Using input-output for analysis - examples
The input-output multipliers provide a way of answering some of the questions often asked by economists and managers. These queries tend to arise because of the types of 'what if?' analysis for which input-output tables can be used (for example, what would be the impact on employment of an x per cent change in output by the chemicals manufacturing industry). This type of analysis is dependent on a knowledge of input-output multipliers and their shortcomings. Using input-output tables, multipliers can be calculated to provide a simple means of working out the flow-on effects of a change in output in an industry on one or more of imports, income, employment or output in individual industries or in total. The multipliers can show just the 'first-round' effects, or the aggregated effects once all secondary effects have flowed through the system.
The basic role of input-output analysis is to analyse the link between final demand and industrial output levels. The inverse table, total requirements coefficient in the national accounts context, could be used to assess the effects on the productive system of a given level of final demand. Employment implications are equally important in this respect. Input-output tables can also be used for analysing changes in prices stemming from changes in costs or from changes in taxes or subsidies.
Here are some practical examples to help illustrate the application of input-output tables. For instance, it is possible to estimate the levels of output of the production sectors required by a given final demand. The effect on other industries of an additional final output of $100 million of the rubber and plastics industry, or a 30 per cent change in exports of steel can be calculated by assuming that average and marginal utilisation rates are the same.
Another example of input-output application is assessing the benefits of a specific project to a regional economy. The analysis of the impact must be broken up into two stages. Firstly the construction phase and secondly the operational phase. Irrespective of which type of industry the project is in, both phases will utilise different input requirements and need to be analysed separately.
For example, the construction of a new motor vehicle plant will require inputs from industries such as; construction, building services, steel and machinery and equipment. The impact of the construction of a $150 million automobile plant on the economy may be $105 million once the direct and indirect benefits have flowed through the economy. That is, regional suppliers have provided this amount of inputs.
Once the plant is up and running it will be drawing on inputs from a diverse range of industries including; rubber and plastics, transport equipment, non-metallic minerals (glass etc.) and the fabricated metals industry. An estimated annual output of $100 million for the plant, may have additional benefit to the regional economy of $75 million. That is, $25 million will be imported intermediate or primary inputs.
The total benefit to the region in the first year will equal $180 million (combining construction and operation impacts).
The results of user analyses will be correct to the extent to which input-output coefficients are stable. This depends on if the assumptions underlying the input-output estimates have been satisfied. One of the main assumptions is homogeneity. It postulates that:
- each sector produces a single output (i.e. all the products of the sector are perfect substitutes for one another or are produced in fixed proportions); and
- there is no substitution between the products of different sectors.
The homogeneity assumption may be weakened by changes in the product mix (and consequent changes in inputs), the introduction of new products or materials and the substitution of imported products for domestic production. This assumption may be realistic for the year the data is collected but becomes progressively less so as time goes on. National Economics has accounted for the short falls due to the homogeneity assumption by allowing for some of these changes. Estimates of input changes brought about by technological advances have been accounted for using the latest international data and expert advice. Also changes from import substitution have been accounted for by using the indirect import allocation method and analysing trends in trade data.
The second main assumption is the proportionality assumption. It postulates that the changes in the output of an industry will lead to proportional changes in quantities of its input (i.e. for each output, each of these inputs will be a fixed proportion of the total). Economies of scale are therefore ignored. This effect could be accounted for by further refinement of the tables. Given however, that the tables (in quadrant 1 and 3 in our diagram above) represent production functions for firms large and small, any distortions created by the proportionality assumption are balanced out and do not overly bias their use in regional analysis.
Another example of input-output application is assessing the benefits of a specific project to a regional economy. The analysis of the impact must be broken up into two stages. Firstly the construction phase and secondly the operational phase. Irrespective of which type of industry the project is in, both phases will utilise different input requirements and need to be analysed separately.
For example, the construction of a new motor vehicle plant will require inputs from industries such as; construction, building services, steel and machinery and equipment. The impact of the construction of a $150 million automobile plant on the economy may be $105 million once the direct and indirect benefits have flowed through the economy. That is, regional suppliers have provided this amount of inputs.
Once the plant is up and running it will be drawing on inputs from a diverse range of industries including; rubber and plastics, transport equipment, non-metallic minerals (glass etc.) and the fabricated metals industry. An estimated annual output of $100 million for the plant, may have additional benefit to the regional economy of $75 million. That is, $25 million will be imported intermediate or primary inputs.
The total benefit to the region in the first year will equal $180 million (combining construction and operation impacts).
National Economics has two different I/O modules. The first is Current Industry Structure analysis and the second is Specific Project Analysis.
Current Industry Structure Analysis is a simple demand shock model. It corresponds to an increase in final demand. That is, an increase in demand for an industry's output. If the region does not have production in that industry the benefit to the region will be minimal as the increase in demand will be sourced from production outside the region.
Specific Project Analysis allows the user to analyse the effects of a new industry or project to the region. The new industry is assumed to expand the level of demand by the full increase modelled (it is assumed that the market for the produced good already exists). This models an increase in final demand.
This module also allows more parameters to be defined, hence increasing the relevance of the analysis. Variables that can be inputted for a specific project include number of employees, annual wage bills, profits and profits retailed locally. These extra options, which are not available using the Current Industry Structure analysis module, increase the accuracy of the estimated impacts on the regional economy.