Modeling dependence between error components of the stochastic frontier model using copula: Application to intercrop coffee production in Northern Thailand

Wiboonpongse, Aree; Liu, Jianxu; Sriboonchitta, Songsak; Denœux, Thierry

doi:10.1016/j.ijar.2015.04.001

Cited by 47 publications

(28 citation statements)

References 19 publications

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“…Referring to (3), we consider the Cobb-Douglas production model as: The maximum likelihood is used to assess SFA model parameters as shown in (9) and SFA-copula model, where the copula functions are shown in the appendix section. We can estimate the parameters of the models and technical efficiency (TE) using the MATLAB software.…”

Section: Outputmentioning

confidence: 99%

“…The copula method was used to model the reliance and then it was possible to estimate parameters of the SFA model. It can lead to partial estimates of parameter and thus generates inaccurate technical efficiency by ignoring reliance between the error elements [9]. The study's primary goal is to compare the technical efficiencies of 12 companies generated by standard SFA model, SFA-copula model and DEA models.…”

Section: Introductionmentioning

confidence: 99%

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Technical Efficiency of Construction Companies: A Stochastic Frontier Model with Dependent Error

Arsad

Isa²,

Razak

2019

IJRTE

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There are several problems with using the Standard Stochastic Frontier (SF) model to produce a company’s technical efficiencies. One of the problem is the hypothesis of independence between the error components, known as, statistical noise and inefficiency term. Recent studies have used the SFA-copula model where the copula element captures the joint distribution of the two error components thus assuming that the errors are dependent. This research seeks to use the Cobb-Douglas Stochastic Frontier production model (standard model), SFA-copula models and DEA models (DEA-CCR and DEA-BCC) to compare the technical efficiencies of 12 publicly listed construction companies in Malaysia. The latter models are non-parametric frontier models which will be used as a base to determine the best SF model. The four copulas considered in this study are Clayton, Gumbel, A12 and Product copulas. The main findings of this study are the SFA-copula models showed consistency in terms efficiency scores and rankings of companies as compared to DEA models. The results further raise the question of the reliability of standard SF model especially when SFA-product copula was chosen as the best model for measuring efficiency performance. Therefore, it is obvious that it is not possible to ignore the reliance between the noise and inefficiency term

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Section: Outputmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Technical Efficiency of Construction Companies: A Stochastic Frontier Model with Dependent Error

Arsad

Isa²,

Razak

2019

IJRTE

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“…In order to determine the marginal distribution for the three groups of delay data, four commonly used probability distribution functions are tested: normal distribution, lognormal distribution, Weibull distribution, and Gamma distribution (Wiboonpongse et al [17]). Maximum likelihood estimation was used to estimate the parameters with continuous probability distributions.…”

Section: Marginal Distribution Of Sample Datamentioning

confidence: 99%

Comparative Analysis on Propagation Effects of Flight Delays: A Case Study of China Airlines

Feng

et al. 2018

Journal of Advanced Transportation

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This paper aims to capture the interdependency among the sequence of flight delays due to airline operations in airports, weather, and air traffic control conditions. A copula function is used to determine the distribution of delay sequence and examine the propagation effects. Using the actual data sourced from an airline in Asia Pacific region, it is found that flight delays could propagate to downstream airports/airlines, where the strength of delays was decreased, passed on, or increased. Considering the possible effects of increased delays under air traffic control or airline factors, scenarios that adjust flight schedules with additional buffer time were created and analyzed. Results show that, by adding buffer time efficiently, flight schedules can become more reliable.

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“…Fortunately, these copulas may then be "rotated" and applied again. A thorough review of rotated copulas may be found in [14,15]. There are three rotated forms: rotated 90 degrees, rotated 180 degrees, and rotated 270 degrees.…”

Section: Copulasmentioning

confidence: 99%

Analysis of Household Consumption Behavior and Indebted Self-Selection Effects: Case Study of Thailand

Liu

Sirikanchanarak

Sriboonchitta

et al. 2018

Mathematical Problems in Engineering

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Copula is deemed to be a good approach for relaxing bivariate or multivariate distributions in econometric models. This paper combines static and dynamic copula functions with endogenous switching to study self-selection effects and interdependence between error terms. This technique, copula-based models, is applied to analyze household consumption behavior and indebted self-selection effects in Thailand. The independent, Gaussian, Frank, Clayton, Gumbel, and Joe copula functions and the relatively rotated copula functions were employed in the empirical work. The best model was selected by the information criterion, AIC. We separated the households into four groups, indebted households, debt-free households, households with housing/land loans, and households without housing/land loans, which favors the examination of the treatment effects of indebted households or households with housing debts. The main results indicate that dynamic copula-based models offer better performance than others, such as classical endogenous switching models or all static copula-based models. Also, the I–I and the G–G models underestimate the treatment effects relative to the best models. Additionally, importantly, the traditional normal bivariate distribution or the static copula function could characterize the relationship as regards errors between household debt choice and household consumption and can lead to very misleading implications about the treatment effects.

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Modeling dependence between error components of the stochastic frontier model using copula: Application to intercrop coffee production in Northern Thailand

Cited by 47 publications

References 19 publications

Technical Efficiency of Construction Companies: A Stochastic Frontier Model with Dependent Error

Technical Efficiency of Construction Companies: A Stochastic Frontier Model with Dependent Error

Comparative Analysis on Propagation Effects of Flight Delays: A Case Study of China Airlines

Analysis of Household Consumption Behavior and Indebted Self-Selection Effects: Case Study of Thailand

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