| Working Paper |
File Downloads |
Abstract Views |
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3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Bootstrap Approach for Bandwidth Selection in Estimating Conditional Efficiency Measures |
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0 |
0 |
0 |
0 |
0 |
1 |
16 |
| A Bootstrap Approach for Bandwidth Selection in Estimating Conditional Efficiency Measures |
0 |
0 |
0 |
6 |
0 |
2 |
2 |
21 |
| A Bootstrap Approach for Bandwidth Selection in Estimating Conditional Efficiency Measures |
0 |
0 |
0 |
60 |
0 |
0 |
1 |
119 |
| A Fast Method for Implementing Hypothesis Tests with Multiple Sample Splits in Nonparametric Models of Production |
0 |
0 |
5 |
5 |
0 |
0 |
5 |
5 |
| A Flexible and Sustainable Analysis of Waste Efficiency at the European Level |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
4 |
| A General Framework for Frontier Estimation with Panel Data |
0 |
0 |
0 |
21 |
0 |
2 |
3 |
239 |
| A General Methodology for Bootstrapping in Nonparametric Frontier Models |
0 |
0 |
0 |
1 |
0 |
1 |
2 |
1,434 |
| A Note on the Convergence of Nonparametric DEA Efficiency Measures |
0 |
0 |
1 |
36 |
0 |
0 |
3 |
457 |
| A Note on the Convergence of Nonparametric DEA Efficiency Measures |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
972 |
| A general framework for frontier estimation with panel data |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
15 |
| A mollifier approach to the deconvolution of probability densities |
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0 |
0 |
0 |
0 |
0 |
3 |
4 |
| A mollifier approach to the deconvolution of probability densities |
0 |
0 |
0 |
14 |
0 |
1 |
3 |
36 |
| A mollifier approach to the deconvolution of probability densities |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
15 |
| A mollifier approach to the deconvolution of probability densities |
0 |
0 |
0 |
5 |
0 |
0 |
3 |
22 |
| A note on Stieltjes moment sequences |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
10 |
| A note on least-squares approximation in the Baesiann analysis of regression models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
19 |
| A note on the asymptotic relative efficiency of M.L.E. in a linear model wih gamma disturbances |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
64 |
| A note on the asymptotic relative efficiency of M.L.E. in a linear model with gamma disturbances |
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0 |
0 |
2 |
0 |
0 |
0 |
15 |
| A panel analysis of microfinance efficiency measures: Evidence on the effects of unobserved managerial ability |
0 |
0 |
6 |
6 |
0 |
0 |
4 |
4 |
| A survey of Bayesian approaches to nonparametric statistics |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
17 |
| Another Look at Productivity Growth in Industrialized Countries |
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0 |
0 |
8 |
0 |
0 |
0 |
6 |
| Another Look at the American Electrical Utility Data |
0 |
0 |
1 |
17 |
0 |
1 |
2 |
57 |
| Approximations and Inference for Nonparametric Production Frontiers |
0 |
0 |
0 |
12 |
0 |
1 |
2 |
11 |
| Approximations and Inference for Nonparametric Production Frontiers |
0 |
0 |
1 |
7 |
0 |
0 |
2 |
10 |
| Approximations and inference for envelopment estimators of production frontiers |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
| Aspects of Statistical Analysis in DEA-Type Frontier Models |
0 |
0 |
0 |
21 |
0 |
0 |
0 |
442 |
| Aspects of statistical analysis in DEA-type frontier models |
0 |
0 |
0 |
6 |
0 |
1 |
1 |
31 |
| Asymmetries in Business Cycles and the Role of Oil Prices |
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0 |
0 |
1 |
0 |
2 |
3 |
8 |
| Asymmetries in Business Cycles and the Role of Oil Prices |
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0 |
0 |
0 |
0 |
0 |
2 |
7 |
| Asymmetries in Business Cycles and the Role of Oil Production |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
| Asymptotic Theory for Aggregate Efficiency |
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0 |
0 |
57 |
0 |
0 |
0 |
88 |
| Asymptotic Theory for Aggregate Efficiency |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
8 |
| Asymptotic distribution of conical-hull estimators of directional edges |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
6 |
| Asymptotics and Consistent Bootstraps for DEA Estimators in Non-parametric Frontier Models |
0 |
0 |
1 |
299 |
0 |
0 |
1 |
605 |
| Bayesian predictions: non parametric methods and least-squares approximations |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
12 |
| Bootstrap Estimation for Nonparametric Efficiency Estimates |
0 |
0 |
0 |
20 |
0 |
0 |
0 |
81 |
| Boundary estimation in the presence of measurement error with unknown variance |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
5 |
| Boundary estimation in the presence of measurement error with unknown variance |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
| Categorical data in local maximum likelihood: theory and applications to productivity analysis |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
8 |
| Central Limit Theorems and Inference for Sources of Productivity Change Measured by Nonparametric Malmquist Indices |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
| Central Limit Theorems for Aggregate Efficiency |
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0 |
0 |
0 |
0 |
1 |
2 |
12 |
| Central Limit Theorems for Directional Distance Functions with and without Undesirable Outputs |
0 |
4 |
8 |
17 |
1 |
8 |
16 |
20 |
| Central limit theorems and inference for sources of productivity change measured by nonparametric Malmquist indices |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
10 |
| Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non-parametric, two-stage models of production |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
22 |
| Computational Efficient, Consistent Bootstrap for Inference with Non-parametric DEA Estimators |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
8 |
| Conditional Nonparametric Frontier Models for Convex and Non Convex Technologies: a Unifying Approach |
1 |
2 |
4 |
230 |
1 |
3 |
10 |
614 |
| Conical FDH Estimators of Directional Distances and Luenberger Productivity Indices for General Technologies |
0 |
0 |
1 |
6 |
0 |
1 |
6 |
10 |
| Conical FDH Estimators of General Technologies, with Applications to Returns to Scale and Malmquist Productivity Indices |
1 |
1 |
2 |
17 |
2 |
3 |
8 |
15 |
| Cross-Section Dependence and Latent Heterogeneity to Evaluate the Impact of Human Capital on Country Performance |
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0 |
0 |
0 |
0 |
1 |
1 |
11 |
| Data Sharpening for improving CLT approximations for DEA-type efficiency estimators |
0 |
0 |
3 |
72 |
0 |
0 |
3 |
72 |
| Data sharpening for improving CLT approximations for DEA-type efficiency estimators |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
7 |
| Data sharpening for improving central limit theorem approximations for data envelopment analysis-type efficiency estimators |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
| Decomposing Regional Efficiency |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
6 |
| Decomposing regional efficiency |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
5 |
| Decomposing regional efficiency |
0 |
0 |
0 |
117 |
0 |
0 |
0 |
218 |
| Directional Distances and their Robust versions. Computational and Testing Issues |
0 |
0 |
0 |
54 |
0 |
0 |
0 |
130 |
| Directional Distances and their Robust versions: Computational and Testing Issues |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
10 |
| Directional distances and their robust versions: Computational and testing issues |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
11 |
| Effect of FDI and Time on Catching-up: New Insights from a Conditional Nonparametric Frontier Analysis |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
| Effect of FDI and Time on Catching-up: New Insights from a Conditional Nonparametric Frontier Analysis |
0 |
0 |
1 |
6 |
0 |
0 |
3 |
14 |
| Efficiency and University Size: Discipline-wise Evidence from European Universities |
0 |
0 |
0 |
144 |
0 |
0 |
3 |
434 |
| Efficiency and benchmarking with directional distances. A data driven approach |
0 |
0 |
0 |
90 |
0 |
0 |
2 |
174 |
| Efficiency and benchmarking with directional distances: a data driven approach |
0 |
0 |
1 |
1 |
0 |
1 |
4 |
9 |
| Efficiency and benchmarking with directional distances: a data-driven approach |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Efficiency and economies of scale and scope in European universities. A directional distance approach |
0 |
0 |
0 |
136 |
0 |
0 |
3 |
347 |
| Efficiency and economies of scale and scope in European universities: a directional distance approach |
0 |
0 |
0 |
0 |
0 |
2 |
5 |
9 |
| Efficiency and economies of scale and specialization in European universities: a directional distance approach |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
7 |
| Efficiency of Italian Municipalities and Waste Regulatory Target |
0 |
0 |
1 |
2 |
0 |
3 |
5 |
9 |
| Efficient Estimation of Monotone Boundaries |
0 |
0 |
0 |
2 |
1 |
1 |
5 |
276 |
| Efficient Semiparametric Estimation in Stochastic Frontier Model |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
985 |
| Efficient semiparametric estimation in a stochastic frontier model |
0 |
0 |
0 |
6 |
0 |
0 |
1 |
94 |
| Efficient semiparametric estimation in stochastic frontier model |
0 |
0 |
0 |
15 |
0 |
0 |
2 |
278 |
| Estimating Nonparametric Conditional Frontiers and Efficiencies: A New Approach |
1 |
2 |
4 |
62 |
1 |
3 |
10 |
24 |
| Estimating a Changepoint, Boundary of Frontier in the Presence of Observation Error |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
287 |
| Estimating and bootstrapping malmquist indices |
0 |
0 |
0 |
67 |
0 |
1 |
2 |
736 |
| Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric methods with boot strapping |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
470 |
| Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric metods with bootstrapping |
0 |
0 |
1 |
13 |
0 |
0 |
4 |
42 |
| Estimating technical inefficiencies with correction for environmental conditions with an application to railway companies |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
27 |
| Estimation and Inference in Nonparametric Frontier Models: Recent Developments and Perspectives |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
| Estimation de frontières déterministes avec facteurs exogènes d'inefficacité |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
25 |
| Estimation of monotone boundaries |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
17 |
| Estimation of the Boundary of a Variable Observed With Symmetric Error |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
2 |
| Estimation of the Boundary of a Variable Observed with A Symmetric Error |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
10 |
| Estimation of the Boundary of a Variable Observed with A Symmetric Error |
0 |
0 |
0 |
48 |
0 |
1 |
2 |
42 |
| Estimation of the Boundary of a Variable observed with Symmetric Error |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
9 |
| Estimation of the Boundary of a Variable observed with Symmetric Error |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
| Estimation of the boundary of a variable observed with symmetric error |
0 |
0 |
0 |
11 |
0 |
0 |
2 |
24 |
| Explaining Inefficiency in Nonparametric Production Models: the State of the Art |
0 |
0 |
0 |
1 |
0 |
1 |
2 |
8 |
| Explaining inefficiency in nonparametric production models: the state of the art |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
11 |
| Fast and Efficient Computation of Directional Distance Estimators |
0 |
0 |
0 |
4 |
1 |
1 |
2 |
12 |
| Fast and Efficient Computation of Directional Distance Estimators |
0 |
0 |
0 |
44 |
0 |
0 |
1 |
96 |
| Fast and Efficient Computation of Directional Distance Estimators |
0 |
0 |
1 |
17 |
1 |
2 |
3 |
61 |
| Fast and efficient computation of directional distance estimators |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
10 |
| Forecasting of Recessions via Dynamic Probit for Time Series: Replication and Extension of Kauppi and Saikkonen (2008) |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
15 |
| Forecasting of Recessions via Dynamic Probit for Time Series: Replication and Extension of Kauppi and Saikkonen (2008) |
0 |
0 |
0 |
25 |
0 |
1 |
2 |
85 |
| Forecasting of recessions via dynamic probit for time series: replication and extension of Kauppi and Saikkonen (2008) |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
| Forecasting the Malmquist Productivity Index |
0 |
0 |
0 |
82 |
0 |
0 |
1 |
171 |
| Forecasting the Malmquist Productivity Index |
0 |
0 |
0 |
21 |
0 |
0 |
1 |
100 |
| Forecasting the Malmquist productivity index |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
10 |
| Frontier Estimation and Extreme Values Theory |
0 |
0 |
0 |
10 |
0 |
0 |
2 |
63 |
| Frontier Estimation and Extreme Values Theory |
0 |
0 |
0 |
29 |
0 |
1 |
2 |
65 |
| Frontier estimation in nonparametric location-scale models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
| Frontier estimation in nonparametric location-scale models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
12 |
| Frontier estimation in the presence of measurement error with unknown variance |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
12 |
| Further Improvements of Finite Sample Approximation of Central Limit Theorems for Envelopment Estimators |
0 |
0 |
0 |
25 |
0 |
1 |
2 |
36 |
| Further Improvements of Finite Sample Approximation of Central Limit Theorems for Envelopment Estimators |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
| Further Improvements of Finite Sample Approximation of Central Limit Theorems for Envelopment Estimators |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
7 |
| Gender effect on microfinance efficiency: A robust nonparametric approach |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
9 |
| Gender effect on microfinance social efficiency: A robust nonparametric approach |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
18 |
| Gender effect on microfinance social efficiency: A robust nonparametric approach |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
11 |
| Gender effect on microfinance social efficiency: A robust nonparametric approach |
0 |
0 |
1 |
11 |
0 |
3 |
6 |
34 |
| Generalized nonparametric smoothing with mixed discrete and continuous data |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
| Global Dependence and Productivity: A Robust Nonparametric World Frontier Analysis |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
| Globalization and productivity: A robust nonparametric world frontier analysis |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
7 |
| How to Improve the Performances of DEA/FDH Estimators in the Presence of Noise? |
0 |
0 |
0 |
20 |
0 |
0 |
0 |
105 |
| How to Measure the Impact of Environmental Factors in a Nonparametric Production Model? |
0 |
0 |
0 |
4 |
0 |
1 |
1 |
15 |
| How to measure the impact of environmental factors in a nonparametric production model |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
10 |
| How to measure the impact of environmental factors in a nonparametric production model? |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
18 |
| Hypothesis Testing in Nonparametric Models of Production using Multiple Sample Splits |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
14 |
| Hypothesis Testing in Nonparametric Models of Production using Multiple Sample Splits |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
12 |
| Impact of a Regulatory Target and External Factors on the Waste Efficiency of Italian Municipalities |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
3 |
| Improving Finite Sample Approximation by Central Limit Theorems for DEA and FDH efficiency scores |
0 |
0 |
1 |
1 |
1 |
2 |
4 |
15 |
| Improving Finite Sample Approximation by Central Limit Theorems for DEA and FDH efficiency scores |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
| Improving Finite Sample Approximation by Central Limit Theorems for DEA and FDH efficiency scores |
0 |
0 |
0 |
34 |
0 |
1 |
1 |
77 |
| Improving Finite Sample Approximation by Central Limit Theorems for Estimates from Data Envelopment Analysis |
0 |
0 |
0 |
24 |
0 |
0 |
1 |
27 |
| Inference by the m out of n bootstrap in nonparametric frontier models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Inference for Aggregate Efficiency: Theory and Guidelines for Practitioners |
0 |
0 |
0 |
24 |
0 |
0 |
0 |
14 |
| Inference for Aggregate Efficiency: Theory and Guidelines for Practitioners |
0 |
0 |
1 |
5 |
0 |
0 |
3 |
7 |
| Inference for aggregate efficiency: Theory and guidelines for practitioners |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
| Inference in Dynamic, Nonparametric Models of Production for General Technologies |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
3 |
| Inference in Dynamic, Nonparametric Models of Production for General Technologies |
0 |
0 |
0 |
9 |
0 |
1 |
2 |
7 |
| Inference in Dynamic, Nonparametric Models of Production: Central Limit Theorems for Malmquist Indices |
0 |
0 |
3 |
5 |
0 |
0 |
3 |
11 |
| Inference in Dynamic, Nonparametric Models of Production: Central Limit Theorems for Malmquist Indices |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
7 |
| Inference in the Nonparametric Stochastic Frontier Model |
0 |
1 |
3 |
33 |
0 |
2 |
9 |
38 |
| Inference in the nonparametric stochastic frontier model |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
4 |
| Inferences From Cross-sectional, Stochastic Frontier Models |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
5 |
| Innovation and export activities in the German mechanical engineering sector: an application of testing restrictions in production analysis |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
9 |
| Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach |
0 |
0 |
2 |
281 |
0 |
1 |
5 |
627 |
| Investigating the unobserved heterogeneity effect on microfinance social efficiency |
0 |
0 |
2 |
6 |
0 |
0 |
5 |
11 |
| Investigating the unobserved heterogeneity effect on outreach to women: lessons from microfinance institutions |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
4 |
| Investigating the unobserved heterogeneity effect on outreach to women: lessons from microfinance institutions |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
| Iterated bootstrap with applications to frontier models |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
13 |
| Iterated bootstrap with applications to frontier models |
0 |
0 |
0 |
164 |
2 |
2 |
2 |
444 |
| Iterated bootstrap with applications to frontier models |
0 |
0 |
0 |
0 |
1 |
2 |
3 |
138 |
| Latent heterogeneity to evaluate the effect of human capital on world technology frontier |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
11 |
| Least squares approximation in Bayesian analysis |
0 |
0 |
1 |
2 |
0 |
0 |
1 |
11 |
| Local Likelihood Estimation of Truncated Regression and Its Partial Derivatives: Theory and Application |
0 |
0 |
0 |
182 |
0 |
0 |
3 |
572 |
| Local Maximum Likelihood Techniques with Categorical Data |
0 |
0 |
0 |
83 |
1 |
1 |
2 |
305 |
| Local likelihood estimation of truncated regression and its partial derivatives: theory and application |
0 |
0 |
0 |
12 |
1 |
1 |
2 |
76 |
| Local maximum likelihood techniques with categorical data |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
4 |
| Maximum likelihood estimation of a compound Poisson process |
0 |
0 |
0 |
22 |
0 |
1 |
2 |
84 |
| Measuring Firm Performance Using Nonparametric Quantile-type Distances |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
7 |
| Measuring Firm Performance using Nonparametric Quantile-type Distances |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
10 |
| Measuring Firm Performance using Nonparametric Quantile-type Distances |
0 |
0 |
0 |
51 |
0 |
0 |
1 |
99 |
| Measuring labor-efficiency in post offices |
0 |
0 |
20 |
318 |
4 |
10 |
65 |
853 |
| Methodologies for assessing government efficiency |
0 |
0 |
0 |
1 |
0 |
0 |
4 |
16 |
| Methodologies for assessing government efficiency |
0 |
0 |
3 |
43 |
1 |
1 |
4 |
60 |
| Modern Tools for Evaluating the Performance of Health-Care Providers |
0 |
0 |
1 |
8 |
1 |
1 |
4 |
16 |
| Modified least-squares estimators for deterministic frontier functions |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
49 |
| Non Parametric Instrumental Variables Estimation for Efficiency Frontier |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
11 |
| Non Parametric Instrumental Variables Estimation for Efficiency Frontier |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
6 |
| Non-Parametric Approach to Dynamic Time Series Discrete Choice Models |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
| Non-Parametric Approach to Dynamic Time Series Discrete Choice Models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Nonparametric Estimation of Dynamic Discrete Choice Models for Time Series Data |
0 |
1 |
1 |
60 |
1 |
4 |
5 |
86 |
| Nonparametric Estimation of Efficiency in the Presence of Environmental Variables |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
14 |
| Nonparametric Estimation of Efficiency in the Presence of Environmental Variables |
0 |
0 |
0 |
113 |
0 |
3 |
3 |
127 |
| Nonparametric Least Squares Methods for Stochastic Frontier Models |
0 |
0 |
0 |
101 |
0 |
1 |
3 |
190 |
| Nonparametric Least Squares Methods for Stochastic Frontier Models |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
13 |
| Nonparametric Least Squares Methods for Stochastic Frontier Models |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
10 |
| Nonparametric Robust Stochastic Frontier Analysis: a Tikhonov Regularization Approach |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
| Nonparametric Statistical Analysis of Production |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
9 |
| Nonparametric conditional efficiency measures: asymptotic properties |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
| Nonparametric estimation of dynamic discrete choice models for time series data |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
7 |
| Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs |
0 |
0 |
2 |
62 |
1 |
1 |
7 |
101 |
| On Farrell Measures of Technical Efficiency |
0 |
0 |
0 |
14 |
0 |
0 |
1 |
38 |
| On Farrell measures of technical efficiency |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
19 |
| On estimation of monotone and concave frontier functions |
0 |
0 |
1 |
7 |
0 |
1 |
3 |
185 |
| On estimation of monotone and concave frontier functions |
0 |
0 |
0 |
4 |
0 |
0 |
2 |
73 |
| On estimation of monotone and concave frontier functions |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
19 |
| On estimation of monotone and convex boundaries |
0 |
0 |
0 |
0 |
1 |
1 |
6 |
264 |
| On teh inconsistency of bootstrap distribution estimators |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
254 |
| On testing equality of distributions of technical efficiency scores |
0 |
0 |
1 |
116 |
0 |
0 |
2 |
321 |
| On the inconsistency of bootstrap distribution estimators |
0 |
0 |
0 |
8 |
0 |
1 |
3 |
35 |
| Optimal Bandwidth Selection for Conditional Efficiency Measures: a Data-driven Approach |
0 |
0 |
0 |
166 |
0 |
0 |
4 |
366 |
| Optimal bandwidth selection for conditional efficiency measures: A data-driven approach |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
11 |
| Performance of the Bootstrap for DEA Estimators and Iterating the Principle |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
666 |
| Performance of the Bootstrap for DEA Estimators and Iterating the Principle |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
891 |
| Performance of the bootstrap for DEA estimators and iterating the principle |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
14 |
| Pitfalls of Normal-Gamma Stochastic Frontier Models |
0 |
0 |
1 |
20 |
0 |
0 |
3 |
111 |
| Pitfalls of normal-gamma stochastic frontier models |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
29 |
| Portfolio Selection in a Multi-Input Multi-Output Setting: a Simple Monte-Carlo-FDH Algorithm |
0 |
0 |
0 |
45 |
0 |
0 |
1 |
55 |
| Portfolio Selection in a Multi-Input Multi-Output Setting:a Simple Monte-Carlo-FDH Algorithm |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
6 |
| Portfolio selection in a multi-moment setting: A simple Monte-Carlo-FDH algorithm |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
7 |
| Predicting Recessions with a Frontier Measure of Output Gap: An Application to Italian Economy |
0 |
0 |
0 |
28 |
0 |
2 |
4 |
34 |
| Predicting Recessions: A New Measure of Output Gap as Predictor |
0 |
0 |
0 |
3 |
0 |
1 |
3 |
14 |
| Predicting Recessions: A New Measure of Output Gap as Predictor |
0 |
0 |
0 |
56 |
1 |
3 |
4 |
84 |
| Predicting recessions with a frontier measure of output gap: an application to Italian economy |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
6 |
| Probabilistic Characterization of Directional Distances and their Robust Versions |
0 |
0 |
0 |
47 |
0 |
0 |
0 |
128 |
| Probabilistic characterization of directional distances and their robust versions |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
7 |
| Probabilistic characterization of directionaldistances and their robustversions |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
7 |
| Productivity Growth in Industrialized Countries |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1,147 |
| Productivity Measurement In Radial Dea Models With Multiple Constant Inputs |
0 |
0 |
0 |
25 |
0 |
1 |
1 |
84 |
| Productivity growth in industrialized countries |
0 |
0 |
1 |
135 |
0 |
0 |
7 |
610 |
| Proportional Incremental Cost Probability Functions and their Frontiers |
0 |
0 |
0 |
10 |
0 |
1 |
1 |
13 |
| Proportional incremental cost probability functions and their frontiers |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
| Protecting against gross errors: the aid of Bayesian methods |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
8 |
| Quality and its Impact on Efficiency |
0 |
0 |
1 |
29 |
1 |
1 |
2 |
52 |
| Quality and its Impact on Efficiency |
1 |
1 |
5 |
40 |
1 |
4 |
24 |
208 |
| Quality and its impact on efficiency |
0 |
0 |
1 |
9 |
0 |
0 |
1 |
14 |
| Quality as a Latent Heterogeneity Factor in the Efficiency of Universities |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
6 |
| Rankings and university performance: A conditional multidimensional approach |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
10 |
| Rankings and university performance: a conditional multidimensional approach |
0 |
0 |
1 |
103 |
0 |
0 |
1 |
148 |
| Rankings and university performance: a conditional multidimensional approach |
0 |
0 |
1 |
4 |
0 |
0 |
2 |
16 |
| Regularization of Nonparametric Frontier Estimators |
0 |
0 |
0 |
46 |
0 |
0 |
1 |
103 |
| Regularization of Nonparametric Frontier Estimators |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
74 |
| Regularization of nonparametric frontier estimators |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
7 |
| Revisiting Forecasting of Recessions via Dynamic Probit for Time Series by Kauppi and Saikkonen (2008) |
0 |
0 |
0 |
21 |
0 |
0 |
0 |
35 |
| Robust frontier estimation from noisy data: a Tikhonov regularization approach |
0 |
1 |
1 |
50 |
1 |
3 |
3 |
71 |
| Robust frontier estimation from noisy data: a Tikhonov regularization approach |
0 |
0 |
0 |
6 |
0 |
0 |
3 |
17 |
| Robust frontier estimation from noisy data: a Tikhonov regularization approach |
0 |
0 |
0 |
1 |
0 |
0 |
3 |
12 |
| Robustified expected maximum production frontiers |
0 |
0 |
0 |
24 |
0 |
1 |
2 |
48 |
| Robustified expected maximum production frontiers |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
| Robustified expected maximum production frontiers |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Scale and research specialization in European Universities: a directional distance approach to teaching efficiency |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
| Schooling inputs, property tax caps and effciency scores in public schools |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
| Semi parametric efficient estimation of dynamic panel data models |
0 |
0 |
0 |
171 |
0 |
0 |
4 |
359 |
| Semiparametric Efficient Estimation of AR(1) Panel Data Models |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
472 |
| Semiparametric Efficient Estimation of AR(1) Panel Data Models |
0 |
0 |
0 |
167 |
0 |
0 |
2 |
454 |
| Semiparametric estimation in single index poisson regression: A practical approach |
0 |
1 |
2 |
46 |
0 |
1 |
3 |
246 |
| Sensitivity Analysis to Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models |
0 |
0 |
1 |
150 |
0 |
1 |
12 |
866 |
| Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models |
0 |
0 |
2 |
50 |
0 |
3 |
13 |
226 |
| Sensitivity to measurement errors of the distance to the efficient frontier |
0 |
0 |
0 |
2 |
0 |
1 |
5 |
21 |
| Sensitivity to measurement errors of the distance to the efficient frontier |
0 |
0 |
1 |
2 |
0 |
0 |
2 |
4 |
| Single-index modeling of conditional probabilities in two-way contingency tables |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
| Some problems with the Ferrier/Hirschberg bootstrap idea |
0 |
0 |
0 |
18 |
0 |
0 |
0 |
445 |
| Statistical Approaches for Nonparametric Frontier Models: A Guided Tour |
0 |
0 |
0 |
3 |
0 |
1 |
3 |
23 |
| Statistical Approaches for Nonparametric Frontier Models: A Guided Tour |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
18 |
| Statistical Inference for Aggregation of Malmquist Productivity Indices |
0 |
2 |
5 |
14 |
1 |
4 |
8 |
23 |
| Statistical Inference for Aggregation of Malmquist Productivity Indices |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
| Statistical Inference for Aggregation of Malmquist Productivity Indices |
0 |
0 |
0 |
44 |
0 |
1 |
3 |
99 |
| Statistical Inference for DEA Estimators of Directional Distances |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
25 |
| Statistical Inference for Hicks–Moorsteen Productivity Indices |
0 |
0 |
1 |
11 |
0 |
1 |
2 |
8 |
| Statistical Inference for Hicks–Moorsteen Productivity Indices |
1 |
1 |
3 |
11 |
2 |
3 |
9 |
14 |
| Statistical Inference in Nonparametric Frontier Models: the State of the Art |
0 |
0 |
0 |
1 |
1 |
3 |
3 |
1,171 |
| Statistical inference for DEA estimators of directional distances |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
6 |
| Stochastic FDH/DEA estimators for Frontier Analysis |
0 |
0 |
1 |
827 |
1 |
1 |
6 |
2,278 |
| Stochastic FDH/DEA estimators for frontier analysis |
0 |
0 |
0 |
0 |
1 |
1 |
5 |
18 |
| Stochastic FDH/DEA estimators for frontier analysis |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
9 |
| Stochastic Frontiers: A Semiparametric Approach |
0 |
0 |
0 |
14 |
0 |
0 |
1 |
132 |
| Stochastic Frontiers: A Semiparametric Approach |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
349 |
| Stochastic Panel Frontiers: A Semiparametric Approach |
0 |
0 |
0 |
25 |
0 |
0 |
3 |
336 |
| Stochastic panel frontiers: A semiparametric approach |
0 |
0 |
1 |
6 |
0 |
0 |
2 |
28 |
| Technical, Allocative and Overall Efficiency: Inference and Hypothesis Testing |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
11 |
| Testing Hypotheses in Nonparametric Models of Production |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
6 |
| Testing Hypotheses in Nonparametric Models of Production |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
9 |
| Testing Restrictions in Nonparametric Efficiency Models |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
456 |
| Testing the "Separability" Condition in Two-Stage Nonparametric Models of Production |
0 |
0 |
0 |
89 |
0 |
2 |
5 |
284 |
| Testing the "Separability" Condition in Two-Stage Nonparametric Models of Production |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
7 |
| Testing the "separability" condition in two-stage nonparametric models of production |
0 |
2 |
7 |
140 |
0 |
4 |
15 |
425 |
| Testing whether two-stage estimation is meaningful in non-parametric models of production |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
23 |
| The "wrong skewness" problem in stochastic frontier models: A new approach |
0 |
0 |
0 |
0 |
0 |
2 |
4 |
45 |
| The European university landscape: A micro characterization based on evidence from the Aquameth project |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
12 |
| The European university landscape: A micro characterization based on evidence from the Aquameth project |
0 |
0 |
0 |
0 |
1 |
2 |
5 |
9 |
| The European university landscape: A micro characterization based on evidence from the Aquameth project |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
38 |
| The Three I's of Public Schools: Irrelevant Inputs, Insufficient Resources and Inefficiency |
0 |
0 |
1 |
29 |
1 |
1 |
2 |
69 |
| The Three Is of Public Schools: Irrelevant Inputs, Insufficient Resources and Inefficiency |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
4 |
| The wrong skewness problem in stochastic frontier models: A new approach |
0 |
0 |
0 |
47 |
0 |
0 |
4 |
98 |
| The “wrong skewnessâ€Ω problem in stochastic frontier models: A new approach |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
8 |
| The “wrong skewnessâ€Ω problem in stochastic frontier models: A new approach |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
6 |
| The “wrong skewnessâ€Ω problem in stochastic frontier models: A new approach |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
| The “wrong skewness” problem in stochastic frontier models: a new approach |
0 |
0 |
0 |
9 |
0 |
0 |
1 |
57 |
| Theory and applications of least squares approximation in Bayesian analysis |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
9 |
| To Smooth or Not to Smooth? The Case of Discrete Variables in Nonparametric Regression |
0 |
1 |
1 |
6 |
0 |
4 |
4 |
31 |
| To Smooth or Not to Smooth? The Case of Discrete Variables in Nonparametric Regressions |
0 |
0 |
0 |
182 |
0 |
0 |
0 |
1,182 |
| To Smooth or Not to Smooth? The Case of Discrete Variables in Nonparametric Regressions |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Two-Stage DEA: Caveat Emptor |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
16 |
| Two-Stage DEA: Caveat Emptor |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
22 |
| Unobserved heterogeneity and endogeneity in nonparametric frontier estimation |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
12 |
| Unobserved heterogeneity and endogeneity in nonparametric frontier estimation |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
8 |
| Viable eco‐efficiency targets for waste collection communities |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
| What is the impact of scale and specialization on the research efficiency of European universities? |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
| When Bias Kills the Variance: Central Limit Theorems for DEA and FDH Efficiency Scores |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
11 |
| When Bias Kills the Variance: Central Limit Theorems for DEA and FDH Efficiency Scores |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
22 |
| Total Working Papers |
5 |
20 |
123 |
6,807 |
44 |
184 |
708 |
32,608 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A BIAS-CORRECTED NONPARAMETRIC ENVELOPMENT ESTIMATOR OF FRONTIERS |
0 |
0 |
0 |
77 |
0 |
1 |
1 |
158 |
| A Computationally Efficient, Consistent Bootstrap for Inference with Non-parametric DEA Estimators |
0 |
0 |
0 |
55 |
0 |
0 |
1 |
145 |
| A Flexible and Sustainable Analysis of Waste Efficiency at the European Level |
0 |
0 |
1 |
1 |
1 |
1 |
5 |
5 |
| A MOLLIFIER APPROACH TO THE DECONVOLUTION OF PROBABILITY DENSITIES |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
| A NOTE ON THE CONVERGENCE OF NONPARAMETRIC DEA ESTIMATORS FOR PRODUCTION EFFICIENCY SCORES |
0 |
0 |
0 |
97 |
0 |
0 |
1 |
215 |
| A bootstrap approach for bandwidth selection in estimating conditional efficiency measures |
0 |
0 |
0 |
14 |
0 |
1 |
3 |
60 |
| A general methodology for bootstrapping in non-parametric frontier models |
1 |
1 |
1 |
618 |
1 |
4 |
9 |
1,275 |
| A note on the asymptotic relative efficiency of M.L.E. in a linear model with Gamma disturbances |
0 |
0 |
0 |
26 |
0 |
1 |
1 |
134 |
| A robust nonparametric approach to evaluate and explain the performance of mutual funds |
0 |
0 |
0 |
79 |
0 |
0 |
3 |
185 |
| ASYMMETRIES IN BUSINESS CYCLES AND THE ROLE OF OIL PRICES |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
21 |
| ASYMPTOTICS AND CONSISTENT BOOTSTRAPS FOR DEA ESTIMATORS IN NONPARAMETRIC FRONTIER MODELS |
0 |
0 |
0 |
161 |
0 |
2 |
3 |
638 |
| Advanced indicators of productivity of universitiesAn application of robust nonparametric methods to Italian data |
0 |
0 |
1 |
13 |
0 |
0 |
3 |
27 |
| Another look at productivity growth in industrialized countries |
0 |
1 |
1 |
2 |
1 |
2 |
4 |
8 |
| Approximations and inference for envelopment estimators of production frontiers |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
3 |
| Categorical data in local maximum likelihood: theory and applications to productivity analysis |
0 |
0 |
6 |
515 |
1 |
1 |
21 |
1,794 |
| Central Limit Theorems for Aggregate Efficiency |
0 |
0 |
0 |
9 |
0 |
0 |
0 |
27 |
| Central limit theorems and inference for sources of productivity change measured by nonparametric Malmquist indices |
1 |
1 |
2 |
3 |
2 |
3 |
5 |
28 |
| Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non‐parametric, two‐stage models of production |
0 |
0 |
3 |
8 |
0 |
0 |
7 |
25 |
| Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach |
0 |
0 |
2 |
135 |
0 |
3 |
12 |
382 |
| Conical Free Disposal Hull estimators of directional distances and Luenberger productivity indices for general technologies |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| Corrigendum to "Semiparametric-efficient estimation of AR(1) panel data models": [J. Econom. 117 (2003) 279-309] |
0 |
0 |
0 |
14 |
0 |
0 |
0 |
52 |
| DECOMPOSING REGIONAL EFFICIENCY |
0 |
0 |
0 |
21 |
1 |
2 |
3 |
79 |
| Data sharpening for improving central limit theorem approximations for data envelopment analysis–type efficiency estimators |
0 |
0 |
0 |
1 |
0 |
0 |
3 |
6 |
| Detecting Outliers in Frontier Models: A Simple Approach |
0 |
0 |
1 |
64 |
0 |
1 |
4 |
179 |
| Directional distances and their robust versions: Computational and testing issues |
0 |
0 |
0 |
13 |
0 |
1 |
2 |
51 |
| ESTIMATING TECHNICAL INEFFICIENCIES WITH CORRECTION FOR ENVIRONMENTAL CONDITIONS |
0 |
0 |
0 |
10 |
0 |
1 |
4 |
42 |
| Effect of FDI and Time on Catching Up: New Insights from a Conditional Nonparametric Frontier Analysis |
0 |
0 |
1 |
25 |
0 |
0 |
3 |
81 |
| Efficiency and benchmarking with directional distances: a data-driven approach |
0 |
0 |
0 |
7 |
0 |
0 |
2 |
36 |
| Efficiency and economies of scale and specialization in European universities: A directional distance approach |
0 |
0 |
0 |
17 |
0 |
2 |
5 |
109 |
| Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error |
0 |
0 |
0 |
41 |
0 |
0 |
1 |
87 |
| Estimating and bootstrapping Malmquist indices |
0 |
0 |
2 |
240 |
0 |
1 |
6 |
509 |
| Estimation and Inference in Nonparametric Frontier Models: Recent Developments and Perspectives |
1 |
1 |
1 |
69 |
2 |
4 |
8 |
190 |
| Estimation and inference in two-stage, semi-parametric models of production processes |
4 |
5 |
34 |
1,460 |
6 |
11 |
103 |
3,302 |
| Estimation de frontières déterministes avec facteurs exogénes d'inefficacité |
1 |
1 |
1 |
3 |
1 |
2 |
3 |
19 |
| Estimation of the Boundary of a Variable Observed With Symmetric Error |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
10 |
| Explaining inefficiency in nonparametric production models: the state of the art |
1 |
1 |
2 |
28 |
1 |
2 |
4 |
74 |
| Fast and efficient computation of directional distance estimators |
0 |
1 |
2 |
10 |
0 |
3 |
8 |
50 |
| Forecasting of recessions via dynamic probit for time series: replication and extension of Kauppi and Saikkonen (2008) |
2 |
2 |
3 |
15 |
3 |
3 |
10 |
68 |
| Forecasting the Malmquist productivity index |
0 |
0 |
1 |
41 |
1 |
2 |
3 |
129 |
| Frontier estimation in nonparametric location-scale models |
0 |
0 |
0 |
21 |
0 |
0 |
1 |
111 |
| Frontier estimation in the presence of measurement error with unknown variance |
0 |
0 |
0 |
28 |
0 |
1 |
3 |
95 |
| Further improvements of finite sample approximation of central limit theorems for envelopment estimators |
0 |
0 |
0 |
2 |
0 |
0 |
3 |
5 |
| Gender effect on microfinance social efficiency: A robust nonparametric approach |
0 |
0 |
1 |
3 |
1 |
1 |
3 |
30 |
| Generalized nonparametric smoothing with mixed discrete and continuous data |
0 |
0 |
0 |
10 |
0 |
1 |
1 |
50 |
| Globalization and productivity: A robust nonparametric world frontier analysis |
0 |
0 |
1 |
29 |
0 |
0 |
3 |
101 |
| How to improve the performances of DEA/FDH estimators in the presence of noise? |
0 |
0 |
0 |
85 |
1 |
1 |
2 |
247 |
| How to measure the impact of environmental factors in a nonparametric production model |
0 |
0 |
2 |
137 |
0 |
0 |
4 |
431 |
| Hypothesis testing in nonparametric models of production using multiple sample splits |
0 |
0 |
4 |
28 |
0 |
0 |
15 |
97 |
| INFERENCE IN DYNAMIC, NONPARAMETRIC MODELS OF PRODUCTION: CENTRAL LIMIT THEOREMS FOR MALMQUIST INDICES |
0 |
0 |
0 |
0 |
1 |
1 |
4 |
5 |
| Improving finite sample approximation by central limit theorems for estimates from Data Envelopment Analysis |
0 |
0 |
1 |
4 |
0 |
1 |
5 |
22 |
| Inference by the m out of n bootstrap in nonparametric frontier models |
0 |
0 |
5 |
80 |
0 |
2 |
12 |
202 |
| Inference for aggregate efficiency: Theory and guidelines for practitioners |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
3 |
| Inference in the nonparametric stochastic frontier model |
0 |
0 |
4 |
4 |
0 |
2 |
10 |
10 |
| Inferences from Cross-Sectional, Stochastic Frontier Models |
0 |
0 |
0 |
85 |
0 |
0 |
0 |
210 |
| Innovation and export activities in the German mechanical engineering sector: an application of testing restrictions in production analysis |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
258 |
| Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach |
0 |
0 |
0 |
169 |
0 |
0 |
9 |
456 |
| Introduction for Journal of Productivity Analysis special issue on transitioning economics |
0 |
0 |
0 |
48 |
0 |
0 |
0 |
187 |
| Investigating the unobserved heterogeneity effect on outreach to women: lessons from microfinance institutions |
0 |
0 |
1 |
2 |
0 |
1 |
4 |
5 |
| Latent heterogeneity to evaluate the effect of human capital on world technology frontier |
0 |
0 |
0 |
4 |
0 |
1 |
5 |
23 |
| Linearly interpolated FDH efficiency score for nonconvex frontiers |
0 |
0 |
0 |
36 |
0 |
1 |
2 |
137 |
| Local likelihood estimation of truncated regression and its partial derivatives: Theory and application |
0 |
0 |
0 |
445 |
0 |
0 |
2 |
1,557 |
| Measuring firm performance using nonparametric quantile-type distances |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
41 |
| Non-parametric tests of returns to scale |
0 |
1 |
8 |
178 |
0 |
1 |
12 |
352 |
| Nonparametric conditional efficiency measures: asymptotic properties |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
36 |
| Nonparametric efficiency analysis: A multivariate conditional quantile approach |
0 |
0 |
0 |
94 |
1 |
1 |
2 |
231 |
| Nonparametric estimation of dynamic discrete choice models for time series data |
0 |
0 |
0 |
23 |
0 |
1 |
3 |
62 |
| Nonparametric frontier estimation: a robust approach |
0 |
1 |
3 |
397 |
0 |
1 |
7 |
850 |
| Nonparametric instrumental variables estimation for efficiency frontier |
0 |
0 |
1 |
17 |
0 |
0 |
2 |
84 |
| Nonparametric least squares methods for stochastic frontier models |
1 |
1 |
4 |
46 |
1 |
2 |
10 |
143 |
| Nonparametric stochastic frontiers: A local maximum likelihood approach |
0 |
0 |
3 |
256 |
0 |
2 |
5 |
560 |
| Nonparametric tests for conditional independence in two-way contingency tables |
0 |
0 |
0 |
21 |
0 |
1 |
1 |
127 |
| Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs |
2 |
2 |
2 |
2 |
3 |
3 |
5 |
7 |
| Of Course We Can Bootstrap DEA Scores! But Does It Mean Anything? Logic Trumps Wishful Thinking |
0 |
0 |
1 |
7 |
0 |
1 |
2 |
35 |
| On Testing Equality of Distributions of Technical Efficiency Scores |
0 |
0 |
0 |
111 |
0 |
2 |
5 |
474 |
| On the inconsistency of bootstrap distribution estimators |
0 |
0 |
0 |
67 |
0 |
0 |
2 |
179 |
| Optimal bandwidth selection for conditional efficiency measures: A data-driven approach |
0 |
1 |
1 |
97 |
0 |
2 |
4 |
298 |
| Parametric approximations of nonparametric frontiers |
0 |
0 |
0 |
58 |
0 |
0 |
1 |
132 |
| Pitfalls of Normal-Gamma Stochastic Frontier Models |
0 |
0 |
1 |
7 |
0 |
0 |
2 |
40 |
| Predicting recessions with a frontier measure of output gap: an application to Italian economy |
0 |
0 |
1 |
5 |
0 |
1 |
2 |
23 |
| Probabilistic characterization of directional distances and their robust versions |
0 |
0 |
1 |
28 |
0 |
0 |
1 |
97 |
| Proportional incremental cost probability functions and their frontiers |
0 |
0 |
0 |
0 |
0 |
3 |
4 |
6 |
| Quality as a latent heterogeneity factor in the efficiency of universities |
0 |
0 |
0 |
6 |
0 |
0 |
2 |
19 |
| ROBUSTIFIED EXPECTED MAXIMUM PRODUCTION FRONTIERS |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
8 |
| Rankings and university performance: A conditional multidimensional approach |
0 |
0 |
1 |
34 |
0 |
0 |
7 |
119 |
| Regularization of nonparametric frontier estimators |
1 |
1 |
1 |
17 |
1 |
1 |
1 |
78 |
| Robust frontier estimation from noisy data: A Tikhonov regularization approach |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
15 |
| Robust nonparametric estimators of monotone boundaries |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
57 |
| Semiparametric efficient estimation of dynamic panel data models |
0 |
0 |
0 |
98 |
0 |
0 |
2 |
280 |
| Semiparametric estimation in single index Poisson regression: A practical approach |
0 |
0 |
0 |
49 |
0 |
0 |
0 |
207 |
| Semiparametric-efficient estimation of AR(1) panel data models |
0 |
0 |
1 |
72 |
0 |
0 |
5 |
212 |
| Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models |
1 |
1 |
4 |
267 |
3 |
5 |
14 |
666 |
| Some Problems with the Ferrier/Hirschberg Bootstrap Idea |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
24 |
| Statistical Approaches for Non-parametric Frontier Models: A Guided Tour |
0 |
0 |
0 |
33 |
0 |
0 |
5 |
89 |
| Statistical Inference for Aggregation of Malmquist Productivity Indices |
0 |
0 |
0 |
0 |
0 |
2 |
6 |
6 |
| Statistical Inference in Nonparametric Frontier Models: The State of the Art |
0 |
2 |
4 |
41 |
1 |
6 |
11 |
181 |
| Statistical inference for DEA estimators of directional distances |
0 |
0 |
1 |
40 |
0 |
1 |
3 |
124 |
| Statistical inference for aggregates of Farrell-type efficiencies |
0 |
0 |
0 |
179 |
0 |
1 |
6 |
630 |
| Stochastic FDH/DEA estimators for frontier analysis |
0 |
0 |
2 |
263 |
1 |
1 |
6 |
950 |
| Stochastic panel frontiers: A semiparametric approach |
0 |
0 |
0 |
56 |
0 |
0 |
2 |
156 |
| THE FDH ESTIMATOR FOR PRODUCTIVITY EFFICIENCY SCORES |
0 |
1 |
2 |
73 |
0 |
1 |
3 |
173 |
| Technical, allocative and overall efficiency: Estimation and inference |
0 |
0 |
0 |
6 |
0 |
2 |
2 |
18 |
| Testing Hypotheses in Nonparametric Models of Production |
0 |
0 |
2 |
24 |
1 |
3 |
17 |
81 |
| The European university landscape: A micro characterization based on evidence from the Aquameth project |
0 |
0 |
1 |
82 |
0 |
0 |
3 |
305 |
| The three s of public schools: irrelevant inputs, insufficient resources and inefficiency |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
22 |
| The “wrong skewness” problem in stochastic frontier models: A new approach |
0 |
0 |
1 |
9 |
0 |
0 |
2 |
35 |
| Two-stage DEA: caveat emptor |
0 |
2 |
3 |
240 |
0 |
4 |
10 |
610 |
| Unobserved heterogeneity and endogeneity in nonparametric frontier estimation |
0 |
0 |
0 |
31 |
0 |
0 |
2 |
166 |
| WHEN BIAS KILLS THE VARIANCE: CENTRAL LIMIT THEOREMS FOR DEA AND FDH EFFICIENCY SCORES |
0 |
0 |
0 |
21 |
0 |
0 |
3 |
77 |
| Total Journal Articles |
16 |
27 |
133 |
8,225 |
38 |
119 |
539 |
23,532 |
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