2015/FDM2/002 Session: 1 Progress of Regional Integration and Connectivity Purpose: Information Submitted by: Asian Development Bank Finance and Central Bank Deputies Meeting Cebu, Philippines 10 September 2015
APEC Deputy Finance Ministers Meeting 10 September 2015 Cebu City, Philippines Progress of Regional Integration and Connectivity Session 1: Global economic and financial outlook, growing inequality, and regional connectivity/integration Shang-Jin Wei Chief Economist and Director General Economics Research and Regional Cooperation Department Asian Development Bank
Outline for the Presentation GDP and Trade Growth in Asia Aging and Labor Mobility Managing Shocks: Natural Disasters 2
3 GDP and Trade Growth in Asia
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 GDP and Trade Growth Developing Asia moderating GDP and falling trade growth 25 Developing Asia 25 World 20 20 15 15 10 10 5 GDP 5 GDP 0 0-5 Trade -5-10 -15-10 -15 Trade Note: Based on growth rate of local currency units at constant prices. Weighted using gross national income, Atlas Method. Trade refers to the sum of exports and imports of goods and services. Source: ADB calculations using data from various issues of the ADB ADO and World Bank WDI. 4 Note: Trade refers to the total trade volume index, following WTO Trade Report 2014. Source: ADB calculations using data from the IMF WEO and WTO.
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 GDP and Trade Growth Developing Asia ex PRC trade growth: Intraregional trade still rising while slowing with PRC Developing Asia (ex PRC) Total Trade Growth, by Partner (%) 40 30 20 10 0-10 -20 PRC Dev Asia ex PRC ROW -30 Note: Developing Asia includes ADB member economies. Source: ADB calculation using data from Direction of Trade Statistics, International Monetary Fund (IMF). 5
GDP and Trade Growth Structural factors behind the recent slowdown in Asia s growth Income Convergence Reasons for the slowdown: Income convergence Demographics Declining productivity growth * GME = "Growth miracle economies" (PRC; Hong Kong, China; Rep. of Korea; Singapore). Note: Dataset comprises of 111 economies from the World Bank's WDI database with GDP per capita data beginning 1985 (96); 1999 (110) and 2010 (111). Log per capita GDP in the x- axis corresponds to values per these three years. The model follows work done by Barro and Sala-i-Martin (NBER, 1990). The dependent variable is log(gdpcap 2014 /GDPcap 1999 )*1/T, where T is the years within each interval (1999-2007 and 2010-2015). The independent variables are per capita GDP (1999) and a GME dummy. Source: World Development Indicators, World Bank. 6
7 Aging and Labor Mobility
Aging & Labor Mobility More and more APEC economies have aging population Number of economies by type of working age population : APEC + non-apec developing Asia APEC economies included per category JPN JPN RUS RUS HKG JPN PRC KOR THA HKG CAN CAN KOR HKG AUS RUS NZL BRU THA PRC CHL USA THA NZL USA SIN KOR USA VIE AUS AUS INO CAN BRU MAL CHL CHL MEX INO INO PER NZL PER PHI PER SIN PRC VIE BRU MEX PNG MAL MAL MEX PNG PHI PHI PNG SIN VIE
Implications: Country-level production patterns and trade Migrant workers 9
log of GDP per capita Aging & Labor Mobility Income level and age of workforce drive outbound migration in APEC 5.5 5 4.5 4 3.5 3 2.5 2 JPN USA AUS SIN CAN NZLHKG THA SRI RUS INO PHI MYA NEP AFG IND 10 15 20 25 30 35 40 % of population age 20-34 10 Outbound Migration High income, ageing population Low income, ageing population KOR PRC SAU MEX PAK BRU VIE BAN MAL MON High income, young population and workforce Notes: (i) Size of bubble corresponds to the number of outbound migrants in 2013. (ii) Blue bubbles indicate receiving economies (outbound migration is less than inbound) (iii) Green bubbles indicate sending economies (outbound migration is greater than inbound). (iv) GDP per capita (current US$) in 2013. BHU CAM UAE Low income, young population and workforce Total migrants from APEC = 59 million Top Sources (million) 1. India 14.2 2. Mexico 13.2 3. Russian Federation 10.8 4. PRC 9.3 5. Bangladesh 7.8 Top Destinations (million) 1. USA 26.4 2. Russian Federation 6.5 3. Saudi Arabia 6 4. UAE 5.8 5. India 5.2
Managing Shocks: Natural Disasters 11
Managing Shocks: Disasters Cumulative disaster costs to APEC over 1980-2014: $2.2 trillion or 4.4% of APEC s 2014 GDP TAJ 19.5% PAK 10.8% CAM 9.4% MLD 17.7% THA APEC economies 12.7% Other Asia-Pacific economies Note: Based on nominal GDP. Data labels are shown for the top 10 economies. 12 VAN 25.2% NZL 13.3% FIJ 14.9% TON 26.3% Source: ADB calculations using data from World Economic Outlook, IMF; and D. Guha-Sapir, R. Below, Ph. Hoyois. EM-DAT: International Disaster Database. Université Catholique de Louvain. Brussels, Belgium. Available at www.emdat.be CHL 13.4%
Managing Shocks: Disasters Output and consumption growth more volatile in smaller economies Output growth volatility: APEC plus non-apec developing Asia (2000-2014) 18 16 14 12 10 8 6 4 2 0 13 PAL TUV MLD TIM GEO AZE ARM TAJ TKM KGZ KAZ RUS SOL MON PNG AFG RMI KIR UZB BHU SIN THA SAM FIJ MAL INO FSM HKG CHL KOR VAN PER MEX CAM PHI IND CAN TON BRU NZL SRI JPN USA NEP PAK PRC LAO AUS VIE BAN 8 10 12 14 16 18 20 22 Log(Population), 2014 Note: Red markers indicate APEC economies. Volatility is measured using standard deviation. Source: ADB calculations using data from World Development Indicators, World Bank. Consumption growth volatility : APEC plus non-apec developing Asia (2000-2014) 18 16 14 12 10 8 6 4 2 0 VAN TIM BHU BRU ARM TAJ KGZ AZE KAZ MON CAN RUS LAO MAL KOR CAM NEP MEX SIN THA HKG CHL PER PAK INO SRI VIE IND BAN PHI NZL PRC AUS USA JPN 8 10 12 14 16 18 20 22 Log(Population), 2014
Managing Shocks: Disasters Cost of Damages vs Occurrences Cost of damages (% of GDP) versus Number of Disasters: All countries 200 180 160 140 120 100 80 60 40 20 0 More occurrence Less occurrence 100 90 80 70 60 50 40 30 20 10 0 High cost of damages Low cost of damages 14 Note: Based on country decade-level data for 3 periods: 1985-1994, 1995-2004, 2005-2014. Covers 135 economies. Source: ADB calculations using data from World Economic Outlook, IMF; and D. Guha-Sapir, R. Below, Ph. Hoyois. EM-DAT: International Disaster Database. Université Catholique de Louvain. Brussels, Belgium. Available at www.emdat.be
Managing Shocks: Disasters Effective national policies and regional cooperation, key to managing disaster risk financing National Level Range of Financial Instruments to Deal with Disaster Risk Possible regional cooperation efforts on disaster risk financing: High severity Low severity More frequent Source: Adapted from Cummins and Mahul (2009) as cited in ADB. 2013. Investing in Resilience: Ensuring a Disaster-Resistant Future. 15 Less frequent International donor assistance Catastrophe bonds and other Insurance linked securities Insurance/reinsurance Contingent credit Reserve/calamity funds (potentially insurance backed) Risk transfer Risk retention Risk information systems Catastrophe insurance market development Standardized products Risk pooling Capacity building ADB s role: policy advice on fiscal risk and public debt management as well as the development of catastrophe risk market infrastructure and DRF strategies
Key Messages 1. Developing Asia s GDP growth moderating, but still robust The fall of the trade growth > fall of GDP growth 2. More APEC economies are aging; fewer economies have fastgrowing workforce Income level and age of workforce drive migration in Asia 3. Natural disasters: costly and increasingly more frequent Disasters cost to APEC economies $2 trillion in the last 34 years or 4.4% of 2014 GDP Needs a combination of national policies and regional cooperation to manage disaster risk financing 16
Thank You! Shang-Jin Wei swei@adb.org Asian Development Bank 17