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- 1. Estimating TFP in the Presence of Outliers and Leverage Points: An Examination of the KLEMS Dataset ArchivedArticles and reports: 11F0027M2007047Geography: CanadaDescription:
This paper examines the effect of aberrant observations in the Capital, Labour, Energy, Materials and Services (KLEMS) database and a method for dealing with them. The level of disaggregation, data construction and economic shocks all potentially lead to aberrant observations that can influence estimates and inference if care is not exercised. Commonly applied pre-tests, such as the augmented Dickey-Fuller and the Kwaitkowski, Phillips, Schmidt and Shin tests, need to be used with caution in this environment because they are sensitive to unusual data points. Moreover, widely known methods for generating statistical estimates, such as Ordinary Least Squares, may not work well when confronted with aberrant observations. To address this, a robust method for estimating statistical relationships is illustrated.
Release date: 2007-12-05 - Surveys and statistical programs – Documentation: 15-206-X2007012Description:
This paper examines the various products associated with the quarterly labour productivity program. It outlines the nature of the volatility in the very short-run estimates and examines properties of the revisions made to the estimates of Canadian labour productivity and its components (gross domestic product and hours worked) since the inception of the program in 2001.
Release date: 2007-10-18 - Articles and reports: 12-001-X20070019847Description:
We investigate the impact of cluster sampling on standard errors in the analysis of longitudinal survey data. We consider a widely used class of regression models for longitudinal data and a standard class of point estimators of a generalized least squares type. We argue theoretically that the impact of ignoring clustering in standard error estimation will tend to increase with the number of waves in the analysis, under some patterns of clustering which are realistic for many social surveys. The implication is that it is, in general, at least as important to allow for clustering in standard errors for longitudinal analyses as for cross-sectional analyses. We illustrate this theoretical argument with empirical evidence from a regression analysis of longitudinal data on gender role attitudes from the British Household Panel Survey. We also compare two approaches to variance estimation in the analysis of longitudinal survey data: a survey sampling approach based upon linearization and a multilevel modelling approach. We conclude that the impact of clustering can be seriously underestimated if it is simply handled by including an additive random effect to represent the clustering in a multilevel model.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019848Description:
We investigate some modifications of the classical single-spell Cox model in order to handle multiple spells from the same individual when the data are collected in a longitudinal survey based on a complex sample design. One modification is the use of a design-based approach for the estimation of the model coefficients and their variances; in the variance estimation each individual is treated as a cluster of spells, bringing an extra stage of clustering into the survey design. Other modifications to the model allow a flexible specification of the baseline hazard to account for possibly differential dependence of hazard on the order and duration of successive spells, and also allow for differential effects of the covariates on the spells of different orders. These approaches are illustrated using data from the Canadian Survey of Labour and Income Dynamics (SLID).
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019850Description:
Auxiliary information is often used to improve the precision of survey estimators of finite population means and totals through ratio or linear regression estimation techniques. Resulting estimators have good theoretical and practical properties, including invariance, calibration and design consistency. However, it is not always clear that ratio or linear models are good approximations to the true relationship between the auxiliary variables and the variable of interest in the survey, resulting in efficiency loss when the model is not appropriate. In this article, we explain how regression estimation can be extended to incorporate semiparametric regression models, in both simple and more complicated designs. While maintaining the good theoretical and practical properties of the linear models, semiparametric models are better able to capture complicated relationships between variables. This often results in substantial gains in efficiency. The applicability of the approach for complex designs using multiple types of auxiliary variables will be illustrated by estimating several acidification-related characteristics for a survey of lakes in the Northeastern US.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019851Description:
To model economic depreciation, a database is used that contains information on assets discarded by companies. The acquisition and resale prices are known along with the length of use of these assets. However, the assets for which prices are known are only those that were involved in a transaction. While an asset depreciates on a continuous basis during its service life, the value of the asset is only known when there has been a transaction. This article proposes an ex post weighting to offset the effect of source of error in building econometric models.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019852Description:
A common class of survey designs involves selecting all people within selected households. Generalized regression estimators can be calculated at either the person or household level. Implementing the estimator at the household level has the convenience of equal estimation weights for people within households. In this article the two approaches are compared theoretically and empirically for the case of simple random sampling of households and selection of all persons in each selected household. We find that the household level approach is theoretically more efficient in large samples and any empirical inefficiency in small samples is limited.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019853Description:
Two-phase sampling is a useful design when the auxiliary variables are unavailable in advance. Variance estimation under this design, however, is complicated particularly when sampling fractions are high. This article addresses a simple bootstrap method for two-phase simple random sampling without replacement at each phase with high sampling fractions. It works for the estimation of distribution functions and quantiles since no rescaling is performed. The method can be extended to stratified two-phase sampling by independently repeating the proposed procedure in different strata. Variance estimation of some conventional estimators, such as the ratio and regression estimators, is studied for illustration. A simulation study is conducted to compare the proposed method with existing variance estimators for estimating distribution functions and quantiles.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019854Description:
We derive an estimator of the mean squared error (MSE) of the empirical Bayes and composite estimator of the local-area mean in the standard small-area setting. The MSE estimator is a composition of the established estimator based on the conditional expectation of the random deviation associated with the area and a naïve estimator of the design-based MSE. Its performance is assessed by simulations. Variants of this MSE estimator are explored and some extensions outlined.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019856Description:
The concept of 'nearest proportional to size sampling designs' originated by Gabler (1987) is used to obtain an optimal controlled sampling design, ensuring zero selection probabilities to non-preferred samples. Variance estimation for the proposed optimal controlled sampling design using the Yates-Grundy form of the Horvitz-Thompson estimator is discussed. The true sampling variance of the proposed procedure is compared with that of the existing optimal controlled and uncontrolled high entropy selection procedures. The utility of the proposed procedure is demonstrated with the help of examples.
Release date: 2007-06-28
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Analysis (15)
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- 1. Estimating TFP in the Presence of Outliers and Leverage Points: An Examination of the KLEMS Dataset ArchivedArticles and reports: 11F0027M2007047Geography: CanadaDescription:
This paper examines the effect of aberrant observations in the Capital, Labour, Energy, Materials and Services (KLEMS) database and a method for dealing with them. The level of disaggregation, data construction and economic shocks all potentially lead to aberrant observations that can influence estimates and inference if care is not exercised. Commonly applied pre-tests, such as the augmented Dickey-Fuller and the Kwaitkowski, Phillips, Schmidt and Shin tests, need to be used with caution in this environment because they are sensitive to unusual data points. Moreover, widely known methods for generating statistical estimates, such as Ordinary Least Squares, may not work well when confronted with aberrant observations. To address this, a robust method for estimating statistical relationships is illustrated.
Release date: 2007-12-05 - Articles and reports: 12-001-X20070019847Description:
We investigate the impact of cluster sampling on standard errors in the analysis of longitudinal survey data. We consider a widely used class of regression models for longitudinal data and a standard class of point estimators of a generalized least squares type. We argue theoretically that the impact of ignoring clustering in standard error estimation will tend to increase with the number of waves in the analysis, under some patterns of clustering which are realistic for many social surveys. The implication is that it is, in general, at least as important to allow for clustering in standard errors for longitudinal analyses as for cross-sectional analyses. We illustrate this theoretical argument with empirical evidence from a regression analysis of longitudinal data on gender role attitudes from the British Household Panel Survey. We also compare two approaches to variance estimation in the analysis of longitudinal survey data: a survey sampling approach based upon linearization and a multilevel modelling approach. We conclude that the impact of clustering can be seriously underestimated if it is simply handled by including an additive random effect to represent the clustering in a multilevel model.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019848Description:
We investigate some modifications of the classical single-spell Cox model in order to handle multiple spells from the same individual when the data are collected in a longitudinal survey based on a complex sample design. One modification is the use of a design-based approach for the estimation of the model coefficients and their variances; in the variance estimation each individual is treated as a cluster of spells, bringing an extra stage of clustering into the survey design. Other modifications to the model allow a flexible specification of the baseline hazard to account for possibly differential dependence of hazard on the order and duration of successive spells, and also allow for differential effects of the covariates on the spells of different orders. These approaches are illustrated using data from the Canadian Survey of Labour and Income Dynamics (SLID).
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019850Description:
Auxiliary information is often used to improve the precision of survey estimators of finite population means and totals through ratio or linear regression estimation techniques. Resulting estimators have good theoretical and practical properties, including invariance, calibration and design consistency. However, it is not always clear that ratio or linear models are good approximations to the true relationship between the auxiliary variables and the variable of interest in the survey, resulting in efficiency loss when the model is not appropriate. In this article, we explain how regression estimation can be extended to incorporate semiparametric regression models, in both simple and more complicated designs. While maintaining the good theoretical and practical properties of the linear models, semiparametric models are better able to capture complicated relationships between variables. This often results in substantial gains in efficiency. The applicability of the approach for complex designs using multiple types of auxiliary variables will be illustrated by estimating several acidification-related characteristics for a survey of lakes in the Northeastern US.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019851Description:
To model economic depreciation, a database is used that contains information on assets discarded by companies. The acquisition and resale prices are known along with the length of use of these assets. However, the assets for which prices are known are only those that were involved in a transaction. While an asset depreciates on a continuous basis during its service life, the value of the asset is only known when there has been a transaction. This article proposes an ex post weighting to offset the effect of source of error in building econometric models.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019852Description:
A common class of survey designs involves selecting all people within selected households. Generalized regression estimators can be calculated at either the person or household level. Implementing the estimator at the household level has the convenience of equal estimation weights for people within households. In this article the two approaches are compared theoretically and empirically for the case of simple random sampling of households and selection of all persons in each selected household. We find that the household level approach is theoretically more efficient in large samples and any empirical inefficiency in small samples is limited.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019853Description:
Two-phase sampling is a useful design when the auxiliary variables are unavailable in advance. Variance estimation under this design, however, is complicated particularly when sampling fractions are high. This article addresses a simple bootstrap method for two-phase simple random sampling without replacement at each phase with high sampling fractions. It works for the estimation of distribution functions and quantiles since no rescaling is performed. The method can be extended to stratified two-phase sampling by independently repeating the proposed procedure in different strata. Variance estimation of some conventional estimators, such as the ratio and regression estimators, is studied for illustration. A simulation study is conducted to compare the proposed method with existing variance estimators for estimating distribution functions and quantiles.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019854Description:
We derive an estimator of the mean squared error (MSE) of the empirical Bayes and composite estimator of the local-area mean in the standard small-area setting. The MSE estimator is a composition of the established estimator based on the conditional expectation of the random deviation associated with the area and a naïve estimator of the design-based MSE. Its performance is assessed by simulations. Variants of this MSE estimator are explored and some extensions outlined.
Release date: 2007-06-28 - Articles and reports: 12-001-X20070019856Description:
The concept of 'nearest proportional to size sampling designs' originated by Gabler (1987) is used to obtain an optimal controlled sampling design, ensuring zero selection probabilities to non-preferred samples. Variance estimation for the proposed optimal controlled sampling design using the Yates-Grundy form of the Horvitz-Thompson estimator is discussed. The true sampling variance of the proposed procedure is compared with that of the existing optimal controlled and uncontrolled high entropy selection procedures. The utility of the proposed procedure is demonstrated with the help of examples.
Release date: 2007-06-28 - Articles and reports: 11-522-X20050019443Description:
A large part of sample survey theory has been directly motivated by practical problems encountered in the design and analysis of sample surveys. On the other hand, sample survey theory has influenced practice, often leading to significant improvements. This paper will examine this interplay over the past 60 years or so.
Release date: 2007-03-02
Reference (3)
Reference (3) ((3 results))
- Surveys and statistical programs – Documentation: 15-206-X2007012Description:
This paper examines the various products associated with the quarterly labour productivity program. It outlines the nature of the volatility in the very short-run estimates and examines properties of the revisions made to the estimates of Canadian labour productivity and its components (gross domestic product and hours worked) since the inception of the program in 2001.
Release date: 2007-10-18 - 2. Multifactor Productivity in Canada: An Evaluation of Alternative Methods of Estimating Capital Services ArchivedSurveys and statistical programs – Documentation: 15-206-X2007009Description:
This paper examines the effects of alternative specifications of the user costs of capital on the estimated price and volume indices of capital services. It asks how sensitive the results are to the use of exogenous versus endogenous rates of return, to alternate ways of including capital gains, and to whether corrections are made for tax rates. The paper also examines the effect of the various user cost formulae on the measured multifactor productivity growth.
Release date: 2007-04-04 - 3. Depreciation Rates for the Productivity Accounts ArchivedSurveys and statistical programs – Documentation: 15-206-X2007005Description:
This paper generates depreciation profiles for a diverse set of assets based on patterns of resale prices and retirements. In doing so, it explores the sensitivity of estimates of the growth in capital stock and capital services to alternate estimates of depreciation.
In the first instance, survival analysis techniques are used to estimate changes in valuation of assets over the course of their service life. In the second instance, a two-step procedure is utilized that first estimates the discard function for used assets (assets discarded at zero prices) and then uses the resulting estimates to correct for selection bias that arises when just positive used-asset prices are employed to estimate age-price profiles to produce depreciation rates. For the third method, a discard function and an asset efficiency function are jointly specified and estimated.
These three different methods produce depreciation profiles that follow convex patterns. Accelerated profiles are apparent for many individual assets in the machinery and equipment and structures classes.
We also compare the ex post estimates of length of life that are based on outcomes to ex ante expected lives and find they are much the same. We therefore choose ex ante lives along with information from the ex post rates on the rate of decline in an asset's value to generate a set of depreciation rates for use in the productivity accounts.
We then use our depreciation model to produce estimates of the growth in capital stock and capital services over the 1961 to 1996 period. We find that the resulting estimates of capital stock and capital services are quite similar to those previously produced.
Release date: 2007-02-12
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