Frontier Production Function: The Stochastic Coefficients Approach

Kalirajan, Kaliappa; Obwona, Marios

doi:10.1111/j.1468-0084.1994.mp56001007.x

Cited by 81 publications

(58 citation statements)

References 14 publications

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“…Estimation of the model can proceed using a classical approach, as proposed by Kalirajan and Obowna (1994). To facilitate model comparisons and testing of alternative specifications, we follow Tsionas (2002) and we proceed with estimation in a Bayesian framework.…”

Section: Modelling and Estimation Approachmentioning

confidence: 99%

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Productivity Growth in German Dairy Farming using a Flexible Modelling Approach

Emvalomatis¹

2011

J Agricultural Economics

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A random‐coefficients specification of an output distance function is used to measure and decompose productivity growth in German dairy farming. This specification can accommodate heterogeneity with respect to the technology employed by dairy farms, allowing for specialised and non‐specialised farms to be included in the analysis. The proposed modelling approach is favoured by the data when compared with the conventional translog specification of distance functions. The average total factor productivity growth rate for German dairy farms is estimated at 1.1%, with the technical progress component contributing most of this growth.

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Section: Modelling and Estimation Approachmentioning

confidence: 99%

“…4 4 Kalirajan and Obowna (1994) and Tsionas (2002) use the terms ‘stochastic coefficients’ and ‘random coefficients’, respectively, to describe this type of models, while Karagiannis and Tzouvelekas (2009) use the term ‘varying coefficients’. …”

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confidence: 99%

Productivity Growth in German Dairy Farming using a Flexible Modelling Approach

Emvalomatis¹

2011

J Agricultural Economics

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“…Of late, varying coefficients frontier model is suggested for estimating productive efficiency without bias (See Kalirajan and Obwona, 1994). …”

Section: Endnotesmentioning

confidence: 99%

Growth and spread of manufacturing productivity across regions in India

Babu

Raj

2013

SpringerPlus

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An expected outcome of economic reforms in India is enhanced pace of industrialization with manufacturing sector playing a crucial role by increasing its share in output via higher investments and increased productivity. This process of industrialization was also expected to usher in possibilities for the slow growing states to catch up with the fast growing ones. This paper assesses the extent of regional manufacturing performance in India by analyzing the trends in labour and total factor productivity for the organized manufacturing sector of 15 major Indian states. Data Envelopment Analysis is used to compute Malmquist total factor productivity index and its components. The results indicate that labour productivity diverges in the reform era and its growth and TFPG follow more or less a similar pattern. The study also finds that growth in productivity vary considerably across states and this variation in productivity growth can be explained, to a great extent, by differences in infrastructural development at the regional level.JEL ClassificationD24, O47, R11

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“…However, their actual output may lie below this frontier and the vertical distance is considered as a measure of inefficiency. The assumption of having a common frontier has been questioned by various authors such as Kalirajan and Obwona (1994), Tsionas (2002Tsionas ( , 2006, Desli et al (2003), Huang (2004), Tsionas and Kumbhakar (2004), which lead to the development of stochastic frontier models with random coefficients and related inference procedures. The introduction of such models serves the purpose of accounting for firm heterogeneity in efficiency measurement.…”

Section: Introductionmentioning

confidence: 99%

Rank Test for Testing Randomness of the Technology Parameters in a Stochastic Frontier Regression Model

Ghadge

Ramanathan

2010

Communications in Statistics - Simulation and Computation

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We propose a class of rank tests for testing the randomness of technology parameters in a stochastic frontier regression model. The asymptotic distribution of the test statistic is derived using the weak convergence results of empirical and rank processes. Since the distribution is quite complex and involves the unknown distribution of the error term, a bootstrap procedure is suggested and its validity is established. Simulation studies indicate that the test works well for most common choices of inefficiency distributions.The proposed test procedure is applied to a data set on electricity utility companies.

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Frontier Production Function: The Stochastic Coefficients Approach

Cited by 81 publications

References 14 publications

Productivity Growth in German Dairy Farming using a Flexible Modelling Approach

Productivity Growth in German Dairy Farming using a Flexible Modelling Approach

Growth and spread of manufacturing productivity across regions in India

Rank Test for Testing Randomness of the Technology Parameters in a Stochastic Frontier Regression Model

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