Technical, allocative and economic efficiency of malt barley producers in Arsi zone, Ethiopia

Figures & data

Table 1. Selected farm households distribution by district and PAs

District	Selected PAs	Total households	No. of interviewed farmers
Digalu-Tijo	Kubsa Bora	897	58
	Digalu Bora	1033	66
Lemu-Bilbilo	Koma Karra	732	47
	Dawa Bursa	835	53
	Koma Katara	810	52
	Sirbo	1006	64
	Bekoji Negesso	701	45
Total		6014	385

Table 2. The hypothesized variables of MB production efficiency and their expected signs

Variable	Measurement	Expected sign	Related empirical studies
Sex	Dummy	+	Asfaw et al. (2019), Bezu et al. (2021)
Farming experience	Years	+	Gebretsadik (2017), Dessale (2019)
Family size	Adult equivalent	±	Debebe et al. (2015), Wana and Sori (2018), Okello et al. (2019)
Education	Years	+	Gela et al. (2019), Tenaye (2020)
Credit	Dummy	+	Tesema et al. (2019), Tafesse et al. (2021)
Extension contact	No. of contacts	+	Ahmed et al. (2014), Wana and Sori (2018)
Distance to market	Walking minutes	-	Teferra et al. (2018), Wollie et al. (2018)
Off/non-farm income	Birr per year	±	Asfaw et al. (2019), Gela et al. (2019), Wai and Hong (2020)
Landholding size	Hectares	+	Elemo et al. (2017), Tesema et al. (2019)
Livestock holding	TLU	+	Bezu et al. (2021),Tafesse et al. (2021)
Cooperativ membership	Dummy	+	Gebretsadik (2017), Gela et al. (2019)
Proximity to homestead	Walking minutes	-	Wollie et al. (2018), Tesema et al. (2019)
Fertility of soil	Categorical	+	Tenaye (2020), Bezu et al. (2021)

Table 3. Descriptive statistics of input and explanatory variables

Variables	Unit	Mean	Std. Deviation
Output	Kilograms	1816.85	1214.68
Malt barley farm size	Hectares	0.82	0.54
Labor	Man-days	40.66	24.22
Seed	Kilograms	77.65	49.85
Oxen	Oxen-days	17.75	12.07
Chemical	Liters	0.64	0.61
Fertilizer	Kilograms	131.83	84.54
Age	Years	44.10	10.90
Family size	Adult equivalent	4.66	1.58
Education	Years	4.61	3.41
Total landholding	Hectares	2.40	1.17
Livestock	TLU	8.53	3.65
Sex	Dummy (1 = male)	0.90	0.31
Cooperative membership	Dummy (1 = yes)	0.41	0.49
Credit access	Dummy (1 = yes)	0.22	0.41

Source: Results from sample survey data (2021).

Table 4. Maximum likelihood and OLS estimates of production function

Variables	ML estimates		OLS estimates
	Coeff.	Std. Error	Coeff.	Std. Error
Constant	5.5374***	0.2008	5.3053***	0.1965
ln (Land)	0.4547***	0.0421	0.4445***	0.0428
ln (Labor)	0.3152***	0.0455	0.3383***	0.0448
ln (Seed)	0.0800**	0.0380	0.0813**	0.0405
ln (Oxen)	0.1457***	0.0420	0.1354***	0.0430
ln (Chemical)	0.0029	0.0129	0.0027	0.0134
ln (Fertilizer)	0.0532***	0.0176	0.0586***	0.0182
Wald χ^2 statistic	5985.27***
Sigma2	.0422465	.0068202
Lambda	1.774589	.0380359
Log likelihood	194.36

Source: Results from sample survey data (2021).

Notes: ** and ***indicate significance at 5% and 1% levels, respectively.

Table 5. Distribution of technical, allocative and economic efficiencies

Efficiencies range	Frequency			Percentage
	TE	AE	EE	TE	AE	EE
0.31–0.40	-	-	3	-	-	0.78
0.41–0.50	-	1	21	-	0.26	5.45
0.51–0.60	-	14	55	-	3.64	14.29
0.61–0.70	5	40	84	1.30	10.39	21.82
0.71–0.80	61	99	131	15.84	25.71	34.03
0.81–0.90	152	172	89	39.48	44.68	23.12
0.91–1.00	167	59	2	43.38	15.32	0.52
Total	385	385	385	100	100	100
Operating below mean	158	158	171	41.04	41.04	44.41
Operating above mean	227	227	214	58.96	58.96	55.58
Mean	0.871	0.806	0.706
Std. Dev.	0.066	0.096	0.119
Min.	0.663	0.487	0.365
Max.	0.966	0.954	0.913

Source: Results from sample survey data (2021).

Table 6. Tobit regression results of the determinants of efficiencies

Variable	Technical Efficiency		Allocative Efficiency		Economic Efficiency
	Coefficient (Std. Error)	Marginal Effects	Coefficient (Std. Error)	Marginal Effects	Coefficient (Std. Error)	Marginal Effects
Education	0.00358*** (0.0010)	0.00348 0.00311 0.00459	0.0040*** (0.0015)	0.0039 0.0034 0.0037	0.00648*** (0.00178)	0.00640 0.00599 0.00224
Family size	0.00123 (0.0019)	0.00120 0.00107 0.00159	0.0063** (0.0031)	0.0061 0.0054 0.0058	0.00669* (0.00357)	0.00661 0.00618 0.00232
Credit	0.01461** (0.0064)	0.01411 0.01245 0.02213	0.0283*** (0.0103)	0.0271 0.0235 0.0313	0.03581*** (0.01192)	0.03520 0.03247 0.01619
Extension contact	0.00200* (0.0011)	0.00195 0.00174 0.00257	-0.0023 (0.0018)	-0.0022 -0.0020 -0.0021	-0.00043 (0.00211)	-0.00043 -0.00040 -0.00015
Off/non-farm income	0.00079** (0.0003)	0.00077 0.00069 0.00102	-0.0007 (0.0005)	-0.0006 -0.0006 -0.0006	-0.00003 (0.00061)	-0.00003 -0.00002 -0.00001
Distance from market	-0.00053*** (0.0001)	-0.00052 -0.00046 -0.00068	-0.0009*** (0.0002)	-0.0009 -0.0008 -0.0009	-0.00118*** (0.00021)	-0.00117 -0.00109 -0.00041
Landholding	-0.00316 (0.0028)	-0.00307 -0.00275 -0.00406	-0.0256*** (0.0046)	-0.0248 -0.0219 -0.0234	-0.02468*** (0.00530)	-0.02437 -0.02281 -0.00854
Livestock size	0.00296*** (0.0009)	0.00287 0.00257 0.00380	0.0050*** (0.0014)	0.0049 0.0043 0.0046	0.00669*** (0.00166)	0.00660 0.00618 0.00231
Cooperative membership	0.01244** (0.0056)	0.01207 0.01076 0.01679	-0.0072 (0.0091)	-0.0070 -0.0062 -0.0065	0.00434 (0.01045)	0.00428 0.00401 0.00152
Proximity to homestead	-0.00134*** (0.0002)	-0.00130 -0.00117 -0.00172	-0.0007** (0.0003)	-0.0007 -0.0006 -0.0007	-0.00167*** (0.00040)	-0.00165 -0.00154 -0.00058
Fertility of soil	0.02838*** (0.0051)	0.02760 0.02469 0.03646	0.0390*** (0.0082)	0.0378 0.0334 0.0357	0.05520*** (0.00946)	0.05451 0.05101 0.01910
Constant	0.82177*** (0.0208)		0.7562*** (0.0336)		0.62095*** (0.03874)
Log likelihood	610.91		426.30		371.72

Notes: ***, **and *indicate significance at 1%, 5% and 10% levels, respectively.

The table presents only values of significant variables. The marginal effects in cells represent Total change $\left[\frac{\mathrm{\partial }E(y)}{\mathrm{\partial }{X}_j}\right]$, expected change $\left[\frac{\mathrm{\partial }E(y^{\ast })}{\mathrm{\partial }{X}_j}\right]$, and probability change $\left[\frac{\mathrm{\partial }\left[\varphi (Z_U)-\varphi (Z_L)\right]}{\mathrm{\partial }{X}_j}\right]$

Source: Results from sample survey data (2021).

1 Summary of variables for efficiency score estimation

Variable	Measurement
ln(Total malt barley output)	Kilograms
ln(Total land covered with malt barley)	Hectares
ln(Total labor used)	Man-days
ln(Quantity of fertilizer used)	Kilograms
ln(Quantity of malt barley seed used)	Kilograms
ln(Oxen-power used)	Oxen-days
ln(Amount of agro-chemicals used)	Liters
ln(Total cost of MB production)	Birr
ln(Price of land used)	Birr per hectare
ln(Price of total labor used)	Birr per man-equivalent
ln(Price of fertilizer used)	Birr per kilogram
ln(Price of seed used)	Birr per kilogram
ln(Price of oxen-power used)	Birr per oxen-day
ln(Price of agro-chemicals used)	Birr per liter

Asfaw, M., Geta, E., & Mitiku, F. (2019). Economic efficiency of smallholder farmers in wheat production: The case of Abuna Gindeberet district, Oromia National Regional State, Ethiopia. International Journal of Environmental Sciences & Natural Resources, 16(2), 41–51. https://doi.org/10.19080/IJESNR.2019.16.555932

 Google Scholar

Bezu, K. H., Chala, B. W., & Wakjira, M. (2021). Economic efficiency of wheat producers: The case of Debra Libanos district, Oromia, Ethiopia. Turkish Journal of Agriculture - Food Science and Technology, 9(6), 953–960. https://doi.org/10.24925/turjaf.v9i6.953-960.4244

 Google Scholar

Gebretsadik, D. (2017). Technical, allocative-and economic efficiencies and sources of inefficiencies among large-scale sesame producers in Kafta Humera District, western zone of Tigray, Ethiopia: Non-parametric approach. International Journal of Scientific and Engineering Research, 8(6), 2041–2061.

 Google Scholar

Dessale, M. (2019). Analysis of technical efficiency of small holder wheat-growing farmers of Jamma district, Ethiopia. Agriculture and Food Security, 8(1), 1–8. https://doi.org/10.1186/s40066-018-0250-9

 Google Scholar

Debebe, S., Haji, J., Goshu, D., & Edriss, A. K. (2015). Technical, allocative, and economic efficiency among smallholder maize farmers in Southwestern Ethiopia: Parametric approach. Journal of Development and Agricultural Economics, 7(8), 282–291. https://doi.org/10.5897/JDAE2015.0652

 Google Scholar

Wana, H., & Sori, O. (2018). Analysis of economic efficiency of sesame (Sesamum Indicum L) production in Babogambel district of West Wollega zone, Oromia region, Ethiopia. Food Science and Quality Management, 76(1), 47–61. https://www.iiste.org/Journals/index.php/FSQM/article/view/42996

 Google Scholar

Okello, D. M., Bonabana-Wabbi, J., & Mugonola, B. (2019). Farm level allocative efficiency of rice production in Gulu and Amuru districts, northern Uganda. Agricultural and Food Economics, 7(1), 1–19. https://doi.org/10.1186/s40100-019-0140-x

 Google Scholar

Gela, A., Haji, J., Ketema, M., & Abate, H. (2019). Technical, allocative and economic efficiencies of small-scale sesame farmers: The case of west Gondar zone, Ethiopia. Review of Agricultural and Applied Economics, 22(2), 10–17. https://doi.org/10.15414/raae.2019.22.02.10-17

 Google Scholar

Tenaye, A. (2020). Technical efficiency of smallholder agriculture in developing countries: The case of Ethiopia. Economies, 8(34), 1–27. https://doi.org/10.3390/economies8020034

 Google Scholar

Tesema, T., Kebede, T., & Shumeta, Z. (2019). Economic efficiency of smallholder farmers in maize production in Gudeya Bila district, Oromia national regional state, Ethiopia: Parametric approach. Journal of Applied Agricultural Economics and Policy Analysis, 2(1), 1–7. https://doi.org/10.12691/jaaepa-2-1-1

 Google Scholar

Tafesse, A., Mena, B., Belay, A., Aynekulu, E., Recha, J. R., Osano, P. M., Darr, D., Demissie, T. D., Endalamaw, T. B., & Solomon, D. (2021). Cassava production efficiency in southern Ethiopia: The parametric model analysis. Frontiers in Sustainable Food Systems, 5, (1–12). https://doi.org/10.3389/fsufs.2021.758951

 Google Scholar

Ahmed, M. H., Lemma, Z., & Endrias, G. (2014). Technical efficiency of maize producing farmers in Arsi Negelle, central rift valley of Ethiopia: Stochastic frontier approach. Agriculture & Forestry, 60(1), 157–167 http://89.188.43.75/agricultforest/20140308-014%20Ahmed%20et%20al.pdf

 Google Scholar

Teferra, B., Legesse, B., Haji, J., & Kassie, G. T. (2018). Farm level efficiency of crop production in the central highlands of Ethiopia. American Journal of Rural Development, 6(2), 49–58. https://doi.org/10.12691/ajrd-6-2-4

 Google Scholar

Wollie, G., Zemedu, L., & Tegegn, B. (2018). Economic efficiency of smallholder farmers in barley production in Meket district, Ethiopia. Journal of Development and Agricultural Economics, 10(10), 328–338. https://doi.org/10.5897/JDAE2018.0960

 Google Scholar

Wai, K. Z., & Hong, S. (2020). Measuring the efficiency and determinants of rice production in Myanmar: A translog stochastic frontier approach. Korean Journal of Agricultural Science, 48(1), 59–71. https://doi.org/10.7744/kjoas.20200100

 Google Scholar

Elemo, M., Tsegaye, R., & Mohammed, T. (2017). A study of economic efficiency of mixed crop-livestock production system in the north eastern highlands of Ethiopia. African Journal of Soil Science, 5(2), 256–366. https://storage.internationalscholarsjournals.org/?id=257634158463917257.pdf&op=1

 Google Scholar