THE IMPACT OF TECHNOLOGY PROGRESS AND CLIMATE CHANGE ON SUPPLY RESPONSE IN YEMEN  PASQUALE LUCIO SCANDIZZOCentre for Economic and International Studies (CEIS), Faculty of Economics, University of Rome "Tor Vergata”

DANIELE CUFARI Department of Economics Law and Institutions, Faculty of Economics, University of Rome “Tor Vergata”

Yemen 

Source: WFP

Yemen is one of the poorest countries in the World:• GDP per capita around 600 USD• Small  land based: around 1.2 Mln Has of arablel and against 24 Mln of 

population• Oil  sector  is  dominant:  around  27%  of  GDP  and  90%  of  merchandise 

exports• Scarcity of water and infrastructure

Yemen Agroecological zones

Source: IFPRI

1.  Upper Highlands (above  1,900  m):  temperate,  rainy  summer  and  a  cool,  moderately  dry winter2.  Lower Highlands (below  1,900  m):  Precipitation  ranges  from  0  mm  to  400  mm  and  the temperature in the summer reaches 40°C.3. Red Sea and Tihama Plain: tropical, hot and humid climate, whilerainfall averages only 130 mm annually and occurs in irregular, torrential storms.4. Arabian sea cost:  average temperature of 25°C in January and 32°C in June, with an average annual rainfall of 127 mm5. Internal Plateau: characterized by a desert environment 6. Desert

Climate  change  poses  a  significant  threat  to  Yemen’s  development,  with  rising  temperature projections and increasing in variance of rainfallClimate-related  hazards  in  Yemen  include  extreme  temperatures,  floods,  landslides,  sea  level rise, and droughts.

Volatility increase and impact on agricultural productivity

The volatility of the yield is negatively related with the productivity

This negative effect, is enhanced by the increase of the variation of the rain, especially for the planting season  

Dependent Variable: NET VALUE OF PRODUCTION  Method: Least Squares    Sample: 1 90      Included observations: 90    

                  

  Coefficient Std. Error t-Statistic Prob.                    

FARM_SIZE 10661.47 1209.997 8.811153 0.0000((FARM_SIZE))^2 -400.2723 129.3618 -3.094208 0.0027VARIABILITY OF SORGHUM YIELD -4.109969 1.349881 -3.044690 0.0031VARIABILITY OF WHEAT YIELD -11.38326 3.574484 -3.184589 0.0020 HIGH RAINFALL VARIATION -5380.643 2233.962 -2.408565 0.0182

                  

R-squared 0.582808  Adjusted R-squared 0.563175  

Volatility increases

Average Effects on farm productivity

Percentages US dollars

sorghum 20% -4% -270,4176

50% -10% -676,044

100% -20% -1352,088

Wheat 20% -4% -283,93848

50% -11% -709,8462

100% -21% -1419,6924

Example of impact Impact of Climate Change (Authors’ estimates on unbalanced Panel data)

Rainfall  variance  has  a  negative  effect  in  the winter  and  the  fall  and  the variation of rainfall in the spring,  a likely  manifestation of climate change, has also a negative effect

Dependent variable: Logarithm of maize yieldIndependent  variables:  logarithm  of  average  quantity  and  variance  of rainfall in critical seasons

Coefficient T-statistic

Constant -2 -5.40

Winter average 0.65 5.67

Spring+Fall average 0.63 4.42

Winter+Fall variance -0.25 -3.97

Variation of average spring rainfall -0.22 -1.81

R-squared 0.87  

Field Survey Descriptive statistics

Unit N° of observations Mean Std. Dev.

Farm size Ha 90 1.18 1.69 Persons living from farm activity Nb 90 11 8 Persons working in the farm Nb 90 4 3 N° of cropping seasons Nb 89 2 1 N° of cultivated crops Nb 391 6 3 Value added USD 90 6261 12910 Ave. St. Dev. Value Added USD 90 5023 7604 Per capita Value Added USD 90 529 965 Log Value Added USD 81 8 2 St. Dev. Value Added USD 81 1 1 Cultivated land under cereals Ha 90 0.49 0.57 Cultivated land under pulses Ha 90 0.10 0.26 Cultivated land under vegetables Ha 90 0.08 0.47 Cultivated land under fruits Ha 90 0.23 0.60 Cultivated land under coffee Ha 90 0.01 0.02 Cultivated land under qat Ha 90 0.28 0.67

Unit N° of observations Mean Std. Dev.

Cost of water USD/year 37 1421 1649 Cost of fertilizers USD/year 51 71 82 Cost of chemicals USD/year 46 104 126 Cost of hired work USD/year 65 233 489 Cost of land operations USD/year 35 223 292 Other costs USD/year 11 539 1002 Total costs of production USD/year 90 998 1692

Adapting to climate change: Mathematical modelAssuming that each option underlying value evolves as a Brownian Motion with zero drift and constant variance 

(1)  where j denote the j-th option and i denote the i-th farmer. The economic value of the ith farm can be represented by the equation:

(2)  where    is  the  value of  the  jth  option  to  adapt  of  the  ith  farmer  and        (Dixit  and Pindyck, 1994). For adoption To be acceptable for option j: 

(3)here At farmer level, the option value over an infinite time horizon for farmers who have not adopted (yet) is given by:

(4)   where      i.  e.  the  coefficient  estimated  in  the  regression  on  an  estimate  of  the increment of value added due to the adoption

 Econometric Results: Value Added equations

VALUE ADDED IN USD OLS TLS Constant -12587.00 -14278.00 p-value 0.00 0.00 Standard Deviation of value added 1.45 1.54 0.00 0.00 Gender (0=female, 1=male) 1829.00 0.07 Dummy high value crops (farmers growing qat, coffee, fruits and vegetables) 1353.29 0.00 Dummy terrace irrigation 2056.57 0.05 Dummy land partly owned and partly rented 4264.50 3134.16 0.00 0.097 Dummy changes of agricultural practices in response to climate change 1315.21 4727.64 0.01 0.049 Age group 15-29 3075.57 0.00 Education from 4 to 8 years 1908.04 0.01 Dummy alternative form of irrigation apart from terrace 13123.55 0.00 R-squared 0.96 0.86 Adjusted R-squared 0.95 0.85

Adapting to climate change: option values  (US $ per year)

Item

Underlying (increase in Value Added per farm)

Estimates of strike prices

Volatility Value of Option

Opportunity option: high value crops (qat, coffee, fruits and vegetables)

1353 835 0.33 815

Growth option: terrace rehabilitation

2057 1269 0.50 1373

Coping option: changes of practices in response to climate change

1315 811 0.39 787

Opportunity option: education 1908 1897 0.30 985

Option values for introducing Drought Tolerant maize (US dollars/ha)

Variable Obs Mean Std. Dev. Min Max

Valueadded/ha 32 2257.081 1980.829 73.77849.05

 

Val. added GM/ha 32 2708.498 2376.994 88.44 9418.86

Difference of VA 32 451.4163 396.1647 14.74 1569.81

Beta 32 1.37 0 1.37 1.37

hurdle 32 3.69 0 3.69 3.69

Underlying 32 15377.96 13495.78 502.14 53477.16

Estim. investments 32 4166.212 3656.293 136.04 14488.09

option value 35% 32 11320.98 9935.358 369.666839368.94

 option value 55% 32 11958.85 10495.16 390.4953 41587.15option value 75% 32 12507.17 10976.37 408.3998 43493.96

Adapting to climate change: Option Values (US dollars per year)

Underlying (increase in Value Added per farm)

Estimates of strike prices

Volatility Option value

Volatility +

Option value +

Volatility ++

Option value ++

Opportunity option: high value crops (qat, coffee, fruits and vegetables)

1353 835 33% 815 53% 916 73% 988

Opportunity option: adoption of drought tolerant maize

1358 416 35% 1131 55% 1196 75% 1250

Growth option: terrace rehabilitation

2057 1269 50% 1373 70% 1485 90% 1594

Coping option: changes of practices in response to climate change

1315 811 39% 787 59% 898 79% 993

Opportunity option: education

1908 1897 30% 985 50% 1188 70% 1335

Option values contribution

Option value Option value   + Option value  ++0

1000

2000

3000

4000

5000

6000

7000

Opportunity option: education Coping option: changes of practices in response to climate changeGrowth option: terrace rehabilitation Opportunity option: adoption of drought tolerant maizeOpportunity option: high value crops (qat, coffee, fruits and vegetables)

CONCLUSIONS

• Climate Change threats provide the incentives to adapt trough a class of projects, which construct capabilities and open real options as a major source of opportunities.

• The  options  to  adapt  to  climate  change  in  Yemen,  exist  not  only  as  a reactive  and  coping  responses  of  existing  farming  system,  but  also  as accumulation  of  capabilities  to  flexibly  create  a  whole  set  of  new farming systems

• The adoption of the GM technology appears to be an especially valuable option for the country to adapt to some of the harshes conditions that may be determined by climate change 

Thank you for your attention