Stochastic Production Frontier Model Research Articles

Effect of poverty level and food insecurity status on poultry farmers' response to high feed costs in south-west Nigeria

The rising cost of feed is a major challenge in Nigeria’s poultry industry. It impacts production costs and threatens the industry's sustainability and food security. Implementing effective coping strategies for rising feed costs is crucial for poultry enterprises. This study examines poverty level, food insecurity status, and poultry farmers’ coping strategies to high feed costs in South-West, Nigeria. A multistage sampling procedure was employed for this study. Three states (Lagos, Ogun, and Oyo) were purposively selected from the six states in the South-West of Nigeria. In the second stage, 575 poultry farmers from all Poultry Association of Nigeria zones were selected using a simple random sampling technique. Data on the production activities of poultry farms were collected from the farmers using a structured questionnaire. Data were analyzed using descriptive statistics, mean per capita household expenditure, household food insecurity access scale, double log regression, multinomial logistic regression, and stochastic frontier production models at p< 0.05. The results of data analysis showed that 48% of the poultry farmers adopted mixed farming to cope with the rising feed cost while 24.7%, 16.1% and 6.2% adopted the use of finished feed, downsizing their flock size and at the verge of exiting the venture, respectively, while 5.2% did not change strategy. At a poverty line of ₦48,500/year, 70.7% of the poultry farmers were poor. The results also indicated that 25.8% of the poultry farmers were food secure, 1.6%, 27.2% and 45.4% were mildly, moderately and severely food insecure, respectively. The multinomial logit analysis results showed that sex (p<0.1), age (p<0.05), education (p<0.01), farm size (p<0.05), food security status (p<0.01), and access to credit (p<0.01) were factors for coping with rising feed costs in South-west Nigeria. The study concludes that the more educated the poultry farmers are the likely they will adopt the most suitable strategies to reduce the effect of rising feed costs. The study recommends that poultry farmers should engage in mixed farming which enables them to be in production. Key words: Adopted strategies, Food security, Poverty level, Poultry farmers, Feed costs

A Stochastic Production Frontier Analysis of Factors That Affect Productivity and Efficiency of Logging Businesses in Virginia

Abstract Understanding the effect of the relationship between timber harvesting attributes on loggers’ productivity and efficiency is crucial for the feasibility and expansion of sustainable forest management and logging. We applied a stochastic production frontier model to firm-level operational data collected from 202 loggers in Virginia, United States, in 2019. Logging equipment value, physiographic region, tract area, number of workers and crews in the woods, college education level, and harvest type statistically increase harvesting productivity. Harvesting productivity in the Coastal Plain was the greatest of all physiographic regions, and pine clearcut productivity was statistically greater than that of hardwood thinning. On the other hand, manual felling reduces harvesting productivity. We found an average efficiency rate of 67% among firms in our sample, which is similar to that found in the literature. The estimated values can show factors that improve forest harvest productivity through better planning and investments while improving the sustainable use of inputs and resources. Study Implications: We empirically analyzed factors affecting logging productivity and efficiency in the southern US state of Virginia. Increased productivity was associated with working in the Coastal Plain physiographic region, investing in logging equipment, increasing the number of workers and crews in the woods, increasing pine clearcut as opposed to hardwood thinning, choosing optimal harvesting tract size, and having a college education as opposed to no high school degree. Manual felling reduces harvesting productivity, and average BMP implementation time does not affect harvesting productivity. Our results can be used as a guide in planning future decisions to increase logging productivity.

A flexible stochastic production frontier model with panel data

SummaryWe propose a flexible stochastic production frontier model with fixed effects for the panel data in which the semiparametric frontier is additive with bivariate interactions. To avoid potential misspecification and/or “wrong skew problem” due to distributional assumptions, we model the conditional mean of the inefficiency to depend on environmental variables and to be known up to a vector of parameters. We propose a difference‐based estimator for parameters characterizing the conditional mean of the inefficiency term, a profile series estimator, and a kernel‐based one‐step backfitting estimator for the frontier to facilitate inference. We establish their asymptotic properties and show that each component in the frontier estimated by the kernel‐based backfitting has the same asymptotic distribution as the one estimated with the true knowledge on the other components in the frontier (i.e., the oracle property). Through a Monte Carlo study, we demonstrate that the proposed estimators perform well in finite samples. Utilizing a panel of Chinese firm‐level data in 2000–2006, we apply our method to estimate the frontier and efficiency scores and conclude that export plays a significant role in reducing the efficiency of firms.

Eficiencia técnica en la ganadería de carne bovina en Uruguay

Livestock farming is the agricultural activity with the greatest individual land-use, but it faces competition from other sectors for land, and is criticized for its environmental footprint. In this global context, Uruguay emerges as an important case study, boasting a long tradition and significance in the beef export sector. Enhancing livestock productivity is imperative to mitigate environmental impacts, and bolster farm competitiveness and food production. This study delves into the technical efficiency of cattle ranches focused on cow-calf production in Uruguay during the 2011 agricultural year, with nationwide and mandatory data coverage. Using data from the 2011 General Agriculture Census we estimate a translog stochastic production frontier model encompassing key inputs (livestock units, grazing area, and labor), along with control variables such as soil suitability and infrastructure improvements. Our findings underscore the potential to augment Uruguay's beef production by an average of 26.4%, harnessing existing resources and technology while improving ranch management. Moreover, variables like the extent of reliance on livestock farming as the primary source of income of the ranch, the use of outsourced services, foreign cattle ownership ratios, and agronomic and veterinary consultation exert noteworthy significant impacts on TE.

Impact of Microdosing Practices on Technical Efficiency: An Analysis Accounting for Selection Bias Among Smallholder Maize Farmers in Burkina Faso

Smallholder maize farmers are currently confronted with the arduous challenge of managing limited financial resources while incessantly facing the issue of land degradation. To address this issue, an alternative solution has been implemented to optimize the use of chemical fertilizer by adopting microdosing. This innovative system not only helps them enhance their agricultural productivity but also allows them to protect the environment. However, it is unclear how microdosing adoption could increase the technical efficiency (TE) of maize production. Therefore, this research aims to assess how the adoption of microdosing affects the technical efficiency of maize production as well as identify the key factors that influence the technical efficiency of maize production in Burkina Faso. To achieve this goal, farm household survey data was conducted with 210 randomly selected farmers from the Plateau Central and northern regions of Burkina Faso. To account for potential selection biases that could result from both observable and unobservable factors, we used a sample selection stochastic production frontier model and a propensity score matching approach. A stochastic meta-frontier approach was applied to estimate TE differences and the technology gap between adopters and non-adopters. The findings showed that adopters of microdosing have an average efficiency of 68 percent, which is higher than the 53 percent estimated for non-adopters. Adopters of microdosing have been found to have high TE and better agricultural technology than non-adopters. The meta-frontier estimation revealed that the adoption of improved maize varieties would yield better returns. This study contributes significantly to the literature on how fertilizer microdosing affects maize productivity, as well as the policy implications of targeting and encouraging smallholder maize farmers in Burkina Faso to optimize the use of productive inputs and improve maize output by using microdosing.

Economic efficiency of smallholder okra (Abelmoschus species) production in Kaduna State, Nigeria: Implication for poverty alleviation

This study evaluated economic efficiency of smallholder okra (Abelmoschus species) production in Kaduna State, Nigeria: Implication for poverty alleviation. A multi-stage sampling technique was used to select 120 smallholder okra farmers. Primary sources of data were used. Data were analyzed using farm budgetary technique, financial analysis, stochastic production frontier model, allocative efficiency model, economic efficiency model, Tobit dichotomous regression model, and principal component model. The results show that the mean age of smallholder okra farmers was 43 years. Averagely, okra farmers had 1.8 hectares of farm land. The gross margin and net farm income of okra production per hectare was estimated at 619,325.77 Naira and 559, 194.76 Naira respectively. This signifies that the smallholder okra production was profitable. The mean technical, economic, and allocative efficiency scores were 0.7918, 0.5338, and 0.8345 respectively. The socio-economic factors influencing economic efficiency of smallholder okra production include: age (P<0.01), educational level (P< 0.10), marital status (P< 0.01), household size (P <0.01), farm size (P<0.01), and member of cooperative organization (P<0.05). The major constraints encountered by okra producers were lack of farm inputs, lack of credit facilities, and high cost of labour. The study recommended that farmers should be provided with improved variety of seeds, chemicals, credit facilities, and fertilizer inputs in order to increase their productivity and efficiency.

Impact of agricultural credit sources heterogeneity on rice production efficiency in Côte d'Ivoire

PurposeThis study examines the impact of agricultural credit on rice farmers' technical efficiency (TE) in Côte d'Ivoire by considering the heterogeneity among credit sources.Design/methodology/approachA multistage sampling technique was used to collect data from 588 randomly sampled rice farmers in seven rice areas of the country. The authors use the endogenous stochastic frontier production (ESFP) model to account for the endogeneity of access to agricultural credit.FindingsOn the one hand, agricultural credit has a significant and positive impact on rice farmers' TE. Rice farmers receiving agricultural credit have an average of 5% increase in their TE, confirming the positive impact of agricultural credit on TE. On the other hand, the study provides evidence that the impact of credit on rice production efficiency differs depending on the source of credit. Borrowing from agricultural cooperatives and paddy rice buyers/processors positively and significantly influences the TE, while borrowing from microfinance institutions (MFIs) negatively and significantly influences the TE. Moreover, borrowing from relatives/friends does not significantly influence TE.Research limitations/implicationsFuture research can further explore the contribution of agricultural credit by including several agricultural productions and using panel data.Originality/valueThe study provides evidence that the impact of agricultural credit on agricultural production efficiency depends on the source of credit. This study contributes to the literature on the impact of agricultural credit and enlightens policymakers in the design of agricultural credit models in developing countries, particularly Côte d'Ivoire.

Efficiency Analysis of the Food and Beverage Industry in Tanzania: A Comparative Analysis

Purpose: This study examined the performance of food and beverage industries in Tanzania in terms of productive and technical efficiency. The specific objectives of the study were to evaluate the productive efficiency performance of food and beverage industries in Tanzania, to determine the level and trend of efficiency of food and beverage of food and beverage industry in Tanzania, and to assess the levels of productive efficiency performance in the food and beverage subsectors in Tanzania
 Methodology: The study used secondary data to achieve its objectives. The study employed a Panel data analysis technique using 40 companies in the manufacturing sector over a period of three years, 2018-2020. A stochastic frontier production model was applied using a linearized Translog production function to determine the performance elasticity coefficients of inputs and technical efficiency. The study used production theory advanced by Koutsoyiannis (1979) to explain the relatonship between input and output factors.
 Findings: One of the key findings was that the level and trend of efficiency in food and beverage industry demonstrated an upward trend for the period between 2018 and 2020 as evidenced by the changes in average in both food and beverage sub-sector which grew from 0.776 in 2018 to 0.7557 in 2019 and finally to 0.7746 in 2020. Another finding of the study was that, the individual productive efficiency distribution between food and beverage sub-sector revealed that beverage sub-sector performs much better than food sub-sectors, with an average technical efficiency of 77.85% and 81.36% for both food and beverage sub-sectors, respectively.
 Unique Contribution to Theory, Practice and Policy: The study’s unique contributions to theory include its assessment of efficiency levels, analysis of efficiency trends, and exploration of sector-specific variations. Its practical contributions encompass policy recommendations, guidance on modernization and technology adoption, and the importance of skills development and export promotion. These insights have direct implications for policymakers, industry stakeholders, and practitioners in Tanzania's food and beverage sector, aiding in the formulation of effective strategies to enhance efficiency and competitiveness.
 The study recommends that the government and other stakeholders comes up with policy reforms to address the underlying factors contributing to the underutilization of each firm’s production capacity. This includes reforming the input market in the manufacturing sector in order to increase the level of efficiency to 100%. There should be establishment of an efficient marketing mechanism that reduces the involvement of many parties in the supply chain and hence high transaction costs.

Technical efficiency and its determinants on lentil (Lens culunaris) production in Nepal

Lentil is one of the important pulse crops of Nepal and has high export potential. This study aimed to analyze the technical efficiency of the lentil production system and its determinants. A multistage sampling technique was employed to select respondent farmers from four districts representing three provinces in Nepal. Primary data were collected through face-to-face interviews with randomly selected 473 respondents using a semi-structured interview schedule. To derive the results, the stochastic production frontier and Tobit model were adopted. The average lentil output in the study area was found 672.6 ​kg ha-1 and the input variables such as seed, labor, tractor use, and area were the significant inputs increasing the output of lentils. The mean technical efficiency percentage for the pooled sample was 61.5% with a range between 23.0% and 89.9%. Further, the result revealed that average-performing farmers and least-performing farmers need to reduce their costs by 42.82% and 85.65%, respectively to attain the status of the most efficient farmer. Education, membership in groups and cooperatives, weeding practice, use of improved seed, and lentil farm size were found as determinants of technical efficiency in lentil production and unit increment of those variables favor lentil yield by 0.3%, 2.6%, 21.5%, 3.1%, and 3.1% respectively. As there is room to increase lentil output by using inputs efficiently, the government and related stakeholders should motivate farmers to get involved in groups and cooperatives to pool resources together and share information. Based on the results, with the application of current available resources farmers are strongly recommended to maintain their lentil farm size between 0.5 and 1 ​ha, use improved varietal seed, and also follow at least one weeding operation to increase their farm technical efficiency level by 21.5%.

The relationship between the ecologisation of farms and total factor productivity: A continuous treatment analysis

AbstractThe European Green Deal aims to mitigate the environmental impact of food production while improving the income of primary producers and strengthening the EU's competitiveness. We examine how the degree of ecologisation affects farms' total factor productivity (TFP). Our analysis combines a random‐parameter stochastic production frontier model with a composite indicator and a dose–response function approach. Results show a monotonically decreasing relationship between ecologisation and expected TFP level. On average, a one‐step increase in the degree of ecologisation results in a 12% decrease in TFP. However, the results indicate a non‐linear relationship. Three regions of the dose–response function can be distinguished; associated with high, medium and low degrees of ecologisation. In a region with a low degree of ecologisation, farms can increase the degree of ecologisation without reducing TFP. Both efficiency and technological differences contribute to these differences, but the main reason is technological. With increasing ecologisation, farm technology becomes more ‘land using’. Therefore, farms can increase their TFP and degree of ecologisation simultaneously by using land‐saving technologies or through sustainable intensification.

Estimating agriculture technologies’ impact on maize yield in rural South Africa

New technologies and digital infrastructures are enabling smart farming with high productivity levels across countries. Yet, there is dearth of evidence on how they are enabling smallholder farmers in Africa to increase their farm produce. By focussing on smallholder maize crop producers in South Africa and relying on a panel data for the period 2011–2021, this study applied a stochastic production frontier framework and Cobb–Douglas production function to estimate the relationship between variance of yield increase in relation to aggregate modern technologies adopted. The stochastic production frontier model was estimated using simple ordinary least square, maximum likelihood estimation and probit regressions. The analysis adopted a three-stage procedure which began with the specification of regression model, the calculation of least residuals squares of the explanatory variables and finally the estimation of the variances in the functional forms of output levels. The results revealed a positive relation between the application of digital agriculture technologies and increased crop performance for rural maize cultivators in South Africa. The policy inference from this study is that accelerating investment in digital agriculture infrastructure offers the promise of a quadruple return for South Africa’s agriculture sector.

Technical efficiency of agroforestry production technology among smallholder farmers in Kaduna State, Nigeria

This study evaluated technical efficiency of agroforestry production technology among smallholder farmers in Kaduna State, Nigeria. Multi-stage sampling technique was adopted. A total sample size of 120 smallholder agroforestry farmers was used. Primary data were collected with the aid of structured and well-designed questionnaire. Analytical tools used were: descriptive statistics, farm budgeting techniques, financial analysis, stochastic production frontier model, and principal component model. About 85% of agroforestry farmers were male, while 15% were female. Also, 87.50% of agroforestry farmers were less than 50 years of age. The mean age was 45 years. Furthermore, 85% of agroforestry farmers had formal education and were literate. The household sizes were large with mean value of 6 members per household. The agroforestry systems practiced include: alley farming, shelterbelts, wind breaks, home gardens, api-silviculture, aqua-forestry, retaining tree on farm land, taungya systems, farmed parkland, and silvo-pasture. The result of the farm budgetary technique show that agroforestry farming was profitable among the smallholder farmers in the study area. The result of the maximum likelihood estimates shows that the significant factors influencing output of agroforestry production technology were: seed input (P<0.05), farm size input (P<0.01), fertilizer input (P<0.10), labour input (P<0.10), and chemical input (P<0.01). The significant factors influencing technical inefficiency of agroforestry production technology were: gender (P<0.10), marital status (P<0.01), education level (P<0.01), experience in agroforestry production (P<0.01) and size of households (P<0.10). The average technical efficiency score obtained by the smallholder agroforestry farmers was 40.18%. The constraints facing agroforestry farmers include: lack of training and capacity building, inadequate extension officers, lack of improved seeds, lack of credit facilities, lack of fertilizers, and lack of agroforestry tree seedlings. The study recommends that agroforestry tree seedlings should be made available to farmers, credit facilities should be provided for easy access to agroforestry production technologies, extension officers should be employed, and improved seeds, fertilizers should be provided for increased productivity.

Does sending farmers back to school increase technical efficiency of maize production? Impact assessment of a farmer field school programme in Indonesia

A farmer field school programme aims to impart knowledge and promote new technology. The programme is expected to enhance farmers’ performances. However, the empirical evidence remains unclear. A few studies have examined the impact of this programme on technical efficiency in Indonesia. The current study specifically investigates the causal impact of the Farmer Field School of Integrated Crop Management (FFS-ICM) programme on technical efficiency of maize production in Indonesia. We used a stochastic production frontier model and propensity score matching (PSM) to examine the causal impact of FFS-ICM on the technical efficiency of maize production. The results show that the average farm technical efficiency is 68.3%, which suggests that the production can be further improved. The PSM estimation indicates that FFS-ICM increased the technical efficiency by 1.48%, demonstrating the importance of agricultural extension programmes in rural areas in Indonesia. Nevertheless, the relatively small estimated impact raises the issue of cost effectiveness of the programme.

ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN

The stochastic production frontier (SPF) is the stochastic frontier analysis (SFA) method used to estimate the production frontier by accounting for the existence of inefficiency. The standard SPF assumes that the noise component follows a Normal distribution and the inefficiency component follows a half-Normal distribution. The presence of outliers in the data will affect the inaccuracy in estimating the parameters and leads to an exaggerated spread of efficiency predictions. This study uses two alternative models, the first with SPF Normal-Gamma and the second with SPF Student's t-half Normal, then the results are compared with standard SPF. This study uses data from statistics Indonesia on the cost structure of paddy cultivation household survey in 2014. This study aims to examine the effect of changes in distribution assumptions on the standard SPF model in estimating parameter value and the technical efficiency score in the presence of outliers. The parameter coefficient estimates similar results that apply to three SPF models. Only the standard error value in the alternative SPF model tends to be smaller than the standard SPF model. The Normal-Gamma model performs better in assessing residual with smaller root mean square error (RMSE) than the others, but the results of the estimated technical efficiency still contain outliers. The Student's t-half Normal model estimates technical efficiency no longer contains outliers, the range is shorter than the other models, and the results of estimating technical efficiency are not monotonous in the distribution of residual tails.  The SPF Student's t-half Normal model is more robust in presence outliers than SPF Normal-half Normal and SPF Normal-Gamma.

Indirect inference estimation of stochastic production frontier models with skew-normal noise

Indirect inference estimation of stochastic production frontier models with skew-normal noise

TECHNICAL EFFICIENCY OF YAM PRODUCTION IN PAIKORO LOCAL GOVERNMENT AREA OF NIGER STATE, NIGERIA

The study examined technical efficiency of yam farmers in Paikoro Local Government Area of Niger State, Nigeria was analyzed using the stochastic frontier production model. Data were collected from 90 yam farmers selected using simple random sampling technique. The data were collected with the aid of structured questionnaire and oral interview were analyzed using Descriptive statistics, stochastic frontier production function. The maximum likelihood estimate (MLE) of the stochastic frontier model production function revealed that the inputs were under-utilized the results of the socio-economic characteristics shows that yam farmers was dominated 50% by male farmers, within the range of 46- 55 years, 47% of the farmers had farm size less-than 1 hectare with at least 10 years’ experience. The technical efficiency of farmers differs substantially among the respondents, ranging between 0.325 and 0.952 with a mean economic efficiency of 0.807.

Estimating and Decomposing the TFP Growth of Service-Oriented Manufacturing in China: A Translogarithmic Stochastic Frontier Approach

By constructing a translogarithmic stochastic frontier production model, this study explores the total factor productivity (TFP) of service-oriented manufacturing in 30 provinces in China during 2004–2020. We carried out decomposition analysis to understand in greater depth the potential drivers of TFP growth. The results show that the overall TFP of service-oriented manufacturing continuously improved during the sample period; however, the overall growth rate showed a significant slowing trend, and the contribution of TFP growth to output growth is still low. The industrial growth of service-oriented manufacturing is mainly driven by capital input, and the transformation of its growth mode from extensive to intensive has not yet been realized. Furthermore, there exists significant regional and sub-sectoral heterogeneity in the TFP growth of the industry. The decomposition of TFP growth shows that technological progress and technical efficiency are the main sources of TFP growth, but the growth rate of technological progress is declining gradually, and its driving effect on TFP is weakening. The deterioration of both scale and allocation efficiency hinders the improvement of TFP in service-oriented manufacturing, and there is still room for the industry to improve its TFP level by improving scale efficiency and allocation efficiency.

Does contract farming affect technical efficiency? Evidence from soybean farmers in Northern Ghana

Understanding how and the extent to which contract farming arrangements impact agricultural productivity is important to ensuring that policies are designed to maximize the likelihood of success. Using cross-sectional data from 516 soybean farmers in Northern Ghana, we provide empirical evidence that contract farming increases soybean productivity and technical efficiency in Northern Ghana. We use propensity score matching to reduce bias from observables, and then estimate a stochastic production frontier model that addresses selection bias arising from unobservable variables. We find that the technical efficiency levels of contract farmers are 77 percent compared with 69 percent for non-contract farmers. We also find that access to credit, extension contact, and farmer group membership are key determinants of participating in contract farming.

Measuring Efficiency of Bamboo Handicrafts in Tribal Society of Bangladesh: An Empirical Analysis

Are the traditional bamboo handicrafts of Sylhet district of Bangladesh being produced efficiently by Patra women? To answer this question, 120 women entrepreneurs from the Patra community were selected using a multistage random sampling technique. Data were collected using face-to-face interviews and Focus Group Discussions (FGDs) structured questionnaires directly from women entrepreneurs considering factors such as age, education, labor, equipment quantity, credit access, raw materials, production volume, product price, and market distance. Each union was divided into 4 sessions with a total of 15 women entrepreneurs in each session. The Stochastic Frontier Production function was used with a theoretical framework to measure economic, allocative, and technical efficiency. Tribal women entrepreneurs are relatively middle-aged with an average age of 38 years and 58.35% were educated in primary school. The coefficient of labor represents a positive sign that is not statistically significant. The value of raw material and capital coefficient was -1.191 which is significant but negatively affects the production efficiency of handicraft making at a 1% level. The stochastic Frontier Production model is 0.999 which is statistically significant, meaning that 99.9 percent of the variability of income from handicrafts is responsible for the technical inefficiency of production techniques. The technical and allocative efficiencies indices of bamboo handicrafts varied significantly at 95 and 92%, respectively. They efficiently and accurately allocated enterprise input. There was a gap between the highest and lowest economic efficiency index, with an average economic efficiency of 87 percent. It was also found that education, credit access, and market distance factors have made a positive and significant contribution to production efficiency. A policy implication of the study is that it is a promising initiative for Patra women as their economic development involves increasing the production of handicrafts. First, the Government of Bangladesh should allocate funds for modern education methods and training in making bamboo handicrafts, and provide financial assistance to these communities in the off-season, especially during the monsoon season, which will further accelerate the production activities of the industry. Also, for the advancement of bamboo handicrafts, it is necessary to set up sales outlets to facilitate marketing.

Technical Efficiency of Small-Scale Pig Farming in Indonesia

Live pigs are still the mainstay of livestock sub-sector exports inIndonesia. Although pig farming in Indonesia has competitivenessin the international market, its productivity shows a decliningcondition. The purpose of this research is to measure the level oftechnical efficiency of small-scale pig breeding and fatteningbusinesses. The data used come from the results of the FarmHousehold Survey conducted by the Central Bureau of Statistics(BPS). The survey was conducted in 20 provinces in Indonesia,with a sample size of 6,681 small-scale or household-scale pigfarming. The research used the Stochastic Production Frontier(SPF) model to measure the level of technical efficiency of pigfarming and used the maximum likelihood method to estimate it. The results showed that the level of technical efficiency of pigfarming is relatively low. The average technical efficiency level offattening pig farming is higher than that of the breeding. Thefactors of farming experience, market orientation, and feed typecombination have a positive influence in improving efficiency. Public policies that improve pig farmers' access to farm inputs andmarkets are expected to significantly improve the productivity ofsmall-scale pig farming.