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2013-05-23
Over the last decades, the service sector has increased as a percentage of the economies. This paper analyzes whether service prices can be internationally standardized based on the Purchasing Power
Parity (PPP) theory. The findings confirm that the services’ unique features intangibility, inseparability, heterogeneity and perishability (IIHP) complicate standardization, for an international price comparison to be possible. From our models, there is no statistical proof that exchange rate, as the sole price adjustor in PPP, has an effect on pricing. We conclude that there are macro factors in the models, not covered by the PPP theory that acts against an implementation of standardized prices. From the study on Flexlink, a company that assembles and installs transporter systems, it was verified that the sales units regularly use price discrimination, as a result of the markets’ high price elasticity, an adaption to the local markets are necessary in order to be competitive.
Keywords: Pricing, Services, PPP, IIHP, FTU, International trade, Wage, Cost of Living
Spring 2013
Supervisor: Martin Holmén
Bachelor Thesis in Corporate Finance (15 hp)
The Department of Economics at the School of Business, Economics and Law
Oscar Johnsson 19900606-0231, Louise Lorentzon 19890518-0140

We would like to thank our supervisor Martin Holmén for sharing his knowledge, and for helping us with the issues that arose during the writing of this thesis. We would like to thank Carina Karlsson, Magnus Andersson and Kristina Wall Jungbjer for assisting us within each of their area of professional expertise.
We would also like to give thanks to all the Finance Managers who participated in the interviews.
And finally, we would like to thank Hilda, who entertained and inspired us during our long working days.
________________________ __________________________
Oscar Johnsson Louise Lorentzon
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ACKNOWLEDGEMENTS
1. INTRODUCTION AND PROBLEM STATEMENT
1.1. Background
1.2 Research Questions
1.3 Methodology and Delimitations
1.3.1 Literature Review
1.3.2 Survey
1.3.3 Regressions
Fig.1 Essay Process: The Figure Shows the Main Structure of the Thesis.
2. FLEXLINK’S HISTORY
3. DEFINITION AND FRAMEWORK
3.1 Definition - Service
3.1.1 Intangibility
3.1.2 Heterogeneity
3.1.3 Inseparability
3.1.4 Perishability
3.2 FTU Framework
3.2.1 Facilities
3.2.2 Transformation
3.2.3 Usage
4. THEORY
4.1 Purchasing Power Parity (PPP)
4.1.1 Definition
4.1.2 Law of One Price
4.1.3 The Development of the PPP
4.1.4 Critiques of the Applied PPP
5. METHODOLOGY
5.1 Macro Variables on Pricing
5.1.1 Dependent Variables
5.2.3 Independent Variables
5.3 The Regression Model
5.4 Hypothesis
6. EMPIRICAL RESULTS
6.1 Correlation Results
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6.2 Regression Results
6.3 Analysis of Regressions
6.3.1 Cost of Living Models
6.2.2 Cost of Engineer Models
6.2.3 Cost of Fitters Models
6.3 Survey Results
6.4 Analysis Survey
7. DISCUSSION
8. CONCLUSIONS
9. LIMITATIONS AND SUGGESTIONS
BIBLIOGRAPHY
Literature and Articles
Websites
Interviews and Observations
APPENDIX
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AGRI_%
UNEMP_%
BMI_PPP
GDP/CAP
GDP_DEF
COL_IN
EX_RATE
POVU_2_%
SERV_%
AV_WAGE
PPP
IIHP
FTU
OECD
ENG_COST
FIT_COST
GDP
CPI
Percentage of the population working in the agriculture sector
Percentage of the population unemployed
Big Mac index – Purchasing Power Parity adjusted
The GDP/ Capita in Dollar
The GDP Deflator
Cost of Living index, with USA as base country
Exchange rate, with SEK as base currency
Percentage of the population earning less than 2 dollars/day
Service sectors percentage part of the GDP
Average wage/hour
Purchasing Power Parity
Intangibility, inseparability, heterogeneity and perishability
Facilities, transformations and usage
Organization for Economic Co-operation and Development
Average Engineer cost/hour at Flexlink
Average Fitter cost/hour at Flexlink
Gross Domestic Product
Consumer Price Index
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Organizations that pursue business globally, are participating in several markets. If a customer has affiliates in more than one country that require services, prices should be internationally standardized to accommodate the trade. International firms want to charge the same price to the same customer in different countries; otherwise, the same customer will have different costs for different countries that will incur problems.
Based on these conditions, standardized prices ought to be the norm, but there are several factors that complicate the standardization of service performance and price.
Service pricing is becoming an increasingly important topic for multinational corporations, as there have been a shift from products to services in developed countries. Cassel (1918) presented the Purchasing Power Parity (PPP) theory, based on the principle of equal purchasing power in all countries after adjusting for exchange rate. The PPP theory by Cassel (1918), as well as Taylor and Taylor (2004) and Rogoff’s (1996) take on the theory, provide the framework for this thesis concerning international standardization of service pricing. A company’s main objective is to maximize profit by using the best strategy. Based on the theory by
McCarthy (1960) there are 4 P’s; product, price, place and promotion, all of which are costs except for price. To set the right price is of utmost importance since a too high price might make the firm non-competitive, while a too low price can create losses.
Furthermore, existing theories and literature mainly consider pricing of products, and there is an absence of thorough studies on services.
This paper will discuss the subject from an economic and management view. Starting from a macro level with empirical results, there will be three cases examined; a general for the world, for fitters and for engineers. The service professions differ in terms of difficulty; fitters assemble the systems, while engineers design and act as project leaders. The macro factors applied are recognized as good indicators for pricing. At a micro level, a case study of Flexlink, a company that assembles and installs transporter systems.
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Current research and literature is vague and ambiguous regarding the difference of goods and services, and therefore there is an attempt to define a service and the specific characteristics. The aim of this thesis is to examine whether service prices can be internationally standardized. According to the PPP theory there should be global price parity, and if violated it provides evidence against internationally standardized service prices.
The case study will be conducted on Flexlink; a global company, headquartered in
Gothenburg, that assembles and installs transporter systems. Their revenue is based on selling projects that include the product and service. The regression analysis will be based on Flexlink’s cost of services since they have reported differences among their
19 sales units, and in-depth interviews will be conducted. The case study will favourably confirm the findings on a global level.
Pricing theory is a complex subject due to the many aspects involved when setting the price, but by a multifaceted approach the aim is to give a comprehensive assessment.
The different perspectives presented in this paper are an attempt to contribute to price theory, with a focus on services; from a macro to a micro point of view.
(i) Can service prices be standardized based on economic theories or should an adaption be made to the local market?
(i.i) Do macro factors affect the pricing of services such that standardized pricing is not feasible?
(ii) Can the Flexlink findings strengthen the Purchasing Power Parity for service pricing?
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The thesis has two approaches:
Macro: Examined through literature and empirically.
Micro: Case study; survey results to strengthen the findings.
The assessment of the perspectives will be carried out by using a survey, regression and an analysis of the literature.
1.3.1 Literature Review
In order to answer the research questions, the characteristics of a service need to be separated from the goods. First the service is discussed with the traditional IIHP
(Intangibility, heterogeneity, perishability and inseparability), a model promoted by
Lovelock (1999), Bowen and Schneider (1988), Gummesson (2004), Berry (1980),
Beaven and Scotti (1990). From critiques of the IIHP, the more recent FTU Framework is introduced with a process based approach (Moeller, 2008; Fließ and Kleinaltenkamp,
2004; Vargo, 2008). However, both models can be seen as simplifications, but are necessary in order to identify the service characteristics.
The thesis main theory is the Purchasing Power Parity (PPP) that supports the standardization of service pricing, if price parity exists (Cassel, 1922; Taylor and
Taylor, 2004). The theory is a valuable tool for explaining pricing, but has been criticized to not hold in a globalized world.
1.3.2 Survey
The survey is based on interviews with the Finance Managers in 7 out of 19 countries where Flexlink have sales units. Due to the short time window for the survey interviews, all countries could not participate. The questions are divided into two parts; internal customers are defined as in-house trade between Flexlink’s sales units, and all other trade is with external customers, non-Flexlink. The dividing of questions into two parts (Appendix), was done after input from the Flexlink supervisors to make it easier for the sales units to give correct answers. There are a total of 31 questions, both multiple-choice and full-answer. The Finance Managers provide an updated and reality based view of service pricing and the questions cover topics from macro, micro to accounting (Appendix).
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1.3.3 Regressions
In the regression tests, panel data is used. The data is collected for the years 2001-
2011. In the world regressions, the dependent variable is Cost of Living, and in the
Flexlink regressions, the dependent variables are Cost of Engineers and Cost of Fitters.
The independent variables are: Big Mac Index, Agriculture, Poverty limit $2, unemployment, GDP/Capita, GDP Deflator, Exchange rate, average wage/hour and percentage employed in the service sector. Below are the countries where the nineteen sales units are located:
Europe Belgium France* Germany
Poland* Spain* Sweden*
Hungary*
Asia and the Pacific Australia* China India Indonesia
North and South
America Brazil Canada United States
*) The countries chosen for personal interviews
Italy
United Kingdom Russian
Malaysia* Singapore
Informatory Exploratory Empirically Analysis Confirmatory
Fig.1 Essay Process: The Figure Shows the Main Structure of the Thesis.
The process of the essay starts from an Informatory point of view, where the authors’ describe and investigate the problems, limitations and main approaches. Thereafter, the essay’s perspective is an
Exploratory view and focus is on relevant literature. After that, an Empirical aspect is applied to analyse the regressions and survey results in order to answer the research questions . Finally, the findings are analysed and evaluated in order to confirm the results.
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Timeline
Flexlink is a manufacturing based company of conveyor system; the procedures are loading, processing, assembly and packaging. In 1980, Flexlink was founded as a spin-off company from the roller ball bearing maker SKF (Svenska Kullagerfabriken AB). The international success came immediately, and the Flexlink conveyor systems quickly got recognition in a wide range of industries (Flexlink 2013). At present, Flexlink is one of the main players in the segment material handling systems, and has established Sales Units in 19 countries and partner companies in over 50 countries (Flexlink information PPT 2013). The historical timeline is based on Flexlink’s documents (2013) and Flexlink’s informational PowerPoint
(2013).
1980
1980 Flexlink was founded in Gothenburg, as an efficiency project within SKF
1988–03 Establishment of Sales Units in:
Japan, USA, Germany, Singapore, Brazil,
France, Italy, UK, the Netherlands,
Australia, Czech Republic, China, Poland,
Hungary, Spain, Malaysia, Thailand,
Finland. The first information/coordination system was introduced
1982-87 Development of the organization and product solutions
1997 Flexlink was aquired by EQT and became an independent company for the first time
2005 Acquired by ABN Amro Capital, now AAC Capita
2006 Acquisition of Tops Conveyors, a company based in Canada
2010 Acquistions of the
Automation Division from Schüco,
Germany, and Italian e-cube.
2012 Flexlink is one of the largest specialized conveyor distributers in the world with revenues of 1,6 billons SEK
2007 Opening of sales companies in India and Indonesia
2011 January 11 TH FlexLink was acquired by
COESIA GROUP, and became a member of the innovation based industrial group from
Bologna, Italy.
2013
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During the past 20-30 years, there has been a dramatic increase in the service sector.
According to Edvardsson et al. (2000), different services in the private as well as in the public sector account for about 70-75 % of the gross national product in most
OECD-countries. He also argues that services are gaining in importance and are gradually becoming an essential part in all types of commodity manufacturing firms; many firms even define themselves as service oriented rather than engineering oriented. Nowadays, it is a common understanding among most service researchers that in a world characterized by turbulence (Mintzberg, 1993), services are becoming an outstanding tool both to differentiate the business (Oliva & Kallenberg, 2003) and to develop sustainable competitive advantage (Barney, 1991).
It has been debated, for instance by Matanovich (2003), that there should be no difference between pricing of goods and services. He emphasizes the importance of focusing on how much value that is offered to the buyer rather than focusing on if it is a good or a service. However, there is more evidence proving that key differences exist between the pricing of goods and services, and this will be our view for this thesis.
Lovelock (1999) argued that the rather intricate nature of the service sector has created a complex problem regarding the definition of a service. Not only have services gained importance in the developed world, but what is perceived as a service has also changed due to technology (Rust, 2004). The out-dated but still general view is that services are based on personal contact (Bowen, 2000), but many services are nowadays net-based e.g. personal banking, lectures, shopping. In order for the term
“service” to be defined correctly, new traits and sectors of application must be added to make it current (Moeller, 2010).
Lovelock(1999) argues that it is the performance/delivery of the service that makes it so hard to grasp, and the fact that services are quite abstract. To most people, he argues that to understand the manufacturing businesses is much simpler. You can easily understand the process of assembly, transformation or creation of goods, by
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using physical input to get physical output in for example a factory. To understand or define what type of value, or how much a service really matters is much harder according to Lovelock (1999).
From findings in the work of other researchers there is a wide range of methods in order to distinguish goods from services. Given the examined research material, two approaches will be discussed. Firstly, the characteristics of a service are condensed into four main groups, IHIP; Intangibility, heterogeneity, perishability and inseparability (Lovelock, 1999), (Hansen & Mowen, 2006), (Barney 1991), (Flipo
1988) followed by a more modern approach, the FTU Framework (Moeller, 2008).
Fig. 3 - IHIP Characteristics (Explained below)
3.1.1 Intangibility
The intangibility aspect is always connected to services and has for long been considered as the most fundamental characteristic (Bowen and Schneider, 1988). The intangible side described; cited Berry (1980, p.24) “A good is an object, a device, a thing; a service is a deed, a performance, an effort”. The intangible side of a service is subject to its immateriality and the very problem when it comes to describing what a service stands for, and the valuation of the performance. This problem is not new, back in the 16 th
century; Smith (1776) felt that services were non-value adding and only goods that could be included in trade would create wealth for the country. Say
(1836) considered Smith to be wrong and argued that even though services are not
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material, their usefulness and surrounding activities create value. The difficulty of selling a service is that what is being sold is a contract of an immaterial performance
(Bowen and Schneider, 1988). What the buyer actually receives and the quality of the service is vague which causes uncertainty regarding the value (Shostack, 1977).
There is criticism of the intangible aspect of a service. In order to perform a service, tangible goods are normally required (Shostack, 1977). An obvious situation is a barber performing a haircut, perceived as an intangible service. For the service to be executed there are a need for a studio, scissors, hairdryer which are tangible. A service performed on a person who is tangible (haircut), will result in a change due to the service and is therefore tangible (Moeller, 2010). Much focus has been placed on the transformation process of resources given by the customers' input, which also can be interpreted as the services’ main purpose (Hill, 1977). For most goods input is not given by the customers for transformation and only the finished product is sold.
However, there are grey areas in terms of customized goods, when the customer asks the seller to perform a service that results in a product (Moeller, 2010).
3.1.2 Heterogeneity
One of the difficulties regarding services is for the outcome to be the same, and thus to standardize a service is hard (Edgett an Parkinson, 1993). Different factors that are considered to be making the service heterogeneous have been investigated with separate viewpoints. Beaven and Scotti (1990) suggested that it was the outcome that differed and thus the services’ results cannot be considered homogeneous. According to Lovelock and Gummesson (2004) it also depends on how the service is performed and that this creates a heterogeneous situation. The same service’s quality can vary a lot depending on who performs it and the daily status of that person. It does not only depend on the service provider for the service to be heterogenic, the customer expectation and participation plays an important role in the service outcome (Palmer and Cole, 1995).
Not everyone agrees that services cannot be homogeneous, it depends on the nature of the service and some may therefore be standardized (Lovelock and Gummesson,
2004). According to Moeller (2010), some services can be standardized by using the same process, while others such as customized services cannot be made by following
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the same model. There are discussions concerning whether it is the service that actually varies, but according to Vargo and Lusch (2004) the variations are due to the human error, which can be reduced but not avoided. The technology has become more advanced over the past centuries, and services previously handled over the counter have become computer-based, e.g. banking and shopping (Furrer, 2003). The result of this is that more services can be standardized and variations will decrease according to
Lovelock (1983). The input to the service provided by the customer will vary, and therefore the amount of time and the execution might differ but this is not due to the service offered (Lovelock, 1983, p.16).
3.1.3 Inseparability
Inseparability comes from the fact that the production and consumption of a service takes place at the same time, making it impossible to divide the two (Say, 1836).
Berry (1980, p.259) argues that this is due to the fact that the customer and the person performing the service cannot be separated and both must be in the same place at the same time. From this follows that the relationship between the provider and customer plays an important role for the perceived service experience and overall impression
(Bitner, 1990). Other differences between services and goods have also been described, such as the order of the sales process; the service is sold in terms of an agreement, and then the service is produced and consumed at the same time.
Lovelock and Gummesson (2004, p.29) found that there are many services provided in today's society where the customer is not present at the process of the service. They gave examples of transport companies carrying goods, but when the customer receives the packet the service is already completed. However, Lovelock (1983) argues that services are sometimes characterized by inseparability but this depends on the service being performed. He chooses to split up the services into two groups, the physical body and physical belongings. The former must be present at the execution of the service but regarding the latter, the customer does not need to be present.
3.1.4 Perishability
This is one of the things that distinguish services from goods; they disappear while they are consumed. It is one of the main opinions regarding why services are difficult to analyse, the fact that the service cannot be kept or stored (Beaven and Scotti, 1990;
Kotler, 1994). Smith (1776, p. 351) was straight to the point on perishability “the
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labour of the mental servant, on the contrary, does not fix or realize itself in any particular subject or vendible commodity. His services perish in the very instant of their performance”.
The criticism of perishability is directed against the fact that services are available in computer systems, knowledge and people (Gummesson, 2004, p.124). Services are also preserved in the form of receipts showing the performed action (Edvardsson et al., 2005). Lovelock (2000) argues that services are different and some has a timelimit while others continue to give value to the customer. The perishable aspect is not unique for services; many goods disappear after consumption e.g. food. From some services, value remains after consumption and therefore what is left behind is a proof that services do not always completely perish. This is very obvious regarding education, the service performed by the professor of teaching the students, will remain as knowledge (Hill, 1977). It is hard to adapt services to the economic cycles since services cannot be stored and are entirely based on customers’ demand when using a facility (Ng et al., 1999).
It is not an optimal approach to describe what differentiates a service from a product by using the four IHIP characteristics (Lovelock and Gummesson, 2004, p.32). The reason is that society has changed and today the research focuses on other kinds of services, and not only the personal based services that were more occurring in the past
(Bowen, 2000). The IHIP characteristics are seen as valuable parameters to describe a service (Edvardsson et al, 2005), but there is a need for adaption to better fit today's society. The problem according to Moeller (2010) is that the implementation of IHIP characteristics is vague, and that the different characteristics need a new interpretation of what part and stage of the service is described. To do this, Moeller (2008) argues that services should be divided into different stages and thus get the four IHIP characteristics to work better as helping tools to define a service. One way to do this is to use the FTU framework that describes a service in three process parts facilities, transformation and usage.
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Transformation
Usage Facilities
Fig. 4 FTU Framework; IHIP Characteristics
3.2.1 Facilities
Facilities enable the service performance and are the value-required input in the processes (Moeller, 2010). Facilities are usually a workplace where the service can be performed, machines and equipment, and staff with knowledge (Shostack, 1992).
Edvardsson et al. (2000) phrased it that these are essentials for a service to take place.
Under these conditions the facilities consist of both tangible and intangible assets and it is clear that a service cannot completely be associated with intangibility. Facilities are only the input for the service to be performed, without customers, the assets remain unused (Fließ and Kleinaltenkamp, 2004) as opposed to goods that can be produced and stored.
According to Moeller (2010) perishability is a characteristic of facilities since the competence (personnel and equipment) provided, must be supported by a customer’s input of resources, in order to be activated and not perish as seen from the provider’s point of view. Heterogeneity is also a part of the facilities regarding what the customers provide, their input will vary and so the prerequisites are not homogenous
(Moeller, 2010).
3.2.2 Transformation
The service that is sold is a promise of a change to fix or improve (Hill, 1977).
Depending on which resources are used, these can be divided into direct and indirect service provisions (Moeller, 2008). First, indirect service provision is when the
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provider arrange for the input to the service in the case of goods. Regarding the direct service provision is when it is the customer who provides input to the service, and what we traditionally call a service. In the latter case the limitation of the provider is that the customer is owner to part of the resources necessary for the service that cannot be accessed otherwise (Hill, 1977). The resource can be the client's body e.g. surgery or an asset like car reparation or knowledge-based banking services etc. (Fließ and Kleinaltenkamp, 2004). The customers contribute their resources because of the need for expertise, along with the providers assets a transformation can be achieved
(Moeller, 2010). Vargo (2008) argues that there are two ways in which the provider interacts with the customer; coproduction is when the two work together to create the transformation, and co-creation of value is when synergies create added value to both parties.
In the transformation part what the provider sells to the customer is an agreement of a service and not a tangible product. The intangibility aspect is therefore a part of the transformation stage (Moeller, 2010). In order for the service to be performed in the transformation stage, the customer’s resources needs to be present and are therefore inseparable from this stage (Moeller, 2010).
3.2.3 Usage
The usage of the transformed service is the last step in the FTU framework (Fließ and
Kleinaltenkamp, 2004). In order to create value the customer needs to use the service to benefit from the improvement (Moeller, 2010). The provided service that is now used can either be standardized based on a template from a catalogue or customized to fit the customer's unique needs (Fließ and Kleinaltenkamp, 2004).
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The Purchasing Power Parity (hereafter PPP) has been chosen as main theory for this thesis, and all discussions will be based on either PPP or the macro factors examined in the next part of the paper. The PPP theory’s assumptions are valuable in order to connect the literature and previous findings, and answer the first research question
“Can service prices be standardized based on economic theories or should an adaption be made to the local market?”.
This part of the thesis will examine and describe the PPP theory, evaluate other researchers’ findings, and provide the reader knowledge of the theory’s limitations.
Factors in the economy affecting the PPP are described below.
4.1.1 Definition
The Swedish economist Gustav Cassel named the theory and stated:
“Our willingness to pay a certain price for foreign money must ultimately and essentially be due to the fact that this money possesses a purchasing power as against commodities and services in that country.
On the other hand, when we offer so and so much of our own money, we are actually offering a purchasing power as against commodities and services in our own country. Our valuation of a foreign currency in terms of our own, therefore, mainly depends on the relative purchasing power of the two currencies in their respective countries.”
Gustav Cassel, economist (1922, pp. 138-39)
The Purchasing Power Parity is an astonishingly simple theory that states that the nominal exchange rate between country A and B must be equal to the purchasing ratio of the price levels between country A and B; implying that one unit of the specific currency in country A has the same purchasing power in a foreign country, country B
(Taylor and Taylor 2004). First and foremost, the idea behind the PPP is that one unit of country A’s currency should buy the same mix of goods in country A, as equivalent amount units of country B’s currency should be able to buy in country B. That means
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that Country A and B have the same Purchasing Power, at the current exchange rate.
(Taylor and Taylor, 2004)
4.1.2 Law of One Price
The PPP theory was developed from the Law of One Price; but a common mistake is to equate the PPP and the Law of One Price (LOP), but in fact there are significant differences between the two. The LOP is based on the theory of international arbitrage. The LOP states that when the price of internationally traded goods are converted to a common currency, the goods should have the same price in different countries. However, there are some assumptions behind the LOP theory that has been questioned. For example LOP assumes that there is perfect competition in the market, no trading barriers or tariffs, and no transportation costs. In reality, due to the existence of transportations cost as well as trading barriers and tariffs, the prices vary between different countries and the LOP assumptions are questionable (Froot and
Rogoff, 1995; Rogoff, 1996).
4.1.3 The Development of the PPP
The Purchasing Power Parity theory has a long and well-debated history that can be can be dated all the way back to the 16 th
century, Spain, Europe. During the 19 th century, well-known economists like Ricardo, Marshall, Mill, Goschen et al, tested and developed comparable PPP landscapes (Rogoff, 1996). T he theory first got its name back in 1918 by Cassel. Cassel’s ideas about the PPP were developed in a backwash of the World War I and the big collapse of the modern financial system.
Before the Great War, all countries followed the global gold standard; the currencies were bound to gold, and could be converted to gold at fixed prices. This created an exchange rate between countries, which reflected the relative price of gold. After the war started it became quite difficult to maintain the gold standard system, and speculators feared that the countries would devalue their currencies to gain short-term revenues. The gold standard system was abandoned, and many countries let the exchange rate float, or bound it to the dollar (Rogoff, 1996). In this turbulent era,
Cassel argued for the accuracy and usage of the PPP theory to explain why the exchange rates should depend on the compared purchasing power between countries.
Since then, the idea of PPP has been discussed and debated in an abundance of reviews and papers among economic researchers all around the globe (Rogoff, 1996).
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4.1.4 Critiques of the Applied PPP
There have been several attempts to prove or undermine the theory, and there are arguments both for and against PPP.
There is an easy way to check whether there are deviations from the Purchasing
Power Parity, by comparing the difference in price of one McDonald´s Big Mac hamburger around the globe. Named by the hamburger, the Big Mac Index is semiannually published by the newspaper “The Economist”. The main purpose of the index is to compare prices in a common currency (dollar), to analyse the price differences. The index effectively measures if a currency is over- or undervalued compared to the USD. The assessment is built on the assumption that the currency would be correctly valued, if the international prices of burgers were equivalent dollars (Rogoff, 1996). This kind of analysis has limitations, and Taylor and Taylor
(2004) argued that the approach is a simplification of reality and therefore should not hold. Nevertheless, despite the imitation mentioned, The Big Mac index has been very popular and therefore the Economist created another index describing the price of a tall cup of coffee at Starbucks (The Economist 2013).
The Big Mac- and the Starbucks index are both engaging ways to visualize the exchange rate’s function. Taylor and Taylor (2004) argued that there are several legitimate reasons why the price of a Big Mac or a Starbucks coffee might differ between countries that cannot be explained by the exchange rate. The primary reason is the fact that the economic environment is not perfect (Taylor and Taylor, 2004).
Reasons for international price differences:

Not easily traded internationally

Local subjective estimation of the services’ complexity factor affect wages

Local differences in price level affect costs
None of the factors above are conveniently arbitraged in the international market, and most of the arguments around the PPP are based on the assumption that there are wide international arbitraging. Hence, this indicates that the Big Mac index should be treated with caution when interpreting results (Taylor and Taylor 2004).
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As mentioned above, in theory the PPP assumptions should hold when comparing to the “Law of One Price”, but the reality is more complex. If the price of a product differs in different regions, a person could make a totally riskless profit by shipping the good from area A, where the price of the good is low, to area B where the price is relatively higher. This statement ignores the fact that there are transaction costs in the market, which hinder the good from being moved from A to B and lower the price.
Furthermore, one of the PPP theory’s limitations is the definition of the market basket in order to compare goods internationally. The taste and preference of goods between countries differ, and it is therefore not accurate to use the same basket for every country. Regardless of the preferences, there are also difficulties in purchasing exactly the same goods in different countries due to availability. However, if there was an accurate market basket of traded goods, in a perfect market without transaction costs, the Law of One Price would imply that the PPP theory of an adjusted exchange rate should hold (Rogoff, 1996).
As mentioned, there are strong objections why the relationship between the LOP and PPP cannot hold. Different transaction costs disaffirm the theory; e.g. transportation cost, trading barriers, tariffs, taxes etc. (Engel and Rogers 1996).
Further, there are goods that are not traded between all countries in the world; consequently the weights of those goods are not going to be equal in the countries’ market baskets. Moreover, observations have also shown that countries tend to create differentiated goods instead of substitutes. Some of these problems, however, could be addressed by using more accurate statistic data (Engel, 1996).
Taylor and Taylor (2004) argue that since the PPP is based on the traded goods, a more appropriate test is the PPI (producer price indices) in comparison to the CPI (consumer price indices). Taylor and Taylor (2004) claim that the PPI usually reflect the tradeable manufacturing goods, while the CPI tends to reflect more non-tradeable goods. By using PPI, the analysis would be more accurate according to Taylor and
Taylor (2004).
21

In this thesis the aim is to test whether the Purchasing Power Parity holds for services internationally, or if it is too simplified and the problems mentioned above are actual issues.
In the regression tests, panel data is used. The regressions are run with data for macro variables clustered by country. The country clusters are independent, but the factors contained in the cluster are dependent. In the regressions, Huber (1967) –White (1980), standard errors are used to adjust for clusters. xtreg matches the regression models to the panel data for both random and fixed effect. The Cost of Living data is unbalanced, since each country is not observed every year. The Engineer and Fitter data is balanced, since each country is observed every year.
The data is collected for the years 2001-2011. Accounting data, economic data and exchange rate data are collected from Thomson’s DataStream. The Cost of Living index is collected from U.S. Department of State, and the Big Mac Index is retrieved from The Economist. Agriculture data, unemployment data and poverty $ 2 are collected from World Bank. The Cost for Fitters and Engineers are collected from
Flexlink’s financial statement. In the world (general measure) regression the dependent variable is Cost of Living, tested for 9 macro-variables in 7 models. The sample consists of 188 countries and the number of years is 1880. For the regression based on Flexlink’s cost of Fitters and Engineers as dependent variables, the tested macro- variables are 9 in 7 models for Fitters, and 9 in 5 models for Engineers. The sample consists of 19 Flexlink Sales Units and the number of years is 190.
In order to investigate the macro factors that have an impact on service pricing, the variables are first discussed below. The variables are seen as representative of the macro- and micro economic factors. There are two types of variables examined;
Dependent and Independent .
5.1.1 Dependent Variables
The dependent variables examined are Cost of Living Index and the hour rate for
Fitters/Engineers at Flexlink.
22

5.1.1.1 Cost of Living Index (COL_IN)
The Cost of Living Index has Washington DC as base (Washington DC=100). The index compares the costs in Dollars ($) of buying representative goods and services
(excluding education and housing) in foreign countries with the cost of equivalent goods in the DC area. The index excludes all kind of extravagant goods and services, and is based on the average American consumption behaviour. The Cost of Living
Index has limitations in measuring and comparing costs differences between countries.
The Index focuses on the comparison of American families and has DC=100 every year, which makes it impossible to use it for measuring cost changes over time in a foreign country. The Cost of Living Index is used in this thesis to examine if there are any differences between countries and if there are any similarities between Cost of
Living and Cost of Engineers and Cost of Fitters at Flexlink (U.S. Department of State
2011).
5.1.2.2 Cost of Engineer
The Cost of Engineer is the average hourly rate for an Engineer at Flexlink, in 19 different locations around the globe. The variable includes Sales and Administrations costs, wages, rents, and social expenses etc.
5.1.2.3 Cost of Fitter
The Cost of Fitter is the average hourly rate for a Fitter at Flexlink, in 19 different locations around the globe. The variable includes Sales and Administrations costs, wages, rents, and social expenses etc.
5.2.3 Independent Variables
5.2.3.1 The Big Mac Index
The Big Mac Index (BMI) was created in 1986 by the magazine The Economist. The index is based on the idea that the exchange rates are reflected in the price levels, when two countries are compared, known as the Purchasing Power Parity (PPP)
(Clements, Lan, & Seah, 2012). The Big Mac index is therefore an indication if the currency is under- or overvalued (Clements, Lan, & Seah, 2012). The Big Mac works very well for representing a bundle of goods described by the PPP, since the hamburger consists of different raw materials e.g. salad, beef, and cheese and is therefore a basket on its own (Dewhurst, 2003). McDonald’s is a big brand and
23

restaurants with a standardized menu are located in 119 countries for comparison
(McDonalds Corp., 2013).
The price of a burger is not only dependent on the input to create a hamburger, but also on wages and the cost of hiring a venue (The Economist, 2009). This view is strengthen by Parsley and Wei (2007) whom claim that there are very little difference between the ingredients that makes a hamburger, and therefore the BMI works very well as a determinant of the correct price for tradable and non-tradable goods. From these close to perfect conditions the Big Mac is a helpful tool to create the absolute
PPP. To investigate whether the PPP theory holds, and if prices can be standardized,
BMI is a good measure of the current situation worldwide and therefore included in the test.
5.2.3.2 GDP-Deflator
The GDP-deflator measures inflation in a country by comparing the current local currency to the constant local currency
1
. The deflator is obtained by looking at the price level from a yearly basket of all new in-country produced goods and services, and comparing to a base level to assess the index
2
. The nominal GDP evaluates the economic worth of transactions in prices for the given period, and thus measures both volume and price. The constant GDP measures the exact change of volume for goods and services for the specific time (Chowdhury, 2008).
𝑮𝑫𝑷 − 𝑫𝒆𝒇𝒍𝒂𝒕𝒐𝒓 =
𝑵𝒐𝒎𝒊𝒏𝒂𝒍 𝑮𝑫𝑷
𝑹𝒆𝒂𝒍 𝑮𝑫𝑷
× 𝟏𝟎𝟎
It is of importance to measure inflation in comparison to other countries as the strength of the currency decides the purchasing power. The advantage of the GDPdeflator is that it covers a broad spectrum of the economy and incorporates the changes that are subject to both consumption and the monetary policy (Chowdhury,
2008). In comparison to BMI the GDP-deflator is a more widely accepted economic variable to measure inflation, and thus included to test wheter the PPP-theory holds in addition to BMI.
1 (http://data.worldbank.org/indicator/NY.GDP.DEFL.KD.ZG).
2 (https://www.boundless.com/economics/measuring-nation-s-output-and-income/gdp-trendsusing-real-and-nominal-values/calculating-gdp-deflator/).
24

5.2.3.3 Poverty lower limit 2$
The minimum income of $2 a day to survive, have been drawn as a guideline worldwide (World Bank). There are many negative effects to low income. The poor may not be able to seek medical care or buy enough food, and the result is decreased productivity in the country as the society cannot make use of the citizens’ maximal capacity. Those who are poor tend to have less education or be illiterate that results in worse jobs that thus have lower wages (UN, 2013).
The poverty line is a generalization of the minimum required income in order to stay alive, but very useful in determining the situation in a country and how poverty affects
PPP regarding pricing. In countries with a high proportion of poor, the price level after being adjusted for exchange rates should give the same purchasing power if the poverty variable has no effect on pricing, but it can be assumed that the prices are lower and not in accordance with the PPP theory. The poverty variable is used in this thesis to test if it is possible to find any significant impact between how poor a country is, the Cost of Living and service pricing.
5.2.3.4 Agriculture
In general, as a society develops, the amount of people working in agriculture decreases. A majority (75%) of the poorest in the world live in rural areas, and it is often far to the nearest town. Even in developed countries 45% of the poor live in rural areas. The only way to make a living is by growing crops or raising livestock, and therefore agriculture make up 70% of their income (World Bank, 2013). For the absolute poor, it is of particular importance since agriculture is the best way to improve their situation due to the fact that they often lack education. It is also positive for the poorer countries, where food needs are secured, and surplus harvest can be sold and exported, leading to growth for the entire country (World Bank, 2013). Generally, where there are more poor people, there are more agriculture and this should affect prices to be lower, even after adjusting for exchange rates and proof against the standardization of prices. Lower prices should also have, at lest some impact on the
Cost of Living and it is therefore of great interest to test this variable in the regression models.
5.2.3.5 GDP/Capita
GDP stands for gross domestic product and is the sum of all economic activity in a country for 1 year. It measures the consumption of all produced services and goods,
25

investments and adjusted for export minus import. A common welfare measure is
GDP/capita that describes the amount of GDP per person living in the country. The higher this ratio is the better of is the country economically. There have been a lot of critiques against the validity of the GDP/capita. Kennedy (1968) argues that it is purely an economical average and does not actually measures the wellbeing of people e.g. education, healthcare. GDP/Capita measures how developed/effective a specific country is, when it comes to output per person. It is therefore interesting to examine how big impact the factor has together with the Agriculture index and the Poverty index on Cost of Living and service pricing, to see if there are any linkages between the effectiveness of a country and the service pricing and Cost of Living.
5.2.3.6 Wage
In developed countries, the wage level is generally higher since people in those countries are more educated and that pushes up wages. The effects are that a higher wage level creates a beneficial situation for abroad travels and import. In developing countries the price level is usually lower, which makes the lower wages purchasing power, in-country, more equal to the developed countries. The factor is included in the analysis because wage is a main component in service pricing. In order to test if this is true, the variable is used. Wage in comparison to the price level in the country is a significant factor after adjusting for exchange rate, for PPP to hold. If the wage to price level ratio differs more than the exchange ratio, it is proof against PPP.
5.2.3.7 Unemployment
The higher the unemployment, the more costs to the society due to social security. If less people are employed, the side effect is that consumption will decline causing hardship for the entire economy. If employment opportunities are scarce, less people will invest in education and businesses (Investopedia, 2013). A high unemployment percentage increases the supply of workers that competes for available jobs, and has a negative effect on wage. Lower wages cause the cost of service to decrease and is therefore important to test.
5.2.3.8 Exchange rate
A strong currency makes import cheaper, but on the contrary makes export harder since the goods will be perceived as more expensive by other countries. The exchange rate ratio, for that reason, has a strong impact on the trading situation. The exchange
26

rate should be a significant factor according to the PPP theory, and is therefore important in the tests.
5.2.3.9 Service employed
Too estimate the value of the service sector; it is useful to know how many percent of the total workforce is employed in the service industry. This shows the importance of this sector to the country. The factor is included to examine if the service-employed level has a significant effect on both the Cost of Living and the service pricing.
In the previous part of the paper, the PPP theory was presented and the macro variables of interest were introduced. To be able to answer the research questions, statistical tests are required that analyze the economic theory and the variables. The selected dependent variables are labor cost and Cost of Engineer/Fitter, and it is going to be examined whether there are any relationships between the variables and the independent macro variables. An estimation of the variables betas together with a hypothesis test will determine the statistical and economic significance. Panel data will be used in the regressions.
There will be three parts to the test since the aim is to investigate the variables impact on:
1) A general measure (worldwide)
2) Engineers
3) Fitters
The three models of costs can be compared and discussed, for a comprehensive view and conclusion.
27

𝐶𝑜𝑠𝑡 𝑜𝑓 𝐿𝑖𝑣𝑖𝑛𝑔 𝐼𝑛𝑑𝑒𝑥
= 𝛽
0
+ 𝛽
1
∗ 𝐺𝐷𝑃 𝐷𝑒𝑓𝑙𝑎𝑡𝑜𝑟 + 𝛽
2
∗ 𝐵𝑖𝑔 𝑀𝑎𝑐 𝐼𝑛𝑑𝑒𝑥(𝑃𝑃𝑃) + 𝛽
3
∗ 𝑈𝑛𝑒𝑚𝑝𝑙𝑜𝑦𝑚𝑒𝑛𝑡(%) + 𝛽
4
∗ 𝐴𝑔𝑟𝑖𝑐𝑢𝑙𝑡𝑢𝑟𝑒(%) + 𝛽
5
∗ 𝐺𝐷𝑃/𝐶𝐴𝑃 + 𝛽
6
∗ 𝐸𝑥𝑐ℎ𝑎𝑛𝑔𝑒 𝑟𝑎𝑡𝑒 + 𝛽
7
∗ 𝑊𝑎𝑔𝑒
𝑊𝑜𝑟𝑙𝑑
+ 𝛽
8
∗ 𝑆𝑒𝑟𝑣𝑖𝑐𝑒 𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑑(%) + 𝛽
9
∗ 𝑃𝑜𝑣𝑒𝑟𝑡𝑦 $2
𝐶𝑂𝑆𝑇
𝐸𝑁𝐺
= 𝛽
0
+ 𝛽
1
∗ 𝐺𝐷𝑃 𝐷𝑒𝑓𝑙𝑎𝑡𝑜𝑟 + 𝛽
2
∗ 𝐵𝑖𝑔 𝑀𝑎𝑐 𝐼𝑛𝑑𝑒𝑥(𝑃𝑃𝑃) + 𝛽
3
∗ 𝑈𝑛𝑒𝑚𝑝𝑙𝑜𝑦𝑚𝑒𝑛𝑡(%) + 𝛽
4
∗ 𝐴𝑔𝑟𝑖𝑐𝑢𝑙𝑡𝑢𝑟𝑒(%) + 𝛽
5
∗ 𝐺𝐷𝑃/𝐶𝐴𝑃 + 𝛽
6
∗ 𝐸𝑥𝑐ℎ𝑎𝑛𝑔𝑒 𝑟𝑎𝑡𝑒 + 𝛽
7
∗ 𝑊𝑎𝑔𝑒 𝑝𝑒𝑟 𝑐𝑜𝑢𝑛𝑡𝑟𝑦
+ 𝛽
8
∗ 𝑆𝑒𝑟𝑣𝑖𝑐𝑒 𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑑(%) + 𝛽
9
∗ 𝑃𝑜𝑣𝑒𝑟𝑡𝑦 $2
𝐶𝑂𝑆𝑇
𝐹𝐼𝑇
= 𝛽
0
+ 𝛽
1
∗ 𝐺𝐷𝑃 𝐷𝑒𝑓𝑙𝑎𝑡𝑜𝑟 + 𝛽
2
∗ 𝐵𝑖𝑔 𝑀𝑎𝑐 𝐼𝑛𝑑𝑒𝑥(𝑃𝑃𝑃) + 𝛽
3
∗ 𝑈𝑛𝑒𝑚𝑝𝑙𝑜𝑦𝑚𝑒𝑛𝑡(%) + 𝛽
4
∗ 𝐴𝑔𝑟𝑖𝑐𝑢𝑙𝑡𝑢𝑟𝑒(%) + 𝛽
5
∗ 𝐺𝐷𝑃/𝐶𝐴𝑃 + 𝛽
6
∗ 𝐸𝑥𝑐ℎ𝑎𝑛𝑔𝑒 𝑟𝑎𝑡𝑒 + 𝛽
7
∗ 𝑊𝑎𝑔𝑒 𝑝𝑒𝑟 𝑐𝑜𝑢𝑛𝑡𝑟𝑦
+ 𝛽
8
∗ 𝑆𝑒𝑟𝑣𝑖𝑐𝑒 𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑑(%) + 𝛽
9
∗ 𝑃𝑜𝑣𝑒𝑟𝑡𝑦 $2
Hypothesis 1 : Cost of Living
𝐻
0
: 𝛽
1
𝐻
1
: 𝛽
1
+ 𝛽
2
+ . . . +𝛽
9
+ 𝛽
2
+ . . . +𝛽
9
= 0
≠ 0
𝐻
0
𝐻
1
: The macro factors have no effect on COL
: At least one of the macro factors has an effect on COL
Hypothesis 2 : Cost of Engineer
𝐻
0
𝐻
1
: 𝛽
1
: 𝛽
1
+ 𝛽
+ 𝛽
2
2
+ . . . +𝛽
+ . . . +𝛽
9
9
= 0
≠ 0
𝐻
0
: The macro factors have no effect on COST_ENG
𝐻
1
: At least one of the macro factors has an effect on COST_ENG
Hypothesis 3: Cost of Fitter
𝐻
0
: 𝛽
1
𝐻
1
: 𝛽
1
+ 𝛽
2
+ . . . +𝛽
9
+ 𝛽
2
+ . . . +𝛽
9
= 0
≠ 0
𝐻
0
𝐻
1
: The macro factors have no effect on COST_FIT
: At least one of the macro factors has an effect on COST_FIT
28

Table 1 - Correlation between the macro factors in the World regression models; calculations below are based on data observations in 188 countries. The values are adjusted for Robustness. The table shows strong correlation between AW_WAGE and GDP/CAP (0,9332) and the two should therefore not be tested in the same regression model.
AGRI_ UNEMP_ BMI_PPP GDP/CAP GDP_DEF COL_IN EX_RATE SERV_% POVU_2_ AW_WAGE
GDPCAP
GDP_DEF
AGRI_% 1.0000
UNEMP_% -0.1121 1.0000
BMI_PPP 0.2596 0.0686 1.0000
-0.5175 -0.2308 -0.1957
-0.0966 0.0055 -0.0786
COL_IN
EX_RATE
Serv_%
POVU_2_
-0.1909
-0.5472
0.7741
-0.0196
-0.3474 0.2064
0.0604
-0.1929
-0.2102
-0.2977
-0.2132 0.2967
AW_WAGE -0.5428 -0.1257 -0.1368
1.0000
0.1126
0.5239
0.2775
0.3957
-0.7154
0.9332
1.0000
0.0906
0.0232
0.0110
-0.0521
-0.1300
1.0000
0.2691
0.1819
1.0000
0.3457
0.0485
0.7735
-0.3452
0.2102
AGRI_% = Percentage of the population working in the agriculture sector
UNEMP_% = Percentage of the population unemployed
BMI_PPP = Big Mac index – Purchasing Power Parity adjusted
GDP/CAP = The GDP/ Capita in Dollar
GDP_DEF = The GDP Deflator
COL_IN = Cost of Living index, with USA as base country
EX_RATE = Exchange rate, with SEK as base currency
POVU_2_% = Percentage of the population earning less than 2 dollars/day
SERV_% = Service sectors percentage part of the GDP
AV_WAGE = Average wage/hour
1.0000
-0.5578
0.3777
1.0000
-0.4478 1.0000

Table 2 - Correlation between the macro factors in the Flexlink regression models; calculations below are based on the 19 target countries. The values are adjusted for Robustness. The table shows high correlation between the independent variables POVU_2_ and AGRI_, and the two should therefore not be tested in the same regression models.
AGRI_%
AGRI_
1.0000
UNEMP_
UNEMP_
BMI_PPP
GDP/CAP
GDP_DEF
AV_WAGE
EX_RATE
-0.2606 1.0000
0.3961 0.3729
-0.5854 0.1708
0.0553 0.0142
-0.7406 0.1139
-0.0421 -0.2340
ENG_COST -0.6382 0.0420
FIT_COST
POVU_2_
-0.8740 0.1163
0.9168 -0.1516
BMI_PPP
1.0000
-0.2356
-0.0475
-0.2981
-0.2862
-0.2918
-0.3797
0.5278
GDPCAP
1.0000
-0.1924
0.5044
0.0680
0.4465
0.4941
-0.5646
GDP_DEF
1.0000
-0.3334
0.1984
-0.3226
-0.1295
0.0487
AV_WAGE
1.0000
0.0881
0.9333
0.9298
-0.5572
EX_RATE
1.0000
0.1232
0.1159
-0.0291
ENG_COST
1.0000
0.9492
-0.5186
FIT_COST
1.0000
-0.7258
POVU_2_ SERV_
1.0000
0.2570 0.7261 0.8952 -0.7094 1.0000 SERV_% -0.8478 0.1152 -0.5336 0.4259 -0.0611
AGRI_% = Value added as a percentage of GDP
UNEMP_% = Percentage of the population unemployed
BMI_PPP = Big Mac index – Purchasing Power Parity adjusted
0.7893
GDP/CAP = The GDP/ Capita in Dollar
GDP_DEF = The GDP Deflator
AV_WAGE = Average wage
EX_RATE = Exchange rate, with SEK as base currency
ENG_COST = Average Engineer cost/hour at Flexlink
FIT_COST = Average Fitter cost/hour at Flexlink
POVU_2_% = Percentage of the population earning less than 2 dollars/day
SERV_% = Service sectors percentage part of the GDP
30

Table 3. Regressions with Cost Of Living as dependent variable
The sample consists of 188 countries 2001-2011. The number of years is 1880. Accounting data, economic data and exchange rate data are collected from Thomson’s DataStream service.
The Big Mac Index is collected from The Economist. Agriculture data, unemployment data and poverty $ 2 are collected from World Bank. The dependent variable is Cost of Living
(COL_Index), collected from the U.S. Department of State, Bureau of Administration. We average all variables and run the regression on all 188 observations when enough data matching the observations are available. AGRI_% is equal to the value added as a percentage of GDP (in a specific country). UNEMP_% is equal to the percentage of the population (in a specific country) unemployed. EX_RATE is equal to the exchange rate with Swedish Krona as base currency. BMI_PPP is equal to the PPP adjusted Big Mac index with USA as base country. GDP/CAP is equal to GDP per capita measured in Swedish Krona. AW_WAGE is the average total wage in the country. GDP_DEF is almost the same as BMI but with adjusted goods baskets depending on the countries preferences and supply. SERV_% is equal to the percentage working in the service sector. POVU_$2_% is equal to the percentage earning less than 2 dollars a day. The confidence interval is set to 95 %. The degrees of freedom are 1870.
The bold numbers are the coefficients, and the values in parentheses are the p-values. In the regressions, Huber (1967) –White (1980), standard errors are used to adjust for clusters.
COST OF
LIVING INDEX M1 M2 M3 M4 M5 M6 M7
AGRI_ %
-2.516769 .2560752 -2.548741 -4.080629
(0.000) (0.326) (0.000) (0.000)
UNEMP_ %
-.3172955
(0.633)
BMI_PPP
-.0002274 .0157492 -.0000752 .0000175
(0.916) (0.410) (0.965) (0.995)
GDP/CAP
.0026859 .0005467
(0.000) (0.004)
GDP_DEF
.4344633 .4122582 .3653433
(0.141) (0.319) (0.188)
AV_WAGE
.6879482 1.063822 1.015382
(0.000) (0.000) (0.000)
EX_RATE
.3390573
(0.337)
SERV_%
.2551647
(0.659)
POVU_$2_%
-.2782521 .199643
(0.122) (0.061)
R2
N
0.6934 0.1619 0.1921 0.6133 0.5921 0.6446 0.5465
370 380 930 350 360 470 490
Summary : Strong correlation between the variables AW_WAGE and GDP/CAP (0,9332), and the two are therefore not tested in the same regression model. The models show that AGRI_%,
GDP/CAP and AV_WAGE have significant effects on Cost of Living.

Table 4. Regressions with Engineer Cost in Flexlink as dependent variable
The sample consists of 19 Flexlink Sales Units 2001-2011. The number of years is 190.
Accounting data, economic data and exchange rate data are collected from Thomson’s
DataStream service. The Big Mac Index is collected from The Economist. Agriculture data, unemployment data and poverty $ 2 are collected from World Bank. Wage information from
Flexlink is collected manually from each Sales Unit’s Finance Manager. The dependent variable is Cost of an Engineer hour at Flexlink (COST_ENG). We average all variables and run the regression on all or 19 observations. AGRI_% is equal to the value added as a percentage of GDP (in a specific country). UNEMP_% is equal to the percentage of the population (in a specific country) unemployed. EX_RATE is equal to the exchange rate with
Swedish Krona as base currency. BMI_PPP is equal to the PPP adjusted Big Mac index with
USA as base country. GDP/CAP is equal to GDP per capita measured in Swedish Krona.
AW_WAGE is the average total wage in the country. GDP_DEF is almost the same as BMI but with adjusted goods baskets depending on the countries preferences and supply. SERV_% is equal to the percentage working in the service sector. POVU_$2_% is equal to the percentage earning less than 2 dollars a day. The confidence interval is set to 95 %. The degrees of freedom are 180. The bold numbers are the coefficients, and the values in parentheses are the p-values. In the regressions, Huber (1967) –White (1980), standard errors are used to adjust for clusters.
COST_ENG M1 M2 M3 M4 M5
AGRI_ % -21.63403
(0.003)
UNEMP_ % -2.383902
(0.894)
BMI_PPP
GDP/CAP -.0000599
(0.804)
.0000772
(0.842)
-.0004061
(0.991)
.0003627
(0.352)
GDP_DEF -.0425837
(0.811)
-.868106
(0.01)
AV_WAGE
EX_RATE
2.211463
(0.000)
POVU_$2_%
-2.609293
(0.620)
14.5916 SERV_%
R2 0.8720
190
(0.000)
.1550995
(0.905)
0.5316
190
0.4912
190
-5.550969
(0.091)
0.2703
190
13.74858
(0.000)
1.042789
(0.554)
0.5542
190 N
Summary : Strong correlation between the variables POVU _$2_% and AGRI_% ( 0.9168
), and the two are therefore not tested in the same regression model. The models show that AGRI_%,
SERV_% and AV_WAGE have significant effects on Cost of Engineer.
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Table 5. Regressions with Fitter Cost in Flexlink as dependent variable
The sample consists of 19 Flexlink Sales Units 2001-2011. The number of years is 190.
Accounting data, economic data and exchange rate data are collected from Thomson’s
DataStream service. The Big Mac Index is collected from The Economist. Agriculture data, unemployment data and poverty $ 2 are collected from World Bank. Wage information from
Flexlink is collected manually from each Sales Unit’s Finance Manager. The dependent variable is Cost of a Fitter hour at Flexlink (COST_FIT). We average all variables and run the regression on all or 19 observations. AGRI_% is equal to the value added as a percentage of
GDP (in a specific country). UNEMP_% is equal to the percentage of the population (in a specific country) unemployed. EX_RATE is equal to the exchange rate with Swedish Krona as base currency. BMI_PPP is equal to the PPP adjusted Big Mac index with USA as base country. GDP/CAP is equal to GDP per capita measured in Swedish Krona. AW_WAGE is the average total wage in the country. GDP_DEF is almost the same as BMI but with adjusted goods baskets depending on the countries preferences and supply. SERV_% is equal to the percentage working in the service sector. POVU_$2_% is equal to the percentage earning less than 2 dollars a day. The confidence interval is set to 95 %. The degrees of freedom are 180.
The bold numbers are the coefficients, and the values in parentheses are the p-values. In the regressions, Huber (1967) –White (1980), standard errors are used to adjust for clusters.
COST_FIT M1 M2 M3 M4 M5 M6 M7
AGRI_ %
UNEMP_ %
BMI_PPP
GDP/CAP
GDP_DEF
AV_WAGE
EX_RATE
SERV_%
POVU_$2_%
R2
N
-19.30471
(0.004)
-.0056208
(0.565)
.0001541
(0.629)
0.5769
9.576969
(0.534)
-.0431647
(0.664)
.0005871
(0,104)
0.3365
-31.40349
(0.026)
-.0175516
(0.575)
3.603382
(0.408)
0.5928
.0003022
(0.238)
-.628382
(0.947)
.0198002 -.0081183
(0.316) (0.582)
.0000788
(0.707)
1.624974
(0.000)
.9061424
(0.778)
10.74919 13.4006
(0.000) (0.000)
0.6779 0.6541 0.8593
1.4876
(0.000)
4.388631
(0.088)
-1.594228
(0.062)
190 190 190 190 190 190 190
Summary : Strong correlation between the variables POVU _$2_% and AGRI_% ( 0.9168
), and the two are therefore not tested in the same regression model. The models show that AGRI_%,
SERV_% and AV_WAGE have significant effects on Cost of Fitter.
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6.3.1 Cost of Living Models
Basically, to be able to make an accurate statistic analysis, all the variables were tested for correlation; See table 01. The result of the correlation showed that all variables except (AW_WAGE; GDP/CAP) were insignificantly correlated. As a result of the correlation test, the correlating variables will not be tested against each other in the same regression model. Between (AW_WAGE; GDP/CAP) was a strong positive correlation of +0,9332, which was not an unexpected result, since a high average wage will directly affect and increase the GDP/CAP in the country.
The regressions with the large data were tested for heteroscedasticity (White 1980), and a robust estimation was preformed and the results were accordingly adjusted.
There was a maximum of 188 observations. The regressions showed that GDP/CAP and AV_WAGE have significant positive effects on the Cost Of Living Index. That means that a land with a higher GDP/CAP (higher AV_WAGE) has higher Cost Of
Living, compared to a country with lower GDP/CAP (lower AV_WAGE).
By testing the regression for a big dataset, it was possible to prove that agriculture has a significant negative effect on the Cost Of Living Index. Three out of four tests showed that AGRI_% has a significant negative impact on COL. Those 3 tests show low p-values (0,000; 0,001; 0,006) and relatively high 𝑅 2
(0,6934; 0,6446;0,5465). The three first tests could be seen as much more reliable sources than the fourth test that has a 𝑅 2 of 0.1921. The result could be misleading in M3 because of the high correlation between POV_% and AGRI_% (0.7741). The negative effect of AGRI_% implies that, the higher percentage of GDP that comes from agriculture, the lower the cost of living.
The remaining variables cannot be statistically proven to have an effect on the
COL_Index. UNEMP_ % may not be significant due to subsidy policies and social safety nets in specific countries, which affects the impact of unemployment. BMI_PPP and GDP_DEF are measures of inflation, which should be controlled by the government, to remain at reasonable levels and not negatively affect the economy. The other factors cannot be fully explained in this examination.
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The result of the regression analysis proved that AV_WAGE, GDP/CAP and AGRI_% have a significant impact on the Cost of Living Index; therefore the null hypothesis
( hypothesis 1) can be rejected.
6.2.2 Cost of Engineer Models
At first, to make a proper statistical analysis, the variables were tested for correlation.
All variables except (AGRI_%; POVU_2_%) were insignificantly correlated. The correlating variables will not be included in the same model. Between the (AGRI_%;
POVU_2_%) was a positive correlation of +0.9168. This is strengthened by World
Bank’s (2013) findings, that the poorest people in the world live in rural areas, where the primary income is agriculture.
The regressions were tested for heteroscedasticity (White, 1980), a robust estimation was performed and the results were accordingly adjusted. There are only 19 observations and 30 are required to be absolutely statistically safe, therefore there might be errors that affect the conclusions. AW_WAGE is significant in the models tested and has a positive effect on ENG_COST, explained by wage being a factor in the total cost. Another significant variable in the models tested is AGRI_% that has a positive effect in M3 but a negative effect in M6 on ENG_COST. A possible explanation is that AGRI_% effect on COST_ENG is dependable on the specific country and therefore provides ambiguous results. The variable SERV_% has an positive effect on ENG_COST and is significant in 2 out of 2 models , M2 and M5.
SERV_% has probably an effect on COST_ENG but it is not completely statistically proven.
The reaming six variables cannot be statistically proven to have an effect on
ENG_COST. UNEMP_ % may not be significant due to subsidy policies and social safety nets in the specific which affects the impact of unemployment. Both BMI_PPP and GDP_DEF are measures of inflation which should be controlled by the government, to remain at reasonable levels and not negatively affect the economy.
That GDP/CAP is not significant as in the World regression might be because of our smaller sample in ENG_COST regression, since it should have a similar effect as wage. Likewise, POVU_$2_% should have an effect if AGRI_% is significant. The market adjusts for arbitrage and EX_RATE should not be a problem and have an effect on ENG_COST.
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The result of the regression analysis proved that AV_WAGE, SERV_% and AGRI_% have significant impact on the Cost of Engineers; therefore can the null hypothesis
( hypothesis 2) be rejected. The dependent variable is strongly described in all models except M4 according to 𝑅 2
.
6.2.3 Cost of Fitters Models
To be statistically accurate the variables were tested for correlation. All variables except (AGRI_%; POVU_2_%) were insignificantly correlated. The correlating variables will not be included in the same model. The correlation between (AGRI_%;
POVU_2_%) is strengthen by World Bank’s (2013) findings, that the poorest people in the world live in rural areas, where the primary income is agriculture.
The regressions were tested for heteroscedasticity (White, 1980), a robust estimation was performed and the results were accordingly adjusted. There are only 19 observations and 30 are required to be absolutely statistically safe, therefore there might be errors that affect the conclusions. AW_WAGE is significant in the models tested and has a positive effect on FIT_COST in M6 and M7, explained by wage being a factor in the total cost. Another significant variable in the models tested is AGRI_% that has a negative effect in M1 and M3 on FIT_COST probably due to that less developed countries have more agriculture and therefore lower costs. The variable
SERV_% has a positive effect on FIT_COST and is significant in the models, M4 and
M5. The reason can be that countries with a high service percentage tend to be more developed.
The remaining six variables cannot be statistically proven to have an effect on
ENG_COST. UNEMP_ % may not be significant due to subsidy policies and social safety nets in the specific, which affects the impact of unemployment. Both BMI_PPP and GDP_DEF are measures of inflation, which should be controlled by the government, to remain at reasonable levels and not negatively affect the economy. That GDP/CAP is not significant as in the World regression might be because of our smaller sample in
ENG_COST regression, since it should have a similar effect as wage. Likewise
POVU_$2_% should have an effect if AGRI_% is significant. The market adjusts for arbitrage and EX_RATE should not be a problem and have an effect on ENG_COST.
The dependent variable is strongly described in all models except M2 according to 𝑅 2
.
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The graphs below show the results from the Flexlink interviews, of selected questions.
The questions have a response scale of 1-5, where 1 is Low and 5 is High. Question 6.6 is a YES or NO question. All questions are attached in Appendix I.
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38

The first part of the interviews, investigates whether it is possible or not, to distinguish any specific service characteristics between engineers and fitters.
By observing the Graph 1.3, it is possible to distinguish a trend among the answers.
The 7 respondents have all chosen numbers between 3 and 5(agree with the statement), that the service of a Fitter is quite advanced, and that the work requires qualified employees with specific knowledge to fulfil the assignments. The same question was also given for the characteristics of an Engineer at Flexlink (question 2.3). The answers showed that Engineers are considered to provide an even more advanced service when comparing to Fitters. The reasoning can be strengthened and proved by looking at the complementary comments that has been given from the respondents. The respondents have written that the work of a Fitter is not very advanced, rather easily performed without firm specific knowledge as long as there are team leaders. It is possible to reduce the hours worked with increased knowledge and experience of Flexlink’s parts/products and modules. Experience together with Flexlink specific knowledge, results in higher efficiency and more well performed work.
Regarding Engineers, the comments on question 2.3 and 2.4 highlighted another important matter. The core competences at Flexlink are application and design, executed by the more educated Engineer. The core competences are thereby captured by the Engineers, and that would support the assumption that the Engineers’ work are much more advanced compared to the work of a Fitter. The Engineers at Flexlink undergo continuous internal training, to develop the competence standard.
Flexlink’s projects are customer specific and no jobs are alike, therefore the service is not standardized. This means that prices vary with respect to the nature of the projects.
It was confirmed in question 6.6 that the sales units regularly use price discrimination; as a result of the markets’ high price elasticity (question 5.1 and 5.2), the adaptions are necessary in order to be competitive.
Question 3.3 indicates that the market is very price sensitive and from the interview questions there are proof of extremely tough competition in some of the markets. The competition was mainly dependent on price competition, since it was quite easy for the
39

customers to find comparable solutions from a wide range of companies. It appears that, depending on the pricing of the services, Flexlink can either lose or win a job. As a result of the service being a main component in the delivery of a project, it is crucial to set the correct price in order to stay competitive. This is not always true, according to Flexlink Malaysia, the wage level is much lower in Asia than in Europe and therefore for the former, wages are of little importance.
From the PPP theory follows that the prices should be the same after the exchange rate has been adjusted for, but there are often price differences unexplained by the theory.
There are specific problems relating to services, according to IIHP characteristics, that affects pricing. The focus of the analysis is the main issues for PPP to hold; primary international trade and wage that complicate the standardization of service prices.
International Trade
The first obstacle for services to be freely traded internationally, is that the seller and the customer must often be at same place at the same time for the service to be performed, the inseparable characteristic. Unlike a commodity, customer relations are very important and the basis for the customers’ perception of the service. However, this is very subjective and there might be crucial cultural differences in the societies regarding power-distance uncertainty avoidance, long-term orientation, femininity/masculinity, individualism/collectivism (Hofstede, 2001). The PPP theory requires standardized services in order to compare prices e.g. Big Mac hamburgers, since the perception of services varies between countries, it is difficult to determine what is actually sold. In a poor country, a service can be seen as more advanced than in a more developed country. How easily substituted the service is and the competition, affects the willingness to pay. In poor countries, a specific service might be regarded as hi-tech and therefore monopolized or oligopolized due to the lack of competition in the advanced sector. Less competition reduces the negotiation power of the price, and as the supply/demand ratio decreases, the prices rise.
One of the main concerns regarding the pricing problem is that the service is intangible, and what is sold is a contract of a performance. The performances’ results
40

are dependable on both knowledge and cultural background of the customers, and it is difficult to demonstrate the quality of a service that is not material. The difficulties of selling a service increase the further away the location of the customer, due to reputation of the seller and differences in contexts. How the service is perceived can be linked to heterogeneity, as the service is perceived differently and reviewed from subjective results, the standardization of pricing becomes problematic. Naturally, different service outcomes are to be expected as the work is done by people, whom may have different daily statuses or skills. The level of satisfaction is all about what the customers expect. How much the customer has "participated" in the process, and the requirements and specifications incorporated in the service affects the price, the level of customization. Customized services cannot be standardized and have the same pricing. The law of one price is therefore difficult to inflict on services since standardization is rarely possible.
Trade in services is also difficult regarding storage, since the service disappear with the performance. This is very obvious regarding installation services; when the installation is complete, the service is over and the only thing that might be left is newfound knowledge for the observers of the performance. The attainment of knowledge is more challenging if the level of education in a country/company is low. There might be few with enough skills to learn the advanced information and perform the service on their own, making the service seller non-replaceable. Since customers often want customized services, prefabrication is impossible, making it harder to adapt to business cycles. A great difference compared to goods adaption to conjuncture, services cannot take advantage of booms by overproducing due to the non-storage aspect.
For services traded to be internationally available, the people behind the services are required to be easily moved. This is not always the case, to be able to cross countryborders, a visa or a proper work permit is necessary. All countries do not allow unlimited labor immigration, since services are based on human capital; international trade is restricted and thus violating PPP. There might be language barriers in some countries where no common language is spoken, causing communication problems and the perception of the service. How easily workers are willing to move abroad are also dependent on the working climate; minimum wages and unions. Culture barriers have also an effect,t since different customs and views might cause disputes and
41

unpleasantness; such issues are religions, women in the workforce or racial discrimination. Even within the same company’s affiliates, these problems might arise due to business culture, how things are done and hierarchy issues. There are also added transaction costs such as relocation, housing and shipping. The obstacles to overcome in order to trade internationally are proof against the PPP and LOP since the basis of the theories is free trade for adjusted price and ceased arbitrage situations.
Wage
There are a range of services, all with different specifications and prerequisites.
Consequently, all employed in the service sector, cannot be bunched together and have the same wage. The necessary background can vary, from apprentice based to a
University master. More advanced services require higher education and therefore an appropriate wage. How advanced a service is perceived by the costumers, contributes to the salary’s size. This is a value-based view of how much the service is worth to the customer, and can even be based on a personal relationship between the worker and the customer. Wage is also dependent on how advanced the service is and if the worker is easily replaced due to sector or company specific knowledge. Accounting based costs that might affect wage are rent and electricity. The supply/ demand ratio can also affect wage as well as the unemployment ratio. For the PPP theory to hold, the wages should be appropriate to the cost of living and exchange rates should compensate for the differences in purchasing power. In the real world, this is unlikely, since there are too many factors affecting wage that are hard to control for. Wage is therefore not a perfect fit for the PPP theory’s assumptions.
To begin, there are extensive studies on goods pricing, but the research often fails to cover services. In a world where services account for an increasing percentage of the economies, we have seen the need to further research the drivers of service pricing.
The focus is whether prices can be standardized or if an adaption to local markets is necessary. In the background to this issue, the PPP theory states that countries should have equal purchasing power after adjusting for exchange rates. Nonetheless, even if this works in theory, the factors not incorporated in the exchange rate refutes the standardization of prices according to PPP.
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The literature confirms that the PPP theory does not hold for service pricing, a consequence of the services’ unique features. A generally accepted service definition is the IIHP characteristics. The characteristics Intangibility, Inseperability, Heterogenity,
Perishability; complicate and preclude the standardization of services for trade. In fact, the traded services must be standardized for an international price comparison to be possible. From our findings the grade of service performance is very subjective and often dependent on background as well as culture, both company- and country based.
Furthermore, the wages in different countries varies and can hardly give the same purchasing power for services. If standardization is solely based on adjusting for exchange rate, purchasing power parity will differ among countries. This further strengthens that implementing standardized prices are difficult and probably a noncompetitive strategy.
The empirical findings are in line with the literature regarding the problematic standardization of service pricing. In order to empirically estimate the results, we created models for our three hypotheses, testing for the validity of the macro variables.
The results are unanimous; more than one macro factor has an effect in Hypothesis 1-3 and the null hypothesis can be rejected in all cases. Wage and AGRI_% are significant in all models for the dependent variables (Cost of Living; Cost of Engineers; Cost of
Fitters), and SERV_% is significant in the models for two of the dependent variables
(Cost of Engineers; Cost of Fitters) an GDP/CAP is significant in the models for one of the dependent variables (Cost of Living). The results are consistent and the influencing variables are accurate as applied to theory. Naturally, both GDP/CAP and AV_WAGE determines the purchasing power domestically and abroad, AGRI_% is less obvious but is consistent with higher percentage of agriculture in poorer countries. SERV_% is significant in the cost of service models as a determinant of the importance of services internationally. From our models, there is no statistical proof that EX_RATE as the sole price adjustor in PPP, has an effect on pricing. We conclude that there are too many factors, not covered by the PPP Theory that acts against an implementation of standardized pricing.
To further determine the accuracy of the findings, interviews were carried out on
Flexlink with the Finance Managers of seven sales units. The reality based findings were notably consistent with the theory and statistical results. The two services studied are engineers and fitters, of which the former are more advanced and require higher
43

education. Flexlink’s projects are customer specific and no jobs are alike, therefore the service is not standardized. This means that prices vary with respect to the nature of the projects. It was confirmed that the sales units regularly use price discrimination; as a result of the markets’ high price elasticity, the adaptions are necessary in order to be competitive. The case study does not support an international price standardization, due to the variety of services offered by Flexlink.
Finally, the paper highlights important issues regarding service pricing and contributes to an increased awareness. The analysis methodology is based on our interpretations of relevant economic aspects. First, the service needs to be standardized in order to compare prices. For the PPP Theory to hold, prices must be adjusted for more factors than the exchange rate in order to achieve the same purchasing power internationally.
Furthermore, pricing standardization is difficult since the factors impacts on local markets are difficult to determine. A local price adaption is the most strategic approach to cope with the differences. We conclude that a standardization of service pricing is not feasible based on the findings.
As has been described in the paper, the present study contains some interesting findings about the factors affecting service pricing and Cost of Living. However, there are some limitations that limit the power of this thesis analysis. Firstly, the data used for the Flexlink regression includes only 19 sales units within one company in the conveyor industry. Because of the few observations, and that only one company and one sector is studied, we cannot extend the results of this study to other industries.
Furthermore, in order to study differences across countries and across industries and their effects on service pricing, more companies in more countries should be included in the study. Bigger datasets would give a more accurate result to which macro factors that affect service pricing on a global level.
One other restriction of the study is that we have only used one theory (PPP). There are probably other theories that could be applicable to explain the service pricing that we did not use in this paper. We have not been able to find any similar studies in the field of factors affecting service pricing (other than accountings studies), and the
44

subject is relatively unexplored, which has had a serious impact on the conclusions since we lack a reference paper. Most of the literature regarding pricing, concern pricing of products, which could have affected the outcome of our study. The paper is written by bachelor students, as a consequence there might be lack of knowledge and execution in comparison to an e.g a postgraduate.
We suggest that further research is made on bigger datasets that includes more companies in different industries, in more than thirty countries. By comparing different industries and different areas around the world, the researcher would maybe find other possible trends regarding service pricing. It would also be interesting to measure the level of competition within an industry and see how that affects service pricing.
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Emphasis on Agriculture for Development . [online] Available at: http://web.worldbank.org/WBSITE/EXTERNAL/NEWS/0,,contentMDK:215133
82~pagePK:64257043~piPK:437376~theSitePK:4607,00.html [Accessed: 14 May
2013].
Worldbank.org (1990) Poverty Overview . [online] Available at: http://www.worldbank.org/en/topic/poverty/overview [Accessed: 14 May 2013].
50

Flexlink Internal Information Power Point (2013), 1(1)
Melanie Saugere , Finance Manager, Flexlink France
Neus Anglès
, Financial Controller, FlexLink Spain
Radosław Masztalerz
, Financial Controller, FlexLink Poland
Susanne Lager , Finance Manager, Flexlink Sverige
Monika Kocsner , Finance Manager, Flexlink Hungary
Robyn Kubeil , Finance Manager Flexlink Australia
Cherry Lee , Finance Manager Flexlink Malaysia
51

Table 6- Significance between the factors in World regression, adjusted for Robust
AGRI_ UNEMP_ BMI_PPP GDPCAP GDP_DEF COL_IN EX_RATE SERV_ POVU_2_ AW_WAGE
AGRI_ 1.0000
UNEMP_ -0.1121
0.1780
BMI_PPP 0.2596
0.0631
GDP/CAP -0.5175
0.0000
GDP_DEF -0.0966
0.2157
COL_IN -0.1909
0.0189
EX_RATE -0.3474
0.0281
SERV_% -0.5472
0.0000
POVU_2_ 0.7741
0.0000
AW_WAGE -0.5428
0.0019
1.0000
0.0686
0.6255
-0.2308
0.0069
0.0055
0.9459
-0.0196
0.8237
0.2064
0.1841
0.0604
0.4693
-0.2132
0.0413
-0.1257
0.4929
0.0906
0.2683
0.0232
0.8827
0.0110
0.8878
-0.0521
0.6030
-0.1300
0.4856
1.0000
1.0000
0.1126
0.1702
0.5239
0.0000
0.2775
0.0830
0.3957
0.0000
-0.7154
0.0000
0.9332
0.0000
1.0000
-0.1957
0.1686
-0.0786
0.5797
-0.1929
0.1708
-0.2102
0.2185
-0.2977
0.0321
0.2967
0.1252
-0.1368
0.4793
0.2691
0.0931
0.1819
0.0254
0.0485
0.6281
0.7735
0.0000
1.0000
1.0000
0.3457
0.0289
-0.3452
0.1606
0.2102
0.2831
1.0000
-0.5578 1.0000
0.0000
0.3777 -0.4478
0.0396 0.1944
1.0000

Table 7 - Significance between the factors in Flexlink’s regression, adjusted for Robust
AGRI_ UNEMP_ BMI_PPP GDPCAP GDP_DEF AV_WAGE EX_RATE ENG_COST FIT_COST POVU_2_ SERV_
AGRI_
UNEMP_
BMI_PPP
1.0000
-0.2606 1.0000
0.2812
0.3961 0.3729
0.0932 0.1159
1.0000
GDPCAP -0.5854 0.1708 -0.2356
0.3316
1.0000
0.0085 0.4846
GDP_DEF 0.0553 0.0142
0.8221 0.9541
AV_WAGE -0.7406 0.1139
-0.0475
0.8467
-0.2981
-0.1924
0.4301
0.5044
1.0000
-0.3334 1.0000
0.2151 0.0277 0.1631 0.0003 0.6425
EX_RATE -0.0421 -0.2340
0.8642 0.3350
ENG_COST -0.6382 0.0420
0.0033 0.8644
FIT_COST -0.8740 0.1163
0.0001 0.7052
POVU_2_ 0.9168 -0.1516
0.0000 0.5355
SERV_ -0.8478 0.1152
0.0000 0.6387
-0.2862
0.2349
-0.2918
0.2254
-0.3797
0.2006
0.5278
0.0202
-0.5336
0.0186
0.0680
0.7821
0.4465
0.0553
0.4941
0.0861
-0.5646
0.0118
0.4259
0.0691
0.1984
0.4156
-0.3226
0.1780
-0.1295
0.6732
0.0487
0.8431
-0.0611
0.8039
0.0881
0.7199
0.9333
0.0000
0.9298
0.0000
-0.5572
0.0132
0.7893
0.0001
1.0000
0.1232
0.6152
0.1159
0.7062
-0.0291
0.9058
0.2570
0.2881
1.0000
0.9492
0.0000
-0,5186
0.0229
0.7261
0.0004
1.0000
-0,7258
0.0050
0.8952
0.0000
1.0000
-0.7094
0.0007
1.0000
53

54