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Economic l essons from crisis Economic l essons from crisis

Economic l essons from crisis - PowerPoint Presentation

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Economic l essons from crisis - PPT Presentation

Rachel Glennerster IGC Lead Academic for Sierra Leone and JPAL Joint work with Tavneet Suri IGC Agriculture and MIT Sloan Overview The importance of good data in a crisis Initial sectors of concern and policy focus not supported by the emerging evidence ID: 693401

areas ebola rice cordon ebola areas cordon rice food prices cases data glennerster 2015 suri leone sierra impacts good

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Presentation Transcript

Slide1

Economic lessons from crisis

Rachel Glennerster (IGC Lead Academic for Sierra Leone and JPAL)Joint work with Tavneet Suri (IGC Agriculture and MIT Sloan)Slide2

Overview

The importance of good data in a crisisInitial sectors of concern and policy focus, not supported by the emerging evidence

Economic impacts were not concentrated where the

disease was

Impact of food aid during the crisisThe role of researchers during a crisisMaintaining confidence while calling for help

2Slide3

Ebola cases end June, Sierra LeoneSlide4

Ebola cases, cordon areas, end

AugSlide5

Ebola cases, cordon areas, end

SeptSlide6

Ebola cases, cordon areas, end

OctSlide7

Ebola cases, cordon areas, end

NovSlide8

Ebola cases, cordon areas, end

DecSlide9

Ebola cases, cordon areas, end

JanSlide10

Ebola cases, cordon areas, mid

MaySlide11

Incentive is to grab headlines

WHO “up to 90%” death rate from EbolaMin of Ag, GDP

had already fallen by 30%

GDP fell by

av of 5% per year during devastating civil warSept 5, FAO reported 40% of farms in Kailahun abandoned, and lack planting materialsIn sept rice is maturing in fields: what does abandoned mean?Planting pre Ebola, would not take place again till May 2015

Reports of skyrocketing food prices

Restrictions on transport did make this a concernSlide12

Messaging ignored basic psychologySlide13

Call reps at 208

markets, 1-2 times monthSource:

Glennerster and

Suri

, 2015 www.theigc/country/sierra-leone Slide14

Food prices similar to 2011/12

Source:

Glennerster and

Suri

, 2015 www.theigc/country/sierra-leone

Domestic Rice

Imported Rice

Imported rice price lower particularly in cordon areas

Consistent with results data on rice prices from household surveySlide15

More high price outliers in 2014

Source:

Glennerster and

Suri

, 2015 www.theigc/country/sierra-leone

Slide16

Household cell phone survey,

Jan-Feb ‘15Source:

Fu,

Glennerster

, Himelein, Rosas, and Suri

, 2015

LFS sample

= 4199

66% had cell phones

68% of these reachedSlide17

Decline in employment in urban areas

Source:

Fu,

Glennerster

, Himelein, Rosas, and Suri, 2015

Slide18

Nonfarm HH

enterprises hit badly Source:

Fu,

Glennerster

, Himelein, Rosas, and Suri

, 2015

P

ercent of HH with non-farm business no longer operating rose from 4% to 12%

1/3

cite

Ebola

as

reason their business no longer operates

Average business revenues shrunk by 40%

>90% urban women worked in non-farm HH enterprises pre-ESlide19

Little evidence of impact on ag

Ebola coincided with the growing and harvest season93 percent of farming households grow riceIn Nov more

than half

had

rice in field, mainly because of rain (72%), not EbolaMore than half farming HH hired outside laborSome cite labor constraints for harvest14% labor constraints in HH vs. 6% labor constraint in communityno significant differences across quarantine areasMost farmers never sell rice, prod estimates unreliableNo clear signs of probs in cocoa but sample smallSlide20

Economic impacts uncorrelated with disease burden

No difference in range of different economic outcomes between cordon vs noncordon areasOnly difference is imported rice prices are lower in cordon areas, possibly because of food assistance

Main differences between urban and nonurban

In Liberia similar declines in employment and revenue in badly hit and less badly hit (

xxxxx, Werker, in progress)As in Sierra Leone biggest impacts in capital (Monrovia)Some sectors hit worse than others (e.g. construction)20Slide21

Aid: 9

% HH received social assistanceSlide22

Aid correlated with Ebola and transport disruption Slide23

F

ood prices lower where food aidMatched market price data with HH assistance data

Difference-in-difference specification

Two way causality

possible:Receiving food aid reduces pricesHigh prices in an area trigger food aidWithout detailed data on timing cant separate the two

Moving from 0-100% assistance reduces rice prices by 10%

Suggests food aid on average reduced food prices by 1%

Net consumers gain from lower food prices, net producers lose

Most poor, even farmers are net consumers riceSlide24

Conclusion: role of researchers

Researchers can play and important role in providing good data in a crisis, to reduce risk of policy effort being diverted to wrong areas

But needs much faster turn around time than normal studies

Much easier if building on existing research, experience, and in country team

Good causal identification can be hard as impacts may not be correlated with direct cause of crisisBut good descriptive evidence is very valuable, especially if good pre crisis data to compare withDifferent methods can be useful: e.g. SMS, cellphone, modeling

The press may only remember the high case scenario

24Slide25

Conclusion: attention vs confidence?

Early stages of Ebola crisis showed how difficult it can be to attract the attention and support of the international community to crisisDisease spread from end April-end June with little attention

World grown weary of calls for help, only threat of total collapse gets through the noise

But risks in overplaying likely impacts

Can further reduce domestic confidence with important economic impactsIf final results not as big as predicted, risks people concluding it “was not so bad after all”Raises the stakes for the next crisis

25Slide26