Ethiopian Development Research Institute (EDRI) and International Food Policy Research Institute (IFPRI, Seventh International Conference on Ethiopian Economy, EEA Conference, June 26, 2010

1. Fantu Nisrane, Guush Berhane, Sinafikeh Asrat, Gerawork Getachew, Alemayehu Seyoum Taffesse International Food Policy Research Institute (IFPRI) (Ethiopia Strategy Support Program, ESSP-II) ESSP-II Conference Addis Ababa 22-24 October, 2009 Sources of Inefficiency and Growth in Agricultural Output in Subsistence Agriculture: A Stochastic Frontier Analysis The views expressed in this paper are those of the authors and do not represent the official position of their institution. ETHIOPIAN DEVELOPMENT RESEARCH INSTITUTE

8. ERHS Sample Villages

9. Data Description…contd . Mean Value of Output and Inputs used in Production Year Variable 1994 1995 1997 1999 2004 2009 Real value of output per household (birr) 1,144 1,214 1,836 1,687 1,811 2,559 Cultivated area (hectares) 1.2 1.2 1.9 0.9 1 1.6 Household members 16 years or older 3.3 3.3 3.9 3 2.7 3 Annual rain 12 months before survey (MLs.) 909 1008 1070 961 942 1049 Fertilizer used (KGs) 38 41.7 48.6 49.6 27.8 82.7 Number of oxen used for ploughing (count) 1.3 1.3 1.7 1.4 0.9 1.1 Average land quality (index) 2.5 2.4 2.1 2.2 2.2 2 Number of hoes owned (count) 0.8 0.9 0.9 1.3 1.1 2.8 Number of ploughs owned (count) 0.8 1.1 1.1 1.4 1.1 4.3 Participated in the extension package 0.06 0.03 0.05 0.12 0.08 0.28

10. Data Description…contd. Mean values of household, peasant association, and agroecologic specific variables used in the inefficiency equation. Variable Units Average across survey Years Sex of head of household 0 if female, 1 if male 0.79 Age of head of household Years 50 Education level of head 0 if illiterate, 1 if literate 0.18 Household size Count 6 Number of plots cultivated Count 4.3 Livestock units per household Index 3 Number of extension officers in PA Count 0.8 Was crop damaged by drought 0 if no, 1 if yes 0.15 Mean elevation (Meters) Meters 2086 Distance to nearest health center Kilometers 18 Distance to closest market Kilometers 22 Distance to nearest PA center Kilometers 20

14. Results: Production Frontier. ML parameter estimates associated with agricultural inputs used in SPF analysis. Variable Estimated Coefficient Calculated elasticity Constant 4.799 Area of cultivated land 0.225 0.225 Household members 16 years and older 0.129 0.129 Level of education 0.154 0.166 Amount of rainfall 0.350 0.350 Amount of Fertilizer used 0.002 0.082 Number of ploughing oxen 0.111 0.143 Average land quality -0.098 -0.219 Number of hoes used 0.053 0.071 Number of ploughs used 0.030 0.050 Participation in extension program 0.111 0.117

16. Results: Production Frontier … contd. ML Estimates of time and AEZ dummy variables Variable Estimated Coefficient Calculated elasticity 1995 dummy 0.314* 0.369 1997dummy 0.097*** 0.102 1999 dummy 0.040 0.042 2004 dummy 0.108** 0.115 2009 dummy -0.060 -0.056 Central Highlands 0.401* 0.493 Arussi/Bale 0.572* 0.772 Hararghe 0.785* 1.193 Enset 0.897* 1.451 Note : Estimates with *, **, and *** are significant at 1, 5, and 10 percent.

19. Results: Inefficiency Equation…contd. ML estimates of the inefficiency function parameters. Variables Coefficient Constant -11.716 Sex (Male = 1) -1.849 Age 0.030 Level of education -0.604 a Female dummy 4.524 Household size -0.222 Number of plots* log of cultivated area -0.190 Cultivated area/ number of members 16 years and older -0.004 Oxen dummy -1.787 Livestock units -0.305 Note : All coefficient estimates are significant at 1 percent except a.

20. Results: Inefficiency Equation…contd. ML estimates of the inefficiency function parameters… Contd. Number of agricultural extension agents in peasant association -0.760 b Crop affected by drought 4.104 Survey month (=1 if surveyed during harvest months) 8.797 Elevation -0.001 Distance to health center 0.111 Distance to closest market -0.071 Distance to nearest PA center 0.098 Sigma-squared (total variation in V and U) 43.095 Gamma (percentage of variance explained by u) 0.994 Log likelihood -21026 Note: All estimates are significant at 1 percent except b, which is significant at 2 percent.

22. Average efficiency estimates of farmers by AEZs and PAs. AEZ/ PA 1994 1995 1997 1999 2004 2009 Average across Years Northern Highlands 0.203 0.037 0.395 0.545 0.517 0.276 0.322 Haresaw 0.003 0.086 0.472 0.569 0.433 0.074 0.258 Geblen 0.150 0.002 0.216 0.399 0.490 0.087 0.222 Shumsheha 0.361 0.024 0.452 0.625 0.592 0.550 0.424 Central Highlands 0.415 0.265 0.393 0.568 0.605 0.549 0.47 Dinki 0.211 0.016 0.209 0.43 0.535 0.471 0.32 Debre Berhan Milki 0.434 0.255 0.341 0.65 0.654 0.521 0.473 Debre Berhan Kormargefia 0.559 0.219 0.412 0.624 0.526 0.538 0.481 Debre Berhan Karafino 0.363 0.223 0.360 0.582 0.660 0.537 0.454 Debre Berhan Bokafia 0.532 0.343 0.402 0.645 0.579 0.526 0.505 Yetemen 0.378 0.358 0.516 0.58 0.665 0.536 0.511 Turufe ketchema 0.467 0.398 0.488 0.553 0.627 0.576 0.515 Bako Tibe 0.529 0.529 Somodo 0.684 0.684

23. Average efficiency estimates of farmers by AEZs and Pas…contd. AEZ/ PA 1994 1995 1997 1999 2004 2009 Average across Years Arussi/Bale 0.388 0.317 0.526 0.439 0.538 0.603 0.473 Sirbana Godeti 0.66 0.541 0.585 0.572 0.516 0.564 0.575 Korodegaga 0.177 0.14 0.479 0.33 0.555 0.652 0.385 Oda Dawata 0.566 0.566 Hararghe 0.478 0.367 0.43 0.568 0.608 0.631 0.512 Adele Keke 0.478 0.367 0.430 0.568 0.608 0.631 0.512 Enset 0.249 0.249 0.300 0.331 0.397 0.275 0.298 Imdibir 0.312 0.143 0.269 0.163 0.393 0.291 0.262 Aze-Deboa 0.221 0.4 0.363 0.404 0.482 0.262 0.355 Adado 0.436 0.36 0.464 0.533 0.327 0.417 0.423 Gara-Godo 0.064 0.187 0.21 0.26 0.401 0.128 0.206 Do'oma 0.121 0.067 0.067 0.099 0.421 0.209 0.154 Average across Zones 0.321 0.230 0.385 0.473 0.517 0.443 0.394