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Testing the augmented Solow model
 Journal of Applied Econometrics
, 1995
"... This paper applies robustness ideas from the modern statistics literature to the study of the augmented Solow model. It also tests the model in other dimensions, including sensitivity to measurement error. The main ¯ndings are that the speed of conditional convergence is highly uncertain, that techn ..."
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Cited by 31 (3 self)
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This paper applies robustness ideas from the modern statistics literature to the study of the augmented Solow model. It also tests the model in other dimensions, including sensitivity to measurement error. The main ¯ndings are that the speed of conditional convergence is highly uncertain, that technology parameters obtained from the augmented Solow model cannot be trusted, and that the model does not work well when attention is restricted to either the OECD or developing countries. Not only that, the equation for steady state human capital is rejected by the data. I am grateful to Steven Klepper, John Muellbauer, Steve Nickell and Steve Redding for useful comments and suggestions. y Email jon.temple@nu±eld.oxford.ac.uk This paper examines the adequacy of the augmented Solow model for explaining international variation in the standard of living. In particular, is technology usefully described by a common CobbDouglas production function, which takes human capital as one of its in...
Using Path Diagrams as a Structural Equation Modelling Tool
, 1997
"... this paper, we will show how path diagrams can be used to solve a number of important problems in structural equation modelling. There are a number of problems associated with structural equation modeling. These problems include: ..."
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Cited by 29 (7 self)
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this paper, we will show how path diagrams can be used to solve a number of important problems in structural equation modelling. There are a number of problems associated with structural equation modeling. These problems include:
Bayesian Estimation and Testing of Structural Equation Models
 Psychometrika
, 1999
"... The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameter ..."
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Cited by 27 (8 self)
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The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those based on the maximum likelihood solution, e.g., output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters of underidentified models, as we illustrate on a simple errorsinvariables model.
Automated search for causal relations: Theory and practice
 Heuristics, Probability and Causality: A Tribute to Judea Pearl
, 2010
"... The rapid spread of interest in the last two decades in principled methods of search or estimation of causal relations has been driven in part by technological developments, especially the changing nature of modern data collection and storage techniques, and the increases in the speed and storage ca ..."
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Cited by 2 (0 self)
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The rapid spread of interest in the last two decades in principled methods of search or estimation of causal relations has been driven in part by technological developments, especially the changing nature of modern data collection and storage techniques, and the increases in the speed and storage capacities of computers. Statistics books from 30 years