On the spending side, limiting Dutch disease impacts will require focusing on activities that have a high import content and that boost the overall supply potential of the economy, especially that of the tradable sector. This likely means focusing spending on public investment. If household spending of mining income is also an important channel of transmission, then there may be a role for tighter monetary policy to reduce the potency of this channel.

The rest of the paper is organized as follows. Section II summarizes the key features of MAMS and the calibration strategy for Mongolia with the underlying structure of the economy. Section III analyzes the results for a set of simulations designed to explore the relative importance of the spending and resource movement channels through which Dutch disease occurs in Mongolia. Section IV discusses the main policy conclusions.

# **II. Model framework**

MAMS is a recursive dynamic CGE model developed at the World Bank to analyze strategies for achieving MDGs, and for undertaking country-level, medium-to-long-run policy analysis (Lofgren et al., 2013). The model is dynamic recursive in that the solution in any time period depends on current and past periods, not the future. Only relative prices matter and these help to clear the markets for factors, goods, and services. As part of the micro foundations of the model, producers maximize profits and consumers maximize utility.

The calibration strategy for Mongolia is detailed in the companion paper (Khan et al., 2017) and this section only describes the broad framework. The underlying Social Accounting Matrix (SAM) that sets out the basic relationships and income flows in the economy was calibrated using publicly available 2005 data from the National Statistical Office (NSO), notably input-output tables for that year. These data were supplemented with other NSO data on employment, balance of payments, and public finances.

In the Mongolia CGE model, there are seven sectors (i.e. activities, each of which produces a specific good or service), five of which are in the private sector (Table 1). In addition, there ae three institutions: a single representative household, the government and the “rest of the world” (ROW). None owns a sector or industry, but rather earns income from a share of the relevant production factors (labor, capital and mining capital). For the household, the income sources also include transfers from the government and remittances from overseas, while the government also earns revenues from indirect and direct taxes. The SAM is set out in Appendix A.

Production technologies are nested. At the top level, output for each sector is generated by aggregates of value added and intermediates. At the lower level, these aggregates are produced by a CES aggregation of production factors and a Leontief aggregation of intermediate inputs, respectively. The mining sector is a special case in that factor use also is determined by a Leontief formulation. Factor inputs other than the mining factor are paid market wages; the mining factor (“mining capital”) is paid the residual. Overall labor supply is determined by exogenous population growth, so that labor is a relatively scarce factor. Finally, the selection of production, trade, input and demand elasticities is set to match actual economic developments as closely as possible (see Khan et al. 2017).

The choice of mechanisms for maintaining internal and external balances are as follows. With respect to the budget, spending adjusts in response to revenues, with additional revenues spent on government consumption (unless specified otherwise as is the case with some individual simulations that explored later). Private investment is kept constant as a share of total absorption while private saving adjusts to provide needed financing. A flexible real exchange rate clears the balance of payments. The numéraire is the CPI so that nominal values like wages, household income, household expenditures are CPI-indexed.

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