89 research outputs found
Estimation of a Two-Equation Panel Model with Mixed Continuous and Ordered Categorical Outcomes and Missing Data
On the Returns to Occupational Qualification in Terms of Subjective and Objective Variables: A GEE-type Approach to the Estimation of Two-Equation Panel Models
This article proposes an estimation approach for panel models with mixed continuous and ordered categorical outcomes based on generalized estimating equations for the mean and pseudo-score equations for the covariance parameters. A numerical study suggests that efficiency can be gained as concerns the mean parameter estimators by using individual covariance matrices in the estimating equations for the mean parameters. The approach is applied to estimate the returns to occupational qualification in terms of income and perceived job security in a nine-year period based on the German Socio-Economic Panel (SOEP). To compensate for missing data, a combined multiple imputation/weighting approach is adopted.Generalized estimating equations, mean and covariance model, multiple imputation, pseudo-score equations, status inconsistency, weighting
Documentation of Sample Sizes and Panel Attrition in the German Socio Economic Panel (SOEP) 1984 - 2003
Documentation of Sample Sizes and Panel Attrition in the German Socio Economic Panel (SOEP) (1984 until 2006)
Documentation of Sample Sizes and Panel Attrition in the German Socio Economic Panel (SOEP) (1984 until 2005)
Documentation of Sample Sizes and Panel Attrition in the German Socio Economic Panel (SOEP) (1984 until 2007)
The Data Quality Concept of Accuracy in the Context of Public Use Data Sets
Like other data quality dimensions, the concept of accuracy is often adopted to characterise a particular data set. However, its common specification basically refers to statistical properties of estimators, which can hardly be proved by means of a single survey at hand. This ambiguity can be resolved by assigning 'accuracy' to survey processes that are known to affect these properties. In this contribution, we consider the sub-process of imputation as one important step in setting up a data set and argue that the so called 'hit-rate' criterion, that is intended to measure the accuracy of a data set by some distance function of 'true' but unobserved and imputed values, is neither required nor desirable. In contrast, the so-called 'inference' criterion allows for valid inferences based on a suitably completed data set under rather general conditions. The underlying theoretical concepts are illustrated by means of a simulation study. It is emphasised that the same principal arguments apply to other survey processes that introduce uncertainty into an edited data set.Survey Quality, Survey Processes, Accuracy, Assessment of Imputation Methods, Multiple Imputation
GEE Estimation of a Two-Equation Panel Data Model: An Analysis of Wage Dynamics and the Incidence of Profit-Sharing in West Germany
We propose a generalized estimating equations approach to the analysis of the mean and the covariance structure of a bivariate time series process of panel data with mixed continuous and discrete dependent variables. The approach is used to jointly analyze wage dynamics and the incidence of profit-sharing in West Germany. Our findings reveal a significantly positive conditional correlation of wages and the incidence of profit-sharing. Furthermore, they indicate that permanent unobserved individual ability is comparatively more important in the profit-sharing than in the wage equation and show that shocks have a long-lasting effect on transitory wages but not on the incidence of profit-sharing. Hence, the results support theoretical predictions that selection into profit-sharing is mostly due to unobservable ability and that profit-sharing ties wages more closely to productivity.Generalized estimating equations, covariance structure, longitudinal data, real wages, variable pay
Modifying the Rebound: It Depends!: Explaining Mobility Behaviour on the Basis of the German Socio-Economic Panel
We address the empirical question to which extent higher fuel efficiency of cars affects additional travel and how this behavioural aspect is modified by additional variables. The data set used to estimate a theoretical model of the rebound effect covers two panel waves, 1998 and 2003, taken from the German Socio-Economic Panel (SOEP). To take full advantage of the information in the data available, and to avoid problems due to possible selection effects, we estimated an unbalanced two-wave random effects panel model. Our results suggest that in line with the rebound hypothesis, there is a negative effect of car efficiency on the kilometers driven. That is, the lower the fuel consumption, the larger the driven distance. However, contrasting recent empirical literature about the rebound effect in the transportation sector, this seems to be true only for cars with a consumption of more than roughly eight liters per hundred kilometers. In addition, we find a positive diesel effect, which implies that owning a diesel engined car, has a positive effect on the driven distance. Both effects can be interpreted as support for the rebound hypothesis, although not in a simple linear way. Moreover, it can be shown that some "soft" variables such as certain attitudes towards the environment tend to amplify this non-linear rebound effect. Our results support the general direction of the rebound effect on households travel activities. But because of the remaining political relevance of the rebound effect, they also highlight the importance of accounting for additional behavioural variables which tend to influence individual mobility behaviour. Hence, the classical interpretation of the rebound as a linear effect of advances in fuel economy on individual travel has to be questioned.energy demand, rebound effect, panel data analysis
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