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- Articles and reports: 12-001-X201900300004Description:
Social or economic studies often need to have a global view of society. For example, in agricultural studies, the characteristics of farms can be linked to the social activities of individuals. Hence, studies of a given phenomenon should be done by considering variables of interest referring to different target populations that are related to each other. In order to get an insight into an underlying phenomenon, the observations must be carried out in an integrated way, in which the units of a given population have to be observed jointly with related units of the other population. In the agricultural example, this means that a sample of rural households should be selected that have some relationship with the farm sample to be used for the study. There are several ways to select integrated samples. This paper studies the problem of defining an optimal sampling strategy for this situation: the solution proposed minimizes the sampling cost, ensuring a predefined estimation precision for the variables of interest (of either one or both populations) describing the phenomenon. Indirect sampling provides a natural framework for this setting since the units belonging to a population can become carriers of information on another population that is the object of a given survey. The problem is studied for different contexts which characterize the information concerning the links available in the sampling design phase, ranging from situations in which the links among the different units are known in the design phase to a situation in which the available information on links is very poor. An empirical study of agricultural data for a developing country is presented. It shows how controlling the inclusion probabilities at the design phase using the available information (namely the links) is effective, can significantly reduce the errors of the estimates for the indirectly observed population. The need for good models for predicting the unknown variables or the links is also demonstrated.
Release date: 2019-12-17 - Articles and reports: 12-001-X201500114149Description:
This paper introduces a general framework for deriving the optimal inclusion probabilities for a variety of survey contexts in which disseminating survey estimates of pre-established accuracy for a multiplicity of both variables and domains of interest is required. The framework can define either standard stratified or incomplete stratified sampling designs. The optimal inclusion probabilities are obtained by minimizing costs through an algorithm that guarantees the bounding of sampling errors at the domains level, assuming that the domain membership variables are available in the sampling frame. The target variables are unknown, but can be predicted with suitable super-population models. The algorithm takes properly into account this model uncertainty. Some experiments based on real data show the empirical properties of the algorithm.
Release date: 2015-06-29 - Articles and reports: 11-522-X201300014283Description:
The project MIAD of the Statistical Network aims at developing methodologies for an integrated use of administrative data (AD) in the statistical process. MIAD main target is providing guidelines for exploiting AD for statistical purposes. In particular, a quality framework has been developed, a mapping of possible uses has been provided and a schema of alternative informative contexts is proposed. This paper focuses on this latter aspect. In particular, we distinguish between dimensions that relate to features of the source connected with accessibility and with characteristics that are connected to the AD structure and their relationships with the statistical concepts. We denote the first class of features the framework for access and the second class of features the data framework. In this paper we mainly concentrate on the second class of characteristics that are related specifically with the kind of information that can be obtained from the secondary source. In particular, these features relate to the target administrative population and measurement on this population and how it is (or may be) connected with the target population and target statistical concepts.
Release date: 2014-10-31 - 4. A balanced sampling approach for multi-way stratification designs for small area estimation ArchivedArticles and reports: 12-001-X200800210763Description:
The present work illustrates a sampling strategy useful for obtaining planned sample size for domains belonging to different partitions of the population and in order to guarantee the sampling errors of domain estimates be lower than given thresholds. The sampling strategy that covers the multivariate multi-domain case is useful when the overall sample size is bounded and consequently the standard solution of using a stratified sample with the strata given by cross-classification of variables defining the different partitions is not feasible since the number of strata is larger than the overall sample size. The proposed sampling strategy is based on the use of balanced sampling selection technique and on a GREG-type estimation. The main advantages of the solution is the computational feasibility which allows one to easily implement an overall small area strategy considering jointly the sampling design and the estimator and improving the efficiency of the direct domain estimators. An empirical simulation on real population data and different domain estimators shows the empirical properties of the examined sample strategy.
Release date: 2008-12-23 - 5. Conditional and unconditional analysis of some small area estimators in complex sampling ArchivedArticles and reports: 12-001-X20030016608Description:
This work deals with the unconditional and conditional properties of some well-known small area estimators: expansion, post-stratified ratio, synthetic, composite, sample size dependent and the empirical best linear unbiased predictor (EBLUP). A two-stage sampling design is considered as it is commonly used in household surveys conducted by the National Statistics Institute of Italy. An evaluation is carried out through a simulation based on 1991 Italian census data. The small areas considered are the local labour market areas, which are unplanned domains that cut across the boundaries of the design strata.
Release date: 2003-07-31 - Articles and reports: 11-522-X20010016271Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
This paper proposes a method for short-term estimation of labour input indicators using administrative data from the Social Security Database (SSD). The rationale for developing this methodology originated from the need for national statistical offices to meet the standard quality criteria in the Regulation no. 1165/98 of the European Community concerning short-term business statistics. Information requested in the Regulation involves such a detailed disaggregation that it would be impossible to meet all the requirements through direct data collection. Administrative data, because of their timeliness and detailed coverage, represent a valuable source for obtaining estimates of business population aggregates that meet such quality requirements.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016309Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
This paper proposes a method for estimating simple and correlated measurement variance components when a re-interview is available for a subsample of respondents. However, the two measurements cannot be considered as being collected under the same conditions and, therefore, are subject to different measurement error variance. This consideration seems more realistic when, in actuality, it is impossible to ensure that the same measurement conditions are implemented in the two interviews, as in the case when operational and budget constraints suggest adopting a different survey mode for the second interview.
Release date: 2002-09-12 - 8. Empirical comparison of small area estimation methods for the Italian Labour Force Survey ArchivedArticles and reports: 12-001-X199400214419Description:
The study was undertaken to evaluate some alternative small areas estimators to produce level estimates for unplanned domains from the Italian Labour Force Sample Survey. In our study, the small areas are the Health Service Areas, which are unplanned sub-regional territorial domains and were not isolated at the time of sample design and thus cut across boundaries of the design strata. We consider the following estimators: post-stratified ratio, synthetic, composite expressed as linear combination of synthetic and of post-stratified ratio, and sample size dependent. For all the estimators considered in this study, the average percent relative biases and the average relative mean square errors were obtained in a Monte Carlo study in which the sample design was simulated using data from the 1981 Italian Census.
Release date: 1994-12-15
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Articles and reports (8)
Articles and reports (8) ((8 results))
- Articles and reports: 12-001-X201900300004Description:
Social or economic studies often need to have a global view of society. For example, in agricultural studies, the characteristics of farms can be linked to the social activities of individuals. Hence, studies of a given phenomenon should be done by considering variables of interest referring to different target populations that are related to each other. In order to get an insight into an underlying phenomenon, the observations must be carried out in an integrated way, in which the units of a given population have to be observed jointly with related units of the other population. In the agricultural example, this means that a sample of rural households should be selected that have some relationship with the farm sample to be used for the study. There are several ways to select integrated samples. This paper studies the problem of defining an optimal sampling strategy for this situation: the solution proposed minimizes the sampling cost, ensuring a predefined estimation precision for the variables of interest (of either one or both populations) describing the phenomenon. Indirect sampling provides a natural framework for this setting since the units belonging to a population can become carriers of information on another population that is the object of a given survey. The problem is studied for different contexts which characterize the information concerning the links available in the sampling design phase, ranging from situations in which the links among the different units are known in the design phase to a situation in which the available information on links is very poor. An empirical study of agricultural data for a developing country is presented. It shows how controlling the inclusion probabilities at the design phase using the available information (namely the links) is effective, can significantly reduce the errors of the estimates for the indirectly observed population. The need for good models for predicting the unknown variables or the links is also demonstrated.
Release date: 2019-12-17 - Articles and reports: 12-001-X201500114149Description:
This paper introduces a general framework for deriving the optimal inclusion probabilities for a variety of survey contexts in which disseminating survey estimates of pre-established accuracy for a multiplicity of both variables and domains of interest is required. The framework can define either standard stratified or incomplete stratified sampling designs. The optimal inclusion probabilities are obtained by minimizing costs through an algorithm that guarantees the bounding of sampling errors at the domains level, assuming that the domain membership variables are available in the sampling frame. The target variables are unknown, but can be predicted with suitable super-population models. The algorithm takes properly into account this model uncertainty. Some experiments based on real data show the empirical properties of the algorithm.
Release date: 2015-06-29 - Articles and reports: 11-522-X201300014283Description:
The project MIAD of the Statistical Network aims at developing methodologies for an integrated use of administrative data (AD) in the statistical process. MIAD main target is providing guidelines for exploiting AD for statistical purposes. In particular, a quality framework has been developed, a mapping of possible uses has been provided and a schema of alternative informative contexts is proposed. This paper focuses on this latter aspect. In particular, we distinguish between dimensions that relate to features of the source connected with accessibility and with characteristics that are connected to the AD structure and their relationships with the statistical concepts. We denote the first class of features the framework for access and the second class of features the data framework. In this paper we mainly concentrate on the second class of characteristics that are related specifically with the kind of information that can be obtained from the secondary source. In particular, these features relate to the target administrative population and measurement on this population and how it is (or may be) connected with the target population and target statistical concepts.
Release date: 2014-10-31 - 4. A balanced sampling approach for multi-way stratification designs for small area estimation ArchivedArticles and reports: 12-001-X200800210763Description:
The present work illustrates a sampling strategy useful for obtaining planned sample size for domains belonging to different partitions of the population and in order to guarantee the sampling errors of domain estimates be lower than given thresholds. The sampling strategy that covers the multivariate multi-domain case is useful when the overall sample size is bounded and consequently the standard solution of using a stratified sample with the strata given by cross-classification of variables defining the different partitions is not feasible since the number of strata is larger than the overall sample size. The proposed sampling strategy is based on the use of balanced sampling selection technique and on a GREG-type estimation. The main advantages of the solution is the computational feasibility which allows one to easily implement an overall small area strategy considering jointly the sampling design and the estimator and improving the efficiency of the direct domain estimators. An empirical simulation on real population data and different domain estimators shows the empirical properties of the examined sample strategy.
Release date: 2008-12-23 - 5. Conditional and unconditional analysis of some small area estimators in complex sampling ArchivedArticles and reports: 12-001-X20030016608Description:
This work deals with the unconditional and conditional properties of some well-known small area estimators: expansion, post-stratified ratio, synthetic, composite, sample size dependent and the empirical best linear unbiased predictor (EBLUP). A two-stage sampling design is considered as it is commonly used in household surveys conducted by the National Statistics Institute of Italy. An evaluation is carried out through a simulation based on 1991 Italian census data. The small areas considered are the local labour market areas, which are unplanned domains that cut across the boundaries of the design strata.
Release date: 2003-07-31 - Articles and reports: 11-522-X20010016271Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
This paper proposes a method for short-term estimation of labour input indicators using administrative data from the Social Security Database (SSD). The rationale for developing this methodology originated from the need for national statistical offices to meet the standard quality criteria in the Regulation no. 1165/98 of the European Community concerning short-term business statistics. Information requested in the Regulation involves such a detailed disaggregation that it would be impossible to meet all the requirements through direct data collection. Administrative data, because of their timeliness and detailed coverage, represent a valuable source for obtaining estimates of business population aggregates that meet such quality requirements.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016309Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
This paper proposes a method for estimating simple and correlated measurement variance components when a re-interview is available for a subsample of respondents. However, the two measurements cannot be considered as being collected under the same conditions and, therefore, are subject to different measurement error variance. This consideration seems more realistic when, in actuality, it is impossible to ensure that the same measurement conditions are implemented in the two interviews, as in the case when operational and budget constraints suggest adopting a different survey mode for the second interview.
Release date: 2002-09-12 - 8. Empirical comparison of small area estimation methods for the Italian Labour Force Survey ArchivedArticles and reports: 12-001-X199400214419Description:
The study was undertaken to evaluate some alternative small areas estimators to produce level estimates for unplanned domains from the Italian Labour Force Sample Survey. In our study, the small areas are the Health Service Areas, which are unplanned sub-regional territorial domains and were not isolated at the time of sample design and thus cut across boundaries of the design strata. We consider the following estimators: post-stratified ratio, synthetic, composite expressed as linear combination of synthetic and of post-stratified ratio, and sample size dependent. For all the estimators considered in this study, the average percent relative biases and the average relative mean square errors were obtained in a Monte Carlo study in which the sample design was simulated using data from the 1981 Italian Census.
Release date: 1994-12-15
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