scholarly journals An efficient variant of dual to product and ratio estimators in sample surveys

Author(s):  
Sayed ZEESHAN ◽  
Gajendra K. VİSHWAKARMA ◽  
Manish KUMAR
2014 ◽  
Vol 247 ◽  
pp. 255-265
Author(s):  
Hilal A. Lone ◽  
Rajesh Tailor ◽  
Housila P. Singh ◽  
Med Ram Verma

Author(s):  
Housila Prasad Singh ◽  
Pragati Nigam

In this paper we have considered the problem of estimating the population mean using auxiliary information in sample surveys. A class of dual to ratio estimators has been defined. Exact expressions for bias and mean squared error of the suggested class of dual to ratio estimator have been obtained. In particular, properties of some members of the proposed class of dual to ratio estimators have been discussed. It has been shown that the proposed class of estimators is more efficient than the sample mean, ratio estimator, dual to ratio estimator and some members of the suggested class of estimators in some realistic conditions. Some numerical illustrations are given in support of the present study.


2020 ◽  
Vol 27 (6) ◽  
pp. 26-36
Author(s):  
A. V. Topilin ◽  
A. S. Maksimova

The article reflects the results of a study of the impact of migration on regional labour markets amidst a decline in the working-age population in Russia. After substantiating the relevance of the issues under consideration, the authors propose a methodological analysis toolkit, the author’s own methodology for calculating the coefficients of permanent long-term external and internal labour migration in regional labour markets, and the coefficient of total migration burden. In addition, the authors provide an overview of the information and statistical base of the study. According to current migration records, data of Rosstat sample surveys on Russian labour migrants leaving for employment in other regions, regional labour resources balance sheets based on the calculated coefficients of labour market pressures, the authors analyzed the impact of migration on the Russian regional labour markets over the past decade. It revealed an increasing role of internal labour migration in many regions, primarily in the largest economic agglomerations and oil and gas territories. At the same time, the role of external labour migration remains stable and minimum indicators of the contribution of permanent migration to the formation of regional labour markets continue to decrease. It has been established that irrational counter flows of external and internal labour migration have developed, which indicates not only an imbalance in labour demand and supply but also a discrepancy between the qualitative composition of migrants and the needs of the economy. It is concluded that the state does not effectively regulate certain types of migration, considering its impact on the labour market. The authors justified the need for conducting regular household sample surveys according to specific programs to collect information about labour migrants and the conditions for using their labour. In addition to the current migration records, using interregional analysis, this information allows making more informed decisions at the federal and regional levels to correct the negative situation that has developed in the regional labour markets even before the coronavirus pandemic had struck.


2020 ◽  
pp. 1-17
Author(s):  
Vikas Kumar

The quality of metadata is a crucial determinant of usability/interpretability of data. This paper draws attention to the poor quality of India’s government statistics and the paucity of metadata necessary to understand the problems. The paper suggests that there has been a decline in India both in terms of the availability and quality of metadata for key government sources of information including maps, decennial population censuses and National Sample Surveys amidst growing sophistication in the understanding of metadata. The poor quality of metadata impairs cross-sectional as well as inter-temporal comparisons and policymaking apart from concealing biases and lapses of government statisticians. The paper draws on the experience of three states – erstwhile Jammu and Kashmir, Manipur and Nagaland – where government statistics have been affected by serious errors that are not well-understood due to the lack of adequate metadata.


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