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PYGMALION EFFECTS ON FOLLOWERS’
FOLLOWERS
Søren C. Winter1
Mogens Jin Pedersen1, 2
Vibeke Lehmann Nielsen2
Simon Calmar Andersen2
1
SFI – The Danish National Centre for Social Research
2
Aarhus University
Corresponding Author: Søren C. Winter [email protected]
January 2016
Paper prepared for presentation at the Annual Meeting of the Southern Political Science Association
at San Juan, Puerto Rico, 7 - 9 January 2016.
Acknowledgements
We would like to thank Emil Rosenlund Andersen for assistance with statistical analyses and Ida
Gran Andersen for first analyzing the role of teacher expectations. We are grateful to the teachers
who participated in our survey. An earlier version of this paper was presented at the 11th Public
Management Research Conference in Madison, Wisconsin, 20-22 June 2013. The research was
supported by grants from Innovation Fund Denmark (Grant no. 0603-00281B), SFI – The Danish
National Centre for Social Research and Aarhus University for a project on “School Management,
Teaching, and Student Performance” directed by Søren C. Winter
PYGMALION EFFECTS ON FOLLOWERS’ FOLLOWERS
ABSTRACT
Since Rosenthal’s pioneering studies of Pygmalion effects showing that teachers’ high expectation
increase the achievement of their students, numerous experimental studies have showed that also
managers’ expectations for followers increase followers’ performance and efforts. In this study we
demonstrate that school principals’ expectations even affect followers’ followers, i.e. in increasing
students’ achievement. As expected by goal setting theory this effect is strongest when the
expectations are most challenging — in this case for socioeconomic disadvantaged students. We do
this in a naturalistic setting using 1,130 teachers’ assessment of 440 school leaders’ expectations,
archival data on test scores of 23,195 students, and detailed control for socioeconomic
characteristics of parents and schools. We show that the associations between leader expectations
and student performance are significant even when controlling for schools’ past performance and
teachers’ own expectations.
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INTRODUCTION
Pygmalion effects are a kind of self-fulfilling prophesy in which leaders’ expectations regarding
their followers increase the effort and performance of followers. In their seminal work Rosenthal
and Jacobson (1968) showed that by experimentally giving teachers high expectations student
achievement was increased. Later Eden (1984, 64) asked: `If raising teacher expectations enhances
pupil performance, wouldn't raising manager expectations boost subordinate productivity?' A
considerable number of studies have demonstrated this effect of manager expectations on
subordinates. Meta-analyses of Pygmalion leadership effects show substantial and statistically
significant effect sizes (McNatt 2000; Kierein and Gold 2000). In addition, more recent metaanalyses find that Pygmalion based leadership has the highest effect of three broad groups of
leadership theories (Avolio et al. 2009) and that manager expectations are among the variables
having most impact on leader-member exchange (Dulebohn et al. 2012). We contribute to this
research by studying whether leader expectation effects extend beyond their immediate followers
and affect the performance of the followers’ followers. We do so by going back to the setting of the
Rosenthal studies and examine how school leaders’ expectations affect the performance of their
teachers’ students.
We also address some of the limitations that have been identified in existing research
on Pygmalion leadership effects. Especially, there has been a call for work that does not involve
deception of manager expectations. Also studies of established leader-follower relationships have
been lacking (e.g., Eden et al., 2000, Kierein and Gold, 2000, and McNatt, 2000). Most Pygmalion
studies involve experimental manipulation of leaders’ expectations. The strength of this method in
terms of identifying causal effects is unquestionable. However, in natural settings where managers’
expectations regarding their subordinates evolve over time probably partly reflecting past
performance, expectations may be less volatile and expectation effects therefore smaller (for a
similar argument pertaining to teacher expectations see Jussim and Harber 2005). More generally,
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since many studies were conducted by a small set of researchers in military settings “a greater
variety of researchers, methods, settings, and so forth, would help demonstrate greater
generalizability” (McNatt 2000, 320).
In line with both Pygmalion theory (Bezuijen et al. 2009) and goal-setting theory
(Locke and Latham 1990, 2002, 2006) there are indications that setting challenging goals is an
important mediator for Pygmalion effects. We extend this line of research by studying the effect of
high leader expectations when they are most difficult – namely for socioeconomically
disadvantaged students that are known to have lower educational achievements, which would imply
lower expectations. We find that high school leader expectations are especially beneficial to this
group of followers’ followers.
THEORETICAL EXPECTATIONS
Leader expectations effects form a key element of several leadership theories, including the
theoretical perspectives on charismatic leadership, transformational leadership, goal-setting, and
more exclusively in Pygmalion leadership. According to charismatic leadership theorizing,
charismatic leaders advocate an appealing vision with optimism and confidence and make
emotional appeals to values. Followers tend to personally identify with the leader and imitate his
behaviors (Conger and Kanungo 1987, Shamir et al. 1993). Transformational leadership theory
shares some elements with charismatic leadership theory including the leader’s role in forming a
vision, motivating subordinates and setting high expectations. The theory suggests that leaders can
increase organizational performance by influencing values and aspirations, inducing a purpose
transcending short-term goals, activating higher-order needs, and motivating people to move
beyond their own self-interests (Avolio and Yammarino 2002, Bass 1985, 1990, Judge and Piccolo
2004, Yukl 2013).
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Basically, transformational leadership is claimed to work by engaging peoples’ selfconcept by psychological mechanisms of personal identification, social identification, and value
internalization. Leaders’ expression of high performance expectations is a key behavior whereby
transformational leaders may engage peoples’ self-concept as such expectations contribute to
enhance self-esteem, self-worth, and self-efficacy (Shamir et al. 1993). Closely related to
transformational leadership theory, social cognitive theory (Bandura 1988, 1997) suggests that
people may internalize a leader’s task performance expectations, i.e., integrate them into their own
value hierarchies.
Similarly, goal-setting research emphasizes the importance of goal content,
particularly goal specificity and goal difficulty (Kanfer 1990, Locke and Latham 1990, 2006).
Numerous studies show that specific and difficult goals may produce higher performance than easy
or general goals: As long as the individual accepts the goal, has the ability to attain it, and does not
have conflicting goals, there is a positive relationship between goal difficulty and task performance
(Locke and Latham 2006). Goal-setting theory thus highlights the importance of providing
individuals with a clear understanding of what is expected of them. Formulating performance
expectancies is of vital importance because it facilitates the individual in focusing her efforts in a
specified direction.
Pygmalion Effects Studies
In 1968 Rosenthal and Jacobson published their seminal work, Pygmalion in the Classroom:
Teacher Expectations and Student Intellectual Development. In the experimental study, the authors
administered an intelligence test to all children in Jacobson’s elementary school. However, they did
not tell teachers it was an intelligence test, but explained it was a test for identifying children likely
to “bloom” by showing a sudden and dramatic intellectual growth over the upcoming academic
year. They then informed each of the teachers which students had been identified as “late
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bloomers.” These students had in fact been randomly selected. One and two years later they
administered the same intelligence test again. The only initial systematic difference between the
controls and the “late bloomers” was in the teacher’s mind. Nevertheless, the designated “late
bloomers showed IQ gains over the controls. The teachers’ false expectations had become true
through a self-fulfilling prophecy. The effect was named “Pygmalion effect” after Shaw’s play,
“Pygmalion,” which later gave inspiration to “My Fair Lady.” The teachers had subconsciously
given the false “late bloomers” more attention by creating a friendlier and warmer climate, e.g.
more smiling and by giving them more challenging assignments (White and Locke 2000).
Pygmalion experimental research was extended to organizational settings focusing on
manager-subordinate relationships first by King (1971, 1974) in industrial plants, and later by Eden
in Israeli Defence Force training-courses (e.g. Eden 1992). Both authors found support for the
Pygmalion leadership theory that inducing managers to have higher expectations for certain
subordinates had self-fulfilling impacts on the performance of these subordinates.
Some of the mediating variables could be identified from higher ratings of the instructors by
the high-expectancy trainees in terms of the instructors’ efforts (1) to coach subordinates in
effective work habits, (2) to stimulate enthusiasm for meeting a goal or achieving excellent
performance, (3) to enhance others’ feelings of importance and self-worth, and (4) to encourage
members to form relationships and work together as a team. Notably, the instructors were unaware
of having treated the trainees differently (White and Locke 2000: 392). We note that some of these
mediating variables—particularly stimulating enthusiasm and enhancing subordinates’ self-worth
and self-efficacy—in combination with high leader expectations or goals form key elements of the
above theories of charismatic and transformational leadership.
However, later research by Eden and his colleagues (Eden et al. 2000) also demonstrated
some limitations of the experimental Pygmalion approach. The induced manager expectations did
not have the expected effects on workgroups that had been established for some time or on female
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subordinates. However, in their meta-analysis Kierein and colleagues (2000) found the same impact
of leader expectations for male and female subordinates (see also Natanovich and Eden, 2008).
While the identified Pygmalion effects were based on deception—which is not a proper
management strategy due to its ethical problems—Eden and his colleagues instead experimentally
tested the role of training of managers in having higher expectations of their subordinates, however
with no observable effects on the performance of subordinates. While the effect of leader
expectations is well-documented and quite substantial, reviews of the research called for more
studies of naturally occurring expectations in established leader-follower relationships (White and
Locke 2000, McNatt 2000, Kierein and Gold 2000). More recently, studies have found Pygmalion
effects in natural settings. In a study of 151 workplace leader-follower dyads in California
Whiteley, Sy, and Johnson (2012) find that follower performance is higher when leader
expectations are high.
Previous Pygmalion and Pygmalion leadership research has shown that leaders’ or streetlevel bureaucrats´ (typically teachers’) expectations affect their immediate followers’ performance.
However, the value of Pygmalion leadership theory would be much greater if leaders’ expectations
affect not only the performance of their immediate followers but also the performance of more
distant followers at lower levels of the organization. We have found no such research regarding
Pygmalion leadership theory. When trying to understand how leaders may affect distant followers,
we can draw on multilevel leadership effect theory by Waldman and Yammarino (1999) and
Hannah et al. (2008). They claim that leaders can affect distant followers in two different ways. One
is called the “falling dominoes” or “cascading” effect. These concepts refer to the step-by-step
process when a leader’s leadership style is being reflected in a similar form at subsequent
organizational levels. The leader’s leadership style is thus reflected in the leadership style of the
immediate subordinate followers by some social learning process, including role-modeling, and that
particular leadership style is then in turn reflected in the leadership style or performance of her
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immediate followers at the next level (Bass et al. 1987, Waldman and Yammarino 1999, Avolio and
Hannah 2008). In this situation, a leader is influencing distant followers indirectly through a
multilevel hierarchical cascade of similar leadership styles.
However, leaders may also affect distant followers by bypassing one or more hierarchical
levels by influencing distant followers directly by skipping one or more of the hierarchical levels inbetween (Waldman and Yammarino 1999, Hannah et al. 2008).
Unfortunately, only very few studies offer some empirical evidence of cascading effects/
and/or by-pass effects. These studies are focusing on charismatic leadership (Bass et al. 1987),
transformational leadership (Dvir et al. 2002), and transactional leadership (Berson and Avolio
2004). Because of the very limited evidence of multilevel leadership effects, there has been a
general call for more research on such relationships (e.g. Hannah et al. 2008, Yukl 2013). We
would like to contribute by examining if the performance of distant followers is affected by
Pygmalion leadership.
Based on the substantial evidence on Pygmalion effects in street-level bureaucrat (teacher) –
target group (students) relations as well as in leader-subordinate relations, we expect that the effect
of leader expectations would extend beyond their immediate followers to the followers’ followers.
This may happen through several channels. First, cascading, indirect effects may occur when leader
expectations are raising followers’ expectations which in turn are raising the expectations or
performance of followers’ followers. Second, leader expectation may also have a direct impact on
distant followers’ performance by bypassing the immediate followers. Third, leader expectations
may have other kinds of indirect effects on performance by affecting other aspects of followers’
behavior than the particular leadership style of communicating expectations, such as followers’
work effort including less absence (King 1971)). We know from several studies of Pygmalion
leadership effects that high leader expectations increase followers’ effort (White and Locke 2000,
Whiteley, Sy and Johnson 2012, McNatt 2000). And general work motivation literature suggests
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that both how hard a person works and the direction that the person’s work efforts take have
important performance consequences. Work effort is a behavioral force, which is driving the
achievement of work-related goals and performance (Kanfer, Chen and Pritchard 2008; Latham
2007; Locke and Latham 2004; Pinder 1998; Porter, Bingley and Steers 2009). However, our
research focus here is not the separate direct and indirect effects but the combined effects of leader
expectations on the performance of followers’ followers. Accordingly, our first hypothesis is:
H1: Leaders’ higher expectations of performance increase the performance of followers’
followers.A special aspect of Pygmalion theory – and as we shall see later also of Goal Setting
Theory - is the role of difficult or ambitious goals in mediating or enhancing the impact of leader
expectations. Based on Pygmalion studies, Rosenthal (1973: 1) identified teaching more and
increasingly difficult material as one of the teacher behaviors that mediate the relationship between
teachers’ expectations and students’ achievement. In their later meta-analysis Harris and Rosenthal
(1985) found support for this supposition by finding positive relationships both between teachers’
or leaders’ expectations and presenting more and increasingly difficult material to the target group
and between that behavior and outcomes. Extending this theorizing to Pygmalion leadership,
Bezuijen et al (2009) in a recent study of 904 manager-subordinate dyads in six organizations find
indications that Pygmalion effects are mediated by leaders setting more specific and difficult goals.
Goal-Setting Theory
The role of difficult goals in achieving better outcomes is also an important and more elaborated
part of goal-setting theory. Locke’s (1968) pioneering work on goal-setting and motivation suggests
that employees are motivated by clear goals and appropriate feedback. Basically, to work toward a
goal is an essential source of motivation in reaching that goal—which, in turn, may improve
performance. Locke and Latham (1990) reinforced the appropriateness of setting specific and
difficult goals. Goal specificity may increase performance for two reasons: First, specific goals
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serve to focus attention, i.e., they let employees know what he or she is expected to do and
accomplish. Second, specific goals can focus effort, i.e., make it easier for employees to understand
the relationship between effort and performance and between performance and subsequent rewards
(Locke and Latham 1990; Wright 2004). The value of goal setting is widely recognized and has
recently been shown to affect performance in an educational setting (Favero, Meier and O’Toole
2014).
Goal difficulty is particularly important, as (a) people are often motivated by achievement,
and because (b) people value a given goal based on the significance of the anticipated
accomplishment. Inasmuch as goal accomplishment is realistic, the accomplishment of a
challenging goal may thus entail a psychological needs satisfaction that, in itself, may boost and
direct enthusiasm and work efforts toward goal accomplishment. Basically, goals set the primary
standard for self-satisfaction with performance (Locke and Latham 2002, 2006). Low or easy goals
may therefore be less motivating than high or challenging goals because they require a person to
attain less in order to be satisfied. For these reasons, we derive our second hypothesis:
H2: The positive influence of leader expectations on the performance of followers’ followers
is enhanced by the difficulty in meeting the expectations for selected target groups.
CONTEXT
The setting for our study is the management of public primary and lower secondary schools in
Denmark. These schools are governed by multi-purpose municipalities. Danish schools provide a
“tough” test of the performance impact of leaders setting goals or expectations. Professionals—and
not least teachers—probably tend to seek some level of autonomy in their work but this tendency
may be particularly strong in Denmark. First, Denmark has a national culture characterized by a
relatively small power distance (Hofstede 1980, 1983). Compared to other countries, Danes
generally have less respect for authority. Therefore, teachers in Denmark may have less respect for
principals than teachers in some of the Anglo-Saxon countries, where "instructional leadership" has
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proven effective (Robinson et al. 2008, 2009). By the same token, Danish students and their parents
may have less respect for their teachers and principals than would be the case in other countries.
Second, Danish school principals have less decision-making autonomy than their peers in
many other countries—due to a considerable degree of corporatism in policy formulation and
implementation. In the area of educational policy, the teachers’ unions are thus normally involved
in the formulation of most laws on schooling and very much so in the implementation of policy at
the local level. For long, school principals’ authority in allocating teacher’s working hours at the
school has been substantially reduced by collective agreements with the teacher unions.1 Principals’
authority is also limited by substantial influence from local branches of the teacher union or the
teacher shop steward at each school (Meier et al. 2015).
Thirdly—and likely as a natural extension of the small power distance and the corporatist
tradition—Danish schools have had a tradition of less "strong" school leaders. Principals were often
perceived as a primus inter pares, once also indicated by the term “first teacher” (head teacher).
Moreover, teachers traditionally have had a high degree of autonomy. Nowadays, however, school
principals can also find some support for their managerial role in the Public School Act, article 45,
according to which the school manager is responsible for the administrative and educational
management of the school.
Variation in school managers’ involvement in setting goals and expectations presupposes
that they (and their school) have some level of autonomy in decision-making. As previously
mentioned, public schools are governed by multi-purpose municipalities. Within a few general
constraints, the municipal council is free to decide the annual school budgets and is authorized to
impose taxes on the municipal inhabitants within certain overall limits, negotiated with the national
government. Local politicians can set strategic goals for the municipal schools, and some take
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As an exception from the rule, the existing collective agreements on teacher’s working hours was cancelled by
Parliament in 2013 after the Danish teachers’ unions refused to accept proposals of doing so from the central and locl
government employer organizations.
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initiatives in terms of regulating the teaching methods that are applied in the schools and personnel
matters.
The Danish national school legislation regulates the themes to be taught in each grade but
gives municipalities and their schools substantial autonomy with respect to objectives and choice of
pedagogical methods. In general, most school principals report having substantial autonomy in
managing their school (Pedersen et al. 2011). Students’ parents are represented in the school board
of each school but students as well as their parents also play important roles in coproducing
education in primary and lower secondary education. The school managements inform students and
parents in various meetings as well as through intranet communication.
DATA AND METHODS
Data
We use two data sources. The first source comprises a survey among Danish and Math teachers in
9th grade in public schools. Their responses to a teacher survey, which was administered in 2011,
form the basis for characterizing school managements. Specifically, a web-based questionnaire was
sent to 1,998 teachers who taught a ninth grade class in Danish or Math in a municipal lower
secondary school. A total of 1,027 teachers from 337 municipal schools responded (57 percent
response rate). The distribution of the schools of the responding teachers does not differ
significantly from the population of Danish schools in terms of student performance, socioeconomic student composition, and school size (analysis based on administrative register data).
Information on school leader practices for quantitative analyses can be provided through
either manager or teacher surveys. While our research project collected information from both
managers and teachers, this article uses teacher survey information. Leader surveys may be more
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susceptible to a social desirability bias (Jacobsen and Andersen 2015, Favero et al. 2015), and
teachers are more likely to be influenced by how they perceive the behavior of their leader rather
than by how the leader is presenting himself.2
Our second data source comprises archival data from administrative registers on the
population of Danish lower secondary students (provided by Statistics Denmark). We merge the
survey data from individual teachers with register data from their students. In this way, in our
analyses we have data on 13,568 students’ test scores at the final exams at the end of ninth grade in
2011 as well as rich demographic and socio-economic information on all students and their family.
Measures
Dependent variables
The main dependent variable in the analyses is student performance, measured by students’ test
scores in summer 2011. Students in lower secondary municipal schools are required to take a final
test at the end of 9th grade, which is a standardized academic subject test. All schools are required to
use the same examination tests, issued by the Ministry of Education. Grades are given on a 7-point
scale. Written examinations are graded by the students’ subject teacher and an external examiner
appointed by the Ministry of Education (Departmental order no. 351, 19 May 2005, section 24).
This procedure arguably makes the scores relatively valid and reliable. For each student, we use the
mean score in the written tests in the two subjects of Danish (understanding of reading, spelling,
and written presentation) and Mathematics (problem-solving and arithmetic). We use the written,
open-ended (not multiple choice) math exams, because they are graded relatively objectively. We
2
In fact, we also examined the performance impact of manager reported management expectations for performance.
The relationship is insignificant in similar fixed effect regression analyses at the municipal level. This manager reported
expectation variable was created as the mean score of two items in which respondents were asked to rate their degree of
agreement with either of two opposing statements A and B. The first set of statement was: A. “I and the other managers
expect that students at our school perform better in marks at the final exams than similar students at other schools.” “B.
I and the other managers have no expectations with regard to students’ performance in marks at this school compared to
similar students at other schools.” The second set of statements was: A. “The school management places very high
demands on teachers’ classroom teaching at our school.” B. “The school management hardly places any demands on
teachers’ classroom teaching at our school. It is their own responsibility.” Scores were reversed to indicate higher scores
for higher expectations.
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use the written exam results in both Danish and math to get a broader measure encompassing both
humanistic and scientific core competencies. Most school management research use test scores in
Math and the national language and literature for measuring student performance (Hattie 2009;
Robinson 2009). Our test score data set, comprising the mean of Danish and math test scores,
provides 13,568 students’ mean test scores in Danish and math that is our unit of analysis.
The 13,568 sample students are distributed around a mean score of 6.20 in Danish and 6.35
in mathematics (with a standard deviation of 2.58 in Danish and 3.24 in mathematics) on the Danish
7-point grading scale. The grading scale ranges from -3 to 12. The mean standard deviation for the
two subjects is 2.91. To obtain a higher degree of normal distribution, the total distribution of the
two sets of tests scores is standardized (mean = 0, standard deviation = 1).
Leaders’expectations
For measuring our key explanatory variable, school leaders’ expectations regaring students’
academic performance, we use two items from the teacher survey and form an index on teachers’
perceptions of the school leadership at their school. The first item is: "How would you describe the
management of the school on a scale from 1 (totally agree with A) to 5 (totally agree with B)?”
where (A) is “The school management expects students to do better in terms of test scores
compared to similar students at other schools” and (B) is “The school management has no
expectations about how students are doing in terms of test scores compared to similar students at
other schools." The second item is: "The school management has high expectations regarding
students' academic level" on a Likert scale from 1 ("Strongly agree") to 5 ("Strongly disagree").
Cronbach's alpha of items is .75. The index is generated using the sum of the two item scores. The
index score is subtracted by one to form a scale ranging from 1 to 9, with high scores indicating that
school management has high expectations for student performance.
Control variables and interaction terms
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To control for other variables potentially affecting both leader expectations and student
performance, we include administrative register data on many relevant background variables. First,
we include information about student gender, ethnicity, and age at the time of testing. Second, we
control for the following family background variables: living with both parents, number of siblings
and birth order, mother and father’s age at birth, mother and father’s length of education, mother
and father’s disposable income, and whether mother and father are currently employed. These
variables have a strong influence on student performance, explaining about 22 percent of the
variation (Andersen and Winter 2011).
In some of our analyses, we examine the conditioning effect of students’ individual socioeconomic background on the relationship between school leader or teacher expectations and student
performance. We do so by employing an interaction term in the regression models. The interaction
term is defined as the product of the individual student's socio-economic status and leader
expectations as these are recorded by each teacher. This approach has been used in previous studies
of the importance of social inheritance (Andersen 2008a; 2008b). We form an overall measure of
student socioeconomic status (SES) using the following four indicators:
- Mother’s length of education (years)
- Father’s length of education (years)
- Mother’s income (in 15 percentiles)
- Fathers’ income (in 15 percentiles)
SES is measured as the first extracted factor of a Principal-Component Analysis of the four
variables (eigenvalue = 2.01). The first factor explains 50 percent of the overall variation, and the
four variables show satisfactory factor loading scores. Cronbach’s alpha for the four items is 0.62.
To ensure comparability between analyses with and without the interaction terms, we use the SES-
15
variable in all analyses, instead of the individual variables comprising the SES-measure. We use the
SES-variable in addition to the other individual student and family background variables.
Several studies suggest that students’ performance is affected by peer group effects,
particularly class-mate peer effects (Rangvid 2008; Hanushek 2006; Somers, McEwan and Willms
2004). Moreover, research finds that school leader behaviors as well as teachers’ teaching are
affected by the social background of the students (Pedersen et al. 2011). Therefore, controlling for
the social background of the students in the class is important when examining the impact of leader
and teacher expectations on student performance. We include the following six variables to control
for student peer effects: Share of mothers and fathers in the lowest income quartile, share of
mothers and fathers in the lowest length of education quartile, share of students not living with both
parents, and share of descendants of parents with a non-Danish origin.
Several studies show that teachers’ teaching experience affects student performance
(Mikkelsen 2013; Clotfelter, Ladd and Vigdor 2007; Rivkin, Hanushek and Kain 2005). Also, and
although the international evidence on the influence of teacher gender is mixed, a recent Danish
study finds a relationship between teacher gender and student performance as well as between
teacher gender and teaching behaviors (Mikkelsen 2013; Andersen 2013b). Therefore, we include
controls for teacher experience and gender. In addition, we include measures on the number of
students in the class, and school size (the number of students at the school) as these factors may
affect teaching as well as student performance.
To control for potential reverse causality bias, namely that leaders express high expectations
because the students at the school in general are talented, we control for student past-performance—
measured as the average of nine grade students’ test scores in Math and Danish in the school year
2008-2009. We choose the school year 2008-2009, instead of, say, 2009-2010, since actual leader
alignment of expectations to past performance may require some time.
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Finally, in order to make sure that principals’ expectations are not completely driven by
teachers’ expectations , we control for teacher expectations. For measuring teacher expectations to
student performance, we use the teacher response to the following survey item: ”The following
questions concern your teaching in your subject [Danish/Math] in your ninth grade. How would you
describe your teaching in your subject [Danish/Math] in your ninth grade on a scale from 1 (fully
agree with A) to 5 (fully agree with B) where 3 is neutral?” A’s statement is: “I express high
expectations to my students’ academic performance” while B’ statement is: “I do not express high
expectations to my students’ academic performance”. We reverse the item responses to let higher
scores indicate higher expectations. Due to a skew distribution (few observations expressing low
expectations), the reversed values 1 and 2 have been merged to 1. Controlling for teachers’ selfreported expectations provides a stronger, more conservative test for two reasons. First, we thereby
account for the indirect cascading effect on performance that leaders may have through their
influence on teachers’ expectations. Second, because social desirability bias might make some
respondents overstate their optimism, controlling for teachers’ self-reported expectations in their
evaluation of leader expectations helps neutralize this risk of bias.
Descriptive statistics for all variables in the analysis are presented in Table 1.
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Table 1: Descriptive Statistics
Variables
Test score1
Leaders’ expectations to students’ performance
Obs
Mean
Std. Dev. Min
Max
13,568
.07
.98 -2.61
1.96
754
5.63
1.79
1
9
SES
13,568
3.98
1.00
.83
7.23
Male
13,568
.51
.50
0
1
Immigrant
13,568
.07
.26
0
1
Age at the time of the test
13,568
16.10
Not living in nuclear family
13,568
.18
.39
0
1
Only child
13,568
.07
.25
0
1
First born (ref.)
13,568
.36
.48
0
1
Second born
13,568
.17
.38
0
1
Youngest child
13,568
.39
.49
0
1
Mother’s age when child was born
13,568
28.42
6.58
0
46
Father’s age when child was born
13,568
30.35
8.64
0
67
Mother employed (ref.)
13,568
.86
.34
0
1
Mother unemployed
13,568
.07
.25
0
1
Mother in education
13,568
.00
.06
0
1
Mother outside workforce
Father employed (ref.)
Father unemployed
13,568
.04
.88
.19
.32
0
0
1
1
.06
.23
0
1
Father in education
13,568
.00
.01
0
1
Father outside workforce
13,568
.04
.20
0
1
Share of mothers in first quartile of education
13,568
.23
.13
0
.91
Share of fathers in first quartile of education
13,568
.20
.12
0
1
Share of mothers in first quartile of income
13,568
.25
.13
0
1
Share of fathers in first quartile of income
13,568
.23
.13
0
1
Peers’ proportion of non-Danes
13,568
.09
.13
0
1
Share of peers’ who are not living in nuclear family
13,568
.21
.12
0
.72
Class size
715
19.70
3.78
1
38
School size
336
507.92
163.11
140
1005
Teacher’s gender (male)
1027
.41
.49
0
1
Teacher’s teaching experience
1027
12.91
12.84
0
43
Student background:
13,568
13,568
.38 14.75
17.92
Peers:
Class, School, and teacher controls:
Past performance
331
6.23
.92
2.75
8.52
Teachers’ expectation to students’ performance
824
3.22
.81
1
4
1. The standardization of marks was performed for all tested students for all schools represented in the teacher survey
while the listed descriptive statistics is made only for those students who are part of the analyses of the paper.
18
Statistical Modeling
Our statistical model specifications must account for the hierarchical, multi-level character of our
data, with students in classes in schools in municipalities. Our models are fixed effects models at
the municipal level3. As leader expectations are measured by teacher perceptions of leader
expectations, a school fixed effects approach would not be appropriate for examining the
relationship between school leader expectations and student performance. Because teachers in the
same school are observing the same leader, the teachers’ perceptions of leader expectations are
likely to be characterized by limited empirical variation. Therefore, we use municipal fixed effects
models for these analyses. Cluster robust standard errors are used to account for spatial
autocorrelation in the hierarchical data set. In addition to modeling interaction effect of students’
SES on the relationship between expectations and performance, we use marginal effect analyses for
quintiles of the SES-distribution.
FINDINGS
Table 2 shows the findings in relation to hypothesis H1. The results in all three models indicate that
high leader expectations are positively associated with students’ test scores (even with control for
past organizational performance) thus supporting H1. Moreover, Model 3 rejects that the impact of
leader expectations to target group performance is fully mediated by teacher expectations as would
be the case if leaders’ expectations only affected student performance through cascading Pygmalion
leadership effects by the leaders’ expectations being reflected in teachers’ expectations. One
interpretation is that high leader expectations have a positive direct impact on students’ test scores
thus bypassing mediation through teacher expectations. However, we cannot exclude the possibility
that leader’s expectations are mediated by other kinds of teacher behavior than their expectations,
for example their effort. Hence, the finding supports H1: that leaders’ communication of higher task
3
In addition to the fixed effects models, as a kind of robustness check we conducted OLS modeling with robust
standard errors clustered at the municipal level. These studies are not shown based on the stronger method of municipal
fixed effects. The findings are similar to those presented.
19
performance expectations increases the performance of followers’ followers. Leaders signaling high
expectations may influence target groups as well indirectly though cascading leadership effects
reflected in teachers’ expectations and perhaps other teacher behaviors, as directly—here students
and their parents. In addition, the findings indicate that the effect of teacher expectations is larger
than the effect of leader expectations, even though teachers’ self-reported expectations are possibly
less valid than their evaluation of their leaders’ expectation due to a possible social desirability bias
when reporting their own expectations.
Moreover, in line with expectations from both Pygmalion and goal-setting research, we test
whether the relationship between leaders’ communication of higher task performance and the
performance of followers’ followers is moderated by the difficulty in meeting leaders’ performance
expectations (H2). Accordingly, we expect that the positive influence of leader expectations is
enhanced by task difficulty. Our indicator for task difficulty is students’ socio-economic
background, as students with low socio-economic background tend to perform poorer in school. In
other words, we expect to find a negative effect of the interaction term between students’ SES and
leader expectations.
Table 3 shows the results of the interaction analyses. In line with our expectations, the
impact of leader expectations on student performance appears to be moderated by student SES. The
coefficient of the interaction variable between leaders’ expectations and SES is negative and
significant. Thus, the positive impact of school leaders’ high expectations is greater among students
with a lower socio-economic status. This applies in models with as well as without control for
teacher expectations – and in models with as well as without control for past performance.
20
Table 2: Impact of leader expectations on student test scores. Unstandardized coefficients
with standard errors in parentheses
Variables
Leaders’ expectations
Past performance (2008-2009)
Municipal fixed
effects
Controlling model 1
for past performance
Controlling model 2 for
teacher expectations
Model 1
Model 2
Model 3
.016**
.014*
.010†
(-.005)
(-.006)
(-.006)
-
.064*
.061*
(.025)
(.024)
.055**
Teacher expectations
(-.013)
Student background:
SES
Male
Immigrant
Age at the time of the test
Not living in nuclear family
Only child
First born (ref.)
Second born
Youngest child
Mother’s age when child was born
Father’s age when child was born
Mother employed (ref.)
Mother unemployed
Mother in education
.307**
.304**
.303**
(-.014)
(-.014)
(-.014)
-.150**
-.151**
-.152**
(-.02)
(.020)
(.021)
-.137**
-.133**
-.136**
(-.036)
(.036)
(.036)
-.243**
-.243**
-.242**
(-.023)
(.023)
(.023)
-.056*
-.055*
-.059*
(-.024)
(.024)
(.024)
-.029
-.030
-.029
(-.035)
(.035)
(.034)
-
-
-
-.190**
-.189**
-.186**
(-.023)
(.022)
(.022)
-.231**
-.231**
-.229**
(-.019)
(.019)
(.019)
.013**
.013**
.013**
(-.002)
(.002)
(.002)
.005*
.005*
.005*
(-.002)
(.002)
(.002)
-
-
-
-0.056
-.058
-.061
(-.037)
(.037)
(.037)
.231*
.232*
.227*
(-.112)
(.110)
(.111)
Table will continue on next page
21
Table 2 (continued): Impact of leader expectations on student test scores. Unstandardized
coefficients with standard errors in parentheses
Model 1
Controlling
model 1 for past
performance
Model 2
Controlling model 2
for teacher
expectations
Model 3
.026
.022
.023
(-.049)
(.049)
(.050)
Municipal fixed
effects
Variables
Mother outside workforce
Father employed (ref.)
Father unemployed
Father in education
Father outside workforce
-
-
-
-0.04
-.042
-.038
(-0.04)
(.040)
(.039)
1.793**
1.767**
1.768**
(-.156)
(.142)
(.115)
-.162**
-.163**
-.161**
(-.05)
(.051)
(.051)
Peers:
Share of mothers in first quartile of education
Share of fathers in first quartile of education
Share of mothers in first quartile of income
Share of fathers in first quartile of income
Peers’ proportion of non-Danes
Share of peers’ who are not living in nuclear
family
-.212
-.196
-.159
(-.142)
(.147)
(.145)
-.214*
-.165
-.175†
(-.1)
(.101)
(.097)
.004
.020
.008
(-.118)
(.113)
(.110)
.062
.072
.110
(-.114)
(.114)
(.114)
.013
.101
.087
(-.138)
(.131)
(.132)
.044
.070
.025
(-.092)
(.093)
(.096)
0
-.000
-.001
(-.004)
(.004)
(.004)
.000**
.000
.000
Class, school and teacher controls:
Class size
School size
Teacher’s gender (Male)
Teacher’s teaching experience
Constant
Observations
Number of schools
Adj. R2
(.0)
(.000)
(.000)
-.009
-.008
-.001
(-.023)
(.023)
(.023)
.001
.001
.001
(-.001)
(.001)
(.001)
2.305**
1.930**
1.789**
(-.374)
(.416)
.422
13,568
330
13,568
330
13.549
324
.19
.19
.19
Cluster robust standard errors in parentheses
** p<.01, * p<.05, † p<.10
22
Table 3: Impact of leader expectations on student test scores conditioned by SES and
controlling for teacher expectations and past performance. Unstandardized coefficients with
standard errors in parentheses
Variables
Leaders’ expectations
Past performance (2008-2009
Teachers' expectations
Leaders' expectations*SES
Student background:
SES
Male
Immigrant
Age at the time of the test
Not living in nuclear family
Only child
First born (ref.)
Second born
Youngest child
Mother’s age when child was born
Father’s age when child was born
Mother employed (ref.)
Mother unemployed
Mother in education
Mother outside workforce
Father employed (ref.)
Father unemployed
Father in education
Father outside workforce
Peers:
Municipal fixed
effects
Model 1
.056***
(.020)
Controlling Model 1 for
teacher expectation & past
performance
-.010**
(.005)
Model 2
.051**
(-0.02)
.061**
(.024)
.055***
(.013)
-.010**
(.005)
.364***
(.031)
-.150***
(.021)
-.138***
(.036)
-.244***
(.023)
-.055**
(.024)
-.03
(.035)
-.189***
(.023)
-.231***
(.019)
.013***
(.002)
.005***
(.002)
-.055
(.037)
.232**
(.111)
.030
(.049)
-.040
(.040)
1.795***
(.158)
-.162***
(.050)
.361***
-.031
-.152***
(.021)
-.137***
(.036)
-.242***
(.023)
-.058**
(.024)
-.031
(.034)
-.185***
(.022)
-.229***
(.019)
.013***
(.002)
.005***
(.002)
-.060
(.037)
.229**
(.110)
.027
(.049)
-.038
(.039)
1.770***
(.117)
-.160***
(.051)
-
Table will continue on next page
23
Table 3 (continued): Impact of leader expectations on student test scores conditioned by SES
and controlling for teacher expectations and past performance. Unstandardized coefficients
with standard errors in parentheses
Variables
Share of mothers in first quartile of education
Share of fathers in first quartile of education
Share of mothers in first quartile of income
Share of fathers in first quartile of income
Peers’ proportion of non-Danes
Share of peers’ who are not living in nuclear family
Class, school and teacher controls:
Class size
School size
Teacher’s gender (Male)
Teacher’s teaching experience
Constant
Observations
Number of municipalities
Adj.R2
Cluster robust standard errors in parentheses
*** p<.01, ** p<.05, * p<.10
Municipal fixed
effects
Controlling Model 1 for
teacher expectation & past
performance
Model 1
-.207
(.141)
-.214**
(.099)
.008
(.118)
.061
(.115)
.011
(.138)
.046
(.093)
Model 2
-.154
(.144)
-.175*
(.097)
.012
(.109)
.109
(.115)
.084
(.133)
.027
(.097)
-.000
(.004)
.000**
(.000)
-.008
(.023)
.001
(.001)
2.078***
(.401)
13,568
80
.19
-.001
(.004)
.000
(.000)
.000
(.022)
.001
(.001)
1.560***
(.441)
13,549
80
.19
Hypothesis 2 is thus supported. In line with goal-setting theory and some Pygmalion research, this
result supports the notion that low or easier-to-achieve goals are less motivating than high and
challenging goals.
Table 4 shows the results of the marginal effect analysis, demonstrating similar
heterogeneous effects of high leader expectations to student performance as above. The positive
impact of high expectations is significant for students in the three lowest SES-quintiles, but non-
24
significant for students in the two highest quintiles. Thus, high expectations appear to be
particularly efficient in fostering better outcomes among more socially-disadvantaged students.
Table 4: Marginal effects of leader’s expectations on student test scores conditioned by
students’ socio-economic background with and without control for teacher
expectations and past performance.
quintile
1st quintile
2nd quintile
3rd quintile
4th quintile
5th quintile
Marginal effects (municipal fixed
effects)
dy/dx (std. err.)
With control for teacher
expectation and past performance
dy/dx (std. err.)
.025**
(.007)
.019**
(.006)
.014*
(.006)
.008
(.006)
-.007
(.013)
** p<.01, * p<.05, † p<.10
.019**
(.007)
.014*
(.006)
.009
(.006)
.003
(.007)
-.013
(.013)
We diminish the risk of reverse causality bias by including a control for past performance.
Moreover, the moderation test findings (i.e., the test of H2) speak against such bias. In brief, the
findings appear counter-intuitive to what we would expect if the leader expectation-student
performance relationship was fully driven by reverse causality (i.e. high performance leading to
high expectations). We find a positive association between leader expectations and student
performance, which is especially predominant among low-SES students. Because the
accomplishment of high performance expectations among leaders and teachers is more difficult in
the contexts of low-SES students—we expect that reverse causality bias would work by lower
social status among students decreasing both performance and expectations to performance. In fact
this is what typically happens as seen in table 3 and table 4 for the impact of SES on student
performance, and in separate analyses (not shown here) we also find that high student social status
25
generally tends to foster higher leader expectations. Moreover, we expect that any reverse causation
effects would engender a stronger expectation-performance relationship among high-SES students.
To the contrary, we find this relationship for low-SES students. The implication is that in general
students’ low social status tends to decrease leader expectations to their performance (not shown
here) while in fact high leader expectations – when practiced - seem to increase the performance of
particularly low social status students. Thus, although we cannot reject the possible issue of reverse
causation, our moderation result helps to minimize this concern.
CONCLUSION
Since Rosenthal’s pioneering studies of Pygmalion effects showing that teachers’ high expectation
increase the achievement of their students, numerous experimental studies have showed that also
managers’ expectations for followers increase followers’ performance and efforts. We extend this
research by showing that leaders’ expectations even have impacts across multiple hierarchical
levels, by affecting the performance of followers’ followers. Thus, school principals’
communicating high expectations have impacts beyond their teachers by increasing students’
achievements. As expected by goal setting theory and some Pygmalion leadership research this
effect is strongest when the expectations are most difficult to meet—in this case for the
performance of socioeconomically disadvantaged students.
Leaders’ expectation may affect distant followers’ performance though several channels.
One is indirect by cascading leadership effects when the leaders’ expectations are reflected in the
leadership style of the immediate subordinate, here in teachers setting high expectations to their
students, which make the latter perform better. However, the impact of leadership expectations does
not exclusively work this way as we show that leader expectations are associated with student
achievement even when controlling for teacher expectations. Accordingly, some of the leader
expectation impact on student achievement must work through other indirect or direct channels.
One of several potential other indirect channels might be subordinate front line staffs’ efforts, which
26
in several Pygmalion leadership studies have been shown to be increased by leaders setting higher
expectations. And as shown in work motivational research greater efforts among workers are
driving goal-achievement and performance. However, leader expectations might also affect distant
followers directly by bypassing one or more hierarchical levels. Leaders with high expectations
could also influence target groups—e.g. students and their parents—directly by communicating
high expectations to them. Target groups, as in this case students and their parents, have important
roles in coproducing public services (Ostrom 1996, Bovaird 2007, McCulloch 2009). Leaders’
signaling high expectations for target group performance could be a crucial way of managing
coproduction among target groups. With the present research design, we cannot disentangle these
indirect cascading and other indirect effects and the direct effects of leader expectation on distant
followers other than stating that the impact is not completely driven by cascading effects.
Clearly, the self-reinforcing nature of our theorizing advises some caution in the causal
interpretation of our statistical findings. High performance is likely to lead to higher expectations
(Jussim and Harper 2005). While non-experimental studies are inherently challenged in terms of
establishing hard evidence in this area, our data and design strategy offer several strong-points—in
turn making our findings contribute to existing empirical knowledge.
First, we do not use self-reported performance measures (which might have led to some
common source bias), but apply students’ test scores in national tests that are graded by external
examiners and thus provide more objective performance measures (Meier and O’Toole 2013, Meier
et al. 2015). Second, we do not use self-reported leader expectations (which might have led to some
social desirability bias), but apply teachers’ assessments of their leaders’ expectations regarding
task performance. By the same token, teachers are likely to be more influenced by how they
perceive their leader’s behaviors than by how leaders prefer to present themselves (Favero et al.
2015, Jacobsen and Andersen 2015).
27
Third, when examining the relation between leader expectation and target group
performance, we control for teachers´ expectations to their students’ performance to make sure that
leaders’ expectations are not merely reflecting those of the teachers. This control also makes it more
probable that a positive relationship between leader expectations and target group performance is
not merely caused by cascading effects by teachers mediating leader expectations to the
performance of target groups. Leader expectations are also affecting the performance of target
groups by other indirect factors or directly.
Fourth, using extraordinarily detailed archival register data, we control for many aspects of
students’ social and economic background, which are known to be highly correlated with student
performance and may also affect leaders’ and subordinates’ expectations. Fifth, we use municipality
fixed effects to control for unobserved heterogeneity at the municipality level. Sixth, we control for
past performance at the school level in order to diminish the risk of adverse causality. This would
be the case if the positive relationship between leader expectations and target group performance is
merely reflecting that high target group performance is increasing leaders’ expectations (Jussim and
Harper 2005).
Finally, we find strongest associations between leader expectations and target group
performance for the most disadvantaged group of students. If students’ previous high performance
was driving leader expectations upward, we would expect to find the strongest associations between
advantaged (hence high-performing) students and expectations among leaders and subordinates. We
find the opposite, which in turn increases the confidence in our causal interpretation of the results.
In sum, the findings presented in this paper support the theoretical notion that the
performance of distant followers – and here organizational performance at the delivery level increases when public managers are signaling high performance expectations to followers and
followers’ followers.
28
The research on Pygmalion effects and Pygmalion leadership effects has been dominated by
experimental research designs in which teachers’ or leaders’ expectations are manipulated with
false information on the virtues of some of their followers. The strength of this method in terms of
identifying causal effects is unquestionable. However, the deception used raises some ethical
concerns. It also fails to take into account that leader-follower relationships typically evolve over
time with expectations affecting follower performance, and follower performance affecting leader
or teacher expectations (Jussim and Harper 2005). Therefore, there has been a call for studies of
established leader-follower relationships in more natural contexts (e.g., Eden et al., 2000, Kierein
and Gold, 2000, and McNatt, 2000). This study makes a contribution towards meeting this call.
While research on Pygmalion effects has predominantly been performed in educational
settings, a few military settings have dominated Pygmalion leadership research. Thus our study of
Pygmalion leadership effects is an extension of that leadership research into the field of education
indicating that Pygmalion leadership effects are relevant in other settings.
Public school principals in Denmark may have less decision-making authority compared to
other countries—due to a corporatist tradition with strong influence from teachers unions and shop
stewards (Meier et al. 2014). According to cultural research by Hofstede (1980, 1983), Denmark is
also an extreme case of small power distance with little respect of authorities. In this perspective,
our case choice constitutes a relatively “tough” test of the impact of leader expectations on
performance, implying that our findings are likely to apply also in other settings. It is though worth
considering if leader expectations might have the greatest impact on performance in public service
organizations where there is a considerable goal-consensus between the organization and the target
groups. However, signaling expectations also seems to have an important role in regulatory
enforcement (Winter and May 2001).
Our research points to some issues calling for future research. For example, what
interventions may actively increase leaders’ expectations? Experimental research by Eden and
29
colleagues (2000) on the role of training as an instrument to increase leader expectations did not
offer any answer to this question. Yet, as indicated by White and Locke (2000), there may be other
experimental as well as observational ways to study the role of training and other instruments for
increasing leader expectations. We also need studies that examine the extent to which and by what
mechanisms leader expectations directly or indirectly are affecting distant followers, including
target groups. There is a lack of research on multilevel leadership not only within Pygmalion
leadership theory but also more generally in leadership and management research (Hannah et al.
2008, Yukl 2013). While a substantial amount of research in the last 15 years has demonstrated that
management and leadership matter for organizational performance, we do not know much about the
mechanisms by which they matter.
Having high expectations for clients who are already performing well may not be very
difficult. But to have high expectations for target group clients with the least likelihood of high
performance is something different. Some leaders of public organizations seem, however, to do so
pretty well.
30
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