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Computational techniques and price tests for determining
relevant markets: a systematic review
Anderson Luiz Coan1
Marislei Nishijima2
Fátima L. S. Nunes3
Abstract
The implementation of the hypothetical monopolist test allows the definition of relevant markets for specific goods or services, allowing antitrust authorities to analyze alleged anti-competitive actions. One way to conduct such an analysis, among others, in some countries, is to study the correlation/cointegration between prices. Considering this context, it is worth investigating a possible intersection between this subarea of economic knowledge and computational/information system techniques, insofar as these could aid in implementing the hypothetical monopolist test. The purpose of this paper was thus to conduct a systematic review (SR) to determine this degree of intersection.
1 EACH-USP – School of Arts, Sciences, and the Humanities of the University of São Paulo, Av. Arlindo
Béttio, 1000, CEP 03828-000, São Paulo, SP {anderson.coan}@usp.br
2
EACH-USP – School of Arts, Sciences, and the Humanities of the University of São Paulo, Av. Arlindo Béttio, 1000, CEP 03828-000, São Paulo, SP {anderson.coan}@usp.br
3 EACH-USP – School of Arts, Sciences, and the Humanities of the University of São Paulo, Av. Arlindo
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1. INTRODUÇÃO
n its guide for analysis of horizontal concentration, the Brazilian System of Competition Defense (SBDC)—like Britain's Office of Fair Trading (OFT) and America's Federal Trade Commission (FTC)—explains the logical analysis for determining the relevant market (RM) of a good or service within a limited geographical area, called a hypothetical monopolist test (Brazil, Ministry of Finance, 2001; U.S. Department of Justice, 2010; Salgado 2011).
This economic logic, however, should translate into an analytical/mathematical tool for delineating the amplitude of a specific market in practice, both in terms of assets included and geographic region. Knowledge of the RM of a good matters to concentration analyses and evaluations of alleged anti-competitive conduct. Basically, there are two groups of techniques used to determine the RM. The first is based on demand estimates associated with other techniques. The second, the focus of this study, is based on price correlation/cointegration tests and is accepted only in some jurisdictions, including Brazil and certain European countries. The advantage of price tests is the need for relatively less information to determine the RM when compared to other techniques (Forni 2004).
Considering the requirements of the calculations involved and the large amounts of information to be analyzed, the contribution from the field of computing/information
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systems can be quite significant. This is because both the delineation of a relevant market and its clarity in presenting it to the agents involved requires computing techniques naturally aligned with the information systems involved.
Based on a systematic review (SR) and using the terms of the subareas of interest as search strings, our aim is to determine the degree of overlap between this sub-area of economics and computational and information system techniques.
The systematic review is a procedure that was initially adopted in the field of health in the late 1980s, because there were many publications lacking a clearly defined methodology at that time. It should be conducted in a planned manner and be able to generate a fair and auditable assessment on the subject of research (Kitchenham 2004; Liberati et al. 2009). Applications of SR are very common in health care and software engineering (Biolchini et al. 2005). Using this methodology to search for the interface between two areas of knowledge is adequate, since there is no clear idea a priori of the possible methods involved between these areas.
To investigate this interaction, academic studies in economics and computing were analyzed. The study’s objective defined the databases to be investigated, which needed to include at least one of the areas of research (economics or computer/information systems).
Besides this introduction, this paper is organized as follows: section 2 presents a brief concept of SR and the established protocol for this study; section 3 consists of a
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synthesis of primary studies identified through research; section 4 discusses the results; and finally, section 5 presents the conclusions.
2. METHODOLOGY
he term systematic review (SR) is used to refer to a research methodology developed to collect and evaluate the available evidence on a focused theme (Kitchenham 2004). According to the author, SR is an explicit, rigorous and verifiable research method that seeks to identify the degree of scientific knowledge in a particular area by collecting, combining, and critically evaluating studies conducted under different approaches.
SR is thus a systematic protocol to search for references on a subject to be studied, in order to assess the state of the art of its intellectual development. The bibliography is based on a sequence or combination of keywords obtained from the object of study, making up the search strings used to guide the search in a digital information database. The search results, a collection of articles/studies, are subjected to inclusion and exclusion criteria previously defined according to the objective of the proposed study, and finally the subgroup of studies that meet the inclusion criteria are summarized in accordance with a specific script.
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The specific script consists of ordering specific classes of data from the included subgroup. It is worth noting that this phase can either add value or change the course of the research process developed so far, depending on the results obtained. The recording of information during all phases of the process can result in an auditable report.
2.1 Planning
The SR for the specific case of this article was composed of two sequential rounds. The first searched for more general keywords (strings) in the areas of economics and computing, such as “markets,” “computer techniques,” and “price techniques.” The second specified less-encompassing statistical/mathematical techniques such as “cointegration” and “Johansen procedure.”
To identify and analyze the methods of price correlation in studies of relevant markets associated with implementations of computational techniques, some questions were set to guide the SR.
The primary question addressed the degree of overlap between price tests for defining relevant markets and computational techniques.
A secondary question applied to the first round pertained to the existence of any studies, completed or underway, involving price tests of the computational techniques for determining relevant markets. In this case, the criterion consisted of approaches presenting
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or evaluating statistical price tests applied to the determination of the relevant market, together with a computational technique.
In the second round—which sought to focus on statistical techniques, which apply to the definition of relevant market, but can be used in other applications of economics— the secondary issue was to assess the degree of relevance of the following methods of statistical computing: the Bierens and Durbin-Watson tests, and the Johansen and Johansen-Juselius procedures to check whether two products are in the same relevant market. The criterion adopted was to examine whether these techniques, widely used in economics, have references in computer applications.
For implementation of the SR, searches were performed in the following digital libraries: ACM Digital Library [http://dl.acm.org, acessed in 02/22/2012], IEEE Xplore Digital Library [www.ieee.org, acessed in 10/02/2011 and 02/22/2012], JSTOR Digital Library [www.jstor.org, acessed in 10/02/2011] USP digital library [www.teses.usp.br, accessed in 10/02/2011], Scirus Digital Library [www.sciencedirect.com, acessed in 11/14/2011 and 11/21/2011], and Web of Knowledge [accessed in 02/22/2012]. These sources were selected because they are the most frequently indexed electronic databases in computer science and economics.
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The languages defined for the search of the studies were English, which is internationally accepted for scientific work, and Portuguese, because the motivation of the study came from antitrust studies in Brazilian Portuguese.
The period analyzed—from 2000 onwards—was defined in accordance with a trade-off verified in pilot pre-tests, using keywords from the objective of this study during the primary searches. This phase consisted of an initial exploratory analysis of the literature in order to define the elements of the protocol to be followed. The works in economics were observed to be quite old compared to those in computing. We assessed that a 10-year period would adequately cover the two search areas covered.
The inclusion and exclusion, as well as the search criteria, result from the SR objective of finding an intersection between the sub-area of relevant price determination in economics and computational techniques.
A) Inclusion criteria: i) presence of methods to analyze market techniques; ii) relevant market and the hypothetical monopoly test, with or without computational implementation; iii) use and implementation of cointegration techniques, such as Johansen's, Bierens', and Granger's; and iv) empirical and/or algorithm computational search techniques.
B) Exclusion criteria: i) matters of general economic knowledge; ii) product's relationship to a geographical area, but without analysis of relevant markets; iii) general informatics and/or
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primary concepts of systems; and iv) techniques of general knowledge of financial mathematics.
To classify articles as included or excluded, the following procedure was adopted: if at least one of the inclusion criteria was met, the article was included; if at least one of the exclusion criteria was met, the article was removed. It is important to note that inclusion and exclusion criteria were formulated so as to prevent overlap. The articles surveyed and classified by the criteria previously presented are found in Table 14.
2.2. Conducting the Review
The SR was conducted between November 2011 and February 2012.
The strategy adopted for data selection consisted of building strings with keywords derived from the objective of this study and their synonyms. The resulting strings were submitted to search engines, returning studies incorporating these factors. The inclusion and exclusion criteria were then applied.
As discussed above, and due to the high complexity of interdisciplinarity between economics and computing, the construction of the strings to provide a satisfactory result required the implementation of the SR in two sequential rounds.
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Below are described the keywords used during the review phase and their respective dates, in conjunction with applications in specific machines. Strings 1 to 5 refer to the first round of SR (more general), and 6 to 8 relate to the second round (more specific).
1. IEEE Xplore digital library (search on 10/02/2011): “econometric and computer”;
2. JSTOR digital library (search on 10/02/2011): “econometric and hypothetical or monopolist”;
3. USP digital library (search on 10/02/2011): “market and relevant”;
4. Scirus digital library (search on 11/14/2011): “multivariable model building and function selection and programs or (TAR-Cointegration)”;
5. Scirus digital library (search on 11/21/2011): “(cointegration and qr decomposition and reduced rank and singular-value decomposition or (level shift and regime shift and cointegration )) or (global warning and radioative forcing and cointegration or (multivariate and bivariate cointegration analysis and international interdependence ))”;
6. IEEE Xplore digital library (search on 02/22/2012): (((engle granger methodology) and cointegration analysis time series) or johansen procedure);
7. ACM Digital Library (search on 02/22/2012): (((engle granger methodology) and cointegration analysis time series) or (johansen procedure);
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8. Web Of Knowledge (search on 02/22/2012): Title=(engle granger methodology) or Title=(johansen procedure) or Title=(Bierens).
The first round returned 23 (twenty-three) articles, and the second returned 16 (sixteen) articles.
Table 1 shows the studies returned by the search strings above. The studies identified (ID) from 1 to 23 were selected in the first round and those identified 24 to 39 make up the results of the second round of searching. The last column of Table 1 shows which inclusion or exclusion criteria were used for the decision.
Table 1: Selection of previous studies according to inclusion and exclusion criteria
ID Article/Studies Status Criteria Round
1 [Yesufu, 2009] Excluded 1 1 2 [Tian, 2009] Excluded 1 1 3 [Qin et al, 2011] Excluded 1; 5 1 4 [Fu and Norsworthy, 2000] Excluded 4 1 5 [Gunes, 2000] Excluded 1 1 6 [Gungor and Gunes, 2000] Excluded 1 1
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7 [Shao et al., 2008] Included 4 1 8 [Yuhong et al, 2008] Excluded 1 1 9 [Feng, 2011] Excluded 1; 2 1 10 [Jing-Rong, 2008] Excluded 1; 5 1 11 [Han et al., 2011] Excluded 1; 2 1 12 [Hongfeng and Xiaofang, 2011] Excluded 1; 3 1 13 [Hörner, 2011] Included 1; 2 1 14 [Christiano, 2011] Excluded 1; 3 1 15 [Gavazza, 2011] Excluded 1 1 16 [Pitelli, 2008] Included 2 1 17 [Bildirici et al, 2010] Included 3; 4 1 18 [Alp, 2009] Excluded 1; 2 1 19 [Bildirici et al, 2008] Excluded 1; 2 1 20 [Sauerbrei et al., 2006] Included 4 1 21 [Davidson and Monticini, 2010] Included 4 1
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22 [Östermark, 2001] Included 3; 4 1 23 [Doornik and O'Brien, 2002] Included 3; 4 1 24 [Ozkan et al, 2010] Included 3; 4 2 25 [Shan, 2010] Excluded 1; 2 2 26 [Zhang et al, 2011] Excluded 1; 2 2 27 [Dvorakav et al.,2001] Excluded 1; 3; 4 2 28 [Bayat et al., 2010] Excluded 1; 3; 4 2 29 [Johansen and Krozer, 2008] Excluded 4 2 30 [Johansen et al., 2004] Excluded 4 2 31 [Hadziabdic et al., 2007] Excluded 4 2 32 [Gutvik et al., 2011] Excluded 4 2 33 [Sorasen et al, 2004] Excluded 4 2 34 [Galenko et al, 2009] Included 3; 4 2 35 [Chu and Glymour, 2008] Included 3; 4 2
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36 [Kasparis, 2010] Included 3; 4 2 37 [Wagner, 2004] Included 3; 4 2 38 [Díaz-Emparanza, 2004] Excluded 1; 3 2 39 [Fan and Li, 2002] Excluded 1; 3 2
3. RESULTS AND DISCUSSION
3.1. Analysis of results
he results of the strings applied to search engines returned 39 valid articles, as shown in Figure 1. Of this total, 13 articles, or 33.3%, were included after applying the inclusion and exclusion criteria present in section 2.1. The return rate for the prior search was 1/3, indicating a good rate of return for the search using strings
Table 2 shows the relative frequency of inclusion and exclusion criteria used for the selection of articles.
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Table 2 - Relative frequency of inclusion and exclusion criteria
Criteria 1 2 3 4 5
Article Included 8% 15% 62% 85%
not applicable Article Excluded 77% 23% 23% 31% 8%
The first criterion for inclusion was employed only 8% of the time. This approach reveals that the use of price tests for defining markets is in itself a topic which has received little interdisciplinary study.
The graph shown in Figure 2 shows the sources (search engines) of articles considered valid after the search for the defined strings. The IEEE Xplore digital library returned the most studies, 56%, followed by Scirus digital library with 18%, and Web of Science with 10%. The three together account for 84% of returned items.
However, after applying the inclusion and exclusion criteria, the composition of the original studies by search engine changed significantly, as can be seen in Table 3 showing the studies included. This phenomenon is related to the composition of the research areas of interest on each search engine used.
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In the case of the IEEE search engine, which had a very small percentage of inclusion, 9%, the reason for the high rate of exclusion was its content, which deals with general issues in economics, not directly related to the sub-area of interest.
Table 3 - Percentage of total articles by search engine
Search Machine Total Total % Included
Included % IEEE Xplore Digital 22 56% 2 9% JSTOR Digital Library 3 8% 1 33% USP Digital Library 1 3% 1 100% Scirus Digital Library 7 18% 5 71% ACM Digital Library 2 5% 2 100% Web Of Knowledge 4 10% 2 50%
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The number of studies returned by the search strings, 39, and their composition by source search engine suggests that, generally speaking, a proper assessment can be made of the subject being researched.
The IEEE Xplore digital library, which includes a great quantity of computational studies, returned the most studies selected from the strings; however, most of these studies were excluded by the application of the criteria for inclusion and exclusion. As shown in Table 3, IEEE articles that are included account for 15% of the total.
In this search engine we verified the presence of majority of studies using neural networks techniques in different applications and some applications of Engle-Granger
cointegration in comparisons among economic growth in different countries. The last is used in pricing tests for determining markets but we did not found this type of application in this search engine.
According to Table 3 the most articles included are from the Scirus digital library, 39%. It is noteworthy that among the topics found in this interdisciplinary search engine were multivariate regression techniques and search techniques based on neural networks.
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Table 3 – Percentage of inclusion of articles by search machine
Search Machine Total Included Perc%
IEEE Xplore Digital 22 2 9% JSTOR Digital Library 3 1 33% USP Digital Library 1 1 100% Scirus Digital Library 7 5 71% ACM Digital Library 2 2 100% Web Of Knowledge 4 2 50%
The results for other search engines (see Table 3) were higher after the use of inclusion and exclusion criteria, although the number of articles found was quite small. The exception was the Scirus search engine, which returned seven articles, of which 71% were included. 7.7 7.7 7.7 7.7 23.1 7.7 30.8 7.7 0 5 10 15 20 25 30 35 year 2001 year 2002 year 2004 year 2006 year 2008 year 2009 year 2010 year 2011 Percent
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Figure 1 shows the items included by year of publication. It appears that the years 2008 and 2010 had the highest proportions of works, with 23% and 31% respectively. No works from the years 2003, 2005, and 2007 were included. The remaining years showed uniform distribution of results.
The field of computing incorporates economic themes in an interdisciplinary fashion in order to examine financial markets and economic growth; it is thus natural to expect a greater number of works in years of crisis.
7,7 % 69,2 % 7,7 % 7,7 % 7,7 % 0 2 4 6 8 10 China EUA Brazil Turkey United Kington Total
Figure 2: Percentage of included articles by country
Figure 2 shows the origin of studies by country of publication. The majority of studies on the intersection between the areas investigated originate in the United States, 69.2%. This result shows to some extent the predominance of that country's scientific intellectual output, although we have not controlled for the origin of the authors.
Brazil appears to have contributed to the studies due to the fact that the SR included the Portuguese language in its search. However, it is possible to notice a pattern in quantity
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of studies: they come most from developed countries (United States and United Kingdom) or from developing (China, Turkey and Brazil).
3.2. Analysis of the content found
The results of SR show that there is no intersection between the field of economics and computational techniques in the subject of determining relevant markets using price tests.
Briefly, no articles exploring the topic of determining relevant markets using pricing techniques were found in the field of computing. However, articles were found in the field of economics dealing with the determination of markets through price tests, using techniques common to the field of computing (Hörner, 2011; Pitelli, 2008; Davidson, 2010; Östermark, 2001; Doornik 2002; Ozkan, 2010; Galenko, 2009; Chu, 2008; Kasparis, 2010; Wagner, 2004.
It should be noted, however, that articles were found in the field of computing that discussed price testing for financial market applications, a different sub-field of economics than the subject of this review. Nevertheless, this is an interdisciplinary contribution to the larger field of economics, and the price tests follow the same methodology employed for the determination of relevant markets (Shao, 2008; Bildirici, 2010; Sauerbrei, 2006) showing an open area for mutual contributions.
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This result was found by conducting the SR in two rounds, as described in the methodology. The first search for strings in the two areas returned a small number of results, but we noticed the use of some common techniques even though the intersection was small. The second round, using strings related to specific price tests/techniques, returned more than one set of articles, including some that are common to the first round, confirming the pattern of use of common techniques, even though the intersection between the areas of research was practically nil.
Table 4 illustrates some common elements encountered in the included articles. The first column describes the technique or element found with positive frequency in the articles. The second shows the absolute frequency of the technique or element in the articles, and the third shows the relative frequency.
Table 4 – Common techniques and elements in the included 13 articles
Technique/element Freq.
Relative Freq.
1. Neural networks 3 23%
2. Mathematical algorithms (Bootstrap, Monte
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3. Relevant market and/or hypothetical
monopolist test 2 15%
4. Results in graphic models 12 92% 5. Qualitative methods 4 31% 6. Use of Haldrup, Mollgaard and Nielsen,
Johansen and Jusileus, Engle-Granger, Johnson, Bierens, and other linear and non-linear
cointegration techniques, 12 92% 7. Relation to geographical studies 1 8% 8. Analysis of prices 2 15%
As can be seen in Table 4, 92% of the included articles deal with techniques of cointegration, linear or nonlinear, and 92% include graphical presentation of results, a typical tool from computation area. These high percentages show the use most frequent techniques in the interdisciplinary area of economics and computing. This result, together with the small analysis of prices found, 15%, suggests that the use of computational techniques in the area of economics investigated presents an open field for interdisciplinary research.
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Specifically related to computing, the techniques found were neural networks (23%), mathematical algorithms (31%), and qualitative methods (31%).
In particular a high percentage, 92%, of articles with graphical/visual analysis suggests the possibility of using this technique in the determination of relevant markets since there is a lack of didactic visual tools in this area. In this area to communicate the results in a clear and didactic manner is essential, since the decision-making of the antitrust authorities involves professionals from various backgrounds, such as lawyers, administrators, and obviously economists.
The cointegration tests are the most commonly used tool for price tests to determine relevant markets; it appears that the state of the art has been its development with non-linear cointegration and testing thresholds, although the more traditional Johansen tests are more widely applied.
4.
Final Considerations
his study aimed to assess the degree of overlap between price tests for
determining relevant markets used in the field of economics and computational techniques in computing/information systems.
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For this purpose we performed a systematic review implemented in two rounds, with the second round intended to confirm the results obtained in the first regarding the use of similar techniques in the two major fields of economics and computing.
Specifically, the second round investigated the use of statistical cointegration techniques (Engle-Granger methodology, Buriens and Johansen) in applications in computing/information systems search engines.
The results of the SR show a small degree of overlap between the areas of the relevant markets in economics and computational techniques in computing. The intersection is restricted to statistical techniques (cointegration tests) that rely on
computational implementation for the numerical solutions of the estimated parameters. The intersection exists in specific applications for the determination of relevant markets, but there are also applications for stock prices in financial markets.
These results, the intersection between the techniques of cointegration, linear or nonlinear, suggest an open field for interdisciplinary research or in the area of information systems.
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