• Survey Research
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• v.5 no.1
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• pp.93-101
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• 2004

In business survey, cut-off sampling is usual, The contribution from cut-off part of the population is at least small in comparison with the remaining population. In this case, part of the target population is excluded from the selection and parameter estimations are only based on Take-all and Take-some stratum. It may be tempting not to use resources on enterprises that contribute little to the overall results of the survey. And this reduces the response burden for these small enterprises. But, the size of cut-off stratum has been increased as a way to manage reduced budgets. This leads to additional bias. In this study, the population have been separated as three stratum, cut -off, take-some, take-all, and we will estimate cut-off part using auxiliary variable.

• Proceedings of the Korean Association for Survey Research Conference
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• 2003.06a
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• pp.29-33
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• 2003

In business survey. cut off sampling is usual. The contribution from cut off part of the population is at least small in comparison with the remaining population. In this study. the population have been separated as three stratum, cut-off. take-some, take-all, and we will estimate cut-off part.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.13-22
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• 2012

Cut-off sampling that discards a part of the population from the sampling frame, is a widely used method for a business survey. Usually, to the estimate of population total, an accurate estimate of the total of the take-nothing stratum is required. Many estimators have been developed to estimate the total of the take-nothing stratum. Recently Kim and Shin (2011) suggested a composite estimator and showed the superiority of that estimator. In this paper, we suggest an alternative composite estimator obtained by combining BLUP estimator and a ratio estimator obtained by the small samples from the take-nothing stratum. Small simulation studies are performed for a comparison of the estimators and we confirm that the new suggested estimator is superior.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1115-1128
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• 2011

Cut-off sampling that discards a part of the population from the sampling frame, is a widely used method for a highly skewed population like a business survey. Usually to the estimate of population total, we need to estimate the total of the take-nothing stratum. Many estimators have been developed to estimate the total of the take-nothing stratum. In this paper, we suggest a new composite estimator which combines the estimator suggested by Sarndal et al. (1992) and a ratio estimator obtained by small samples from the take-nothing stratum. Small simulation studies are performed for the comparison of the estimators and we confirm that the new suggested estimator is superior to the others.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.43-59
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• 2014

Cut-off sampling has been widely used for a highly skewed population like a business survey by discarding a part of the population, so called a take-nothing stratum. For a more accurate estimate of the population total, Hwang and Shin (2013) suggested a composite estimator of a take-nothing stratum total that combined the survey results of a take-nothing stratum and a take-some sub-stratum (a part of take-some stratum). In this paper we propose a new cut-off sampling scheme by considering a cost function and a composite estimator based on the proposed sampling scheme. Small simulation studies compared the performances of known composite estimators and the new composite estimator suggested in this study. We also use Briquette Consumption Survey data for real data analysis.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.501-512
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• 2014

Modified cut-off sampling is widely used for highly skewed data. A serious drawback of modified cut-off sampling is the difficulty of adjustment of non-response in take-all stratum. Therefore, solutions of the problems of non-response in take-all stratum have been studied in various ways such as substitute of samples, imputation or re-weight method. In this paper, a new cut-off point based on minimizing MSE being used in exponential and power functions is suggested and it can be reduced the number of take-all stratum. We also investigate another cut-off point determination method with underlying distributions such as truncated log-normal and truncated gamma distributions. Finally we suggest the optimal cut-off point which has a minimum of take-all stratum size among suggested methods. Simulation studies are performed and Labor Survey data and simulated data are used for the case study.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.409-420
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• 2020

In business survey, modified cut-off sampling is commonly used to greatly increase the accuracy of the estimation while reducing the number of samples. However, non-response rate of take-all stratum has increased significantly and the sample substitution is not possible because the non-response in the take-all stratum affects the accuracy of the estimation. It is important to adjust the bias appropriately if non-response is affected by the variable of interest. In this study, a bias adjusted estimation is proposed as an appropriate method to deal with a non-response in the take-all stratum. In particular, the estimator proposed by Chung and Shin (2020) was applied to the bias adjustment for the take-all stratum; therefore, we suggest a new method to adjust properly for the take-all stratum. The superiority of the proposed estimator was examined through simulation studies and confirmed through actual data analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.411-417
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• 2017

It is necessary to determine the current and future energy consumption by farm households for the rational specification of energy related policy in the Korean agricultural sector. Especially, It is important to identify the consumption by source of energy and by the crops. On the other hand, the world has tried to reduce the production of greenhouse gases and, in line with this, the Korean government established related legislations to contribute to this reduction (30% reduction in emissionsby 2020). The reduction target of the agricultural sector is specified as 5.2% of the national total. This study focuses on sampling design to determine the energy consumption and emission of greenhouse gases, and suggests several alternatives to improve the confidence level and to make a dent survey and estimation errors. The population for the energy consumption survey of the agricultural sector was derived from agricultural census data. In the case of commodities with high skewness, we cut the sample range to within the statistical significant range. The number of samples in each class is specified using the Neyman allocation method and 95% significance level. The estimation results are compared with the population to verify the statistical significance and several management methods of sampling errors are suggested.