Canadian Labour Force Survey Research Articles

On the Adjustment of Gross Flow Estimates for Classification Error With Application to Data from the Canadian Labour Force Survey

Abstract Gross flows represent transition counts between a finite number of states for individuals in a population from one point in time to the next. Such flows are important for researchers and policy analysts; for example, gross labour flows for understanding labour market dynamics. Unfortunately, the observed flows are typically subject to classification error. As a result, the problem of adjusting observed flows for classification error has received considerable attention. Currently, three methods for adjustment of classification error are available. All these methods use the key assumption of independent classification errors (ICE) in conjunction with interview-reinterview data. We first give modifications to two of the methods that ensure that margins of the adjusted flow table agree with the published “stocks” without requiring a final margin adjustment. We then propose e-response contamination models and procedures for studying the robustness of ICE under different scenarios of departures from ICE applicable for all the methods. Our empirical results, based on data from the Canadian Labour Force Survey, show that for many scenarios the ICE assumption is fairly robust. There are, however, situations where this is not the case. We thus suggest that users apply the proposed procedures to check the robustness of ICE under scenarios relevant for their own applications. Finally, we provide valid chi-squared tests for modeling flow tables adjusted for classification error under ICE so that the adjusted flows could be further smoothed under the model. These tests are also illustrated using data from the Canadian Labour Force Survey.

On the Adjustment of Gross Flow Estimates for Classification Error with Application to Data from the Canadian Labour Force Survey

Abstract Gross flows represent transition counts between a finite number of states for individuals in a population from one point in time to the next. Such flows are important for researchers and policy analysts; for example, gross labour flows for understanding labour market dynamics. Unfortunately, the observed flows are typically subject to classification error. As a result, the problem of adjusting observed flows for classification error has received considerable attention. Currently, three methods for adjustment of classification error are available. All these methods use the key assumption of independent classification errors (ICE) in conjunction with interview-reinterview data. We first give modifications to two of the methods that ensure that margins of the adjusted flow table agree with the published “stocks” without requiring a final margin adjustment. We then propose e-response contamination models and procedures for studying the robustness of ICE under different scenarios of departures from IC...

A look at response errors in the labour force survey

AbstractIn conducting surveys, survey‐takers impose upon respondents certain cognitive and perceptual tasks the difficulty of which will depend upon a variety of factors. This paper examines the types of questions asked in the Canadian Labour Force Survey with an eye to assessing their “difficulty” and to identifying covariates of difficulty, with respect to both the nature of the information sought and the circumstances of the reinterview. The conclusions are extended to retrospective surveys, where response errors often lead to estimates that are seriously biased.

Modeling Nonignorable Nonresponse in Categorical Panel Data With an Example in Estimating Gross Labor-Force Flows

Many large-scale sample surveys use panel designs under which sampled individuals are interviewed several times before being dropped from the sample. The longitudinal data bases available from such surveys could be used to provide estimates of gross change over time. One problem in using these data to estimate gross change is how to handle the period-to-period nonresponse. This nonresponse is typically nonrandom and, furthermore, may be nonignorable in that it cannot be accounted for by other observed quantities in the data. Under the models proposed in this article, which are appropriate for the analysis of categorical data, the probability of nonresponse may be taken to be a function of the missing variable of interest. The proposed models are fit using maximum likelihood estimation. As an example, the method is applied to the problem of estimating gross flows in labor-force participation using data from the Current Population Survey and the Canadian Labour Force Survey.

Logistic regression analysis of sample survey data

SUMMARY Standard chi-squared, X2, or likelihood ratio, G2, test statistics for logistic regression analysis, involving a binary response variable, are adjusted to take account of the survey design. These adjustments are based on certain generalized design effects. Logistic regression diagnostics to detect any outlying cell proportions in the table and influential points in the factor space are also developed, taking account of the survey design. Finally, the results are used to analyse some data from the October 1980 Canadian Labour Force Survey.

Estimating Gross Flows Using Panel Data with Nonresponse: An Example from the Canadian Labour Force Survey

Abstract This article considers the problem of using categorical data from a panel survey in which there is nonrandom nonresponse to estimate gross flows. The methods are illustrated for the case of estimating gross flows in labor force participation using data from the Canadian Labour Force Survey. Three models are proposed that allow nonresponse to be related to employment classification, time, or both employment classification and time. Maximum likelihood estimation is used to fit the models to a single panel of Labour Force Survey data.

Estimating Gross Flows Using Panel Data With Nonresponse: An Example From the Canadian Labour Force Survey

Estimating Gross Flows Using Panel Data With Nonresponse: An Example From the Canadian Labour Force Survey

A strategy for up-dating continuous surveys

The need for regular up-dating of the selection probabilites in continuous surveys is emphasized in this paper. A simple strategy (selection method for the initial sample with the revision procedure) is presented and its application to the Canadian Labour Force Survey is discussed.

Several Methods of Re-Designing Area Samples Utilizing Probabilities Proportional to Size when the Sizes Change Significantly

Abstract For purposes of obtaining statistical data by enumeration, systematic sampling with probability proportional to size in one or more stages is frequently employed. The article describes two methods of changing the measures of sizes without introducing a bias in the estimation procedure. They result in the reduction of the variance of sample take, and, in the illustrative material presented, result in varying degrees of overlap before and after the changes of sizes. These methods are particularly applicable to systematic samples where repetitive panel operations are employed, for example, as in the Canadian Labour Force Survey. In the Canadian Labour Force Survey, a self-weighting sample is selected in two to four stages, often by means of systematic sampling with probability proportional to size, the size being Census or field counts of persons or dwellings. This results in a sample which provides population estimates of employment and unemployment with sufficient accuracy for the cost provided at...

Several Methods of Re-Designing Area Samples Utilizing Probabilities Proportional to Size when the Sizes Change Significantly

Abstract For purposes of obtaining statistical data by enumeration, systematic sampling with probability proportional to size in one or more stages is frequently employed. The article describes two methods of changing the measures of sizes without introducing a bias in the estimation procedure. They result in the reduction of the variance of sample take, and, in the illustrative material presented, result in varying degrees of overlap before and after the changes of sizes. These methods are particularly applicable to systematic samples where repetitive panel operations are employed, for example, as in the Canadian Labour Force Survey. In the Canadian Labour Force Survey, a self-weighting sample is selected in two to four stages, often by means of systematic sampling with probability proportional to size, the size being Census or field counts of persons or dwellings. This results in a sample which provides population estimates of employment and unemployment with sufficient accuracy for the cost provided at the provincial and national levels and a sample which can be easily maintained for long periods of time. Unfortunately, the so-called measures of size used in the systematic samples become out of date because of uneven growth in the first stage units. N. Keyfitz [3] and I. P. Fellegi [2] have dealt effectively with methods of adjusting measures of size in the case where one or two units are selected at random without replacement with probability proportional to size so that as few new units need be selected as possible. Other methods of dealing with burgeoning growth have been dealt with by L. Kish [4] and the Bureau of the Census [5].

The New Design of the Canadian Labour Force Survey

Abstract The Canadian Labour Force Survey is the largest continuing field survey conducted by the Dominion Bureau of Statistics. It was established as a quarterly survey in 1945 and was altered to a monthly one in 1952. Changes in the basic needs of the users of the survey and changes in the characteristics of the country made it increasingly difficult to cope with the survey without a complete over-haul. The Canadian Labour Force Survey was completely redesigned over a two year period beginning early 1964 and ending December, 1965. Decisions, which led to the re-design of the Canadian Labour Force are dealt with extensively. A detailed description is given of all the stages involved in the new design. The L.F.S. design introduced changes in stratification and in a re-allocation of the sample both between provinces and within strata. An important departure from the old design is the selection of two p.s.u.'s per stratum and the establishment of special samples in the self-representing units. The important feature of the new design is its design-flexibility so that future changes may be achieved without major revision of the whole survey. The theoretical aspects of cost and variance function are also described in detail.

The New Design of the Canadian Labour Force Survey

Abstract The Canadian Labour Force Survey is the largest continuing field survey conducted by the Dominion Bureau of Statistics. It was established as a quarterly survey in 1945 and was altered to a monthly one in 1952. Changes in the basic needs of the users of the survey and changes in the characteristics of the country made it increasingly difficult to cope with the survey without a complete over-haul. The Canadian Labour Force Survey was completely redesigned over a two year period beginning early 1964 and ending December, 1965. Decisions, which led to the re-design of the Canadian Labour Force are dealt with extensively. A detailed description is given of all the stages involved in the new design. The L.F.S. design introduced changes in stratification and in a re-allocation of the sample both between provinces and within strata. An important departure from the old design is the selection of two p.s.u.'s per stratum and the establishment of special samples in the self-representing units. The important...