Starting from the fact that the metallurgical industry is the main supplier of raw material both for the equipment and machines industry, as well as for the car industry, this paper analyses, by means of the regression function, to what extent the quantity of casting of steel was influenced, on the one hand by the manufacture of machines and equipment, and on the other hand, by the manufacture of car body. Data subject to the study were related to the period January 2002 – June 2016 (174 months) and was conducted both at the level of the European Union, as well as at the level of the main countries manufacturing steel at its level, namely: Germany, Italy, France and Spain

A.V. Todoruț

G. Bușan

I.E. Chirtoc

L. Paliu-Popa

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Interdependence between the steel castings and manufacture of machines and equipment

I. E. Chirtoc

A. V. Todoruț

Hrčak - Portal of scientific journals of Croatia

252  METALURGIJA 56 (2017) 1-2, 252-254L. PALIU-POPA, I.E. CHIRTOC, G. BUȘAN, A.V. TODORUȚINTERDEPENDENCE BETWEEN THE STEEL CASTINGS AND MANUFACTURE OF MACHINES AND EQUIPMENTReceived – Primljeno: 2016-05-07Accepted – Prihvaćeno: 2016-09-25Review Paper – Pregledni radL. Paliu-Popa, I.E. Chirtoc, G. Busan, “Constantin Brancusi” Uni-versity of Targu Jiu, Faculty of  Economics, Targu Jiu, Romania, A.V. Todoruţ, “Constantin Brancusi” University of Targu Jiu, Faculty of Education Science and Public Management, Targu JiuStarting from the fact that the metallurgical industry is the main supplier of raw material both for the equipment and machines industry, as well as for the car industry, this paper analyses, by means of the regression function, to what extent the quantity of casting of steel was influenced, on the one hand by the manufacture of machines and equipment, and on the other hand, by the manufacture of car body. Data subject to the study were related to the period January 2002 – June 2016 (174 months) and was conducted both at the level of the European Union, as well as at the level of the main countries manufacturing steel at its level, namely: Germany, Italy, France and Spain. Key words: metallurgical industry, steel casting, manufacture, machines and equipment.   INTRODUCTION Nowadays, steel is one of the most important mate-rials in the world, almost everything around us being made of steel. It is used for building roads, railways, buildings, bridges, pipes for gas, water and sanitation, but also for building fabrics, machines and not only [1]. According to the conducted studies, averagely, 900 kg of steel are used for building a vehicle and the total quantity annu-ally used by the automobiles segment is of about 80 million tons of steel [2]. In this context, the research purpose is to establish the interdependence between the achieved quantity of cast steel and the manufacture of equipment and ma-chines, but also cars bodies, trailers and semi-trailers, both for the main steel manufacturing countries within the European Union (EU), and for UE.USED METHOD AND DATA BASISThe conducted study aimed the period January 2002 – June 2016, and data subject to the research were taken from the data basis Eurostat [3], building influence pat-terns specific for the four analyzed countries (Germany, Italy, France and Spain), but also for EU [4], by means of the regression function [5]. The analysis includes, for each analyzed subject, a number of 174 observations, the used data being monthly taken and are expressed in value indices whose reference value is the year 2010 [3]. Data were processed using the software IBM SPSS [6]. The patterns’ building has been started from the evo-lution of the indices concerning the quantity of cast ISSN 0543-5846METABK 56(1-2) 252-254 (2017)UDC – UDK 669.015:669.18.17:339.21:65.011.4 = 111steel (ICS), the machines and equipment manufacture indices (IME) and the car bodies manufacture (coach-work) for motor vehicles, trailers and semi-trailers (IBV), for each pattern the dependent variable being ICS and the independent variables (Vi): IME and IBV. Additionally, before building the pattern it has been verified if between the independent variables there is collinearity for each country separately and EU, reason for which it is calculated the factor of the variation in-flation (VIF) for each of the two independent variables IME and IBV (Table 1). Table 1 Establishing VIF / 2002 – 2016* [2]Country VIF Country VIFGermany 2,086 France 4,172Italy 4,209 Spain 3,964EU 2,269Legend: 2016* - date for the first six monthsThe VIF value lower than 5 indicates that IME and IBV are not are not influencing each other, reason for which the two independent variables may be included together in the project. The genera form of the proposed pattern, from which the analysis starts, is the following:  ICSi = β0 + β1 IMEi + β2 IBVi (1)where β0, β1, β2 are the pattern coefficients, i – the value of the variables at the moment t. TESTING THE VALIDITY OF PATTERNS INCLUDING THE VARIABLES ISC, IME AND IBVFor testing the validity of patterns, it will be calcu-lated the value of the parameters and of the random variable and tested the statistical power, choosing a con-fidence level α = 0,05. Thus, it will be calculated the statistical coefficients (Cs), represented by the simple correlation coefficient (R) and the coefficient of deter-253L. PALIU-POPA et al.: INTERDEPENDENCE BETWEEN THE STEEL CASTINGS AND MANUFACTURE OF MACHINES...METALURGIJA 56 (2017) 1-2, 252-254mination (R2) for the pattern related to each country, for calculating percentage with which IME and IBV influ-ence ICS (Table 2). From the analysis of the data it re-sult that R has, for each built pattern, a value of over 0,50, meaning that there is a strong relation between the dependent variable ICS and the independent IME and IBV. In case of Spain is good relation between the de-pendent variable because R is under 0,50.Table 2 Regression statistics / 2002 – 2016* [2] Cs Value Germany Italy France Spain EUR 0,741 0,867 0,873 0,436 0,782R2 0,549 0,751 0,762 0,190 0,612Legend: 2016* - date for the first six monthsBut, deeply analyzing the relation between these variables by means of the coefficient R2, it may state that during the period January 2002 – June 2016 in EU 61,2 % of the quantity of cast steel was influenced by the manufacture of machines and equipment and by the manufacture of car bodies, trailers and semi-trailers. Among the analyzed countries the greatest influence was registered in France where the percentage was of 76,2 %, followed by Italy with 75,1 %, Germany with 54,9 % and Spain with 19,0 %. The value of the stand-ard error calculated using the application IBM SPSS [6], for each of the built patterns is of 12,257 for the European Union, 11,177 for Germany, of 17,043 for France, of 15,287 at the level of Italy and of 23,402 for the Spain pattern. In order to test the patterns using the F test (F) the analysis based on the ANOVA table shall be used (Table 3). Table 3 Analysis using F test / 2002 – 2016* [2]Country Fv Country FvGermany 103,981 France 273,396Italy 258,064 Spain 20,064EU 134,838Legend: 2016* - date for the first six monthsThus, from the analysis of the results obtained after using the F test, correlated with the possible critical value of F (Fcv) which is 3,0479 (value taken from the Table of F Function), it may be said that the Fcv is smaller than calculated value of F (Fv).  It result that the null hypothesis is rejected in the favor of the alternative one for each country separately and for EU. Addition-ally, the proposed model may be tested (Table 4) by means of a student t test (t).Table 4 Analysis using t test / 2002 – 2016* [2]Vi Value tGermany Italy France Spain EUIME 2,294 11,792 3,607 2,987 4,315IBV 8,202 – 0,831 8,166 0,222 7,292Legend: 2016* - date for the first six monthsFrom the comparison of the calculated values (t) in the Table 4 for the t test with the critical values of this indicator is 1,6537 taken from the t distribution tables, it results that for EU the calculated values of the test area greater than the critical value, resulting that the pattern is different from the null value and, therefore, it may be used for establishing ICS knowing IME and IBV. The same may be noticed for Germany and France, but, in case of Italy and Spain one of the parameters of the independent variables has the value smaller than the critical value, resulting that the null hypothesis in their situation may not be accepted, but it shall notice that the parameter of the other indicator is greater and, there-fore, the two patterns are different from the null value. For verifying the hypothesis of errors independency it will be calculated the value of the Durbin-Watson variable (DW), date being presented in Table 5. Table 5 Analysis using DW / 2002 – 2016* [2]Country DW Country DWGermany 1,068 France 0,695Italy 1,493 Spain 1,523EU 1,138Legend: 2016* - date for the first six monthsThe obtained values shall be compared with the crit-ical values DWlower = 1,72879 and DWupper = 1,77526 taken from the Durbin-Watson distribution ta-ble for n = 174 and k = 3. It may be noticed that the calculated value is lower than DWlower, resulting a positive autocorrelation of errors, and thus, the rejection of the null hypothesis.After testing the patterns it results that they are sta-tistically significant, so the quantity of cast steel is pos-itively influenced both by the machines and equipment manufacture, as well as by the manufacture of cars bod-ies, trailers, semi-trailers, influence which is valid both at the level of EU, as well as at the level of the four ana-lyzed countries. BUILDING PATTERNS SHOWING THE INTERDEPENDENCE BETWEEN ICS, IME AND IBVBased on the equation (1) it will be shown to what extent each indictor (IME and IBV) influences ICS. Thus, further (Table 6) it will be determined the value of the pattern coefficients (C) and the range from which they take values, using the software IBM SPSS [6]. Table 6 Coefficients value / 2002 – 2016* [2]C Germany Italy France Spain EUβ0 38,995 – 6,379 –1,491 51,510 19,880β1 0,187 1,166 0,424 0,423 0,442β2 0,401 – 0,031 0,555 0,015 0,380Legend: 2016* - date for the first six monthsFrom the analysis of the previously calculated coef-ficients it results that both for EU and each country sub-ject to the study, it may build econometric patterns. For Germany, the pattern has the following form: 254L. PALIU-POPA et al.: INTERDEPENDENCE BETWEEN THE STEEL CASTINGS AND MANUFACTURE OF MACHINES... METALURGIJA 56 (2017) 1-2, 252-254 ICS = 38,995 + 0,187 IME + 0,401 IBV (2)From the equation (2) it can be seen that when changing the IME by one unit, ICS shall be changed by 0,187 units, and when changing IBV by one unit, ICS shall be changed by 0,401 units. From the conducted calculations [6], the β1 coefficient related to the IME variable takes values from the range [0,026; 0,348], and β2 coefficient related to the IBV variable takes values from the range [0,304; 0,497]. For Italy, the pattern is:  ICS = – 6,379 + 1,166 IME – 0,031 IBV (3)The equation (3) shows that when changing IME by one unit, ICS shall be changed by 1,166 units, and when changing IBV by one unit, ICS shall be changed by – 0,031 units. The β1 coefficient related to the IME varia-ble takes values from the range [0,971; 1,361], and the β2 coefficient related to the IBV variable takes values from the range [– 0,104; 0,042], according to the calcu-lations made by means of the used software [6]. For France, the built pattern is:  ICS = – 1,491 + 0,424 IME + 0,555 IBV (4)The coefficients related to the equation (4) show that when changing IME by one unit, ICS shall be changed by 0,424 units, and when changing IBV by one unit, ICS shall be changed by 0,555 units. Following the con-ducted calculations [6], the possible values of the pat-tern coefficients belong to the range [0,192; 0,657] for β1 and the range [0,421; 0,690] for β2. The pattern built at the Spain level has the following form:  ICS = 51,510 + 0,423 IME + 0,015 IBV (5) In this situation when changing IME by one unit, ICS shall be changed by 0,423 units, and when chang-ing the IBV by one unit, ICS shall be changed by 0,015 units. The pattern coefficient takes values from the ranges: [0,143; 0,702] for β1 and [– 0,115; 0,145] for β2 [6]. For EU, the built pattern is:  ICS = 19,880 + 0,442 IME + 0,380 IBV (6)This time when changing IME by one unit, ICS shall be changed by 0,442 units, and when changing the IBV by one unit, ICS shall be changed by 0,380 units. In this model the IME and IBV coefficients take values from the range [0,240; 0,644] for β1, namely [0,277; 0,482] for β2 [6]. As at least one of the terms is different from 0, it re-sults that the pattern is different from the null value and therefore, it may be used for determining ICS, knowing the value of IME and IBV, both for the four countries subject to the study, as well as at the level of EU. CONCLUSIONS The coefficients value proves in the five cases that there is a strong and positive interdependence between the indices of the cast steel quantity and the indices of the machines and equipment manufacture, but also those of car bodies, trailers, semi-trailers manufacture. After testing the patterns proposed for Germany, Italy, France, Spain and EU, results that they are correct form the econometric point of view, but it shall mention that in reality, not only the requirement of cast steel for the industry of manufacturing machines and equipment, but also for the industry of manufacturing care bodies influ-ences the quantity of cast steel, as there is other indus-tries using the steel. Additionally, it must be taken into account that a part of the steel is designed to the export both to EU countries and to non-EU countries. The pat-terns made for the period January 2002 – June 2016 showed that in Germany, Italy and France over 50 % of the quantity of cast steel was influenced by the manu-facture of machines and equipment and by the manufac-ture of car bodies, trailers and semi-trailers, while in Spain the influence was of only 19 %, and at the level of EU of 61,2 %. At the same time, it must be retained that the patterns are based on data existing a certain period and in a certain space, and the values they shall take in the future are uncertain. BIBLIOGRAPHY [1]  http://www.worldsteel.org, Sustainable steel. At the core of a green economy.[2]  http://www.worldsteel.org/Steel-markets/ Automotive.html – Automotive.[3]   http://ec.europa.eu/eurostat/data/database.[4]  Paliu-Popa L., Impact of the economic and financial crisis on the evolving trend of crude steel consumption, Metalur-gija 55 (2016) 2, 267-270.  [5]   Seber G.A.F., Lee A.J., Linear Regression Analysis, Se-cond Edition, John Wiley & Sons Publication, Canada, New Jersey, 2003, pp. 36.[6]   Arbuckle J.L.,IBM SPSS Amos 19 User’s Guide, Amos Development Corporation, IBM Corporation, USA, Chi-cago, 2010, pp. 221-229. Note:  The responsible translator for English language is A.L. Florea, Craiova, Romania

English

Paliu-Popa, Lucia

Chirtoc, Irina Elena

Busan, Gabriela

Todorut, Amalia Venera

Munich RePEc Personal Archive

Munich Personal RePEc ArchiveInterdependence between the steelcastings and manufacture of machinesand equipmentPaliu-Popa, Lucia and Chirtoc, Irina Elena and Busan,Gabriela and Todorut, Amalia VeneraConstantin Brancusi University of Targu Jiu25 September 2016Online at https://mpra.ub.uni-muenchen.de/87382/MPRA Paper No. 87382, posted 29 Jun 2018 18:41 UTC252  METALURGIJA 56 (2017) 1-2, 252-254L. PALIU-POPA, I.E. CHIRTOC, G. BUȘAN, A.V. TODORUȚINTERDEPENDENCE BETWEEN THE STEEL CASTINGS AND MANUFACTURE OF MACHINES AND EQUIPMENTReceived – Primljeno: 2016-05-07Accepted – Prihvaćeno: 2016-09-25Review Paper – Pregledni radL. Paliu-Popa, I.E. Chirtoc, G. Busan, “Constantin Brancusi” Uni-versity of Targu Jiu, Faculty of  Economics, Targu Jiu, Romania, A.V. Todoruţ, “Constantin Brancusi” University of Targu Jiu, Faculty of Education Science and Public Management, Targu JiuStarting from the fact that the metallurgical industry is the main supplier of raw material both for the equipment and machines industry, as well as for the car industry, this paper analyses, by means of the regression function, to what extent the quantity of casting of steel was influenced, on the one hand by the manufacture of machines and equipment, and on the other hand, by the manufacture of car body. Data subject to the study were related to the period January 2002 – June 2016 (174 months) and was conducted both at the level of the European Union, as well as at the level of the main countries manufacturing steel at its level, namely: Germany, Italy, France and Spain. Key words: metallurgical industry, steel casting, manufacture, machines and equipment.   INTRODUCTION Nowadays, steel is one of the most important mate-rials in the world, almost everything around us being made of steel. It is used for building roads, railways, buildings, bridges, pipes for gas, water and sanitation, but also for building fabrics, machines and not only [1]. According to the conducted studies, averagely, 900 kg of steel are used for building a vehicle and the total quantity annu-ally used by the automobiles segment is of about 80 million tons of steel [2]. In this context, the research purpose is to establish the interdependence between the achieved quantity of cast steel and the manufacture of equipment and ma-chines, but also cars bodies, trailers and semi-trailers, both for the main steel manufacturing countries within the European Union (EU), and for UE.USED METHOD AND DATA BASISThe conducted study aimed the period January 2002 – June 2016, and data subject to the research were taken from the data basis Eurostat [3], building influence pat-terns specific for the four analyzed countries (Germany, Italy, France and Spain), but also for EU [4], by means of the regression function [5]. The analysis includes, for each analyzed subject, a number of 174 observations, the used data being monthly taken and are expressed in value indices whose reference value is the year 2010 [3]. Data were processed using the software IBM SPSS [6]. The patterns’ building has been started from the evo-lution of the indices concerning the quantity of cast ISSN 0543-5846METABK 56(1-2) 252-254 (2017)UDC – UDK 669.015:669.18.17:339.21:65.011.4 = 111steel (ICS), the machines and equipment manufacture indices (IME) and the car bodies manufacture (coach-work) for motor vehicles, trailers and semi-trailers (IBV), for each pattern the dependent variable being ICS and the independent variables (Vi): IME and IBV. Additionally, before building the pattern it has been verified if between the independent variables there is collinearity for each country separately and EU, reason for which it is calculated the factor of the variation in-flation (VIF) for each of the two independent variables IME and IBV (Table 1). Table 1 Establishing VIF / 2002 – 2016* [2]Country VIF Country VIFGermany 2,086 France 4,172Italy 4,209 Spain 3,964EU 2,269Legend: 2016* - date for the first six monthsThe VIF value lower than 5 indicates that IME and IBV are not are not influencing each other, reason for which the two independent variables may be included together in the project. The genera form of the proposed pattern, from which the analysis starts, is the following:  ICSi = β0 + β1 IMEi + β2 IBVi (1)where β0, β1, β2 are the pattern coefficients, i – the value of the variables at the moment t. TESTING THE VALIDITY OF PATTERNS INCLUDING THE VARIABLES ISC, IME AND IBVFor testing the validity of patterns, it will be calcu-lated the value of the parameters and of the random variable and tested the statistical power, choosing a con-fidence level α = 0,05. Thus, it will be calculated the statistical coefficients (Cs), represented by the simple correlation coefficient (R) and the coefficient of deter-253L. PALIU-POPA et al.: INTERDEPENDENCE BETWEEN THE STEEL CASTINGS AND MANUFACTURE OF MACHINES...METALURGIJA 56 (2017) 1-2, 252-254mination (R2) for the pattern related to each country, for calculating percentage with which IME and IBV influ-ence ICS (Table 2). From the analysis of the data it re-sult that R has, for each built pattern, a value of over 0,50, meaning that there is a strong relation between the dependent variable ICS and the independent IME and IBV. In case of Spain is good relation between the de-pendent variable because R is under 0,50.Table 2 Regression statistics / 2002 – 2016* [2] Cs Value Germany Italy France Spain EUR 0,741 0,867 0,873 0,436 0,782R2 0,549 0,751 0,762 0,190 0,612Legend: 2016* - date for the first six monthsBut, deeply analyzing the relation between these variables by means of the coefficient R2, it may state that during the period January 2002 – June 2016 in EU 61,2 % of the quantity of cast steel was influenced by the manufacture of machines and equipment and by the manufacture of car bodies, trailers and semi-trailers. Among the analyzed countries the greatest influence was registered in France where the percentage was of 76,2 %, followed by Italy with 75,1 %, Germany with 54,9 % and Spain with 19,0 %. The value of the stand-ard error calculated using the application IBM SPSS [6], for each of the built patterns is of 12,257 for the European Union, 11,177 for Germany, of 17,043 for France, of 15,287 at the level of Italy and of 23,402 for the Spain pattern. In order to test the patterns using the F test (F) the analysis based on the ANOVA table shall be used (Table 3). Table 3 Analysis using F test / 2002 – 2016* [2]Country Fv Country FvGermany 103,981 France 273,396Italy 258,064 Spain 20,064EU 134,838Legend: 2016* - date for the first six monthsThus, from the analysis of the results obtained after using the F test, correlated with the possible critical value of F (Fcv) which is 3,0479 (value taken from the Table of F Function), it may be said that the Fcv is smaller than calculated value of F (Fv).  It result that the null hypothesis is rejected in the favor of the alternative one for each country separately and for EU. Addition-ally, the proposed model may be tested (Table 4) by means of a student t test (t).Table 4 Analysis using t test / 2002 – 2016* [2]Vi Value tGermany Italy France Spain EUIME 2,294 11,792 3,607 2,987 4,315IBV 8,202 – 0,831 8,166 0,222 7,292Legend: 2016* - date for the first six monthsFrom the comparison of the calculated values (t) in the Table 4 for the t test with the critical values of this indicator is 1,6537 taken from the t distribution tables, it results that for EU the calculated values of the test area greater than the critical value, resulting that the pattern is different from the null value and, therefore, it may be used for establishing ICS knowing IME and IBV. The same may be noticed for Germany and France, but, in case of Italy and Spain one of the parameters of the independent variables has the value smaller than the critical value, resulting that the null hypothesis in their situation may not be accepted, but it shall notice that the parameter of the other indicator is greater and, there-fore, the two patterns are different from the null value. For verifying the hypothesis of errors independency it will be calculated the value of the Durbin-Watson variable (DW), date being presented in Table 5. Table 5 Analysis using DW / 2002 – 2016* [2]Country DW Country DWGermany 1,068 France 0,695Italy 1,493 Spain 1,523EU 1,138Legend: 2016* - date for the first six monthsThe obtained values shall be compared with the crit-ical values DWlower = 1,72879 and DWupper = 1,77526 taken from the Durbin-Watson distribution ta-ble for n = 174 and k = 3. It may be noticed that the calculated value is lower than DWlower, resulting a positive autocorrelation of errors, and thus, the rejection of the null hypothesis.After testing the patterns it results that they are sta-tistically significant, so the quantity of cast steel is pos-itively influenced both by the machines and equipment manufacture, as well as by the manufacture of cars bod-ies, trailers, semi-trailers, influence which is valid both at the level of EU, as well as at the level of the four ana-lyzed countries. BUILDING PATTERNS SHOWING THE INTERDEPENDENCE BETWEEN ICS, IME AND IBVBased on the equation (1) it will be shown to what extent each indictor (IME and IBV) influences ICS. Thus, further (Table 6) it will be determined the value of the pattern coefficients (C) and the range from which they take values, using the software IBM SPSS [6]. Table 6 Coefficients value / 2002 – 2016* [2]C Germany Italy France Spain EUβ038,995 – 6,379 –1,491 51,510 19,880β10,187 1,166 0,424 0,423 0,442β20,401 – 0,031 0,555 0,015 0,380Legend: 2016* - date for the first six monthsFrom the analysis of the previously calculated coef-ficients it results that both for EU and each country sub-ject to the study, it may build econometric patterns. For Germany, the pattern has the following form: 254L. PALIU-POPA et al.: INTERDEPENDENCE BETWEEN THE STEEL CASTINGS AND MANUFACTURE OF MACHINES... METALURGIJA 56 (2017) 1-2, 252-254 ICS = 38,995 + 0,187 IME + 0,401 IBV (2)From the equation (2) it can be seen that when changing the IME by one unit, ICS shall be changed by 0,187 units, and when changing IBV by one unit, ICS shall be changed by 0,401 units. From the conducted calculations [6], the β1 coefficient related to the IME variable takes values from the range [0,026; 0,348], and β2 coefficient related to the IBV variable takes values from the range [0,304; 0,497]. For Italy, the pattern is:  ICS = – 6,379 + 1,166 IME – 0,031 IBV (3)The equation (3) shows that when changing IME by one unit, ICS shall be changed by 1,166 units, and when changing IBV by one unit, ICS shall be changed by – 0,031 units. The β1 coefficient related to the IME varia-ble takes values from the range [0,971; 1,361], and the β2 coefficient related to the IBV variable takes values from the range [– 0,104; 0,042], according to the calcu-lations made by means of the used software [6]. For France, the built pattern is:  ICS = – 1,491 + 0,424 IME + 0,555 IBV (4)The coefficients related to the equation (4) show that when changing IME by one unit, ICS shall be changed by 0,424 units, and when changing IBV by one unit, ICS shall be changed by 0,555 units. Following the con-ducted calculations [6], the possible values of the pat-tern coefficients belong to the range [0,192; 0,657] for β1 and the range [0,421; 0,690] for β2. The pattern built at the Spain level has the following form:  ICS = 51,510 + 0,423 IME + 0,015 IBV (5) In this situation when changing IME by one unit, ICS shall be changed by 0,423 units, and when chang-ing the IBV by one unit, ICS shall be changed by 0,015 units. The pattern coefficient takes values from the ranges: [0,143; 0,702] for β1 and [– 0,115; 0,145] for β2 [6]. For EU, the built pattern is:  ICS = 19,880 + 0,442 IME + 0,380 IBV (6)This time when changing IME by one unit, ICS shall be changed by 0,442 units, and when changing the IBV by one unit, ICS shall be changed by 0,380 units. In this model the IME and IBV coefficients take values from the range [0,240; 0,644] for β1, namely [0,277; 0,482] for β2 [6]. As at least one of the terms is different from 0, it re-sults that the pattern is different from the null value and therefore, it may be used for determining ICS, knowing the value of IME and IBV, both for the four countries subject to the study, as well as at the level of EU. CONCLUSIONS The coefficients value proves in the five cases that there is a strong and positive interdependence between the indices of the cast steel quantity and the indices of the machines and equipment manufacture, but also those of car bodies, trailers, semi-trailers manufacture. After testing the patterns proposed for Germany, Italy, France, Spain and EU, results that they are correct form the econometric point of view, but it shall mention that in reality, not only the requirement of cast steel for the industry of manufacturing machines and equipment, but also for the industry of manufacturing care bodies influ-ences the quantity of cast steel, as there is other indus-tries using the steel. Additionally, it must be taken into account that a part of the steel is designed to the export both to EU countries and to non-EU countries. The pat-terns made for the period January 2002 – June 2016 showed that in Germany, Italy and France over 50 % of the quantity of cast steel was influenced by the manu-facture of machines and equipment and by the manufac-ture of car bodies, trailers and semi-trailers, while in Spain the influence was of only 19 %, and at the level of EU of 61,2 %. At the same time, it must be retained that the patterns are based on data existing a certain period and in a certain space, and the values they shall take in the future are uncertain. BIBLIOGRAPHY [1]  http://www.worldsteel.org, Sustainable steel. At the core of a green economy.[2]  http://www.worldsteel.org/Steel-markets/ Automotive.html – Automotive.[3]   http://ec.europa.eu/eurostat/data/database.[4]  Paliu-Popa L., Impact of the economic and financial crisis on the evolving trend of crude steel consumption, Metalur-gija 55 (2016) 2, 267-270.  [5]   Seber G.A.F., Lee A.J., Linear Regression Analysis, Se-cond Edition, John Wiley & Sons Publication, Canada, New Jersey, 2003, pp. 36.[6]   Arbuckle J.L.,IBM SPSS Amos 19 User’s Guide, Amos Development Corporation, IBM Corporation, USA, Chi-cago, 2010, pp. 221-229. Note:  The responsible translator for English language is A.L. Florea, Craiova, Romania

Interdependence between the steel castings and manufacture of machines and equipment

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