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235
Missing data: Our view of the state of the art
 Psychological Methods
, 2002
"... Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missingdata problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random ..."
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Cited by 689 (1 self)
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Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missingdata problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art. Why do missing data create such difficulty in scientific research? Because most data analysis procedures were not designed for them. Missingness is usually a nuisance, not the main focus of inquiry, but
Evaluating the Accuracy of SamplingBased Approaches to the Calculation of Posterior Moments
 IN BAYESIAN STATISTICS
, 1992
"... Data augmentation and Gibbs sampling are two closely related, samplingbased approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accurac ..."
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Cited by 583 (14 self)
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Data augmentation and Gibbs sampling are two closely related, samplingbased approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accuracy of the approximations to the expected value of functions of interest under the posterior. In this paper methods from spectral analysis are used to evaluate numerical accuracy formally and construct diagnostics for convergence. These methods are illustrated in the normal linear model with informative priors, and in the Tobitcensored regression model.
Foreign Investment and Productivity Growth in Czech Enterprises
 The World Bank Economic Review
, 1999
"... this paper was presented at the conference Trade and Technology Diffusion: the Evidence with Implications for Developing Countries, Fondazione Mattei, Milan April 1819, 1998. We are grateful to Magnus Blomstrom, Caroline Freund, Ann Harrison, Roberto Rocha, Jim Tybout and three anonymous referees f ..."
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Cited by 132 (0 self)
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this paper was presented at the conference Trade and Technology Diffusion: the Evidence with Implications for Developing Countries, Fondazione Mattei, Milan April 1819, 1998. We are grateful to Magnus Blomstrom, Caroline Freund, Ann Harrison, Roberto Rocha, Jim Tybout and three anonymous referees for helpful comments and suggestions. 1
Semiparametric estimation of the intercept of a sample selection model
 Review of Economic Studies
, 1998
"... This paper provides a consistent and asymptotically normal estimator for the intercept of a semiparametrically estimated sample selection model. The estimator uses a decreasingly small fraction of all observations as the sample size goes to infinity, as in Heckman (1990). In the semiparametrics lite ..."
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Cited by 66 (2 self)
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This paper provides a consistent and asymptotically normal estimator for the intercept of a semiparametrically estimated sample selection model. The estimator uses a decreasingly small fraction of all observations as the sample size goes to infinity, as in Heckman (1990). In the semiparametrics literature, estimation of the intercept has typically been subsumed in the nonparametric sample selection bias correction term. The estimation of the intercept, however, is important from an economic perspective. For instance, it permits one to determine the "wage gap " between unionized and nonunionized workers, decompose the wage differential between different socioeconomic groups (e.g. malefemale and blackwhite), and evaluate the net benefits of a social programme. 1.
TwoStep Estimation of Panel Data Models with Censored Endogenous Variables and Selection
"... This paper presents some twostep estimators for a wide range of parametric panel data models with censored endogenous variables and sample selection bias. Our approach is to derive estimates of the unobserved heterogeneity responsible for the endogeneity/selection bias to include as additional expl ..."
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Cited by 56 (3 self)
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This paper presents some twostep estimators for a wide range of parametric panel data models with censored endogenous variables and sample selection bias. Our approach is to derive estimates of the unobserved heterogeneity responsible for the endogeneity/selection bias to include as additional explanatory variables in the primary equation. These are obtained through a decomposition of the reduced form residuals. The panel nature of the data allows adjustment, and testing, for two forms of endogeneity and/or sample selection bias. Furthermore, it incorporates roles for dynamics and state dependence in the reduced form. Finally, we provide an empirical illustration which features our procedure and highlights the ability to test several of the underlying assumptions.
Developing Measures of Airports Productivity and Performance: An Application of Data Envelopment Analysis
 Transportation Research Part E
, 1997
"... Since deregulation the measurement of productivity performance and profitability of the air transport industry has attracted significant attention. Many studies have been undertaken on the financial and economic productivity of airlines but few have concentrated on the productivity or performance of ..."
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Cited by 33 (0 self)
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Since deregulation the measurement of productivity performance and profitability of the air transport industry has attracted significant attention. Many studies have been undertaken on the financial and economic productivity of airlines but few have concentrated on the productivity or performance of airports, and how changes in the industry may have affected them. Airports have been quite traditional in their approach to assess their performance. Most measure it in strictly accounting terms by looking at only their total costs and revenue levels and at the resulting surpluses or deficits. Few utilize any type of productivity measures or performance indicators. A broader method of measuring the efficiency and productivity in both financial and physical terms is therefore needed In this paper a new approach to assessing the performance or productivity of airports is developed and estimated. Data Envelope Analysis is used to construct performance indices on the basis of the multiple outputs which airports produce and the multiple inputs which they utilize. In particular we develop productivity measures for terminals and airside operations. The performance measures are then used in a second stage Tobit regression in which environmental, structural and managerial variables are included. The regression results provide a 'net ' performance index and also identify which variables the managers have some control over and what the relative importance of each variable is in affecting
2009, Pitfalls in estimating asymmetric effects of energy price shocks, Mimeo
"... Abstract: A common view in the literature is that the effect of energy price shocks on macroeconomic aggregates is asymmetric in energy price increases and decreases. We show that widely used asymmetric vector autoregressive models of the transmission of energy price shocks are misspecified, resulti ..."
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Cited by 25 (7 self)
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Abstract: A common view in the literature is that the effect of energy price shocks on macroeconomic aggregates is asymmetric in energy price increases and decreases. We show that widely used asymmetric vector autoregressive models of the transmission of energy price shocks are misspecified, resulting in inconsistent parameter estimates, and that the implied impulse responses have been routinely computed incorrectly. As a result, the quantitative importance of unanticipated energy price increases for the U.S. economy has been exaggerated. In response to this problem, we develop alternative regression models and methods of computing responses to energy price shocks that yield consistent estimates regardless of the degree of asymmetry. We also introduce improved tests of the null hypothesis of symmetry in the responses to energy price increases and decreases. An empirical study reveals little evidence against the null hypothesis of symmetry in the responses to energy price shocks. Our analysis also has direct implications for the theoretical literature on the transmission of energy price shocks and for the debate about policy responses to energy price shocks.
Maximum likelihood estimation via the ECM algorithm: Computing the asymptotic variance
, 1994
"... Abstract: This paper provides detailed theory, algorithms, and illustrations for computing asymptotic variancecovariance matrices for maximum likelihood estimates using the ECM algorithm (Meng and Rubin (1993)). This Supplemented ECM (SECM) algorithm is developed as an extension of the Supplemented ..."
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Cited by 25 (3 self)
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Abstract: This paper provides detailed theory, algorithms, and illustrations for computing asymptotic variancecovariance matrices for maximum likelihood estimates using the ECM algorithm (Meng and Rubin (1993)). This Supplemented ECM (SECM) algorithm is developed as an extension of the Supplemented EM (SEM) algorithm (Meng and Rubin (1991a)). Explicit examples are given, including one that demonstrates SECM, like SEM, has a powerful internal error detecting system for the implementation of the parent ECM or of SECM itself.
Innovation and productivity in SMEs: empirical evidence for Italy
 SMALL BUS ECON
, 2009
"... Innovation in SMEs exhibits some peculiar features that most traditional indicators of innovation activity do not capture. Therefore, in this paper, we develop a structural model of innovation that incorporates information on innovation success from firm surveys along with the usual R&D expendit ..."
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Cited by 22 (1 self)
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Innovation in SMEs exhibits some peculiar features that most traditional indicators of innovation activity do not capture. Therefore, in this paper, we develop a structural model of innovation that incorporates information on innovation success from firm surveys along with the usual R&D expenditures and productivity measures. We then apply the model to data on Italian SMEs from the
Insider lending and bank ownership: The case of Russia
 Journal of Comparative Economics
, 2001
"... Abstract: We develop a model of insider lending in which a borrower can give incentives to a bank manager to misuse his right of control by extending a loan at favorable rates to the borrower at the expense of the equity value of the bank. The model explains why insider loans are often made to borro ..."
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Cited by 20 (1 self)
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Abstract: We develop a model of insider lending in which a borrower can give incentives to a bank manager to misuse his right of control by extending a loan at favorable rates to the borrower at the expense of the equity value of the bank. The model explains why insider loans are often made to borrowing firms that are also large shareholders of the bank. Although in principal every borrower could bribe the bank manager for insider loans, large shareholders have the power to fire the bank manager and will use this power if the manager extends insider loans to others. Therefore, a bank manager has an incentive to favor large shareholders when engaging into insider lending. Using a World Bank survey of Russian enterprises, we provide support for our model. We find that Russian firms and banks engaged into insider lending on the basis of loan volume. To limit insider lending, we propose proper incentives for bank managers, such as high penalties or equity incentive schemes.