Regional implications of public investments and external shocks in Papua New Guinea: An economywide analysis

Improvements in telecommunications have enabled a tremendous increase in the flow of information across Papua New Guinea. Although transport costs remain high between various parts of the main island of Papua New Guinea, as well as between the main island and other parts of the country (e.g. the islands of New Britain and Bougainville to the East), phone and internet conditions enable government, traders and entrepreneurs to share market information that reduces transactions costs and improves market function. Nonetheless, there remain major differences in agricultural production, income sources and demand patterns across regions that are important to take into account in analyzing the impacts of external shocks and formulating development strategies. Earlier work on PNG by Schmidt et al., (2021) explored the effects of Covid-related income and world rice price shocks with a partial equilibrium model of PNG’s rice economy. Diao et al., (2021) used a regional multi-market model to analyze broader effects of Covid-19 and other shocks to agriculture and household incomes in four regions of PNG. Various other studies, including Dorosh and Pradesha (2022) and Diao et al. (2024), used national computable general equilibrium (CGE) models of PNG to analyze exchange rate, terms of trade, and productivity shocks on various household groups. In this paper, we extend these earlier analyses through use of a new regional CGE model that utilizes recent household survey data, including the 2023 IFPRI PNG rural household survey. The plan of this paper is as follows. The next section provides an overview of agriculture and economic growth in PNG over the last decade, highlighting the almost constant share of agriculture in GDP and very low per capita agricultural GDP growth rate. Section 3 describes the regional disaggregation of the PNG economy and the structure of household incomes and expenditure as reflected in the economywide database, the Social Accounting Matrix (SAM), used in this analysis. Section 4 then presents a summary of the regional economywide model. (Details of the model are found in the annexes and in the references included in the paper.) Design of the model simulations and simulation results covering investments in agriculture and transport sectors, as well as world price shocks are discussed in Section 5. Chapter 6 concludes with a summary of the main findings and policy implications, as well as suggested areas for further work.