Silva, João M.C. Santos; Windmeijer, Frank
Blundell, Richard; Dias, Monica Costa
The research is part of the program of the ESRC Centre for the Microeconomic Analysis of Fiscal Policy at IFS. Financial support from the ESRC is gratefully acknowledged. The second author also acknowledges the financial support from Sub-Programa Cieˆncia e Tecnologia do Segundo Quadro Comunita´rio de Apoio, grant number PRAXIS XXI/BD/11413/97.
Wooldridge, Jeffrey M.
I provide an overviewof inverse probability weighted (IPW)M-estimators for cross section and two-period panel data applications. Under an ignorability assumption, I show that population parameters are identified,and provide straightforward √ N-consistent and asymptotically normal estimation methods. I show that estimating a binary response selection model by conditional maximum likelihood leads to a more efficient estimator than using known probabilities,a result that unifies several disparate results in the literature. But IPW estimation is not a panacea: in some important cases of nonresponse,unweighted estimators will be consistent under weaker ignorability assumptions.
Bond, Stephen R.
This paper reviews econometric methods for dynamic panel data models, and presents examples that illustrate the use of these procedures. The focus is on panels where a large number of individuals or firms are observed for a small number of time periods, typical of applications with microeconomic data. The emphasis is on single equation models with autoregressive dynamics and explanatory variables that are not strictly exogenous, and hence on the Generalised Method of Moments estimators that are widely used in this context. Two examples using firm-level panels are discussed in detail: a simple autoregressive model for investment rates; and a...
Honore, Bo E.
Panel data play an important role in empirical economics. With panel data one can answer questions about microeconomic dynamic behavior that could not be answered with cross sectional data. Panel data techniques are also useful for analyzing cross sectional data with grouping. This paper discusses some issues related to specification and estimation of nonlinear models using panel data.
Bellemare, Charles; Melenberg, Bertrand; Soest, Arthur van
An overview is presented of some parametric and semi-parametric models, estimators, and specification tests that can be used to analyze ordered response variables. In particular, limited dependent variable models that general- ize ordered probit are compared to regression models that generalize the linear model. These techniques are then applied to analyze how self-reported satisfac- tion with household income relates to household income, family composition, and other background variables. Data are drawn from the 1998 wave of the German Socio-Economic Panel. The results are used to estimate equivalence scales and the cost of children. We find that the standard ordered probit...