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2 Definitions and measurement

2.1 Definitions

Productivity is a measure of the degree of efficiency with which an organisation turns inputs, such as labour and capital, into outputs (eg consumer goods and services). Producing more goods and services with a fixed amount of inputs, producing the same quantity of goods and services with fewer inputs, or producing goods and services at a faster rate than the rate of increase in inputs, are all examples of rising productivity.

Productivity is typically defined as the ratio of a volume measure of output to a volume measure of input. Beyond this basic definition a range of issues arise. Productivity can be defined in relation to a single input (eg labour) or to a combination of inputs (eg, labour and capital). Labour productivity can change as a result of a change in technology or additional capital. As a result, a limitation of partial productivity measures, such as labour productivity, is that they attribute to one factor of production, in this case labour, changes in efficiency attributable to other factors of production.

Multifactor productivity (MFP) is the part of output growth that cannot be attributed to the growth of labour or capital inputs. MFP reflects such things as business process innovations, advances in disembodied technology, or almost any other type of improvement in the efficiency of a firm's operations. When MFP rises in an economy, then that economy can produce more output with the same quantity of labour and physical capital. MFP can be equated with technological change if certain conditions are met (eg firms seek to maximise profits, markets are competitive, and the coverage of inputs is complete). Because these conditions are typically not met, measured MFP will, in addition to technological change, include the effects of model misspecification and errors in the measurement of the variables.

2.2  Measurement and coverage

In addition to the definition of productivity, choices exist about coverage - whether we are assessing the performance of the total economy (ie economy-wide), groupings of industries into particular sectors (eg market), or individual industries. Strengths of economy-wide measures of productivity include consistency with real GDP (and therefore the well established National Accounting procedures for that aggregate), real GDP per capita, and forecasts of these variables. Furthermore, they allow for economy-wide growth accounting analysis of GDP and GDP per capita. Economy-wide measures are generally better suited to international comparisons, because the definition of the measured sector is not uniform across countries and official measured sector series are only available for a limited number of countries (eg, Australia, New Zealand, Canada, the Netherlands, Switzerland, and the United States).[5] Economy-wide measures are also typically more up to date, being quarterly and sourced from current series, and provide information on productivity levels and not just growth rates.

However, the ability to gauge productivity varies across the economy. Measurement difficulties with regard to output are generally greater in the service industries, especially government activities in education, health, administration, and defence. Direct volume measures of output are often not obtainable, and so the widespread lack of market prices gives rise to difficulty for statisticians in measuring these services. Market prices also provide weighting information, in order to combine a range of outputs into a single aggregate. In their absence, cost weights are used internationally. Productivity statistics that cover the ‘business' or ‘market' sector are less prone to output measurement issues and are more closely related to the entities (ie, firms) that are seeking the best mix of resources to exploit market opportunities and earn profits. In addition, the existence of market prices provides a set of weights to add a range of individual outputs into a single aggregate output.

For any given productivity series there are also issues of interpretation across time, including the role of the business cycle, and possibly changes in the terms of trade. Because the New Zealand and Australian business cycles do not match, we focus here on long spans of data. The effects of changes in the terms of trade on measured productivity have been extensively canvassed in the Australian context (see, for example, Ewing, Fenner, Kennedy and Rahman, 2007; Dolman, 2009; Australian Productivity Commission, 2009).


  • [5]. See OECD (2008).
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