The influence of diversified factors on non-parliamentary activities in the United Kingdom: a descriptive and explanatory research

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The influence of diversified factors on non-parliamentary

activities in the United Kingdom: a descriptive and explanatory

research

Student number: S2647966

Name: Azra Zejnilovic

Study Program: MSc IFM

Supervisor: S. HomRoy

Key Words: non-parliamentary activities, agency problem, explanatory research, United

Kingdom

Abstract

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In many countries Members of the Parliament (MPs) are, next to their parliamentary job, legitimately allowed to engage in non-parliamentary activities (Geys, 2012). Looking at the opinion of the media and the wider public it can be concluded that these do not always react positively to MPs‟ outside engagements (Geys, 2012). The negative perspectives seem to have reinforced because of numerous public scandals, think of the expenses claims in the UK in 2009 and the „cash for influence‟ in the European Union in 2011 (Geys, 2013; The Telegraph, 2009; The Times, 2011). MPs engaging in outside positions seems to increase the moral worries voters might experience regarding the MP‟s behavior (Allen & Birch, 2010; Birch & Allen, 2010). The reasoning behind these moral worries is that the relationship between citizens and the elected member (MP) can be seen as a principal-agent relationship (Besley, 2006; Kalt & Zupan, 1990; Mitchell, 2000). The general concern of the public voters (principals) could be that the elected administrators (agents) may redirect their attention from their full-time position in the parliament (Gagliarducci, Nannicini & Naticchioni, 2010a). MPs can also start experiencing several contesting forces (conflict of interest), such as the party, voters and various groups of interest and can induce severe problems with coordination and time (Geys & Mause, 2012a). Additionally, the inadequate use of MPs‟ positions may have a negative influence on their public appearance (Geys, 2013).

Over the years a reasonable amount of literature has been discussing MPs‟ outside job engagements (Besley, 2004, 2006; Borghans, Duckworth, Heckman & ter Weel, 2008; Becker, Peichl & Rincke, 2009; Gagliarducci et al., 2010; Geys & Mause, 2011, 2012, 2013; Kalt & Zupan, 1990; Mitchell, 2000; Norris, 1996). This literature has been examining topics such as adverse selection, conflict of interests, gender, electoral majority differences, regulated industries and the influences on the outside activities of MPs. Thereby, there is much research that focuses on the effect of political connections on companies (Acquaah, 2007; Faccio, 2010; Faccio, Masulis & McConnell, 2006; Hillman, 2005). So far, this literature has mostly been focusing on restricted research questions and therefore some questions remain (partly) unanswered. Think of questions such as; what kind of outside connections do MPs have, how much do they earn with them, what kind of information do politicians disclose and is there an external legislative factor that could influence the MPs‟ engagements in outside activities? Not having an answer to these questions indicates that the literature and general public are not fully aware of what MPs are exactly doing next to their parliamentary duties. Answering these questions is needed in order to gain a better understanding of all the MPs‟ general non-parliamentary activities, what factors affect these MPs‟ engagements and how the MPs‟ activities changed of the years.

One of the main reasons for the overall shortfall of literature in this area of interest could be that the data forms a bottleneck. The reasoning lies in the fact that researchers are dependent on the disclosure and quality of the (publicly) available data. Research shows that less than one-sixth of the 109 countries with disclosure laws show to have information that possibly can be used (Djankov, La Porta, Lopez-de-Silanes & Schleifer, 2010). Wealthier countries show to have more public disclosure, which is related with a better government (Dajnkov et al., 2010). If the disclosure and quality are set to a minimum, the scope and quality of the research could decrease. Adding to this, the available data often has a qualitative nature. This makes the collection of the data very time consuming. Lastly, it is shown that the public availability of the database often was not enforced by law (Djankov et al., 2010). Nevertheless, in a considerable amount of European countries registers of interests are seen to be made publicly available (Geys & Maus, 2013). A few examples from the list are Austria, Denmark, Finland, Germany, The Netherlands and the UK (Geys & Maus, 2013). Geys (2013) states that the UK government, compared to for instance Spain or Italy, requires MPs to disclose information about their assets, non-parliamentary activities and earnings. It looks like the rules and regulations regarding the disclosure have moderately been established in the more developed European countries.

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affecting the engagements. Additionally, the enlargement of transparency to the public also made it possible to conduct more specific research regarding all the MPs‟ outside activities. As in the UK the disclosure of information is relatively high compared to other countries this research will focus on merely the MPs in the UK. The main aim of this paper is to examine all the MPs‟ non-political engagements and the factors affecting the MPs‟ outside activities. Apart from individual characteristics, constituency differences and industry differences also legal frameworks are taken into account as factors that could potentially influence the MPs‟ engagement in non-parliamentary activities. Generally, this research focuses on a more descriptive and explanatory analysis and the will focus on two essential research questions: First, what can be concluded from the MPs' disclosure of all the non-parliamentary activities and earnings? Secondly, did the MPs‟ outside activities change over the years? In order to be able to answer these questions, an entirely new single-country sample was created. Data from the UK House of Commons was collected and analyzed. The sample covers two complete legislative terms from 2005 until 2015 and can be said to be informative as it includes diversified variables. Given that the collection of the data is very time consuming, to my knowledge such a widespread research has not been conducted for the UK before. This research is the very first study to do so.

It is found that most MPs‟ individual characteristics affect the MPs‟ outside connections, corporate connections, media engagements and speaking engagements. Thereby, constituency differences show mixed results. Electoral majority affects the MPs‟ outside connections, corporate connections, media engagements and speaking engagement. Whereas, looking at the committee memberships, it only shows to have an effect on the MPs‟ corporate connections and media engagements. Industry differences also show that companies that are operating in a regulated industry group and companies that are listed show to influence MPs‟ corporate connections. Lastly it is found that changes in legal framework show to have an effect on the MPs‟ corporate connections and media engagements. There was no effect found on MPs‟ outside connections and speaking engagements. The main implication of this research is that it shows the importance of shedding a light on the MPs. This is not only essential for the world of research but surely also the general public. This research illustrates that MPs do not only engage in corporate activities but also extensively focus on other, maybe less obvious, activities such media and speaking engagements. Furthermore, it is illustrated that it is also valuable to look at legal frameworks that might influence the MP‟s engagement in outside activities. It seems like current literature often „forgets‟ to look at the wider picture. Taking all in consideration, will definitely contribute to gaining a deeper understanding of the mechanisms driving outside activities but also surely the disclosure of these outside activities to the general public.

The paper is structured as follows. Firstly, an institutional background is presented and thereafter the current literature is reviewed resulting in various hypotheses. Third, the data is presented as well as the methodology used in the research process. A logistic regression was conducted from which the essential results are interpreted. Finally, the results are reviewed and a conclusion is provided, as well as implications, limitations and ideas for future research will be discussed.

2. Institutional background

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focus on the House of Commons and follows previous research (Geys, 2013). The House of Commons consists of 650 members corresponding to the 650 electoral districts in the UK (UK Parliament, 2020). The appointee serves as a representative for the interests and concerns of the UK public in a particular constituency and is also known as Member of the Parliament (MP) (UK Parliament, 2020). The MPs have various purposes: 1) legislation, propose new laws and raise issues or concerns, 2) debating, on various present-day affairs 3) scrutiny, challenge and monitor the work of the government. 4) budget/taxes, review and confirm government spending (UK Parliament, 2020). Overall, the MPs have to manage their time regarding three main parties: political party they are related to, the Parliament and the constituency there are elected for (UK Parliament, 2020). There are also various committees that analyze issues in detail, think of revision of the government‟s work and newly suggested legislature (UK Parliament, 2020).

An important element of the parliament is the Register of Members‟ Financial, which dates back to 22 May 1974 following a Resolution of the house (UK Parliament, 2020). The interests that are required to be registered are displayed in the “Code of Conduct and Guide to the Rules related to the Conduct of Members”, that was firstly settled in July 1996, revised in May 2002, July 2005, June 2009, April 2012, April 2015, August 2018 and October 2019 (UK Parliament, 2020). In the House of Commons the register is managed by the Parliamentary Commissioner for Standards, who is an independent appointee (UK Parliament, 2020). The Parliamentary Commissioner for Standards maintains the Code of Conduct for MPs. From 1995 until 2013 this Commissioner was supported by the Committee of Standards and Privileges, whose main task was to oversee the work of the Commissioner (UK Parliament, 2020). The committee was split up in at the beginning of 2013 in two separate committees and has been replaced by two different committees Committee on Standards and Committee on Privileges (UK Parliament, 2020). After the committee separation only the Committee on Standards still remained to have the supervisory function (UK Parliament, 2020). In 1994 the committee on Standards in Public Life was established (UK Government, 2020). This committee is an advisory non-departmental public body and is occupied with mostly an advisory role (UK Government, 2020). The committee on Standards in Public Life provides advises to the Prime Minister regarding ethical standards across the whole public life in England. Thereby, the committee also oversees and communicates when there are issues related to the Code of Conduct of all public representatives (UK Government, 2020).

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3. Literature review

3.1 Non-parliamentary activities

That the MPs are engaged in paid and unpaid non-parliamentary activities is not something new. The study by Braggion and Moore (2013) explains that in the UK economy there were many connections between politicians and firms in late Victorian Britain. In the past and still nowadays, the MPs are allowed to be hold or be engaged in non-parliamentary activities. Every individual decides whether he or she wants to take outside (private) offers (Grey & Mause, 2012b). Thereby there is also a situation where the politician activity seeks to be involved in such positions (Grey & Mause, 2012b). The MP‟s decision is dependent on job characteristics (job compensation or available time), personal circumstances (partner‟s income) or professional factors (trust) (Grey & Mause, 2012b). Boubakri, Cosset and Saffar (2012) explain that in many countries the prime ministers and presidents are wealthy businessmen and prominent entrepreneurs. Geys and Maus (2013) explain that the MP‟s outside income can serve as a „survival insurance‟ that is activated after the parliamentary term. Furthermore, that non-parliamentary income decreases the MP‟s reliance on re-election to safeguard their income (Norris, 1996; von Arnim, 2006). Whatsoever reasoning the politician might have for engaging in external positions, it is often the case that the obtained financial benefits are large (Geys & Mause, 2013). The engagement in outside activities is frequently labeled as „moonlighting‟ (Gagliarducci et al., 2010a, Geys & Mause, 2013). Such external engagements can be described as either a new activity or a continuity of an earlier seat (Gagliarducci et al., 2010b). Adding to this, these positions do not only entail MPs that are employed by an organization but also MPs that have partial or full ownership over a company (Bunkanwanicha & Wiwattanakantang, 2009; Faccio, 2006). Geys and Mause (2013) provide another definition that is close to the framework in this paper: the engagement of MPs in additional (un)paid working involvements next to their political mandate. Some examples of external positions and activities from the dataset of this paper are; business consulting, advocate, solicitor, chartered accountant, farming, board membership, councilor, general practitioner, lecturing at universities, speaking at varying events, author, journalist, engagement in television and/or radio. In this research the terms „moonlighting‟, „outside activities‟ and „outside engagements‟ are used interchangeably.

3.2 MPs as agents of the public

It has become clear that in the (inter)national debate, a particular type of behavior comes to light; the carrying out of legally approved (un) paid outside positions next to MP‟s parliamentary position (Geys & Maus, 2012a). In the first place, the MP is chosen by the citizens to represent them. It is possible to see the relationship between citizens and the elected member (MP) as a principal-agent relationship (Besley, 2006; Kalt & Zupan, 1990; Mitchell, 2000). Looking from the angle of the citizen, also referred to as principal, a significant worry can arise (Geys & Maus, 2012a). This concern is tied to the question how to check and, if needed, penalize the MP, also referred to as agent, when he/she does not behave in the best interest of the principal (Geys & Maus, 2012a). This leads to a situation of moral hazard, wherein, the agent does not merely focus on the tasks provided by the principal and also making it more difficult to monitor the agent in such a situation.

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& Maus, 2012a). Concerning that a political position is aimed to be a full-time position, moonlighting activities may create a problem of opportunity cost which results in overlooking the parliamentary tasks (Becker et al., 2009; Maddox, 2004). Adding to this, MPs engaged in outside positions might experience critical conflict of interests when faced with the resolutions of policies (Atkinson & Mancuso, 1991). This is because the MP has to serve more than one principal (e.g. constituency and a firm) (Strøm, 2000). When a MP is taking outside positions it leads to a situation wherein he or she is not only occupied with the interests of the initial principals (the voter and party) yet is also concerned with the externally created principals (e.g. firms and newspapers) (Geys & Maus, 2012a). These challenging interests make it very complicated, and sometimes even unthinkable, to meet all the principal‟s demands (Geys & Maus, 2012a).

3.3 Changes Code of Conduct

Even though the politicians are allowed to take outside positions, they need to follow a Code of Conduct. It is important to highlight that having such codes are not a matter of course. It took some time to develop them. In the UK various amendments have been made throughout the years. For example Green and HomRoy (2018) explain that during the 2002 amendment the restrictions for participation and initiation in parliamentary proceedings of MPs with outside business interests were removed. Even if paid advocacy was still prohibited, it would imply that for MPs it was more easily to discuss interests of corporations they shared a connection with, comparing it to before the 2002 revision (Green and HomRoy, 2018). Green and HomRoy (2018) provide evidence that the 2002 amendment has influenced the behavior of UK MPs and firms. They show that UK MPs have an increasing likelihood of having a corporate affiliation after the amendment, compared to other politicians. It is also demonstrated that the connected MPs, compared to other non-connected MPs, were more likely to hold positions in significant committees (Green and HomRoy, 2018). Overall, this 2002 amendment showed that both parties produced private returns, meaning that the space between political decisions and corporate interests was reduced (Green and HomRoy, 2018). This resulted in corporate connected MPs practicing more engagement in significant political decision making (Green and HomRoy, 2018).

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other countries, the UK parliament has taken the lead in the sense that it started demanding more specific information from its MPs.

3.3 Variables affecting outside connections

So far the focus has been on moonlighting activities and the codes MPs are required to follow. However, it is also important to look at the starting point of these connections, namely the MP. It is possible to examine the differences between MPs taking outside positions. It needs to be recognized there might be factors that could affect the MPs‟ engagement in outside activities. These elements can be discussed on various levels.

Firstly, the MPs all have individual characteristics. An emerging amount of research is focusing on the differences between female and male administrators and what contributes to these discrepancies (Geys & Maus, 2012b). The reasoning that always comes forward is the concept of glass ceiling, which it said to block the women in their ambitions (Geys & Maus, 2012b). Especially for leadership jobs, males seem to have a preferential position over women and this simultaneously harms women (Heilman, 1996; Watts, 2009). McKay (2004) explains that apart from being able to overpower the significant barrier of getting elected in the first place, negative stereotypes can even be present in the post-election period. This implies that negative stereotypes could still disrupt the female MP‟s advancement (McKay, 2004). Self-fulfilling effects can also clarify gender differences (Harris & Rosenthal, 1985). Previous research also shows that women are in general less inclined to apply or accept an outside job (Grey & Maus, 2012b). Moreover, there are fewer demands for female MPs to accept or search for outside positions in order to enlarge the household income (Geys & Maus, 2012b). Another explanation that goes back in time, but still can be applicable today, is the research by Berardo, Shenan and Leslie (1987). Their research shows that male MPs coming from the more conservative parties tend to come from more traditional families, wherein the male earns the money and women are the caretakers. It seems that these traditional ideas about gender roles are still present in today‟s world (Wood & Eagly, 2012). Borghans et al. (2008) argue that generally women are more risk averse comparing to men. This implies that female MPs might experience the, so-called, political risk in a different manner (Geys & Mause, 2012b). These risks are associated with real or recognized conflicts of interest of the non-parliamentary activities (Geys & Mause, 2016). Following this argument previous research shows that women are also less inclined to have various non-parliamentary positions (Geys, 2011; Mause, 2009). Women also have lower chances of receiving external income compared to men (Becker et al., 2009; Gagliarducci et al., 2010a).

It is also possible to look at the effect of political parties on the engagement in outside positions, so called partisan effect. Previous research shows that these partisan effects are to be found in the United Kingdom and Germany (Geys, 2011; Geys & Mause, 2011; Mause, 2009; Niessen & Ruenzi, 2010), however, show no clear effects in Italy (Gagliarducci et al., 2010a). Research provides evidence that in the UK and Germany left-wing parties show to have a lower likelihood of having outside activities when compared to the, in the economic manner, conservative and/or liberal parties (Geys & Maus, 2013). By looking at the traditional voting public of these parties the intuitive explanation would make sense; entrepreneurs and self-employed for right-wing parties focusing on economic growth and blue-collar workers for left-wing parties focus on a welfare state (Geys & Maus, 2013). Bearing in mind these arguments, implying that the individual characteristics could influence the MP‟s engagement in outside activities, the following testable hypotheses, are hypothesized:

Hypothesis 1: The likelihood of MP’s outside connections is associated with individual characteristics.

Sub hypothesis 1.1: The MP’s gender affects the likelihood of outside connections.

Sub hypothesis 1.2: The MP’s party affects the likelihood of outside connections.

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Secondly, constituency level differences exist. Galasso and Nannicini (2011) explain these differences can appear because of a selection effect. This leads to political parties sending the candidates with the best qualities, and thus lower rates of parliament absence, to very competitive constituencies. Norris (1996) and Becker et al. (2009) present evidence on this issue for the UK and Germany respectively. In their research it is shown that MPs who are encountering less electoral contest have significantly higher external earnings. The reasoning lies in the compromise between „internal‟ and „external‟ efforts (Becker et al., 2009; Norris, 1996). Politicians confident of their re-election may feel less urged to display efforts to their constituency or the parliament (Becker et al., 2009; Norris, 1996). This implies these MPs have additional spare time that can be assigned to external positions creating external earnings (Becker et al., 2009; Norris, 1996). Galasso and Nannicini (2011) include both previously discussed effects and provide evidence that the selection effect overshadows the electoral reasoning. Bearing in mind these arguments, implying that the constituency differences could influence the MP‟s engagement in outside activities, the following testable hypotheses, are hypothesized:

Hypothesis 2: The likelihood of MP’s outside connections is associated with constituency level differences.

Sub hypothesis 2.1: The electoral majority affects the likelihood of outside connections.

Sub hypothesis 2.2: The MP’s committee membership affects the likelihood of outside connections.

Third, there might be industry level differences. Previous papers have demonstrated that there is a positive association between the amount of industry regulation and political connections (Bunkanwanicha & Wiwattanakantang, 2009; Cooper, Gulen & Ovtchinnikov, 2010). Carboni (2017) explains that regulations have a significant importance for organizations. The reasoning behind this lies in the fact that regulations are expensive and that they form a barrier for the development of the business (Carboni, 2017). Firms operating in industries that are highly regulated might have a greater interest to create connections with politicians as in this way they can attempt to influence the regulatory environment and its impact on the industry they operate in (Carboni, 2017). Overall, Carboni (2017) provides evidence that organizations operating in highly regulated industries have a higher likelihood of creating relationships with politicians. Claessens, Feijen and Laeven (2008) state that highly regulated industries are for example the telecommunication, financial, electricity, oil or mining sectors. Some industries receive more subsidies to promote their specific industry product (Sobel & Graefe-Anderson, 2018). This implies all the businesses operating in this industry would benefit, which generally increases the overall performance level of business operating within this industry (Sobel & Graefe-Anderson, 2018). These kind of „benefit‟ programs illustrate a model of competition for political support and taking place between various industries (Sobel & Graefe-Anderson, 2018). Therefore, one may say that some industries „win‟ this competition and accordingly receive gains, whereas others do not benefit in any kind of way (Sobel & Graefe-Anderson, 2018). This also shows that for companies operating in various kinds of industries the creation of political connections is essential. Without these connections there is no possibility to influence the policies and no way to benefit the industry the company is operating in. Bearing in mind these arguments, implying that the industry differences could influence the MP‟s engagement in corporate activities, the following testable hypothesis, is hypothesized:

Hypothesis 3: The likelihood of MP’s corporate connections is associated with industry level differences.

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amount received, is an eye-catching fact. Approaching this case from an agency theory perspective, the independent body and the adjustments can help the citizens (principals) to better monitor and check the MPs (agents) behavior (Jensen & Meckling, 1976). Adding to this, it is also possible that after the 2009 parliamentary expenses scandal the MPs‟ public image came under attack. Generally, this might have resulted in MPs putting more emphasis on a good public image. After the parliamentary expenses scandal and introduction of IPSA in 2009, MPs know that they potentially are more actively monitored. This can be either through the IPSA and their enforcement or through the general public and the information disclosed in the Register. This may lead to MPs acting more according to their „expected public behavior‟ and as a result it could decrease the moral hazard behavior MPs were pursuing. It can be said that the adjustments regarding the registration are exposed to a so called self-reporting bias (Geys & Maus, 2012a). The question that arises here is what will happen to MPs caring about their public image. Will they continue reporting their outside jobs? (Geys & Maus, 2012a). The extra information that needs to be registered in the first three categories might also draw scrutiny from the public, which could contribute to a decrease in the MPs‟ stimulus to engage in outside activities (Geys, 2013). Usually the registered information is very difficult to validate (Geys & Maus, 2012a). This is the reason why there always exists a substantial likelihood for under-reporting of MPs. Generally, apart from a MP caring about public image, the above mentioned measurements could result in four outcomes; 1) MPs start taking more responsibility in shape of honestly filling in the Register 2) MPs generally taking less outside positions 3) Some MPs might even further avoid registration and search for new ways to non-register and 4) a combination of one of the previous options might appear.

The 2009 parliamentary expenses scandal and the further enforcement of the Code and, especially, the newly introduced amendment of registering the exact earnings in the first three categories may have lead to a decrease in the information-asymmetry between the principal and the agent (Jensen & Meckling, 1976). Until 2009, there could also have been an imbalance between monitoring and the strong information-asymmetry. The measurements could have helped to restore this imbalance. That is the reason why it is possible the changes in legal frameworks could have influenced the amount and quality of registrations. One may argue that the amount of registrations could potentially decrease after 2009. This indirectly implies there could be a lower likelihood that the MPs are taking outside positions. If the likelihood is affected, the measurements taken show to be effective tools preventing moral hazard behavior of MPs. Overall it is suggested that 2009 could have been a tipping point in the engagement in outside activities and disclosure of information. Bearing in mind these arguments and that the scandal, the introduction of IPSA and the requirement to register exact amounts could have influenced the MP‟s engagement in outside activities but also the (quality of) registrations of these activities in general, the following testable hypothesis is hypothesized:

Hypothesis 4: The likelihood of MP’s outside connections is associated with legal frameworks.

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4. Data & Methodology

4.1 Data sources and data collection

For this study an entirely new dataset was created from scratch. This dataset is the only sample used for this study and consists of 7,389 observations including 1,345 MPs from the House of Commons. The decision has been made to merely focus on MPs for the House of Commons. This is due to the fact that the House of Commons can be considered have more power, and the complexity and range of the data. The sample starts after the general elections of 5 May 2005 and ends at 30 March 2015. The sample starts after the general election of 5 May 2005 because after this date the 54th parliament was installed. During this period of time another general election took place at 6 May 2010, after which the 55th parliament was installed. The sample ends at 30 March 2015 because at this date the 55th parliament was dissolved to prepare for the general elections of 7 May 2015. This period of time was also chosen because it covers two election periods wherein also the power shifted from the labor to the conservative party. The sample covers nearly a decade of registrations and also includes the changes in the legal framework in the UK in 2009.

It is important to highlight here that not every MP sits in the parliament for full 5 or 10 years. This is because some MPs resign, die, are sentenced a severe criminal breach, are confirmed bankrupt or are unable to carry their responsibilities because of mental illness (Parliament UK, 2020). If one of these situations happens, a seat becomes vacant and a by-election is held so that someone else can take over the seat (Parliament UK, 2020). The MPs, who because of one of the previously mentioned reasons, exited the parliament are not registered anymore after their final year in the House of Commons. An example is Stuart Bell who passed away in 2012. Mr. Bell was seated in the House of Commons until 13 October 2012 and was succeeded by Andy McDonald on 30 November 2012. For Mr. Bell data is registered up to and including 2012 and for Mr. McDonald data is registered from 2012 up to and including 2015.

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made it very challenging to collect information from bigger databases such as Eikon. That is the reason why all information on industry and listings was manually assigned. To assign the industry information a publicly available Global Industry Classification Standard (GICS), excel sheet, published on the MSCI website, was used. It was important to learn more about the business in to decide which GICS industry fits best and determining whether the company was listed or not. The company website was searched for and reviewed. Thereby, the UK government has a special website called „Companies House‟ where it is possible to search for companies registered in the UK. This website also presents information about the SIC industries which gave an indication about the industry the company was operating in. Both sources were combined to assign a suitable industry to the company. If neither the website nor the Companies House provided information, other sources were used. These consist of the Register of Member‟s Financial Interest, The Gazette and Bloomberg. Only if absolutely no company information was found on one of the previously mentioned sources, LinkedIn was used. It must be underscored only in a minimum amount of cases this was required. Based on one or a combination of the previously mentioned sources the information on industry and the listing was assigned. If a company was active in two different industries the company history was reviewed to see which industry firstly belonged to the company. Only the company‟s initial industry was registered. In some cases no company information could be found. In this situation the industry group was left blank. Regarding to the company‟s listing, the decision was made to identify a company as „non-listed‟ if the corporation was not found with the help of all previously mentioned sources. The reasoning behind this is that if the company would have been listed, it would have been possible to find it in some kind of way.

Outside connections and earnings are considered to be the most important data and therefore more information on the sources and data collection will be given. The information was collected by relying on the publicly available Register of Member‟s Financial Interest (Register) of the House of Commons, focusing on the period from 2005 until 2015. Table 1 below displays what specific Register was used for which year.

Table 1

The table provides a description of the Registers used per year Year Registers used

2005 14 December, 2005 2006 11 December 2006 2007 18 December 2007 2008 2009* 17 December 2008

10 December 2009, 12 April 2010, 20 December 2010 2010 12 April 2010, 20 December 2010, 13 December 2011 2011 13 December 2011, 19 December 2012

2012 19 December 2012, 9 December 2013 2013 9 December 2013, 8 December 2014 2014 8 December 2014, 30 March 2015 2015** 30 March 2015

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In the Register of Members‟ Financial Interests various categories exist. From 2005 to 2015 some minor changes were made, resulting in twelve instead of ten categories. The minor changes were introduced on 23 June 2009 and 16 April 2012. To be able to decide what categories in the Register are useful, the type and amount of categories were reviewed for every Register. For each Register it was determined what categories were providing information about 1) MP‟s involvement in external activities and/or positions and 2) any kind of external income the MP received. It was determined that for the Registers starting from 2005 up to and including 2008 the following categories provided information on outside activities and earnings, and were therefore used;

1) Remunerated directorships

2) Remunerated employment, office, profession etc. 3) Clients

6) Overseas visits 8) Land and property 9) Registrable shareholdings

10) Miscellaneous and unremunerated interests.

It was decided that for the registers starting from 2009 up to and including 2015 the following categories provided information on activities and earnings, and were therefore used;

1) Directorships

2) Remunerated employment, office, profession etc. 3) Clients

6) Overseas visits 8) Land and/or property 9) Shareholdings 11) Miscellaneous

Appendix A displays all the Register‟s categories and the years wherein these categories were operational. The bold categories were used for the creation of the dataset. It is important to highlight that if there were no earnings registered this does not necessarily mean that there was no earning received by the MPs. This is because from 2005 until mid-2009 for most categories only earnings of more than £590 a year must be registered (UK Parliament, 2005). From 1 July 2009 all earnings for categories 1, 2 and 3 required to be registered (UK Parliament, 2009). For the other categories the threshold varies between £150 and £1,500 (UK Parliament, 2009). This suggests, that it is possible that from 2005 to mid-2009 some information on especially categories 1, 2 and 3 is unknown and therefore is also missing in the dataset. The update of the Code in 2009, could have contributed to a better disclosure of information for especially the first three categories. This also might have resulted in a better completed dataset.

4.2 Variables and measurement

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Table 2

This table provides an overview of the variables and their corresponding definitions. For each variable an example is given in order to get a better idea of what the variable looks like.

Variable Definition Example

Outside connection Whether the MP has an outside connection in a certain year, 1 for at least one outside connection and 0 for none.

0

Corporate connection Whether the MP has a corporate connection in a certain year, 1 for at least one corporate connection and 0 for none.

1

Media engagement Whether the MP has a media engagement in a certain year, 1 for at least one media engagement and 0 for none.

0

Speaking engagement Whether the MP has a speaking engagement in a certain year, 1 for at least one speaking engagement and 0 for none.

1

Gender The gender of the MP, 1 for male and 0 for female. 1

Minister Whether the MP is a minister in a certain year, 1 for yes and 0 for no.

0

Party Which party the MP is affiliated with in a certain year, 1 for conservative and 0 otherwise.

1

Electoral majority The percentage point difference in the voting percentage of the winning party in a certain constituency and the runner-up party in a certain constituency.

0.31

Committee The total amount of committees the MP is member of in a certain year.

3

Industry The industry of the company the MP is connected to in a certain year, 1 if at least one of the companies the MP is connected to belongs to a regulated industry and 0 if none of the companies the MP is connected to belongs to a regulated industry.

0

Listed Whether the company the MP is connected to in a certain year was listed, 1 for at least one company that is listed and 0 for none.

1

Years after 2009 Whether the year is after 2009. The variable takes value 1 for years after 2009 (e.g. 2010, 2011, 2012, 2013, 2014 and 2015) and 0 for 2009 and before (e.g. 2005, 2006, 2007, 2008 and 2009).

0

4.2.1 Dependent variable

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Table 3

This table provides an overview of the variables used to create the dependent variable outside connection. For each variable an example is given in order to get a better idea of what the variable looks like.

These five variables were at first of qualitative nature and were later transformed into quantitative variables (as displayed in table 3). Appendix B provides more information on the initial qualitative variables and explains what was (not) included in the creation of these variables. To create a total amount per variable, all the qualitative information was counted per MP and per year. The sum (total amount) per variable was recorded per MP and per year. This lead to the creation of the five quantitative variables as displayed in table 3. Thereafter, the total amounts of all variables, per MP and per year were summed. This resulted in a variable called total outside connections and displayed the total amount of all connections per MP and per year. Using the variable total outside connections, a dichotomous variable was created named outside connection. The decision to use a dichotomous variable to represent outside connection is based on the fact that the data is skewed and follows a non-normal distribution.

4.2.2 Independent variables 4.2.2.1 Individual characteristics

The individual characteristics consist of three variables namely gender, party and minister. All three are dichotomous variables. Gender takes value 1 for male and 0 for female. Party takes value 1 for Conservative and 0 for other parties. Lastly, minister takes value 1 if the MP is a minister in a certain year and 0 if the MP is not a minister in a certain year.

All three variables were first qualitative variables called male/female, party affiliation and position. These, respectively, indicate whether the MP is a male or female, which party the MP belongs to in a certain year and the ministerial position(s) the MP holds in a certain year. Using male/female, a dichotomous variable was created named gender. Using party affiliation, a dichotomous variable was created named party. Using position, a dichotomous variable was created named minister.

4.2.2.2 Constituency variables

The constituency variables consist of two variables namely electoral majority and committees. Electoral majority is the percentage point difference in the voting percentage of the winning party in a certain constituency and the runner-up party in a certain constituency. Committees shows the total amount of committees the MP is member of in a certain year.

First a variable electoral majority difference was created by taking the percentage of votes for the winning party minus the percentage of votes for the runner-up party in a certain constituency. The result of this is thus the percentage point voting difference between these parties. Only rounded percentages were used. The electoral majority differences were calculated per constituency and for the general elections of 2005, general elections of 2010 and the 35 by-elections. An overview of the

Variable Definition Example

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electoral majority differences per constituency can be found in Appendix D and E. Appendix E also provides an overview of the MPs that exited, entered, the dates of the by-election and the constituencies for which by-elections were held. For the creations of the variable electoral majority the electoral majority differences were divided by 100 so the values would only show to be less than 1.

First a qualitative variable committee membership was created by manually filing in the MPs‟ committee membership in a certain year. The committees that are registered per MP per year imply that the MP is either member of all committees at the same time or switches from one committee to another in the same year. Later, this qualitative data was transformed into quantitative data. All the committee memberships per MP per year were summed. This resulted in the variable committee showing the total amount of committees the MP is member of in a certain year.

4.2.2.3 Industry variables

The industry variables consist of two variables namely industry and listed. Both are dichotomous variables. Industry takes value 1 if at least one of the companies the MP is connected to in a certain year belongs to a regulated industry and 0 if none of the companies the MP is connected to in a certain year belongs to a regulated industry. Listed takes value 1 if at least one of the companies the MP is connected to in a certain year is listed and 0 if none of the companies of the companies the MP is connected to in a certain year is listed. It must be mentioned that both variables originally were of qualitative nature. Creations of these variables are based on various decisions and followed several processes.

First industry will be discussed. After all the industries were manually assigned using GICS‟ industries, the regulated industries were marked. To decide whether an industry belongs to a regulated industry suggestions from previous literature have been used (Borisov, Goldman & Gupta, 2016; Claessens et al., 2008). In this sample an industry was recognized to be regulated if it was assigned to one of the following GICS industries; diversified telecommunication services, wireless telecommunication services, banks, diversified financial services, electric utilities, independent power and renewable electricity producers, oil, gas & consumable fuels, metals & mining, gas utilities, water utilities, transportation infrastructure, road & rail or insurance. After identifying the regulated industries, all the regulated industries per MP and per year were summed. This resulted in the creation of a quantitative variable named total regulated industries and covers the total amount of companies belonging to a regulated industry per MP and per year. Lastly, following Borisov et al. (2006), using the variable total regulated industries a dichotomous variable was created named industry.

After identifying the listed companies, all the listed companies per MP and per year were summed. This resulted in the creation of a quantitative variable named total listed companies and covered the total amount of listed companies per MP and per year. Lastly, using the variable total listed companies a dichotomous variable was created named listed.

4.2.2.4 Legal framework variable

The legal framework variables consists of one variable namely Years after 2009. In 2009 there was a change of the legal framework (introduction IPSA and amendment of the Code). As these changes were introduced in the middle of 2009, the potential effect was measured from 2010 onwards. This variable is a dichotomous variable. Years after 2009 takes value 1 for years after 2009 (2010, 2011, 2012, 2013, 2014 and 2015) and 0 for 2009 and before (2005, 2006, 2007, 2008 and 2009).

5. Results

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performed robustness tests and provides evidence for the robustness of the estimates. Table 7 shows the results of these robustness tests.

5.1 Descriptive statistics

Table 4: Descriptive statistics and correlations

Panel A shows descriptive statistics for variables used in the analysis. The number of observations, average, standard deviation, minimum and maximum are presented per variable. The description of the decisions regarding in the variables remuneration can be found in Appendix C. Decisions regarding the recording of electoral majority can be found in Appendix F.

Panel A: descriptive statistics

Variables N Mean

Standard

deviation Minimum Maximum

Connections 1. Dummies Outside connection 7,389 0.416 0.493 0 1 Corporate connection 7,389 0.192 0.394 0 1 Media engagement 7,389 0.111 0.314 0 1 Speaking engagement 7,389 0.089 0.285 0 1 2. Total connections

Total outside connections 7,389 1.118 2.484 0 50

Total corporate connections 7,389 0.386 1.123 0 14

Total non-profit connections 7,389 0.082 0.390 0 6

Total other positions 7,389 0.194 0.486 0 4

Total media engagements 7,389 0.265 1.104 0 19

Total speaking engagements 7,389 0.191 1.147 0 42

Individual characteristics Gender 7,389 0.788 0.409 0 1 Party 7,389 0.385 0.487 0 1 Minister 7,389 0.166 0.372 0 1 Constituency variables Electoral majority 7,389 0.189 0.125 0 0.66 Committees 7,389 0.723 0.862 0 4 Industry variables Total industry 7,389 0.048 0.323 0 7 Industry 7,389 0.033 0.179 0 1 Total listed 7,389 0.054 0.335 0 8 Listed 7,389 0.036 0.186 0 1 Remuneration

Total earnings total outside connections 7,389 5,773.000 25,738.17 0 565,000

Total earnings corporate connections 720 29,767.32 43,691.55 100 281,680.9

Total earnings non-profit connections 167 12,500.89 14,363.77 20 102,334

Total earnings other positions 233 21,030.92 40,959.41 88 379,450

Total earnings media engagements 713 13,413.79 35,138.14 2.86 420,000

Total earnings speaking engagements 425 10,993.71 31,366.47 5 460,000

Total earnings relative 1,674 0.365 0.456 0 1

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concluded that the majority of the MPs are males (78.8 %). Thereby, only 16.6% of the MPs had a ministerial position over all those years. It is important to mention here that the percentage MPs from the conservative party (38.5%) differs compared to the numbers dislayed in the tables below. This is because my sample looks at a time span of 10 years and thus does not make a distinction between the first and second term. Almost half of the MPs shows to have at least one outside connection (41.6%).It is interesting to highlight that there is a big difference in the total amount of outside connections a MP in a certain year, varying from 0 to 50. Thereby, there is also a large distincition in the MP‟s total amount of speaking engagements in a certain year, varying from 0 to 42. Lastly, the total amount of corporate connections and media engagements in a certain year show quite generous differences, 0 versus 14 and 0 versus 19 respectively.

Looking at the electoral majority we can see that on average the MP won an election with a 18.9 percentage point voting difference from the runner-up. However, also a large distincition is present where the winning MP won the election with a 66 percentage point voting difference compared to the runner-up party in a certain constituency. A full overview of the electoral majority differences per constituency can be found in appendix D and E. The average number of committees shows to be almost one per MP (0.723) and varies between 0 and 4. Appendix G displays all the industry groups including frequencies. The bold indsutries are the ones that are included in the total amount of regulated industries and thus is also used for the creation of the dummy. Summing the frequencies of these bold categories it shows that there are 353 companies assigned to the regulated industry group. Table 4 shows that this makes up only approximately 4.8% of the corporate connections observations. It is important to state that this number looks quite small, however, it must be underscored that also if there is no company connection the industry group is registerd as 0. The same applies to the listed companies. In total there are there areactually 2804 industries registered (summing all frequencies in Appendix G). Comparing 353 to this number it can be concluded that the regulated industries still make up a considerable amount (12.5%) of the total amount of industries registered. This means that approximately 1 out of 7 companies the MP has a connection to operates in a regulated industry. From the MP‟s total amount of corporate connection oberservations approximately 5.4% shows to be a connection to a listed company (=396). Also again 396 applies to the total amount of corporate connection observations and not to the actual total amount of corporate connections (=2,853). Approximately 14% of the companies of the total amount of corporate connections is listed. This means that approximately 1 out of 7 companies the MP has a connection to is listed. Thereby the maximum amount of companies the MP is connected to that is assigned tot his regulated industry group is 7 and the minimum is 0.

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Looking at the earnings for corporate connections it can be seen that the average earnings per MP, out of 720 who showed to have a coprorate connection, is £29,767.32. Something that may also be interesting is that MPs earn with their non-profit connections approximately 40% of the corporate connections. Hearing the word „non-profit‟ you would expect that such organizations do not recklessly spend their money on expensive directorships. Still it seems a considerable of the income generated goes to paying MPs for being involved in their organization. Lastly, the earnings relative show that the remuneration received from corporate connections forms around 36% of the total income received from all outside connections. Overall it can be concluded, the earnings received are noticeably high and very contrasting.

To see whether there is a significant difference between male and female MPs‟ total received outside earings regarding a t-test was performed. As the sample size for female (=1,567) and male(=5,822) differs it cannot be assume that the variances are equal. That is why a Welch approximation t-test was used. With a smaple of 7,389 MPs it is determined whether there is a significant difference between the males (=1) and females (=0) total average outside earnings registers. The resuls shows that the males do have statistical significant higher average total outside earnings registered (6,675.75± 363.67) compared to females (2,418.95± 398.46) with t(-7.89) = 4,436.97, p = 0.000.

Figure 2: Graphical representation of the total connections per category

The figure below shows the total amount of connections per category and per year.

From figure 2, it can be acknowledged that for all outside (996), corporate (343), other positions (189) and media (261) the peak of the amount of connections shows te be in 2010. For the above mentioned categories, the time span between 2010 and 2011 shows either a sharp decline (e.g. total outside connection and total corporate connections) or a gradually decreasing number (e.g. other positions and media). Also afer 2010, the total non-profit connections decreased and in the following years gradually increased again, reaching its peak in 2014 (76). Looking at the total amount of speaking engagements, the peak is reached in 2009 (202) and in the following years fluctuates. In 2012 this catgory reached its second-highest point and over the following years it decreased. This graph gives an indication that 2009 and 2010 have been crucial years and thus something might impact on the likelihood on connections in these years. It must be mentioned that these descriptives are merely an examination of the data and chapter 5.4 displays the results of the logit analysis and provides an answer to the hypotheses. 0 200 400 600 800 1000 1200 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 To tal co n n e ction s Year

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5.2 Elected political parties

Throughout history, and still today, in the UK parliament there are two leading parties (three if also the Liberal Democrats are taken into account). These are the Labour Party and the Conservative Party (UK Parliament, 2020). Table 5 provides an overview of the other main elected parties in the 2005 and 2010 general elections for the House of Commons.

Table 5: Political parties and election summary

Both panels provide an overview of the elected political parties, the percentage of received votes, the amount of assigned seats in the House of Commons and the political stance. Panel A displays the results of the 2005 elections, whereas Panel B presents the results of the 2010 elections.

Panel A: election results 2005

Political party Percentage of votes Seats Political stance

Labour 35.2 355 Centre-left

Conservative 32.4 198 Centre-right

Liberal Democrats 22.0 62 Centre to centre-left

Democratic Unionist 0.9 9 Centre right to right-wing

Scottish National 1.5 6 Centre-left, catch-all party

Sinn Féin 0.6 5 Centre left to left-wing

Plaid Cymru 0.6 3 Centre left to left-wing

Social Democratic and Labour 0.5 3 Centre-left

Ulster Unionist 0.5 1 Centre-right

Respect 0.3 1 Left-wing to far left

Panel B: election results 2010

Political party Percentage of votes Seats Political stance

Conservative 36.1 306 Centre-right

Labour 29.0 258 Centre-left

Liberal Democrats 23.0 57 Centre to centre-left

Democratic Unionist 0.6 8 Centre right to right-wing

Scottish National 1.7 6 Centre-left, catch-all party

Sinn Féin 0.6 5 Centre left to left-wing

Plaid Cymru 0.6 3 Centre left to left-wing

Social Democratic and Labour 0.4 3 Centre-left

Green 1.0 1 Left-wing

Alliance 0.1 1 Centre

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5.3 Regression model specification

Previous literature explains that outside connections do not appear randomly. MPs are affected by various factors whether to engage in connections or not (Galasso & Nannicini; 2011; Geys & Mause, 2012). The focus will be on presenting various factors that could potentially affect the likelihood of MPs‟ outside connections. A diversified set of factors are taken into account, ranging from factors that have been discussed in previous research (e.g. gender, electoral majority and total amount of committees) to newly introduced variables (e.g. minister and changes to legal framework in 2009). The fact that the dependent variable only takes value 1 or 0, a logit model estimation is used. In this research four models were estimated and are displayed below. The estimations for outside connection and corporate connection are included because these follow from the hypotheses. Previous research has already discussed MPs‟ connections to corporations and non-profit organizations (Geys 2013). Thereby general other professions (e.g. barrister or GP) the MP holds is something that has been reviewed before (Geys 2013; Geys & Maus 2012a). Therefore, to provide new insights only separate estimations for media and speaking engagement are included. To the researchers‟ knowledge such models have not yet been discussed before. In the all equations the subscript i is referring to the individuals and thus MPs, t is referring to the time and thus year and j is referring to the firm. The error term is displayed as ε.

(1) Outside connectionit =β0 + β1 (Genderi) +β2(Partyit) + β3(Ministerit) + β4 (Electoral majorityit) + β5 (Committeesit) + β6 (Years after 2009t) + εit

Equation (1) is estimated with a dichotomous variable taking value 1 if the MP has at least one outside connection in a certain year and 0 if the MP has no outside connection in a certain year. In hypotheses 1, 2 and 4 it is predicted that the MP‟s individual characteristics, constituency variables and legal frameworks will affect the likelihood of outside connections.

(2) Corporate connectionit =β0 + β1 (Genderi) +β2 (Partyit) + β3 (Ministerit) + β4 (Electoral majorityit) + β5 (Committeesit) + β6 (Industryj) + β7 (Listedj)

+ β8 (Years after 2009t) + εit

Equation (2) is estimated with a dichotomous variable with value 1 if the MP has at least one corporate connection in a certain year and 0 if the MP has no corporate connection in a certain year. In hypotheses 1, 2, 3 and 4 it is predicted that the MP‟s individual characteristics, constituency variables, industry variables and legal frameworks will affect the likelihood of corporate connections.

(3) Media engagementit =β0 + β1 (Genderi) +β2 (Partyit) + β3 (Ministerit) + β4 (Electoral majorityit) + β5 (Committeesit) + β6 (Years after 2009t) + εit

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4) Speaking engagementit =β0 + β1 (Genderi) +β2 (Partyit) + β3(Ministerit) + β4 (Electoral majorityit) + β5 (Committeesit) + β6 (Years after 2009t) + εit

Equation (4) is estimated with a dichotomous variable with value 1 if the MP has at least one speaking engagement in a certain year and 0 if the MP has no speaking engagement in a certain year.

5.4 Empirical findings

In this section the results of the logit estimation models are presented. Table 6 gives an overview of all the marginal effects per equation.

Table 6: Regression analysis results

Panel A shows the marginal effects of various variables on all outside connections. Panel B shows the marginal effects of various variables on corporate connections. Panel C shows the marginal effects of various variables on media engagements. Panel D shows the marginal effects of various variables on speaking engagements. For Panel A, C and D; model 1 shows the effect of the individual characteristics on connections/engagements, model 2 adds the effect of constituency variables on connections/engagements, model 3 adds the effect of the legal frameworks on connections/engagements. For Panel B; model

1 shows the effect of the individual characteristics on corporate connections, model 2 adds the effect of constituency variables

on corporate connections, model 3 adds the effect of the industry variables on corporate connections and model 4 adds the effect of the legal frameworks on corporate connections. The intercept, number of observations and pseudo R-squared are presented per model. *, ** and *** denote significance at the 1%, 5% and 10%, respectively. The numbers in the parentheses display the standard errors.

Panel A: The marginal effects of various variables on all outside connections

Variables (1) (2) (3) Gender 0.117*** (0.014) 0.113*** (0.014) 0.112*** (0.014) Party 0.268*** (0.009) 0.270*** (0.009) 0.271*** (0.009) Minister -0.197*** (0.015) -0.207*** (0.016) -0.206*** (0.016) Electoral majority 0.106** (0.044) 0.105** (0.044) Committees -0.006 (0.006) -0.005 (0.006) Years after 2009 -0.010 (0.011) Intercept -1.143*** (0.061) -1.199*** (0.074) -1.175*** (0.079) N 7,389 7,389 7,389 Pseudo R2 0.091 0.092 0.092

Panel B: The marginal effects of various variables on corporate connections

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23 Committees 0.002 (0.005) 0.007* (0.004) 0.010** (0.004) Industry 0.609*** (0.074) 0.609*** (0.074) Listed 0.633*** (0.074) 0.629*** (0.074) Years after 2009 -0.030*** (0.008) Intercept -2.973*** (0.105) -3.061*** (0.118) -3.015*** (0.126) -2.868*** (0.131) N 7,389 7,389 7,389 7,389 Pseudo R2 0.150 0.151 0.295 0.297

Panel C: The marginal effects of various variables on media engagements

Variables (1) (2) (3) Gender 0.031*** (0.010) 0.024** (0.010) 0.027*** (0.010) Party 0.017** (0.007) 0.021*** (0.007) 0.017** (0.008) Minister -0.057*** (0.012) -0.071*** (0.012) -0.075*** (0.012) Electoral majority 0.173*** (0.029) 0.176*** (0.028) Committees -0.009** (0.004) -0.011** (0.004) Years after 2009 0.037*** (0.008) Intercept -2.327*** (0.094) -2.558*** (0.114) -2.779*** (0.126) N 7,389 7,389 7,389 Pseudo R2 0.009 0.017 0.022

Panel D: The marginal effects of various variables on speaking engagements

Variables (1) (2) (3) Gender 0.023** (0.009) 0.015* (0.009) 0.015* (0.009) Party 0.021*** (0.007) 0.027*** (0.007) 0.027*** (0.007) Minister -0.073*** (0.012) -0.086*** (0.012) -0.086*** (0.012) Electoral majority 0.203*** (0.026) 0.203*** (0.026) Committees -0.005 (0.004) -0.005 (0.004) Years after 2009 -0.001 (0.007) Intercept -2.554*** (0.104) -2.957*** (0.127) -2.950*** (0.135) N 7,389 7,389 7,389 Pseudo R2 0.015 0.029 0.029

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Table 6, Panel A presents the results of the marginal effect of various variables on the likelihood of at least one outside connection. Model 1, 2 and 3 all show positive significant effects for the individual characteristics. Model 3 shows that gender has a positive significant effect (β1 = 0.112; P

≤ 0.01). A one-unit increase in gender would increase probability of having at least one outside connection with 11.2 percentage points. In other words going from female MP to male MP it would increase the probability of having at least one outside connection with 11.2 percentage points. Male MPs have a higher probability of having at least one outside connection, compared to female MPs. Thereby, also a positive significant effect for the variable party is found (β2= 0.271; P ≤ 0.01). This

implies that with a one-unit increase in party the probability of having at least one outside connections increases with 27.1 percentage points. In other words going from any other party to the conservative party it would increase the likelihood of having at least one outside connection with 27.1 percentage points. Thus, a MP from the conservative party has a higher probability of having at least one outside connection, compared to non-conservative party MPs. Lastly, looking at the minister variable, it shows to have a negative significant effect (β3= -0.206; P ≤ 0.01). This means that with a one-unit increase in

minister the probability of having at least one outside connections decreases with 20.6 percentage points. In other words going from non-minster MP to minister MP decreases the likelihood of having at least one outside connection with 20.6 percentage points. A minister MP has a lower probability of having at least one outside connection, compared to a non-minister MP. Electoral majority (β4= 0.105;

P ≤ 0.05) is positive significant. This implies with a one percentage point increase in the electoral majority the probability of having at least one outside connection would increase with 10.5 percentage points. Thus a MP who has a higher chance to win the elections in a certain constituency, will have a higher probability of having at least one outside connection. The other two variables namely committees (β5= -0.005; P > 0.10) and years after 2009 (β6= -0.010; P > 0.10) show negative

insignificant results. Overall, these results show that all sub hypotheses 1 are supported and thus hypothesis 1 is fully supported. Only sub hypothesis 2.1 is supported, whereas sub hypothesis 2.2 is rejected. Overall hypothesis 2 is partially supported whereas, hypothesis 4 is rejected.

Table 6, Panel B presents the results of the marginal effect of various variables on the likelihood of at least one corporate connection. In this panel we can see that in model 4 all effects are significant. Model 4 shows for example shows that for electoral majority the marginal effect shows to be negative and significant (β4= -0.092; P ≤ 0.01). This implies with a one percentage point increase in

the electoral majority the probability of having at least one corporate connection would decrease with 9.2 percentage points. Therefore a MP who has a higher chance to win the elections in a certain constituency, will have a lower probability of having at least one corporate connection. This can also be argued the other way around, a MP who has a lower probability to win the election in a certain constituency, will have a higher chance of having at least one corporate connection. Committees shows to have a positive significant effect (β5= 0.010; P ≤ 0.05). This implies with a one-unit increase

in committees the probability of the MP having at least one corporate connection would increase with 1 percentage point. In other words if the MP is going from, for example, one to two committee memberships the likelihood of this MP having at least one corporate connection increases with 1 percentage point. If a MP has more committee memberships it increases the MP‟s probability of having at least one corporate connection. Looking at industry we see a positive significant effect (β6=

0.609; P ≤ 0.01). This means that with a one-unit increase in industry it increases the probability of having at least one corporate connection by 60.9 percentage points. In other words a company going from a non-regulated industry group to a regulated industry group it increases the likelihood of the MP having at least one corporate connection with 61 percentage points. Also listed shows to have a positive significant effect (β7= 0.629; P ≤ 0.01). This implies a one-unit increase in companies listed

The influence of diversified factors on non-parliamentary activities in the United Kingdom: a descriptive and explanatory research