The impact of consumer credit protection on the
consumer credit interest rate across EU-19 from 2005
to 2018
Faculty: Governance and Global Affairs
L.J. (Lauren) Haayen Student number: s2036215 Supervisor: Dr. P.W. van Wijck
FOREWORD
With this thesis my time as a master student comes to an end. Everything I have learned from Economic & Governance specialisation of the Master in Public Administration program at the Leiden University will be the backbone of the rest of my career. This thesis enlarged my knowledge on the impact of the Consumer Credit Directive (2008), on the economic growth and consumer welfare amongst the member states of the Eurozone. Looking back on this thesis trajectory I feel that I overcame several challenges and I am proud of the final result. I would like to thank my academic supervisor Dr. P.W. van Wijck for the guidance during my master thesis. His advice, knowledge and experience were important for this research. Finally, I would like to thank my family and friends for their support during my thesis trajectory. I hope you will enjoy reading this thesis and I hope that this research can contribute to the ever-growing knowledge of the European economy.
Table of Contents FOREWORD ... 2 LIST OF TABLES ... 4 LIST OF FIGURES ... 5 MAIN ACRONYMS/ABBREVIATIONS ... 6 1. Introduction ... 7 1.1 Research question ... 8
1.2 Academic and social relevance ... 9
1.3 Structure of thesis ... 10
2. Case Description: Consumer Credit Directive (2008) ... 12
2.1 Historical content ... 12
2.1.1 The Consumer Credit Directive (87/102/EEC) ... 12
2.1.2 Consumer protection ... 13
2.1.3 Consumer credit market ... 13
2.1.4 Interest rate ... 16
2.2 Consumer Credit Directive (2008) ... 17
2.2.1 The purpose ... 17
2.2.2 The relevant charges ... 18
2.2.3 Implementation of the Consumer Credit Directive (2008) ... 20
2.2.4 Main definitions ... 22
2.2.4.1 Credit agreements………22
2.2.4.2 Credit standards, terms, and conditions………...22
3. Theoretical Framework ... 23
3.1 Difference between the interest rates paid by consumers and by banks ... 23
3.2 Economic forces influencing the difference in interest rates ... 24
3.2.1 Market concentration ... 24
3.2.2 Inflation ... 26
3.3 Summary of expected hypotheses ... 28
4. Research Design and Data ... 29
4.1 Models to test the hypotheses ... 29
4.1.1 Panel data analysis ... 29
4.2 Data sources and operationalisation of variables ... 31
4.2.1 Dependent variable: Gap between the consumer credit interest rate and interest rate of banks ... 33
4.2.2 Independent variable: Level of implementation in the Eurozone ... 36
4.2.3 Lagged independent variables: Level of implementation ... 39
4.2.4 Control variables: Market concentration and inflation ... 39
5. Results and Analysis ... 41
5.1 Panel data regression results and description ... 41
5.1.1 Choice of model ... 41
5.1.2 Main results ... 41
5.1.2.1 Description of the results of model 1, 2, and 3………....42
5.1.2.2 Description of the results of model 4, 5, and 6………43
5.2 Empirical analysis and interpretation ... 44
6. Conclusion ... 46
7. Discussion ... 47
7.1 Future research and policy recommendation ... 48
8. Appendices ... 49
Appendix A ... 49
Appendix B ... 51
Appendix C ... 52
LIST OF TABLES
Table 2.1 Overview of the articles stated in CCD 2008 that needed 21
to be transposed into the national law of the EU-19
Table 3.1 The expected hypotheses 28
Table 4.1 The summary of expected hypotheses 30
Table 4.2 Operationalisation measurements 33
Table 4.3 Comparative table including the dates of the national transposition 38
that enabled legislative change of the CCD 2008 in the EU-19
Table 4.4 Summary statistics 40
Table 5.1 Panel data fixed effect (within) regression results 42
Table 8.1 Description of the articles, concerning section Transported 49
into National Law, as described in the CCD 2008
Table 8.2 Description of the articles, concerning section: Clarification 50
of terms in the National laws, as described in the CCD 2008
Table 8.3 Description of the articles, concerning section: Choice of Law 50
Provisions, as described in the CCD 2008
Table 8.4 Description of the articles, concerning section: Exclusion from 51
Scope, as described in the CCD 2008
Table 8.5 Panel data fixed effect (within) regression with lagged variables 52
results
LIST OF FIGURES
Figure 1.1 Moment of entry into Euro-area 9
Figure 2.1 Credit for consumption amongst fourteen Euro-area households 15
reported by MFI, excluding ESCB in the Eurozone, 2005 to 2008
Figure 2.2 Credit for consumption amongst five 5 Euro-area households 16
reported by MFI, excluding ESCB in the Eurozone, 2005 to 2008
Figure 4.1 The difference in interest rates for households and the Euribor 35
(legislative change in June 2008 and the deadline of transposing the CCD 2008 into national law in May 2010)
MAIN ACRONYMS/ABBREVIATIONS
Acronym ExplanationAPR: Annual Percentage Rate CCD: Consumer Credit Directive
EU: European Union
ECB: European Central Bank Euribor: Euro Interbank Offered Rate HHI: Herfindahl-Hirschman Index
1. Introduction
Consumer credit aims to encourage economic growth and consumer welfare since consumers can be granted loans for mainly personal consumption of goods and services (ECB, 2016). Simultaneously, consumer credit entails uncertainty for lenders and the risk of fraud or bankruptcy for consumers. As a result of an increase in the various types of credit and consumer credit agreements, member states of the European Union (EU) initiated their own level of protection since the original EU protection did not apply well to these new types of credit. Owing to the result that the level of protection amongst the different member states diverged from the original directive of the EU, this led, according to the European
Commission, to a distortion of competitiveness across the EU, limiting the cross-border supply of consumer credit, which disrupts the demand for goods and services (Kösters, Paul, & Stein, 2004, p. 84).
Due to various legal procedures and provisions in the banking and financing sector, the European Commission noted that EU consumers did not experience the same levels of protection. It considered that the existing legal framework should be reviewed to allow consumers and businesses to enjoy a harmonised market (Kösters et al., 2004, p. 84).
Given these circumstances, the European Parliament and Council adopted the new Consumer Credit Directive (CCD) 2008/48/EC (Nwaogu, Upson, Rzepecka, Simittchieva, Bowman, Olesiak et al., 2013). The ambition of the CCD 2008 is to enable the equal application of legislations concerning consumer credit agreements in all the European member states (European Commission, 2008, p. 71). In this respect, consumer information is considered to be the most important measure of this directive to ensure that the consumer is informed of the advantages and disadvantages of the credit agreement.
Banks use interest rates to cover account costs; consumers who want to borrow money from the bank must pay the interest rate in order to spend money (Heakal, 2019). As
mentioned, the CCD 2008 imposes regulations and more administrative provisions,but the
extra administrative provisions are not free of charge. It is therefore questionable who will pay for these costs. Since banks use interest rates to cover account costs, it could be possible that the extra costs caused by the CCD 2008 will be passed on to the consumer, meaning that consumers will have to pay for their own protection. This could have serious unintended consequences since the demand for credit could decrease, affecting the economic growth and consumer welfare of the EU member states. It is therefore of great importance to investigate if the legislative changes concerning consumer protection that need to be transposed into the
national law of the European member states increase the costs for credit consumers. Since the aim of the directive is to increase consumer welfare, this would have the opposite effect, all at the expense of the consumers.
1.1 Research question
This research aims to answer the main question: Did the national transposition measures, introduced by the CCD (2008), increase the interest rate paid by consumers across the EU-19 from 2005 to 2018?
This study is based on monthly consumer credit interest rates and monthly interest rates paid by banks for the following nineteen member states: Austria (AT), Belgium (BE), Cyprus (CY), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (GR), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxemburg (LU), Malta (MT), Portugal (PT), Slovenia (SI), Slovakia (SK), Spain (ES), and the Netherlands (NL) (Worland, n.d.). These countries are selected for this research since they are members of the Euro-area, which makes it possible to investigate the credit market in economies using the same currency. Figure 1.1 illustrates all the member states that belong to the Euro-area, with the specific data from when the member state entered the Euro-area. It is important to take these dates into account since the thesis focusses on the Eurozone from January 2005 to January 2018.
1.2 Academic and social relevance
In the recent academic literature, research is devoted to exploring and analysing different credit markets in which differences in local competition are observed (Lee & Hogarth, 1999). The impact of the level of competition and the total effect of market concentration on interest rates are examined (Maudos & De Guevara, 2004), and a particular focus is placed on the Euro-area, in which the different economic structures are observed under the same currency (Van Leuvensteijn, Kok, Bikker, & Van Rixtel, 2008). Moreover, numerous articles focus on the impact of inflation on the interest rates for banks (Fisher, 2006).
Additional studies devote their research to the default risk of the credit applicants caused by the adverse selection problem that arises from informational asymmetry (Igawa & Kanatas, 1990; Bergstresser, 2001). However, only some studies concentrate on the historical
member state member since
Austria 1 January 2002 Belgium 1 January 2002 Cyprus 1 January 2008 Estonia 1 January 2011 Finland 1 January 2002 France 1 January 2002 Germany 1 January 2002 Greece 1 January 2002 Ireland 1 January 2002 Italy 1 January 2002 Latvia 1 January 2014 Lithuania 1 January 2015 Luxembourg 1 January 2002 Malta 1 January 2008
The Netherlands 1 January 2002
Portugal 1 January 2002
Slovenia 1 January 2007
Slovakia 1 January 2009
Spain 1 January 2002
Figure 1. 1 Moment of entry into Euro-area Source: Worland (n.d.)
implications and debates on the ratification of the Consumer Credit Directive in the EU (Kösters et al., 2004). Finally, more recent studies focus on the implications of the European Commission consumer protection techniques that brought about unintended consequences to the disadvantage of consumers (Bar-Gill & Be-Shahar, 2013). Only a few studies concentrate on the effect of the legal choices that are made by member states on the implementation of the CCD 2008 and the impact this has on the consumer credit market in the EU (Nwaogu et al., 2013). Even though this study is related to the recent academic literature, the impact of this specific Consumer Credit Directive (2008) on the difference between the interest rate paid by consumers and that paid by banks is missing in the current academic literature and could therefore contribute to the existing research.
In summary, this research uses an economic framework to determine the impact of the policy measures that are used to implement the CCD 2008 in the nineteen member states. The timespan of this study is more recent compared to the previous studies mentioned above. This study focusses on the different CCD measures that are implemented across the nineteen member states of Eurozone to examine if the implementation of the CCD 2008 resulted in unintended consequences for consumers such as higher interest rates than those paid by banks. Therefore, this research is relevant for policymaking on both national and European levels; the relevance of the results of this research is briefly discussed in the conclusion of this paper.
1.3 Structure of thesis
The structure of the paper is as follows. The second chapter gives a description of the case study, in which the historical content of the CCD is explained. Since it is important to understand the impact of the legislative changes set in the CCD 2008 on the interest rate of the consumer, consumer protection is briefly discussed as well as the functioning of the consumer credit market in the EU-19 and the factors that can influence the interest rates. The second part of this chapter provides the reader with a review of the different provisions that are imposed by the CCD 2008 and have been adopted by the EU-19. This chapter finishes with an explanation of the main definitions and the focus of this study. In the third chapter, a literature review is conducted to identify the difference between the interest rate paid by consumers and that paid by banks and the control measures influencing the difference in these interest rates. Based on the literature review, the chapter ends with a summary of the expected hypotheses. The fourth chapter provides the research design with an explanation of the
descriptive statistics. The data analysed in this study is collected from the European Central Bank (ECB), Eurostat, and EUR-lex. Chapter 5 gives an empirical analysis and interpretation based on the results of the regression models. With regard to the theories and a succinct summary of the results, chapter 6 offers an clear answer to the research question. The limitations and the possible avenues for future research are outlined in chapter 7. Finally, chapter 8 provides the appendix, and chapter 9 gives a list of references consulted.
2. Case Description: Consumer Credit Directive (2008)
This chapter is divided into two main sections. The first section explains the relevance and existence of a consumer credit directive. The second part introduces the Consumer Credit Directive (2008) by explaining the purpose, relevant charges, implementation, and description of the main definitions.2.1 Historical content
2.1.1 The Consumer Credit Directive (87/102/EEC)
Before the new Consumer Credit Directive was introduced in 2018, the already existing Consumer Credit Directive (87/102/EEC) presented the legal foundation for consumer credit (Kösters et al., 2004, p. 84). During this period, this legal foundation had set its footprint all across the European member states, even though not all consumers of the European Union (EU) had access to consumer credit (Nwagou et al., 2013, p. 3). However, it aims to sufficiently protect consumers (Kösters et al., 2004, p. 84). The European Commission published the conditions of the directive in 1995 (Kösters et al., 2004, p. 84). In response to this publication, it became evident that member states adopted different laws and regulations that had an impact on both the opportunity of cross-border credit and competition between the different creditors in the EU (Kösters et al., 2004, p. 84; Nwaogu et al., 2013, p. 3). As a result of these findings, the European Commission composed a comprehensive comparative analysis. In the view of the European Commission, credit aims to encourage economic growth and consumer welfare since consumers can be granted loans for mainly personal consumption of goods and services (ECB, 2016). At the same time, consumer credit entails uncertainty for lenders and the risk of fraud or bankruptcy for consumers. As a result of an increase in the various types of credit and consumer credit agreements, member states of the EU initiated their own legislation in order to protect their consumers, since the original EU protection did not apply well to these new types of credit anymore. For the commission, however, this development has led to a distortion of competitiveness across the EU, limiting the cross-border supply of consumer credit, which disrupts the demand for goods and services (Kösters et al., 2004, p. 84). On the basis of the commission’s findings, it is clear that the level of consumer protection varies amongst the member states of the EU due to different legal provisions and procedures in the field of banking and finance. It considered that the existing legal framework should be reviewed to allow consumers and businesses to enjoy a
on 11 September 2002, the suggestion to establish a new directive that would increase the amount of protection for the consumers amongst the member states of the EU. While at the same time increase the development of a harmonised and well functioning credit market (Kösters et al., 2004, p. 84).
2.1.2 Consumer protection
When there is much competition within and amongst member states in the credit market, consumers benefit the most. The level of consumer protection in this situation is high because consumers can choose amongst varieties of different credit suppliers since it forces credit suppliers to offer their products at competitive prices. However, this situation is only possible with the help of regulation. To prevent the existence of monopolies, cartels, or unfair and harmful competition, regulations must contain rules that control both excess competition and too little competition (Kösters et al., 2004, p. 85). Therefore, these rules must be designed in a way that they do not hinder competition but ensure an efficient market. To stimulate this level of competition, consumers must choose good products over bad ones. However, this is only possible if the market is transparent. According to Kösters, Paul, and Stein (2004): “such transparency usually requires government regulations over the supply and quality
information, consulting and so on” (p. 85). Relevant information is necessary for consumers to distinguish the quality of products or contracts, and regulation seems to be an instrument that improves the economy of a country and protect consumers. However, it is not as easy as it may seem since too much regulation can result in a market that negatively affects the economy. This negative effect is seen when, due to an overregulated market, the
administrative costs for firms rise. As a consequence, the higher administrative costs are passed on to the consumer, decreasing the demand for credit (Kösters et al., 2004, p. 85). To conclude, regulation aims to stimulate the welfare of consumers, but a balance is needed to ensure that regulation does not negatively affect the economy of the country.
2.1.3 Consumer credit market
Consumer credit can be defined as a loan that is provided by a financial institution to a consumer, the consumer can use the loan for the consumption of goods and services (ECB, 2016). In the consumer credit market, a distinction can be made between loans to households and those to private companies. The approach of different member states towards credit markets differs, affecting the competition across and within borders. However, from 1980,
deregulation was imposed to create a general framework to stimulate a single consumer credit market across Europe (Kösters et al., 2004, p. 86).
To obtain insight into the development of the consumer credit market across the Euro-area, Figures 2.1 and2.2 illustrate the amount of consumer credit relative to the Euro-area households and nonprofit institutions serving households. The unit for the collected data in both figures is expressed in billions of euros. All EU-19 are included in a monthly timeframe from January 2005 to December 2018. Since there is a large difference in the amount of credit for consumption per member state, the different developments of the EU-19 households are divided into two figures. Figure 2.1 shows the level of credit for consumption for the
households of Austria, Belgium, Cyprus, Estonia, Ireland, Finland, Lithuania, Luxembourg, Latvia, Malta, the Netherlands, Portugal, Slovenia, and Slovakia. Figure 2 shows the level of credit for consumption for the households of Germany, France, Greece, Italy, and Spain. Figure 1 shows that the level of consumer credit for households and nonprofit institutions serving households is nearly stable in Estonia, Latvia, and Lithuania and is the lowest in Malta. However, Figure 2.2 illustrates that the level of consumer credit for households and nonprofit institutions serving households is very high for Spain, Italy, and France but is the highest for Germany.
In some countries, the level of consumer credit fluctuates heavily. Figure 2.1 shows a strong rise of consumer credit in Ireland during 2008 and 2009, and after March 2010, it decreases tremendously. When the level of consumer credit starts to decrease in 2010 in Ireland, a strong increase is visible in the Netherlands; however, this stops in 2011, when the level starts to decrease again. In 2005 and 2006, the level of consumer credit increases much in Austria, and after 2006, the level decreases. The level of consumer credit in Portugal is fairly high from the period of 2008 until 2011; after 2011, the level decreases, and as of 2015, it starts to rise again. In Figure 2.2, the biggest fluctuation is seen in the level of consumer credit of Spain. After an increase of the amount of consumer credit from 2005 until 2008, the level decreases, but from 2015, it rises again. When observing the levels of Italy, France, and Germany, a rising trend is noticeable.
In sum, these figures are inserted to inform the reader and to give an impression of the different consumer credit levels for households and nonprofit institutions serving households across the Eurozone. Since the consumer credit directive discussed in this study concerns all the members of the Eurozone, it is important to understand that the effect of the regulation could differ because the amount of credit is different for all the EU-19.
Figure 2. 1 Credit for consumption amongst fourteen Euro-area households reported by MFI, excluding ESCB in the Eurozone, 2005 to 2008
2.1.4 Interest rate
As mentioned, to encourage a transparent and efficient market, regulation is necessary as long as the rules do not hinder competition (Kösters et al., 2004, p. 84). Moreover, when a market is overregulated, administrative costs for firms can rise and be passed on to the consumer (Kösters et al., 2004, p. 85). These costs could be calculated in the form of the interest rate. To analyse this perception, it is necessary to understand the reasons for changes in interest rates.
Interest rates can be seen as ‘the price of money’; put simply, when a borrower wants to spend more than he or she is capable of, the borrower will need to find someone who will lend the additional amount. When the lender agrees to lend the particular amount, an interest payment will be charged on the loaned amount. The interest payment can be seen as the cost
0 20 40 60 80 100 120 140 160 180 200 Ja n-05 Jul -05 Ja n-06 Jul -06 Ja n-07 Jul -07 Ja n-08 Jul -08 Ja n-09 Jul -09 Ja n-10 Jul -10 Ja n-1 1 Jul -1 1 Ja n-12 Jul -12 Ja n-13 Jul -13 Ja n-14 Jul -14 Ja n-15 Jul -15 Ja n-16 Jul -16 Ja n-17 Jul -17 Ja n-18 Jul -18 B il li on s of E u ro
Time
DE FR GR IT ESFigure 2. 2 Credit for consumption amongst five Euro-area households reported by MFI, excluding ESCB in the Eurozone, 2005 to 2008
of borrowing, in which the borrower pays for the risk and service of borrowing money (Financial Pipeline, 2019; Heakal, 2019).
Furthermore, both lenders and borrowers have an impact on the change of the interest rate. First, lenders are confronted with two types of risk: the risk of default and the risk of inflation (Heakal, 2019). The first type is self-explanatory mainly because the lender is never certain if the borrower will be able to pay the money back. The second type is the impact of inflation; over time, the original purchasing power of money could decrease when prices increase. This impact can result in changes in the interest rate. Section 3.2.2 gives a more detailed explanation about this impact.
Moreover, banks use interest rates to cover the account costs, so consumers must pay the interest rate to borrow money and spend it, which they were otherwise not able to do; it is similar for businesses (Heakal, 2019).
When looking at the supply and demand of credit, both have an impact on the interest rate. The supply of credit is driven by the quantity of money offered to consumers. When the supply is high, the interest rate will drop and vice versa. In contrast, when the demand for money rises, the interest rate will rise as well (Heakal, 2019). Apart from risk, supply, and demand, the government could also have an impact on the level of the interest rate through monetary policy. Section 3 will elaborate on this impact in more detail.
Note that the calculations for the borrowing rate, for which the creditor may determine a method applicable with national law, fall outside the CCD 2008. The directive does not regulate any method to calculate the borrowing rate, so the interest rate may differ amongst member states (European Commission, 2012).
2.2 Consumer Credit Directive (2008)
2.2.1 The purposeIn 2008, the European Parliament and Council adopted the Consumer Credit Directive (CCD) 2008/48/EC (Nwaogu et al., 2013, p. 3). The purpose of the Directive on Credit Agreements for Consumers (CCD) is, according to the European Commission (2008): “to facilitate the emergence of a well functioning internal market in consumer credit . . . This market should also offer a sufficient degree of consumer protection to ensure consumer confidence” (pp. 66–
67). Credit instruments keep developing in such a way that current provisions do not apply
anymore, so the scope of the provisions must be renewed (European Commission, 2008, p. 66). To achieve a modern consumer credit system, the laws and regulations stated in the CCD 2008, is lenient towards the member states in terms of implementation. Moreover, the
directive is structured in such a way that the laws remain customary, even in a constantly changing credit market (European Commission, 2008, p. 66). Flexibility of implementation is seen in Recital 10 of the CCD 2008, in which member states are allowed to enforce rules of the CCD 2008 outside the scope of the credit agreement described within it (European Commission, 2008, p. 67).
In sum, the ambition of the CCD 2008 is to enable the equal application of legislations concerning consumer credit agreements in all the European member states (European
Commission, 2008, p. 71). In this respect, consumer information is considered to be the most important measure of this directive to ensure that the consumer is informed of the advantages and disadvantages of the agreement. The information must be provided using the ‘European Standard Information for Consumer Loans’ form (European Commission, 2008).
2.2.2 The relevant charges
The main changes described in the CCD 2008 are divided into five different topics: advertising and APRs, creditworthiness and adequate explanations, precontractual information and agreements, right of withdrawal, and other key changes. The following section focusses on the advertising and precontractual information and agreements as key elements of the CCD 2008.
2.2.2.1 Standard information to be included in advertising
When the interest rates and costs in advertising a particular credit agreement are added, these should incorporate standard information as described in the CCD 2008 (Nwaogu et al., 2013, p. 5; European Commission, 2008, p. 73). The elements of this standard information are:
- The borrowing rate, fixed or variable or both, together with particulars of any charges included in the total cost of the credit to the consumer;
- The total amount of credit;
- The annual percentage rate of charge;
- If applicable, the duration of the credit agreement;
- In the case of a credit in the form of deferred payment for a specific good or service, the cash price and the amount of any advance payment;
- If applicable, the total amount payable by the consumer and the amount of instalments (European Commission, 2008, p. 74)
Member states are expected to use the Standard European Consumer Credit Information form when credit agreements are arranged. This is divided into five different subjects:
1. Identity and contact details of the creditor/credit intermediary; 2. Description of the main features of the credit product;
3. Costs of the credit;
4. Other important legal aspects;
5. Additional information in the case of distance marketing of financial services (European Commission, 2008, pp. 86–89)
2.2.2.2 Precontractual information
Before the consumer has signed any credit agreement, he or she must be handed the Standard European Consumer Credit Information form, which is outlined in Annex 2 of the CCD. In the precontractual stage, the information presented to the consumer must include the following elements:
- Type of credit;
- Identity and geographical address of the creditor; - Total amount of credit and associated conditions; - Duration of credit agreement;
- In the case of a credit in the form of deferred payment for a specific good or service and linked credit agreements, that good or service and its cash price;
- Borrowing rate;
- Annual percentage rate of charge and the total amount payable by a consumer, illustrated by a representative example which takes into account all assumptions used to calculate the rate;
- Amount, number, and frequency of payments to be made by the consumer; - Any extra charges deriving from the credit agreement;
- Existence of costs payable to notary (if applicable);
- Obligation to enter into an ancillary service contract relating to the credit agreement, in particular an insurance policy
2.2.3 Implementation of the Consumer Credit Directive (2008)
Since 11 June 2008, the CCD had been in force, and member states had to transpose it into
their national law within two years, by 12 May 2010 (Nwaogu et al., 2013, p. 3; European
Commission, 2008, p. 82).
However, the measures that needed to be implemented into national law were not communicated to the European Commission in time by some of the member states. As a result, the European Commission opened infringement proceedings against the sixteen member states that failed to meet the deadline (European Commission, 2014, p. 3). Four member states failed to implement the directive, resulting in a transitional period during which the directive was inactive. At the same time, the infringement procedure was closed when the European Commission was informed on the transposition measures of the member states concerned (European Commission, 2014, p. 3).
Table 2.1 provides a detailed overview of different measures described in CCD 2008, which have or have not been implemented by the EU-19. The comparative table is divided into four sections; the first compares the articles that are transported into the national law of the member state. When a member state transposes one of the articles, as described under the first section, the member state has to communicate the changes to the European Commission. In doing so, the member state must take adequate requirements to disseminate this
information to national lenders and consumers (Nwaogu et al., 2013, p. 25). The second section compares if the articles, that describe the clarification of terms and concepts, are implemented into the national law of the member states (Nwaogu et al., 2013, p. 81). The third concerns the choice of law provisions for article 22 (4). This article ensures that
consumers to retain the protection of the CCD 2008 (Nwaogu et al., 2013, p. 115). Finally, the last section analyses whether the member states did not implement the articles concerned (see Table 8.4) into their national law (Nwaogu et al., 2013, p. 135).For a more detailed
description about the articles, consult Table 8.1 to Table 8.4 (see Appendix A).
However, as Table 2.1 provides a comparative overview of the different articles transposed into the national law of the nineteen member states of the Euro-area, this study does not focus on these specific articles since there is a lack of data. There are no specific dates of the implementation of the articles as described in the CCD 2008 available. In addition, Table 4.3 provides the list of dates of which certain measures, concerning the CCD 2008, are transposed by the nineteen member states of the Eurozone into their national law. As a result of a lack of information, a specification of these transposing measures is not
available. However, the data of Table 4.3 is used to compare the level of implementation amongst the nineteen member states of the Eurozone.
Table 2. 1
Overview of the articles stated in CCD 2008 that needed to be transposed into the national law of the nineteen member states of the Euro-area
2.2.4 Main definitions
2.2.4.1 Credit agreements
The terms of a loan agreement are laid down in a credit agreement, also known as a legally binding agreement. This describes all the terms and conditions of the loan (Kagan, 2018). The measures described in the CCD 2008 apply to credit between € 200,- and € 75.000,- with the exception of loans:
- Secured by a mortgage;
- Concluded for the purchase of land or real estate;
- For lease or rental agreements where there is no obligation to purchase;
- Granted free of interest, without other charges, or in the form of an overdraft facility to be repaid within one month;
- Resulting from a judicial ruling;
- Linked to loans granted to a restricted group from within the general public (European Union, n.d.)
2.2.4.2 Credit standards, terms, and conditions
Credit standards are set and are non-negotiable. On the other hand, the conditions of a loan can be negotiated. Based on the credit standards, a loan may or may not be approved by the bank (European Central Bank, 2016, p. 2). According to the European Central Bank (2016), credit standards may fluctuate depending on shifts in: “the bank’s cost of funds and balance sheet situation, changes in competition, changes in the bank’s risk perception, changes in the bank’s risk tolerance or regulatory changes” (p. 2).
A bank includes the credit terms and conditions for granting a loan; these include, for example, the credit margin, the term, and the required collateral (European Central Bank, 2016, p. 2).
3. Theoretical Framework
This chapter discusses the different definitions used to answer the research question: ‘Did the national transposition measures, introduced by the CCD (2008), increase the gap between the consumer interest rate and the Euribor interest rate across the EU-19 from 2005 to 2018?’ This literature review contributes to the preparation of the hypotheses, which are outlined in section 3.4.
3.1 Difference between the interest rates paid by consumers and by banks
According to the models of Stiglitz and Weiss (1981), lenders can neither perfectly evaluate nor perfectly monitor potential borrowers, leaving banks uncertain about whether an
individual borrower will repay a particular loan. Increasing interest rates can affect both the pool of borrowers applying for credit and how they behave once they are extended credit, possibly in ways that substantially reduce the likelihood of repayment (Bergstresser, 2001, p. 6). In the classical economic theory, the level of risk only determines the price of a loan when a consumer has access to complete information from the consumer credit market. This allows the consumer to compare the advantages and disadvantages of the different loans offered by competing lenders (Lee & Hogarth, 1999, p. 66). However in the real world, this can be hindered, causing inefficient prices for consumer credit products. Mainly since incomplete information about credit consumers creates risks for financial institutions, leading to price inefficiency. In contrast, complete information is not always to the advantage of the
consumer, because the complexity of the credit information makes consumers unable to make the right choices when it comes to purchasing credit products. In addition, the price of
consumer credit products may also fluctuate due to competing credit providers. Nevertheless, these negative developments can be reduced by technological developments and deregulation (Lee & Hogarth, 1999, pp. 66–67).
When lenders are not aware of the default risk of the credit applicants, the lenders could ration credit. This option results from the adverse selection problem that arises from informational asymmetry (Igawa & Kanatas, 1990, p. 469). However, this unfavourable situation could also be observed from the position of the credit applicant. Lenders generate information from their older customers, which gives them the ability to lend to new
consumers at higher interest rates, which in former situations resulted in losses (Sharpe, 1990, p. 1069). Nevertheless, this is seen as a problem resulting from the borrowers’ behaviour since the consumer who borrows a certain amount agrees to disadvantageous prices or additional costly products because he or she is unable to make proper decisions (Reifner &
Schröder, 2012, p. 46). To prevent these situations from happening, credit agreements are signed by both the lender and the consumer. To increase consumer protection, the member states must implement the Consumer Credit Directive (2008) to ensure that consumers are well aware of their decisions because of complete information on price and terms of the credit. Due to this directive, lenders must ensure that consumers obtain the right information. However, according to the research of Bar-Gill and Be-Shahar (2013), the European
Commission employed consumer protection techniques that brought about unintended consequences at the disadvantage of consumers (p. 1). Bearing this in mind, it is not surprising that the extra tasks that must be carried out according to the directive come at a cost. If this eventually results in unintended consequences for consumers will be investigated since the question of whether the lender will pay for the cost or the consumer will pay for the cost indirectly, resulting in a higher interest rate, is answered in this research. (The difference between the interest rate paid by banks and that paid by the consumer is from herein called ‘the gap’.)
There are several factors that can impact the spending or saving behaviour of
households. In the short term, central banks can set a number of mechanisms in motion, which cause a change in the money market interest rates. High interest rate will have a negative impact on the households that want to take out a loan. It will encourage households to save their income instead of spending it, affecting the supply of credit (European Central Bank, 2009, p. 36). It is therefore necessary to control for several variables to get a valid result when researching the gap. In the following part of this chapter, the variables that can influence the gap are explained.
3.2 Economic forces influencing the difference in interest rates
To analyse the gap between the consumer credit interest rate and the interest rate of banks, it is necessary to examine what could influence the gap.
3.2.1 Market concentration
Market concentration is a function that can indicate whether there is much competition in the banking sector and is used as a function to indicate the sum of the market share of banks. When the market concentration is low, the market does not experience much competition, which results to an increase in market power. In these circumstances, higher prices can be charged compared to a market that behaves competitively (Alvarado, 1998, p. 1).
The Structure Conduct Performance (SCP) model describes that the structure of the credit market can influence the functioning of banks (Van Leuvensteijn et al., 2008, p. 11). The SCP model relies on microeconomic theory and describes two extreme examples. The first
example describes a competitive market in which companies make normal profits. The second example describes a monopolized market. The monopolist in this market makes extra profits. In this specific market, market power collusion is used to reduce competition and the barriers to entry are stricter. However, according to the contestability theory, competition is still possible in this market. Furthermore, the efficiency hypothesis states that when bank
efficiency is high, the bank gains market share at the expense of less efficient banks (Bikker, Spierdijk, & Finnie, 2007, p. 4). In other words, more efficient banks set the prices of their services more competitively compared to the less efficient banks, which set their prices less competitively (Corvoisier & Gropp, 2002, p. 7).
However, when investigating the impact of market concentration on the interest rate, Maudos and De Guevara (2004) found a relationship between market power and interest rate. They show that when the market power of banks increases, the net interest margins will increase as well (Van Leuvensteijn et al., 2008, p. 9). Mojon (2000) used an index of deregulation, which was found by Gual (1999), to examine the influence of competition within the banking sector on the transposing process connected to the interest rates of the Eurozone. Mojon (2000) found that a more competitive market increases in the ability for banks to alter the interest rates. An increase of competition puts pressure on banks, which makes it harder for them to increase the lending rates when, at the same time, money market rates are moving up (Van Leuvensteijn et al., 2008, p. 10). Van Leuvensteijn, Kok, Bikker, and Van Rixtel (2008) refer to this as an asymmetric pass-through effect, in which the degree of price cohesion is
asymmetric over the interest rate cycle (p. 10). Moreover, Corvoisier and Gropp (2002) used in their research a longitudinal dataset comprising all the Euro-area countries except for Luxembourg and found that a growth in market concentration leads to market collusion which in turn results in higher interest rates for loans (p. 9). The ECB (2007) also states that the interest rate pass-through process is influenced by various factors, including changes in competition that determine the market environment in which banks operate (p. 28). These theoretical findings indicate that it would be likely that an increase in market concentration would result in an increase in the difference between the interest rates paid by consumers and banks. Therefore, when controlling for this effect, a more valid impact analysis on the effect of the implementation of the directive and the question of if the interest rate of the credit agreements increase when the consumer has more protection can be examined.
3.2.2 Inflation
As mentioned in section 2.1.4, changes in the interest rate could be caused by inflation. To understand this effect, this section explains how this change occurs.
Substantial economic phenomena that have a negative impact on the economy are inflation and deflation. According to the ECB (2009): “inflation is defined as a general, or broadly-based, increase in the prices of goods and services over an extended period which consequently leads to a decline in the value of money and thus its purchasing power” (p. 24). The opposite of this definition describes the meaning of the term deflation.
When observing the impact of inflation, over time, the original purchasing power of money could decrease when the prices increase; as a result, this leads to an impact on the interest rate (Heakal, 2019). To explain this effect, this section focusses on the temporary effects, also referred to as the transition period. It should be noted that this period concerns rising or falling prices. This does not involve stationary levels, in which rising prices are characterised as being a high price and falling prices as being a low price. The change of state between a low level and a high level of prices concerns rising prices (Fisher, 2006, p. 56).
Business loans are granted to acquire goods; this is necessary to keep in mind in order to understand the impact of inflation on the purchase power and the effect this has on the interest rate. This effect is explained by using a very simple example. Borrower (B) wants to purchase a thousand units of goods, each unit being one euro; lender (L) will grant € 1.000,- to B so that he or she is able to buy the thousand units. After one year, B returns € 1.000,- to L, but the amount at which B bought the thousand units changed, resulting in losing a fraction of the original purchasing power at which L loaned to B. Even though B returned the same amount of money that was borrowed, the value differs from the original currency used to purchase the thousand units (Fisher, 2006, p. 57).
When connecting this interpretation to the interest rates, it should be assumed that the rate of rising prices is 2 per cent each year. L wants to lend the € 1.000,- and get 4 per cent of purchasing power. This leads to the equivalent that L must receive € 1.020,- and 4 per cent of this amount. Receiving back a total of € 1.060,80 euros to acquire 4 per cent interest in actual purchasing power, L must get back slightly more than 6 per cent interest in money. In sum, the rate of rising prices adds up to the rate of interest (Fisher, 2006, p. 57).
Now assume that the prices are falling; the € 1.000,- at the beginning of the year will buy more than thousand units. For the same thousand units, only € 980,- is needed to purchase these goods. When again L wants to get back 2 per cent of interest and a purchasing power identical to the primary, L gets € 980,- and 4 per cent of this amount, resulting in € 1.019,20,
which is less than 2 per cent. Thus, a 2 per cent fall in prices reduces the rate of interest by nearly 2 per cent (Fisher, 2006, p. 58). In sum, taking these two examples, it can be stated that to ensure that the relationship between the lender and the borrower is the same at the end as in the beginning when prices are rising or falling, the interest rate will rise or fall (Fisher, 2006, p. 57).
However, when applying this theory to the banking sector, the impact of inflation is more complex. From a monetary policy and price and financial stability perspective, the pass-through mechanism of interest rates is important for the ECB (Siakoulis, Petropoulos, Lazaris, & Lialiouti, 2018, p. 3). According to Siakoulis et al. (2018): “alternatively in order to face inflationary pressures in economic expansion central banks increase interest rates” (p. 3), resulting in a rise of the interest rate paid by the bank. As a consequence, the interest rate for the consumer will rise as well.
As mentioned, when the interest rate paid by consumers decreases, consumers will be able to spend more money. In contrast, when interest rates rise, the disposable income of consumers will decrease, resulting in consumers cutting back on their consumption and spending (Heakal, 2019). Since banks still want to grant loans to consumers, competition in the banking sector will ensure that the interest rate paid by consumers differs amongst banks (European Central Bank, 2007, p. 28). More importantly, according to the ECB (2007), such competitive pressure: “induces banks to reduce their spreads when interest rates are rising” (p. 29), resulting in a decrease of the difference in interest rates paid by consumers and banks.
3.3 Summary of expected hypotheses
To give validity to the hypotheses, the indicators are operationalised in the following chapter. Hypothesis
Hypothesis 1
The implementation of the CCD 2008 will increase the difference between the interest rate paid by consumers and the interest rate paid by banks.
Hypothesis 2
When the number of articles, stated in CCD 2008, transposed into the national law of the nineteen different members of the Eurozone is high, the difference between the interest rate paid by consumers and the interest rate paid by banks will increase.
Hypothesis 3
When the market concentration increases, the interest margins of banks on loans will increase, resulting in an increase of the difference between the interest rate paid by consumers and the interest rate paid by banks.
Hypothesis 4
When the inflation level increases, the interest margins for banks will increase, but due to market forces, the difference between the interest rate paid by consumers and the interest rate paid by banks will decrease.
Table 3.1
4. Research Design and Data
In this chapter, the theoretical expectations are operationalised. The impact of the CCD 2008 on the difference between the consumer and the bank’s credit interest rates is analysed within the EU-19 countries from 2005 to 2018. The choice of the model to analyse this effect is discussed in the first part of this chapter, together with an explanation of the choice of data. To measure the effect, the different concepts must be operationalised into instruments. Therefore, the second part discusses the operationalisation of the different variables with an elaboration of the various instruments.
4.1 Models to test the hypotheses
4.1.1 Panel data analysis
This study uses a panel (data) analysis to test the hypotheses described in section 3.3. A panel (data) analysis, also referred to as a longitudinal data analysis, is useful when subjects are observed over time (Frees, 2004, p. 13). The hypotheses summarised in Table 4.1 are tested by using monthly panel data of the difference between the consumer credit interest rate and the bank’s interest rate in the nineteen members of the Eurozone between January 2005 and December 2018. For the robustness tests, control variables are employed; the rates of market concentration and inflation have an impact on the difference between the consumer credit interest rate and the bank’s interest rate, so it is important to include these measures as explanatory variables. In other words, these measures have an impact on the dependent variable—the difference between the consumer credit and bank’s interest rates—but will not have any impact on the level of implementation of the directive.
The following part adopts the following notations and definitions. Firstly, the dependent variable is calculated by the following formula:
𝑌!" = 𝑅𝑐!"− 𝑅𝑏!"
Where 𝑌 is the difference between the interest rates for the loans to household for
consumption with an initial period of one year (Rc), and the interest rate according to Euribor (Rb) in member state i for 19 observed member states at month t, with 𝑇 implying the
monthly timeframe of 14 years (2005–2018), resulting in a total of 3,192 observations. However, of the 19 countries in the dataset, 5 had missing values of the dependent
market concentration. Therefore, a total of 3,103 observations were thus used to estimate the models, but only 2,666 observations were used to estimate the models when the explanatory variable market concentration was used in the estimation (see Table 4.3).
In this study, the panel regression model is structured as follows:
𝑌!" = 𝛼 + 𝛽!Level_Implem_01!"+ 𝛽!Level_Implem!"+ 𝛽!𝐻𝐻𝐼!"+ 𝛽!𝐻𝐼𝐶𝑃!" + 𝜀!"
𝑌it is the gap in member state 𝑖 at year 𝑡. The 𝛽1 is the beta coefficient for the explanatory
variable that indicates the implementation of CCD 2008 in a member state at a certain period of time, indicated as Level_Implem_01. The 𝛽2 is the beta coefficient for the explanatory
variable that indicates total number of articles stated in the CCD 2008 that were transposed into the national law of a member state at a certain point of time, indicated as Level_Implem. Section 4.2.2 gives a more detailed explanation about these independent variables. Moreover, the values of the control variables, market concentration and inflation, are indicated by HHI and HICP. The value of the coefficients for the control variables is indicated with the coefficient 𝛽3 and 𝛽4. The random error is indicated with 𝜀it.
Table 4.1 provides a brief summary of the expected hypotheses in operationalised terms.
Hypothesis Expected sign Hypothesis in summary
H1 β1 < 0
The implementation of the CCD 2008 will have a positive effect on the difference between the bank interest rates for the loans to households and the Euribor.
H2 β2 < 0 The total number of articles to implement the CCD 2008 will have a positive effect on the difference between the bank interest rates for the loans to households and the Euribor.
H3 β3 < 0
The market concentration will have a positive effect on the difference between the bank interest rates for the loans to households and the Euribor.
H4 β4 > 0
Inflation will have a negative effect on the difference between the bank interest rates for the loans to households and the Euribor.
Table 4.1
4.2 Data sources and operationalisation of variables
In this study, nineteen member states of the Eurozone are analysed from a period of monthly data of fourteen years, from January 2005 to December 2018. This timeframe indicates if there is a certain impact of the implementation of the CCD 2008, mainly since data before and after the implementation give a more accurate understanding of the effect. The impact of the implementation of the CCD 2008, which aims to improve consumer credit information to increase consumer protection, on the difference between the consumer credit interest rate and the bank’s interest rate is analysed. Primary and secondary literature is collected to obtain theoretical expectations that give insight into the impact described above. The data was collected from the ECB and Eurostat. The data concerning the dates of implementing the measures across the EU-19 was collected from EUR-lex.
The dependent variable is based on the difference between consumer credit interest rate and the bank’s interest rate. The interest rate of the bank is the Euro Interbank Offered Rate (Euribor) and is collected from Eurostat. The Euribor is a term for the interest rate that banks have to pay for borrowing money. The interest rate is determined by the average interest rate at which European banks lend each other money (Euribor-rates.eu., n.d.). The consumer credit interest rate data is the interest rates for the loans to household for
consumption with an initial period of one year, collected from the ECB.
The independent variable represents the data at which each member state implemented the national transposition measures described in the CCD 2008. EUR-lex provided the
specific dates when each member state implemented the measures.
The control variables concern two indicators for market concentration and inflation. The indicator for market concentration is the Herfindahl-Hirschman Index (HHI). As
explained in section 4.1.1, the HHI had missing values for the years 2017 and 2018; therefore, 2,666 observations were used to estimate the models when the HHI was controlled for. The HHI data collected from the ECB contained yearly data. The monthly missing data was interpolated using linear interpolation to transform yearly data into monthly data.
Furthermore,inflation is measured in the Euro-area by using the Harmonised Index of Consumer Prices (HICP). This indicator, collected from the ECB, calculates the alteration in prices of consumer goods and services paid for, used by, or purchased by Euro-area
households. The term ‘harmonised’ indicates that the data of this indicator can be compared amongst every European member state since the identical methods are used (European Central Bank, n.d.). These two variables help to establish validity for the hypotheses since
they reflect economic effects that can influence the dependent variable, just as in the real world. Table 4.2 gives a detailed description of the operationalisation of the different concepts used in this analysis.
4.2.1 Dependent variable: Gap between the consumer credit interest rate and interest rate of banks
The dependent variable, indicated in the formula as 𝑌it , represents the difference between the
interest rates for the loans to household for consumption with an initial period of one year and Variable Type of variable Description
countrynum Group This variable ensures that all observations of each EU-19 member state are grouped and indicated by a number.
Date Time variable This variable indicates the first day of each
month, from 01-01-2005 until 01-12-2018.
Gap Dependent variable
The difference between the bank interest rates for the loans to household for consumption and other purposes with an original maturity of up to one year (Rc) and the interest rate according to Euribor (Rb); in the dataset, the following formula is used (Rc-Rb).
Level_Implem_01 Independent variable
Adoption of CCD 2008 measure, with 1 if implemented by the member state and 0 otherwise.
Level_Implem Independent
variable
Adoption of CCD 2008 national transposition measures, with 0 if not implemented by member state and 1-10 as factor of the number of
national transposition measures implemented of the CCD 2008. Level_Implem_01_ Lag (Lagged) Independent variable
Adoption of CCD 2008 measure, with 1 if implemented by the member state and 0 otherwise, lagged in dataset by one year.
Level_Implem_Lag
(Lagged) Independent variable
Adoption of CCD 2008 national transposition measure, with 0 if not implemented by Member State and 1-10 as factor of the number of national transposition measures implemented of the CCD 2008, lagged in dataset by one year.
HHI Control variable
This indicator is a measure of market concentration used to determine market competitiveness in the Eurozone.
HICP Control variable
This indicator, collected from the ECB, calculates the alteration in prices of consumer goods and services paid for, used by, or purchased by Euro-area households. Table 4.2
the Euribor rate. The Euribor rate depends on the supply and demand and is due to intervention of European banks created.
Figure 4.1 shows the development of the difference between the interest rates for households and the Euribor spreads in the nineteen member states of the Eurozone before and after the legislative change on 11 June 2008 and before and after the deadline on 12 May 2010, when the member states had to transpose the CCD 2008 into their national law, resulting in consumers experiencing higher levels of protection. Figure 4.1 illustrates a visible trend in which the difference between the interest rate for households and the Euribor spread, in the figure called The Gap, increases over time. Between 11 June 2008 and 12 May 2010, the gap increases in all nineteen member states of the Eurozone. After 12 May 2010, the trend of the gap becomes more stable for twelve member states (France, Italy, Luxembourg, Austria, Belgium, the Netherlands, Lithuania, Slovenia, Finland, Cyprus, Malta, and Germany), in which the difference in the interest rate for households and the Euribor is (in December 2018) the lowest in France at 0.03 per cent and the highest in Germany at 0.07 per cent. Much fluctuation is seen in the other seven member states (Spain, Portugal, Slovakia, Greece, Estonia, Ireland, and Latvia) after a big rise in 2014; the biggest difference between the interest rates of households and the Euribor is seen in Latvia, being approximately 0.18 in December 2018. Since the difference between the interest rates of households and the Euribor increases after the legislative change on 11 June 2008, and increases between 11 June 2008 and 12 May 2010, this provides some descriptive empirical support for the claim that the implementation of the CCD 2008 increased the difference between the interest rates of households and the Euribor.
However, external factors have an impact on the difference between both interest rates, mainly economic circumstances influence the level of the interest rate (Euribor-rates.eu, n.d.-a). Therefore, more variables are used in the analysis to examine the gap, as described in Figure 4.1.
Figure 4. 1 The difference in interest rates for households and the Euribor (legislative change in June 2008 and the deadline of transposing the CCD 2008 into national law in May 2010) Source: Appendix C
4.2.2 Independent variable: Level of implementation in the Eurozone
The data collected from EUR-lex includes the national transposition measures that are communicated by each member state to the European Commission (EUR-lex, n.d.). The specific measures and dates differ amongst the member states of the Euro-area. Table 4.3 illustrates a comparative graph, including the dates of the different national transposition measures that enabled legislative change of the CCD 2008 in the EU-19 (EUR-lex, n.d.). As mentioned in section 2.2.3, specifications of these transposing measures were not available. This study assumed that the impact of each transposing measure presented in Table 4.3 is the same. The dates presented in Table 4.3 are used to compare the level of implementation amongst the nineteen members of the Euro-area.
In Table 4.3 all the member states of the Euro-area are presented. The right column next to the names of the member states, present the total number of transposing measures the member state concerned has implemented into their national law. The column next to the total number of transposing measures, illustrates the data at which each measure was transposed into the national law of the member state concerned. These dates are used differently in order to analyse the impact of the implementation of the CCD 2008 in the nineteen member states.
The variable Level_Implem_01 is a dummy variable calculated according to a 0/1 value, where 0 indicates that a member state has not implemented any transposition measures of the CCD 2008 into their national law. The first date of the transposition measure, which is indicated with number 1 in Table 4.3, represents the value 1, which indicates that at that date the CCD 2008 is implemented by the member state.
The variable Level_Implem is calculated according to a 0 to 10 factor. The factor indicates the number of transposing measures that is implemented in one of the nineteen member states. To be more specific, Table 4.3 illustrates that Austria has a total amount of one national transposing measure; in contrast Estonia has a total amount of ten national transposing measures. This study assumes that the impact of each transposing measure is the same. This also assumes that the number of transposition measures implemented in Estonia would result in having more impact on the difference between the interest rates of households and the Euribor, compared to Austria that has only one transposing measure implemented. Moreover, in order to analyse this impact the variable Level_Implem uses both the dates of, and the number of transposing measures that are presented in Table 4.3. The variable starts with the value 0 when a member state has not implemented any transposing measure. The value rises each time a new transposition measure is implemented at a certain date (see Table 4.3). For Belgium, the total amount of transposition measures is 3. Indicating that the value of
the variable Level_Implem rises to 3. In more specific terms, value 0 rises to 1 as of the date 21-06-2010. The value rises again at 31-12-2010, when a total of 2 transposition measures are implemented into the national law of Belgium. At 29-06-2011, the value rises for one last time to 3. The value 3 remains unchanged for Belgium until the end of the analysis, because it has 3 moments in time at which a transposition measure was implemented. For Estonia the value will rise to 10, which means that the value is adjusted at 10 different dates.
The panel data regression results determine which variable is the most valid to test the hypotheses and eventually answer the main research question.
Table 4. 3
Comparative table including the dates of the national transposition that enabled legislative change of the CCD 2008 in the EU-19
4.2.3 Lagged independent variables: Level of implementation
This study checks whether lagged independent variables yield better results. Due to including lagged independent variables, the years of implementation of the CCD 2008 per member state are lagged by one year. The two lagged independent variables are described as follows:
- Level_Implem_01_Lag represents the lagged variable for the dummy variable.
Level_Implem_01 indicates that at 0, the member state has not implemented the CCD 2008, and at value 1, the member state implemented the CCD 2008 into national law. - Level_Implem_Lag represents the lagged variable for the Level_Implem variable that
indicates the number of articles stated in the CCD 2008 a member state has transposed into its national law, as described in section 4.2.2.
This study also estimates the regression models (explained in chapter 5) once with the lagged independent variables (see Table 8.2). However, these results did not provide any new insights; hence, these models are not included in the study.
4.2.4 Control variables: Market concentration and inflation
Besides the measures in the CCD 2008, other factors could affect the difference of the interest rates for households and the Euribor. This difference could also vary amongst all the member states of the Eurozone. In the regression model, the two additional variables are used as control variables, concerning the indicators of market concentration and inflation.
As described in section 4.2, to estimate the gap between the interest rates for households and the Euribor, an indicator for market power, the HHI, is necessary to control for. This indicator measures and assesses the degree of market concentration.
As described in section 4.2, to estimate the impact of the CCD 2008 on the difference between the interest rates of households and the Euribor, it is also important to control for the indicator for inflation, the HICP.
Table 4.4 presents summary statistics for all employed variables. The following chapter presents the results of this study.
Variable N S.D. Min Max Mean
The gap 3,103 0.0370106 -0.04524 0.22315 0.661362 Level of implementation 1 (dummy) 3,192 0.471145 0 1 0.6676065 Level of implementation (factor) 3,192 2.690114 0 10 2.12218 Level of implementation 1 (dummy) lagged 3,192 0.4907395 0 1 0.5961779 Level of implementation (factor) lagged 3,192 2.570951 0 10 1.840539 HHI 2,755 0.0831786 0.0174 0.4039 0.1237537 HICP 3,192 1.935816 -2.5 15.8 1.99104 Country 3,192 5.478084 1 19 10
Date 3,192 1476.351 Jan 01, 2005 Dec 01, 2018 Dec 16, 2011
Table 4.4
Summary statistics
Note: The following variables are dummy variables: Level of implementation 1, Level of
implementation lagged. N gives the number of months, i.e., observations available for the statistical analysis.
5. Results and Analysis
This chapter presents the results of the estimation of this study. To be specific, the expected hypotheses described in Table 4.1 are tested. Based on the results presented in the regression models, the hypotheses can be adopted or rejected. Finally, the empirical analysis and interpretation answer the question if the CCD 2008 had an impact on the difference between the interest rates of households and the Euribor.
5.1 Panel data regression results and description
5.1.1 Choice of model
Table 5.1 presents the results of the estimation of this study. When the models do not take the control variables into the regression, the results are biased. Thus, to get a more valid and real effect, which could be reflected in the real world, control variables are taken into all the regression models; in some models, the number of control variables differs. Models 1, 2, and 3 describe the results of the panel data fixed effect (within) regression when all the control variables are included. Models 4, 5, and 6 describe the results of the panel data fixed effect (within) regression when only the control variable HICP is taken into the regression model. (The reason behind this strategy is explained in the following section.) Furthermore, there is a difference in the strategy behind the way in which the independent variables are observed. In models 1 and 4, only the dummy independent variable is taken into the regression model; in contrast, in models 2 and 5, only the factor independent variable is taken into the regression model. Finally, models 3 and 6 include both the dummy and factor-independent variables.
5.1.2 Main results
In Table 5.1, the results of the panel data fixed effect (within) regression, including the total of all the variables used in the regression are presented.
