The change of cultural values over time is an issue that concerns, among other things, economic science, as this change is responsible for the reform of the economic, political and social life of societies. Boyd and Richerson (2005) argue that cultural change should be considered an evolutionary process based on Darwin’s theory, in which some cultural values become more common and others are lost.

The general observation about the change in cultural background is that it remains relatively stable over time “under normal conditions”. This conclusion emerges simply if one considers that the cultural dimensions that shape the cultural background remain relatively constant over time (De Jong, 2009; Petrakis and Kostis 2014). The cultural background often appears stable at any given time because cultural mutations occur gradually (Jones, 2006). Research (Johnston, 1996) shows that stereotypes are generally very resistant to change and redefinition. Individuals who have adopted specific cultural characteristics tend to retain them in the process of gathering information. Therefore, they do not show signs of change in existing stereotypes.

Thus, the fact that the cultural dimensions and consequently the cultural background remain stable “under normal conditions” leaves much room for reflection and control of these conditions. Eurozone has suffered much from the crisis and many of its members adopted adjustment programs, significantly changing the function of the economies and the general living conditions.

The aim of the present paper is to investigate the effects of uncertainty on cultural values change. The main hypothesis examined is whether conditions such as those related with the recent global financial crisis of 2008 have led to changes in behaviors and values and, thus, on the cultural background of the societies.

The structure of the paper is as follows: In Section 2, a literature review is presented regarding the factors that may lead to cultural background change. Section 3 presents the data used in the empirical analysis, as well as the methodology employed. Then, Section 4 presents the empirical results. Finally, the basic conclusions of the overall analysis are presented.

The factors that exogenously influence the creation and shaping of the cultural background of a society are related to specific conditions that prevail in that society. The most serious sources of external influence on the formation of the cultural background are considered to be the available resources, the climate and in general the geographical features (McClelland, 1961; Diamond, 1999; Tavassoli, 2009; Triandis, 2009; Petrakis, 2014). These are factors that do not change or change gradually over time. As these factors create the background for the formation of the cultural background of a society, any change they show affects the prevailing cultural background accordingly.

Globalization is also considered an important factor in changing the cultural values of societies. Two conflicting schools of thought regarding the impact of globalization emerge. The first school of thought is based on the theory of modernization (Inglehart and Baker, 2000), arguing that globalization contributes to the convergence of differences between cultural backgrounds, as political and social forces lead to a change in cultural values. The consequence of globalization is the creation of a network of cultural values (Hermans and Kempen, 1998). This grid is based on common features between different societies that interact with the local cultural background of the societies, ultimately leading to a cultural transformation with high coherence between cultural fields. The second school emphasizes the stability and “resilience” of traditional values to the economic and political changes that are taking place under globalization. DiMaggio (1994) argues that the resistance of traditional values to change stems from the fact that these values are independent of economic change.

The aging of the population is another cause of incremental changes in the cultural background in recent decades. While the greatest differences in personality occur in adolescence (Borghans et al., 2008), significant changes in personality characteristics appear—even to a lesser extent—later in life. As individuals grow older, they become more emotionally stable personalities (Roberts et al., 2006). At the same time, behavior associated with being open to new experiences is something that increases at younger ages and decreases at older populations (Roberts et al., 2006). As people get older, they tend to become more “myopic” in the sense that they appear more oriented in the present while they do not seem to be particularly interested in long-term situations. In addition, older people are considered more politically active, forming the main bulk of the electorate and relying more on traditional and materialistic values.

In addition, developments such as generational replacement, increased access to higher education, urbanization, increasing gender equality and increasing national diversity have led to the shift of cultural values from materialistic to post-materialist, from the 1970s onwards (Norris and Inglehart, 2016, 2019). These developments have also brought about gradual changes in the cultural background.

The above changes in cultural background do not happen suddenly and so can be characterized as incremental. Significant but also sudden are the changes observed in the cultural background after an external shock. It is a fact that crises tend to “give birth” or accelerate cultural changes which, if accepted once because of the crisis, tend to become permanent. Changes of this type can cause high stress in individuals (Eschbach et al., 2001), affecting their psychological adaptation to new conditions and can be a strong shock to the context of cultural values that characterize the societies. In such cases, the result is a change in cultural background, which is usually much faster than the incremental change described above.

An example is the recent financial crisis of 2008, which has affected most economies worldwide. Economic developments significantly affect the cultural background of individuals. Thus, the economic crisis not only affects economies but also societies and more specifically their cultural background (Magee et al., 2013). As a result of the global financial crisis, there were significant economic consequences for economic actors, which led to significant stress and psychological pressure (Eschbach et al., 2001; Petrakis 2011; Sargent-Cox et al., 2011). Casanova (2018) focuses on political culture and values and examines whether it changed after the financial crisis of 2008 in those countries that adopted an adjustment program in Europe, noting that people’s orientation towards politics and democracy got worse in those countries in relevance to the other European countries. Proponents of the insecurity hypothesis argue that the economic stress, insecurity and austerity experienced by individuals as a result of the crisis have changed their cultural values and are responsible for the rise of the populist wave (Norris and Inglehart, 2019; Rodrik, 2019).

To investigate the relationship between uncertainty and culture, an unbalanced panel dataset, for the Eurozone countries1 for the period from 2002 to 2018, is used. The choice of the time period under consideration is determined by the availability of data regarding culture, based on the European Social Survey (ESS) waves that have been released during that period.

To examine the effects of uncertainty on cultural background, the following equation is estimated: (1) Cultur e it = a i +βUncertaint y it + λ t + u it , where i denotes the economies of the Eurozone (N_max = 18) and t is the ESS wave under analysis (T_max = 9). The dependent variable Culture is a vector of variables that represent the cultural background, Uncertainty is an index of economic uncertainty, a_i is a constant term that captures the country-specific fixed effects and which records the country-specific time-invariant heterogeneity. Finally, λ_t is a set of dummies that control for specific effects per wave that are common to all economies under analysis.

The estimation of Equation (1) is done through the two ways fixed effects analysis (FE), which allows the economy-specific heterogeneity using a different constant term per economy and can be estimated using the standard least squares method (OLS). In addition, time dummies for each wave are included in order to incorporate in the analysis time effects that are common to all countries in the sample. In addition, cluster-robust estimates of the standard errors were taken into account in order to control for the correlation and heteroskedasticity for each economy.

In order to construct the Economic Uncertainty Index, following our previous research work (Petrakis and Kostis, 2014; Kafka et al., 2020), daily data of high capitalization stock indices are used for the countries under analysis. Additionally, as a proxy for global uncertainty, an Index is calculated that expresses the Global Stock Market based on the daily prices of the largest stock markets (USA, Canada, Mexico, Brazil, Eurozone, United Kingdom, Japan, China–Hong Kong, and India) as the weighted average based on the Gross Domestic Product (GDP) of each economy (GDP at current prices) as derived from the International Monetary Fund (IMF) World Economic Outlook Database.

Table 1 presents the indices used for each country under analysis, as well as the major stock indices used to construct the global stock market index. This table also presents the descriptive statistics of those indices, after maintaining only the daily prices for which data were available for all countries. All data were obtained using Reuters Datastream.

Then, an Economic Uncertainty Index (UI) is created for each economy by calculating the rolling standard deviation of the previous 30 days of the returns of the main stock index of each economy. To isolate the shocks due to each economy, the monthly average of this index (standard deviation of 30 days) is regressed on its global counterpart and the residuals of each regression are marked as the uncertainty index for each economy. The monthly evolution of the residuals of each regression is the monthly evolution of the uncertainty index of each country from 2001 to 2018. Next, these monthly UI data are converted into biennial data to be compatible with the culture values that get released in waves every two years by the ESS. The climate of uncertainty increases on dates of significant political and economic turmoil. Since the onset of the crisis, most Eurozone economies have been hit by a series of uncertainty shocks.

Regarding the cultural background, the ESS questions are used, which are presented in the second column of Table 2, which concern the way in which the cultural values of Schwartz (1992, 2006) are compiled. The percentage of those who answered “Very Much Like Me” was used in the sentences that appear in the second column. Based on Smith and Schwartz (1997) and Schwartz (2012), the following table is derived, which relates human values to cultural values based on specific questions that are realized in the waves of the ESS.

Table 3 presents the descriptive statistics for the ESS questions through which the Schwartz’s cultural values are captured.

Then, Principal Component Analyses (PCA) are realized in order to capture the cultural values dipoles “Conservatism/Embeddedness vs. Autonomy”, “Hierarchy vs. Egalitarianism”, and “Mastery vs. Harmony” based on the ESS questions that are related with each cultural value. Moreover, a PCA is performed for all ESS questions in order to capture a total measurement of cultural background.

Table 4 presents a correlation matrix between the ESS questions. The questions used in the analysis present high correlation between each other, something that allows for using PCA in order to capture the overall culture measure and the Schwartz’s cultural values.

Moreover, Table 5 presents the PCA for the “Conservatism/Embeddedness vs. Autonomy” cultural value.

The first two principal components are used. The first one has an eigenvalue of 4.42 and is related to 55.28% of total variance. It is positively configured by the following questions: “Important to think new ideas and be creative” and “Important to try new and different things in life”. In that way it is a component that is characterized by self-direction and stimulation.

The second one has an eigenvalue of 1.43 and is related to 17.89% of total variance. It is positively configured by the following questions: “Important to show abilities and be admired” and “Important to be successful and that people recognize achievements”. Moreover, it is configured negatively by “Important to have a good time” and “Important to understand different people”. In that way it is a component that is characterized by affective autonomy.

Table 6 presents the PCA for the “Hierarchy vs. Egalitarianism” cultural value.

The first two principal components are used. The first one has an eigenvalue of 3.07 and is related to 61.43% of total variance. It is positively configured by the following questions: “Important to do what is told and follow rules”, “Important to live in secure and safe surroundings”, “Important that government is strong and ensures safety” and “Important to behave properly”. In that way it is a component that is characterized by power and security and, thus, hierarchy.

The second one has an eigenvalue of 0.76 and is related to 15.40% of total variance. It is positively configured by the question “Important to be rich, have money and expensive things” and negatively by “Important to behave properly”. In that way it is a component that is characterized by power and non-conformity and, thus, hierarchy as well.

Table 7 presents the PCA for the “Mastery vs. Harmony” cultural value.

The first two principal components are used. The first one has an eigenvalue of 4.57 and is related to 65.31% of total variance. It is positively shaped by “Important that people are treated equally and have equal opportunities”, “Important to help people and care for others well-being” and “Important to understand different people”. In that way it is characterized by benevolence and, thus, mastery.

The second one has an eigenvalue of 1.15 and is related to 16.49% of total variance. It is positively shaped by “Important to get respect from others” and “Important to follow traditions and customs”. In that way it is characterized by tradition and, thus, mastery as well.

Finally, Table 8 presents the PCA for overall culture. The first two principal components are used. The first one has an eigenvalue of 9.76 and is related to 51.39% of total variance. The second one has an eigenvalue of 3.02 and is related to 15.89% of total variance.

Table 9 presents the estimation of Equation (1). Each column represents a different estimation of Equation (1) since different depended variables are used. The first eight columns represent the results when uncertainty is used as independent variable, and columns 9 to 18 represent the results when uncertainty with a lag is used as independent variable.

Looking at regressions 1 to 8, no statistically significant effects of uncertainty on culture emerge. However, using a lag in uncertainty the results are completely different (regressions 9 to 16). All regressors are positive and statistically significant, at 1% level of statistical significance, except from the second principal component of the cultural value of hierarchy vs. egalitarianism (regression 10). This means that when uncertainty is higher this leads to higher levels of hierarchy (authority humbleness), self-direction (independent thought and action) and stimulation (excitement, novelty and challenge in life), affective autonomy (pursuit of actively positive activities: pleasure, exciting life) and mastery (ambition and hard work, daring, independence, drive for success), at least two years later.

The analysis provided by the present paper concludes that there is significant effect of uncertainty on cultural values in the Eurozone countries during the period from 2002 up to 2018. This means that under conditions characterized by a high level of uncertainty such as the global financial crisis of 2008 or the recent pandemic of COVID-19, the behaviors, the preferences and, in general, the cultural background of the societies is about to change, thus affecting the way decisions are made and economic development.

While cultural background is a slow-moving structure that usually is changed in an incremental way, when uncertainty shocks are present culture can change more suddenly. The empirical analysis provided by this paper revealed no effect of uncertainty within the first two years of presence of high uncertainty. However, after two years of an uncertainty shock all Schwartz’s cultural values as well the overall culture significantly changed.

In addition, the empirical analysis concludes that when uncertainty is high this leads to higher levels of hierarchy (authority, humbleness), self-direction (independent thought and action), stimulation (excitement, novelty and challenge in life), affective autonomy (pursuit of actively positive activities such as pleasure and an exciting life) and mastery (ambition and hard work, daring, independence, drive for success) which means their life’s harmony is disrupted, at least two years later.

In general, the cultural background has a long-term homocyclic effect in many Eurozone countries. In the economic prosperity phase, there are a number of “anti-growth” aspects of social values linked to a lack of openness. However, in times of recession, this social model itself is giving rise to lines of defense linked to inward-looking while, at the same time, opposing its change. Thus, during the crisis, in-group collectivism (family) helps to reduce the negative effects of the crisis. However, the fact that, in the very difficult phase of recession, cultural background works as a “life-saver” gives it the chance to survive, possibly even grow stronger in the development phase where it is now acting as an obstacle. This is known as a cultural anti-growth trap (Petrakis and Kostis, 2021).

These results may be critical for governments and policymakers that face increased uncertainty levels. The cultural background of the societies affects the effectiveness of economic policy, since a society firstly has to approve an economic policy in order to make it more effective (Kafka, 2020; Kafka et al., 2020). Thus, countries exhibiting systematically high levels of uncertainty are about to develop a cultural background that is going to hinder economic development, and vice versa.