Economic institutions

Following the War, Europe designed the Common Agricultural Policy, which has resulted in effective institutional arrangements, which in turn has improved agriculture in a spectacular fashion.

Contract farming represents an agreement between farmers and contractors (mostly processing and/or marketing firms) for the production and supply of agricultural products.

Under contract farming, farmers usually agree to deliver specific commodities in predetermined quantities and to meet predetermined quality standards, while contractors agree to provide production support (e.g. supply of input and provision of technologies) and accept products at predetermined prices (Eaton and Shepherd, 2001). These institutions are highly developed in Europe, which has resulted in a significant power base to the farm lobby over the years.

It is well known that the most important advantage of genetic modification is its potential to allow farmers to grow crops with high yields while using less herbicide.

90 According to a research by the Economic and Social Research Council in the UK, in what is claimed to be the first systematic examination of what large-scale farmers think about genetically modified crops, new technology such as GM is attractive to farmers since they want to produce high-quality food profitably and they want to farm in an environmentally sensitive way, and that genetic modification may allow them to reconcile this conundrum by doing both of these things at once.²⁷ Thus, while the consumer in Europe appears to be against GM foods, European farmers tend to favor genetically modified crops for the above reasons.

Since the farming sector is closely linked to the issue of genetic modification of food, the size of the agricultural sector (normalised as a % of a country’s GDP) may have an impact on the importance of this issue amongst the population. Although activists such as José Bové in France, along with organized NGOs such as Greenpeace and Friends of the Earth ensure that the noise levels against the use of genetic modification in agriculture remains at a high level, this has not hampered the farmers’ interest in GM crops. Thus, it is hypothesised that the media will support the farm lobby and hence be less negatively biased against GM foods in countries where agriculture is seen as an important activity and the general population consequently has a more sympathetic attitude towards the farming community.

H3a: The higher the share of agriculture to total GDP of a country, the lower will be the negative media bias towards GM foods.

The food industry is yet another important stakeholder in the GM foods issue and the strong institutional linkage between the farming sector and the food industry is a major reason for the success of European agriculture in the last 50 years. The strategy followed by European food companies has been a subject of debate in Europe, and it is planned to study their reactions to this issue at a later stage of this research. Consumer opinions on food companies in general have deteriorated and the trust levels have declined over the last couple of decades. At this stage, it is felt that in countries where the food industry is

27http://ec.europa.eu/research/biosociety/news_events/news_whatfarmersthink_en.htm

91 proportionately larger, the media will play the role of a gate-keeper and bias the population against GM foods and thus ‘warn’ them about the dangers of such a new technology and the possibility of these ‘powerful’ food companies using such a technology.

Thus a lack of organized interest groups against the bias will favor the development of reputation cascades, which will be measured through the two interest group variables:

‘relative importance of agriculture’ and ‘the size of the food industry per capita’. This is in line with the theoretical approach on the creation of reputation and information cascades by Bonardi and Keim (2005).

H3b: The higher the size of the food industry per capita of a country, the higher will be the negative media bias towards GM foods.

Yet another variable chosen as an economic indicator was the % population that has access to internet. Access to internet in a particular country is mostly under the control of the government, and a strong support from the various European governments in building both formal and informal institutions is also reflected in the generally high level of internet access across European countries. In the aggregate, a newspaper reader, with access to all news sources, could get an unbiased perspective (Mullainathan, Shleifer (2005)). This should mean that in those countries where the population has a higher access to internet, the supply side of media bias (bias from the newspapers) will be less effective.

Extending the analysis of Bonardi and Keim (2005), institutional arrangements favoring access to outside information can be argued to make it more difficult for informational cascades to take place, and information competition can stop or slow down this process.

This research plans to measure such an effect through the two variables ‘education’ and

‘internet access’.

H3c: The higher the access of a country’s population to internet, the lower will be the negative media bias towards GM foods.

92 3.4 Data and methodology

The study analysed the contents related to news coverage on GM foods in selected European newspapers over a period of 6 years (from 1^st January 2005 to 31^st December 2010). The detailed methodology is given in Chapter 2 of this thesis.

The negative bias score for the contents of each article was used as the key indicator in the present analysis. A dummy variable was created out of this cscore (content score) to reflect the negative bias scores. This was chosen as the dependent variable of the regression analysis. The different variables mentioned in the hypotheses section were treated as the independent variables.

While freedom of press is an important independent variable to be considered in this analysis, the problem of possible endogeneity with the dependent variable, media bias, has to be taken into account. The problem of endogeneity occurs when the explanatory variable in an econometric model is correlated with the error term in a regression model. The level of freedom the press has will have an impact on the direction and level of bias that the media choose to be associated with. But it is also possible that the direction and level of bias imparted by the media may well be a measurement of and an influencing factor for the level of press freedom in that country. Thus there is a concern about reverse causality or endogeneity when these two variables are used in a regression model. In our case, the problem of endogeneity can also be due to some missing variables, particularly related to the activists such as Greenpeace (who influence the media), as well as the private sector which all influence media bias. The data on these variables could not be obtained for this analysis.

In order to ensure the robustness of the regression, an instrumental variable analysis has been used at this stage. An instrument is a variable that does not itself belong in the regression equation and is correlated with the endogenous explanatory variable, conditional on the other covariates. There are two main requirements for using an instrumental variable:

1) the instrument must be correlated with the endogenous explanatory variable, conditional on the other covariates, and 2) the instrument cannot be correlated with the error term in the

93 explanatory equation, i.e. the instrument cannot suffer from the same problem as the original predicting variable.

Thus, it is important to find a suitable instrumental variable that can be used for the regression equation.

Petrova (2008) compares the relationship between media freedom and public spending on health and education in democracies and autocracies. In democracies, the study found that media freedom was significantly related to higher spending in these sectors. The public expenditure devoted to health care (expressed as a proportion of GDP) represents a suitable cross‐national proxy for measuring the priority with which this critical component of social wellbeing is given by elected officials.

While that study found some correlation between press freedom and government expenditure on health (R² =.207), the correlation observed between these two variables in the present study is much stronger at 0.66 as seen below:

the negative sign of the correlation is consistent with a positive correlation between press freedom and per capita public health expenditure since press freedom is expressed as a rank, and thus the lower the rank, higher the press freedom.

Hence, it was decided to use government health expenditure as the instrument in this study in order to account for the possible endogeneity effect between the two variables, press freedom (explanatory variable) and media bias (dependent variable).

While the iv, per capita public health expenditure, is strongly correlated with press freedom, why could it be uncorrelated with the error term of the second stage regression? Why would it not suffer from the same challenge as press freedom? Firstly, the correlation between the

healthexpp~p -0.6635 1.0000 pfreedom 1.0000

pfreedom health~p (obs=3045)

. cor pfreedom healthexppercap

94 media bias score and per capita public expenditure was small at -0.0035. Further, the government exerts a strong and significant influence on both the chosen instrument variable (public health expenditure) as well as the press freedom variable, although the government is only one of the many variables of influence in the case of media bias. This further strengthens the choice of the instrument in this analysis.

Thus, due to the possible endogeneity problem associated with the variable pfreedom (press freedom), the government expenditure on health was chosen as the instrument and an instrumental variable probit regression was run using Stata.

An ivprobit regression with a stata command 'robust' was run to ensure that the standard errors are appropriately estimated, and the chi sq. value of the Wald test of exogeneity was found to be 0.000. This also indicated that an instrument will be required in this particular case.

3.5 Results

The Hasuman test using the ‘per capita public expenditure’ variable as the instrument gave the prob >chi sq. as 0.0233. Hence the hypothesis of exogeneity was rejected at 0.05.

Table 3.1 gives the results of the first stage of the ivprobit regression, the beta coefficients as well as the marginal effects. The inclusion of country fixed effects and year effects did not give significant coefficients. It can be seen that for one standard deviation increase in health expenditure (standard deviation = 1132.76) the press freedom ranking goes up by around 3.

95 Table 3.1 Effect of institutional variables on the negative bias of content score

(Instrument variable regression) Dependent variable: dummy of negative bias of content score (dcsore)

Variables dcscore

Note: standard errors shown in brackets

*, ** and *** represent significant levels at 10%, 5% and 1% respectively

Hypotheses H1a and H1b related to two political factors, press freedom, and EU vs non-EU.

Thus, it can be seen from Table 3.1 that both the political factor hypotheses H1a and H1b (concerning press freedom and EU vs non-EU respectively) cannot be rejected.

The demographic factors appear to be relatively unimportant in this context. While hypothesis H2a (% Catholic population) is almost valid, hypothesis H2b (% graduates) is rejected.

Two of the economic factors tested, agricultural output as a % of total GDP as well as % of people using internet, have proved to be significant, thus hypotheses H3a and H3c cannot be rejected. However, the variable food industry size per capita is not significant and hence hypothesis H3b is not proved.

While the p values from the probit regression are the basis for the validity of the hypotheses, the strength of the selected independent variables is measured by the marginal effects of the

96 regression analysis. While the dy/dx value for the variable ‘agricultural output as a % of total GDP’ is around 0.05, the corresponding values for the other significant variables are 0.01 and below. These results indicate that institutional factors may play a secondary role, along with the supply and demand factors as explained earlier, in determining media bias. Hence, these institutional factors do influence the media bias, which is often said to be ‘liberal’ and thus ‘anti-capitalist’.

‘Press freedom’ as a variable has been used along with its instrument ‘public expenditure on healthcare as a % of GDP’ in order to avoid endogeneity issues. Mullainathan and Shleifer (2005) show the differences between the biases based on spin and ideology. While theirs is a theoretical model, I have adapted their argument in my empirical result to argue that the European media treats the issue of GM foods as a spin bias since a majority of the articles show a negative coverage (if it were an ‘ideology’, the scores will be more or less even). An increasing level of press freedom should increase the media bias against GM foods, and the dy/dx value of -0.14 in the ivprobit regression shown in Table 3.1 shows that the hypothesis that higher the level of press freedom, higher will be the media bias against GM foods cannot be rejected. It should be mentioned again that press freedom is used as a ‘rank variable’, i.e.

lower the rank number, higher is the press freedom. In other words, the country with a rank 1 has the highest press freedom.

3.6 Discussion

The impact of political institutions on media bias is on expected lines since various studies have shown the constant interaction between the two. However, the possible influence of economic factors such as agriculture as % of GDP and internet penetration on media bias is certainly more interesting.

Farmers in Europe, in general, are in favor of genetic modification of crops. The majority (61%) of the sampled Greek farmers in the study by Skevas et al. (2012) responded positively about cultivating Bt maize if the ban is lifted. The authors argue that their results are in line with Skevas et al. (2009), who conducted a survey of GM and non-GM maize

97 farmers in Portugal. They found that 50% of the non-GM maize farmers were open to cultivating GM maize, 2% were answered negatively, and 48% were undecided. The authors also quote a Polish Federation of Biotechnology (PFB, 2004) survey on the knowledge and acceptability of GM crops by Polish farmers which found that 59% of the interviewed farmers would like to have the choice to cultivate GM crops, and that a more recent farm report from Poland (PFB, 2006), presenting results from GM crops’ marketing tests, revealed that 42%

and 85% of the respondents agree that GM seeds should be commercially available and farmers should have the right to choose whether to cultivate GM crops, respectively. Finally, Areal et al. (2011) show that in a recent study among farmers in Spain, France, and Hungary on the potential adoption of herbicide-tolerant maize, it was found that a low rate of French (37%) and Hungarian (38%) farmers agree with their countries’ bans on Bt maize and the governments’ strong opposition towards GM crops. Thus, it is interesting that the current study supports the hypothesis that higher the share of agriculture in the GDP of a country, lower will be the negative media bias towards GM foods; in other words, newspapers tend to be influenced by this variable regarding the level and type of bias against GM foods.

The increasing access to internet in Europe has increased information competition across countries (as against national newspapers whose circulation is mostly restricted in the country of origin) which in turn will slow down the process of bias in one specific direction.

Thus, the notion that higher the access of a country’s population to internet, lower will be the negative media bias towards GM foods holding true within Europe is understandable.

However, we are clearly talking of this variable in a democratic context, since in a country such as China, where internet penetration is growing very rapidly (10% growth in 2013 to 591 million users according to Pew Research Center), the strong political control of the internet will provide a very different view and the resulting analysis of the bias in such a country.

The variable food industry as a % of GDP may be less effective due to the free transport of goods across EU countries, which does reduce the specificity of this variable to some extent.

98 Thus, while the selected political and economic factors have largely proved to be influencing media bias, the selected demographic factors do not appear to be very relevant. The variable ‘catholic population’ is somewhat weakened by the fact that a growing population in Europe refuses to be associated with any religion. On the other hand, education as a variable, reflected by the % of university graduates in a specific country has very little impact on the negative bias.

This work clearly takes the discussion of media bias away from the political sphere to a much wider institutional environment. Interestingly, Buss (2007) argues that there is a need for an institution which the author calls “the public court” that would play a role of an effective medium between the politicians and the public, which in essence is an unbiased and idealistic on-line media which will provide debates amongst politicians so that the public can make informed decisions in their choice of candidates. Such an attempt to establish totally unbiased media, although interesting, still remains a dream. As can be seen in this paper, some of the institutional factors do play a role in influencing the bias by media when new and perceived to be harmful technologies are launched. While institutional factors cannot be directly influenced by individual activists, they can use these factors in their favor when they understand the impact of these factors on media bias.

It should be mentioned that institutional economics is the only field of economics that also encompasses both the cultural and social aspects of the society and hence it can act as an ideal lens for the activists to examine media bias as explained in this paper.

3.7 Conclusions

The above analysis indicates that media is likely to bias negatively when a new technology/product/service is generally viewed by the population as risky for health or for the environment. These risky sectors would currently include mobile telephones and telephone towers, nuclear technology, powerful chemicals, etc.

The role and influence of some institutions, both formal and informal, on media bias against a new technology with a presumably harmful side to it, is confirmed albeit their secondary

99 importance. Institutions can and do shape the various economic and social activities of a society and the variations in the levels of some of these institutions across countries and regions do impact on the level and direction of media bias - in this case, specifically against genetically modified foods in Europe.

3.8 Limitations and future research

A limitation of the study can be the assumption that activists have spread their efforts equally across countries in Europe. This is because ‘activists’ as a variable could not be used in this study due to lack of data availability, such as their expenditure on GM-related projects, number of brochures on GM food distributed by country, number of articles written in local press, number of press conferences by country, number of employees by country, etc. Any future research in this area will have to take this factor into account and possibly involve one or more of the leading activists in the project and obtain the relevant data for further analysis.

Yet another limitation is linked to the methodology used. As mentioned in section 1.7 in the Introduction chapter, the measurement used (reader perception of the bias) will be applicable

Yet another limitation is linked to the methodology used. As mentioned in section 1.7 in the Introduction chapter, the measurement used (reader perception of the bias) will be applicable