1 Introduction

The success or failure of an economic development or industry policy is often judged on whether it has contributed to the development of the supported sector or possibly a small group of closely-related sectors. However, because we should be interested in the impact on national welfare from policy interventions, this narrow focus on the supported sector(s) misses important flow-on or economy-wide effects that are a critical part of the assessment of policy proposals.

These economy-wide effects arise because every sector is linked to the rest of the economy through their demand for inputs such as land, capital, labour; and their provision of outputs. The growth in the targeted sector will change the demand and price for both inputs and outputs, which in turn affects other sectors and the overall economy. A growing sector will demand more labour and intermediate inputs, raising prices of those inputs across the economy often to the detriment of other sectors. A growing sector will also produce more outputs, which may lower their price, leaving consumers more money to spend elsewhere or providing cheaper inputs to other sectors. These flow-on effects quickly multiply, but it is the net effect of all these impacts that is important for assessing the overall welfare implications of a particular industry policy.

However, these economy-wide effects are rarely quantified and sometimes not considered at all. This could be due to the difficulty in identifying all the various flow-on impacts in a systematic way. However, computable general equilibrium (CGE) modelling is an established economic modelling technique that can be used to highlight and quantify the effects of an industry policy that extend beyond the targeted sector. Originally developed for studying trade and taxation policies, these models are now also heavily used for analysis of climate change policies. The Australian Productivity Commission (and its predecessors) in particular have been using CGE models regularly in their enquiries since 1977 (Powell & Snape, 1992). Examples include studying the effects of greenhouse gas emissions and policies to reduce those effect on the economy (Industry Commission, 1991); support packages provided to the automotive industry (Productivity Commission, 2008); and reducing regulatory burdens for multi-jurisdiction firms (Productivity Commission, 2012). CGE models have also been used to study the economy-wide effects of regulatory reform and of energy efficiency; but their use is not limited to these areas.

This paper describes what CGE modelling is, then shows how CGE modelling is used to study the economy-wide effects of four illustrative industry policy scenarios. The scenarios span a range of topics: the effect of a policy that results in a 10% increase in demand for exports; comparing the effect of a policy that brings about a 10% productivity improvement in large but low value-added sectors to a policy that brings about the same improvement in small but high value-added sectors; a 15% R&D tax credit; and a policy that brings about a 10% improvement in international freight productivity. They include some results that are initially counter-intuitive, and show the importance of considering the economy-wide effects of a policy change rather than just the effects on the directly affected sector. The New Zealand Treasury commissioned NZIER[1] to study these scenarios and provide the results summarised in this paper.

It is important to stress that the analysis presented here does not purport to be a full cost-benefit analysis of various policy proposals. In fact, aside from the R&D tax credit scenario, we do not attempt to specify the policy that brings about the scenario being modelling. The scenarios simply seek to illustrate how the economy-wide effects might work through in each case. The aim of this paper is to inspire greater use of CGE modelling to understand the economy-wide effects of industry policies, rather than to provide advice on the example policy scenarios provided.