{'fraction_non_alphanumeric': 0.01556951652553947, 'fraction_numerical': 0.0010925976509150504, 'mean_word_length': 5.206779661016949, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Multi-Regional Computable 
General Equilibrium Model 
for New Zealand

Although New Zealand has had an active CGE modelling community since the 1980's, a multi-regional CGE model for the country has not been developed until now. This thesis presents a prototype multi-regional CGE model to demonstrate the feasibility of developing a comprehensive model that captures the benefits of modelling agent behaviour with a bottom-up approach. The prototype model is built upon bottom-up regional micro-foundations and New Zealand data is used to operationalise a particular implementation of the model. The thesis fills an important gap in the New Zealand CGE modelling literature as none of the models in current use have a structure involving bottom-up regional modelling. The method of implementation is also a key contribution, utilising a maximum-entropy approach to overcome data shortages. An illustrative simulation of a natural disaster that strikes the Wellington central business district demonstrates the strengths of the bottom-up multi-regional approach - that the model can capture differential effects across regions of shocks that occur at the regional level, and incorporate  flow-on and feedback effects between regions. Sensitivity testing of the substitution elasticity between domestic sources of products reinforces the importance of empirically-estimated parameters in CGE models. The basic model is extended in two ways. The first is to introduce modelling of distribution services as has been done in the ORANI and subsequently FEDERAL models. The key structural difference here is that products identified as distribution services are required to facilitate movement of other products from seller to buyer. Thus there are no opportunities to substitute away from these services if they become relatively more expensive. To implement the additional structure, sets of coefficients are specified to control technical possibilities in the usage of the distribution services. These include switches that can dictate, for example, that wholesale trade is only involved in the delivery of tangible products, that retail trade is only used by in-region purchasers, and that transport is required for moving physical products across regional borders or to exporters. That these assumptions can be integrated seamlessly into the database highlights the strength of the maximum-entropy approach used to generate the multi-regional input-output database. Simulations of an oil price shock show that the regional assumptions surrounding the distribution networks are material to the results. The second extension to the model is the addition of a module to control the degree of inter-regional labour mobility. Essentially the user is given the ability to specify the extent to which households respond to regional real wage di erences by moving to regions with relatively higher rates. Therefore, in short-run simulations labour can be made more mobile than capital, while in the long-run it can be less mobile than capital. The module also introduces additional structure to link populations, households, and labour market components. One important element of this new structure is a link back to the endogenous labour supply theory of the basic model. Publicly available demographic and labour market data are used to implement the mobility module. The importance of a mobility response to relative real wage changes is explored in an illustrative application looking at the impact of regionally-concentrated immigration  flows. The simulations suggest that population movements can work to dissipate the welfare effects of such migration inflows.