شبکه فضایی، مدل کلی تعادل با یک برنامه تلطیف شده

Spatial aspects of economic policy are often important. However, multi-region computable general equilibrium (CGE) models have rarely explicitly treated geographical space. This paper develops a spatial-network, mixed-complementarity CGE model, incorporating formulations from partial-equilibrium programming models. We implement the model with a prototype data set for a stylized, poor, developing country with rural regions linked to an urban region that is linked to international markets. We demonstrate that the model provides a good framework for analyzing the impact of higher world prices and reduced domestic transportation costs and that the explicit incorporation of space has a strong impact on simulation results.

Consideration of the spatial impact of economic policy is of critical importance to policy makers. In recent years, the relevance of space has been underlined by a surge in regional strife in nation states throughout the world. The need for spatial disaggregation is underlined by empirical findings which suggest that the regional effects of changes in policies and exogenous shocks may be significantly different from the national average (Nijkamp et al., 1986, pp. 259 and 261; Miller and Blair, 1985, p. 63). At the same time, models of a single region inside a country, for which the national economy is assumed to be given, may generate misleading results since they do not allow for inter-regional and nation-region feedbacks. In this environment, spatially disaggregated national models are often the preferred tool for policy analysis. In recent years, many countries have undergone changes in trade and exchange rate policies. Policy shifts in these areas may have very different effects across regions due to regional differences in economic structure and the existence of high transportation and communications costs. When, as a result, market links across regions are weak, the ‘national’ economy may be better seen as a collection of imperfectly linked regional economies. In this environment, changes in national policy may have little effect on some regions when the changes in prices are too small to induce changes in regional trade. There will also be ‘threshold effects’ whereby changes in, say, trade policy will have little or no effect until the changes are large enough to cause regional producers and consumers to react to changes in prices external to the region, generating sectoral trade flows where before particular regional markets were autarkic. The multi-region modeling literature includes both partial- and general-equilibrium approaches. In the partial-equilibrium, programming tradition, the typical formulation permits the model to endogenously select the quantities traded, including the regime for each tradable commodity and regional link. This link may be inactive or may ship in one of the two directions, but not both.1 This approach assumes that tradable commodities are homogeneous or perfectly substitutable irrespective of source (from the perspective of the demander) or destination (from the perspective of the supplier). In the general-equilibrium literature, which encompasses economywide input–output models and computable general equilibrium (CGE) models, available multi-region models rarely consider space explicitly.2 Most models assume product differentiation. Input–output models rely on fixed trade coefficients, trade pool theory (Nijkamp et al., 1986, pp. 263–265; Batten and Boyce, 1986, p. 389), or the theory of demand distinguished by place of production (the Armington approach).3 CGE models tend to use the Armington approach, often complemented by a constant-elasticity of transformation formulation to capture quality differences between output supplied to different destinations. These general equilibrium models do not permit ‘regime shifts’ and ‘threshold effects’ for trade flows: if, for the base solution, one region exports to or imports from another region, then this trade flow will always be present and adjust smoothly to simulated exogenous changes.4 While this may be appropriate for a wide range of commodities, it is often not the preferred way of modeling homogeneous agricultural commodities. Country-level FAO data indicate that, for foreign trade in relatively homogeneous agricultural commodities, significant two-way trade is not the typical case, and that regime shifts have occurred for many countries. For example, in the 1970s, India shifted from imports to exports in its rice trade. Similarly, between 1979 and 1986, Malawi’s trade in maize, the country’s main staple, changed regime four times; since independence (in 1964), the country has never had any significant two-way trade in maize. In these contexts, the trade assumptions associated with the partial-equilibrium, programming approach seem preferable. The purpose of this paper is to enrich the general equilibrium modeling tradition by incorporating into a CGE model the treatment of space and trade that commonly is found in the partial-equilibrium, multi-region programming literature. The resulting model will combine strengths of the two literatures. First, we present a country-level, spatial-network, CGE model and a prototype data set (reflecting stylized conditions commonly found in poor, developing countries) with which the model is implemented (Section 2). A mathematical model statement and the full data set, including a multi-region social accounting matrix (SAM), are presented in two appendices. Secondly, we demonstrate that the model provides a good framework for analyzing the impact of higher world prices and reduced domestic transportation costs in an environment with important threshold effects. We also show that the explicit treatment of space and transportation costs has a strong impact on the results (Section 3). The paper ends with some concluding remarks (Section 4).

We have demonstrated that a mixed-complementarity CGE model can incorporate a multi-region spatial network with region-specific transportation costs that permit regime shifts and threshold effects in regional trade and production. Our application of the model suggests that it provides a good framework for analyzing issues such as the impact of higher world prices and reduced domestic transportation costs. The framework should also be useful for many other kinds of policy analysis. The distinguishing features of the model play an important role in the simulations: multiple regime shifts occur in domestic and foreign trade; responses are in many instances discontinuous; transportation costs provide a natural barrier that prevents excessive specialization; and disaggregated regional impacts are diverse. The results are compatible with findings in the literature on multi-region CGE models according to which spatial disaggregation matters in many contexts. Explicit inclusion of transportation costs is likely to be important when transportation costs constitute a significant share of prices, typically in settings where the transportation infrastructure is underdeveloped and/or when population density is low and the population is dispersed. Regime shifts in trade are more likely when large price changes occur for relatively homogeneous commodities. In terms of policy analysis, the results indicate the importance of considering infrastructure investment as a crucial part of development strategy involving trade liberalization and an increased role for foreign trade.11 The choice of model structure is inextricably linked to data availability and the purpose of the analysis. Rather than the purposefully pure model presented in this paper, hybrid models are more likely to be useful in applied work. Such models would incorporate the spatial-network and a regime-shift formulation for the parts of the model that are most disaggregated (for example, grain commodities in a model focused on grain-market policies), while, in other areas, they might draw on features typical of existing multi-region CGE models (most importantly product differentiation, but perhaps also a less data-demanding treatment of transportation costs).