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PPPs for policy making: a visual guide to using data from the ICP - Chapter 1: The size of the economy and price levels

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Subnational analyses

PPPs can be constructed at subnational levels to reflect the different price levels and economic structures prevalent within a country. These subnational PPPs can assist with domestic analyses at the state, province, and regional levels and help to direct appropriate locale-specific policy initiatives.

The General Statistics Office of Vietnam produces the subnational Spatial Cost of Living Index (SCOLI), based on prices collected throughout the country’s six economic regions (figure 1.6 and figure 1.7). The SCOLI data provide a window on how living standards, economic performance, general productivity, and price competitiveness vary across Vietnam. The data inform a range of regional socioeconomic development policies such as analyses of the impact of poverty reduction policies, hardship allowances, and wage subsidies in the different regions. Furthermore, business enterprises use SCOLI data to evaluate competitiveness related to price, output, market share, and product cost. Employees and employers use the index to negotiate wage rates and assess inter-provincial migration advantages and disadvantages.

The Bureau of Economic Analysis (BEA) in the United States produces annual regional price parities (RPPs) by state and metro area. State RRPs and the national personal consumption expenditures price index are used to calculate real personal incomes at the subnational level, which reflect price differences across the country (map 1.4). RPPs are also used for adjustments to poverty estimates, comparisons of minimum wage levels, and the calculation of pension estimates in different parts of the country among other applications.

The Office for National Statistics (ONS) in the United Kingdom (UK) produces relative regional consumer price levels (RRCPLs) which provide an indication of a region’s price level compared with the UK average price level for a number of goods and services aggregates (figure 1.8).