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Page 1: Bibliography978-3-658-29413...Alagidede, P., Adu, G., and Frimpong, P. B. (2016). The Effect of Climate Change on Eco The Effect of Climate Change on Eco- nomic Growth: Evidence from

Bibliography Abreu, A. (2010). The New Economics of Labor Migration: Beware of Neoclassicals Bearing

Gifts. Forum for Social Economics, DOI: https://dx.doi:10.1007/s12143-010-9077-2 Adams, R. M., Hurd, B. H., Lenhart, S., and Leary, N. (1998). Effects of global climate change

on agriculture: An interpretative review. Climate Research, 11, pp.19-30. Adaptation Watch. (2015). Toward Mutual Accountability: The 2015 Adaptation Finance

Transparency Gap Report. Retrieved from www.AdaptationWatch.org on December 25, 2015.

Admassu, G., Getinet, M., Thomas, T. S., Waithaka, M., and Kyotalimye, M. (2013). Ethiopia. Chapter 6 in M. Waithaka, Michael; Nelson, G.C. Nelson; Thomas, T.S. Thomas, and M Kyotalimye (Eds.), East African Agriculture and Climate Change: A Comprehensive Analysis (pp.149-182). Washington, DC: International Food Policy Research Institute.

Afful-Koomson, T. (2015). The Green Climate Fund in Africa: what should be different? Cli-mate and Development, 4, pp.367–379

Ahmed, V., and O’Donoghue, C. (2010). External Shocks in a Small Open Economy: A CGE -Microsimulation Analysis. The Lahore Journal of Economics, 15(1), pp.45-90.

Alagidede, P., Adu, G., and Frimpong, P. B. (2016). The Effect of Climate Change on Eco-nomic Growth: Evidence from Sub-Saharan Africa. Environmental Economics and Pol-icy Studies, 18, pp.417-436.

Alene, A. D., and Coulibaly, O. (2009). The impact of agricultural research on productivity and poverty in sub-Saharan Africa. Food Policy, 34, pp.198–209.

Ali, N. S. (2012). Climate Change and Economic Growth in a Rain-fed Economy: How Much Does Rainfall Variability Cost Ethiopia? Retrieved from http://dx.doi.org/10.2139/ssrn.2018233

Alston, J. M., and Pardey, P. G. (2013). Agricultural R & D and Food Security of the Poor. Economic Papers, 32(3), pp.289–297.

Andre´, F. J., Cardente, M. A., and Romero, C. (2010). Economic Policy Using Applied General Equilibrium Models: An Overview. Chapter 2 in F. J. Andre´, M. A. Cardente, and C. Romero, Designing Public Policies: An Approach Based on a Multi-Criteria Analysis and Computable General Equilibrium Modeling (pp. 9-31). Heidelberg: Springer.

Annual Agricultural Sample Survey (AgSS). (2006). Volumes I-V. Central Statistics Agency. Retrieved from www.csa.gov.et. Accessed on 15 November, 2015.

Annual Agricultural Sample Survey (AgSS). (2014). Volumes I-V. Central Statistics Agency. Retrieved from www.csa.gov.et. Accessed on 15 November, 2015.

Annual Agricultural Sample Survey (AgSS). (2015). Volumes I-V. Central Statistics Agency. Retrieved from www.csa.gov.et. Accessed on 15 November, 2015.

Antle, J. M., and Capalbo, S. M. (2010). Adaptation of Agricultural and Food Systems to Cli-mate Change: An Economic and Policy. Applied Economic Perspectives and Policy, 32(3), pp.386–416.

Arndt, C., Robinson, S., and Willenbockel, D. (2011). Ethiopia’s growth prospects in a chang-ing climate: A stochastic general equilibrium approach. Global Environmental Change, 21, pp.701-710.

Auriol, E., and Warlters, M. (2012). The marginal cost of public funds and tax reform in Africa. Journal of Development Economics, 97, pp.58-72.

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020A. W. Yalew, Economic Development under Climate Change,https://doi.org/10.1007/978-3-658-29413-7

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Appendix Materials and Methods Table A1-Description of the SAM accounts

Account Notation Description ACTIVITY AGRAIN Grains: Cereals, Pulses, Oilseeds

ACCROP Cash Crops: Coffee, Chat, Tea, Spices, Sugarcane, Cotton

AENSET Enset

ALIVST Livestock: raising animals and production

AFISFOR Fishery and Forestry

AMINQ Mining and Quarrying

ACONS Construction

AMAN Manufacturing, Electricity, Water Supply

ATSER Trade Services: Wholesale, Retail Trade, Repair services

AHSER Hotels and Restaurants

ATRNCOM Transport and Communications

AFSER Financial Intermediaries

ARSER Real Estate and Renting Business

APADMN Public Administration (General)

APAGRI Public Administration (Agriculture)

ASSER Social Services: Education, Health Community Services

AOSER Other Services: services n.e.c.*

COMMODITY CGRAIN Grains: Cereals, Pulses, Oilseeds

CCCROP Cash Crops: Coffee, Chat, tea, Spices, Sugarcane, Cotton

CENSET Enset

CLIVST Livestock: Raising Animals and Production

CFISFOR Fishery and Forestry

CMINQ Mining and Quarrying

CCONS Construction

CMAN Manufacturing, Electricity, Water Supply

CMMAN Fertilizers, Coal, Natural Gas, and Petroleum Oil

CTSER Trade Services: Wholesale, Retail Trade, Repair services

CHSER Hotels and Restaurants

CTRNCOM Transport and Communications

CFSER Financial Intermediaries

CRSER Real Estate and Renting Business

CPADMN Public Administration (General)

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020A. W. Yalew, Economic Development under Climate Change,https://doi.org/10.1007/978-3-658-29413-7

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130 Appendix

CPAGRI Public Administration (Agriculture)

CSSER Social Services: Education, Health, Community Services

COSER Other Services: services n.e.c.*

TRC Transaction Costs (Transport and Trade Margins)

FACTOR FLAB0 Agricultural Labor

FLAB1 Administrative workers (e.g., Legislators, Senior Officials, Managers)

FLAB2 Professional workers (e.g., Professionals, and Technical Associate)

FLAB3 Unskilled workers (e.g. workers engaged in elementary occupation

FLAB4 Skilled workers (e.g., workers that have some skill)

FLND Cropland

FTLU Tropical Livestock Units

FCAP Nonagricultural Capital

INSTITUTION ENT Enterprises

GOV Government

RURH Rural Households

URBH Urban Households

TAX STAX Sales (Domestic Indirect) Tax

MTAX Import Tariffs and Duties

DTAX Direct (Income) Tax

S-I DSTK Stock (Inventory) Changes

S-I Savings-Investment

ROW ROW Rest of the World

Source: Author’s aggregation and disaggregation from EDRI (2009) Notes: (*) Business Activities, Other Community, Social and Personal Service activities, Private Households with Employed Persons

Page 18: Bibliography978-3-658-29413...Alagidede, P., Adu, G., and Frimpong, P. B. (2016). The Effect of Climate Change on Eco The Effect of Climate Change on Eco- nomic Growth: Evidence from

Tabl

e A

2-Re

gion

al e

cono

mic

stru

ctur

e ba

sed

on e

mpl

oym

ent i

n H

ICES

(200

5) (G

DP

valu

es a

re in

bill

ion

USD

) A

ctiv

ity

Des

crip

tion

E

TH

T

IG

AFR

A

MH

O

RM

SO

M

BN

G

SNN

P G

AM

H

AR

A

DD

D

D

GD

P1

Unw

eigh

ted

14

.05

0.77

0.

23

3.46

5.

30

0.71

0.

16

2.80

0.

07

0.03

0.

47

0.05

GD

P2

Wei

ghte

d

14.0

5 0.

71

0.37

2.

45

4.62

1.

08

0.10

2.

83

0.10

0.

07

1.63

0.

11

AG

RA

IN

Gra

ins

0.18

0.

24

0.07

0.

33

0.22

0.

07

0.42

0.

13

0.10

0.

03

0.00

0.

04

AC

CR

OP

Cas

h cr

ops

0.10

0.

03

0.06

0.

07

0.13

0.

06

0.09

0.

18

0.14

0.

06

0.00

0.

03

AEN

SET

En

set

0.01

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

05

0.01

0.

00

0.00

0.

00

ALI

VST

Li

vest

ock

0.14

0.

06

0.14

0.

12

0.21

0.

12

0.05

0.

19

0.02

0.

00

0.00

0.

02

AFI

SFO

R

Fish

ery

and

fore

stry

0.

05

0.00

0.

03

0.02

0.

02

0.24

0.

00

0.08

0.

00

0.00

0.

00

0.00

AM

INQ

M

inin

g an

d qu

arry

ing

0.01

0.

01

0.00

0.

01

0.00

0.

01

0.00

0.

00

0.01

0.

02

0.01

0.

01

AC

ON

S C

onstr

uctio

n 0.

04

0.05

0.

16

0.04

0.

02

0.02

0.

03

0.01

0.

09

0.10

0.

15

0.13

AM

AN

M

anuf

actu

ring,

ele

ctric

ity, w

ater

supp

ly

0.07

0.

06

0.11

0.

10

0.05

0.

04

0.04

0.

06

0.07

0.

05

0.06

0.

08

ATS

ER

Trad

e se

rvic

es

0.11

0.

10

0.12

0.

07

0.11

0.

15

0.07

0.

13

0.15

0.

19

0.13

0.

20

AH

SER

H

otel

s and

resta

uran

ts

0.02

0.

04

0.04

0.

03

0.02

0.

01

0.03

0.

02

0.02

0.

01

0.02

0.

03

ATR

NC

OM

Tr

ansp

ort a

nd c

omm

unic

atio

ns

0.05

0.

03

0.05

0.

02

0.04

0.

08

0.03

0.

02

0.08

0.

11

0.18

0.

17

AFS

ER

Fina

ncia

l int

erm

edia

ries

0.02

0.

03

0.02

0.

01

0.02

0.

01

0.03

0.

00

0.02

0.

03

0.07

0.

03

AR

SER

R

eal e

state

and

rent

ing

busi

ness

0.

08

0.18

0.

05

0.08

0.

06

0.07

0.

01

0.04

0.

07

0.10

0.

17

0.11

APA

DM

N

Publ

ic a

dmin

istra

tion

(Gen

eral

) 0.

04

0.04

0.

08

0.03

0.

02

0.05

0.

09

0.03

0.

08

0.11

0.

09

0.05

APA

GR

I Pu

blic

adm

inis

tratio

n (A

gric

ultu

re)

0.01

0.

01

0.02

0.

02

0.01

0.

01

0.02

0.

01

0.02

0.

01

0.00

0.

01

ASS

ER

Soci

al se

rvic

es

0.04

0.

07

0.04

0.

03

0.04

0.

02

0.06

0.

04

0.08

0.

14

0.06

0.

06

AO

SER

O

ther

ser

vice

s 0.

03

0.05

0.

03

0.03

0.

02

0.02

0.

01

0.01

0.

03

0.03

0.

07

0.05

TOTA

L R

egio

nal G

DP

1.

00

1.00

1.

00

1.00

1.

00

1.00

1.

00

1.00

1.

00

1.00

1.

00

1.00

Sour

ce: A

utho

r’s c

ompu

tatio

n ba

sed

on H

ICES

(200

5), P

HC

(200

7), a

nd A

gSS

(200

6)

Appendix 13

1

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Tabl

e A

3-C

onsu

mpt

ion

patte

rn o

f rep

rese

ntat

ive

regi

onal

hou

seho

lds (

valu

es in

%)

Item

E

TH

T

IG

AFR

A

MH

O

RM

SO

M

BN

G

SNN

P G

AM

H

AR

A

DD

D

D

Food

and

non

-alc

ohol

ic b

ever

ages

45

43

53

47

47

50

46

48

53

41

39

44

Alc

ohol

, tob

acco

, cof

fee,

tea,

cha

t and

buc

ktho

rn

3 2

5 3

3 12

3

4 3

10

1 7

Clo

thin

g an

d fo

otw

ear

5 6

6 4

6 6

5 5

4 4

5 6

Hou

sing

, wat

er, f

uel,

and

ener

gy

22

19

21

21

21

21

19

25

22

23

29

27

Furn

ishi

ng, h

ouse

hold

equ

ipm

ent a

nd m

aint

enan

ce

4 5

5 4

5 5

5 4

5 4

5 4

Hea

lth a

nd m

edic

al tr

eatm

ent

1 1

1 1

1 0

2 1

1 1

1 1

Educ

atio

n 0

0 0

0 0

0 0

0 0

1 2

1

Uni

ncor

pora

ted

hous

ehol

d en

terp

rise

6 8

2 10

6

2 9

4 1

9 0

1

Oth

er g

oods

& s

ervi

ces,

recr

eatio

n, tr

ansp

orta

tion,

co

mm

unic

atio

n, re

staur

ant/h

otel

11

16

8

11

11

5 12

9

10

8 18

10

Tota

l 10

0 10

0 10

0 10

0 10

0 10

0 10

0 10

0 10

0 10

0 10

0 10

0

Sour

ce: A

utho

r’s c

ompu

tatio

n fr

om H

ICES

(201

1)

Not

es: E

TH (E

thio

pia)

, TIG

(Tig

ray

regi

onal

sta

te),

AFR

(Afa

r re

gion

al s

tate

), AM

H (A

mha

ra r

egio

nal s

tate

), O

RM (O

rom

ia r

egio

nal s

tate

), SO

M (S

omal

i reg

iona

l sta

te),

BNG

(Ben

shan

gul-G

umuz

reg

iona

l sta

te),

SNN

P (S

outh

ern

natio

ns, n

atio

nalit

ies,

and

peop

les

regi

onal

sta

te),

GAM

(Gam

bella

reg

iona

l sta

te),

HAR

(Har

ari r

egio

nal s

tate

), AD

D (A

ddis

Abab

a ci

ty a

dmin

istra

tion)

, and

DD

(Dir

e D

awa

city

cou

ncil)

.

13 Appendix

2

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Appendix 133 Sensitivity analysis Table A4-Sensitivity of households’ welfare effects (selected simulations)

Source: CGE simulations Note: SIM0 (Base-run), SIM1 (all import substitution and export transformation elasticities increased by 25%)), SIM2 (all import substitution and export transformation elasticities decreased by 25%), SIM3 (all factor substitu-tion elasticities increased by 25%), SIM4 (all factor substitution elasticities decreased by 25%), SIM5 (all Frisch and income elasticities increased by 25%), and SIM6 (all Frisch and income elasticities decreased by 25%). The CGE results of different simulations in the text are robust to ±25% of the elasticities of factor substitution, import substitution, export transformation, income, and Frisch parameter (see Table 4.11). I present the case for households’ welfare effects for selected simulations in Table A4. Urban households’ welfare is slightly sensitive to many of the perturbations. Urban households are slightly better off (worse off) when elasticities are increased (decreased) by 25%

Household

Simulation

Sensitivity runs (% change)

SIM0 SIM1 SIM2 SIM3 SIM4 SIM5 SIM6

RURAL EPIC-PM -9.9 -9.8 -9.8 -10.0 -9.6 -9.6 -9.8

PAG2 -2.1 -2.1 -2.2 -2 -2.5 -2 -2.3

PAGGA -0.9 -0.9 -0.9 -0.8 -1.2 -0.9 -1.0

PAGSS -0.6 -0.6 -0.6 -0.5 -0.9 -0.6 -0.7

PAGF -1.3 -1.3 -1.3 -1.1 -1.7 -1.2 -1.4

PAGD -1.6 -1.6 -1.6 -1.4 -1.9 -1.5 -1.7

PAGS -1.9 -1.9 -2 -1.8 -2.3 -1.8 -2

PAGT -2.1 -2.1 -2.1 -1.9 -2.4 -2 -2.2

URBAN EPIC-PM -11.2 -9.4 -13.6 -10.6 -12.0 -8.4 -13.0

PAG2 1.6 1.4 1.7 1.3 2.2 1.1 2.1

PAGGA 0.5 0.5 0.6 0.0 1.0 0.3 0.8

PAGSS 0.2 0.1 0.2 0.3 0.5 0.1 0.3

PAGF 2.2 2.1 2.3 1.9 2.8 1.8 2.5

PAGD -0.1 -0.2 0.0 -0.4 0.5 -0.5 0.3

PAGS 1.0 0.9 1.1 0.7 1.6 0.5 1.4

PAGT 1.1 1.0 1.2 0.8 1.8 0.7 1.7

TOTAL EPIC-PM -10.2 -9.7 -10.7 -10.1 -10.2 -9.3 -10.6

PAG2 -1.2 -1.2 -1.2 -1.2 -1.4 -1.3 -1.2

PAGGA -0.6 -0.6 -0.6 -0.5 -0.7 -0.6 -0.6

PAGSS -0.4 -0.4 -0.4 -0.4 -0.5 -0.4 -0.4

PAGF -0.4 -0.4 -0.4 -0.4 -0.6 -0.5 -0.4

PAGD -1.2 -1.2 -1.2 -1.2 -1.3 -1.3 -1.2

PAGS -1.2 -1.2 -1.2 -1.2 -1.3 -1.3 -1.2

PAGT -1.3 -1.3 -1.3 -1.3 -1.4 -1.3 -1.3

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134 Appendix compared to the base-run. Compared to other sensitivity runs, urban households’ welfare is relatively sensitive to income elasticities and Frisch parameter (SIM5 and SIM6). In contrast, relatively, rural households’ welfare effects are almost insensitive to ±25% of elasticities. This is expected as 40% of rural households’ consumption accrue to home commodities which will not directly respond to the market demand and supply shocks. Rural households’ welfare effects are relatively sensitivity to changes in elasticities of factor substitution (SIM3 and SIM4). In spite of these, however, one can see that the households’ welfare effects are generally robust to changes to elasticities. There is no major change to the rural and urban households’ welfare effects (across sensitivity simulations – SIM0 to SIM6) and in overall all rankings of adaptation finance schemes.