Productive Resources

factors_of_productionProductive resources are the requirements for producing goods and services in an economy.  Often economists call these ‘factors of production’.   Usually these are represented as capital, labour and land.  Entrepreneurship is increasingly included as a fourth factor.

Capital usually comprises fixed capital such as structures, buildings, physical plant, machinery and tools.  Circulating capital is often described in terms of components and raw materials.

Labour includes all aspects of human resources and may be unskilled, semi-skilled or skilled.

Land comprises naturally occurring resources where supply is inherently fixed.  These resources may be renewable or non renewable.  Examples are geographic locations, mineral deposits, forests, fisheries, air quality, geostationary orbits and parts of the electromagnetic spectrum.

Entrepreneurship is often described as the capacity and willingness to develop, organise and manage a business venture along with any of its risks in order to make a profit.  It is often closely associated with starting new businesses.

How we define what we use to supply goods and services is critical to our understanding of the economy.  How can we test if the traditional  capital-labour-land approach is still valid?  How strong or significant is entrepreneurship in the mix?


This Micro Brief is part of an ongoing series provided as a general public information service.  These concepts underpin modern economic analysis.  Find out more about smarter capital investment decisions using economics at




Consumers are individuals who acquire goods or services for direct use or ownership, rather than for resale or use in production or manufacturing. This group is a critical element in an economy.

The needs and wants of consumers drive economic activity and direct the production and distribution of goods and services. Without them producers lack a key motivation to produce.

Consumers are said to be sovereign because they decide what bundles of goods and services they wish to purchase. However they value this consumption also in terms of quality and safety.

Many consumers are now shifting to becoming ‘prosumers’ – consumers that are also producers or influence the products and services being created by being directly involved in their production. This is especially the case for services delivered via the Internet – including information and media on the social web.

So are we seeing a new paradigm with ‘prosumers’ or just a blurring of boundaries as the same economic participants take on multiple roles in the economy?


This Micro Brief is part of an ongoing series provided by Lytton Advisory as a general public information service.  These concepts underpin modern economic analysis.  Find out more about smarter capital investment decisions using economics at

Cost Benefit Analysis Economics Lytton Advisory

Make the Casino Work for You

rouletteNothing is more hair raising than exposure to risk without a sense of the level of that exposure.  This is especially true in capital investment decisions.

Monte Carlo simulations perform risk analysis by building models of possible results by substituting a range of values—a probability distribution—for any factor that has inherent uncertainty and significant impact on the final result.

By using probability distributions, variables can have different probabilities of different outcomes occurring.  Probability distributions are a much more realistic way of describing uncertainty in variables of a risk analysis and improve the quality of sensitivity analysis.

During a Monte Carlo simulation, values are sampled at random from input probability distributions.  This is done hundreds or thousands of times, and results in a probability distribution of possible outcomes.  It provides a much more comprehensive view of what may happen.

Advantages over deterministic, or “single-point estimate” analysis include:

  • Probabilistic Results. Showing how likely each outcome is.
  • Clearer Graphical Results. Visual presentation of probabilities.
  • Improved Sensitivity Analysis. Sharper sensitivity analysis to show what counts.
  • Scenario Analysis: Model repeated variations in combinations of factors to show which scenarios need further investigation.
  • Correlation of Inputs. Represent how, in reality, when some factors goes up, others go up or down accordingly.

Done poorly or with low quality input data, the results can be potentially misleading – producing a level of certainty on the basis of some very uncertain assumptions.

Lytton Advisory holds an @Risk software licence which enable us to provide this type of probabilistic analysis to clients, helping them make better informed decisions. Examples of how we have applied this for clients include:

  • Estimating financial costs of schedule delay on a major metropolitan public transport project.
  • Assessing probability of breaching a cost contingency levels on a +$500 million infrastructure program.
  • Building probabilistic NPV profiles in cost benefit analyses given uncertainty about key economic inputs.

Contact us today to find out how we might be able to help you.