Student Registration Number:
Term paper
- The Silent Revolution
A test of the Inglehart hypothesis
Hand-in date:
08.06.2009
Campus:
BI Oslo
Exam code and name:
GRA 5917 Public Opinion and Input Politics
Program:
Master of Science in Leadership Political economy
Term Paper in GRA 5917
08.06.2009
Content
CONTENT ........................................................................................................................................ I
LIST OF FIGURES ......................................................................................................................... I
SUMMARY .................................................................................................................................... II
SUMMARY .................................................................................................................................... II
INTRODUCTION........................................................................................................................... 1
RESEARCH TOPIC ....................................................................................................................... 2
CAUSALITY ................................................................................................................................... 2
ACADEMIC CONTRIBUTION.................................................................................................... 3
THEORY ........................................................................................................................................ 3
DATA ............................................................................................................................................... 5
INDEPENDENT VARIABLES ............................................................................................................. 5
DEPENDENT VARIABLES ................................................................................................................ 5
METHODS ...................................................................................................................................... 6
ANALYSIS ...................................................................................................................................... 7
CONCLUSIONS ........................................................................................................................... 13
BIBLIOGRAPHY ......................................................................................................................... 15
List of figures
Figure 1 Maslow’s hierarchy of needs..................................................................... 4
Figure 2 Scatter dot diagram, Postmaterialism and GDP ........................................ 7
Figure 3 Correlation matrix ..................................................................................... 8
Figure 4 Descriptive statistics.................................................................................. 9
Figure 5. Linear regression analysis. ..................................................................... 10
Figure 6. Binary logistic regression ....................................................................... 11
Figure 7 Fixed effects models................................................................................ 12
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Summary
Ronald Inglehart (1977) claims that postmaterialism in a society is a product of increased
economic security and security from external threats. His scarcity hypothesis, which is based on
Maslow’s hierarchy of needs, says that people will always put greatest value on those goods that
are short in supply. Once the basic physiological needs are covered, one will put greater value to
other goods not essential for survival. This will eventually lead to a desire to fulfil needs of a
non-material nature, like respect of others, morality, lack of prejudice and other values that can
be categorised as postmaterial. His second hypothesis is the socialisation hypothesis. Here
Inglehart focus on the environment in which people form their values. A person who grows up in
a stable wealthy society will have a different set of values than a person who grow up in war
struck and poor society.
While Inglehart in his work focus on level of economic development as an important explanation
for postmaterialism, he only uses current level of GDP as a measure of this feature. As Inglehart
himself says, values are formed in the early stages of life, which is why this article tries to
explain postmaterialism by using the level of economic development for each participant of the
World Values Survey at the time when they were 20 years old. Through some robust regression
techniques can this article conclude that GDP in early stages of life explain as much, if not more,
of the variation in postmaterialism as GDP at the time of the survey.
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Introduction
The World Values Survey (WVS) is extensive academic project measuring the state of moral,
religion, political preferences, trust and several other aspects of life in societies all over the
world. The surveys grew out of the European Values surveys in 1981, and have covered an ever
increasing number of countries. This is now an extensive dataset which now covers over 80
states, and many of these have taken place in more than one wave of the survey. The number of
variables included in the survey is around 3000 and the number of individual responses is around
260.000. This dataset gives social scientists almost unlimited possibilities for quantitative
research.
One researcher who has really taken advantage of the possibilities in these data is Ronald
Inglehart. Inglehart has published several articles and books based on the findings he has done in
the WVS. Among his findings is the shift towards so-called postmaterialistic values in wealthy
and stable societies. The concept of postmaterialism will be defined to greater detail later, but in
short it implies that people’s preferences shift on questions on what their country’s political aims
should be in the years to come. The shift occurs as socio-economic level of the society is getting
higher. The postmaterialist-theory suggests that people will to a decreasing degree focus on
security and economic as main priorities for their country. And people will to an increasing
degree prefer a focus on “issues such as individual freedom, self expression, and
participation”(Dalton 2002).
Inglehart (Inglehart 1977; Inglehart 1997; Inglehart and Abramson 1999) have done extensive
analysis on the phenomena of postmaterialism. He has investigated changes between regions,
changes over time, changes between generations, and much more. What this article will deal
with is the causes of postmaterialism. Inglehart explains, to a large extent, postmaterialistic
values with the level of economic development in the society. Inglehart’s analysis uses GDP per
capita as measure of economic development. That in itself in uncontroversial, but he uses the
level of GDP per capita in the year of the survey, and this is where this article will differ from a
pure replication of Inglehart’s analysis. In his analysis (Inglehart 1997:151) place the
investigated countries in a scatter diagram with level of GNP per capita on the x-axis and
postmaterialism on the y-axis. Postmaterialism is here measured by subtracting percentage of
materialists in a country from percentage of postmaterialists. This gives each country one value
for postmaterialism. My analysis will focus more on the individual level. I will investigate the
relationship between individual postmaterialism scores and level of economic development in
society for each individual at their formative age. This analysis is important because both
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Inglehart (1997) and others (2002) argue that values depend on the individuals situation in life at
an early stage. But Inglehart still use a non-satisfactory measurement for measuring one of his
most important variables.
More generally is postmaterialism argued to be a part of a wider “silent revolution” taking place
in the last couple of decades, called post modernism. This revolution has had great impact on
party systems, introducing environmental movements and parties. It has also led to a dramatic
increase of women in politics. Samuel Huntington (1991) even suggests that it has triggered a
“third wave” of democratization. These issues, green politics, equal opportunities, participation,
and minority rights have been called “new politics” (Dalton 2002:134), and the increased
importance of this dimension can be seen as a result of postmaterialism.
Research topic
This article aims to build on the admirable analysis of Ronald Inglehart but is going to introduce
a new explanatory variable. So instead of explaining the variance in postmaterialism by level of
economic development at time of survey, this analysis will use the level of economic
development at the time in life when people’s values are set. By using this method we will
hopefully be able to understand even more of the concept of how postmaterialist values are
established in a society.
Inglehart’s theory, that economic security causes postmaterialism, rests on two main
hypothesis(Dalton 2002). One scarcity hypothesis, very much related to Maslow’s pyramid of
needs. It states that people will value those things that are scarce and tend to take for granted
those things that are relatively abundant (Duch and Taylor 1993). The second hypothesis is what
Inglehart has called the socialisation hypothesis (Dalton 2002). In my analysis, this will be the
most important hypothesis because it suggests “...that values become crystallized early in life;
thus, the overall values of a society reflect the conditions decades or more earlier, when values
were being formed” (Dalton 2002). So, growing up in an affluent society will increase the
probability of holding postmaterialistic values as an adult. This hypothesis will by tested by
using historic data of GDP per capita across states of the world.
Causality
Most of the theory on postmaterialism agrees on the causal relationship in this analysis.
Increasing postmaterialism is caused by higher levels of economic development. It is likely that
there also will be other important variables that explain postmaterialism, like historic and
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cultural variables. This analysis will be careful to go beyond the work of Inglehart when it comes
to choice of variables.
Academic contribution
There is a large literature on postmaterialism and most of it is in some way or another connected
to Ronald Inglehart. His first book on the subject was published in 1977 and have over the last
three decades published numerous articles, chapters and books in which he expands on his
theories of “the silent revolution” (Inglehart 1977), and he makes use of better and more updated
data material for each publication.
The Norwegian political scientist Ottar Hellevik has himself done a lot of research on changing
values in society, specifically within the Norwegian context (Hellevik and Børretzen 1996). In
his book from 1996 he tests Inglehart’s and theories using a data set collected by Norwegian
statistics bureau MMI from 1985 – 1995. He argues that his findings from the Norwegian
context can not support Inglehart’s theories. In the period he investigates, a period of rapid
economic growth in Norway, he can not detect any substantial increase in the share of
postmaterialists Norway (Hellevik and Børretzen 1996:84). Except for the first two years of the
period, he only finds decline in share of postmaterialists in Norway. Another Norwegian who has
done research on this topic is Oddbjørn Knutsen (1979; Knutsen 1989). He started his academic
career by testing Inglehart’s theory with data from three small Norwegian industrial towns in his
dissertation from 1979. He has continued to work on related themes for the following decades.
Theory
As previously mentioned, Inglehart rests his postmaterialism theory on two main hypotheses.
The first one is what he calls the scarcity hypothesis. To a large extent is this in line with the
theories of psychologist Abraham Maslow. Maslow created a very famous hierarchy of needs
(figure 1), in which he argued that a humans most basic needs, the physiological needs had to be
covered before one could move on to cover the needs which were the next in the hierarchy. In
his hierarchy, one can see a clear resemblance with what Inglehart describes as materialistic
values at the lower steps, and more typical postmaterialistic values, like respect for others and
morality, at the higher steps of the pyramid. Inglehart describes the scarcity hypothesis like this:
“An individual’s priorities reflect the socioeconomic environment: one places the greatest
subjective value on those things that are relatively short in supply” (Inglehart 1997:32). So
according to this, persons values will reflect the socioeconomic situation in which the person
lives. If for example the water supply is short, then people will put high emphasis on the need for
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getting clean water every day. But if those basic needs are met, values reflecting these needs are
lowered in priority (Knutsen 1989:4).
Figure 1 Maslow’s hierarchy of needs
Inglehart’s early work was closely linked to the Maslovian hierarchy, but is less prominent in his
more recent work. The second of the main hypothesis are the socialization hypothesis. This
thesis suggests that personal values to a greater degree depend on the socialisation process and
assume that values and priorities to a large degree are set in the early years of life. According to
Knutsen (1989:4) this will suggest a substantial time lag between socio-economic development
and change in values in the population. This is somewhat contradictive to the scarcity hypothesis
which does not mention any time lag. Inglehart explains that “The relationship between
socioeconomic environment and value priorities is not one of immediate adjustment: a
substantial time lag is involved because, to a large extent, one’s basic values reflect the
conditions that prevailed during one’s pre-adult years.” (1997:33)
Based on these two hypotheses we can form some clear predictions on where and when we will
be able to observe a society with large share of postmaterialists. I will expect postmaterialist
values to be most widespread in richer societies than in poor societies, and even more in the
richest and most secure strata of a society than in the less educated and poorer strata. I can also
expect there to be significant differences between the old and young population in societies
which have experienced long term growth in the economy. Hence will the intergenerational
differences be smaller in countries with low or no growth in economy and security.
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Data
This analysis will use data from two main sources, the World Values Survey(2006), and Angus
Maddison’s(2009) data on GDP per capita across countries from 1900 – 2006. As I aim to
investigate the effect of level of economic development on personal values, I find it very useful
to make use of the World Values Survey. This dataset contains, in addition to responses to wide
range of questions on different subjects, personal information about socio-economic status, sex,
number of children, geographic information age and a lot more. These provide the researcher
with endless possibilities for analyzing change in values over time, between countries, between
different socio-economical groups or between men and women.
Independent variables
The British economist Angus Maddison has compiled an extensive dataset which contains data
on the level of GDP in the countries of the world from year 1 to 2006. This dataset will provide
the data for my two most important independent variables. That is GDP per capita in year of
survey and GDP per capita in formative years. The first one is the level of economic
development, in GDP per capita, in the country where the respondent live measured at the year
the survey took place. The second variable is the level of economic development in the same
country at the year in history when the respondent was twenty years old. So in the data for my
analysis every individual in the WVS have values for GDP in their country at two different
points in their life. Hopefully will this article be able to conclude on which of the two is the
better predictor of postmaterialistic values. Dalton(2002) tries to test Inglehart’s hypothesis by
aggregating the postmaterialist results for each country in 1990 and comparing them with level
of GDP in 1965. He explains that “this is roughly when values were being formed for many of
the adults surveyed in 1990”(Dalton 2002:95). This analysis will try to replicate that method,
with updated data, for so to introduce the more specific variable for GDP in formative year.
Other important control variables will also be introduced in the analysis. This is done to
investigate which other factors can increase the probability of an individual within a society at a
given time in history will possess postmaterialistic values. Control variables will be sex, income,
and age. Some will be used in several models, and some in fewer of my models.
Dependent variables
The dependent variables of this analysis are provided in the WVS. The WVS-data includes two
variables measuring postmaterialism. They are constructed in a similar way, but the 12-item
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index is somewhat more comprehensive and robust than the 4-item index. The values of these
variables are based on the answers the respondents give to questions on what they think should
be preferred goals for their country in the next ten year period. Each question has four alternative
answers, out of which the respondent must name two preferences. Out of the four alternatives,
two are typical material values and two are typical postmaterial values. In the 4-item index,
respondents are given one such question battery with a total of 4 answer alternatives, and in the
12-item index, the respondents are given 3 question batteries with a total of 12 alternatives
answers. Based on the responses in these questions the respondents are given a score from zero
to five in the 12-item index and from one to three in the 4-item index.1
Dalton (2002) suggests that the 4-item index may be to narrow to tap a broad dimension of
human values. It may also be sensitive to short term inflation rates, as one of the items it deals
with is “fight rising prices”. Its advantage is that it has been used in European value surveys for
several decades, so it makes it easy to compare changes in values over time. In the binary
regression analysis I will make use of a dummy as a dependent variable in the binary regression.
I recode the 4- item postmaterialism index and recode it so that all those categorized as
postmaterialists get the score 1, and the rest 0. a similar variable is made with materialist being 1
and the rest 0. These two dummy variables are further used to create the PM variable in the
scatter diagram. I create that one by subtracting percentage materialists from postmaterialists in
each country/year.
Methods
This analysis will take advantage of different forms of tools to explore the effects of Economic
development on postmaterialism. Initially I will make use of an ordinary least squares (OLS)
regression to explore the effect of my new variable measuring level of economic development in
formative year and compare it to the effect of the regular economic development variable.
Further on I will make use of more sophisticated regression techniques, such as fixed-effect
models, to find out if the findings I make in the first round are robust, and a binary logistic
regression model to calculate the probability that a person will be in the postmaterialist category
given a set of fixed variables.
1
The question battery for the 4-item index looks like this “There is a lot of discussion about what the aims of this country should
be for the next ten years. On this card are listed some of the goals which different people would prefer. Would you please say
which one of these you, yourself, consider most important? What is your second choice? And what is your third choice?
1Maintaining law and order in the nation? 2. Giving the people more to say in important government decisions? 3. Fighting
rising prices? 4. Protecting freedom of speech?”
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Analysis
In this section of the article will I present and discuss the statistical findings I have done when
investigating the data material. First I will try to replicate some of Ingleharts main findings. It
seems like a very difficult task to create a prefect replication, because of the availability of data,
but I have strived to do an analysis as similar as possible. I will go on to discuss some
preliminary regression results that will guide the way for more robust and sophisticated
regression analysis.
Figure 2 Scatter dot diagram, Postmaterialism and GDP
”pm” is a measure of the 4-item postmaterialism index. It is constructed by subtracting percentage of materialist
from percentage of postmaterialists. Gdp_pc_form_year_mean is a measure of economic development. In this case it
is an aggregated number for each country year of GDP for year of the WVS. This is a close replication of the
analysis by Inglehart (1997:151)
Inglehart use aggregated data for countries for many of his analyses. In the above figure I have
tried to replicate one of his models. Inglehart use one observation for each country, while I use
several observations. Ingleharts naturally use only one observation of GDP for each country, and
I have used one observation for each country-year. Consequently, I have a higher number of
observations in my scatter diagram, but the trend is very much the same as in Ingleharts diagram.
The relationship between postmaterialism and economic development is a clear and quite linear.
An important assessment to consider is whether this linear relationship is due to changes over
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time within each country, or due to changes between countries. As I will show in a later,
descriptive analysis, there is no clear development towards more postmaterialism in society in
general. In the period investigated, from the early 1980s to the mid 2000s, the level of
postmaterialism in the investigated countries first declined, before an increase in the last decade.
It is then a fair assessment to suggest that all the linear relationship in the diagram above is
mostly due to differences between countries, because all countries studied have had an increase
in GDP in the period studied, and, as I show in figure 4, the share of postmaterialists have not
increased significantly. These considerations may be somewhat conflicting with the theories of
Inglehart, but in the fixed effects regression analysis’ (figure 7) I will control for the effects of
both time and countries, hence, I can conclude with greater confidence on this matter.
Figure 3 Correlation matrix
In a regression analysis it is important to check for multicollinearity. That implies a linear
correlation between two or more of the explanatory variables. Large multicollinearities weaken
the explanatory power of the model because the variables explain the same variation of the
dependent variable. In correlation matrix below are all the correlations between the variables I
will use in the regression analysis. We find high correlations between education level and both
income (0.33) and socio economic status (0,45), these are to be expected and hence, these
variables will not be used at the same time in the analysis. The two post materialist variables
correlate, and so do the two GDP variables, this is unproblematic as they are supposed to
measure almost the same. Other interesting findings from the correlation matrix include a strong
and significant correlation between the GDP-variables and the postmaterialist variables. GDP in
formative year seem to have the strongest correlation with GDP and it has a correlation
coefficient of 0,27 with the 12 item postmaterialist index. These findings are encouraging
because they support my initial theory.
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Figure 4 shows some descriptive statistics for the two dependent variables that will be used in
this article. It is divided into different “waves” in which the world values survey has taken place.
We find that there it is impossible to observe any increase in share of postmaterialists in the
surveys. In fact there even appears to be a slight decline in postmaterialists over the years.
N Valid
Wave 1, 1981 1989
Wave 2, 1990 1994
Wave 3, 1995 1998
Wave 4, 1999 2005
total
Postmaterialist 4 item index (range 1-3)
Mean Std dev Percent in PM category
22093
1,81
0,65
13,5
57635
1,87
0,65
15,1
71320
1,76
0,64
11,3
57596
245961
1,76
0,61
9,6
1,8
0,64
12,4
Postmaterialist 12 item index (range 0-5)
Mean Std dev Percent in PM category
N Valid
Wave 1, 1981 1989
2084
2,58
1,28
8,3
Wave 2, 1990 1994
54173
2,24
1,23
3,8
Wave 3, 1995 1998
64892
1,9
1,22
2,1
Wave 4, 1999 2005
54175
1,92
1,18
1,7
total
175324
2,02
1,22
2,6
Figure 4 Descriptive statistics
It must be noted that the 12 item index was only in use in a few countries in the first wave.
Therefore will it be difficult to conclude that these findings are valid for the entire population.
As previously mentioned, the findings done in this figure 4 hints to an assumption that it might
be the variation between countries, rather than variation over time that provides the development
we find in the scatter diagram in figure 2.
In the following regression analysis will the relationship between postmaterialism and economic
development be investigated more closely, and I will introduce the variable that separates my
research from Ingleharts’. That is the variable measuring the level of economic development for
each individual in the WVS in their country at the time when they were 20 years old. This will
let me know whether we can detect a more accurate explanation of postmaterial values.
The main findings I do in the preliminary analysis (Figure 5) is a confirmation that there is a
positive relationship between level of economic development in a society and postmaterialistic
values. Both GDP-variables have a positive effect on the level of postmaterialism. In three out of
four regression models where both variables are entered, I find that the effect of GDP in
formative years is relatively a lot stronger than the original GDP-variable. This supports
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Ingleharts socialization hypothesis, which states that values are crystallized early in life, and the
conditions in a society at that point in life contributes to form people’s values. Further, I find that
also the level of personal income, this shows that the scarcity hypothesis can applied not only to
societies, but also to individuals. This is very much in line with the theories of Maslow and his
hierarchy of needs. People will need to get their basic physiological and safety needs covered
before focusing on values represented by the postmaterialism index. However, I also observe that
the R² for all of these models are relatively small (all models have R² below 0.1). This indicates
that there is a great deal of variation in the postmaterialism-variables that cannot be explained by
the explanatory variables included in the regression models.
Model 1
12 Item
Model 2
4-item
Model 3
12 Item
Model 4
12 Item
Model 5
12 Item
1.692*
(.005)
1.610*
(.003)
1.590*
(.008)
1.0901*
(.019)
1.666*
.016*
(.001)
.008*
(.000)
.016*
(.001)
.034*
(.001)
--
GDP formative1000 $ .046*
(.001)
.024*
(.000)
.044*
(.001)
.019*
(.002)
.062*
(.001)
Sex
---
---
---
-.018*
(.007)
-.013
(.007)
Age
---
---
---
-.007*
.000
.000*
(.000)
Scale of income
---
---
.026*
(.001)
.024*
(.001)
.027*
(.001)
.076
.081
.073
Dependent variable:
Model Variables:
Constant
GDP
year1000$
survey
R²:
.075
.069
Figure 5. Linear regression analysis.
Std. errors. in parenthesis, *= significant at 0.05 –level
I will now investigate the findings we have done in the regression analysis a little bit closer by
making use of some more advanced analysis techniques. I will firstly make use of a binary
logistic regression model in which the dependent variable is recoded as a dummy variable, and
the independent variables will predict the probability that the value of the dependent,
postmaterialism-variable will be 1, the other variables hold constant. I will secondly make use of
some fixed effects models, to check how robust my findings are. By holding the effects of some
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of the explanatory variables constant, we only take into account those effects that are
independent of the other variables. These two methods will reveal any flaws in the analysis
performed so far. And I can with greater confidence conclude on whether my results
significantly differ from Ronald Ingleharts findings.
Model 1
PM
dummy
Model 2
PM
dummy
Model 3
PM
dummy
Model 4
Mat
dummy
Model 5
Mat
dummy
-2.264
(.104)
<.033>
-1.667
(.189)
<.028>
-2.916
(.054)
<.055>
-.099
(.905)
<.038>
-.506
(.603)
<.024>
.093
(1.097)
<.001>
---
.023
(1.024)
<.004>
-.041
(.960)
<.004>
-.118
(.889)
<.001>
GDP survey year 1000$
----
.079
(1.082)
<.001>
.050
(1.052)
<.003>
-.059
(.943)
<.002>
---
Sex
-.164
(.849)
<.014>
-.195
(.823)
<.001>
-.093
(.911)
<.019>
.142
(1.153)
<.014>
.212
(1.237)
<.011>
Age
.000
(1.000)
<.000>
-.020
(.980)
<.000>
-.006
(.995)
<.001>
.005
(1.006)
<.001>
.000
(1.000)
<.000>
Scales of income
---
---
.013
(1.013)
<.004>
-.018
(.982)
<.003>
---
Education level
----
---
.135
(1.145)
<.055>
.080
-.097
(.907)
<.003>
.104
---
Dependent variable:
Model Variables:
Constant:
GDP formative year
1000$
Nagelkerke R²:
.057
.072
.079
Figure 6. Binary logistic regression
Exp (B) in parenthesis, and Standard errors in brackets The dependent variable PM dummy is
constructed by assigning the score 1 to every individual with the high score 3 in the 4 item
postmaterialism index, all other individuals are assigned 0. The dependent variable mat dummy
assigns 1 to all individuals who score the low score 1 on the 4 item postmaterialism index and 0 to
all other individuals.
The interpretations of these results are a little bit different than in the linear regression analysis.
The numbers in parenthesis are not standard deviation here, but expected B. This means that they
indicate the increase or decrease in odds that a person will be in the category 1 of the dependent
variable given an increase in 1 unit of the independent variable. An exp (B) is larger than 1,
indicates an increase in the odds, while a value lower than 1 indicates a decrease in the odds that
the value of the dependent variable will be 1, the other variables hold constant. In model 1 in the
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figure above “GDP in formative year “have an Exp (B) of 1.097. Hence, we can conclude that
the odds of a person being a postmaterialist increases by 9,7 % for a 1000$ increase in GDP in
his or her formative year, if all other variables are held constant. In this analysis I find some of
the same main effects that was observed in the linear regression analysis. An increase in any of
the GDP-variables will increase the probability of being a postmaterialist, and decrease the
probability of being a materialist. The two variables are approximately equally strong. I can se in
model 1 and 2 that GDP in formative year have a somewhat stronger effect than GDP in survey
year when they are used in identical models. However, when they are used together in the same
model (see model 3 and 4), we find the opposite result, that GDP in survey year seem to provide
the strongest effect on postmaterialism. These contradictory results make it difficult to conclude
on whether the GDP- variable that I introduced has any significant explanatory power. The rest
of the explanatory variables also provide results that are less than surprising, considering the
results we found in the preliminary regression analysis.
Model 1
Model 2
Model 3
Model 4
Model 5
12- Item
4-item
4-Item
12-Item
12-Item
1,7937*
(0,0275
1,8808*
(0,0207)
2,0092*
(0,0288)
2,1422*
(0,404)
1,9021*
(0,0577
0,0092*
(0,0008)
0,0266*
(0,0010)
0,0005
(0,0022)
0,0077
(0,0043)
0,086*
(0,0064
GDP formative1000 $
0,0482*
(0,0011)
0,0044*
(0,0007)
0,0044*
(0,0007)
0,0114*
(0,0016)
0,0151*
(0,0017)
Sex
---
-0,0681*
(0,0029)
-0,0677*
(0,0029)
-0,0353*
(0,0064)
-0,0346*
(0,0064
Age
---
-0,0048*
(-0,0002)
-0,0048*
(0,0001)
-0,0097*
(-0,0003)
-0,0090*
(0,0003)
Country dummies
Year dummies
No
Yes
Yes
No
Yes
Yes
Yes
No
Yes
Yes
Dependent variable:
Model Variables:
Intercept
GDP
year1000$
survey
Figure 7 Fixed effects models
Std. errors in parenthesis, * = significant at .005 level
According to model 2, we find that he odds of being a postmaterialist is about 18% lower for
females than for males, and the odds decreases with about two percent for every year of age of
the respondent. I can hereby confirm that both education level and income level increase the
odds of being in the postmaterialist category.
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After completing the binary logistic regression I will move on to the fixed effects model where I
will put my findings through a tough test to find out whether my results are robust and credible.
When adding dummy variables for both years and countries we control for any differences that
occur between countries or any change over time, which means that only the variation within
countries at the different points in time is accounted for. This method is one of the strictest tests
which you can apply to regression analyses.
What I find when we introduce country and year dummies in the fixed effects models (figure 7)
is that in general most effects are weaker than in the linear regression analysis. This is because I
remove the unwanted variation of the explanatory variables. The directions of the effects are still
the same as in the previous analyses, with positive effects of Both GDP variables and negative
effects of sex and age. This confirms that postmaterialism is a feature more often prominent for
younger people and males. The effect of the two GDP-variables varies from model to model and
it seems difficult to give a conclusive interpretation of them. It is worth to note that the “GDP in
formative years” –variable is significant at the 5% level in all five models, while the “GDP in
survey year”-variable fails to pass the significance test I two of the five models. In my most
robust test, when I include dummy variables for every country and for every year in the period
(model 4), I find that GDP in formative years have somewhat stronger impact on postmaterialism
than GDP in survey year, and the impact of the first GDP variable is also significant, while the
impact of the latter is not.
Conclusions
Ronald Ingleharts theories have been put to the test in this article. My aim was to elaborate on
Ingleharts analyses by introducing a new explanatory variable measuring the level of economic
development for each person in the world value survey in their country at the time of their when
their values were being formed. Inglehart discusses this effect in his books, but never puts it to
the test in the way I have done in this article. I have made several interesting findings in this
article and will try to summarize some of them here.
My analyses shows that the apparent linear relationship between economic development and
level of postmaterialism (figure 2), can for a great part be attributed to variation between
countries rather than developments over time. This is a plausible inference because the scatter
diagram shows that there is a positive relationship between economic development and
postmaterialism, but still we observe a relative decline of postmaterialist over the period
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investigated (figure 4). The correlation matrix in figure 3 confirms that it is a positive
relationship between economic development and postmaterialism, and it also shows that the
impact of the GDP-variable variable that I added seems to have a stronger correlation with
postmaterialism than the original GDP-variable. In the linear regression analysis (figure5) I find
this trend once again. When using both GDP-variables in the same regression, it appears that the
effect of GDP in formative years is stronger than GDP in the year of the survey. This is very
much in line with the theory that personal values will be influenced more by level of economic
development at the time when the person grows up than the current level of economic
development.
The interpretations are a bit more difficult in the more complicated regression models. When
calculating the odds for being a post materialist or a materialist in the binary regression analysis
both the two GDP- variables have the expected direction of influence, but it is difficult to
conclude on which of them that has the strongest effect. However, I can conclude that men and
young people have higher probabilities of being postmaterialists than women and older people.
In the fixed effects model, I put my data to the toughest test available. By holding the variation
between countries and over time constant, I only check for the variation within a country at any
given year. In this test I once again find that both GDP- variables have a positive impact on
postmaterialism. These results are significant and so robust that I conclude that level of GDP
both in the formative years and in the year of survey definitely have an impact on
postmaterialism. It is, however, not possible to determine which of the two that has the greatest
explanatory power.
Even if my findings are both robust and significant, the entire models seem to lack some
explanatory power, with very low R² and coefficients. This means that there is yet a great deal of
variation in postmaterialism to be explained. In order to sufficiently explain this phenomenon,
the analyses should include more variables on cultural and historical data. Such data on various
historical and cultural features of states and regions combined with individual data on political
preferences and type of area of residence (urban vs. rural) could possibly improve the analysis.
Another further analysis which could be interesting with regards to postmaterialism would be to
see to what degree level of postmaterialism in a country influences the level of females with
parliament or introduction of environmental standards (emission levels and compliance of
international environmental agreements). Both gender equality and environmental responsibility
can be interpreted as postmaterialistic values, and hence we would expect a positive relationship
in these cases.
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In the beginning of this article (page 4) I made some predictions on what results I would find the
analyses. It turns out that most of my predictions were right. I predicted postmaterialism to be
more widespread in richer societies than poorer societies, and even more among the richer strata
of the population. As I have already noted, GDP definitely have an impact on postmaterialism,
and so does income. So we can conclude that both these predictions were correct. Finally I
predicted a higher level of postmaterialism among the young population than the old population.
As I have noted before, age is negatively related to postmaterialism, so the probability of being a
postmaterialist decreases the older a person is.
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