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Statistics in Transition Volume 7 Number 6 STATISTICS IN TRANSITION, December 2006 1199 STATISTICS IN TRANSITION, December 2006 Vol. 7, No. 6, pp. 1199—1202 FROM THE EDITOR This issue contains twelve articles devoted to small area estimation, methods of estimation and other topics, one book review, three reports, an announcement on a conference and acknowledgements of referees of volume 7. There are following three articles devoted to small area estimation: 1. Attempts at Applying Small Area Estimation Methods in Agricultural Sample Surveys in Poland (by Dorota Bartosińska from Poland). The paper is devoted to the application of small area estimation (SAE) methods in agricultural sample surveys in Poland, using last Census of Agriculture as an auxiliary source of data. The author briefly describes agricultural sample surveys in Poland, and sources of additional data which may be used in SAE methods in agriculture. To obtain more precise estimates of agricultural characteristics from agricultural sample surveys by county (poviat), empirical and hierarchical Bayes estimators, and some auxiliary information from last census of agriculture are used. Two different regression models are considered: area-level regression model and unit-level one. The unit-level approach required matching of particular farms in the agricultural sample surveys to the census of agriculture. The precision of model-based estimates is significantly increased compared to direct estimates. Ecological effect that can cause different results of estimation, depending on regression model type, is also discussed. 2. Estimation of the Mean Squared Error of Model-based Estimators (by Wojciech Rabiega from Poland). The author stresses that model-based methods of small area estimation have received a lot of attention because of making specific allowance for local variation through complex error structures in models that link small areas. Efficient indirect estimators can be obtained with the assumed models. Models can be validated from the sample data. Stable area specific measures of variability associated with the estimates can be obtained unlike the overall measures for synthetic and composite estimators. 3. On Accuracy of EBLUP under Random Regression Coefficient Model (by Tomasz Żądło from Poland). The author analyzes the accuracy of the empirical best linear unbiased predictor (EBLUP) of the domain total (see Royall, 1976), assuming random coefficient superpopulation model which is a special case of the general linear mixed model. To estimate the mean square error (MSE) of the EBLUP he uses the results obtained by Datta and Lahiri (2000) for the predictor proposed by Henderson (1950) and 1200 From the Editor adopts them for the predictor proposed by Royall (1976). In a simulation study he studies real data on Polish farms from one region in Poland to consider the decrease of the accuracy of the EBLUP comparing with the best linear unbiased predictor (BLUP) due to the estimation of unknown variance components. What is more, he compares the MSE of the EBLUP with MSEs of two other predictors which are BLUPs but under different models. For methods of estimation are devoted following papers: 4. Estimation of a Population Mean Using Different Imputation Methods (M. S. Ahmed from Oman, Omar Al-Titi and Walid Abu-Dayyeh from Saudi Arabia, and Ziad Al-Rawi from Jordan). Several methods of imputation are suggested and their corresponding estimators of the population mean are considered. The bias and mean square error of each of the estimators are derived up to first orders. Then these estimators are compared with each others and with other well known estimators using their biases and mean square errors. It turns out that some of the new estimators are more efficient than the well known estimators. Real data example is used for illustration. 5. A Modified Regression Estimator of a Population Mean Under General Sampling Design (Vyas Dubey from India). The author studies a generalized estimator of a population mean under any sampling design, which utilizes the knowledge of a population mean and variance of auxiliary variable has been studied. Properties of proposed estimator have been discussed and an optimum class of estimators has been obtained. The proposed class of estimators has been discussed in probability proportional to size sampling. Results are supported by numerical examples. 6. Design-Based Horvitz-Thompson Variance Estimation: π-Weighted Ratio Type Estimator (by P.A. Patel and R.D. Chaudhari from India). In this article, motivated by the ratio method of estimation, a π-weighted ratio type estimator for Horvitz-Thompson variance is suggested and is shown to be asymptotically design unbiased and consistent. An empirical study is conducted to compare its performance. To assess the performances, several important summary statistics such as the percentage relative bias, the relative efficiency, and the empirical coverage rate of the resultant confidence intervals are computed and presented. 7. Post-Stratification in a Two-Way Deeply Stratified Population (by D. Shukla, Manish Trivedi and G. N. Singh). This paper presents an estimation strategy for the population mean for a two-way r x s deeply stratified population using technique of post-stratification. The size of each stratum and frame are both assumed unknown. The information known is the proportion of row and column-size-totals of two-way deep- stratification. A new estimator is proposed and its optimum properties are STATISTICS IN TRANSITION, December 2006 1201 examined along with comparison of efficiencies. An approximate expression of mean square error (MSE) is derived for this set-up. 8. An Efficient Variant of the Product and Ratio Stimators in Stratified Random Sampling (by Housila P. Singh and Gajendra K. Vishwakarma from India). This paper introduces two classes of estimators of population mean of the study variable using auxiliary variable in stratified random sampling. The biases and variances of the proposed estimators have been derived under large sample approximation. Estimators based on “estimated optimum values” are also investigated. An empirical study is carried out to demonstrate the performances of the suggested estimators over others. 9. Estimation of Mean with Known Coefficient of Variation of an Auxiliary Variable in Two Phase Sampling (by Lakshmi N. Upadhyaya, Housila P. Singh and Ritesh Tailor from India). The authors discuss the possibility of obtaining efficient estimators of the population mean of the variable y under investigation by means of two phase sampling and the help of two auxiliary variables x (main auxiliary variable) and z (second auxiliary variable). Asymptotic expression for bias and mean squared error (MSE) of the proposed estimator are obtained. Asymptotic optimum estimator (AOE) in the family is identified with its approximate MSE formula. Numerical illustration is given to support the present study. The third part of this issue under the title Other Articles contains three articles devoted to different topics: 10. Methodology and Empirical Results of the Time Use Surveys in Poland (by Ilona Błaszczak-Przybycińska from Poland). The paper presents the methodology and the selected results of time use surveys in Poland. They have a long tradition in this country. Several time use surveys were conducted in the 1950s and 1960s. The first nationwide survey was carried out in 1968/1969. The nationwide time use surveys in Poland were performed by the Central Statistical Office four times. The last one was organized in 2003/2004. It was performed within the framework of the harmonized European time use surveys. 11. Labour Flows Into and Out of Polish Agriculture: A Micro-Level Approach (by Hilary Ingham & Mike Ingham from the UK). Notwithstanding its admission to the EU, agricultural restructuring and sustainable rural development remain major transition challenges confronting Poland. Achieving these joint goals will necessitate major labour flows from farming into other occupations and sectors. This paper employs a multinomial logit model on Labour Force Survey data to analyse mobility in the agricultural labour market. Its major finding is that of a largely stagnant pool of farm workers into and out of which are small flows that are insufficient to bring about the requisite change without explicit, perhaps radical policy intervention. 1202 From the Editor 12. Changes in Competitiveness and Labour Market Developments: A Comparative Analysis of Poland, Hungary and The Czech Republic (by Eugeniusz Kwiatkowski and Paweł Gajewski from Poland). The paper attempts to analyse the links between both domestic and external competitiveness and labour market developments in manufacturing industry branches in the three new member states of the European Union – Poland, Hungary and the Czech Republic. These are mostly the industries of deteriorating competitiveness, which reduced employment. The industries, where positive changes in the level of competitiveness occurred, showed no clear pattern with regard to employment changes. The part Book Review contains a review of an interesting book written by Sarjinder Singh entitled Thinking Statistically: Elephants Go to School (prepared by M.q Kozak from Poland). In the section Reports there are three reports on: a) The 9th Vilnius Conference on Probability Theory and Mathematical Statistics, Vilnius, Lithuania, June 25—30, 2006 (prepared by D. Krapavickaitė and A. Plikusas) b) XXVI European Meeting of Statisticians, Toruń, Poland, July 24—28, 2006 (Prepared by J. Białek) c) The
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