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William Gbohoui, Mr. Waikei R Lam, and Victor Duarte Lledo
Growing regional inequality within countries has raised the perception that “some places and people” are left behind. This has prompted a shift toward inward-looking policies and away from pro-growth reforms. This paper presents novel stylized facts on regional inequality for OECD countries. It shows that regional disparity in per-capita GDP is large (even after adjusting for regional price differences), persistent, and widening over time. The paper also finds that rising nationwide income inequality is associated with both rising within-region income inequality and widening average income across regions. The rise in inequality is related to declining incentives for interregional labor mobility, especially for poor households in lagging regions, which are estimated to reduce by as much as one-third in the United States. Against these facts, the paper proposes a framework to identify whether, how and by whom fiscal policies can be used to tackle regional inequality. It outlines conditions under which those policies should be spatially-targeted and illustrates how they can be complementary to conventional means-testing methods in mitigating income inequality.
Mr. Roberto Cardarelli and Ms. Lusine Lusinyan
Total factor productivity (TFP) growth began slowing in the United States in the mid-2000s, before the Great Recession. To many, the main culprit is the fading positive impact of the information technology (IT) revolution that took place in the 1990s. But our estimates of TFP growth across the U.S. states reveal that the slowdown in TFP was quite widespread and not particularly stronger in IT-producing states or in those with a relatively more intensive usage of IT. An alternative explanation offered in this paper is that the slowdown in U.S. TFP growth reflects a loss of efficiency or market dynamism over the last two decades. Indeed, there are large differences in production efficiency across U.S. states, with the states having better educational attainment and greater investment in R&D being closer to the production “frontier.”
International Monetary Fund. Western Hemisphere Dept.
This Selected Issues paper on the United States of America examines the recent US labor force penetration rate (LFPR) dynamics. LFPR dynamics can be driven by structural factors and cyclical ones related to job prospects. With participation rates for older workers lower than for prime age workers, demographic models suggest that aging of the baby boom generation explains about 50 percent of the near 3p.p. LFPR decline during 2007–2013. State-level panel regression analysis is used to tie down the cyclical effect, which is estimated to account for about 30–40 percent of the decline. Significant remaining slack in the labor market points to an important role for macroeconomic and labor supply policies. This suggests a still important role for stimulative macroeconomic policies to help reach full employment. Macroeconomic policy should remain accommodative for a while given sizeable labor market slack. This slack goes beyond that signaled by the unemployment rate and takes account of the LFPR being below trend and many employees working part time ‘involuntarily’.
International Monetary Fund. Western Hemisphere Dept.

OECD Regional Database using elementary (6 years), secondary (12 years) and tertiary (20.52 years) attainment series to calculate the average years of schooling. The data for the total U.S. are from the Census “Table A-1. Years of School Completed by People 25 Years and Over, by Age and Sex: Selected Years 1940 to 2012.” Innovation indicators (R&D expenditure) : The OECD Regional Database for state-level data on R&D expenditure by sector, R&D personnel by sector, employment in high-tech sectors, patent applications (by sector) and ownership. The data are annual

Mr. Roberto Cardarelli and Ms. Lusine Lusinyan

.S. as a whole. IT-using industries are those with more than the median share of IT-intensity index, defined in turn as the share of IT-capital input (and IT services purchased) in total capital input of a given industry. For the construction of the synthetic index, see above, except the reference year here is 2005 reflecting data availability in Jorgenson, Ho, and Samuels (2010) . Educational attainment : Average years of schooling. The main data source, Turner et al. (2006) has been extended after 2000 with the data from the OECD Regional Database using

William Gbohoui, Mr. Waikei R Lam, and Victor Duarte Lledo

income Nonworking population Life expectancy (at birth) 0.4596 * 0.5990 * -0.2345 * -0.1133 * 0.0932 * Health access 0.2266 * 0.1324 * -0.1748 * -0.1875 * -0.1714 * Education attainment (secondary level) 0.5542 * 0.6517 * -0.5758 * -0.5370 * -0.0348 * denotes 5 percent statistical significance level. Sources: OECD Regional Database and IMF staff estimates. 2. The between-inequality on income has also been persistent and widened over time, particularly after the global financial crisis

Metodij Hadzi-Vaskov and Mr. Luca A Ricci

. Regional Inequality Source: OECD Regional Database Notes: (I) Figure on regional gap in GOP per capita: OECD regions refer to the administrative tier of subnational government (targe regions, Territoriat level 2); Chile is composed of 15 targe regions. (2) Figure on index of regional disparity: top (bottom) 20% regions are defined as those with the highest (lowest) GDP per capita until the equivalent of 20% of national population is reached, this indicator provides a harmonised measure to rank OECD countries, using data for small regions {Territorial Level 3) when

International Monetary Fund. Research Dept.

region, while Mississippi’s is about one-third lower than the median). Among the advanced economies with larger regional differences are Canada and Italy, with 90/10 ratios at about 2. Figure 2.6. Subnational Regional Disparities in Real GDP per Capita (Ratio to regional median times 100, 2013) Sources: Organisation for Economic Co-operation and Development (OECD) Regional Database; and IMF staff calculations. Note: P10(50, 90) indicates the 10(50, 90)th percentile of the regional real GDP per capita (purchasing power parity-adjusted) distribution within