Artificial insemination, livestock productivity and economic growth in Senegal  

François Joseph CABRALMamadou DIALLO

PLAN

1. Objective

2. Background

3. Méthodology

4. Simulation and résultats

Objective

• The aim of this research is to assess the effects of artificial insemination on livestock productivity, overall GDP growth and households well-being.

Background

• The potential to increase the productivity of livestock and livestock production is very large in sub-Saharan Africa.

• The production of meat per animal is two times less than the average obtained in developing countries and it is five times less than the average obtained in developed countries according to the species.

• The production of milk from local breeds is itself up to 10 times lower than that achieved by the European breeds (Boly and Leroy, 1999).

• Increasing productivity in the livestock sector must bring an answer to many challenges of market supply, food security and the fight against poverty, which requires borrowing techniques to improve weight and livestock productivity.

• Therefore, livestock sector plays a key role in achieving the Ecowap goals which is an average growth rate of 6% in agricultural sector so as to allow countries to in which this program is applied to halve poverty.

Background

• In Senegal, this sector has the greatest contribution to agricultural value added and incomes. Under Ecowap predictions, a growth of this sector sustained until 2015 will generate an additional flows of income of 32.2 millions of dollars in 2005.

• From bovine outputs, one can except milk (62% of milk production), leather, “livestock & hunting”.

• A program of Artificial insemination set by policymakers since 2008 has an objective to create by 2012, a population of 500 000 crossbred cows.

• It is expected from this artificial insemination program, a production of 400 million of liters of milk, 43,500 tons of meat and 120,000 pieces of leather.

• The cumulative insemination since 2008 to the end of 2012 totaled 107,000 cattle inseminated which is equal just to 1/5 of the original target of 500,000 cattle.

Background • Attempts to endogeneously integrate innovation in economic analysis has

been made through several approaches .

• For Arrow (1962), knowledge on the TFP is the accidental product of experience in the production of new capital goods. He qualifies this phenomenon as a process of "learning by doing".

• For Frankel (1962), the accumulation of capital leads to an increase of knowledge.

• However, it’s really with Romer (1990) that we know that technical progress and innovation is at the heart of economic growth. The author assumes that technical progress comes from rationality of agents who meet the incentives issued by the market. The model therefore includes a rather endogenous technical progress.

Background

• Traditional farming is often characterized by the coexistence of two systems: - the transhumant system that is characterized by high mobility and a weak link with agriculture and

- a sedentary system that can be mixed and combined with different food crops or annuity (Douhoux and Hounsou, 1993; Chentouf et al, 2004).

• The literature on the livestock activity remains divided on the impact of a number of variables on the productivity of animals. Among these variables, we find age at first calving and calving interval (Dehoux and Hounsou , 1993; Sow et al , 1988) and lactation (Dehoux and Hounsou, 1993), the rate of withdrawal (Dekhili and Dekhili 2003), he fertility rate (Senussi, 2004).

Background

• Traditionally, animal reproduction biotechnologies include four generations: an artificial insemination, the embryo transfer, in vitro fertilization and transgenesis (Thibier and Guerin , 1993). The AI is the biotechnology breeding most widely used worldwide and is one of the effective tools for disseminating genetic material (Lofti et al , 1996).

• In Senegal, only two genetic improvement techniques are used. It is artificial insemination (AI) and embryo transfer (Beye et al , 2013) but the one that policymakers use for national purpose is AI program.

Background • Livestock sector and its related sectors (meat, milk and leather) account for

about 4.7% of GDP

VAj/XSj VAj/VA crops 84.5% 9.9% fishery 56.8% 1.8% traditional cow 49.8% 0.1% metis cow 89.7% 0.9% ovine 86.8% 0.5% goat 86.8% 0.3% Cameline-porcine 85.3% 0.1% Equine 85.3% 0.0% traditional poultry 83.3% 0.4% industrial poultry 60.7% 0.3% other type of livestock 67.7% 0.3% Processed meat 58.3% 1.5% Processed fish 41.3% 1.7% Leather 56.1% 0.2% Processed milk 4.8% 0.1% Other industry 18.7% 17.4% Tradable services 59.6% 46.8% Non radable services 77.3% 17.8% Total

100%

Background • more wages from skilled labor and non skilled wages to urban households

and capital. 80% is owned by cow capital by Senegal sylvo pastoral area. • Basket consumption structure…

labsq labnq cappra capprelb capprela capprna cappu land

firm 0.0% 0.0% 0.0% 0.0% 0.0% 18.1% 100.0% 0.0%

Dakar 65.9% 35.1% 0.0% 0.0% 0.0% 43.1% 0.0% 0.0%

ACU 13.6% 47.8% 0.0% 0.0% 0.0% 24.8% 0.0% 0.0%

BA 1.7% 5.5% 40.2% 16.1% 20.8% 6.2% 0.0% 56.9%

Niay 0.5% 1.4% 2.9% 1.2% 12.6% 1.0% 0.0% 3.4%

Casa 1.8% 2.7% 28.1% 23.6% 18.9% 2.6% 0.0% 16.6%

ZSP 0.2% 5.0% 14.6% 36.2% 16.4% 1.0% 0.0% 5.1%

SO 15.0% 0.1% 6.8% 9.2% 17.0% 0.6% 0.0% 4.1%

Fleuv 1.3% 2.4% 7.4% 13.6% 14.5% 2.6% 0.0% 13.9%

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Dakar ACU BA Niay Casa ZSP SO Fleuv

crops 12% 17% 18% 12% 21% 22% 13% 21% fishery 10.6% 10.7% 7.2% 7.4% 6.5% 0.2% 2.7% 6.5% traditional cow 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% metis cow 0.3% 0.2% 0.2% 0.1% 0.2% 8.7% 0.1% 0.2% ovine 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.0% 0.1% goat 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Cameline-porcine 0.1% 0.0% 0.0% 0.0% 0.0% 0.1% 0.0% 0.0% Equine 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% traditional poultry 0.7% 0.6% 0.5% 0.4% 0.6% 0.7% 0.3% 0.6% industrial poultry 0.6% 0.5% 0.4% 0.3% 0.5% 0.5% 0.3% 0.5% other type of livestock 0.9% 0.8% 0.7% 0.5% 0.7% 0.8% 0.4% 0.7% Processed meat 2.6% 2.3% 1.9% 1.4% 2.2% 2.3% 1.2% 2.2% Processed fish 0.4% 0.4% 0.3% 0.2% 0.3% 0.4% 0.2% 0.3% Leather 6.4% 7.4% 5.4% 6.3% 5.0% 5.6% 2.8% 5.0% Processed milk 4.3% 4.9% 3.6% 4.2% 3.3% 3.7% 1.9% 3.3% Other industry 1.4% 1.2% 1.1% 1.2% 1.0% 1.0% 0.5% 1.0% Tradable services 1.4% 1.6% 1.2% 1.4% 1.1% 1.2% 0.6% 1.1% Non radable services 58.7% 52.5% 59.4% 64.5% 57.7% 53.1% 76.0% 57.7% Total 100% 100% 100% 100% 100% 100% 100% 100%

Méthodologie• Based on Romer’s model, we try to endogenously introduce diffusion of innovation

through artificial insemination in livestock sector technology. The artificial insemination, as it comes from government R&D efforts, can be supposed also a non rival good and is quite non exclusive.

• As the program of artificial insemination (AI) relies mainly on budgetary efforts, the rate of increase of insemination is supposed to be a function of expenditures devoted to R&D

RDAI

IA ˆ

RDAI

IATFP

ˆ

ttr

t

cow KDpriv

KDpubGRD*t

cowtcow AA

KLCowM

KLCowM

KLCowM t

CowMKL

CowMt

CowMKL

CowMKLt

CowMtmetiscow KDCLDCAVA ___

1

_____ 1

.

Methodology• CGE• 2 types of labour

– qualified labour– qualified labour

• 3 types of capital – private agricultural capital – private metis cow capital – private non metis cow capital – private non agricultural capital – public capital– Land

15 sectors

crops fishery traditional cow metis cow ovine goat Cameline-porcine Equine traditional poultry industrial poultry other type of livestock Processed meat Processed fish Leather Processed milk Other industry Tradable services Non radable services

Simulation et résultats

Ratio of RD/KD in cow metis sub-sector has been multiplied by 3.07 between 2009 and 2012. Simulation : teta_r increase by 3.07 for 4 periods.

2009 2010 2011 2012 teta_r 2012/2009

teta_r (RD/KD) 0.30 0.51 0.70 0.91 3.07

Simulation et résultats

Change in GDP (w.r.t the BAU) Period 1 2 3 4 5 6 7

Change in GDP 0 0 0 -0.172 0.109 -0.03 0.013

Change in value added (w.r.t the BAU)

1 2 3 4 5 6 7

crops 0 0 0 0.092 0.08 0.094 0.098 fishery 0 0 0 0.107 -0.005 0.033 0.022 traditional cow 0 0 0 0.121 0.093 0.07 0.051 metis cow 0 0 0 15.303 16.341 17.452 18.588 ovine 0 0 0 -8.826 -9.921 -11.019 -12.122 goat 0 0 0 -8.789 -9.881 -10.975 -12.075 Cameline-porcine 0 0 0 0.149 0.16 0.17 0.178 Equine 0 0 0 0 0 0 0 traditional poultry 0 0 0 0.029 0.039 0.039 0.041 industrial poultry 0 0 0 0.002 0.047 0.035 0.041 other type of livestock 0 0 0 0.034 0.024 0.029 0.028 Processed meat 0 0 0 1.842 1.819 1.892 1.937 Processed fish 0 0 0 0.027 0.009 0.017 0.017 Leather 0 0 0 0.077 0.022 0.045 0.041 Processed milk 0 0 0 1.465 1.372 1.424 1.434 Other industry 0 0 0 0.112 0.036 0.061 0.053 Tradable services 0 0 0 0.037 0.005 0.016 0.012 Non radable services 0 0 0 -0.047 -0.126 -0.106 -0.119

Simulation et résultatsChange in local sales (w.r.t the BAU)

1 2 3 4 5 6 7 crops 0 0 0 0.094 0.085 0.097 0.103 fishery 0 0 0 0.07 0.515 0.393 0.452 traditional cow 0 0 0 0.059 0.053 0.048 0.044 metis cow 0 0 0 6.486 6.679 6.936 7.194 ovine 0 0 0 1.085 0.957 0.897 0.818 goat 0 0 0 1.137 1.007 0.949 0.87 Cameline-porcine 0 0 0 0.149 0.16 0.17 0.178 Equine 0 0 0 0 0 0 0 traditional poultry 0 0 0 0.029 0.039 0.039 0.041 industrial poultry 0 0 0 -0.001 0.042 0.031 0.037 other type of livestock 0 0 0 0.027 0.028 0.029 0.03 Processed meat 0 0 0 1.704 1.794 1.829 1.883 Processed fish 0 0 0 0.015 0.029 0.027 0.03 Leather 0 0 0 0.063 0.031 0.045 0.044 Processed milk 0 0 0 1.334 1.248 1.295 1.304 Other industry 0 0 0 0.112 0.042 0.065 0.057 Tradable services 0 0 0 0.023 0.007 0.012 0.01 Non radable services 0 0 0 -0.047 -0.126 -0.106 -0.119 egg 0 0 0 0.489 0.903 0.799 0.859 raw milk 0 0 0 4.222 4.255 4.309 4.379

Change in returns to factors (w.r.t the BAU)

1 2 3 4 5 6 7

cappra 0 0 0 0.07 0.116 0.084 0.079 capprelb 0 0 0 -12.692 -9.828 -7.579 -5.674 capprela 0 0 0 -5.666 -5.138 -4.876 -4.566 capprna 0 0 0 -0.066 0.054 0.01 0.02 cappu 0 0 0 -0.166 -0.05 -0.076 -0.058 land 0 0 0 0.053 0.143 0.135 0.154 labsq 0 0 0 -0.253 0.008 -0.071 -0.043 labnq 0 0 0 -0.009 0.045 0.027 0.031

Simulation et résultatsChange in nominal income national level %

0 0 0 0 0 -0.207 -0.058 -0.107 -0.091

Change in household consumer price national level %

0 0 0 0 0 -0.153 -0.064 -0.089 -0.077

Equivalent variation Ensemble national %

0 0 0 0 0 0.066 0.106 0.096 0.103

Change in nominal income

Dakar ACU BA Niay Casa ZSP SO Fleuv 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 -0.165 -0.136 -0.273 -0.501 -0.404 -0.455 -0.412 -0.355 5 -0.022 0.001 -0.073 -0.365 -0.228 -0.259 -0.274 -0.179 6 -0.066 -0.043 -0.14 -0.435 -0.294 -0.331 -0.325 -0.243 7 -0.05 -0.028 -0.121 -0.439 -0.283 -0.319 -0.315 -0.231

Change in household consumer price

Dakar ACU BA Niay Casa ZSP SO Fleuv

1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 -0.249 -0.248 -0.236 -0.194 -0.253 -1.238 -0.17 -0.253 5 -0.157 -0.161 -0.159 -0.116 -0.174 -1.157 -0.103 -0.174 6 -0.182 -0.184 -0.18 -0.137 -0.195 -1.179 -0.122 -0.195 7 -0.17 -0.173 -0.17 -0.128 -0.184 -1.17 -0.114 -0.184

Equivalent variation en %

Dakar ACU BA Niay Casa ZSP SO Fleuv 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0.076 0.107 -0.009 -0.152 -0.094 0.32 -0.025 -0.02 5 0.108 0.144 0.092 -0.122 -0.021 0.37 -0.017 0.006 6 0.101 0.135 0.061 -0.144 -0.048 0.369 -0.02 -0.003 7 0.107 0.142 0.072 -0.15 -0.044 0.386 -0.02 -0.002

Conclusions et enseignements de politique

• Production of cow increase very significantly. It also induces an increase in its multiples products (meat, milk, leather). However, this increase seems to have a depressive effect on price as income for all households tends to decrease. It occurs also that, due to the weak size of this program, price effects seem to dominate income effects.

• Winners from this program are households from sylvo pastoral rural area, other cities and groundnut belt area.

• The aim of AI program was to cover not more than 15% of the total population of cows but only 3% of the cow population is effectively covered .

• Therefore, the challenge of this program is increase its size for wide effects in the sector, on GDP and well-being.

Merci!