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RULES FOR 
SCIENTIFIC 
RESEARCH IN 
ECONOMICS
The Alpha-Beta 
Method 
Adolfo Figueroa
 Rules for Scientifi c Research in Economics 
 
 Adolfo   Figueroa 
 Rules for Scientifi c 
Research in 
Economics 
 The Alpha-Beta Method 
 ISBN 978-3-319-30541-7 ISBN 978-3-319-30542-4 (eBook) 
 DOI 10.1007/978-3-319-30542-4 
 Library of Congress Control Number: 2016944657 
 © The Editor(s) (if applicable) and The Author(s) 2016 
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 The publisher, the authors and the editors are safe to assume that the advice and information 
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material contained herein or for any errors or omissions that may have been made. 
 Printed on acid-free paper 
 This Palgrave Macmillan imprint is published by Springer Nature 
 The registered company is Springer International Publishing AG Switzerland 
 Adolfo   Figueroa 
Pontifi cal Catholic University of Peru
 Lima , Peru 
 To Nicholas Georgescu-Roegen, my teacher, in memoriam 
 
vii
 Why has the growth of scientifi c knowledge in the social sciences pro-
ceeded at a rate that is slower than that of the natural sciences? The 
basic reason seems to rest upon the differences in the complexity of the 
reality they study. Compared to the natural sciences, the social sciences 
seek to explain the functioning of the social world, which is a much 
more complex world than the physical world. As biologist Edward 
Wilson pointed out:
 Everyone knows that the social sciences are hypercomplex. They are inher-
ently far more diffi cult than physics and chemistry, and as a result they, not 
physics and chemistry, should be called the hard sciences (1998, p. 183) 
 Methodology deals with the problem of how to construct scientifi c 
knowledge. Is the understanding of the social world more demanding 
on methodology than understanding the physical world? Economist Paul 
Samuelson argued in his classic book Foundations of Economic Analysis 
that indeed this is the case:
 [This] book may hold some interest for the reader who is curious about 
the methodology of the social sciences…[I]n a hard, exact science [as phys-
ics] a practitioner does not really have to know much about methodology. 
Indeed, even if he is a defi nitely misguided methodologist, the subject 
itself has a self-cleansing property which renders harmless his aberrations. 
By contrast, a scholar in economics who is fundamentally confused con-
cerning [methodology] may spend a lifetime shadow-boxing with reality. 
 PREF ACE 
viii PREFACE
In a sense, therefore, in order to earn his daily bread as a fruitful contribu-
tor to knowledge, the practitioner of an intermediately hard science like 
economics must come to terms with methodological problems. (1947, pp. 
viii–ix) 
 Paraphrasing both Wilson and Samuelson, the researcher’s good com-
mand of methodology is more critical for producing scientifi c knowledge 
on the highly complex sciences (social sciences) than in the less complex 
sciences (natural sciences). Therefore, the answer to the question posed 
above seems to be that the difference lies in methodology. Social sciences 
development needs to use better methodology and more intensively. This 
book intends to contribute to that development. 
 Methodology is also called epistemology (from the Greek episteme , 
knowledge). Epistemology or methodology is usually presented as part 
of philosophy of science. In this view, epistemology is a branch of phi-
losophy that seeks to scrutinize the philosophical problems that arise in 
the practice of science, such as epistemological, metaphysical, and ethi-
cal problems. Philosophy of economics is the particular fi eld that deals 
with philosophical problems in economics, as economists practice it. To 
be sure, this book is not about philosophy of economics. There are good 
recent books that show the state of this discipline (e.g. Reiss 2013). 
 The approach followed in this book will be different. It will correspond 
to the view of epistemology as the theory of knowledge—the logic of 
scientifi c knowledge. Then epistemology will be seen as part of the formal 
science of logic, not of philosophy. Indeed, some textbooks of logic now 
deal with the logic of scientifi c knowledge (e.g. Hurley 2008). 
 The book will show practical rules for the construction and growth of 
scientifi c knowledge in economics, which will be derived logically from a 
particular theory of knowledge or epistemology. No such rules exist cur-
rently in economics; that is, economists follow a diversity of rules, derived 
from a diversity of epistemologies or having no epistemological justifi ca-
tion. The intended contribution of the book is then normative: what rules 
of scientifi c research ought economists to follow. This view of epistemol-
ogy is more natural for working scientists, who are epistemology users 
rather than makers. 
 The epistemology proposed by Karl Popper (1968) will be adopted in 
this book. This is one of the most popular epistemologies in the literature. 
It essentially says that theory is required for scientifi c knowledge, but this 
theory must be empirically falsifi able or refutable; thus, good theories will 
PREFACE ix
prevail and bad theories will be eliminated, as in a Darwinian competition. 
Scientifi c progress will result from this competition. 
 However, Popperian falsifi cation epistemology is also the most debated. 
Many authors have argued that Popperian epistemology is not applica-
ble in economics. The arguments are clearly summarized in the Stanford 
Encyclopedia of Philosophy by Daniel Hausman (2013), a leading philoso-
pher of economics. They are
 1. Economic theories are rarely falsifi able. 
 2. When they are, they are rarely submitted to testing. 
 3. When they fail the test, they are rarely repudiated. 
 Consequently, we can understand why in economics we observe that 
no theory is ever eliminated and that progress in scientifi c knowledge is 
relatively limited, in spite of large amounts of research work. 
 Problems (2) and (3) refer to what economists do and why. These are 
not within the scope of this book. Problem (1) is the subject of this book. 
The challenge is how to make Popperian epistemology applicable and 
operational in economics. Can we logically derive from Popperian episte-
mology a set of practical rules for scientifi c research in economics? As the 
book will show, this derivation is subject to the transformation of a com-
plex social world into a simple abstract world. Popperian epistemology 
might be suitable for physics, but whether it is so for economics, a science 
dealing with a complex world, is another question. In fact, problem (1) 
has to do with the complexity of the social world. 
 How to make knowable a complex reality, such as the social world? The 
late Vanderbilt University professor of economics, Nicholas Georgescu- 
Roegen (1971) proposed a solution to this problem, and developed the 
 process epistemology . Georgescu-Roegenis mostly known as the founder of 
bio-economics, an economic school different from standard economics, 
but his contribution to epistemology is less known. 
 Consider now combining the epistemologies of Popper and Georgescu- 
Roegen into a single one, as they do not contradict each other. Call this 
combination the composite epistemology . Then, as will be shown in this 
book, a set of rules for scientifi c research in economics can be derived from 
the composite epistemology. This set of rules will thus constitute a scien-
tifi c research method, as it will have epistemological justifi cation or logi-
cal foundations. This will be called the alpha-beta method . This method 
intends to solve the falsifi cation problem in economics, the problem that 
x PREFACE
“economic theories are rarely falsifi able”—the problem (1) of Popperian 
epistemology, cited above. The alpha-beta method is a scientifi c research 
method that ensures economic theories be always falsifi able. Thus, the 
alpha-beta method is not another name for a known method, but a truly 
new scientifi c research method, the application of which should contrib-
ute to scientifi c progress in economics. The book is thus intended to be 
problem-solving. 
 Economics is a social science. However, this defi nition of economics 
is not always accepted and the term social science is usually reserved for 
sociology, anthropology, and political science. Although scientifi c rules are 
derived for economics only, the book will show that extensions to the other 
social sciences are nearly straightforward. This procedure means that eco-
nomics is presented as an example of the social sciences, not as the exemplar . 
 Differences in the complexity of the social world compared to the phys-
ical world must be refl ected in the different epistemologies social sciences 
and natural sciences use. The book presents a comparison between these 
epistemologies, just to better understand the epistemology of economics 
and the other social sciences. 
 Therefore, this book is concerned with the problem of how sciences 
ought to seek scientifi c knowledge, not with what scientists actually do. 
The common proposition “Science is what scientists do” ignores this dis-
tinction. Therefore, this book deals with the question of how scientifi c 
research in economics ought to operate. The question of what economists 
actually do and why is outside the scope of this book, for the answer 
would require a scientifi c theory to explain that behavior. The book takes 
the epistemologies of Popper and Georgescu-Roegen as given, and deals 
with the problem of deriving logically from them a set of practical rules for 
scientifi c research in economics. 
 The book includes 10 chapters. Chapters 1 , 2 , 3 and 4 deal with the 
construction of the alpha-beta method and its application to economics. 
Chapters 5 and 6 show the logic of statistical testing of economic theories 
under the particular alpha-beta method. Chapter 7 compares the alpha- 
beta method with other empirical research methods. Chapter 8 discusses 
the most common fallacies found in economics that are uncovered by the 
alpha-beta method. Chapter 9 compares the epistemologies of natural sci-
ences and economics in the light of the alpha-beta method. Chapter 10 
presents the conclusions of the book. 
 In sum, the objective of this book is to present a set of rules for scien-
tifi c research in economics, which are contained in the alpha-beta method. 
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PREFACE xi
These rules are scarcely used today, which is refl ected in the fact that no 
economic theory has been eliminated so far, and thus we observe the coex-
istence of the same economic theories (classical, neoclassical, Keynesian, 
and others) over time, with the consequent lack of Darwinian competition 
of theories. Scientifi c progress is the result of such evolutionary competi-
tion. Therefore, the book seeks to contribute to the scientifi c progress 
of economics by proposing the use of the alpha-beta method, a method 
designed for the evolutionary progress of economics. 
 The book is primarily addressed to students of economics at advanced 
undergraduate and graduate levels. Students in the other social sciences 
may also fi nd it useful in the task of increasing the growth of interdisci-
plinary research within the social sciences. Even students of the natural 
sciences may benefi t from the book by learning the differences in the rules 
of scientifi c research of their own sciences with that of the social sciences. 
This understanding will prepare economists, physicists, and biologists to 
work in interdisciplinary research projects, such as the relations between 
economic growth and degradation of the biophysical environment, which 
is, certainly, one of the fundamental problems of our time. 
 
xiii
 Parts of this book have been taught in economics courses at the Social 
Science School and in the epistemology course in the Doctorate in 
Business Administration at CENTRUM Graduate Business School, both 
at Pontifi cal Catholic University of Peru, and at the Universities of Notre 
Dame, Texas at Austin, and Wisconsin at Madison, where I have been 
Visiting Professor. I would like to thank the students in these courses for 
their valuable comments and questions about my proposal of the Alpha- 
beta Method. 
 I am also grateful to the three anonymous reviewers appointed by 
Palgrave Macmillan. Their comments and suggestions to my manuscript 
were very useful to make revisions and produce the book. Sarah Lawrence, 
the Economics & Finance Editor of Palgrave Macmillan, has been most 
helpful to go through the review process of the book project. 
 My gratitude is immense with my current institution, CENTRUM 
Graduate Business School, Pontifi cal Catholic University of Peru, and 
with its Director Fernando D’Alessio, for providing me with great sup-
port for the preparation of this book. 
 ACKNOWLEDGMENTS 
 
xv
1 Science Is Epistemology 1
2 Alpha-Beta: A Scientifi c Research Method 15
3 The Economic Process 29
4 The Alpha-Beta Method in Economics 47
5 Falsifying Economic Theories (I) 63
6 Falsifying Economic Theories (II) 73
7 The Alpha-Beta Method and Other Methods 99
8 Fallacies in Scientifi c Argumentation 117
9 Comparing Economics and Natural Sciences 129
 CONTENTS 
xvi CONTENTS
10 Conclusions 145
Bibliography 151
Index 153
xvii
LIST OF FIGURES
Fig. 1.1 Diagrammatic representation of an abstract process 12
Fig. 3.1 Types of economic processes: static, dynamic, and 
evolutionary 36
Fig. 3.2 Deterministic and stochastic static processes 42
Fig. 6.1 Assumptions of regression analysis 75
Fig. 6.2 Breakdown of the variation of Yj into two components 76
 
xix
LIST OF TABLES
Table 1.1 Meta-assumptions of the theory of knowledge 6
Table 1.2 Scientifi c research rules derived from Popperian 
epistemology 8
Table 2.1 The alpha-beta method 23
Table 2.2 Matrix of beta propositions or matrix of causality 26
Table 3.1 Economic process according to E-theory 32
Table 4.1 The alpha-beta method in economics 56
Table 5.1 Frequency distribution of income in the population B 67
Table 5.2 Distribution of sample means for n = 2 drawn from 
population B 67
Table 5.3 Frequency distribution of income in the population C 70
Table 5.4 Distribution of sample means for n = 2 drawn from 
population C 70
Table 6.1 Kinds of reality based on Searle’s classifi cation 89
Table 7.1 Research methods: scientific and empirical 112
1© The Editor(s) (if applicable) and The Author(s) 2016
A. Figueroa, Rules for Scientific Research in Economics, 
DOI 10.1007/978-3-319-30542-4_1
Chapter 1
Abstract What is the criterion to accept or reject propositions about 
the social reality as scientific? We need rules for that, which must have 
some rationality, some logic. this logic is called epistemology. Science is 
epistemology. What is the epistemology of economics? the answer is still 
debated. the use of the falsification epistemology of Karl popper in eco-
nomics has been questioned. this chapter presents this epistemology and 
analyzes the reasons for its shortcomings. then the chapter introduces 
the process epistemology of Nicholas Georgescu-roegen, which deals with 
complex realities, and shows that the two epistemologies are complemen-
tary and thus can be combined into a single composite epistemology. the 
composite epistemology is now applicable to sciences dealing with com-
plex realities, such as those studied by economics.
Scientific knowledge seeks to establish relations between objects. the 
objects can be mental or physical. Formal sciences study the relations 
between mental objects, whereas factual sciences study the relations 
between material objects. Mathematics and logic are examples of formal 
science; physics and economics are instances of factual sciences.
Scientific knowledge takes the form of propositions that intend to be 
error-free. Scientific knowledge is therefore a particular type of human 
knowledge. What would be the criterion to accept or reject a proposi-
tion as scientific? It depends upon the type of science. In the formal 
sciences, the criterion seems to be rather straightforward: the relations 
Science Is epistemology
established must be free of internal logical contradictions, as in a math-
ematical theorem.
In the factual sciences, by contrast, the criteria are more involved. as 
will be shown in this book, factual science propositions are based on for-
mal science propositions; that is, the propositions of a factual science must 
also be free of internal logical contradictions. however, this rule consti-
tutes just a necessary condition, for the propositions must also be con-
fronted against real-world data.
Scientific knowledge in the factual sciences can be defined as the set 
of propositions about the existence of relations between material objects 
together with the explanations about the reasons for the existence of such 
relationships. therefore, it seeks to determine causality relations: what 
causes what and why. It also seeks to be error-free knowledge, as said above.
We can think of several criteria to accept or reject a proposition in the 
factual science. Common sense is the most frequent criterion utilized in 
everyday life. Common sense refers to human intuition, which is a strong 
force in human knowledge. Intuition is the natural method of human 
knowledge.
the assumption taken in this book is that intuitive knowledge is subject 
to substantial errors. Intuitive knowledge is based on human perceptions, 
which can be deceiving. Galileo’s proposition that the earth spins on its 
axis and orbits around the sun was not generally accepted for a long time 
(even up to now) because it contradicted intuitive knowledge: people can-
not feel the earth spinning and what they can see is rather that the sun 
is going around the earth. the same can be said about today’s climate 
change because the greenhouse gases are invisible to human eyes. Intuitive 
knowledge is thus the primitive form of human knowledge.
as said earlier, science seeks to produce error-free human knowledge. 
therefore, human knowledge in the form of scientific knowledge requires 
the use of a scientific method, which needs to be learned and educated. thus, 
science has to do with method. thus, the criteria for accepting or reject-
ing propositions as scientific in the factual sciences—the scientific method—
needs to be constructed. this construction is the task of epistemology.
The Role of episTemology in scienTific Knowledge
In this book, epistemology is viewed as the field that studies the logic of 
scientific knowledge in the factual sciences. epistemology sees scientific 
knowledge as fundamentally problematic and in need of justification, of 
2 a. FIGUerOa
proof, of validation, of foundation, of legitimation. therefore, the objec-
tive of epistemology is to investigate the validity of scientific knowledge. 
For this we need a criterion to determine whether and when scientific 
knowledge is valid. this criterion cannot be based on facts, for they are the 
objective of having a criterion; thus, the criterion can only be established 
logically. Scientific knowledge must have a logic, a rationality, established 
by a set of assumptions. therefore, the criterion is given by a theory of 
knowledge, which as any theory is a set of assumptions that constitute a 
logical system.
epistemology will thus be seen as theory of knowledge, as a logi-
cal system. In this book, the concept of theory will be applied to the 
logic of scientific knowledge as well as to the scientific knowledge itself. 
Consequently, two very useful definitions in parallel are needed at the very 
beginning:
Theory of knowledge is the set of assumptions that gives us a logical criterion 
to determine the validity of scientific knowledge, from which a set of rules 
for scientific research can be derived. the set of assumptions constitutes a 
logical system, free of internal contradictions.
Scientific theory is the set of assumptions about the essential underlying fac-
tors operating in the observed functioning of the real world, from which 
empirically testable propositions can be logically derived. the set of assump-
tions constitutes a logical system, free of internal contradictions.
any factual science needs to solve the criterion of knowledge before 
doing its work because this question cannot be solved within the factual 
science. the logical impossibility of obtaining the criterion from within 
the factual science is relatively easy to proof. Let S represent any factual 
science. then
Factual science (S) is a set of relations (r) between material objects X and 
material objects Y, which are established according to criterion (L).
this proposition can be represented as follows:
 
S = R X, Y / L( ){ }
 
(1.1)
SCIeNCe IS epISteMOLOGY 3
how would L be determined? If L were part of S, then L would be estab-
lished through the relations between physical objects, that is, relations 
between atoms (physical world) or between people (social world); how-
ever, this leads us to the logical problem of circular reasoning because 
we need L precisely to explain the relations between atoms or between 
people.
the criterion L will thus have to be determined outside the factual sci-
ence. how? the alternative is to go to the formal science, in particular to 
the science of logic. the criterion L is now justified by a logical system. 
this logical system is precisely the theory of knowledge (t), which as any 
theory is a set of assumptions (a). then we can write
 
S = R X,Y / L
L = T A / B
( ){ }
( ){ }
= ( ){ }
……… ……
′ ′ ′B T A B/
...... .. 
(1.2)
the first line of system eq. (1.2) just repeats the definition of factual sci-
ence. the second says that criterion L is logically justified by deriving it from 
the theory of knowledge t, which includes a set of assumptions a, given the 
set of assumptions B that is able to justify a. the set B constitutes the meta-
assumptions, the assumptions underlying the set of assumptions a. the set 
B is logically unavoidable, for the set a needs justification. (e.g., why do 
I assume that there is heaven? Because I assume there is God? Why do I 
assume that there is God? Because…, etc.). therefore, the set B needs a logi-
cal justification by using another theory t′, which now contains assumptions 
a′, which in turn are based on meta-assumptions B′, and so on. hence,we 
would need to determine the assumptions of the assumptions of the assump-
tions. this algorithm leads us to the logical problem of infinite regress.
the logical problem of infinite regress is a torment in science. a classical 
anecdote is worth telling at this point (adapted from hawking 1996, p. 2):
an old person challenged the explanation of the universe given by an astron-
omer in a public lecture by saying:
 – “What you have told us is rubbish. the world is really a flat plate 
supported on the back of a giant tortoise.”
4 a. FIGUerOa
the scientist gave a superior smile before replying:
 – “What is the tortoise standing on?”
 – “You’re very clever young man, very clever,” said the old person. 
“But it is turtles all the way down.”
how could science escape from the infinite regress problem? this is a 
classical problem, the solution of which goes back to aristotle’s “unmoved 
mover.” everything that is in motion is moved by something else, but 
there cannot be an infinite series of moved movers. thus, we must assume 
that there exists an unmoved mover.
In order to construct scientific knowledge, we need an unmoved mover, 
an initial point, established as axiom, without justification, just to be able 
to start playing the scientific game, which includes eventually revising the 
initial point, and changing it if necessary. the scientific game includes the 
use of an algorithm, that is, a procedure for solving a problem by trial and 
error, in a finite number of steps, which frequently involves repetition of 
an operation. thus, the initial point is not established forever; it is only 
a logical artifice. If the route to his desired destination is unknown, the 
walker could better start walking in any direction and will be able to find 
the route by trial and error, instead of staying paralyzed.
In the system eq. (1.2) above, the only way to avoid the infinite 
regress problem in the theory of knowledge is by starting with the meta- 
assumption B as given, and thus ignoring the third line and the rest. then 
the set of assumptions B will constitute the foundation or pillar of the 
theory of knowledge t, which in turn will be the foundation or pillar of 
the criterion L, which we can use to construct the theory of knowledge. 
the infinite regress problem is thus circumvented and we are able to walk.
the role of the theory of knowledge in the growth of scientific knowl-
edge is to derive scientific rules that minimize logical errors in the task 
of accepting or rejecting propositions that are intended to be scientific 
knowledge. the theory of knowledge needs foundations, that is, meta- 
assumptions. Consider that the meta-assumptions B of the current theo-
ries of knowledge include those listed in table 1.1.
as shown earlier, these meta-assumptions need no justification. (please 
do not try to justify them! We need to move on.) thus, this initial set of 
assumptions constitutes just the beginning of an algorithm to find the best 
set of assumptions. Given these initial or fundamental assumptions, we 
have a rule to follow: any particular theory of knowledge will have to be 
logically consistent with these four general principles.
SCIeNCe IS epISteMOLOGY 5
In table 1.1, assumption (i) implies that we may fail to understand a 
reality because it is unknowable. examples may include chaotic systems 
(weather), rare events (earthquakes), and ancient civilizations where 
facts are limited. assumption (ii) in turn implies that research is needed 
to attain scientific knowledge. according to assumption (iii), a theory of 
knowledge seeks to provide science with a logical foundation or justifica-
tion, that is, with a rationality. therefore, discovery cannot appear “out 
of the blue.” accidental discoveries are not “accidental”, but part of a 
constructed logical system; otherwise, it could hardly be understood as 
discovery. according to assumption (iv), a theory of knowledge must 
have a rule that enables us to separate scientific knowledge from pseudo- 
knowledge in order to have error-free knowledge.
theory of knowledge is a set of assumptions that constitute a logical 
system; that is, the assumptions cannot contradict each other. thus, the-
ory of knowledge can be seen as part of logic, that is, as a formal science. 
Factual sciences and formal sciences thus interact: theory of knowledge 
(constructed in the formal science of logic) is needed in factual sciences. 
any theory of knowledge has a particular set of assumptions that justify 
rules of scientific knowledge, in which the set of assumptions are all con-
sistent with the meta-assumption presented in table 1.1.
It should be clear from the outset that a theory of knowledge is a nor-
mative theory. It says what the rules of scientific knowledge ought to be. 
therefore, a theory of knowledge cannot seek to explain what scientists 
do. these are not epistemological questions; they are scientific research 
questions in themselves, equivalent to researching about why financial 
investors choose a particular portfolio to allocate their funds. the answer 
to both questions (the behavior of scientists and that of investors) will 
come from a factual science. the usual sentence “science is what scientists 
do” cannot constitute a scientific rule because it is inconsistent with the 
meta-assumptions shown in table 1.1.
Table 1.1 Meta-assumptions of the theory of knowledge
(i) reality is knowable. It might not be obvious to everyone that this proposition is 
needed, but reality could be unknowable to us
(ii) Scientific knowledge about reality is not revealed to us; it is discovered by us
(iii) Discovery requires procedures or rules that are based on a single logical system, which 
implies unity of knowledge of a given reality; moreover, there exists such logical system
(iv) there exists a demarcation between scientific knowledge and non-scientific knowledge
6 a. FIGUerOa
Just to be clear on definitions:
•	 epistemology is sometimes called methodology, as it deals with the 
procedure (the “how” question) to attain scientific knowledge.
•	 epistemology is also called theory of knowledge, as it deals with the 
logic of scientific knowledge.
therefore, the three terms—epistemology, methodology, and theory of 
knowledge—can be considered synonymous and will be used interchange-
ably in this book. however, a possible confusion may arise with the use of 
the category “theory,” which may refer to either the theory of knowledge 
or to the scientific theory. In order to avoid this possible confusion, the 
book will use the term “epistemology” or “methodology” rather than 
“theory of knowledge” whenever the risk of confusion should appear.
The AssumpTions of poppeRiAn episTemology
this section will present the theory of knowledge developed by Karl 
popper (1968, 1993). popperian epistemology includes the following set 
of assumptions:
First, scientific knowledge can only be attained by using hypothetic- deductive 
logic, which implies the construction of scientific theories. Scientific theories 
are needed to explain the real world. Second, the scientific theory is empiri-
cally falsifiable or refutable. Third, the logical route for scientific knowledge 
can only go from theory to testing it against facts; in contrast, there is no 
logical route from facts to scientific theory, for it would require inductive 
logic, which does not exist.
table  1.2 displays the scientific research rules that can be logically 
derived from the assumptions of popperian epistemology. rule (a) is self- 
explanatory. rule (b) indicates that the criterion of demarcation is falsi-
fication. a proposition is not scientific if it is not empirically falsifiable. 
a falsifiable proposition is one that in principle is empirically false. Under 
the falsification principle, the presumption is that the proposition is false 
so that its testing becomes a necessity; that is, the proposition is presumed 
false until proved otherwise. If the presumption were that theproposition 
is true, or that it could be false, then the testing would become discre-
tionary; the proposition would be presumed true until proved otherwise. 
SCIeNCe IS epISteMOLOGY 7
through the falsification principle, science is protected from including 
untested propositions within its domain.
rule (c) indicates the criterion to accept or reject a scientific theory. It 
implies that the opposite of the sentence “the theory is false” is not “the 
theory is true,” but “the theory is consistent with facts” because there may 
exist another theory able to explain the same reality. this rule can be illus-
trated with a simple example. Consider a theory that states, “Figure F is 
a square” (suppose Figure F is unobservable). By definition, a square is a 
rectangle with all four sides equal. If these characteristics are taken as the 
assumptions of the theory, then the following empirical proposition can be 
logically derived: the two diagonals must be equal. If empirical evidence 
on the diagonals becomes available, and are not equal, Figure F cannot 
be a square. the theory has been refuted by facts. however, if empirically 
the diagonals are equal, we can only say that the prediction has been cor-
roborated; we cannot say that we have verified that F is a square, for the 
figure could be a rectangle.
therefore, the popperian criterion to accept a proposition as scientific 
knowledge is not based on theory alone or on empirical data alone; it is 
rather based on the empirical refutation of theories, on the elimination of 
false theories. Falsification leads us to an evolutionary (in the Darwinian 
sense) scientific knowledge. “the evolution of scientific knowledge is, in 
the main, the evolution of better and better [scientific] theories. this is a 
Darwinian process. the theories become better adapted through natural 
selection: they give us better and better information about reality. (they 
get nearer and nearer to the truth)” (popper 1993, p. 338). In sum, the 
logic of scientific knowledge is this: falsification is the way to eliminate 
Table 1.2 Scientific research rules derived from popperian epistemology
(a) Scientific theory is required to explain the real world: No scientific theory, no 
explanation
(b) Falsification is the criterion of demarcation. a scientific theory must be falsifiable. In order 
to be falsifiable, a scientific theory must contain a set of assumptions that constitute a logically 
correct system, from which empirically falsifiable propositions can be logically derived
(c) If the empirical predictions are refuted by the reality, the scientific theory is rejected; if 
they are not, the theory is accepted. a scientific theory cannot be proven true; it can only 
be proven false, which implies that a scientific theory cannot be verified, but only 
corroborated. rejecting a scientific theory is definite, but accepting it is provisional, until 
new data or superior theory appears; hence, scientific progress is a Darwinian evolutionary 
process in which scientific theories compete and false theories are eliminated
8 a. FIGUerOa
false theories and thus to generate the progress of science. In this sense, 
we may say that popperian epistemology leads to the construction of a 
critical science.
the assumptions of the popperian epistemology are consistent with 
the general principles of epistemology, established as meta-assumptions in 
table 1.1. they are clearly consistent with principles (i) and (ii), that is, the 
popperian epistemology implies rules to discover the functioning of the 
real world, assuming that this real world is knowable. referring to prin-
ciples (iii) and (iv), the popperian epistemology proposes the logic of sci-
entific knowledge based on deductive logic and falsification as the principle 
of demarcation. therefore, regarding system eq. (1.2) above, the scientific 
rules (L) have been derived from the set of assumptions of the popperian 
epistemology (set a), for given set of meta-assumptions (set B).
The AssumpTions of geoRgescu-Roegen’s 
episTemology
Social sciences seek to explain the functioning of human societies. We 
may say that human societies constitute highly complex realities. at a first 
glance, the social world seems to be a more complex reality than the physi-
cal world. the notion of complexity refers to the large number and the 
heterogeneity of the elements that constitute the particular reality under 
study, and to the multiple factors that shape the relations between those 
elements. human diversity together with the multiplicity of human inter-
actions makes human societies intricate realities; moreover, the individuals 
that make up human society are not identical, as opposed to atoms in the 
physical world. human society is a highly complex system because many 
individuals interact and individuals themselves are complex systems.
the problem that concerns us now is to find the proper epistemology 
for the social sciences. the popperian epistemology presented above gives 
us general scientific rules. according to popper, these rules are applicable 
to the natural and social sciences, for these types of sciences differ in scope, 
not much in method (popper 1976). however, the use of popperian 
epistemology in the social sciences is something that needs logical justi-
fication. to this end, this book will show, firstly, that social sciences and 
physics indeed differ in scope, but, and contrary to popper’s statement, 
that they also differ in method.
how can a complex social reality be subject to scientific knowledge? It 
will now be shown that complex realities are subject to scientific knowledge if, 
SCIeNCe IS epISteMOLOGY 9
and only if, they can be reduced to an abstract process analysis. this is the 
process epistemology of Georgescu-roegen (1971, Chap. IX), which will be 
summarized in this section.
Conceptually, a process refers to a series of activities carried out in the 
real world, having a boundary, a purpose, and a given duration; further-
more, those activities can be repeated period after period. the farming 
process of production, for example, includes many activities having a given 
duration (say, seasonality of six months), the purpose of which is, say, to 
produce potatoes, which can be repeated year after year. the factory pro-
cess of production also includes many activities, but with a shorter dura-
tion, say, the hour, the purpose of which is, say, to produce shirts, which 
can be repeated day after day.
the process epistemology makes the following assumptions:
First, the complex real world can be ordered in the form of a process, with 
given boundaries through which input–output elements cross, and given 
duration, which can be repeated period after period. this ordering is taxo-
nomic. Second, the complex real world thus ordered can be transformed into 
a simpler, abstract world by constructing a scientific theory. this is the prin-
ciple of abstraction. By transforming the complex real world into an abstract 
world, by means of a scientific theory, we can reach a scientific explanation 
to that complex real world.
On the boundary of the process and the input–output elements, the 
first assumption implies that we are able to separate those elements that 
come from outside and enter into it—called the exogenous elements—from 
those that come out from inside the process—the endogenous elements. 
all the elements that participate in a process have thus been classified as 
endogenous, exogenous, or underlying mechanisms. this is just a taxo-
nomic ordering of a process. therefore, the first assumption says that the 
complex real world can be represented in the form of a process.
the second assumption says the complex social reality can have a scien-
tific explanation if it is reducible to an abstract process, a simpler abstract 
world, by means of a scientific theory, which assumes what the essential 
elements of the process are. this is the well-known abstraction method. 
Certainly, to presentthe complete list of the elements of a process would 
be equivalent to constructing a map to the scale 1:1. as in the case of the 
map, a complex reality cannot be understood at this scale of representation. 
In the abstract form, theoretical form, the complex reality is represented by 
a map at a higher scale.
10 a. FIGUerOa
although a process would include observable and unobservable 
elements, the abstract process will select only those that are observable or 
measurable. Call endogenous variables and exogenous variables to those ele-
ments that are observable. In order to explain the changes in the endog-
enous variables, the object of the research, the scientific theory selects 
only the essential exogenous variables and the most important underly-
ing mechanisms (unobservable) by which the endogenous and exogenous 
variables are connected. the use of abstraction or the use of scientific the-
ory implies that some elements of the real-world process must be ignored. 
the process must be represented at higher scales, as in maps. In sum, this 
is how a complex real social world can be transformed into an abstract 
world, into an abstract process, in which only the supposedly important 
elements of the process are included, and the rest are just ignored.
how do we decide which elements are important in a process and 
which are not? how is an abstract process constructed? the construc-
tion of an abstract process is made through the introduction of a scien-
tific theory, which is a set of assumptions, as was defined earlier. hence, 
the assumptions of the scientific theory will determine the endogenous 
variables, the exogenous variables that are important in the process, and 
the underlying mechanisms that are also important. a scientific theory 
is, therefore, a logical artifice by which a complex real world can be 
transformed into a simple abstract world. the assumption of the process 
epistemology is that by constructing the abstract world, by means of a sci-
entific theory, we will be able to explain and understand the complex real 
world: We will know the determinants of the endogenous variables and 
also the causality relations, namely, the relations between endogenous 
and exogenous variables.
Figure 1.1 depicts the diagrammatic representation of an abstract pro-
cess. the segment t t0 1− represents the duration of the process, which is 
going to be repeated period after period; X is the set of exogenous variables, 
and Y is the set of endogenous variables. the shaded area indicates the 
underlying mechanism by which X and Y are connected. What happens 
inside the process is not observable, as indicated by the shaded area in 
the figure. If it were, the interior of the process would be considered as 
another process in itself, with other endogenous and exogenous variables 
and other mechanism; the latter mechanism would also be observable and 
then constitute another process, and so on. thus, we would arrive at the 
logical problem of an infinite regress. We may avoid this trap by making 
assumptions about the mechanism and maintaining it fixed. Ultimately, 
SCIeNCe IS epISteMOLOGY 11
there must be something hidden beneath the things we observe. Science 
seeks to unravel those underlying elements.
the scientific theory must also include assumptions about how the 
abstract process operates. the social relations taking place within the 
mechanism constitute the structural relations. these social interactions 
must have a solution, which will be repeated period after period. Call this 
solution the equilibrium conditions. the outcome of the abstract process 
showing the relations between endogenous and exogenous variables—
more precisely, the endogenous variables as a function of the exogenous 
variables alone—constitutes the reduced form relations.
the reduced form relations may be represented as the following equa-
tion: Y = F X( ) , where Y and X are vectors. In this equation, the exog-
enous variables X are the ultimate factors in the abstract process that 
determine the values of the endogenous variables Y, after all internal rela-
tions or structural relations have been taken into account. the structural 
equations show only the proximate factors that affect the endogenous vari-
ables Y. Moreover, according to the reduced form equation, changes in 
the exogenous variables will cause changes in the endogenous variables. 
therefore, the reduced form equations may be called the causality rela-
tions of the scientific theory.
the rules of scientific research that are logically derived from Georgescu- 
roegen’s epistemology include:
 1. Construct an abstract process to represent the complex social world 
with the help of a scientific theory;
 2. Select a particular type of abstract process according to the nature of 
the process repetition (static, dynamic, or evolutionary, to be shown in 
Chap. 3);
 3. Submit the reduced form equation of the scientific theory to empirical 
test.
Fig. 1.1 Diagrammatic representation of an abstract process
12 a. FIGUerOa
http://dx.doi.org/10.1007/978-3-319-30542-4_3
combining The Two episTemologies inTo one
Comparing the set of assumptions of popper’s epistemology and Georgescu-
roegen’s epistemology, we can see that they do not contradict each other; 
thus, they are complementary and can be combined into a single epistemol-
ogy. Call this combination the composite epistemology. to the need of scien-
tific theory and the principle of falsification of popperian epistemology, the 
process epistemology adds the principle of abstraction, the need of scientific 
theory for the particular purpose of reducing the complex real world into a 
simpler, abstract world so as to be understood in terms of endogenous and 
exogenous variables, and underlying mechanisms; moreover, whether the 
abstract world is a good approximation to the real complex world is resolved 
by using the falsification principle.
therefore, the composite epistemology assumes the following:
We can explain and understand a complex real world if, and only if, it is 
reducible to a simpler and abstract world in the form of an abstract process, 
by means of a scientific theory, which is also falsifiable; such scientific theory 
exists and can be discovered.
Comparing the rules that were derived from Georgescu-roegen’s epis-
temology with those that were from popperian epistemology (presented 
in table 1.2), we can see that rule (1) and rule (a) are consistent with each 
other. Scientific theory is needed to understand the real world in both 
epistemologies. however, process epistemology is more precise in that the 
role of the scientific theory is clearly established: the set of assumptions by 
which a complex real social world is transformed into an abstract process. 
rule (2) is absent in popperian epistemology, but it does not contradict it. 
Falsification as the demarcation principle, rules (b) and (c), are absent in 
process epistemology, but they can be introduced into rule (3) of process 
epistemology, as they complement each other.
It is clear that both epistemologies are complementary, for the two sets 
of assumptions do not contradict each other; thus, they can be seen as a 
single logical system, from which a single set of rules for scientific research 
can be derived. this set of rules are obtained just by consolidating the 
comparisons made above. the derived rules are the following:
 1. Construct an abstract process to represent the complex social world by 
means of a scientific theory;
SCIeNCe IS epISteMOLOGY 13
 2. Select a particular type of abstract process according to the nature of 
the process repetition (static, dynamic, or evolutionary, to be shown in 
Chap. 3);
 3. Submit the scientific theory to the falsification process.
It should be clear that the composite epistemology is also logically con-
sistent with the assumptions of the meta-theory B, which was presented in 
table 1.1. the reason is that each epistemology taken separately complies 
withthat consistency, as was proven earlier, and that the assumptions of 
the composite epistemology are just the elementary aggregation of the 
assumptions of both epistemologies, for they are complementary.
It should be noted that the composite epistemology is now applicable 
to complex realities, such as those studied by economics and the social sci-
ences in general. We have given popper’s epistemology the needed logic to 
be applicable to complex realities by adding the principles of Georgescu- 
roegen’s epistemology. this is the most significant finding of this chapter. 
however, the derived set of research rules are still too general. In order 
to make them operational, a set of more specific research rules will have 
to be developed. this calls for a scientific research method, containing the 
rules logically derived from the composite epistemology in a more practi-
cal way, which will be called the alpha-beta method. this is the subject of 
the next chapter.
14 a. FIGUerOa
http://dx.doi.org/10.1007/978-3-319-30542-4_3
15© The Editor(s) (if applicable) and The Author(s) 2016
A. Figueroa, Rules for Scientific Research in Economics, 
DOI 10.1007/978-3-319-30542-4_2
Chapter 2
Abstract In this chapter, a set of rules for scientific research, which is called 
the alpha-beta method, is logically derived from the composite epistemol-
ogy. this method makes the composite epistemology operational. alpha 
propositions constitute the primary set of assumptions of an economic the-
ory, by which the complex real world is transformed into a simple, abstract 
world; beta propositions are logically derived from alpha and are, by con-
struction, empirically falsifiable. alpha propositions are unobservable but 
beta are observable. thus, the economic theory is falsifiable through beta 
propositions. Beta propositions also show the causality relations implied by 
the theory: the effect of exogenous variables upon endogenous variables. 
the principles of the alpha-beta method will constitute the rules for scien-
tific research in economics in later chapters.
the highly complex social world will be subject to scientific knowledge if, 
firstly, it is reducible to an abstract process, as indicated by the Georgescu- 
roegen’s epistemology; secondly, if the scientific theory is falsifiable, which 
comes from popperian epistemology. as shown in the previous chapter, 
both epistemologies are not contradictory and can be combined into a 
single epistemology. to make this composite epistemology operational, 
this chapter derives a particular research method, containing a practical set 
of rules for scientific research, which is called the alpha-beta method.
the debate about the applicability of popperian epistemology in 
economics is that economic theories “are rarely falsifiable,” as shown in 
alpha-Beta: a Scientific research Method
the preface. We need a method to deal with the problem of falsification in 
economics. the objective of the alpha-beta method is precisely to ensure 
that economic theories are constructed in such a way that they are always 
falsifiable. therefore, the alpha-beta method is not just another name for 
a known research method; it is truly a new scientific research method, the 
application of which should contribute to the growth of the science of 
economics.
The AlphA And BeTA proposiTions
It will help to introduce the following concept, in which Georgescu- 
roegen presents the structure of scientific knowledge as a logically ordered 
system, as follows:
In terms of the logical ordering of its propositions, any particular field of 
knowledge can be separated into two classes: alpha and beta, such that 
every beta proposition follows logically from …alpha propositions and no 
alpha proposition follows from some other alpha propositions. (Georgescu- 
roegen 1971, p. 26)
the task before us is to apply this definition to the composite epistemol-
ogy and particularly to make it consistent with the principle of falsification.
Let alpha propositions constitute the foundation or primary assump-
tions of the scientific theory and beta propositions the empirical predic-
tions of the theory. the assumptions of a theory seek to construct an 
abstract world to make the complex world understandable. Because the 
social world is too complex to understand, abstraction must be applied, 
which implies ignoring the variables that are supposedly unessential and 
retaining only those that are supposedly essential. this is the role of a 
scientific theory. hence, the objective of the theory is to construct an 
abstract world that resembles best the real complex world. this is consis-
tent with Georgescu-roegen’s epistemology.
What are the logical requirements for a proposition to be considered 
an alpha proposition?
Looking back to the abstract process diagram (Fig. 1.1, Chap. 1), it was 
clear that there were observable and unobservable elements. the alpha 
propositions refer to the first and beta propositions to the latter. alpha 
propositions are the assumptions of the scientific theory and must deal 
with the mechanisms or forces that connect the endogenous and exogenous 
16 a. FIGueroa
variables. therefore, alpha propositions refer to the set of assumptions 
about the underlying factors operating in the relationships between the 
endogenous and the exogenous variables. alpha propositions are unob-
servable, but they must be non-tautological because they need to generate 
beta propositions, which should be observable and falsifiable. the set of 
alpha propositions must constitute a logical system, free of internal con-
tradictions. this is just the definition of scientific theory presented earlier. 
hence, a scientific theory is a set of alpha propositions.
Can the assumptions of a scientific theory be logically derived from 
empirical observation? No, they cannot. the main reason is that the the-
ory precisely seeks to explain those observations, so it cannot assume what 
it intends to explain. alpha propositions intend to discover the essential 
factors that lie beneath the observed facts; therefore, the mechanisms 
contained in alpha propositions are unobservable. What we can get from 
reality by empirical observation is a description of it, not an abstraction. 
the listing of all elements one observes in the real world cannot discover 
by itself the essential and nonessential variables. as will be demonstrated 
later on (Chap. 7), there is no logical route from empirical observations 
to scientific theory.
how are then the assumptions of a scientific theory chosen? Not by 
empirical observations. Do these assumptions need justification? No, they 
do not. the assumptions are in the nature of axioms; they do not need 
logical justification. the reason has to do with logical arguments: If the set 
of assumptions needed justification, another set of assumptions to justify 
them would be needed, which in turn would need another set to justify 
the latter, and so on; hence, we would end up in the logical problem 
of infinite regress. the assumptions of a scientific theory are, to some 
extent, chosen arbitrarily. therefore, the need to test the theory becomes 
a requirement for scientific knowledge.
Beta propositions are derived from alpha propositions by logical deduc-
tion and make the theory comply with the testing requirement. Beta prop-
ositions are, by construction, observable and refutable because they refer 
to the relations between endogenous and exogenous variables, which are 
observable. then the logical relations between alpha and beta proposi-
tions are as follows:
 (a) If alpha is true, then beta must be true.
 (b) If beta is false, then alpha must be false.
 (c) If beta is true, then alpha is corroborated.
aLpha-Beta: a SCIeNtIFIC reSearCh MethoD 17
therefore, beta propositions are observable and refutable, and thus they 
can be utilized to falsify the theory. this is consistent with the popperian 
epistemology.
alpha propositions are chosen somewhat arbitrarily, assaid earlier. 
however, they are subject to some logical constraints: they must be unob-
servable and non-tautological. the condition of unobservable is required 
because alpha propositions refer to the underlying forces in the workings 
of the observed world. Furthermore, alpha propositions that are non- 
tautological will be able to generate beta propositions, which are both 
observable and refutable.
unfalsifiable propositions are unobservable or, if observable, they are 
tautologies in the sense given to this term in logic: propositions that are 
always true. as examples of propositions that are unfalsifiable, consider 
the following:
“Men die when God so wishes”
“If you have faith on this medicine, you will get well”
“It will rain or not rain here tomorrow”
the first example is unfalsifiable because God’s wishes are unobserv-
able; hence, a person is alive because God so wishes and when he dies 
it is just because God so wanted. the proposition will never fail. the 
second is also unfalsifiable because if the person complains that he is not 
getting well, he or she can be told, “You had no faith on this medicine.” 
this proposition will never fail because faith is unobservable. the third is 
tautological because it includes all possible outcomes. thus, tautological 
propositions are unfalsifiable, useless for scientific knowledge, for they can 
never fail.
Consider now the statement “people act according to their desires.” It is 
unobservable but tautological, and thus unfalsifiable. this statement will 
always be true because whatever people do will always reflect their desires; 
hence, it cannot be an alpha proposition and no beta proposition can be 
derived from it. however, the statement “people act guided by the moti-
vation of egoism” (not of altruism) is unobservable and non- tautological, 
and thus qualifies to be an alpha proposition. a beta proposition can logi-
cally be derived from it. For example, selfish motivations imply free-riding 
behavior toward public goods; therefore, people will be forced (through 
taxes) to produce public goods (parks and bridges). this empirical propo-
sition could in principle be false; thus, it is a beta proposition.
18 a. FIGueroa
take note that beta propositions are observable and refutable, even 
though they are derived from alpha propositions, which are unobservable. 
this paradox is apparent because alpha propositions are free from tautolo-
gies; moreover, alpha propositions assume the endogenous variables (Y) 
and exogenous variables (X) of the abstract process, which are observable, 
and beta propositions refer to the empirical relations between X and Y. If 
beta propositions cannot be derived from a theory, this “theory” is actu-
ally not a theory; it is a tautology, useless for scientific knowledge. to take 
the example shown above: the statement “people act according to their 
desires” is not an alpha proposition, for no beta proposition can be logi-
cally derived from it. It follows that the alpha-beta method eliminates any 
possibility of protecting scientific theories from elimination because beta 
propositions are falsifiable. this is so by logical construction.
although subject to some logical constraints, the set of alpha proposi-
tions is established somewhat arbitrarily. however, this presents no major 
problem for falsification because the theory is not given forever. on the 
contrary, a theory is initially established as part of an algorithm, of a trial-
and- error process, the aim of which is to reach a valid theory by eliminat-
ing the false ones. If the initial theory fails, a new set of assumptions is 
established to form a new theory, and a new abstract world is thus con-
structed. If this second abstract world does not resemble well the real 
world, the theory fails and is abandoned, and a new set of assumptions 
is established, and so on. a valid or good theory is the one that has con-
structed a simple abstract world—in the form of abstract process—that 
resembles well the complex real world.
under the alpha-beta method, the valid theory is found by a trial-and- 
error process, in which we assist to the funerals of some theories. the beta 
propositions derived logically from the alpha propositions are observable, 
falsifiable, and mortal. this is consistent with the Darwinian evolutionary 
principle of scientific progress. hence, what the set of assumptions of a 
theory needs is not justification; what it needs is empirical falsification, 
testing it against the facts of the real world using the beta propositions.
Beta propositions thus have the following properties:
•	 Beta propositions show the falsifiable empirical predictions of a sci-
entific theory. the reason is that beta propositions represent the 
reduced form relations of the abstract process: the relations between 
the exogenous and endogenous variables that the theory assumes. 
hence, beta propositions are logically derived from the theory and 
aLpha-Beta: a SCIeNtIFIC reSearCh MethoD 19
are observable and refutable; if beta propositions are not consistent 
with facts, then the theory fails and is rejected; if the beta propositions 
are consistent with facts, then the theory is accepted.
•	 Beta propositions also predict causality relations: changes in the 
exogenous variables (X) will cause changes upon the endogenous 
variables (Y), which again are observable and falsifiable, that is, 
Y = F X( ) , from the process diagram (Fig. 1.1, Chap. 1). therefore, 
causality requires a theory, that is, no theory, no causality.
Because beta propositions indicate causality relations, for each endog-
enous variable of the theory there will exist a causality relationship; hence, 
there will be as many causality relations or beta propositions as there are 
endogenous variables (variables the theory seeks to explain) in the theo-
retical system.
according to the alpha-beta method, if the abstract world constructed 
by the theory is a good approximation of the real world, we should 
observe in the real world what the beta propositions say. although a beta 
proposition is logically correct—it is the reduced form equation of the 
theoretical system—it may be empirically false. the reason is that the set 
of assumptions contained in the alpha propositions was selected somewhat 
arbitrarily. Falsification of a scientific theory is thus a logical necessity.
In order to illustrate the principle that logically correct propositions may 
be empirically false, consider the following syllogism:
all men are immortal
Socrates is a man
then, Socrates is immortal
the conclusion follows logically from the premises, but it is empirically 
false. the reason falls upon the first premise, which is empirically false. In 
the alpha-beta method, by contrast, the premises (the assumptions) are 
unobservable and they may be false in the sense that the underlying forces 
of the workings of the real world are not those assumed by the theory; 
then the logically correct proposition may be empirically false. Consider 
the following example:
Capitalist firms seek to maximize employment
Workers seeking jobs are fixed in number
then, the capitalist system operates with full employment
20 a. FIGueroa
In this case, the conclusion follows logically from the premises, but it is 
empirically false. Capitalism is characterized by the existence of unemploy-
ment. the reason for failure falls upon the premises, particularly, on the 
assumption about the motivation of capitalists, which is proved wrong: 
capitalists do not seek to maximize employment (but, say, seek to maximize 
profits).
a theory will fail because the abstract world is not a good approxima-
tion of the real world; it has made the wrong assumptions about what the 
essential factors of the economic process are. If, in spite of the abstraction, 
the so-constructed simple abstract world resembles well the complex real 
world, the theory constitutes a good approximation to the real world. the 
abstract world resembles thereal world; accordingly, we say the theory 
explains the reality. then this is a valid theory.
to be sure, in the alpha-beta method, submitting a theory to the pro-
cess of falsification has the following logic. Because the theory is in prin-
ciple false (it is an abstraction of the real world!), it must be proven that it 
is not false. If the theory were in principle true, there would be no need 
to prove that it is, or the proof would be discretionary. By comparison 
with the judiciary court, in which the individual is in principle innocent 
of a crime (legal rights) and it must be proven that he or she is guilty, the 
falsification principle says that the individual, the theory in this case, is in 
principle guilty, and must be proven that it is not. therefore, if the theory 
is found true, in spite of the expectation that it was false, then the theory is 
a good one. the concept of falsification is also similar to the concept that 
an honest person is one who having had the opportunity of committing 
a crime did not do it, but whether the person never had had the chance, 
we cannot say.
From the example of the theory “Figure F is a square,” shown earlier, 
it is clear that falsification through beta propositions implies that the alpha 
proposition cannot be proven true; it can only be proven false. Why? this is 
so because the same beta propositions could be derived from another set of 
alpha propositions. It may be the case that there is no one-to-one relation 
between alpha propositions and beta propositions. alpha implies beta, but 
beta may not imply alpha. If the Figure F is a square, then it follows that 
the two diagonals must be equal. however, if the two diagonals are equal, 
it does not follow that Figure F is a square; it could be a rectangle.
this simple example shows another property of the alpha-beta method. 
If all beta propositions of the theory coincide with reality, the theory is 
not refuted by the available facts; if at least one beta proposition fails, the 
aLpha-Beta: a SCIeNtIFIC reSearCh MethoD 21
theory fails to explain the reality. If the two diagonals are not equal, it follows 
that the theory fails: Figure F cannot be a square.
Consider the case in which there is a one-to-one relation between alpha 
and beta propositions. Let the theory say, “people seek to kill their credi-
tors when repayment is unviable.” Individual B is suspected of individual 
C’s death because B was debtor of C. Suppose only one fingerprint was 
found in the scenery of the crime. If the fingerprint is that of B, then he is 
the killer; if it is not, then he is not the killer. this is so because fingerprints 
are personal. the same conclusion would follow with DNa tests. In the 
previous example, the fact of equality of diagonals does not belong to the 
square figure only. In social sciences, we deal with aggregates; therefore, 
there cannot be a kind of “fingerprints” variables from which to draw 
definite conclusions as in the case of the people, and the relevant example 
is that of the “Figure F is a square” theory.
Logically, therefore, scientific theories in the social science cannot be 
proven true; they can only be corroborated. to be sure, here “corrobo-
ration” means consistency, not truth. It also means to assess how far the 
theory has been able to prove its fitness to survive by standing up to tests. 
how many wars has the theory survived? how far has the theory been 
corroborated?
In sum, scientific theory is a logical artifice to attain scientific knowl-
edge. a scientific theory allows us to construct an abstract world that 
intends to resemble well the complex real world. If there is no theory, 
there is no possibility of scientific knowledge. however, how accurate 
is the approximation of the theory to the real world? the theory needs 
empirical confrontation against reality. the prior set of assumptions needs 
posterior empirical falsification. the reason behind falsification is that the 
assumptions of the scientific theory were established arbitrarily (for there 
is no other way). If in this confrontation theory and reality are inconsis-
tent, theory fails, not reality; that is, the arbitrary selection of its assump-
tions is proved wrong.
the rules for scientific research in economics derived from the compos-
ite epistemology, shown in Chap. 1, can now be restated in terms of the 
alpha-beta method, as follows:
 1. the rule that scientific theory is needed for explaining a complex real 
world is given by constructing the set of alpha propositions.
 2. the rule that falsification is the criterion of demarcation is given by the 
beta propositions, derived logically from the set of alpha propositions. 
22 a. FIGueroa
the rule of rejection-acceptance of a scientific theory is given by the 
iterations of alpha-beta propositions, eliminating false theories until 
the valid one is found.
 3. the use of abstraction implies that the beta propositions need not fit all 
empirical cases, as there will be exceptions; hence, falsification requires 
statistical testing. the alpha-beta method as an algorithm is shown in 
table 2.1 above.
therefore, the alpha-beta method constitutes a logic system to construct 
scientific theories of complex realities and submit those theories to the 
process of falsification. this is a scientific research method.
The Workings of The AlphA-BeTA MeThod
according to the alpha-beta method, alpha propositions are not observ-
able and thus cannot directly be subject to empirical refutation; however, 
it can indirectly, through beta propositions. the beta propositions are uti-
lized to seek refutation of the alpha propositions, which make assumptions 
to transform the complex real world into a simpler, abstract world. the 
principle of abstraction is contained in the alpha propositions. Logically, 
therefore, a beta proposition can fit only the general or typical cases of the 
real world. Due to the use of abstraction, it may not fit all the observed 
cases and exceptions may exist. therefore, the refutation of a theory needs 
to be based on statistical testing; the relationships between the average 
values of the endogenous and exogenous variables are the critical ones. 
this is another scientific rule of the alpha-beta method.
a single empirical observation that contradicts a beta proposition is 
insufficient to refute the theory, for the statistical value of one observation 
is nil. that observation could just correspond to a statistical error, a devia-
tion from the average by pure chance. By comparison, a single counter- 
example is sufficient to invalidate a theorem in mathematics, but it is not 
Table 2.1 the alpha-beta method
α β β1 1 1⇒ → ≈[ ]b
 If β1 = b, α1 is consistent with facts and explains reality
 If β1 ≠ b, α1 does not explain reality and is refuted by facts. then,
α β β2 2 2 b⇒ → ≈[ ]
 If … (the algorithm is continued)
aLpha-Beta: a SCIeNtIFIC reSearCh MethoD 23
sufficient to refute a scientific theory. the empirical proposition “smoking 
causes cancer” cannot be refuted by finding someone that smokes but has 
no cancer, as this individual can be the exception. accordingly, a distinc-
tion must be made between error of a theory and failure of a theory.
the continuous confrontation between theory and empirical data is 
the basic property of the alpha-beta method. From funeral to funeral of 
theories (false theories are eliminated and good theories take their place), 
science makes progress.
table 2.1 depicts the scientific research rules of the alpha-beta method. 
From the set of alpha propositions α1, the set of beta propositions β1 is 
logically derived (indicated by the double arrow). the set β1 must then 
be subject to the operational procedure of statistical testing (indicated by 
the single arrow). While the double arrow indicates logical deduction, the 
single arrow indicates operational procedure, or the task to be performed. 
Statistical testing of the theory implies seeking a statistical conformitybetween beta propositions and the available set of statistical associations 
between endogenous and exogenous variables, the set b. this search for sta-
tistical conformity is indicated by the double-swung dash symbol ≈( ) , which 
means investigating for “approximately equal to.” If statistically (not 
mathematically) β1 = b , then α1 is consistent with reality, facts do not 
refute the theory; therefore, there is no reason to reject the theory at 
this stage of the research, so we may accept it, although provisionally, 
until new empirical evidence or new theories appear. If β1 ≠ b , then real-
ity refutes the theory α1, and another theory α2 should be developed; thus 
the algorithm is continued.
It should be noted that in the alpha-beta method facts can refute a 
theory, but facts cannot verify a theory. the opposite of the conclusion 
“the theory is false” is not the “theory is true,” but “the theory is con-
sistent with facts.” When facts have not been able to refute the theory, 
we say that “the theory is consistent with facts” or “the theory has been 
corroborated”, and we accept the theory provisionally, until new superior 
theory or new empirical facts appear.
as in the case of the social world, the biological world may also be con-
sidered as a highly complex reality. Indeed, human societies are biological 
species. hence, the alpha-beta method is also applicable to biology.
an example of application of the alpha-beta method to biology is the 
following:
α plants seek to maximize the reception of solar energy.
24 a. FIGueroa
β then, plants will position their leaves in a particular distribution so 
as to maximize exposure to sun: each leave collects its share of sun 
interfering the least with other leaves.
b We observe that tree leaves form a canopy, a near-continuous ceiling.
then, b = β . We can conclude that α is a valid scientific theory that explains 
plant behavior.
the alpha proposition is the scientific theory. It is an assumption about 
the underlying forces operating in the functioning of the real world; thus, 
it is unobservable and non-tautological. the beta proposition is derived by 
deductive logic from the alpha. the term b indicates the statement about 
facts. the last row indicates that because beta proposition and b coincide, 
the assumption of the theory cannot be rejected; fact b does not refute the 
theory. (If the leaves distribution of trees had shown no canopies, then the 
theory would have failed.) therefore, the theory explains the behavior of 
plants and why the leaves of trees form canopies, that is, the why-question 
is answered.
as this elementary biological example illustrates, a scientific theory is 
unobservable and is submitted to the refutation process indirectly, through 
its beta propositions. For one thing, in this case it is unviable to do the 
direct refutation of a theory by asking the trees what their motivations 
are; it is also unnecessary. It is a principle of the alpha-beta method that 
unobservable propositions can be transformed into observable ones—a 
scientific theory as set of alpha propositions can be transformed into beta 
propositions. a good scientific theory has empirical implications over the 
real world, which can be tested against facts. the theory is tested indirectly.
In the social sciences, the same principle of the alpha-beta method 
applies. even though, in contrast with plants, we may ask people about 
their motivation, it is unviable and unnecessary for falsification. It is unvi-
able because beta propositions refer to observable propositions, to human 
behavior, to what people do—not to what people say what they do. It is 
unnecessary because we can make assumptions on the people’s motiva-
tions (the alpha proposition, unobservable), which can be transformed into 
an observable proposition, which can then be confronted against facts. If 
facts refute the beta proposition, we know that the alpha proposition (the 
theory) is false. If they coincide, the theory is consistent with facts and then 
we may accept it provisionally. Whatever people’s real motivations are, it is 
equivalent to what the corroborated theory says.
aLpha-Beta: a SCIeNtIFIC reSearCh MethoD 25
If the theory is accepted, it follows that its assumption on motivations is 
a good approximation of what the real motivations of individuals are; it is as 
if, people did what the alpha propositions say. If the scientific theory fails, 
people act guided by motivations other than those established by the alpha 
proposition. therefore, people’s motivations, the forces underlying their 
behavior, can be discovered through the alpha-beta method. to know these 
motivations by asking people directly is unnecessary and, more importantly, 
insecure. people know to lie and they may decide to lie because they feel 
embarrassed to confess their true motivations (say, seek money above all).
It should also be noted that failure of a single beta proposition is suf-
ficient for refuting a scientific theory. therefore, a theory is valid if, and 
only if, none of its beta propositions fails. table 2.2 illustrates this prop-
erty of the alpha-beta method. Let the scientific theory have two endog-
enous variables (Y1 and Y2) and three exogenous variables (X1, X2, and X3). 
then the beta propositions can be represented in matrix form. the effect 
of changes in the exogenous variables upon Y1 is given by the first row of 
the table: the effects are positive, positive, and undetermined; similarly, 
the signs of the second row indicate the effect of changes in the exogenous 
variables upon Y2: negative, no-effect or neutral, and positive.
the two endogenous variables of the theory give rise to two beta prop-
ositions, one for each endogenous variable. each row of the matrix shows 
the corresponding beta proposition. thus, we can write
proposition beta 1 
+ +
= ( )
?
Y , ,1 1 2 3F X X X
proposition beta 2 
− +
= ( )
0
Y , ,2 1 2 3G X X X
the relation between each endogenous variable and the exogenous 
variables is represented by functions F and G. the signs on top of each 
exogenous variable indicate the direction of the effect of changes in the 
exogenous variables upon changes in each endogenous variable.
Endogenous 
variables
Exogenous variables
X1 X2 X3
Y1 + + ?
Y2 − 0 +
Table 2.2 Matrix of beta 
propositions or matrix of 
causality
26 a. FIGueroa
the matrix shown in table 2.2 may also be called the causality matrix. 
thus, an increase in the exogenous variable X1, maintaining fixed the 
values of the other two exogenous variables (X2 and X3), will cause an 
increase in the value of the endogenous variable Y1 and a fall in Y2. hence, 
the functions F and G show the causality relations of the theory. these are 
the reduced form equations of the scientific theory.
Falsification can now be analytically defined as follows: a theory fails 
if one of the signs of the matrix is different from the sign of the observed 
statistical associations between the corresponding variables. this is a suf-
ficient condition to have a theory refuted by facts. It should be clear that 
the cell in which the effect is undetermined cannot be used to refute the 
theory.
In the case of falsifying several theories at the same time, given data set 
b, some theories will be false and some will be consistent. those theories 
that survive the entire process of falsification will become the corroborated 
theories (not the verified or true theories), whereas the theories that fail 
are eliminated. the corroborated theory will reign until new information, 
new statistical testing methods, or a new superior theory appears. a theory 
is superior to the others if it derives the same beta propositions as the oth-
ers, but in addition derives other beta propositions that are consistent with 
facts, which the other theories cannot. a theory is thus superior to others 
when it can explain the same facts that the others can and some additional 
facts that the others cannot.
From the