pitfalls problems & roadblocks
Post on 15-Feb-2016
38 Views
Preview:
DESCRIPTION
TRANSCRIPT
Pitfalls problems & roadblocks
• Financial melt-down• National scale land purchases• Food fuel ...• War on terror ...• Nations in bondage to IMF debt• Unfair trade practices• Climate change• Globalization of food economics• Clean water & air have become commodities
Vandana Shiva on globalization
Vandana Shiva on Food Laws
Diverts development & aid $ Increases the price of foods
Also displaced persons & Destroys the local economy
Supplementary data & tables follow
2
Stunted children (poverty-trapped)
3
195 million worldwide 2008
http://www.unicef.org/media/files/Tracking_Progress_on_Child_and_Maternal_Nutrition_EN_110309.pdf3
4
http://www.actionaid.org.uk/doc_lib/hungerfree_scorecard.pdf
Contrary view 2010
http://aidwatchers.com/2010/09/%E2%80%9Cproofiness%E2%80%9D-trashing-back-on-fao-hunger-numbers/
William Easterly
Num
ber o
f peo
ple
(mill
ions
) ad
equa
tely
nou
rishe
d (F
AO d
ata)
51970 1980 1990 2000 2010200
300
400
500
600
f(x) = 8.21121293077501 x − 15930.2774664487
[ ]2010 UN 86% 587b ?
6
30%
2000Decreasing poverty
80%Fr
actio
n in
pov
erty
Ethiopia: on the development ladder
% In
fant
mor
talit
y <
5 ye
ars
71920 1930 1940 1950 1960 1970 1980 1990 2000 20100
10
20
30
40
http:
//w
ww
.chi
ldin
fo.o
rg/m
orta
lity_
infa
ntm
orta
lity.
php
also
ww
w.g
apm
min
der.o
rg
Still poverty trapped
India
USA
Singapore
Porkbarrelling & Swiss bank a/c’s
multi-nationals
dictators
numbered bank a/c’s
Rich nationpoliticians government
taxpayers in poor countries
commod
ities
taxpayers in rich (Nato?) countries
“military-industrialcomplex”
Tanks & rockets for right wing regimes, invasions for “freedom & democracy”, & depose “socialists” Treaties force unfair
tariffs & trade.
Share-holders
$
$
$
$$$
$
election funds,inducements
concessions
$$ 8
Prevalence of stunting >2SD
10
http://www.unicef.org/media/files/Tracking_Progress_on_Child_and_Maternal_Nutrition_EN_110309.pdf
MDG
s: w
orld
pro
gres
s
110 10 20 30 40 50 60 70 80 90
2005
2006
% < $1.25 /day
% undernourished
% infant mortality
H2O
gree
n ba
r is t
arge
t for
201
5
2006
amber bar is 1990; yellow is 2008 or ..
school
pregnt
12
13http://ije.oxfordjournals.org/content/32/4/518.full.pdf
Nations in the poverty trapIn 5 of them hunger is increasing
14www.foreignpolicy.com/articles/2010/06/21/2010_failed_states_index_interactive_map_and_rankings
http://www.ifpri.org/datasets
Nearly all are conflict zones, rich in resources or militarily strategic
16
http://www.globalissues.org/article/35/foreign-aid-development-assistance#GovernmentsCuttingBackonPromisedResponsibilities
•Ireland•Luxemborg•Sweden•Denmark•Norway•Netherlands•UK
Low share of phantom aid
60% of US ODA goes to Iraq & Israel
Nothing helps Poverty will go
17
It’s their own fault
Corrupt dictators
Malthus
2008 recession
Trillions wasted
MDGs are unachievable
Corrupt multinationals
They will be achievedWe know what works & doesn’t
Throwing $ at problems
Will delay progress by 4-8 y
They don’t need $
• there is no reason for complacency or self-satisfaction
• 10,000,000 kwash ward [= no of kids born in Can in 30 years] 35M birth rate 10/1000 = 350k kids/y]
• The faster we move the less we have to cope with population growth,
18
Show as stacked histogram• %le rank Member countries• 90-100 NZ, Scand, Switz, Can, Aus, HK, W Eur & UK• 50-90 US, France, UAE, Israel, Botsw, SA, Namib, Turky• Kuwait, Ghana, Greece, China, Swaziland, India, Panama,
Thailand• 33-50 Morocco, Malawi, Lesotho, Mex, Rwanda, SriLan, Liberia,
Zambia, Senegal, Niger, Gambia, Argentina, Egypt, Algeria, Mali
• 15-30 Vietnam, Ethiopia, Uganda, Nigeria, Lybia, Zimbabwe, Russia, Kenya, Ukraine
• 5-10 Tajikistan, Cambodia, Laos, Central African Republic, Congo, Angola, Venezuela,
• 0-5 Turkmenistan, Iran, Haiti, Guinea, Uzbekistan, Iraq, Sudan, Myanmar, Afghanistan, Somalia (6 /54 African)
19
•1-liner Toward MDGs - what works, what doesn’t•Introduce the antagonist. “Dead aid”. 3 points: 1 the trajectory says YES ... but too slow2 transp, sustained, targeted aid works3 it’s working thanks to few nations & initiatives•Visual slides – not for note-taking•Visual presentation of quantitative data•Reveal the holy smokes moment•Rehearsals beginning mid-late Sept•Just before the talk remind yourself of passion
“Our kids will see hunger relegated to museums”Trade
barriers
It’s their own faultWe already give more
than anyone else
Trillions wasted
There are more hungry now than ever
MDGs are unachievable
Corrupt dictators
Corrupt
multinationals
Steady progress MDGs
Tilted playing field
“Things will get worse no matter what we do”
Malthus
Rich nations broke
their promises2008 recession
We never promised 0.7%
Trade not aid
MDG progress 2010
• http://www.who.int/mediacentre/factsheets/fs290/en/index.html
• http://www.fao.org/mdg/en/• http://www.un.org/millenniumgoals/reports.s
html#mdgs
23
MDG Critique & Scenarios• MDGs a critique from the south Sept 2010• http://allafrica.com/stories/201010010582.html
The MDGs after the Crisis The MDGs after the Crisis
World bank analyses scenarios. Crisis recovery matters, but not as much as kept promises
24
Deaths (millions) before age 5 in 2006
26
http://www.globalissues.org/article/35/foreign-aid-development-assistance#GovernmentsCuttingBackonPromisedResponsibilities
•Ireland•Luxemborg•Sweden•Denmark•Norway•Netherlands•UK
Low share of phantom aid
60% of US ODA goes to Iraq & Israel
27
[US Senator Patrick] Leahy noted that two-thirds of US government aid goes to only two countries: Israel and Egypt. Much of the remaining third is used to promote US exports or to fight a war against drugs that could only be won by tackling drug abuse in the United States.”
UN Secretary General Kofi Annan noted that the flow of money from poor to rich countries far exceeded total ODA.“Funds should be moving from developed countries to developing countries, but the opposite is happening…. Funds that should be promoting investment and growth in developing countries, or building schools and hospitals, or supporting other steps towards the Millennium Development Goals, are, instead, being transferred abroad.”
instead of promoting investment in health, education, and infrastructure development in the third world, this money has been channeled to the North, either because of debt servicing arrangements, asymmetries and imbalances in the trade system or because of inappropriate liberalisation and privatisation measures imposed upon them by the international financial and trading system.
GDP per capita / past 10 years
281998 2000 2002 2004 2006 2008 2010$600
f(x) = 292376.226469201 ln(x) − 2214918.51992798f(x) = 6434.86075784702 ln(x) − 48497.8881060144f(x) = 15848.6410819205 ln(x) − 120034.398796703f(x) = 15848.6410819205 ln(x) − 120034.398796703f(x) = 118551.334790581 ln(x) − 898968.779757485f(x) = 210784.13289449 ln(x) − 1598330.19689864f(x) = 210784.13289449 ln(x) − 1598330.19689864
Sub-Sahara (minus SA)
1999 $5992009 $743
Av growth rate 2.7%
$700
It’s not that complicated• There is enough for everyone …
… suffering is widespread & extreme
• We know the trajectory• We know what doesn’t work & why
• We know what works & why
“Initiatives since the MDGs”
29
30
The trajectory
Gapminder IMF WB CIA FAO USDA % fed% in povertyChanges in income to 2009
What is the dataset?
• There are data going back to the 1800s• Gapminder• Also a plethora of tightly focused data from
1960 to 2005• The WHO, FAO, World Bank, USDA / ERS, CIA
• Comprehesive data to 2009 USDA 31
321968 1973 1978 1983 1988 1993 1998 2003 2008
$40
$2,000
f(x) = 292376.226469201 ln(x) − 2214918.51992798
f(x) = 6434.86075784703 ln(x) − 48497.8881060145f(x) = 15848.6410819206 ln(x) − 120034.398796704f(x) = 15848.6410819206 ln(x) − 120034.398796704
f(x) = 118551.334790581 ln(x) − 898968.779757484
f(x) = 210784.13289449 ln(x) − 1598330.19689863f(x) = 210784.13289449 ln(x) − 1598330.19689863
GDP all of Africa past 40 y
The focus• There is steady progress• Three kinds of aid
relief development
harm > goodAid that doesn’t workAid that does workWhat’s changing
33
What’s the evidence?
• Progress is steady, but slow • Expect it to accelerate • We know what works &
what doesn’t - “dead aid?”• Initiatives since the MDGs• No cause for complacency
34
Assertion vs Evidence
35
MDGs unachievable?progress is slow - 1% pa (should be 2.5%)
$2trillion wasted harm > good?
ask instead what works & doesn't?
seeds, water, fertilizer, DDT, ARVs
Malthus – population trumps food?
development slows growthNothing helps?
spectacular new initiatives Watchful waiting
10,000,000 under 5
Bill Clinton: Senate Foreign Rlns Ctte: Forced poor to buy US ag products < cost
… “a disaster - destroyed local agriculture”
“I did that. I have to live every day with the consequences of lost capacity to produce a rice crop in Haiti to feed those people, because of what I did. Nobody else”
36
Aid that helps NATO farmers
Contingent on unfair markets
37
That goes to corrupt dictators
38
Pitfalls problems & roadblocks
• Financial melt-down• National scale land purchases• Food fuel ...• War on terror ...• Nations in bondage to IMF debt• Unfair trade practices• Climate change• Globalization of food economics• Clean water & air have become commodities
Vandana Shiva on globalization
Vandana Shiva on Food Laws
Diverts development & aid $ Increases the price of foods
Also displaced persons & Destroys the local economy
• Recent factors accelerating progress• MDGs, Grameen, Millennium villages,
Billionaire philanthropists, WWW / technology, passionate agents of change, leverage
40
Why does so much aid not workTeams of publish or perish “anthropologists”
“Another needs assessment? …
“We have noticed that Americans have very tiny ears” ...
... & very large mouths. But we would prefer it to be the other way around
Aid that designed to benefit the donor, not the recipient
Not billions given to buy loyalty of corrupt leaders
Advocates for the poor rate the World Bank, IMF, & WTO fail!
Vandana Shiva
Look around. Ask people”
• Recent factors accelerating progress• MDGs, Grameen, Millennium villages,
Billionaire philanthropists, WWW / technology, passionate agents of change, leverage
42
• Your mindset vs my dataset
• Don’t want to rain on your parade
View from N & South are the same• N emphasizes 15 y vs 50 y• S emphasizes 10 M / near
43
top related