Urbanization in East Asia and the Pacific has created enormous opportunity for many. Yet the rapid growth of cities can also create challenges as national and local governments try to keep up with the needs of their growing populations. Among these challenges is a lack of affordable housing, resulting in increasing slums, deficits in basic service provision, and widening inequality for urban dwellers. This study aims to better understand urban poverty and inequality in East Asian cities, recognizing that many countries of the region, particularly those of middle-income status, are at a critical juncture in their urbanization and growth process where potential social divisions in cities could harm prospects for future poverty reduction. The study uses a multidimensional approach to understand urban poverty and inclusion and draws on examples of programs and policies that have been successfully implemented in the East Asia region to develop a set of guiding principles for policy makers.

Understanding how the Papua New Guinea (PNG) agricultural economy and associated household consumption is affected by climate, market and other shocks requires attention to linkages and substitution effects across various products and the markets in which they are traded. In this study, we use a multi-market simulation model of the PNG food economy that explicitly includes production, consumption, external trade and prices of key agricultural commodities to quantify the likely impacts of a set of potential shocks on household welfare and food security in PNG. In this study, we use a multi-market simulation model of the PNG food economy that explicitly includes production, consumption, external trade and prices of key agricultural commodities to quantify the likely impacts of a set of potential shocks on household welfare and food security in PNG. We have built the model to be flexible in order to explore different potential scenarios and then identify where and how households are most affected by an unexpected shock. The model is designed using region and country-level data sources that inform the structure of the PNG food economy, allowing for a data-driven evaluation of potential impacts on agricultural production, food prices, and food consumption. Thus, as PNG confronts different unexpected challenges within its agricultural economy, the model presented in this paper can be adapted to evaluate the potential impact and necessary response by geographic region of an unexpected economic shock on the food economy of the country. We present ten simulations modeling the effects of various shocks on PNG’s economy. The first group of scenarios consider the effects of shocks to production of specific agricultural commodities including: 1) a decrease on maize and sorghum output due to Fall Armyworm; 2) reduction in pig production due to a potential outbreak of African Swine Fever; 3) decline in sweet potato production similar to the 2015/16 El Niño Southern Oscillation (ENSO) climate shock; and 4) a decline in poultry production due to COVID-19 restrictions on domestic mobility and trade. A synopsis of this report, which focuses on the COVID-19 related shocks on the PNG economy is also available online (Diao et al., 2020).1 The second group of simulations focus on COVID-19-related changes in international prices, increased marketing costs in international and domestic trade, and reductions in urban incomes. We simulate a 1) 30 percent increase in the price of imported rice, 2) a 30 percent decrease in world prices for major PNG agricultural exports, 3) higher trade transaction costs due to restrictions on the movement of people (traders) and goods given social distancing measures of COVID-19, and 4) potential economic recession causing urban household income to fall by 10 percent. Finally, the last simulation considers the combined effect of all COVID-19 related shocks combining the above scenarios into a single simulation. A key result of the analysis is that urban households, especially the urban poor, are particularly vulnerable to shocks related to the Covid-19 pandemic. Lower economic activity in urban areas (assumed to reduce urban non-agricultural incomes by 10 percent), increases in marketing costs due to domestic trade disruptions, and 30 percent higher imported rice prices combine to lower urban incomes by almost 15 percent for both poor and non-poor urban households. Urban poor households, however, suffer the largest drop in calorie consumption - 19.8 percent, compared to a 15.8 percent decline for urban non-poor households. Rural households are much less affected by the Covid-19 related shocks modeled in these simulations. Rural household incomes, affected mainly by reduced urban demand and market disruptions, fall by only about four percent. Nonetheless, calorie consumption for the rural poor and non-poor falls by 5.5 and 4.2 percent, respectively.

In this collection of essays, seven authors discuss issues of urbanization and urban poverty, including patterns of urbanization, the characteristics of the urban poor, their access to housing and infrastructure, aspects of the labour market, and the urban physical environment.