| Working Paper |
File Downloads |
Abstract Views |
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3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Comparison of Two Averaging Techniques with an Application to Growth Empirics |
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0 |
10 |
1 |
1 |
2 |
55 |
| A Comparison of Two Averaging Techniques with an Application to Growth Empirics |
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0 |
0 |
1 |
1 |
1 |
3 |
12 |
| A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance |
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0 |
0 |
1 |
1 |
1 |
1 |
20 |
| A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
8 |
| A note on instrumental variables and maximum likelihood estimation procedures |
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0 |
1 |
1 |
0 |
0 |
3 |
6 |
| A note on instrumental variables and maximum likelihood estimation procedures |
0 |
0 |
0 |
17 |
0 |
0 |
1 |
78 |
| A representation theorem for (trAp)1/p |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
12 |
| ASYMPTOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR IN THE NONLINEAR REGRESSION MODEL WITH NORMAL ERRORS |
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0 |
0 |
6 |
0 |
0 |
1 |
18 |
| Adaptation for Mitigation |
0 |
0 |
0 |
39 |
0 |
0 |
0 |
71 |
| Adaptation for Mitigation |
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0 |
0 |
10 |
1 |
1 |
1 |
57 |
| Adaptation for Mitigation |
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0 |
0 |
1 |
3 |
3 |
4 |
33 |
| Adaptation for mitigation |
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0 |
0 |
13 |
4 |
5 |
5 |
53 |
| An experiment in applied econometrics |
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0 |
0 |
1 |
0 |
0 |
0 |
5 |
| Are Economic Agents Successful Optimizers? An Analysis Through Strategy in Tennis |
0 |
0 |
0 |
8 |
1 |
1 |
4 |
58 |
| Are Economic Agents Successful Optimizers? An Analysis through Service Strategy in Tennis |
0 |
0 |
0 |
112 |
1 |
2 |
6 |
325 |
| Asymptotic normality of maximum likelihood estimators obtained from normally distributed but dependent observations |
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0 |
0 |
1 |
1 |
2 |
3 |
19 |
| Asyptopic Properties of Maximum Likelihood Estimators in a Nonlinear Regression Model with Unknown Parameters in the Disturbance Convariance Matrix |
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0 |
0 |
0 |
0 |
0 |
3 |
7 |
| Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala |
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0 |
0 |
11 |
0 |
1 |
1 |
44 |
| Bayesian Model Averaging and Weighted Average Least Squares: Equivariance, Stability, and Numerical Issues |
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0 |
0 |
36 |
1 |
2 |
4 |
119 |
| Benzine is al eens duurder geweest |
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0 |
0 |
0 |
0 |
0 |
0 |
8 |
| Burr Utility |
0 |
0 |
0 |
5 |
1 |
2 |
2 |
30 |
| CONSISTENT MAXIMUM LIKELIHOOD ESTIMATION OF THE NONLINEAR REGRESSION MODEL WITH NORMAL ERRORS |
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0 |
0 |
4 |
0 |
0 |
1 |
12 |
| CONSISTENT MAXIMUM LIKELIHOOD ESTIMATION WITH DEPENDENT OBSERVATIONS: THE GENERAL (NON-NORMAL) CASE AND THE NORMAL CASE |
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0 |
0 |
18 |
3 |
3 |
6 |
49 |
| Climate Change, Economic Growth, and Health |
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0 |
0 |
27 |
1 |
3 |
3 |
100 |
| Climate change, economic growth, and health |
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1 |
2 |
68 |
0 |
3 |
7 |
135 |
| Comments on “Unobservable Selection and Coefficient Stability-Theory and Evidence” and “Poorly Measured Confounders are More Useful on the Left Than on the Right” |
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0 |
0 |
56 |
1 |
2 |
5 |
166 |
| Concept-Based Bayesian Model Averaging and Growth Empirics |
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0 |
0 |
0 |
1 |
1 |
1 |
8 |
| Concept-Based Bayesian Model Averaging and Growth Empirics |
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0 |
0 |
7 |
1 |
2 |
4 |
39 |
| Consistency of Maximum Likelihood Estimators When Observations Are Dependent |
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0 |
2 |
4 |
3 |
5 |
17 |
32 |
| Consistent maximum-likelihood estimation with dependent observations: the general (non-normal) case and the normal case |
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0 |
0 |
2 |
0 |
0 |
0 |
31 |
| De kans om een tenniswedstrijd te winnen: Federer-Nadal in de finale van Wimbeldon 2007 |
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0 |
0 |
3 |
1 |
1 |
2 |
19 |
| Design of the experiment |
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0 |
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2 |
0 |
0 |
0 |
10 |
| EVALUATION OF MOMENT OF QUADRATIC FORMS IN NORMAL VARIABLES |
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0 |
0 |
1 |
0 |
1 |
1 |
271 |
| EVALUATION OF MOMENTS OF RATIOS OF QUADRATIC FORMS IN NORMAL VARIABLES AND RELATED STATISTICS |
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0 |
0 |
0 |
0 |
0 |
0 |
254 |
| Earthquake risk embedded in property prices: Evidence from five Japanese cities |
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0 |
0 |
23 |
0 |
0 |
4 |
76 |
| Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known |
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0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known |
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0 |
0 |
3 |
0 |
1 |
1 |
37 |
| Evaluation of moments of quadratic forms and ratios of quadratic forms in normal variables: background, motivation and examples |
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0 |
0 |
5 |
0 |
0 |
2 |
15 |
| Evaluation of moments of quadratic forms in normal variables |
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0 |
0 |
0 |
0 |
0 |
0 |
2 |
| Evaluation of moments of quadratic forms in normal variables |
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0 |
0 |
1 |
4 |
6 |
6 |
16 |
| Evaluation of moments of ratios of quadratic forms in normal variables and related statistics |
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0 |
0 |
0 |
0 |
2 |
2 |
5 |
| Evaluation of moments of ratios of quadratic forms in normal variables and related statistics |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
14 |
| Expected Utility and Catastrophic Risk |
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1 |
1 |
42 |
3 |
4 |
6 |
100 |
| Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model |
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0 |
1 |
13 |
0 |
4 |
5 |
75 |
| Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model |
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0 |
0 |
0 |
1 |
3 |
6 |
16 |
| FORECASTING, MISSPECIFICATION AND UNIT ROOTS: THE CASE OF AR(1) VERSUS ARMA (1,1) |
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0 |
0 |
0 |
0 |
1 |
2 |
334 |
| Forecast Accuracy after Pretesting with an Application to the Stock Market |
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0 |
0 |
5 |
0 |
0 |
2 |
30 |
| Forecast Accuracy after Pretesting with an Application to the Stock Market |
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0 |
0 |
1 |
0 |
1 |
1 |
9 |
| Forecasting the Winner of a Tennis Match |
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0 |
0 |
2 |
2 |
5 |
6 |
30 |
| Forecasting the Winner of a Tennis Match |
0 |
0 |
0 |
47 |
2 |
3 |
4 |
175 |
| Forecasting, misspecification and unit roots: The case of Ar(1) versus ARMA(1,1) |
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0 |
0 |
4 |
0 |
3 |
3 |
21 |
| Forecasting, misspecification and unit roots: The case of Ar(1) versus ARMA(1,1) |
0 |
0 |
0 |
1 |
0 |
2 |
4 |
8 |
| Global Warming and Local Dimming: The Statistical Evidence |
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0 |
0 |
0 |
0 |
2 |
3 |
20 |
| Global Warming and Local Dimming: The Statistical Evidence |
0 |
0 |
0 |
5 |
0 |
0 |
4 |
65 |
| Grade Expectations: Rationality and Overconfidence |
0 |
1 |
1 |
90 |
2 |
5 |
7 |
198 |
| How to reduce the service dominance in tennis? Empirical results from four years at Wimbledon |
0 |
0 |
0 |
5 |
0 |
0 |
3 |
35 |
| Inter-fuel substitution in Dutch manufacturing |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
31 |
| L-structured matrices and linear matrix equations |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
9 |
| Least squares autoregression with near-unit root |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
| Local Sensitivity and Diagnostic Tests |
0 |
0 |
0 |
0 |
0 |
3 |
3 |
6 |
| Local Sensitivity and Diagnostic Tests |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
45 |
| MATRIX DIFFERENTIAL CALCULUS AND STATIC OPTIMIZATION part II- differentials: Theory |
0 |
0 |
2 |
7 |
0 |
1 |
5 |
27 |
| Macro accounts estimation using indicator ratios |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
| Matrix differential calculus and static optimization Part III- differentials: Practice |
0 |
0 |
0 |
7 |
3 |
6 |
7 |
28 |
| Matrix differential calculus with applications to simple, Hadamard, and Kronecker products |
0 |
0 |
1 |
12 |
1 |
2 |
6 |
51 |
| Maximum Likelihood Estimation of the Multivariate Normal Mixture Model |
0 |
0 |
1 |
85 |
2 |
3 |
5 |
384 |
| Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
22 |
| Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix |
0 |
0 |
0 |
3 |
0 |
0 |
4 |
33 |
| Maximum likelihood estimation of the multivariate normal mixture model |
0 |
0 |
0 |
1 |
0 |
2 |
2 |
25 |
| Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood |
0 |
0 |
0 |
2 |
1 |
1 |
3 |
46 |
| Normal's deconvolution and the independence of sample mean and variance (problem 03.4.1) |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
6 |
| Notation in Econometrics: A Proposal for a Standard |
0 |
0 |
0 |
1 |
2 |
2 |
2 |
6 |
| Notation in Econometrics: A Proposal for a Standard |
0 |
0 |
0 |
39 |
4 |
4 |
4 |
181 |
| ON THE FIRST-ORDER EFFICIENCY AN DASYMPTOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR OBTAINED FROM DEPENDENT OBSERVATIONS |
0 |
0 |
0 |
1 |
0 |
2 |
3 |
10 |
| ON THE FIRST-ORDER EFFICIENCY AND ASYMPOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR OBTAINED FROM DEPENDENT OBSERVATIONS |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
13 |
| On Theil's Errors |
1 |
1 |
1 |
4 |
1 |
1 |
1 |
30 |
| On Theil's Errors |
1 |
1 |
1 |
2 |
3 |
3 |
3 |
9 |
| On Theils' errors |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
6 |
| On certain moments relating to ratios of quadratic forms in normal variables: Further results |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| On differentiating eigenvalues and eigenvectors |
0 |
0 |
1 |
33 |
1 |
1 |
3 |
86 |
| On levies to reduce the nitrogen surplus: The case of Dutch pig farms |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
23 |
| On some definitions in matrix algebra |
0 |
0 |
0 |
106 |
0 |
0 |
0 |
262 |
| On tests and significance in econometrics |
0 |
0 |
0 |
18 |
1 |
1 |
1 |
60 |
| On tests and significance in econometrics |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
57 |
| On tests and significance in econometrics |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
4 |
| On the Ambiguous Consequences of Omitting Variables |
0 |
0 |
0 |
49 |
0 |
0 |
1 |
86 |
| On the Asymptotic Normality of the Maximum Likelihood Estimator With Dependent Observations |
0 |
0 |
0 |
4 |
1 |
3 |
5 |
18 |
| On the Choice of Prior in Bayesian Model Averaging |
0 |
0 |
0 |
16 |
0 |
1 |
3 |
77 |
| On the Choice of Prior in Bayesian Model Averaging |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
7 |
| On the Harm that Pretesting Does |
0 |
0 |
0 |
3 |
2 |
2 |
3 |
31 |
| On the Harm that Pretesting Does |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
| On the Independence and Identical Distribution of Points in Tennis |
0 |
0 |
0 |
13 |
1 |
1 |
1 |
45 |
| On the Independence and Identical Distribution of Points in Tennis |
0 |
0 |
0 |
3 |
0 |
1 |
1 |
11 |
| On the Unbiasedness of Iterated GLS Estimators |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
22 |
| On the ambiguous consequences of omitting variables |
0 |
0 |
1 |
17 |
1 |
2 |
5 |
79 |
| On the estimation of a large sparse Bayesian system: the Snaer program |
0 |
0 |
0 |
36 |
0 |
1 |
2 |
134 |
| On the first-order efficiency and asymptotic normality of maximum likelihood estimators obtained from dependent observations |
0 |
0 |
0 |
1 |
1 |
2 |
2 |
17 |
| On the first-order efficiency and asymptotic normality of the maximum likelihood estimator obtained from dependent observations |
0 |
0 |
0 |
2 |
1 |
1 |
1 |
12 |
| On the fundamental bordered matrix of linear estimation |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
7 |
| On the fundamental bordered matrix of linear estimation |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
5 |
| On the maximum likelihood estimation of multivariate regression models containing serially correlated error components |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
7 |
| On the maximum likelihood estimation of multivariate regression models containing serially correlated error components |
0 |
0 |
0 |
3 |
0 |
1 |
1 |
20 |
| On the sensitivity of the t-statistic |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
5 |
| On the sensitivity of the usual t-and f-tests to AR(1) misspecification |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
| On the sensitivity of the usual t-and f-tests to AR(1) misspecification |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
13 |
| On the unbiasedness of iterated GLS estimators |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
8 |
| Optimal taxation for the reduction of nitrogen surplus in Dutch dairy farms, 1975 to 1989 |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
12 |
| Organization of the experiment |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
11 |
| Peer Reporting and the Perception of Fairness |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Peer Reporting and the Perception of Fairness |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
56 |
| Posterior moments and quantiles for the normal location model with Laplace prior |
0 |
0 |
0 |
13 |
2 |
3 |
4 |
67 |
| Practical use of sensitivity in econometrics with an illustration to forecast combinations |
0 |
0 |
0 |
26 |
0 |
1 |
2 |
20 |
| Records in Athletics through Extreme-Value Theory |
0 |
0 |
0 |
2 |
0 |
1 |
2 |
16 |
| Records in Athletics through Extreme-Value Theory |
0 |
1 |
1 |
11 |
0 |
1 |
2 |
80 |
| Resource Abundance and Resource Dependence in China |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
6 |
| Resource Abundance and Resource Dependence in China |
0 |
0 |
0 |
32 |
0 |
0 |
0 |
154 |
| SYMMETRY, 0-1 MATRICES, AND JACOBIANS: A REVIEW |
0 |
0 |
0 |
3 |
1 |
2 |
5 |
24 |
| Sampling properties of the Bayesian posterior mean with an application to WALS estimation |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
32 |
| Sampling properties of the Bayesian posterior mean with anapplication to WALS estimation |
0 |
0 |
0 |
10 |
1 |
2 |
2 |
39 |
| Scrap Value Functions in Dynamic Decision Problems |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
7 |
| Scrap Value Functions in Dynamic Decision Problems |
0 |
0 |
0 |
7 |
0 |
1 |
2 |
73 |
| Separability and aggregation |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
6 |
| Separability and aggregation |
0 |
0 |
0 |
2 |
1 |
1 |
1 |
13 |
| Some properties of a generalized two-error components matrix (problem 01.5.1) |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
15 |
| Substitution between energy and non-energy inputs in the Netherlands, 1950-1974 |
0 |
0 |
0 |
2 |
1 |
2 |
4 |
15 |
| Substitution between energy and non-energy inputs in the Netherlands, 1950-1976 |
0 |
0 |
0 |
4 |
2 |
2 |
3 |
18 |
| Substitution between energy and other inputs in the Netherlands, with contributions to related econometric problems |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
10 |
| Symmetry, 0-1 matrices and Jacobians: A review |
0 |
0 |
1 |
4 |
1 |
3 |
6 |
24 |
| Testing some common hypotheses: Four years at Wimbledon |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
13 |
| Testing some common tennis hypotheses: Four years at Wimbledon |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
| Testing some common tennis hypotheses: Four years at Wimbledon |
0 |
0 |
0 |
14 |
2 |
2 |
3 |
115 |
| Testing the Sensitivity of OLS when the Variance Maxtrix is (Partially) Unknown |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
3 |
| Testing the Sensitivity of OLS when the Variance Maxtrix is (Partially) Unknown |
0 |
0 |
0 |
0 |
2 |
2 |
3 |
25 |
| The ET interview: Professor J. Tinbergen |
0 |
0 |
2 |
3 |
3 |
3 |
6 |
20 |
| The Forecast Combination Puzzle: A Simple Theoretical Explanation |
0 |
0 |
0 |
101 |
1 |
2 |
4 |
189 |
| The Jacobian of the exponential function |
0 |
0 |
0 |
44 |
2 |
2 |
4 |
47 |
| The Perception of Small Crime |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
9 |
| The Perception of Small Crime |
0 |
0 |
0 |
5 |
0 |
1 |
1 |
55 |
| The asymptotic variance of the pseudo maximum likelihood estimator |
0 |
0 |
1 |
63 |
2 |
2 |
6 |
215 |
| The bias of forecasts from a first-order autoregression |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
11 |
| The bias of forecasts from a first-order autoregression (Revised version) |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
15 |
| The central limit theorem for student's distribution (problem 03.6.1) |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
10 |
| The commutation matrix: Some properties and applications |
0 |
0 |
2 |
53 |
0 |
0 |
2 |
183 |
| The commutation matrix: some theorems and applications |
0 |
1 |
1 |
6 |
1 |
3 |
7 |
39 |
| The data: A brief description |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
6 |
| The elimination matrix: Some lemmas and applications |
1 |
1 |
5 |
88 |
2 |
2 |
11 |
240 |
| The evaluation of cumulants and moments of quadratic forms in normal variables (CUM): Technical description |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
9 |
| The evaluation of moments of ratios of quadratic forms in normal variables and related statistics (QRMOM): Technical description |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
7 |
| The exact moments of a ratio of quadratic forms in normal variables |
1 |
1 |
4 |
16 |
3 |
3 |
6 |
46 |
| The exact multi-period mean-square forecast error for the first-order autoregressive model |
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0 |
0 |
0 |
0 |
0 |
2 |
5 |
| The exact multi-period mean-square forecast error for the first-order autoregressive model with an intercept |
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0 |
0 |
1 |
0 |
0 |
0 |
10 |
| The exact multi-period mean-square forecast error for the first-order autoregressive model with an intercept |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
7 |
| The exact multi-period meansquare forecast error for the first-order autoregressive model |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
6 |
| The expectation of products of quadratic forms in normal variables: The practice Statistica Neerlandica |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
9 |
| The forecast combination puzzle: a simple theoretical explanation |
0 |
0 |
0 |
9 |
4 |
4 |
6 |
53 |
| The maximum number of omitted variables, Problem 00.2.2 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
8 |
| The moments of products of quadratic forms in normal variables |
0 |
0 |
0 |
16 |
0 |
0 |
2 |
42 |
| The perception of climate sensitivity: Revealing priors from posteriors |
0 |
0 |
0 |
8 |
1 |
2 |
4 |
20 |
| The significance of testing in econometrics |
0 |
0 |
0 |
3 |
1 |
1 |
1 |
8 |
| Von Hamburg nach Berlin im sommer 1841: Emma Isler berichtet |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
12 |
| WALS Prediction |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
63 |
| WALS estimation and forecasting in factor-based dynamic models with an application to Armenia |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
17 |
| WALS estimation and forecasting in factor-based dynamic models with an application to Armenia |
0 |
0 |
0 |
10 |
0 |
1 |
2 |
91 |
| Wat tenniscommentatoren niet weten: Een analyse van vier jaar Wimbledon |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
15 |
| Weighted-Average Least Squares Estimation of Generalized Linear Models |
0 |
0 |
0 |
41 |
0 |
0 |
3 |
223 |
| Weighted-average least squares estimation of generalized linear models |
0 |
0 |
1 |
20 |
4 |
4 |
9 |
78 |
| Weitzman meets Nordhaus: Expected utility and catastrophic risk in a stochastic economy-climate model |
0 |
0 |
1 |
53 |
2 |
4 |
6 |
126 |
| Zero-diagonality as a linear structure |
0 |
0 |
0 |
3 |
1 |
1 |
1 |
17 |
| Total Working Papers |
4 |
9 |
35 |
1,934 |
125 |
215 |
415 |
8,305 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| 03.4.1. Normal's Deconvolution and the Independence of Sample Mean and Variance |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
44 |
| 03.6.1 The Central Limit Theorem for Student's Distribution—Solution |
0 |
0 |
1 |
19 |
0 |
0 |
2 |
77 |
| 03.6.1. The Central Limit Theorem for Student's Distribution |
0 |
0 |
0 |
6 |
0 |
1 |
1 |
61 |
| A Note on Instrumental Variables and Maximum Likelihood Estimation Procedures |
0 |
0 |
0 |
3 |
1 |
2 |
5 |
23 |
| A comparison of two model averaging techniques with an application to growth empirics |
0 |
1 |
2 |
320 |
3 |
4 |
7 |
822 |
| Adaptation for Mitigation |
1 |
1 |
1 |
12 |
3 |
3 |
7 |
61 |
| Are Points in Tennis Independent and Identically Distributed? Evidence From a Dynamic Binary Panel Data Model |
0 |
0 |
0 |
182 |
1 |
2 |
8 |
436 |
| Asymptotic Normmality of Maximum Likelihood Estimators Obtained from Normally Distributed but Dependent Observations |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
15 |
| BALANCED VARIABLE ADDITION IN LINEAR MODELS |
1 |
1 |
4 |
17 |
1 |
2 |
7 |
58 |
| Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues |
0 |
0 |
1 |
206 |
1 |
3 |
8 |
735 |
| Comments on “Unobservable Selection and Coefficient Stability: Theory and Evidence” and “Poorly Measured Confounders are More Useful on the Left Than on the Right” |
0 |
0 |
0 |
9 |
0 |
1 |
3 |
42 |
| Concept-Based Bayesian Model Averaging and Growth Empirics |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
44 |
| Consistent maximum-likelihood estimation with dependent observations: The general (non-normal) case and the normal case |
0 |
0 |
0 |
143 |
0 |
0 |
3 |
352 |
| Design of the Experiment |
0 |
0 |
0 |
62 |
1 |
1 |
1 |
326 |
| Editors' introduction: The significance of testing in econometrics |
0 |
0 |
0 |
22 |
0 |
0 |
2 |
97 |
| Estimation of Regression Coefficients of Interest When Other Regression Coefficients Are of No Interest |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
399 |
| Estimation of Variance Components and Applications |
0 |
0 |
3 |
8 |
2 |
2 |
5 |
30 |
| Estimation of the mean of a univariate normal distribution with known variance |
0 |
0 |
0 |
122 |
0 |
0 |
2 |
1,111 |
| Expected utility and catastrophic consumption risk |
0 |
0 |
0 |
10 |
1 |
1 |
6 |
60 |
| Expected utility and catastrophic risk in a stochastic economy–climate model |
1 |
1 |
2 |
12 |
2 |
2 |
4 |
101 |
| Forecast accuracy after pretesting with an application to the stock market |
0 |
0 |
1 |
48 |
0 |
0 |
2 |
241 |
| Forecasting the winner of a tennis match |
0 |
0 |
1 |
124 |
0 |
6 |
11 |
357 |
| Global Warming and Local Dimming: The Statistical Evidence |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
90 |
| HANDBOOK OF MATRICES |
0 |
1 |
1 |
59 |
0 |
3 |
5 |
216 |
| Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations |
0 |
0 |
0 |
5 |
1 |
1 |
3 |
36 |
| Local sensitivity and diagnostic tests |
0 |
0 |
0 |
49 |
0 |
0 |
1 |
366 |
| Maximum Likelihood Estimation of the Multivariate Normal Mixture Model |
0 |
0 |
1 |
10 |
0 |
2 |
4 |
66 |
| Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix |
0 |
0 |
1 |
220 |
1 |
2 |
5 |
1,069 |
| Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood |
0 |
0 |
0 |
108 |
3 |
3 |
5 |
305 |
| NATIONAL ACCOUNTS ESTIMATION USING INDICATOR RATIOS |
0 |
0 |
0 |
2 |
0 |
2 |
2 |
10 |
| NOTES AND PROBLEMS A GENERAL BOUND FOR THE LIMITING DISTRIBUTION OF BREITUNG'S STATISTIC |
0 |
0 |
0 |
14 |
0 |
0 |
2 |
49 |
| Natural Resources, Institutional Quality, and Economic Growth in China |
0 |
0 |
1 |
51 |
4 |
7 |
12 |
186 |
| Notation in econometrics: a proposal for a standard |
0 |
0 |
0 |
309 |
2 |
2 |
8 |
1,453 |
| ON THE FIRST–ORDER EFFICIENCY AND ASYMPTOTIC NORMALITY OF MAXIMUM LIKELIHOOD ESTIMATORS OBTAINED FROM DEPENDENT OBSERVATIONS |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
17 |
| On Differentiating Eigenvalues and Eigenvectors |
0 |
0 |
2 |
59 |
0 |
5 |
12 |
167 |
| On Theil's errors |
0 |
0 |
0 |
48 |
0 |
0 |
1 |
250 |
| On Using the t -Ratio as a Diagnostic |
0 |
0 |
0 |
9 |
0 |
0 |
0 |
22 |
| On levies to reduce the nitrogen surplus: The case of Dutch pig farms |
0 |
0 |
0 |
3 |
0 |
2 |
6 |
57 |
| On tests and significance in econometrics |
0 |
0 |
0 |
142 |
1 |
1 |
4 |
600 |
| On the Maximum Likelihood Estimation of Multivariate Regression Models Containing Serially Correlated Error Components |
0 |
0 |
0 |
144 |
1 |
1 |
2 |
470 |
| On the concept of matrix derivative |
0 |
0 |
1 |
23 |
0 |
1 |
4 |
130 |
| On the estimation of a large sparse Bayesian system: The Snaer program |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
36 |
| On the harm that ignoring pretesting can cause |
0 |
0 |
0 |
48 |
0 |
1 |
3 |
153 |
| On the sensitivity of the usual t- and F-tests to covariance misspecification |
0 |
0 |
0 |
17 |
1 |
2 |
2 |
163 |
| Organization of the Experiment |
0 |
0 |
0 |
8 |
1 |
1 |
3 |
177 |
| Pareto utility |
0 |
0 |
0 |
17 |
2 |
4 |
9 |
104 |
| Peer Reporting and the Perception of Fairness |
0 |
0 |
0 |
5 |
3 |
5 |
6 |
74 |
| Records in Athletics Through Extreme-Value Theory |
0 |
0 |
0 |
48 |
0 |
2 |
3 |
144 |
| Rejoinder |
0 |
0 |
0 |
3 |
1 |
2 |
2 |
55 |
| SPECIFICATION OF VARIANCE MATRICES FOR PANEL DATA MODELS |
0 |
0 |
0 |
39 |
1 |
1 |
5 |
101 |
| Some equivalences in linear estimation (in Russian) |
0 |
0 |
0 |
17 |
0 |
1 |
2 |
96 |
| Substitution between Energy and Non-Energy Inputs in the Netherlands, 1950-1976 |
0 |
0 |
0 |
35 |
0 |
1 |
1 |
116 |
| Symmetry, 0-1 Matrices and Jacobians: A Review |
0 |
0 |
0 |
19 |
0 |
1 |
6 |
67 |
| THE ASYMPTOTIC VARIANCE OF THE PSEUDO MAXIMUM LIKELIHOOD ESTIMATOR |
0 |
0 |
0 |
6 |
3 |
3 |
4 |
41 |
| The Bias of Forecasts from a First-Order Autoregression |
0 |
0 |
0 |
3 |
0 |
1 |
3 |
18 |
| The Data: A Brief Description |
0 |
0 |
0 |
28 |
1 |
1 |
2 |
240 |
| The Exact Moments of a Ratio of Quadratic Forms in Normal Variables |
0 |
0 |
2 |
28 |
0 |
2 |
10 |
90 |
| The Third Special Issue on Computational Econometrics |
0 |
0 |
0 |
46 |
0 |
0 |
2 |
139 |
| The effect of health benefits on climate change mitigation policies |
0 |
0 |
0 |
9 |
0 |
2 |
3 |
41 |
| The efficiency of top agents: An analysis through service strategy in tennis |
0 |
0 |
2 |
41 |
1 |
3 |
7 |
236 |
| The exact multi-period mean-square forecast error for the first-order autoregressive model |
0 |
0 |
0 |
23 |
2 |
2 |
3 |
110 |
| The exact multi-period mean-square forecast error for the first-order autoregressive model with an intercept |
0 |
0 |
0 |
10 |
2 |
2 |
2 |
64 |
| The expectation of products of quadratic forms in normal variables: the practice |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
6 |
| The final set in a tennis match: Four years at Wimbledon |
0 |
0 |
0 |
197 |
1 |
3 |
5 |
828 |
| The forecast combination puzzle: A simple theoretical explanation |
0 |
0 |
0 |
17 |
0 |
0 |
1 |
139 |
| The moments of products of quadratic forms in normal variables* |
0 |
0 |
0 |
3 |
1 |
4 |
6 |
16 |
| The perception of small crime |
0 |
0 |
0 |
17 |
1 |
1 |
4 |
123 |
| The price of Moscow apartments |
1 |
2 |
3 |
191 |
5 |
8 |
14 |
523 |
| The sensitivity of OLS when the variance matrix is (partially) unknown |
0 |
0 |
0 |
24 |
0 |
0 |
1 |
192 |
| Tolerance of Cheating: An Analysis Across Countries |
0 |
1 |
6 |
115 |
2 |
4 |
32 |
454 |
| USING MACRO DATA TO OBTAIN BETTER MICRO FORECASTS |
0 |
0 |
0 |
24 |
0 |
0 |
1 |
82 |
| WALS Estimation and Forecasting in Factor-based Dynamic Models with an Application to Armenia |
0 |
0 |
1 |
16 |
0 |
2 |
11 |
208 |
| WEIGHTED-AVERAGE LEAST SQUARES (WALS): A SURVEY |
0 |
0 |
1 |
11 |
0 |
0 |
2 |
69 |
| Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market |
0 |
0 |
0 |
29 |
3 |
4 |
4 |
162 |
| Weighted-Average Least Squares Prediction |
0 |
0 |
0 |
1 |
1 |
1 |
4 |
40 |
| Weighted-average least squares estimation of generalized linear models |
0 |
0 |
0 |
18 |
1 |
4 |
13 |
100 |
| Weighted-average least squares: Beyond the classical linear regression model |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| Weighted-average least squares: Improvements and extensions |
1 |
3 |
3 |
3 |
1 |
5 |
5 |
5 |
| Total Journal Articles |
5 |
11 |
41 |
3,722 |
63 |
137 |
350 |
16,263 |
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