OUTPUT AND EFFICIENCY IN THE PRODUCTION

OF

BUSINESS AND ECONOMICS MAJORS by

Carlos Asarta
A DISSERTATION
Presented to the Faculty of

The Graduate College at the University of Nebraska

In Partial Fulfillment of Requirements

For the Degree of Doctor of Philosophy Major: Economics
this study was comprehensive and included information on the standardized test scores,
demographic characteristics, ability levels, transfer status, major areas of study and core
business course performance of 689 graduating seniors from the College of Business
Administration (CBA) at the University of Nebraska-Lincoln (UNL).
The production and retention of core business knowledge was influenced by a
number of demographic, ability and transfer variables. Male students outperformed
females in all four Major Field Test in Business (MFT-B) models, suggesting that gender
is a significant factor in the production of core business knowledge. Other significant
demographic factors included the age, ethnicity/race and nationality of graduating
seniors. Entry SAT scores and core GPAs were highly significant in explaining the
production of core business knowledge, while the transfer of core business courses from
outside institutions negatively influenced the performance of students on the MFT-B.
Economics major were the only students to exhibit a positive and significant MFT-B
point advantage, while marketing students were the only major to score significantly
lower than their business peers. The performance of students in the Principles of Macroeconomics, Business Law, and Principles of Finance courses contributed to
significantly higher MFT-B scores. The transfer of Statistics, Principles of Accounting II
and Business Law was detrimental to the production of core business knowledge. Finally,
all majors but economics were less efficient at retaining core business knowledge when
they transferred at least one core business course from an outside institution.
The basic academic abilities of graduating seniors were unrelated to a student’s
age or gender. White students, however, tended to exhibit significantly higher exit ability
levels than students from other races/ethnicities. A student’s nationality and entry SAT
scores were not found to significantly improve his/her basic academic abilities. Student
performance in non-core courses, however, consistently explained student scores on the
Collegiate Learning Assessment (CLA) test. The performance of students in Principles of
Macroeconomics and Principles of Marketing positively influenced their exit academic
abilities, while the transfer of the Business Law course offered at UNL was the only


Special thanks go to Jan Hime and Lindsay Kruse for their support in locating the
sources for the data used in this study. Sharon Nemeth was instrumental in proofreading
and formatting the various documents included in this dissertation.

Me gustaria darle las gracias a mis queridos padres, Alberto y Clara, por darme la
education, ayuda y cariño necesarios para poder completar este sueno. Espero que esteis
orgullosos de vuestro hijo.

Finally, I would like to thank my wife, who has been supportive of my dream of
becoming a doctor since day one. Your support, love and care for our family have
allowed us to overcome the many obstacles encountered through the past five years.
This dissertation is dedicated to you and to our beautiful children, Cristian and Kenedi. Table of Contents
List of Tables i

Chapter 1: The Nature and Objectives of the Research 1

Chapter 2: Literature Review 7

2.1 The Production Function Model 7

2.1.1 The Education Production Function 8
2.1.2 Educational Production Inputs 10
2.1.3 Educational Production Outputs 11
2.1.4 Conceptual, Methodological and Empirical Issues 13

2.2 Outcome Measures and Assessment 18


3.2.1 The Business Senior Assessment Course (BSAD098) 61
3.2.2 Common Body of Knowledge Topics and Sequence 65

3.3 Concluding Comments 66

Chapter 4: Variables and Sample 68

4.1 Dependent Variables 68

4.1.1 MFT-B Score (MFTB) 68
4.1.2 CLA Score (VADDCLA) 69

4.2 Independent Variables 69

4.2.1 Student Gender (MALE) 71
4.2.2 Student Age (AGE) 72
4.2.3 Ethnic Background (WHITE, ASIAN, OTHER) 72
4.2.4 Student Citizenship (ORIGIN) 73
4.2.5 Transfer Status and Credits (TRANSFCORE/OTHER,
TRANSFCORECR) 73
4.2.6 SAT Score (SAT) 74
4.2.7 Overall, Core and Other Grade Point Averages (GPA,
CORE/OTHERGPA) 74
4.2.8 Student Major 76
4.2.9 Course Grades in the Common Body of Knowledge 76
4.2.10 Common Body of Knowledge Course Transfer (TRANSF+COURSE) 78
4.2.11 Student Major and Transfer Status (MAJOR+TRANSFCORE) 78

4.3 Descriptive Statistics 78


6.2 Results 151

6.3 Implications 157

6.4 Limitations 162

References 165

Appendix 2.1: Major Field Test in Business Sample Questions 176

Appendix 2.2: Major Field Test in Business Content 181

Appendix 2.3: Standards for Business Accreditation 185

Appendix 3.1: CBA Senior Survey 192
Appendix 3.2: Career Placement Assessment Survey 198

Appendix 3.3: Required Core Business Courses, UNL 202

Appendix 4.1: Standard ACT to SAT Table 205

Appendix 5.1: Correlation Coefficients for Models 1-4 206

Appendix 5.2: Transfer Intensity on MFT-B Performance 210

i

Table 5.10: Choice of Major Effects of CLA Performance 138
Table 5.11: Core Course Achievement Effects on CLA Performance 141
Table 5.12: Transfer of Core Courses Effects on CLA Performance 143

Appendix 4.1: Standard ACT to ACT Conversion Table 205
ii Appendix 5.1: Correlation Coefficients for Models 1-4 206
Model 1 206
Model 2 207
Model 3 208
Model 4 209
Appendix 5.2: Transfer Intensity on MFT-B Performance 210

1 Chapter 1
The Nature and Objectives of the Research
The production of education is characterized by choices derived from scarcity of
resources. Due to recent declines in public funding, the burden of education has
increasingly fallen on students and parents, and a greater emphasis has been placed on
streamlining and improving the efficiency of the educational process by carefully
selecting and using the available educational inputs to maximize the creation and
retention of knowledge. Declining enrollments and shrinking market shares have also
created added pressures for legislators and school administrators. As a result, universities
and colleges are expected to assess and continuously improve the quality of their
programs, and accrediting institutions have gain importance in the world of academia
(Becker and Andrews, 2004). Generally, the efficiency of educational inputs and the

than similar students who major in other areas within the business curriculum? And if this
is the case, are there other significant factors involved in such production? In other
words, are accountants more productive, in terms of their core business knowledge and
basic general abilities, than economists after controlling for demographic characteristics,
ability levels, and transfer status? There is a possibility that a student’s major may not be
a determinant in explaining student performance on the MFT-B and CLA exams, or that
the difference between the core knowledge and basic abilities accumulated by graduating
3 seniors from different majors not be significant. The repercussions of such findings could
have a direct impact in labor markets. An accounting graduate could become as desirable
as a finance graduate to a prospective general business sector employer if in fact
accountants and finance students generate similar amounts of core business knowledge
and exhibit similar general ability levels after the completion of their undergraduate
programs. On the other hand, if certain majors are found to generate statistically larger
amounts of core business knowledge before graduation, such information should be made
available to students and the majors should be promoted by departments and colleges.
The contributions of specific business courses to the production of core business
knowledge by undergraduate business students are of special interest in answering the
first question asked in this study. The identification of significant courses would allow
administrators to place more emphasis and increase the requirements in those specific
classes so as to improve the student production of core business knowledge and their
basic general abilities. A secondary incentive for institutions to promote learning in these
specific courses includes gaining faster membership or continuous accreditation with
their accrediting agencies (i.e. The Association to Advance Collegiate Schools of
Business (AACSB)).
In recent years, universities in the United States have seen an increasing flow of
students transferring from community and junior colleges, which could be detrimental to
the production of knowledge if such institutions provide a lower undergraduate education
these standardized exams is, in a way, a measure of how efficient students are at
maintaining their basic business and general ability levels because there is a time-lag
between the moment they are presented with the materials and the time when they have
to take the assessment instruments. In this study, the efficiency of the different majors
offered at UNL in retaining basic knowledge will be examined. Of special interest is the
retention of knowledge for the group of students majoring and minoring in economics.
The limited availability and recent use of comprehensive business outcome measures, and
the reduced number of students graduating with economic degrees has made it impossible
for researchers to answer this question. Unlike previous research, the dataset used in this
study is large and comprehensive, but the number of students majoring in economics is
still relatively small. Information regarding the minors of graduating seniors, however, is
available and will be included in this study. Students minoring in economics are required
to enroll in the same general economic courses as economic and business majors, but
differ from all other business student because they receive economic training beyond the
basic business requirement. There are no known published research studies in the area of
economic education using production functions where the educational output is the
performance on the MFT-B (or any other comprehensive business output measure) and
the educational inputs belong or are related to students majoring or minoring in
economics.
Finally, this study will measure efficiency by identifying the factors that
contribute to higher levels of basic academic ability after controlling for initial levels of
general ability, demographic characteristics, other ability measures, transfer status and
student majors. The Collegiate Learning Assessment instrument (CLA) is an innovative
6 internet testing instrument designed to simulate complex, ambiguous situations that every
successful college graduate may one day face in the form of written communication,

production of academic business knowledge. An overview of the inputs and outputs used
in the literature, as well as a summary of the main conceptual, methodological and
empirical issues frequently encountered in production function studies can be found in
this section. Section two presents several standardized outcome measures available to
business schools to assess the overall performance of their students and programs. A
review of the Association to Advance Collegiate Schools of Business International is
included in this second section. The chapter concludes by examining the main student
characteristics that have been studied in previous education production models. The
emphasis is placed in the economic education literature but reference is made to other
business areas.

2.1 The Production Function Model
The 1964 “Coleman Report” was the first and most influential educational
production function study ever conducted. It included information on over half a million
students and more than 300 schools and concluded that traditional school inputs, as
reflected by per pupil expenditures, class-size and certain teacher attributes have minimal
effects on student achievement. Since then, many researchers have attempted to utilize
production functions to estimate the relationship between educational inputs and student
achievement, both at the pre-college and college and university levels. Considerable
8 confusion remains about how such studies should be conducted and interpreted, as well
as what can be learned from them (Hanushek, 1978; Becker, 2004). More importantly,
there seems to be a series of conceptual, methodological and empirical problems that
have “shadowed” previous research findings and conclusions in the area of education
production functions.
This section is organized as follows. First, the reader can find a brief description
of the theoretical model that will be used to assess the effect of different educational
inputs on the production of academic business knowledge. An overview of the inputs and

diminishing marginal returns are mild; linear approximations are not valid if the range
being observed belongs to an area where diminishing marginal returns are considerably
strong. Cohn and Geske also point out that the conclusions derived from the use of linear
analysis should not be applied to input levels beyond the range of the sample observation.
The general form of the ith educational production function using a linear
approximation to the production of knowledge is given by:

ij
m
j
ijh
k
h
ihg
n
g
igii
esdxcqbaq ++++=
∑∑∑
=== 111
[Equation 2]
10 In equation 2,
i
a is the intercept, while scsb
ihig
, and sd
ij


student achievement. This influential study ignited an intense debate in the areas of
education and forced researches to look beyond traditional school inputs when trying to
estimate educational production functions. Watts (1985) included a “poverty index”
variable while testing different specifications of an educational production functions for
student belonging to more than two hundred classes in the state of Indiana. Family
income, number of books at home, the general characteristics of the student body, grade
point average for a students’ section, family size, race or sex are some of the non-
university inputs that have been frequently used in previous production function
estimates (Cohn and Geske, 1990).
It is obvious that although some of the inputs are easily manipulable by university
administrators (i.e. course content) other are not manipulable (i.e. age of students) and
can not be controlled and changed to increase educational output. The non-manipulative
nature of such educational inputs makes the selection process of those entering the
educational system, especially at the higher education level, even more relevant as they
directly relate to the technical and internal process of generating educational knowledge.

2.1.3 Educational Production Outputs
The two types of educational outputs that have been identified and measured in
the economics of education literature are consumption and investment outcomes (Cohn
and Geske, 1990). Consumption outcomes relate to the present utility that students, their
families and society derive from the consumption of education. On the other hand,
investment outcomes relate to the future productive skills and well-being of society.

12 Consumption outcomes include satisfaction from the direct involvement of
students in activities offered by universities or intellectual satisfaction from learning new
materials and skills. Other consumption outcomes include family relieve of responsibility

[…] student attitudes have rarely entered a formalized educational input-output model”
(p.165).

Since the production of education differs from “industrial” production in that the
educational industry generates multiple outputs, estimates of educational outcomes
should include as many relevant and reliable measures of educational attainment as
possible, including the widely used and available battery of standardize test score.

2.1.4 Conceptual, Methodological and Empirical Issues
In theory, the production function represents the maximum achievable output for
a given level of inputs and firms make decisions on the optimal amount of inputs to use
in order to maximize their profits. The question is whether production functions, as they
are used in standard production, are a viable method for modeling the creation of
educational output. In reality, the application of production functions to education is
complicated because the technological process of transforming inputs into output is
generally not known and needs to be estimated through observation, the contribution of
similar inputs to the creation of knowledge may vary widely and due to the
heterogeneous nature of the produced output (individuals with different quality
attributes).
Hanushek (1978) and Becker (2004) addressed conceptual and statistical issues
related to research on the estimation of educational production functions and teaching
methods. They observed that student outcomes were generally measured through the use
of standardized tests, but that other plausible outcomes had been studied (i.e. attendance
rates and continuation or dropout rates). The use of different outcome measures, in
conjunction with the variety of inputs introduced in studies of educational production