Journal of Business and Economics, ISSN 2155-7950, USA September 2014, Volume 5, No. 9, pp. 1681-1690 DOI: 10.15341/jbe(2155-7950)/09.05.2014/021  Academic Star Publishing Company, 2014 http://www.academicstar.us

Introduction to the Scientific Problem of Econometric Methodology

Karmen Marguč (ECHO, d.o.o., Slovenia)

Abstract: Social disciplines are difficult to attribute the scientificity because they are not based on controlled experiments. Many authors dealt primarily with the technical methods and models for data processing in the past, while the problem of the econometric methodology remained less explored. Today we are facing poor and limited technical discussions in this area. The primary objective of this research is to define as scientific, based on its methodology. Descriptive and comparable findings suggest that econometrics’ origin, based on logical positivism, is a crucial problem for the identification of the econometric methodology as scientific. According to analysis of the econometric methodology and considering philosophical prospective, it cannot be attributed to scientific field. Keywords: econometrics; methodology; scientific theory; positivism JEL code: B410

1. Introduction

Roots of econometrics according to Mary Morgan go back to the year 1699, when Charles Davenant and Gregory King published an article about demand curve (Morgan 1990). Francisco Louca located the origin of econometrics in the year 1933 or at the end of Morgan’s history, and describes it as “the most daring and successful innovation” in the economy of 20th Century (Louca, 2007). According to Louca, Regnar Frisch is the founder of econometrics (1895-1973), whose term “econometrics” did not merely represent naming economic statistics, but formation of a new research field. Econometrics thus represents “economic theory in relation to statistics and math” which should “make uniform… theoretical-quantitative and empirical-quantitative approaches in economy” with “constructive and strict mind, similar to that, which dominates in naturalistic science” (Frisch, 1933, pp. 1-2, see Hoover, 2005). Similar descriptions can be found in introductory parts of various articles and books of econometrics. In Malinavaud’s work Statistical Methods in Econometrics, econometrics is defined as a discipline including “usage of math or statistic methods in researches of economic phenomena” (Malinvaud, 1966). Carl F. Christ’s work Econometrics Models and Methods describes econometrics as “…acquisition of economic affirmations, which are used to describe manners of existing variables or to predict behaviour of variables” (Christ, 1966). Chow defines econometrics “as art and science of statistic method usage and measuring economic relations” (Chow, 1983). Econometrics is therefore a discipline which combines different fields such as: economic models, mathematical statistics and economic data (Hansen, 2010). Econometrics as a term refers to statistical aspects

Karmen Marguc, MA, Project Manager, ECHO; research areas/interests: econometrics, macroeconomics, ecological economics. E-mail: [email protected].

1681 Introduction to the Scientific Problem of Econometric Methodology conditional on economic theory. Nowadays, mathematical and statistical methods in econometrics also include computer science (Pesaran, 1987). With an emphasis on quantitative aspect of economic problems, econometrics calls for “making uniform” the empirical researches with economic theory. On one hand, theory which does not hold empirical measurements only represents primary logic with limited relevance of actual economic problems analysis. On the other hand measurements which do not hold theory, also do not include important bases, on the basis of which statistical observations can be interpreted (Hansen, 2010). We can conclude that neither “theory” nor “measurements” by themselves are sufficient for understanding economic phenomena. Theoretical structure need to be accurate, actual and more complex. In formulation of its abstract entity, theory needs to be based on different techniques of observation. New statistical and other empirical researches represent a healthy element which constantly loads theory and in this manner prevents from grounding it on the basis of obsolete presumptions. As mentioned above, econometric theory deals with development of quantitative economic models, features of econometric methods and use of econometric methods related to economic models and economic data (Hansen, 2010). The essence of econometrics represents systematic meta-study of basic principles, procedures and philosophical presumptions, which ground empirical modelling with the purpose of efficacy assessment of primary goals or as Malinvaud states:“learning based on empirical data of economic phenomena.” (Malinvaud, 1966). In other words; econometrics represents the essence of philosophical economics, which primary deals with epistemological and metaphysical problems, referring to empirical grounds of economy. It is particularly concerned with methodological problems in the field of efficiency and procedure methods, used in empirical researches, as well as ontological problems concerning econometric aspects. Applied econometrics deals with complexity of lacuna between theory and collected empirical data and faces various philosophical-methodological problems referring to transformation of imperfect data to authentic proofs, which serve as aid to hypotheses (Spanos, 2007). According to Granger applied econometrics uses theoretical econometrics and data of the real world for evaluating economic theories, development of econometric models and analyzing economic history and following foreseeing (Granger, 2008). Problem, occurring in standard statistical model, when researching economic questions, lies in standard statistical model itself, because it is general observed datum and not controlled experiment or quasi-experiment. This is the experiment which is not carried out in strict experimental environment, where distractive influences are excluded. Model of observed data is in the field of econometrics similar to researches of other scientific fields like: astronomy, sociology and political science (Wold, 1969). Present research indicates problems occurring in the field of methodology of econometrics. For general understanding the latter, it is necessary to argument whether the econometrics, in the field of economy, is science or has the needed features to be a part of science.

2. Economy as a Science

Based on the question whether economy is science or not developed two poles of representatives. On one hand philosophers deny scientificity of economy, because the essence of economy does not represent scientific experimenting (testing of physical parameters), but scientific method which constantly gives preference over testing hypotheses and theories based on functioning of the latter in the world (Kitanović & Krstić, 2009). Traditionally classical economists only rely on deductive theories, gained on the basis of complex maths (for example: existence of microeconomic axiom about concurrent balance is based on fix point theorems). In accordance to the latter,

1682 Introduction to the Scientific Problem of Econometric Methodology classical economy cannot be described as science of world facts (Sherlock b.l.). Anyhow, it is possible to apply scientific method in the state economic research in the same way as researching gravity and evolution of bodies. Moreover, we can say that exactly scientificity of its method, gives the economy status of science which can not be easily accepted. On the basis of studied literature it is possible to make inferences whether specific discipline is scientific dependent on the definition of science. In order to evaluate scientificity of the economy it is important to study its scientificity on the basis of various philosophical definitions of science. Philosopher Karl Popper believed that the statement is scientific only when it is supported with logical option of mistake. This definition of science, the so called falsification, means valuing scientific statement and checking, when comparing it to the world (Popper, 1959, p. 41). The statement is not scientific if it does not have any chance of risk to be false; in other words—if there is not any way to check the statement against observed facts or happening. Popper named this distinction “line of demarcation”. On the basis of this definition Popper claims that we cannot be certain whether whichever science theory is real. Confirmation of scientific theory means, there is no existent evidence that contradicts it. Despite all that, there is still a possibility of contradiction in the future. For instance we cannot be certain whether the statement “Tomorrow, the sun will rise up in the east” is true only because it is a scientific assertion. It will probably be logical to picture oneself “a sunrise in the west” although we are pretty certain this is not going to happen, despite of previous experiences, which have always been consistent with the assertion. Popper summarizes, the latter does not prove that the statement will never be disproved. He comprehends scientific behaviour as a process of conjunction and disproval. An explanation of defined facts could be based on conjuncture, guessing and the theory of how the facts are related to each other. If the following observations are inconsistent with the theory, it means that the theory is disproved and has to be replaced with the new one or a conjuncture. On the contrary, originally non-scientific explanations will never be disproved and there will never be a need for the change of beliefs. Most of the economists see their discipline as scientific in a Popperian sense of the world. According to the economic theory there are always new facts, which enable testing of theories. The economy constantly proves, whether the facts match with each other and if they are such like, the theory predicts them. According to Nash the econometric methodology was comprehended as dividing line between general economy and scientific method, which means that hypotheses can be empirically tested and based on this, falsified. Because of that they meet the scientific method (Nash, 2007, p. 56). In the field of economy, this procedure is much more complicated than in the field of physical science, because on the contrary to the latter, economists can rarely use controlled experiment, in order to capture all the facts available for testing theories. Besides that, they have to be satisfied with whichever facts available and rely on statistical procedures, based on which the conclusions are carried out. Although statistical data enable some variables to stay constant, with the purpose of observing other variables, they are exposed to various limitations. In case there are present important variables but cannot be measured or are partially measurable, there is a possibility of misleading results gained by statistical method. There is also a chance of failure, especially when there is uncertainty of variables used in testing. One of the advantages of control experiment is the list of variables which should not include all of them. Due to the difficulties which occur when specifying variables, economy faces with contradictions, whether results of statistical analysis prove or disprove the theory. The latter can be present in economy for several years. Spanos claims no economic theory was disproved (based on empirical tests), nor was chosen to be the best among all the concurrent theories (Spanos, 1986, p. 660). That is the reason why some economists do not consider the economy as scientific in Popperian sense. Distinctive proponents of the latter are the representatives of Austrian

1683 Introduction to the Scientific Problem of Econometric Methodology school, who claim the economy originates from a supposition where economic theory is a derivation of specific assumptions. If the theory does not fit to the facts, we cannot conclude the theory is wrong, is just inappropriate to apply it to individual situation, due to the primary conditions, which are not consistent with the assumptions of theory. Well known economist Ludwig Heinrich Edler von Mises (1881-1973) defined science as “any way of a research where objective and systematic knowledge is gained” (Mises, 1956). In his work The Ultimate Foundation of Economic Science he criticizes the econometrics as “... a method of economic analysis, which represents a game with the features, which do not contribute to clear the problem in economic reality” (Mises, 1956, p. 3). In order to improve econometric models, so the changes in economy could be easier to predict, econometrists often use various tricks. Ability to predict each equation in the model is usually evaluated on the basis of actual data. Difference between actual data and data gained, based on the equation is known as an add factor and is included in equation models (Shostak, 2002). Add factor has an influence on the announcement made with econometric model, which enables the author of the model to include a subjective factor that has an influence on the result of the announcement according to his “good feeling”. The latter negatively affects “scientificity” of econometric modelling. Besides that, Mises warns of the data quality, based on which the econometric models are made. He also believes:“... econometric models are nothing but glorified game” (Mises-Shostak, 2002). Such critiques of econometrics cause doubts among economists; which method is appropriate to check specific theories in economy. Pearson (1938) advocates the principle of unified science, according to which the essence of existence lies in scientific method. Ritchie (1923) emphasizes similar aspect than Pearson; the only constant in science is scientific method, meanwhile theories constantly change, procedures used for generating theories are static. Consequently developed a discussion among the economists, whether econometrics supplies the economy with all the important scientific procedures or not and if it provides the discipline with an intellectual legality, we are looking for. Koutsoyiannis (1973) for instance identifies the following steps as main econometric methodology: formulating the existent hypotheses, testing existent hypotheses and evaluation of predictive modelling. The emphasis is on testing the hypotheses in the field of regression analyses as the whole. Koutsoyannis confirms the scientific status of classic economy with the fact that it is capable of maintaining rigorous testing. Koop claims, such testing of hypotheses when the null hypothesis is negated include error of a Straw man and therefore prove statistical significance (Koop, 2005, p. 80). This procedure should be problematic because such statistical significance is not necessarily scientific significance. Popper for instance defines scientific significant effect like the one which could be checked every time and is carried out as corresponding and prescribed experiment (Popper, 1959, p. 23). Based on various researches we can conclude that repetition of empirical researches in economy is not possible (Dewald et al., 1986). That is also the main reason why we cannot understand econometric statistical significance as scientific significant. Basic problem represents the nature of the data in non-experimental discipline, because of which repetition is not possible. Falsification is also not possible; therefore the whole procedure is de-facto non-scientific. The fact, that data retrieved with econometric methods are merely possible to certain extent of certainty, puts the econometrics and the economy in domain, which is not accurate in a way some can attribute it a status of scientific discipline (Nash, 2007, p. 57). Of the four components of the econometrics which are: a priori theories, empirical data, econometric methods and techniques of evaluation the most problematic component is the econometric method, which is also frequently discussed. In order to clarify this position, it is important to search the econometric methodology and procedures itself more analytically.

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3. The Econometric Methodology

Discussion concerning econometric methodology faces with the question whether econometrics is capable of testing hypotheses. In the very beginning of econometrics development, some economists doubted that econometrics can achieve goals of the economy. In order to understand the importance of the econometrics, it is crucial to explain the term “methodology” in the econometrics. History of the econometrics (see: Epstein, 1987; Morgan, 1990; Hendry & Morgan, 1995) is full of methodological discussions. Systematization of methodology is possible to monitor since 1940 up to early fifties by authors like: Haavelmo (1944) and in Cowles Commission (Koopmans, 1950; Hood & Koopmans, 1953). Since 1950 until 1980 econometrists tried to focus on technical development (method) and not on bigger conceptual problems (methodology). Interest in the econometric methodology came back in the following period especially in articles (e.g., Hendry, 1980; Sims, 1980; Leamer, 1983; McAleer, Pagan & Volcker, 1985; Pagan, 1987; Aldrich, 1989; Hoover, 1990, 1994a, b, 1995a, b; Kydland& Prescott, 1991; Spanos, 1995) and books (e.g., Spanos, 1986 and 1999; Darnell & Evans, 1990; Lawson, 1997; Cartwright, 1999; Magnus & Morgan, 1999; Granger, 1999; Keuzenkamp, 2000; Stigum, 2003; Zellner, Keuzenkamp & McAleer, 2001) (as cited in Mills, 2006). The term “methodology” was generally used as a term of “method” in econometrics (Dharmapala & McAleer, 1966). The latter is also the main reason why the field of econometric methodology leads before the discussion of econometric techniques. Primary, econometric methodology was not integrated in philosophical debates (Granger, 2008; Hendry et al., 1980; Leamer, 1988; Pagan, 1987; Spanos, 1986 and 2007), while other social sciences like psychology, sociology or political science dedicated more time to facing the philosophical/methodological problems, which referred to statistical conclusions and modelling. Key exceptions are authors like: Hoover, 2005 and 2007; Keuzenkamp, 2000. Generally, methodology should mean a method research and should have a broader meaning in science of philosophy. Methodology is not a research of definite methods but a meta-study of manners, which contribute to the scientific as whole. Mark Blaug defines economic methodology as:

“...research of the relation between theoretical concepts and defined conclusions of real world; methodology is the part of economy, which explores the manners according to which economy apologises its theories and explains the reasons for favouring one theory or the other” (Blaug, 1992, p. 12 as cited in Keuzenkamp, 1995).

Dharmapala and McAleer (1966) claim that the term “econometric methodology” should be more precisely defined and the taxonomy of econometric methodology should also be presented. The statement written above would represent the basis for further discussions in the field of philosophy science. Pagan described three econometric methodologies: Hendry’s (1980) (LSE) model strategy from basic to specific, Leamer’s (1983) Bayesianski’s approach and vector auto regression model by Sims (1980) (Pagan, 1987). Such classification is also used in some other books for, e.g., Darne and Evans (1990), who added the fourth methodology named cointegration. The described principle of methodology is based on technical procedures (or methods) (Dharmapala & McAleer, 1966). Analysis of cointegration is a technique, which is comparable to other philosophical approaches of econometrics. Meanwhile Darnell and Evans (1990, p. 13) distinguish between methodology and methods (Pagan, 1987), they also did not stick to the definition of the terms therefore it is possible to notice their criticism of “methodology” on the basis of technicalities. As Dharmapala and McAleer (1966) emphasize, the term “methodology” refers to subdiscipline, which deals with the researches of philosophical bases and justifying of

1685 Introduction to the Scientific Problem of Econometric Methodology econometric procedures. With the purpose to avoid this common mistake, we will use a term “methodology” with the meaning of econometric procedures. The econometric methodology is going to be connected with the general field of economic methodology. The role of econometrics in the economic field and its relation with economic theory will be discussed separately. While methodology per se is “distant” from economic theory, econometrics represents main source of proving the theories, which is not only useful in economy but in other fields of science.

4. Logical Positivism

The basis of economy as a science and various approaches of economic methodology represent variants of logical positivism or philosophical school, founded in Wien (1920). The representatives of the latter are: Otto Neurath Feigl, Karl Menger, Kurt Gödel and Rudolph Carnap (Hoover, 2005). The term “positivism” could describe different methodological aspects, developed through history. Generally speaking, positivism refers to philosophy of science, according to which metaphisic aspects are presupposed as non scientific. Kalakowski thinks that “positivism” could be noticed at least in the Middle Ages. David Hume is believed to be the father of positivism who is Adam Smith’s contemporary (Kolakowski, 1972, p. 43 as cited in Alvey, 2005). Representatives of positivism are also: G.E.Moor, Wittgenstein, J.S. Mill, Mach, even Karl Popper (Alvey, 2005). According to Kolawski we can conclude there are five types of positivism, namely:

 specific version (David Hume),

 early broader version (Comte, Mill and others),

 logical positivism named empirical positivism and

 falsificationism (Popper) (Alye, 2005). Present article argues logical positivism, because “positivism” usually stands for logical positivism. Logical positivism is based on physical language (Putnam, 2002, p. 25), which represents the main difference between previous variants of positivism. Most of logical positivists think, merely “facts” are subject of rational discussion. Following written above, we could perceive logical positivism as radical empiricism and older versions as weak empiricism. According to logical positivism, verified statements are perceived as science: “meaning or cognitive significance” and need to be empirical tested (Walsh, 1987, p. 862). According to Carnap:“all metaphysical statements... are not provable and are therefore non-scientific” (Carnap, 1995, p. 26, as cited in Putnam, 2002, p. 18). Scientific behaviour from the positivistic aspect is based on two sources: deductive reasoning from axioms and inductive reasoning, based on empirical facts (Hoover, 2005). Until 50’s of twentieth century, logical positivism reaches its peak and was named as “logical empiricism” (Caldwell, 1987, p. 922). In early fifties Quine sets arguments against positivists-we cannot separate “facts” from “agreements” or “facts” from “non-facts” (Aley, 2005). In the seventies logical positivism was not popular among philosophers, while it was still generally present in public (Putnam, 2002, p. 1), especially in social disciplines. Due to the statement written above, we are today discussing about methodological problems in economy and econometrics. Economy is well known for the proponent of logical positivism named T. Hutchison. In 1983 he claimed “science progress on the basis of two interchangeable and mutually coherent activities: empirical research and logical analysis, of which one deals with the way facts act and other with language, used for discussion” (Hutchison, as cited in Aley, 2005). In other words, he defended the position that logical analysis and empirical research is the base of science. This is also the reason why mathematical model became a language of Keynesian’s economy, based on logical analysis, while testing in

1686 Introduction to the Scientific Problem of Econometric Methodology econometrics became popular method of empirical research (Aley, 2005). Spanos, beside strong influence of logical positivism on economy, also recognises influence on philosophical base of “traditional” econometric methodology (Spanos, 1986, p. 659). Besides written above he defends three mutually correlated features of “traditional” econometric methodology, namely: verification, possibility of neutral observation- language and emphasis on provability of economic hypotheses (Caldwell, 1982, pp. 659-660). Hacking states some other important features of logical positivists’ methodology: (1) Verification (or specific ways of the latter, such as falsification): significant statements are those, of which truth or falsehood could be proved. (2) Advanced observation: what can be felt, sensed, touched etc., gives us the best content or the ground for the rest of our non-mathematic behaviour. (3) Non-causality: there is no causality in nature, besides constancy, where events follow other events. (4) Inadequacy of interpretation: explanation can help to organize the phenomena, but cannot give detailed answer of the question: why question expect the phenomena to occur in one way or another. (5) Non-theoretical entities: Positivists tend to be unrealistic, not only because they restrict reality to observers, but also because they are against causes and are doubtful in explanations (Hacking, 1983, pp. 41-42). Zaman claims, econometrics is in its essence insufficient, because is based on principles of logical positivism (Zaman, 2012), which are no longer in use. Further, econometric problems, based on logical positivism, are going to be discussed.

5. Econometric Methodology and Its Problems

According to Zaman, the main problem of econometric methodology lies in the false idea of scientific procedures. It is possible to notice two forms of positivistic concepts of science and models: nominalistic and realistic conception. Realistic conception represents possible worlds, based on certain rules or physical laws, which lead to certain social interaction and causality in our mental processes. The main reason why scientists are interested in causality is the explanation of causality and the way world functions (Zaman, 2012). It is also necessary to stress, that causality is actually not entitled to relations and structures, existing in real world. If the mentality only exists in mental world, we will not place great importance on it. On the contrary, Heckman and other econometrists, defend nominalistic and positivistic perspective of science and models. He claims, that science can occupy with sample stability, which are more or less similar to the law. The procedure of analysis in econometrics runs in econometric mental model, because actual factors and relations according to econometric (epistemologically base) methodology are unclear and immeasurable (Heckman, 2000). The latter proves that the econometrics is based on nominalistic-positivists approach. Therefore it is important to prove whether nominalistic approach is scientific or not. We also can suppose that there are two major nominalistic problems in econometrics, namely:

 Intangibility and immeasurability of variables and relations (epistemologically based methodology) and

 Testing the mechanisms of model in relation to the studied objects. Zaman mentioned, conventional econometric methodology is false, because it only tries to find specific samples, occurring in collected data. Moreover it does not use any tools, which could determine or evaluate whether these samples reflect the real power of facts (Zaman, 2012). Zaman’s criticism of positivism coincides with opinion of statistical mathematician David Freedman, who in his work Statistical Models and Causal Inference describes

1687 Introduction to the Scientific Problem of Econometric Methodology regression model and its deficiency in the field of empirical research of social sciences, because the technique is dependent on knowledge we posses. The consequence of the written above lies in incoherence of models and searched phenomena (Freedman, 2010). Main support in econometric models represent linear regression model. For a long period, the model was used in statistical tests (heteroskedasticity, autocorrelation etc.). With the purpose of more detailed analysis of complex data source, improvements in a shape of panel data developed. As Hendry states, such statistical approach leads to larger number of inauthentic regressions. Hendry cites an example, which represents greater correlation between annual inflation rate and dysentery as between annual inflation rate and money supply rate of change. The latter underestimates scientific credibility, because proving hypotheses has, besides false results, no meaning (Hendry, 1980, p. 395). As Hendry expresses in his work called Econometrics-alchemy or science?, econometrists assert that regression analysis is useful for transforming data in significant results (Hendry,1980). Implicit doubt of modelling and difficulties of certain variables are despite minor reliability, usually proved with inferential statistics, supported by probability distribution. Testing the hypothesis is carried out with certain level of significance. Krueger stresses; it is more appropriate to use the term “hypothesis cannot be proved” than “we deny hypothesis”, meaning that econometrics as such defines results as sets of analyses (Krueger, 2001, p. 10). Alternative level of significance enables the statistical non-significant regression coefficient to be significant. Such arbitrary use of significance seems to be problematic in objective view, which is the scientific basis. Berksonproposes that in case of asymptotic patterns, one denies each null hypothesis and proposes to determine the level of significance on the basis of pragmatic research (Berkson, 1938). Keuzenkamp and Magnus also emphasize the problem of subjectivity in the case of arbitrary use of significance. In practical use, there is a possibility of significance determined with subjective needs of single econometrist and is dependent on conventional needs of econometrist in order to prove or deny hypotheses despite of defining the values (Keuzenkamp & Magnus, 1995, p. 16). In this way, the objectivity of econometric procedures is weakened, which leads to the problem sensed in general econometrics when searching for data-mining. The economist Jack Heckman thinks that econometrics draws a distinction between statistics, because the econometrics focuses on restoration of causal relation, while statistics deals with correlation. The idea that econometrics is science of causes seems attractive, but is certainly not historical (Hoover, 2005). In the last twenty years there is still present a rivalry between micro and macro econometrists. In search of causality in econometrics we can use Freedman’s statement in Statistical models. “Inference can be certain in so far as its premise is certain.” (Freedman, 2009). At this point other problem in econometrics occurs. Causal inference is grounded on observed data, which is problematic if basic mechanisms are not understandable. Actual models are rarely epistemological equal shape as axiomatic-deductive model and also if they were, they would support validity of inference, based on epistemological models. Causal inference is therefore based on statistical/econometrical procedures, like regression analysis and is valid in “closed” model. Economy is known for its causal proves in real world unlike econometrics. Besides, there occurs a question about relevance of econometrics in the field of anticipation. Freidman asserts that reality of testing the theory is dependent on the ability of anticipation (Friedman, 1940, p. 658). There are lot of critics in the field of econometrics, who exactly because of the latter disprove economy as scientific. Anticipation implies causal relation. In order to prove the relation, we need to use statistical assumptions (Gauss-Marks assumptions). Main assumption is the one about null condition, which proves ceretis paribus relation between independent and dependent variable, without which causal relationship cannot be re-established. The latter actually means an attempt of statistical control, which tries to draw near ideal controlled experiment.

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Based on studied literature of econometric methodology and its scientific aspect, we can conclude, that econometrics faces the same problems as scientific basis for modelling and prediction of global climate changes. Fundamental problems of both are: unrepeated study of relations and phenomena, difficulties when determining causes and results, problematic determination of suitable variables when observing certain phenomena, not having enough knowledge of specific variables, complexity of phenomena and inability to use all of the variables in one model, problem of non-objective results, unreal predictions, uncertainty and lack of methodological research in both fields. As global climate change modelling is questionable in the field of science, so is econometrics due to its similar nature of studied phenomena and relations. It would probably be useful to study the scientific aspect of methodology according to new disciplines, dealing with unpredictable natural and social factors, as well as classifying the scientific aspect, based on methodological procedures and real approach.

6. Conclusion

Social sciences are facing difficulties related to recognition of existent relations between various phenomena, existing within different realities. If the econometrics wants to develop, it has to drop the nominalistic-positivists approach and belief that science can only deal with observed regular patterns, more or less similar to principles. Scientific theories should do more than just describe the regularity of events and patterns- it should as well analyse and describe mechanisms, structures and procedures, which generate the patterns. That is the reason why various authors believe, it should be necessary to find the alternative methodology, which binds the observed patterns with actual structures, we want to study (Alvey, 2005; Dharmapala & McAleer, 1996; Hendry, 1980; Hoover, 2005; Spanos, 2007; Zaman, 2012 et al.). Econometrics is used to test the self-evident theories. It is also used for measuring unknown theoretically defined parameters or unobserved variables. In extreme cases we could assert that econometrics gives the basis for phenomenal legality—this is direct measuring of basic relation, presupposed by theory. The ability of statistical/mathematical use of principles for testing and potential denial of theoretical hypotheses is necessary, but not sufficient condition for authorization the economy as science. The research shows that we cannot treat classical economists as scientific. Similar problem can be noticed in contemporary econometric researches, which try to lean on researches based on causal relations. The essence of econometric methodology represents the development of basis for adequate economic theory and corrects empirical measurements, whereby statistical techniques and theories are used for bridging. It is also important to distinguish between econometrics and other use of statistics in non-economic context. This requires parallels of specific contemporary disciplines, facing with study of facts, but it is difficult to study them scientifically, due to the complexity and other specific features.

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