FACULTAD DE CIENCIAS ECONÓMICAS Y EMPRESARIALES

20

Introduction

This paper makes several observations and 
recommendations pertaining to economic modelling. 
Based on a careful study of the total of 1775 research 
papers published in the journal of economic modelling 
(JEM) Journal between 1984 and 2012, it presents the 
percentages of papers published in individual categories 
of economic modelling identified. Second, based on 
an observation of the common approaches used in 
economic modelling papers in the past 28 years in JEM, 
this paper recommends multidisciplinary approach 
to economic modelling. It suggests the incorporation 
of multidisciplinary, non-economic variables in 
economic modeling to formulate strong policies. Third, 
in connection with the multidisciplinary approach, 
it proposes the application of the ‘Omnia Mobilis’ 
assumption (Ruiz Estrada, 2011) to economic modeling. 
Under this assumption (‘everything is moving’), a good 
range of variables should be included and no relevant 
variables should be neglected in economic modelling. 

Moreover, it is obvious that the use of more economic 
practical approaches could facilitate the explanation 
of a dynamic and complex economic and social 
phenomenon. The main idea behind the use of practical 
economic approaches is to find suitable and applicable 
models that can help to reduce the negative impact of 
any economic and social problem(s) in the society by the 
most efficient and realistic way. In the 21th century the use 
and application of economic modelling among economists 
were often based on sophisticated mathematical and 
statistical techniques, methods and models introduced 
during the development of new economic models. In 
particular, calculus, trigonometry, geometry and statistical 
and forecasting methods were employed by economists 
in policy modeling. Consequently, the application of 
sophisticated mathematical and statistical techniques, 
methods, and models can be seen in the development 
of the following economic models: The Foundations of 
Economics Analysis (Samuelson, 1947), Monetary Theory 
and Fiscal policy (Hansen, 1949), Econometric Models 
and the Evidence of Times Series Analysis (Klein, 1956), A 
Contribution to the Theory of Economic Growth (Solow, 
1956), Economic Policy: Principles and Design (Tinbergen, 
1956), The Input–Output Economics (Leontief, 1966).

In fact, the rapid development of economic modelling has 
been facilitated by high technology and sophisticated 
analytical instruments such as the electronic calculator and 
the computer. The development of analysis instruments in 
economics took place in two stages. The first stage involved 

“basic computational tools”, where electronic calculators 
were used to compute basic mathematical expressions 
(e.g. long arithmetic operations, logarithm, exponents and 
squares). 

This took place between the 1940s and 1960s. The second 
stage which involved “advance computational tools” began 
in the middle of the 1990s up to the present day. This marks 
the era when high speed and efficient storage-capacity 
computers that are installed with sophisticated software 
were introduced for the first time. The use of sophisticated 
software enables easy information management, 
application of difficult simulations as well as the creation of 
high resolution graphs. Obviously, the analysis instruments 
contributed substantially to the development and research 
in economics.

Over the years the high computational instruments backed 
by sophisticated software have been used to formulate 
large economic models which are largely beneficial for 
secondary data uses. Economic modelling approaches 
basically comprise of the descriptive economic modelling 
and analytical economic modelling, both of which can be 
categorized according to functions and database sizes. In 
terms of function, the two economic modeling approaches 
are either descriptive or analytical. The descriptive 
economic modelling on the one hand shows arbitrary 
information that is used to observe a long historical data 
behavior from a simple perspective. While analytical 
economic modelling on the other hand is used to generate 
time-series, cross-section modelling to show the trends 
and relationships between two or more variables from a 
dynamic perspective. The research leading to this paper 
shows a strong link between the introduction of new 
economic modelling and the development of theories, 
methods and techniques in statistics and mathematics. 
It is important to note the difference and similarity that 
exist between economic modelling and policy modeling 
(Ruiz Estrada and Yap, 2013). The main difference is 
based on the research focus and theoretical approaches 
applied to the analysis of different economic phenomena. 
In terms of similarity, both fields focus on the analysis of 
different economic phenomena to study the irrational 
and chaotic behaviors through time (history) and space 
(geographical). To study the difference and similarity that 
exists between economic modelling and policy modelling, 
the bibliographical references of two prestigious journals 
viz. the journal of policy modeling (Elsevier, 2012a) and 
the journal of economic modeling (Elsevier, 2012b) are 
employed.