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"There is nothing as practical as a relevant theory"


Some definitions

A decision analysis model: a decision analysis model relates the known determinants of an outcome (result) in functional terms. Therefore by making assumptions on the state of determinants different outcomes can be quantified. Similarly by specifying desired outcomes the values of determinants that can achieve such an outcome can be calculated.

At the macroeconomic level there is a need to identify the motivation for some policy such as lack of food production or inadequate employment levels. This leads to the definition of an overall strategy, for example to increase food production or increase employment levels.

Most decision analysis models supporting policy analysis are concerned with evaluating the tactics identified to delivery specific objectives so as to identify the most appropriate in terms of defined preferences such as minimization of costs.

In this situation reference is made to policy instruments. These are the specific levers that influence the state of the of desired goals that are described in terms of policy targets. In broad terms policy instruments can be divided into four subsets:
a) Monetary policy
b) Fiscal policy
c) Real incomes policy
d) Constitutional economic policy
e) Policies incorporating the minority constitutional principle

Economic performance models

Why are models a useful discipline?

Economic policy models have an important role in evaluating economic theory and practice by:
  • forcing economists and analysts to expose how they think the economy works and to evaluate assumptions by comparing model predictions with actual outcomes
  • providing a means of refining models on the basis of the decision analysis cycle so as to improve knowledge of determinant relationships, event and process probabilities and to assess the quality of models based on existing information so as to identify additional information needs
  • enabling comparative analysis of sensitivities of economic and social constituency outcomes to possible conditions
  • preventing serious economic prejudice arising from policies based upon unrealistic assumptions and models
This page might appear to be out of place in a website dedicated to an object orientated scripting in the form of server side ECMAScript. However, this topic is important because it presents a challenge in demonstrating the value of computer based decision analysis models in supporting decision making throughout the policy decision analysis cycle. So it is a test of what scripting can bring to this important topic that affects all of us.

OOP was first identified in the early 1960s, as a way to describe heterogeneity and to simulate reality1;OOP is a way of "scripting reality". It is therefore a sound basis for creating realistic decision analysis models to simulate options and select preferable ways to secure objectives. The means of securing objectives can be through macroeconomic policy, a corporate strategy or even a specific project. A project being defined as an activity that uses material, human and financial resources to achieve a predefined objective.

4P-Policy Procedures Prototyping Platform

Policy assessment consists of defining the procedural package made up of:

  • Name of procedure
  • The name of the methods applied
  • The analytical formulae used
  • The core data set required to complete the procedure

This procedural package is in fact a DRM (Data Reference Model)2 and the DRM is all that is needed to specify a policy procedure. In terms of OOP, each DRM is in reality an object with a name (the object), properties (the data) and operational analyses (methods).

The Policy Procedure Prototyping Platform (4P) is an instructional simulator that I developed using DScript3 making us of the tools and language introduced by Vanguard, around 2003, as part of the new Vanguard System Integrated Development Environment, but directed to the evaluation of policy procedures. The benefits are that this model can accommodate the simplest arithmetic models through to the most complex operations research methods.

I first applied this modeling approach in 2000, in Hungary as an online demonstration system  (AFA_Agronet) for regional and farm planning making use of data similar to the EU Farm Accountancy Data Network (FADN) . This was before Hungary had an FADN system and this prototype was operational between 2000 to 2009.

It was then used to validate Price Performance Policy, a comprehensive macroeconomic policy proposal based on the Real Incomes Approach to economics.

In 2010 I was involved in the development of an Agricultural Information Systems strategy in Bosnia & Herzegovina. However, I noticed that, like previous experience in Hungary, the national authorities were over-emphasizing EU compliance somewhat at the expense of national policy. This was because of the limited number of Ministry staff available to undertake serious national policy decisions analysis. This EU emphasis led to a weakening of ongoing national policy, creating political problems for the Ministry of Agriculture in Hungary in 2002 and 2003 with the farming community before accession in 2004.

With a weaker agricultural sector, but with good potential, Bosnia was likely to face worse issues, largely because of a highly contentious political environment that resisted "Federal policy", including agriculture, involving non-collaboration justified on the basis of assertion rather than evidence-based considerations with respect to policy decision-making. This convinced me of the need for a robust means to demonstrate in a practical and transparent fashion the relative merits of policy options. This is why I developed 4P4 as a policy procedure prototyper and instructional simulator. Besides providing a basis for designing and testing policies, this can provide evidence to justify policy decisions. The transparency of the system makes it a practical basis for the training of business and ministry management, policy analysts and strategists. It is an ideal learning-by-doing tool that is accessible online, at any time, by trainees.

4P has been used to support decision analysis training have delivered on how to program using DScript and to demonstrate the application of Monte Carlo simulation for industrial extension training staff in industry-supported research and extension services in the UK (2012).

Hector McNeill

1  Object Oriented Logic (OOL) was developed as a way to program computers with a programming logic known as object oriented programming (OOP). This was first developed in the 1960s by Kristen Nygaard and Ole-Johan and who until their deaths worked at the Department of Informatics at the University of Oslo, Norway. Their objective was to address the problem of simulating reality when reality is characterized by heterogeneity. In agriculture, one of the most complex heterogeneous systems in the economy, the best approach to the identification of essential data for policy making is to deploy OOL. This is a rational approach since the relationships between critical variable elements of OOL is Boolean Logic which is the mathematical logic of how humans analyse and deduce. This is based on known cause and effect relationships, recent experience and access to information and our view of the probabilities of events. These are the basic factors deployed in human decision analysis.
OOL provides a transparent arrangement of all relevant data to identifying all of the agricultural factors, or objects, that make up agricultural processes and the measured properties (variables) of interest as well as determinant methods describing how the objects act upon the variables.
2 DRM-Data Reference Model is am emerging standard of OQSI (Open Quality Standards Initiative).
3 ® DScript is a registered trademark of Vanguard Software Corporation.
4  4P has been submitted to OQSI for consideration as a standard.


The Decision Analysis Initiative 2010-2015
George Boole Foundation