influence of customs regulations on the growth of sales of Brazilian companies? What is the influence of labor regulations on the growth of sales of Brazilian companies? What is the influence of foreign exchange regulations on the growth of sales of Brazilian companies? What is the influence of environmental regulations on the growth of sales of Brazilian companies? What is the influence of fire regulations on the growth of sales of Brazilian companies?
Analyzing emergent markets, we also pay special attention to two categories of companies. There are manufacturing companies and large companies. We want to see how regulations influence the growth of sales in these cases. Therefore, additional research questions appear. They include:
What is the influence of business regulations on the growth of sales of manufacturing companies in emergent markets? What is the influence of customs regulations on the growth of sales of manufacturing companies in emergent markets? What is the influence of labor regulations on the growth of sales of manufacturing companies in emergent markets? What is the influence of foreign exchange regulations on the growth of sales of manufacturing companies in emergent markets? What is the influence of environmental regulations on the growth of sales of manufacturing companies in emergent markets? What is the influence of fire regulations on the growth of sales of manufacturing companies in emergent markets?
What is the influence of business regulations on the growth of sales of large companies in emergent markets? What is the influence of customs regulations on the growth of sales of large companies in emergent markets? What is the influence of labor regulations on the growth of sales of large companies in emergent markets? What is the influence of foreign exchange regulations on the growth of sales of large companies in emergent markets? What is the influence of environmental regulations on the growth of sales of large companies in emergent markets? What is the influence of fire regulations on the growth of sales of large companies in emergent markets?
Finally, we also want to compare results for the companies from emergent markets with results for companies from other markets. Therefore, we also make the analysis of the influence of regulations on the growth of sales for the full sample (emergent markets, developed markets, and others) and for the developed countries exclusively. As a result, next additional research questions appear:
What is the influence of business regulations on the growth of sales of companies in developed markets? What is the influence of customs regulations on the growth of sales of companies in developed markets? What is the influence of labor regulations on the growth of sales of companies in developed markets? What is the influence of foreign exchange regulations on the growth of sales of companies in developed markets? What is the influence of environmental regulations on the growth of sales of companies in developed markets? What is the influence of fire regulations on the growth of sales of companies in developed markets?
What is the influence of business regulations on the growth of sales of companies in all markets? What is the influence of customs regulations on the growth of sales of companies in all markets? What is the influence of labor regulations on the growth of sales of companies in all markets? What is the influence of foreign exchange regulations on the growth of sales of companies in all markets? What is the influence of environmental regulations on the growth of sales of companies in all markets? What is the influence of fire regulations on the growth of sales of companies in all markets?
Telling about the developed markets, we mean such countries as USA, UK, Germany, France, Canada, Sweden, Italy, and Spain. The mentioned term (all markets) assumes the including of all companies of all 81 countries, which are available in our sample.
Also, if the value of growth of some performance characteristic exceeds 100%, we exclude this value from the analysis. For example, if the growth of investments of the certain company is equal 150%, we do not consider it. There are three reasons for this strategy. The first reason has the mathematical nature. It is obvious that the value of falling cannot be more than 100% because if some characteristic falls by 100% it will be equal 0 and the further falling is impossible. The value of sales cannot be negative for example. From another side, the growth by 1,000% is quite possible. Therefore, the certain shift on the side of growth appears. We want to exclude this aspect. Moreover, the influence of regulations has the limited character. It is obvious that growth by 1,000% is explained by other factors. Moreover, the share of companies with the dramatically high rates of growth of performance characteristics is very low. Therefore, we exclude these values to receive more clear results.
Telling about our hypotheses, for each question about the growth of sales, investment, export, and labor force, we assume that the influence of regulations will be negative. For each question about the growth of debt, we assume that the influence of regulations will be positive. For the checking of these assumptions, we use the correlation and regression analysis. In addition, we test the presence of the quadratic relationship between variables using regression analysis.
 
Business regulations as the measure of control and their influence on performance of companies (the sample of all companies of emergent countries)
Considering the business regulations as the obstacle, companies on average estimated its value as 2.14 on the scale from 1 to 4. The lowest extent of the problem is observed in Poland where the value of this variable is equal 1.37. In Mexico, this problem is more significant than in other countries and the value of the variable is equal 3.17. The strongest linear relationship between business regulations and performance is demonstrated for the pair of business regulations and growth of export (coefficient of correlation is equal 0.07721), while the pair of business regulations and the growth of debt is characterized by the lowest correlation (the corresponding coefficient is equal 0.0257). In general, it also should be noted that business regulations is more serious problem for medium enterprises (mean score is equal 2.15) than for small enterprises (mean score is equal 2.11), while for big companies (mean score is equal 2.2) this obstacle is more significant than for both small companies and medium companies. Below, we consider the influence of business regulations on all five measures of performance.
The coefficient of correlation between the variable business regulations and growth of sales is equal -0.03715. Regressing growth of sales on business regulations we receive the equation Growth of sales = Business Regulations * (-1.35) + 8.28, which was built on 2,806 observations. Adjusted R-square for this regression is equal 0.001 and explanatory variable is significant at 5% level because its p-value is equal 0.049 (<0.05). Moreover, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.049 to 0.183). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample business regulations negatively significantly influence the growth of sales. Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable business regulations and growth of investment is equal -0.06638. Regressing growth of investment on business regulations we receive the equation Growth of investment = Business Regulations * (-2.71) + 20.04, which was built on 1,960 observations. Adjusted R-square for this regression is equal 0.004 and explanatory variable is significant at 1% level because its p-value is equal 0.0033 (<0.01). Moreover, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.0033 to 0.75). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample business regulations negatively significantly influence the growth of investment.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable business regulations and growth of export is equal -0.07721. Regressing growth of export on business regulations we receive the equation Growth of export = Business Regulations * (-3.36) + 13.07, which was built on 848 observations. Adjusted R-square for this regression is equal 0.005 and explanatory variable is significant at 5% level because its p-value is equal 0.025 (<0.05). Moreover, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X falls but intercept is not significant in this model). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample business regulations negatively significantly influence the growth of export.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable business regulations and growth of labor force is equal -0.04539. Regressing growth of labor force on business regulations we receive the equation Growth of labor force = Business Regulations * (-1.5) + 2.2, which was built on 2,294 observations. Adjusted R-square for this regression is equal 0.0016 and explanatory variable is significant at 5% level because its p-value is equal 0.029 (<0.05). However, the intercept is not significant. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows only from 0.029 to 0.088 but intercept is still not significant). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample business regulations neutrally influence the growth of labor.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable business regulations and growth of debt is equal 0.0257. Regressing growth of debt on business regulations we receive the equation Growth of debt = Business Regulations * 0.996 + 7.6, which was built on 1,665 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.29 (>0.1). However, the intercept is significant at 1% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X falls only from 0.29 to 0.146). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample business regulations neutrally influence the growth of debt.Therefore, our null hypothesis was rejected in this case.
 
Customs regulations as the measure of control and their influence on performance of companies (the sample of all companies of emergent countries)
Considering the customs regulations as the obstacle, companies on average estimated its value as 2.26 on the scale from 1 to 4. The lowest extent of the problem is observed in Slovenia where the value of this variable is equal 1.75. In Bangladesh, this problem is more significant than in other countries and the value of the variable is equal 3.02. The strongest linear relationship between customs regulations and performance is demonstrated for the pair of customs regulations and growth of investment (coefficient of correlation is equal -0.0778), while the pair of customs regulations and the growth of debt is characterized by the lowest correlation (the corresponding coefficient is equal -0.0031). In general, it also should be noted that customs regulations is more serious problem for medium enterprises (mean score is equal 2.33) than for small enterprises (mean score is equal 2.1), while for big companies (mean score is equal 2.38) this obstacle is more significant than for both small companies and medium companies. Below, we consider the influence of customs regulations on all five measures of performance.
The coefficient of correlation between the variable customs regulations and growth of sales is equal -0.01211. Regressing growth of sales on customs regulations we receive the equation Growth of sales = Customs regulations * (-0.43) + 7.4, which was built on 2,471 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.547 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.547 to 0.61). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample customs regulations neutrally influence the growth of sales.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable customs regulations and growth of investment is equal -0.0778. Regressing growth of investment on customs regulations we receive the equation Growth of investment = Customs regulations * (-3.08) + 22.2, which was built on 1,745 observations. Adjusted R-square for this regression is equal 0.0055 and explanatory variable is significant at 1% level because its p-value is equal 0.0011 (<0.01). Moreover, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.0011 to 0.103). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample customs regulations negatively significantly influence the growth of investment.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable customs regulations and growth of export is equal -0.05212. Regressing growth of export on customs regulations we receive the equation Growth of export = Customs regulations * (-2.3) + 13.01, which was built on 848 observations. Adjusted R-square for this regression is equal 0.002 and explanatory variable is not significant because its p-value is equal 0.129 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.129 to 0.88). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample customs regulations neutrally influence the growth of export.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable customs regulations and growth of labor force is equal -0.00553. Regressing growth of labor force on customs regulations we receive the equation Growth of labor force = Customs regulations * (-0.18) + 0.11, which was built on 2,039 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.803 (>0.1). Moreover, the intercept is not significant. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X falls only from 0.803 to 0.2899). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample customs regulations neutrally influence the growth of labor.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable customs regulations and growth of debt is equal -0.00309. Regressing growth of debt on customs regulations we receive the equation Growth of debt = Customs regulations * (-0.116) + 9.4, which was built on 1,484 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.905 (>0.1). Moreover, the intercept is significant at 1% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X falls only from 0.905 to 0.808). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample customs regulations neutrally influence the growth of debt.Therefore, our null hypothesis was rejected in this case.
 
Labor regulations as the measure of control and their influence on performance of companies (the sample of all companies of emergent countries)
Considering the labor regulations as the obstacle, companies on average estimated its value as 2.35 on the scale from 1 to 4. The lowest extent of the problem is observed in Russia where the value of this variable is equal 1.68. In Brazil, this problem is more significant than in other countries and the value of the variable is equal 3.46. The strongest linear relationship between labor regulations and performance is demonstrated for the pair of labor regulations and growth of labor force (coefficient of correlation is equal -0.06907), while the pair of labor regulations and the growth of investment is characterized by the lowest correlation (the corresponding coefficient is equal -0.01564). In general, it also should be noted that labor regulations is more serious problem for medium enterprises (mean score is equal 2.41) than for small enterprises (mean score is equal 2.18), while for big companies (mean score is equal 2.54) this obstacle is more significant than for both small companies and medium companies. Below, we consider the influence of labor regulations on all five measures of performance.
The coefficient of correlation between the variable labor regulations and growth of sales is equal -0.01721. Regressing growth of sales on labor regulations we receive the equation Growth of sales = Labor regulations * (-0.63) + 7.11, which was built on 2,830 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.36 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.36 to 0.8). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample labor regulations neutrally influence the growth of sales.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable labor regulations and growth of investment is equal -0.01564. Regressing growth of investment on the labor regulations we receive the equation Growth of investment = Labor regulations * (-0.645) + 15.97, which was built on 1,974 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.4874 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.49 to 0.78). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample labor regulations neutrally influence the growth of investment.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable labor regulations and growth of export is equal -0.01788. Regressing growth of export on labor regulations we receive the equation Growth of export = Labor regulations * (-0.77) + 8.83, which was built on 860 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.6 (>0.1). However, the intercept is significant at 5%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.6 to 0.94). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample labor regulations neutrally influence the growth of export.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable labor regulations and growth of labor force is equal -0.069. Regressing growth of labor force on labor regulations we receive the equation Growth of labor force = Labor regulations * (-2.29) + 4.55, which was built on 2,319 observations. Adjusted R-square for this regression is equal 0.004 and explanatory variable is significant at 1% level because its p-value is equal 0.00087 (>0.1). Moreover, the intercept is significant at 5% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X grows from 0.00087 to 0.8056). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample labor regulations negatively significantly influence the growth of labor force.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable labor regulations and growth of debt is equal -0.0432. Regressing growth of debt on labor regulations we receive the equation Growth of debt = Labor regulations * (-1.7) + 14.17, which was built on 1,681 observations. Adjusted R-square for this regression is equal 0.001 and explanatory variable is significant at 10% level because its p-value is equal 0.077 (<0.1). Moreover, the intercept is significant at 1% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X grows from 0.077 to 0.21). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample labor regulations negatively significantly influence the growth of debt.Therefore, our null hypothesis was rejected in this case.
 
Foreign exchange regulations as the measure of control and their influence on performance of companies (the sample of all companies of emergent countries)
Considering the foreign exchange regulations as the obstacle, companies on average estimated its value as 2.04 on the scale from 1 to 4. The lowest extent of the problem is observed in Argentina where the value of this variable is equal 1.39. In Nigeria, this problem is more significant than in other countries and the value of the variable is equal 2.82. The strongest linear relationship between foreign exchange regulations and performance is demonstrated for the pair of foreign exchange regulations and growth of investment (coefficient of correlation is equal -0.08029), while the pair of foreign exchange regulations and the growth of labor force is characterized by the lowest correlation (the corresponding coefficient is equal -0.00016). In general, it also should be noted that foreign exchange regulations is more serious problem for medium enterprises (mean score is equal 2.11) than for small enterprises (mean score is equal 1.91), while for big companies (mean score is equal 2.14) this obstacle is more significant than for both small companies and medium companies. Below, we consider the influence of foreign exchange regulations on all five measures of performance.
The coefficient of correlation between the variable foreign exchange regulations and growth of sales is equal 0.00058. Regressing growth of sales on foreign exchange regulations we receive the equation Growth of sales = Foreign exchange regulations * 0.02 + 6.27, which was built on 2,582 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.98 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X falls only from 0.98 to 0.72). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample foreign exchange regulations neutrally influence the growth of sales.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable foreign exchange regulations and growth of investment is equal -0.08029. Regressing growth of investment on foreign exchange regulations we receive the equation Growth of investment = Foreign exchange regulations * (-3.3) + 22.07, which was built on 1,831 observations. Adjusted R-square for this regression is equal 0.006 and explanatory variable is significant at 1% level because its p-value is equal 0.0006 (<0.01). Moreover, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.0006 to 0.79). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample foreign exchange regulations negatively significantly influence the growth of investment.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable foreign exchange regulations and growth of export is equal -0.04623. Regressing growth of export on foreign exchange regulations we receive the equation Growth of export = Foreign exchange regulations * (-1.95) + 11.47, which was built on 852 observations. Adjusted R-square for this regression is equal 0.001 and explanatory variable is not significant because its p-value is equal 0.18 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X falls only from 0.18 to 0.17). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample foreign exchange regulations neutrally influence the growth of export.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable foreign exchange regulations and growth of labor force is equal -0.00016. Regressing growth of labor force on foreign exchange regulations we receive the equation Growth of labor force = Foreign exchange regulations * (-0.005) – 0.26, which was built on 2,118 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.99 (>0.1). Moreover, the intercept is not significant. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X falls only from 0.99 to 0.41). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample foreign exchange regulations neutrally influence the growth of labor force.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable foreign exchange regulations and growth of debt is equal 0.0279. Regressing growth of debt on foreign exchange regulations we receive the equation Growth of debt = Foreign exchange regulations * (1.1) + 7.29, which was built on 1,534 observations. Adjusted R-square for this regression is equal 0.00013 and explanatory variable is not significant because its p-value is equal 0.27 (>0.1). However, the intercept is significant at 1% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X grows from 0.27 to 0.98). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample foreign exchange regulations neutrally influence the growth of debt.Therefore, our null hypothesis was rejected in this case.
 
Environmental regulations as the measure of control and their influence on performance of companies (the sample of all companies of emergent countries)
Considering the environmental regulations as the obstacle, companies on average estimated its value as 2.11 on the scale from 1 to 4. The lowest extent of the problem is observed in Romania where the value of this variable is equal 1.64. In Chile, this problem is more significant than in other countries and the value of the variable is equal 2.69. The strongest linear relationship between environmental regulations and performance is demonstrated for the pair of environmental regulations and growth of investment (coefficient of correlation is equal -0.076), while the pair of environmental regulations and the growth of debt is characterized by the lowest correlation (the corresponding coefficient is equal 0.0054). In general, it also should be noted that environmental regulations are more serious problem for medium enterprises (mean score is equal 2.18) than for small enterprises (mean score is equal 1.96), while for big companies (mean score is equal 2.22) this obstacle is more significant than for both small companies and medium companies. Below, we consider the influence of environmental regulations on all five measures of performance.
The coefficient of correlation between the variable environmental regulations and growth of sales is equal -0.024. Regressing growth of sales on environmental regulations we receive the equation Growth of sales = Environmental regulations * (-0.95) + 7.28, which was built on 2,752 observations. Adjusted R-square for this regression is equal around 0.00022 and explanatory variable is not significant because its p-value is equal 0.2 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.2 to 0.93). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample environmental regulations neutrally influence the growth of sales.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable environmental regulations and growth of investment is equal -0.07594. Regressing growth of investment on environmental regulations we receive the equation Growth of investment = Environmental regulations * (-3.3) + 21.39, which was built on 1,918 observations. Adjusted R-square for this regression is equal 0.005 and explanatory variable is significant at 1% level because its p-value is equal 0.00087 (<0.01). Moreover, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.00087 to 0.7). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample environmental regulations negatively significantly influence the growth of investment.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable environmental regulations and growth of export is equal -0.03121. Regressing growth of export on environmental regulations we receive the equation Growth of export = Environmental regulations * (-1.42) + 9.82, which was built on 838 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.37 (>0.1). However, the intercept is significant at 5%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.37 to 0.48). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample environmental regulations neutrally influence the growth of export.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable environmental regulations and growth of labor force is equal -0.0677. Regressing growth of labor force on environmental regulations we receive the equation Growth of labor force = Environmental regulations * (-2.37) + 3.85, which was built on 2,258 observations. Adjusted R-square for this regression is equal 0.004 and explanatory variable is significant at 1% level because its p-value is equal 0.001 (<0.01). Moreover, the intercept is significant at 5% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X grows from 0.001 to 0.47). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample environmental regulations negatively significantly influence the growth of labor force.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable environmental regulations and growth of debt is equal 0.0054. Regressing growth of debt on environmental regulations we receive the equation Growth of debt = Environmental regulations * 0.23 + 9.38, which was built on 1,631 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.83 (>0.1). However, the intercept is significant at 1% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X falls only from 0.83 to 0.23). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample environmental regulations neutrally influence the growth of debt.Therefore, our null hypothesis was rejected in this case.
 
Fire regulations as the measure of control and their influence on performance of companies (the sample of all companies of emergent countries)
Considering the fire regulations as the obstacle, companies on average estimated its value as 1.94 on the scale from 1 to 4. The lowest extent of the problem is observed in Romania where the value of this variable is equal 1.51. In Mexico, this problem is more significant than in other countries and the value of the variable is equal 2.46. The strongest linear relationship between fire regulations and performance is demonstrated for the pair of fire regulations and growth of investment (coefficient of correlation is equal -0.05561), while the pair of fire regulations and the growth of debt is characterized by the lowest correlation (the corresponding coefficient is equal -0.00362). In general, it also should be noted that fire regulations is more serious problem for big enterprises (mean score is equal 1.94) than for small enterprises (mean score is equal 1.86), while for medium companies (mean score is equal 2.02) this obstacle is more significant than for both small companies and big companies. Below, we consider the influence of fire regulations on all five measures of performance.
The coefficient of correlation between the variable fire regulations and growth of sales is equal -0.024. Regressing growth of sales on fire regulations we receive the equation Growth of sales = Fire regulations * (-1.02) + 7.34, which was built on 2,803 observations. Adjusted R-square for this regression is equal 0.00023 and explanatory variable is not significant because its p-value is equal 0.2 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X grows from 0.2 to 0.93). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample fire regulations neutrally influence the growth of sales.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable fire regulations and growth of investment is equal -0.05561. Regressing growth of investment on fire regulations we receive the equation Growth of investment = Fire regulations * (-2.63) + 19.51, which was built on 1,955 observations. Adjusted R-square for this regression is equal 0.0026 and explanatory variable is significant at 5% level because its p-value is equal 0.014 (<0.05). Moreover, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X^2 is equal 0.24). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample fire regulations negatively significantly influence the growth of investment.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable fire regulations and growth of export is equal -0.03514. Regressing growth of export on fire regulations we receive the equation Growth of export = Fire regulations * (-1.82) + 10.5, which was built on 841 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.31 (>0.1). However, the intercept is significant at 1%. The adding of quadratic form of relationship does not improve the quality of the model (p-value of the coefficient near X falls only from 0.31 to 0.24). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample fire regulations neutrally influence the growth of export.Therefore, our null hypothesis was rejected in this case.
The coefficient of correlation between the variable fire regulations and growth of labor force is equal -0.05437. Regressing growth of labor force on fire regulations we receive the equation Growth of labor force = Fire regulations * (-2.08) + 3.04, which was built on 2,295 observations. Adjusted R-square for this regression is equal 0.0025 and explanatory variable is significant at 1% level because its p-value is equal 0.009 (<0.01). Moreover, the intercept is significant at 10% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X grows from 0.009 to 0.944). Therefore, the linear relationship is optimal in this case. Our results show that for the whole sample fire regulations negatively significantly influence the growth of labor force.Therefore, our null hypothesis was confirmed in this case.
The coefficient of correlation between the variable fire regulations and growth of debt is equal -0.00362. Regressing growth of debt on fire regulations we receive the equation Growth of debt = Fire regulations * (-0.16) + 10.26, which was built on 1,657 observations. Adjusted R-square for this regression is equal around 0.0000 and explanatory variable is not significant because its p-value is equal 0.88 (>0.1). However, the intercept is significant at 1% level. The adding of quadratic form of relationship does not improve the quality of the model (p-value near X falls only from 0.88 to 0.4). Therefore, we cannot approve the presence of relationship in this case. Our results show that for the whole sample fire regulations neutrally influence the growth of debt.Therefore, our null hypothesis was rejected in this case.
 
Regulations as the measure of control and their influence on growth of sales of Russian companies
Basing on 350 observations, we build the regression equation for the influence of business regulations on the growth of sales of Russian companies. The received formula can be represented as Growth of Sales = Business Regulations * (-2.58) + 13.07 and its adjusted R-square is equal 0.002. P-values for the coefficient of independent variable and intercept are equal 0.2 and 0.011 respectively. Therefore, the independent variable is not significant (0.2>0.1), while the intercept is significant at 5% level (0.011<0.05). The coefficient of correlation between two variables is equal -0.069. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.2 to 0.61. Referencing the received results, we can consider the influence of business regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 258 observations, we build the regression equation for the influence of customs regulations on the growth of sales of Russian companies. The received formula can be represented as Growth of Sales = Customs regulations * (-3.26) + 16.56 and its adjusted R-square is equal 0.003. P-values for the coefficient of independent variable and intercept are equal 0.18 and 0.002 respectively. Therefore, the independent variable is not significant (0.18>0.1), while the intercept is significant at 1% level (0.002<0.01). The coefficient of correlation between two variables is equal -0.084. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X^2 is equal 0.13. Referencing the received results, we can consider the influence of customs regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 353 observations, we build the regression equation for the influence of labor regulations on the growth of sales of Russian companies. The received formula can be represented as Growth of Sales = Labor regulations * (-2.03) + 11.22 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.45 and 0.026 respectively. Therefore, the independent variable is not significant (0.45>0.1), while the intercept is significant at 5% level (0.026<0.05). The coefficient of correlation between two variables is equal -0.04. The using of quadratic form of the independent variable significantly improves the quality of the regression. New formula can be represented as Growth of Sales = Labor regulations * (-28.4) + Labor regulations * Labor regulations * 6.13 + 33.46 and its adjusted R-square is equal 0.007. P-values of coefficients near X and X^2 are equal 0.034 and 0.044 respectively. Therefore, both variables are significant at 5% level (0.034<0.05 and 0.044<0.05). The intercept is significant at 1% level (0.006<0.01). Therefore, the parabolic relationship exists between labor regulations and the growth of sales. As we see, our null hypothesis was rejected in this case.
Basing on 258 observations, we build the regression equation for the influence of foreign exchange regulations on the growth of sales of Russian companies. The received formula can be represented as Growth of Sales = Foreign exchange regulations * (0.06) + 10.43 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.98 and 0.07 respectively. Therefore, the independent variable is not significant (0.98>0.1), while the intercept is significant at 10% level (0.07<0.1). The coefficient of correlation between two variables is equal 0.0014. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.98 to 0.4. Referencing the received results, we can consider the influence of foreign exchange regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 341 observations, we build the regression equation for the influence of environmental regulations on the growth of sales of Russian companies. The received formula can be represented as Growth of Sales = Environmental regulations * (-4.7) + 16.69 and its adjusted R-square is equal 0.008. P-values for the coefficient of independent variable and intercept are equal 0.054 and 0.002 respectively. Therefore, the independent variable is significant at 10% level (0.054<0.1), while the intercept is significant at 1% level (0.002<0.01). The coefficient of correlation between two variables is equal -0.105. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls grows from 0.054 to 0.31. Referencing the received results, we can consider the influence of environmental regulations on the growth of sales as negative and significant.Therefore, our null hypothesis was confirmed in this case.
Basing on 354 observations, we build the regression equation for the influence of fire regulations on the growth of sales of Russian companies. The received formula can be represented as Growth of Sales = Fire regulations * (-2.59) + 12.5 and its adjusted R-square is equal 0.0004. P-values for the coefficient of independent variable and intercept are equal 0.28 and 0.016 respectively. Therefore, the independent variable is not significant (0.28>0.1), while the intercept is significant at 5% level (0.016<0.05). The coefficient of correlation between two variables is equal -0.057. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.28 to 0.85. Referencing the received results, we can consider the influence of fire regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
 
Regulations as the measure of control and their influence on growth of sales of Indian companies
Basing on 139 observations, we build the regression equation for the influence of business regulations on the growth of sales of Indian companies. The received formula can be represented as Growth of Sales = Business Regulations * 3.29 + 4.92 and its adjusted R-square is equal 0.01. P-values for the coefficient of independent variable and intercept are equal 0.11 and 0.28 respectively. Therefore, the independent variable is not significant (0.28>0.1), as well as the intercept (0.11>0.1). The coefficient of correlation between two variables is equal 0.135. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the intercept is equal 0.19. Referencing the received results, we can consider the influence of business regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 133 observations, we build the regression equation for the influence of customs regulations on the growth of sales of Indian companies. The received formula can be represented as Growth of Sales = Customs regulations * (-1.61) + 14.95 and its adjusted R-square is equal around 0.00. P-values for the coefficient of independent variable and intercept are equal 0.48 and 0.02 respectively. Therefore, the independent variable is not significant (0.48>0.1), while the intercept is significant at 5% level (0.02<0.05). The coefficient of correlation between two variables is equal -0.061. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X^2 is equal 0.12. Referencing the received results, we can consider the influence of customs regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 144 observations, we build the regression equation for the influence of labor regulations on the growth of sales of Indian companies. The received formula can be represented as Growth of Sales = Labor regulations * (-3.42) + 22.29 and its adjusted R-square is equal 0.01. P-values for the coefficient of independent variable and intercept are equal 0.12 and 0.001 respectively. Therefore, the independent variable is not significant (0.12>0.1), while the intercept is significant at 1% level (0.001<0.01). The coefficient of correlation between two variables is equal -0.13. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.12 to 0.39. Referencing the received results, we can consider the influence of labor regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 135 observations, we build the regression equation for the influence of foreign exchange regulations on the growth of sales of Indian companies. The received formula can be represented as Growth of Sales = Foreign exchange regulations * (0.017) + 10.48 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.99 and 0.06 respectively. Therefore, the independent variable is not significant (0.99>0.1), while the intercept is significant at 10% level (0.06<0.1). The coefficient of correlation between two variables is equal 0.0006. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.99 to 0.6. Referencing the received results, we can consider the influence of foreign exchange regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 134 observations, we build the regression equation for the influence of environmental regulations on the growth of sales of Indian companies. The received formula can be represented as Growth of Sales = Environmental regulations * (-2.45) + 17.4 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.33 and 0.006 respectively. Therefore, the independent variable is not significant (0.33>0.1), while the intercept is significant at 1% level (0.006<0.01). The coefficient of correlation between two variables is equal -0.09. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls grows from 0.33 to 0.91. Referencing the received results, we can consider the influence of environmental regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 135 observations, we build the regression equation for the influence of fire regulations on the growth of sales of Indian companies. The received formula can be represented as Growth of Sales = Fire regulations * (4.54) + 3.84 and its adjusted R-square is equal 0.012. P-values for the coefficient of independent variable and intercept are equal 0.11 and 0.5 respectively. Therefore, the independent variable is not significant (0.11>0.1), as well as the intercept (0.5>0.1). The coefficient of correlation between two variables is equal 0.14. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.11 to 0.57. Referencing the received results, we can consider the influence of fire regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
 
Regulations as the measure of control and their influence on growth of sales of Brazilian companies
Basing on 144 observations, we build the regression equation for the influence of business regulations on the growth of sales of Brazilian companies. The received formula can be represented as Growth of Sales = Business Regulations * (-4.02) + 13.24 and its adjusted R-square is equal 0.006. P-values for the coefficient of independent variable and intercept are equal 0.18 and 0.13 respectively. Therefore, the independent variable is not significant (0.18>0.1), as well as the intercept (0.13>0.1). The coefficient of correlation between two variables is equal -0.11. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.18 to 0.94. Referencing the received results, we can consider the influence of business regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 134 observations, we build the regression equation for the influence of customs regulations on the growth of sales of Brazilian companies. The received formula can be represented as Growth of Sales = Customs regulations * (-1.08) + 5.91 and its adjusted R-square is equal around 0.00. P-values for the coefficient of independent variable and intercept are equal 0.7 and 0.46 respectively. Therefore, the independent variable is not significant (0.7>0.1), as well as the intercept (0.46>0.1). The coefficient of correlation between two variables is equal -0.033. The using of quadratic form of the independent variable significantly improves the quality of the regression. New formula can be represented as Growth of Sales = Customs regulations * (-34.8) + Customs regulations * Customs regulations * 6.85 + 37.87 and its adjusted R-square is equal 0.018. P-values of coefficients near X and X^2 are equal 0.037 and 0.04 respectively. Therefore, both variables are significant at 5% level (0.037<0.05 and 0.04<0.05). The intercept is significant at 5% level (0.031<0.05). Therefore, the parabolic relationship exists between customs regulations and the growth of sales. As we see, our null hypothesis was rejected in this case.
Basing on 148 observations, we build the regression equation for the influence of labor regulations on the growth of sales of Brazilian companies. The received formula can be represented as Growth of Sales = Labor regulations * (-4.31) + 17.66 and its adjusted R-square is equal 0.002. P-values for the coefficient of independent variable and intercept are equal 0.26 and 0.2 respectively. Therefore, the independent variable is not significant (0.26>0.1), as well as the intercept (0.2>0.1). The coefficient of correlation between two variables is equal -0.09. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.26 to 0.87. Referencing the received results, we can consider the influence of labor regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 137 observations, we build the regression equation for the influence of foreign exchange regulations on the growth of sales of Brazilian companies. The received formula can be represented as Growth of Sales = Foreign exchange regulations * (-6.52) + 19.68 and its adjusted R-square is equal 0.026. P-values for the coefficient of independent variable and intercept are equal 0.034 and 0.02 respectively. Therefore, the independent variable is significant at 5% level (0.034<0.05), as well as the intercept (0.02<0.05). The coefficient of correlation between two variables is equal -0.18. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.034 to 0.16. Referencing the received results, we can consider the influence of foreign exchange regulations on the growth of sales as negative and significant. Therefore, our null hypothesis was confirmed in this case.
Basing on 147 observations, we build the regression equation for the influence of environmental regulations on the growth of sales of Brazilian companies. The received formula can be represented as Growth of Sales = Environmental regulations * (-2.96) + 9.38 and its adjusted R-square is equal around 0.0014. P-values for the coefficient of independent variable and intercept are equal 0.27 and 0.19 respectively. Therefore, the independent variable is not significant (0.27>0.1), as well as the intercept (0.19>0.1). The coefficient of correlation between two variables is equal -0.09. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls grows from 0.27 to 0.94. Referencing the received results, we can consider the influence of environmental regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 147 observations, we build the regression equation for the influence of fire regulations on the growth of sales of Brazilian companies. The received formula can be represented as Growth of Sales = Fire regulations * (-6.08) + 16 and its adjusted R-square is equal 0.018. P-values for the coefficient of independent variable and intercept are equal 0.055 and 0.04 respectively. Therefore, the independent variable is significant at 10% level (0.055<0.1), while the intercept is significant at 5% level (0.04<0.05). The coefficient of correlation between two variables is equal -0.16. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.055 to 0.18. Referencing the received results, we can consider the influence of fire regulations on the growth of sales as negative and significant.Therefore, our null hypothesis was confirmed in this case.
 
Regulations as the measure of control and their influence on growth of sales of manufacturing companies in emergent countries
Basing on 1,123 observations, we build the regression equation for the influence of business regulations on the growth of sales of manufacturing companies. The received formula can be represented as Growth of Sales = Business Regulations * (-1.71) + 7.67 and its adjusted R-square is equal 0.0015. P-values for the coefficient of independent variable and intercept are equal 0.104 and 0.002 respectively. Therefore, the independent variable is not significant (0.104>0.1), while the intercept is significant at 1% level (0.002<0.01). The coefficient of correlation between two variables is equal -0.05. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.104 to 0.56. Referencing the received results, we can consider the influence of business regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 1,056 observations, we build the regression equation for the influence of customs regulations on the growth of sales of manufacturing companies. The received formula can be represented as Growth of Sales = Customs regulations * 0.41 + 4.23 and its adjusted R-square is equal around 0.00. P-values for the coefficient of independent variable and intercept are equal 0.7 and 0.12 respectively. Therefore, the independent variable is not significant (0.7>0.1), as well as the intercept (0.12>0.1). The coefficient of correlation between two variables is equal 0.012. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.7 to 0.41. Referencing the received results, we can consider the influence of customs regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 1,149 observations, we build the regression equation for the influence of labor regulations on the growth of sales of manufacturing companies. The received formula can be represented as Growth of Sales = Labor regulations * (-0.26) + 5.07 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.8 and 0.06 respectively. Therefore, the independent variable is not significant (0.8>0.1), while the intercept is significant at 10% level (0.06<0.1). The coefficient of correlation between two variables is equal -0.007. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.8 to 0.37. Referencing the received results, we can consider the influence of labor regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 1,074 observations, we build the regression equation for the influence of foreign exchange regulations on the growth of sales of manufacturing companies. The received formula can be represented as Growth of Sales = Foreign exchange regulations * 0.84 + 3.44 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.44 and 0.17 respectively. Therefore, the independent variable is not significant (0.44>0.1), as well as the intercept (0.17>0.1). The coefficient of correlation between two variables is equal 0.02. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.44 to 0.74. Referencing the received results, we can consider the influence of foreign exchange regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 1,116 observations, we build the regression equation for the influence of environmental regulations on the growth of sales of manufacturing companies. The received formula can be represented as Growth of Sales = Environmental regulations * (-1.11) + 7 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.33 and 0.012 respectively. Therefore, the independent variable is not significant (0.33>0.1), while the intercept is significant at 5% level (0.012<0.05). The coefficient of correlation between two variables is equal -0.03. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls grows from 0.33 to 0.95. Referencing the received results, we can consider the influence of environmental regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 1,129 observations, we build the regression equation for the influence of fire regulations on the growth of sales of manufacturing companies. The received formula can be represented as Growth of Sales = Fire regulations * (-0.21) + 4.84 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.87 and 0.07 respectively. Therefore, the independent variable is not significant (0.87>0.1), while the intercept is significant at 10% level (0.07<0.1). The coefficient of correlation between two variables is equal -0.005. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.87 to 0.10004. Referencing the received results, we can consider the influence of fire regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
 
Regulations as the measure of control and their influence on growth of sales of large companies in emergent countries
Basing on 542 observations, we build the regression equation for the influence of business regulations on the growth of sales of large companies. The received formula can be represented as Growth of Sales = Business Regulations * (-0.4) + 13.1 and its adjusted R-square is equal around 0.00. P-values for the coefficient of independent variable and intercept are equal 0.78 and 0.0002 respectively. Therefore, the independent variable is not significant (0.78>0.1), while the intercept is significant at 1% level (0.0002<0.01). The coefficient of correlation between two variables is equal -0.012. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.78 to 0.61. Referencing the received results, we can consider the influence of business regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 516 observations, we build the regression equation for the influence of customs regulations on the growth of sales of large companies. The received formula can be represented as Growth of Sales = Customs regulations * 0.11 + 12.06 and its adjusted R-square is equal around 0.00. P-values for the coefficient of independent variable and intercept are equal 0.94 and 0.002 respectively. Therefore, the independent variable is not significant (0.94>0.1), while the intercept is significant at 1% level (0.002<0.01). The coefficient of correlation between two variables is equal 0.003. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.94 to 0.11. Referencing the received results, we can consider the influence of customs regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 547 observations, we build the regression equation for the influence of labor regulations on the growth of sales of large companies. The received formula can be represented as Growth of Sales = Labor regulations * (-3.04) + 19.9 and its adjusted R-square is equal 0.006. P-values for the coefficient of independent variable and intercept are equal 0.04 and around 0.000 respectively. Therefore, the independent variable is significant at 5% level (0.04<0.05), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.089. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.04 to 0.86. Referencing the received results, we can consider the influence of labor regulations on the growth of sales as negative and significant.Therefore, our null hypothesis was confirmed in this case.
Basing on 521 observations, we build the regression equation for the influence of foreign exchange regulations on the growth of sales of large companies. The received formula can be represented as Growth of Sales = Foreign exchange regulations * 1.92 + 8.15 and its adjusted R-square is equal 0.001. P-values for the coefficient of independent variable and intercept are equal 0.19 and 0.02 respectively. Therefore, the independent variable is not significant (0.19>0.1), while the intercept is significant at 5% level (0.02<0.05). The coefficient of correlation between two variables is equal 0.06. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.19 to 0.76. Referencing the received results, we can consider the influence of foreign exchange regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 532 observations, we build the regression equation for the influence of environmental regulations on the growth of sales of large companies. The received formula can be represented as Growth of Sales = Environmental regulations * 0.19 + 11.57 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.9 and 0.003 respectively. Therefore, the independent variable is not significant (0.9>0.1), while the intercept is significant at 1% level (0.003<0.01). The coefficient of correlation between two variables is equal 0.005. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.9 to 0.26. Referencing the received results, we can consider the influence of environmental regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 533 observations, we build the regression equation for the influence of fire regulations on the growth of sales of large companies. The received formula can be represented as Growth of Sales = Fire regulations * (-0.75) + 13.71 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.67 and 0.0003 respectively. Therefore, the independent variable is not significant (0.67>0.1), while the intercept is significant at 1% level (0.0003<0.01). The coefficient of correlation between two variables is equal -0.018. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.67 to 0.92. Referencing the received results, we can consider the influence of fire regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
 
Regulations as the measure of control and their influence on growth of sales of companies in developed countries (USA, UK, Germany, France, Canada, Sweden, Italy, and Spain)
Basing on 493 observations, we build the regression equation for the influence of business regulations on the growth of sales of companies in developed countries. The received formula can be represented as Growth of Sales = Business Regulations * (-1.33) + 22.8 and its adjusted R-square is equal around 0.00. P-values for the coefficient of independent variable and intercept are equal 0.26 and around 0.000 respectively. Therefore, the independent variable is not significant (0.26>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.05. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.26 to 0.56. Referencing the received results, we can consider the influence of business regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 416 observations, we build the regression equation for the influence of customs regulations on the growth of sales of companies in developed countries. The received formula can be represented as Growth of Sales = Customs regulations * (-1.09) + 22.6 and its adjusted R-square is equal around 0.00. P-values for the coefficient of independent variable and intercept are equal 0.45 and around 0.000 respectively. Therefore, the independent variable is not significant (0.45>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.04. The using of quadratic form of the independent variable significantly improves the quality of the regression. New formula can be represented as Growth of Sales = Customs regulations * (-15.4) + Customs regulations * Customs regulations * 3.18 + 35.4 and its adjusted R-square is equal 0.006. P-values of coefficients near X and X^2 are equal 0.039 and 0.0504 respectively. Therefore, X and X^2 are significant at 5% level (0.039<0.05) and 10% level (0.0504<0.1) respectively. The intercept is significant at 1% level (0.000<0.01). Therefore, the parabolic relationship exists between customs regulations and the growth of sales. As we see, our null hypothesis was rejected in this case.
Basing on 529 observations, we build the regression equation for the influence of labor regulations on the growth of sales of companies in developed countries. The received formula can be represented as Growth of Sales = Labor regulations * (-0.16) + 19.95 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.89 and around 0.000 respectively. Therefore, the independent variable is not significant (0.89>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.006. The using of quadratic form of the independent variable significantly improves the quality of the regression. New formula can be represented as Growth of Sales = Labor regulations * (-12.1) + Labor regulations * Labor regulations * 2.37 + 32.4 and its adjusted R-square is equal 0.003. P-values of coefficients near X and X^2 are equal 0.058 and 0.057 respectively. Therefore, both variables are significant at 10% level (0.058<0.1 and 0.057<0.1). The intercept is significant at 1% level (0.000<0.01). Therefore, the parabolic relationship exists between labor regulations and the growth of sales. As we see, our null hypothesis was rejected in this case.
Basing on 457 observations, we build the regression equation for the influence of foreign exchange regulations on the growth of sales of companies in developed countries. The received formula can be represented as Growth of Sales = Foreign exchange regulations * (-2.46) + 24.85 and its adjusted R-square is equal 0.004. P-values for the coefficient of independent variable and intercept are equal 0.096 and around 0.000 respectively. Therefore, the independent variable is significant at 10% level (0.096<0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.08. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X^2 is equal 0.13. Referencing the received results, we can consider the influence of foreign exchange regulations on the growth of sales as negative and significant. Therefore, our null hypothesis was confirmed in this case.
Basing on 504 observations, we build the regression equation for the influence of environmental regulations on the growth of sales of companies in developed countries. The received formula can be represented as Growth of Sales = Environmental regulations * (-2.05) + 24.45 and its adjusted R-square is equal around 0.004. P-values for the coefficient of independent variable and intercept are equal 0.09 and around 0.000 respectively. Therefore, the independent variable is significant at 10% level (0.09<0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.08. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.09 to 0.67. Referencing the received results, we can consider the influence of environmental regulations on the growth of sales as negative and significant. Therefore, our null hypothesis was confirmed in this case.
Basing on 527 observations, we build the regression equation for the influence of fire regulations on the growth of sales of companies in developed countries. The received formula can be represented as Growth of Sales = Fire regulations * (-1.62) + 22.94 and its adjusted R-square is equal around 0.001. P-values for the coefficient of independent variable and intercept are equal 0.2 and around 0.000 respectively. Therefore, the independent variable is not significant (0.2>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.06. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.2 to 0.75. Referencing the received results, we can consider the influence of fire regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
 
Regulations as the measure of control and their influence on growth of sales of companies in different countries (84 countries)
Basing on 6,565 observations, we build the regression equation for the influence of business regulations on the growth of sales of companies. The received formula can be represented as Growth of Sales = Business Regulations * (-0.95) + 10.2 and its adjusted R-square is equal around 0.0006. P-values for the coefficient of independent variable and intercept are equal 0.02 and around 0.000 respectively. Therefore, the independent variable is significant at 5% level (0.02<0.05), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.028. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.02 to 0.21. Referencing the received results, we can consider the influence of business regulations on the growth of sales as negative and significant.Therefore, our null hypothesis was confirmed in this case.
Basing on 5,957 observations, we build the regression equation for the influence of customs regulations on the growth of sales of companies. The received formula can be represented as Growth of Sales = Customs regulations * (-0.04) + 9.06 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.92 and around 0.000 respectively. Therefore, the independent variable is not significant (0.92>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.001. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the intercept grows from 0.000 to 0.25. Referencing the received results, we can consider the influence of customs regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 6,635 observations, we build the regression equation for the influence of labor regulations on the growth of sales of companies. The received formula can be represented as Growth of Sales = Labor regulations * 0.55 + 7.13 and its adjusted R-square is equal 0.0001. P-values for the coefficient of independent variable and intercept are equal 0.2 and around 0.000 respectively. Therefore, the independent variable is not significant (0.2>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal 0.016. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the intercept grows from 0.000 to 0.84. Referencing the received results, we can consider the influence of labor regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 6,201 observations, we build the regression equation for the influence of foreign exchange regulations on the growth of sales of companies. The received formula can be represented as Growth of Sales = Foreign exchange regulations * (-0.09) + 9.06 and its adjusted R-square is equal around 0.000. P-values for the coefficient of independent variable and intercept are equal 0.84 and around 0.000 respectively. Therefore, the independent variable is not significant (0.84>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.003. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X falls only from 0.84 to 0.75. Referencing the received results, we can consider the influence of foreign exchange regulations on the growth of sales as neutral. Therefore, our null hypothesis was rejected in this case.
Basing on 6,462 observations, we build the regression equation for the influence of environmental regulations on the growth of sales of companies. The received formula can be represented as Growth of Sales = Environmental regulations * (-0.74) + 9.74 and its adjusted R-square is equal 0.0002. P-values for the coefficient of independent variable and intercept are equal 0.106 and around 0.000 respectively. Therefore, the independent variable is not significant (0.106>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.02. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.106 to 0.56. Referencing the received results, we can consider the influence of environmental regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
Basing on 6,585 observations, we build the regression equation for the influence of fire regulations on the growth of sales of companies. The received formula can be represented as Growth of Sales = Fire regulations * (-0.66) + 9.37 and its adjusted R-square is equal 0.0001. P-values for the coefficient of independent variable and intercept are equal 0.17 and around 0.000 respectively. Therefore, the independent variable is not significant (0.17>0.1), while the intercept is significant at 1% level (0.000<0.01). The coefficient of correlation between two variables is equal -0.017. The using of quadratic form of the independent variable does not improve the quality of the regression. P-value of the coefficient near X grows from 0.17 to 0.61. Referencing the received results, we can consider the influence of fire regulations on the growth of sales as neutral.Therefore, our null hypothesis was rejected in this case.
 
Discussion and conclusion
Our results show that in emergent countries, the influence of business regulations on the growth of sales, export, and investment is negative and significant, while there is no influence on the growth of labor force and debt. Customs regulations and foreign exchange regulations influence significantly only on the growth of investment and this impact is negative. The influence of these regulations on other indexes of performance is neutral. Labor regulations expectedly negatively influence the growth of labor force and this impact is significant. Moreover, they also negatively significantly influence the growth of debt and it does not correspond with our hypothesis. The influence on other indexes of performance is neutral. Environmental and fire regulations demonstrate the negative significant impact on the growth of investment and labor force, while the influence on the other performance indexes is neutral. We do not observe the quadratic relationship between regulations and performance in emergent countries.
The Russian market is characterized by the presence of the parabolic relationship between labor regulations and growth of sales of companies. Also, the negative significant impact is produced by the environmental regulations. Other regulations do not generate the impact on the growth of sales.
Indian market is characterized by the absence of influence of regulations on the growth of sales. We tell about both linear impact and quadratic impact.
We have detected that fire regulations and foreign exchange regulations negatively significantly influence the growth of performance in the Brazilian market. The relationship between the growth of sales and customs regulations is described by the parabolic form. The influence of other regulations is not observed.
It is interesting but the growth of sales of manufacturing companies in emergent markets is not influenced by any regulations. We again tell about both linear impact and quadratic impact.
The growth of sales of large companies from emergent markets is also resistant to the impact of regulations. Only labor regulations influence it significantly and this impact is negative.
Making the comparison with developed markets, we can note that both foreign exchange regulations and environmental regulations negatively significantly influence the growth of sales. Moreover, the impact of customs regulations and labor regulations is described by the parabolic form. Other regulations do not demonstrate any impact.
Finally, the including of all types of markets in the sample makes the influence of the most of regulations not significant. Only business regulations negatively significantly influence the growth of sales in this case.
 
 
References
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